using gis to derivation of gamma giuh, khanmirza watershed...

Proceedings of The Fourth International Iran & Russia Conference 1131

Using GIS to derivation of Gamma GIUH, Khanmirza Watershed Case Study, IRAN

K. Abdollahi Center for Agriculture and Natural Resources Researches, Shahrekord , IRAN;Email: [email protected]; Website: www.iranhydrology.com

ABSTARCT The hydrograph at watershed outlet can be expressed as hydrological response of watershed to geomorphological behavior. In this work with the aid of the GIS and the concept of geomrphological instantaneous unit hydrograph, watershed response was simulated. In present physical approach, the GIUH is derived from geomorphological characteristic and then is related to parameters of Nash instantaneous unit hydrograph model based on Rosso method. The basic idea of this model can be understood by considering the watershed as a linear reservoir system in witch geomorphological properties play controlling role of this system. Nash model determines watershed rainfall-runoff response using a Gamma probability function with two form and scale parameters. Based on Rosso method Horton laws, stream velocity and highest order average length of stream will be applied to estimate form and scale parameters of Nash model.Estimated hydrograph were tested against observed data. The hydrograph shape was compared both visually and statistically. Results indicate that in most cases model was underestimated. Ratio between observed and computed flow rate were used as calibration factor. In other hand scale factor is constant for each subwatershed. With take account these geomorphological index four forms of model were developed for each subwatershed.

Keywords: Runoff Modeling, GIS,GIUH, Watershed, Geomorphometry, Iran.

Introduction Recently, many attempts have been made to relate the hydrologic response of a watershed to its geomorphological properties, using various hypothesis of network hydrology. In 1979 Rodriguez-Iturbe and Valdes introduced the concept of the geomorphologic instantaneous unit hydrograph (GIUH), later generalized by Gupta et al. in1980. In GIUH theory basins are assumed to respond as linear systems and the distribution of arrival times at the basin outlet of a unit instantaneous impulse injected throughout a channel network is affected by the underlying natural order in the geomorphology of the catchment and it is represented by the Horton lows. Geographic information system has facilitated extraction of geomorphological properties of the watershed. Several researchers have been focused in this field of study. Chen and Singh (1986) Gupta and Waymire (1980), Jin (1992), Garcia (1998) are some of these people. Rosso (1983) developed an alternative form of GIUH by means of coupling the model with Nash model. In this way he parameterized Gamma function based on Horton ratios and water velocity. This method was investigated in Khsnmirza Watershed. 1.1. Location of area Khanmirza watershed covers 392 Km2 area of upper Karoon (greatest river in Iran) basin in the Southwest of country. The boundary of the catchment locates from E 55˚50 to E ˝3


18˚51 in longitude and E ˝2422˚31 to N ˝3037˚31 in latitude . Elevation from sea level of the Khamirza watershed ranging from 1730m to 2972m. 1.2. Runoff Modeling Rosso method applies a gamma form of the geomorphologic instantaneous unit hydrograph (GIUH). Geomorphology is shown to be main explanatory factor of the shape of the hydrologic response, while its time-scale is found to depend also on the scale of the watershed and the average stream flow velocity. GIS is able to compute some local geomorphologic parameters (i.e. average slope and elevation, main stream length, concentration time, etc.). The ordering scheme of drainage networks, which has been introduced by Strahler (1952) in order to assess Horton procedure to represent stream network topology, can describe the hydrologic response. A catchment is displayed together with the Strahler’s ordering procedure. It denotes "first-order stream" as any channel originating from a source. The source is a point of the flownet whose drained area is equal to the fixed threshold area. Strahler’s ordering scheme denotes "stream of order u+1" a channel by the junction of two streams of order u. When two streams of different order join, the channel immediately downstream this junction has the higher of the orders of the two joining streams. If U denotes the highest order achieved moving downstream, Nu the number of stream of order u, Lu the average length of streams of order u, and Au the average area of the basin of order u. The Horton’s laws can be

represented by the following equations: Au/Au-1=RA (1) Nu/Nu+1=RB (2) Lu/Lu-1=RL (3) where RB is the Horton bifurcation ratio, RL is the Horton stream length ratio and RA is the Strahler basin area ratio. These Ratios can be calculated by putting the log-transformed experimental values of Nu, Lu and Au against their order u for all stream orders (Rosso, 1984). Horton order ratios RA, RB and RL provide the basic parameters of a basin as an ordered system of geomorphologic elements. The ranges of these dimensionless parameters are usually between 3 and 6 for RA, between 2.5 and 5 for RBand between 1.5 and 3.5 for RL. Formula for the main characteristics of the IUH, i.e. the peak value hP, and the time to peak tP, has been obtained by regression analysis: hP = 0.36 RL

0.43 vL-1 (4)tP = 1.58 (RB/RA)0.55RL

-0.38(vL-1)-1 (5) Where v is the average streamflow velocity. A very common and useful analytical form for the IUH is the two-parameter gamma density function (pdf), the so-called Nash model: h(t)=[kΓ (α )]-1(t/k)α -1exp(-t/k) (6) h(t) is the impulse response function of IUH (T-1), α is a shape parameter, k is a scale parameter measured with coherent units. The gamma fit to geomorphologic IUH has been processed by means of multiple regression analysis in the logarithmic space and the following results allow estimating the parameters of the Nash model (Rosso, 1983): α =3.29 (RB/RA)0.79RL

0.07 (7)k=0.70(RA/(RB RL))0.48 L/v meter k.

Methodology and Results (8)


If the shape parameter α is considered to be determined by the geomorphic pattern of the drainage basin, the estimation procedure records processing can be only addressed toward the calibration of the scale paraIranian Geomantic Organization has provided digital topographical map of the country in 1:25000 scale. Digital maps of basin were imported into ILWIS environment to extraction of geomorphological parameters of the model. The water velocity computed from plotting field observed velocity against discharge data and after that Horton ratios were applied to prediction of hydrograph for 5 runoff-rainfall evens. Fig. 1 shows results of simulated and observed hydrograph of basin for all events. Bias ratio and constant factor of number of reservoirs in linear system were used to localize model for each subcatchment. Table 1. presents a list of calibrated form of the model in four subwatersheds. Table 1. Calibrated formula of the model for each subwatershed

Calibrated form of model Subwatershed kt

t ektkq /788.21 )/(256.0 −−=Kh1kt

t ektkq /697.51 )/(0028.0 −−=Kh2kt

t ektkq /47.41 )/(024.0 −−=3Khkt

t ektkq /717.41 )/(0159.0 −−=Kh4

Discussion and conclusion Many researchers have endeavored to relate geomorphology of watershed to its hydrological response. In traditional techniques some parameters such as area, Tc, … were used to present a relation between input and output of watershed. In present model watershed consider as a linear reservoir system in witch geomorphological properties play controlling role of this system. As it can be understood by visualization, in most cases model was underestimated; but statistics analysis indicates that model is able to estimate peak discharge and volume of flood in acceptable rates. In order to improvement outputs of model one can make suggestion for more research on velocity parameter; because of in spite of using small scale maps and enough accurate modeling in GIS environment; model is very sensitive to this factor.

Acknowledgements The author wishes to acknowledge the kind cooperation of Dr. Sadeghi, Dr. Farajzadeh, Karoon Watershed Management office and Center for Natural Resources and Animals Husbandry Researches, Shahr-e-kord, IRAN in this study.


Figure 1. Observed and estimated hydrograph for 5 runoff-rainfall events


Table 2 Resultes of statistical index ESMR ... VRE% QpRE% index

event 1.09 13.3 37.3 1 1.40 10.6 36.7 2 0.05 23.0 5.7 3 2.47 6.1 23.0 4 5.49 21.1 22.2 5 2.09 15.0 24.9 Mean

1. Abdollahi, K., 2002, Runoff modelling based on geomorphological properties using GIS in Khanmirza Watershed, Iran, MSc. Thesis, Dept. of Watershed Management Engineering, Tarbiyat Modarres University, Noor, IRAN

2. Chen, S. J. and Singh, V. P.,1986, Drivation of new variable instantaneous unit hydrograph, Journal of Hydrology, 88, 25-42.

3. Garcia, S. G.,1998, Geomorphological analysis based on GIS applied to distributed hydrological modeling, Hydroinformatics 98, 511-518

4. Gupta, V. K. and Waymire, E., ,1980 A representation of an instantaneouse unit hydrograph from geomorphology, Water Resources Research, 16(5), 855-862.

5. Horton, R. E., Erosional development of streams and morphology, Bull. Soc. Am.,1975, 38(40), 275-375.

6. Jin, C. X., Detrministic Gama-type GIUH based on path-type, Water Resoures Research,1992, 28(2), 479-486.

7. Nash, J. E., The form of the instantaneous unit hydrograph. IASH Pub., 72 114-118

8. Rodrigues-Iturbe, I.M.,1981.” A geomorphoclimatic theory of the instantaneous unit hydrograph” Water Resources Researches, 18(4),886-8

9. Rodriques-Iturbe, I, ,1993, The Geomorphological Unit Hydrograph, Chapter 3, Channel Network hydrology, Edited By K. Beven and M. J. Kirby, John Wiley and Sons Ltd.

10. Rodriques-Iturbe, I., and Valdes, J., B., 1979, Geomorphologic stracture of hydrological response,Water Resources Researches, 15, 1409-1420

11. Rosso, R., Nash Model relation to Horton order ratios, Water Resources Researches, 1984, 20(7), 914-920

12. Strahler, A. N., 1952, Hypsometric (area-altitude) analysis of erosional topography, Geol. Soc. Bull. , 69:1117-1142

13. Strahler, A. N.,1957, Quantitative analysis of watershed geomorphology, Trans. Am. Geophys. Union, 38, 913-920


Economic optimization of wheat production under deficit irrigation in the Zayanderoud Region,Isfahan

Dr. Asghar Abedi Shapourabadi1 and Ali Akbar Jafarpour Boroujeni 2

1- Asst. Prof. Dept. of Agronomy, Faculty of Agriculture, Shahrekord University Iran.Email:[email protected] 2. Lecturer of English language Dept.,Faculty of Humnities ,Shahrekord university. Iran.Email:[email protected]

Abstract Water is indispensable in agricultur. Water shortage, along with low irrigation efficiencies in Iran, as a semi-arid country, justifies research in deficit irrigation. In the current study, the economic of deficit irrigation of wheat in Zayanderoud region, Isfahan was examined. The aim and the general expressions were used to derive a set of specific expressions for a particular case study involving a quadratic production function and a cubic cost function. The method was used to find out the crop water requirements. Required water was employed to evaluate the effects of over irrigation(dry/land). Economic data for each farm were collected through interviews with farmers using two steps cluster sampling in the 2000-2001 years. The information were collected from the farmers facing limitation in land and water as well, and the irrigation was full. This investigation clearly demonstrates that maximam profit achived naturally by full irragation and the next preference would be limitation in water rather than the land.The findings of the study show that deficit irrigation will be more profitable than full irrigation in semi-aried regions, and the estimate of optimum water use as an exact prescription for amount of water to apply is recommended.

Key words:Deficit irrigation, Production function, Cost function

Introduction

Under some circumstances, maximum attainable income for an irrigated field may be achieved by deficit irrigation, the deliberate under-irrigation of the crop. Design or manage irrigation for deficit irrigation, the analyst must rely upon crop production function that relate water use to crop yields. It is important to know precisely what level of water use will maximize profit. Deficit irrigation is a concept that can be use- fully applied. Many farms are,deliberately under-irrigating some field to increase net income. This paper leads to estimates of the profit-maximizing level of the range of water use within which deficit irrigation is more profitable than full irrigation(English, 1981). The increase in applied water is associated with higher irrigation frequencies, greater evaporation may occur with relatively little increase in yield (Hanks,1974; Hanks and Hill, 1980). The irrigation system will be become less efficient as water use approches full irrigation .This decline in efficiency is largely associated with variability in applied water, crop characteristics, and soil characteristics (English et al.,1986).The expressions are completely general in the sense that they can be used with any crop procuction function and cost function that the analyst chooses. Farm operations are often constrained by a shortage of irrigation water. When that is the case,the water saved by deficit irrigation of one piece of land might be used to irrigate additional land, thus increasing farm income. The potetial increase in farm income is an opportunity cost of the water.Where water supplies are limited, opportunity costs may be the amount of land under irrigation is constrained by a limited water supply, the economic returns to water will be maximized the depth of water applied and increasing the area of land


under irrigation until the marginal profit per hectar multiplied by the number of hectares irrigated just equals the total profit per Hectare(English and Orlob,1978) The economics of deficit irrigation are examined. The concepts developed in the heuristic discussion are developed into a set of rigorous mathematical expressions for determination of optimum water use under deficit irrigation. These expressions can also be used to estimate the water use within which deficit irrigation would be more profitable than full irrigation(English, 1990). The effect of irrigation intensity on the net revenu of cotton and potato in two separate regions in the northeastern part of Iran was investigation by Ghahremani and Sepasckhah (1994).They came to the conclusion that the optimum level of water deficit in Esfarayen was 20 percent for potato and cotton and, in Esfarayen and Daregaz it was 25 percent and 9 percent respectively.With this amount of reserved water, be it is possible to increase yeild crop up to 25,10 and 15 percent respetively. The findigns of the study also showed that if the ratio benefit of cost(B/C) for each irrigation treatment was smaller than 1.5, those types of potato and cotton would not be recommended for Esfarayen and Daregaz. A research done by Hargreaves and Samani (1984) showed that the system of irrigation had a meaningful effect on yeild product. They also mentioned that the relation between crop and water used can be divided into two parts. The first part relates to deficit irrigation and the second relates to over- irrigation . If full irrigation used,the production function curve will be linear up to 50 percent . Solomon (1985) believes that plant production function differences should be taken into account, and the amount of water used by the plant during its growth should be investigated. Keith (2003) proved the efficent irrigation management for any crop based on the crops yeild threshold, the soil’s allowable soil moisture depletion percetage or a predermined soil moisture level as in a vineyard deficit irrigation program. The results of Keith,s study show that the efficient use of water resources throught good management has a great effect on crops yield. Pascual et.al (2004) said that regulated deficit irrigation treatment improved water-use efficiency bcause about 30 percent less irrigation water was applied in the regulated deficit irrigation in the control treatment . They concluded that high-cropping almonds can be succedssfully grown in semiarid regions.

Materials and Methods

A general relationship exists between irrigation water use and crop yield. When a small amount of water is applied it will be almost completely used by the crop. At higher levels of applied water, reflecting various water losses that develop as water use approaches full irrigation. If the increase in applied water is associated with higher irrigation frequencies, greater evaporation may occur with relatively little increase in yields. It is possible to derive a set of equation to estimate the values of the aforementioned variables. Such equation would be useful for analysis of optimum water use for alternatives of system design and operation. The profit to be relized from irrigation will be determined by the amount of water applied.Assume that we are concerned with only one crop like wheat, and that fixed amount of land and water have been allocated for production of that crop. The irrigated area may also be a function of water use:


A=wWt ( 1)

Where: A=total area of wheat crop to be irrigated(ha) w t : total availabel water supply( m 3 )

w:water applied per unit of land ( m 3 ha )

The level of water use which maximize yields(w m )can be determined by taking the derivative of the yield function:

w

wy

∂∂ )(

=0 ( 2)

Where:y(w)=yield per unit of land,expressed as a function of w(kg/ha) The value of w that satisfies Eq. 2 will be w m .We determine the level of water use that will maximize net income when land is limiting, we begin by taking the partial I f : (w) =A.i1 (w) with respect to w. The net income per hectare is

a function of applied water.

w

wI f

∂∂ )(

=Aw

wi

∂∂ )(1 + i 1 w

A

∂∂

(3)

Where: I f (w)=net farm income from all irrigation land($/ha)

i 1 (w)=net income per unit of land under irrigation($/ha) When land is limiting, A is presumed constant. The optimum level of water use(w l ) will be defined by the equation:

w

wi

∂∂ )(1 =0 (4)

When water is limiting,A is a function of w, as was noted and optimum water use(w w ) can be determined:

w

wi

∂∂ )(

=Pcw

wy

∂∂ )(

-w

wC

∂∂ )(

(5)

w

A

∂∂

=2w

wt ( 6)

The equation for optimum water use are, then:

Pcw

wy

∂∂ )(

=w

wC

∂∂ )(

( 7)

Let: Pc=crop price of wheat($/ha) C(w)=production costs per unit of land,expressed as a function of w($/ha) When land is limiting,and :


w. [ Pcw

wy

∂∂ )(

-w

wC

∂∂ )( ] = Pc.y(w)-c(w) (8)

The net income per hectare is a function of applied water.

i l (w)=p c .y(w)-c(w) (9)

By substituing w m into Eq. 9:

i l (w m )=p c .y(w)-c(w) (10)

When water is limiting,solving Eqs. 7 and 8 for w will yield the optimal values of applied water,w l and w w . Eq. 7 is where the marginal cost of production equals the value of the marginal product. The optimum water use will occur at the point where the MC=VMP are equal (w l ) when land is the limiting factor. It will be necessary to first develop specific models of yield and cost [ y(w) and

C(w) ],then substitute those models into the general equations and solve for the various values of w.The yield function can be represented:

y(w)=a1 +b 2 w+C1 w (11)

The cost function might reasonably be represented:

C(w)=a 2 +b 2 +C 2 w 2 (12)

Where the coefficients a 2 and b 2 are fixed costs and variable costs of production,

the various levels of water used is of interest to the analyst (W l ,W w ,W m ,W el ,W em ) can be derived by substituting Eqs. 9 and 10 into the general equations derived earlier. The five levels of water use are shown in the index.

The data shows water use and yield for 120 fields of wheat on various farms that were Monitored as part of that study in 2001.

Results

A study of irrigation in the Zayanderoud Region was carried out by the researchers.The analytical framework developed in this paper was used to study optimum irrigation.The farm applied 398 mm of water to the field, realiaing a yield of 5180 kg of wheat/ha.Full irrigation would have required 408 mm of water to the field. The yield curve is closely approximated by the following regression equation for water use.


y(w)=1900+25.3w-.027w 2 (20) t (2.4) (2.97) (-4.8) R 2 =.98

Where y(w)=yield, in kg/ha and w=depth of water applied, in millimeters equivalent depth or m 3 *10 per hectare. The price of wheat was considered in the analysis: 0.2 $/kg. Production costs for the field were determined from interviews with the farm owner-operator. The resulting cost function was:

C(w)=1152930+915w-.486w 2 (21)

Where:c(w)=total production cost in dollars per hectare. Let:

a. fixed costs=1117530 b. variable costs=459.6w c. price of water m 3 /ha=120*10wd. cost of irrigation=50*10w e. others costs 18*y1 (w)=18(1900+25.3w-.027w 2 )

The values of w m ,w l ,w w ,w el , and w ew were determined for crop price using Eqs. 11-17. The approach involves determination of five levels of water use: (1) the level at which yield is maximized(w m )(2) the deficit levels at which the net income would just equal the income at full

irrigation, either when land is limited or when water is limited(w el or w ew )

(3) the deficit at which returns to land are maximized (w l )

(4) the deficit at which returns to water are maximized(w w ). By determining these five levels of irrigation, the analyst can gain a useful perspective on the returns associated with deficit irrgation.

Discussion

An analytical framework for dealing with deficit irrigation has been presented.Table 1 summarizes the results of the analyses.( Refer to table 1.) When available land is limited the optimum use strategy will be that which maximizes net returns to land. The range within deficit irrigation would be more profitable than full irrigation begins at 260 mm or 63 percent of full irrigation. In the water limiting situation, the profitable deficit begins at 68 percent of full irrigation .The decision –maker can regard the estimate of optimum water use as an exact prescription for amount of water to apply. Completely general equations for calculating optimum levels of water use were derived analytically(Eq. 4,7,8,9,10).These equations can be combined with any yield and cost functions to derive the five relevant levels of water use. As an illustration, specific yield and cost function were derived based on a quadratic production function and cost function. The resulting equation for w m ,w l ,w w ,w el , and w ew (Eq. 13-19) provide a simple algorithm for


analysis of optimum irrigation with use.The required inputs are the coefficients in Eqs. 11 and 12 and the price of the crop. While the optimum irrigation levels can be estimated, they can not be known precisely.However, within the range between w m and w el , or w ew deficit irrigation will be more profitable, than full irrigation. The optimal levels of water use(w l and w w ) were found to be relatively low, and the

profitable deficit range(the range between w m and w el ,w e w )was rather wide,suggesting that the decidion to under-irrigate in these particular circumstances was potentially profitable and reasonably safe.

Refrences:English, M. J. (1990) Deficit irrigation. Analytical framework, J. , of Irig. And Drainge Engineering. English, M. J. and Nakamura (1989) Effects of deficit irrigation and irrigation frequency on wheat yields. Journal of irrigation and drainage Engineering 115(2):172-184. English, M. J. (1981) The uncertainty of crop models in irrigation optimiation . Trans.ASAE, 24(4):917-928. English, M. J., Taylor, A. R., and John, P. (1986) Evaluating sprinker system performance . New Zealnd J. Agric. Sci., 20(1):32-38. English, M. J., and Orgob , G. T.(1978) Decision theory applications and irrigation optimization, California Water Resour.Ctr. Contribution, 174, Univ. of California, Davis, Calif., Sep. Ghahremani, B. and A.R. Sepaskhah (1994) Optimum water deficit in irrigation management at a semi-aried region of Iran, 17 th Europen regiones conference on irrigation and derinages.Vol.1, Paper 10-15, 127-134. Hanks, R. J. (1974) Model for prediting yield as influenced by water use. Agronomy J. 66(5), 660-665. Hanks, R. J., and Hill , R. W. (1980)Modelling crop response to irrigation in relation to soils, climate, and salinity , Int. Irrig. Info. Ctr. , Bet Dagan,Israel. Hargreaves, G.H. and Samani, Z.A.(1984) Economic cosiderations of deficit irrigation And

Drain Engineres., Assocation, 110(4),343-358 Keith,W. (2003) Precise siol moisture testing for Irrigation sheduling, deficit irrigation in agriculture, using a new portable, field test . www.dexsil. Yahoo.com.Pascual, P. et. al (2004) Effects of regulated deficit irrigation during the pre-harvest period on gas sexchage, leaf development and crop yield of matur almond tree.http://heronpublishing.com/tree/summaries/volume24/a24-303.html. Solomon, K.H. (1985) Typical crop water production function, Paper No.85-2596, Winter Meeting, American Society of Agricultural Enginers, Ghicago, 11:17-20


Table Legend Table 1.Case study Summary

Irrigation Strategy

Water use(mm)

w m408

w el260

w ew277

w l320

w m310

Derived from the research results. Index

The five levels of water use:

w m =1

1

2c

b (13)

w el = 1

112

2 cp

zbpb

c

c +− (14)

w ew =]

21

1

21122

2

)(4

cp

aapcpzz

c

cc

−−+− (15)

w l =1

12

2 cp

bpb

c

c− (16)

w w =]

21

1

21

2

)(

cp

aap

c

c

− (17)

Where:

z1 = ( )[ ]

−−−

1

21

1

21

12

21 244

c

bb

c

bpcpbbp c

cc2

1

(18)

z 2 =1

11122

1

2

44

b

capcabp cc +− (19)


Simulation of rainfall-runoff process by artificial neural networks and HEC-HMS model (case study Zard river basin)

Mehrdad Akbarpour MSc. Graguate, Water Structures Engineer, Shahid Bahonar University, Kerman, Iran, Phone: +98(916) 6522571, E-mail: [email protected]

Abstract The rainfall-runoff modeling is nonlinear process according to the temporal and spatial distribution of the rainfall, and it is not possible to explain the response catchment system with the simple models. In the present research simulation of the rainfall-runoff process were carried out by Artificial Neural Networks (ANNs) and HEC-HMS model. The ANN models of, Multi Layer Perceptron (MLP) with two structures of one and two hidden layer, and Radial Basis Function (RBF), was used for simulation of this process. It has been applied to the Zard river basin in Khuzestan province using daily rainfall and runoff data, during the period of 1991-2000. In this period, 14 flood events were selected for simulation of the HEC-HMS model. The obtained results of the above models were compared with the observed data from Zard river basin. This comparison shows that RBF model has much more power than MLP and HEC-HMS models for simulating of the rainfall-runoff process in Zard river basin.

Key Words: Artificial neural network, HEC-HMS, Rainfall-runoff process

Introduction Simulation of rainfall-runoff process is very important in water resources management, river engineering, flood control and surface water and groundwater utilization. Due to existence of various hydrologic factors basin’s response is very complex to the rainfall. Runoff depends on geomorphologic properties of a basin such as geometry, vegetative covering, soil type and climate characteristics such as rainfall, temperature, etc. The effects of these factors are not uniform in runoff generation. Up to now many physically used models have been suggested to simulate this process such as HEC-HMS model. These models have required many catchments’ characteristics for simulation such as rainfall depth, evapotranspiration, infiltration, initial losses, time of concentration, etc. Recently with new advancement many world scientific communities become interested in different branches of artificial intelligence, such as neural networks. With the same logic hydrologists also were persuaded to simulate the hydrologic involute processes by these techniques.

Artificial neural networks (ANNs) Artificial neural networks (ANNs) are simple model of human’s brain. An ANN is nonlinear mathematical structure that has ability to show the nonlinearity process for communicating between inputs and outputs of any system. This network is training with present data in learning process and can be used for future prediction. Generally, each ANN is formed with a number of layers which built-up some neurons. Neurons are the smallest unit of ANN constructor and are like to human brain cells. Each network has been formed from one input layer, one output layer and one or more hidden layer. Neurons of each layer are connected to next layer by weights. During the network training process, weights


and values that called bias is frequently changing until objective functions will reach to desire value. For transferring outputs of each layer to the others, activation functions are used for nonlinear amplifier to neurons. The technique is adopted for access of weights and biases to ideal values called “Learning Rule”. That almost it is complex mathematical algorithm. Each ANN needs two data sets for to create and to acceptable: train set and test set. About 80% of data are used for train set and residue for test set. During the training process, network learning rate is regularly measured by objective functions and finally a network will be acceptable which has less value of error and maximal correlation coefficient. The objective functions that are more used than others include the root mean squared error (RMSE), the sum squared error (SSE) and the correlation coefficient (R2) that equations as follows:

∑=

−=n

iiQiQ

nRMSE

1

2)ˆ(1

∑=

−=n

iii QQSSE

1

2)ˆ(

∑

∑

=

=

−

−−= n

iii

n

iii

QQ

QQR

1

2

1

2

2

)(

)ˆ(1

Where iQ is the Observed data; iQ̂ is the forecasting data; iQ is the average of observed data.

Multi Layer Perceptron (MLP) neural network The MLP neural network structure is shown in Figure 1. In this network, neurons outputs of each layer have been entrance to next layer neurons and it is continued to import the network’s output. Learning algorithms of MLP neural network are basis on back propagation algorithm (BP).

Figure 1. Multi layer perceptron neural network Learning process in MLP neural networks were done in three steps: forward pass, backward pass and computation iterance pass. The input value to the each neuron is given by:

1

1

. −

=∑= n

j

m

j

nji

ni ownet


Where ninet is the input value of ith neuron in nth layer; n

jiw is the connection weights between

ith neuron in nth layer and jth neuron in the (n-1)th layer; 1−njo is the output of jth neuron in the

(n-1)th layer; m is the number of neurons in the (n-1)th layer.

The output of each neuron will be obtained after to apply the activation function. The common activation function for use in back propagation algorithm is sigmoid function. The output value of each neuron was calculated by:

)exp(11)( n

j

nj net

netSig−+

=

Radial Basis Function (RBF) neural network The RBF network structure is shown in Figure 2. The main differences between this network and MLP network are as follows:

• The RBF network has one hidden layer and activation functions of neurons are Gussian function with particular center and spread.

• There are not weights between input layer and hidden layer and the distance between each pattern and center vector of each neuron in hidden layer is used as an input of Gussian activation function.

• In this network, activation functions of output neurons are simple linear functions and because of this reason we can use of linear optimum algorithms. They have been caused to improve the processing rate and prevent to fall in local minimums that deal with there at learning process in MLP network.

Figure 2. Radial basis function neural network

Output of jth hidden neuron given by:

−−

= 22exp

j

ji

j

UXh

σ

Where jU the center and jσ the spread of gussian function; iX the ith input vector.

jju σ,

jju σ,

jju σ,

∑

∑

∑

Input Hidden Output

w


HEC-HMS Program The HEC-HMS program was developed at the Hydrologic Engineering Center (HEC) of the US Army corps of engineers. Of this program advantages is ability to parameters optimization. It used for simulation of rainfall-runoff process by losses, direct runoff and baseflow that each of those calculated by different methods. In this research has been used of SCS curve number to losses calculation, SCS unit hydrograph to runoff and exponential recession model to baseflow.

Case study Case study in this research is Zard river basin in Khuzestan province in southwest of Iran. The area of the basin is 875 Km2, the length of main channel is about 70 Km and average slope is about 3%. There are six precipitation gages and one hydrometric station in the basin, and their locations are shown in Figure 3. Rainfall and runoff data were used for period of 1990-2000.

Figure 3. Zard river basin

Results and discussion The target of this research was estimation of river discharge in a number of events. For training of MLP and RBF, networks were considered the rainfall data for input and discharge data for target. Also, it was used two different structures by one and two hidden layer for MLP network. All of the simulation stages of networks were used in MATLAB software. Results are shown below:


Figure 4. Comparison between observed data and MLP one hidden layer estimation data

Figure 5. Comparison between observed data and MLP two hidden layer estimation data

Figure 6. Comparison between observed data and RBF estimation data

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The results showed that the RBF network has a better ability than MLP network. The 14 flood events were simulated and parameters were optimized with use of HEC-HMS program. For compared between MLP and RBF networks and HEC-HMS model one flood events that weren’t used to previous simulations as shown:

Figure 7. Comparison between MLP, RBF and HEC-HMS

ConclusionIn general ANN is a technique, which solve the nonlinear and complex nature of catchment’s system required the long time and accurate series of input, and output data and if non-adequate data is given, the inaccurate results will be obtained. Both ANN and HEC-HMS models have their own advantages. The HEC-HMS model if calibrated for a basin then can be used to estimate the flood discharges in ungaged catchment. The advantage of ANN model is that the prediction is based on data in previous time interval.

Acknowledgement The author wishes to thank the water engineering researches department of Khuzestan Water and Power Agency (KWPA) for to support of this research.

References Dawson CW, Wilby RL (2001) Hydrological modeling using artificial neural networks. Progress in

Physical Geography 25(1): 80-108 Hsu K, Gupta HV, Sorooshian S, (1995) Artificial neural network modeling of the rainfall-runoff process.

Water Resources Research 10(31): 2517-2530 Jayawardena AW, Achela D, Fernando K, (1998) Use of radial basis function type artificial neural

networks for runoff simulation. Computer-Aided Civil and Infrastructure Engineering 13: 91-99 Shamseldin AY, O’Connor KM, Liang GC, (1997) Methods for combining the outputs of different

rainfall-runoff models. Journal of Hydrology 197: 203-229 Imrie CE, Durucan S, Korre A, (2000) River flow prediction using artificial neural networks:

generalization beyond the calibration range. Journal of Hydrology 233: 138-153 Sajikumar N, Thandaveswara BS, (1999) A Non-linear rainfall-runoff model using an artificial neural

network. Journal of Hydrology 216: 32-55

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Evaluation of Mud-Rock Flow Hazard using Remote Sensing and GIS in the Arid Land Watersheds of Central

IranMohammad Akhavan Ghalibaf 1 and Vera Sergeivna Krutina 2

1-Combat Anthropogenic Desertification and Kevir Department, Yazd University, Iran. 2-Soil Science Department, Moscow Timiriazev Academy, Russia.

Abstract: In the some subtropical mountainous regions in Central Iran mud-rock flows can be happened after high intensity rainfall in spring. This research investigates the effectiveness of pedogenic and litogenic parameters using remote sensing. Sediment sampling was done after mud-rock flows. The mechanical and physical properties of samples like granulometry and thermogravimetry were determined. The upperlands of watershed classified to homogeneous units regarding to morphology, geology and pedology characters. After field diagnostic of hazardous land units for mud-rock flows tried to classify the sensitive areas by Landsat7 data. As a result more sensitive land units for mud-rock flows in Central Iran were the lands on the violet micacious sandy shales and near by dolomites related to geochemical properties and the effectiveness of slope and aspect of land. These Cambrian period formations determined by image processing and GIS.

Key word: Mud-rock, Pedogenic, Lithogenic, and RS.

Introduction: A natural Hazard is defined as any potentially dangerous geologic or hydrologic process. Such processes include flood, landslides, volcanic eruptions, hurricanes, earthquakes, tsunamis, and etc [4]. These hazards pose serious threat to communities lie in their path. Chen et al (2001) look at the combination of geographic information systems (GIS) with multicriteria evaluation methods (MEM) in other for policy makers to make better risk based decisions for natural hazards. For the past decades, China’s regional and local government s have used a digital network for natural hazard assessment and monitoring [5]. Satellite images (spot and landsat) and field work were used by Garcia-Maclendez et ales (1998) to divide the area in to homogenous zones of natural hazard called terrain mapping units (TMU). Iran has an long time history and experiments on the some objects of natural hazards like as wind erosions. The use of digital maps, however, is not more than a decade. In this research some characters of land put in a spatial data map to forecasting the time and location of mud-rock flow hazard.

Materials and methods: After mud-rock flow in the some regions in Central Iran (40 km south-west to Yazd city) were done fieldwork and sampling from depositions(fig.1). Depositions were prepared for some routine physical, Chemical and christalochemistry Analyses. Thermogravimetry was done on the samples by STA503 BAHR thermoanalyse. Homogeneous land units were recognized combination of data in geological, morphological and soil maps. Landsat7(date of 2000/09/22) images were used to identify the most sensitive land for mud-rock flowing. Meteorological data like as rainfall is used tried to define the best time of mud -rock flowing on the lands.


Fig. 1. Location of studied land in Yazd region(*).

Results:

Thermogravimetry analyses show heterogeneous christalochemistry characters of depositions. This character is related to complex of lithogenic origin of carbonates and shales[2] in mud rock flow (fig.2).

Fig2. Thermogravimetry from some particle size and materials in mud-rock deposition.

The Mud-Rock depositions had a bulk density and solid density equal 1.57 and 2.58 g/cm3 respectively. Porosity in mud –rock depositions is equal 39% and it had a saturation water content equal 24.93%(θm) and a volumetric saturation water contents equal 39.15 %(θv). The plasticity index equal to 6%(θm) or 9,42%(θv) of samples


were determined with Atterberg method .The upper plastic limit will be less than 80% of the saturation case of sediments. The average of soil depth in the uplands of mud-rock flow was 15cm and after multiplying by 9.42%(θv) was calculated 1.41cm effective rainfall for beginning of mud-rock flow. Meteorological data show the rainfall quantity equal 15mm in 1 day in these lands before mud- rock flowing. Band combination of bands 7, 4 and 1, has shown in fig.3. In this RGB, sensitive soils and parent paterials that have formed on the shale formations have a dark blue color. In the classified image(fig.4) in the same area were seperated potentially for mud-rock flow with blue color(class2). After PC analyses on the bands the sensitive area to mud-rock flow was detrmined as hydroxyl alternated zones. In these regions with more than 30 degrees land slope, hydrated trioctahedral micas can play an effective role for mud-rock flow although with a rainfall under soil saturation limit.

Fig.3. 7, 4, and 1 combination bands of Landsat7(date of 2000/09/22) in the studied region.

Fig.4. the classified Landsat7 image(bands;4,5, and 7) for diagnostic of potential mud rock flow.

References:

1. Chen, Keping, Russel Blong, and Carol Jacobson (2001) MCE-Risk: Integrating Multicriteria Evaluation and GIS for Risk Decision –Making in Natural Hazards. Environmental Modeling & Software, 16(4): 387-397.

2. Dixon J.B. and S.B.Weed (1989) Minerals in Soil Environments, SSSA Book Series: 1, 1244p.

3. Garcia – Mclendez, E., I. Molina, M. Ferre-Julia, and J.Aguirre (1998) Multisensor Data Integration and GIS Analysis for Natural Hazard Mapping in a Semiarid Area.


Advance in Space Research; The official Journal of the Committee on Space Research (COSPAR), 21(3): 493-499.

4. Hogue Jenifer A. (2003) GIS Application for Natural Hazards and Risk Assessment with Special Emphasis on Volcanic Hazards.Geographic Information Systems and Science Department of Geosciences, Oregon State University.Geo 565.

5. Tang Aiping, Tao Xiaxin, and Ou Jinping(2003) Natural Disaster Mitigation in China; Hazard Monitoring Using Digital Techniques.GIM International, 17(3):48-51.


Effects of Groundwater Over-exploitation on Water Quality of the Azarshahr Plain Aquifer

Asghar Asghari Moghaddam Department of Geology, University of Tabriz, Iran, Tel: 04113858964 Email: [email protected]

Abstract The fertile plain of Azarshahr is located 50 km southwest of Tabriz city and east of Orumiyeh Lake and its area is about 136 km2. The climate of Azarshahr area is semi-arid with average annual precipitation and temperature of 221 mm and 13

oC, respectively. The plain is an active cultivated area with low annual precipitation and

surface runoff; thus, the groundwater resources have a vital role in supplying agricultural, drinking, domestic and industrial water demands. Because of over-exploitation from fresh water aquifer, saline water intrusion into this aquifer is highly increased in recent years and some of abstraction wells have been abandoned. The purpose of this paper is to determine the effects of excessive groundwater abstractions on water quality of the Azarshahr plain aquifer. Therefore, from the previous hydrogeological data, the groundwater level data were analyzed for a 10-year period. The groundwater level in the aquifer is declined about 3 m during this period. For determining the groundwater quality deterioration, 34 samples (in June 2002) were collected from pumping wells and analyzed to determine the main physicochemical components. These data were compared with data from year 1992, which show high increases in TDS values in most of the wells. The groundwater budget for year 2002 is carried out by calculating water wells abstraction rates, spring and qanats discharges and groundwater flow into and from the aquifer, direct infiltration from precipitation, return flow from irrigation and sewage water and seepage from river. The amount of total recharge to the aquifer from above-mentioned components is less than those of artificially and naturally discharge from the aquifer.

Keywords: Azarshahr plain, groundwater fluctuations, hydrochemistry, over-exploitation, saline water intrusion

Introduction The Azarshahr Plain is one of the sub-basins of the Orumiyeh Lake basin, which is located

50 km southwest of Tabriz city, northwest of Iran. The plain is bordered to the east and southeast by volcanic Sahand Mountain, to the south by travertine of Ghezeldagh, to the north and west by Aji Chay and Orumiyeh Lake salty flat plain, respectively (Fig.1). The study area is a densely populated area of Iran, with 100 percent of its drinking, domestic and industrial water and 80 percent of agricultural water supplied from groundwater resources (Moghaddam, 1991). The total area of the Azarshahr basin and plain is about 580 km2 and 136 km2, respectively. The highest elevation of the basin is 3100 m and the lowest 1282 m above mean sea level. According to Azarbijan Regional Water Authority (2003), the average annual precipitation values in Azarshahr station for a 30-year period is 221.2 mm and for year 2002 it is about 204.2 mm. The amount of mean annual precipitation increases from the lowlands (220 mm) toward the higher altitude mountainous area (450 mm). The mean monthly variations of precipitation for a 10-year period (1993-2002) are shown in Fig.2. As the figure shows, most of the precipitation occurs during the spring and autumn seasons. Long-term mean annual precipitations in the area were decreased in recent years. These values for the Azarshahr station are shown in Fig. 3 (1993-2002). Azarshahr Chay is the main river in the study area, which is originated from Sahand Mountain (east of the area) and it inters the plain from east side and through the plain discharges into the Orumiyeh Lake. The river rarely discharges into the Lake due to percolation and evaporation losses, as well as diversion of water for irrigation. There are two gauging stations, which operate on the river Azarshahr, namely Ghermezi-Gol station on the river Gombar Chay (higher elevation) and Azarshahr station on the Azarshahr Chay. The average annual volumetric water discharges from these stations for a 40-year period are 31.62x106 and 33.77x106 m3, respectively.


Mean daily temperatures at Azarshahr (1340 m amsl) station vary from 0.14oC in January up

to 25.8oC in July with a yearly average of 13

oC. The dominant winds over the area blow from

the northeast and the southwest. In general, mean monthly relative humidity at the Tabriz station is relatively high during the November-February period, ranging from 75 to 80%, and lower during July and August, when it is about 35 to 45%. The pan evaporation data from Azarshahr meteorological station during the water year 2001-2002 is 1579 mm. From geological point of view the Quaternary alluvial deposits including water course and plain deposits form the main water bearing layers in the study area. Some of qanats and springs are originated from alluvial tuffs of Sahand Mountain and come up from the boundary of these formations and Pliocene marls and fish-beds.

Geological setting The study area lies in East Azarbijan province, which is structurally part of Central Iran unit. It is wedged between the Zagros and Alborz mountain systems. The area includes representatives of Jurassic to Quaternary age with various movements affecting it, most strongly those of Alpine origin. Pliocene time involved a marine regression and a change to continental conditions, mainly lacustrine, coupled with the deposition of clay and clastics. Then the Plio-Pleistocene was marked by significant volcanic activity, with lava flows and pyroclastic masses associated with the continental conditions of that epoch. Hence, the eastern part of the Azarshahr area is occupied by the extinct Sahand volcano, which is built up from a volcanic series of rocks. This massif is surrounded by volcanic sediments called “alluvial tuff”, which were deposited around the andesitic core (Moinvaziri et al.1975). The Sahand alluvial tuff conformably overlies Pliocene marls, sandstones and fish-bed layers (the bedrock of the study area). The southwestern part of study area includes Jurassic and Cretaceous limestone with Pliocene travertine, which is believed to be connected to the thermal mineral issuing from the Cretaceous limestone as well as from alluvial tuff (Issar 1969). The alluvial water course and plain deposits of the study area are derived from the erosion of Sahand pyroclastic materials, which have transported by water and other transporting agents and deposited in the Azarshahr Plain. They are coarse and poorly sorted in the highest parts of the plain and become progressively finer and more clayey towards the Orumiyeh Lake, which is flanked by a salty loam and huge clay plug.

Investigation methods

HydrogeologyThe alluvial aquifer of the study area has been known for many years as a good aquifer, through qanats, geophysics and well-distributed drilled wells. It has been extensively developed for public and agriculture water supply and investigated hydrogeologically, particularly in connection with groundwater development. According to Azarbijan Regional Water Authority (2002), 233 deep and 500 shallow active pumping wells, 162 qanats and 6 springs operate in the alluvial aquifer of the plain (see Fig. 4). Geo-electrical surveys have been established to determine the thickness and limitations of the aquifer (Abkav Con. Eng. 1970). The resultant isopach map of this investigation is shown in Fig.5. Aquifer properties of the plain have been determined from 18 pumping well tests as well as from groundwater modeling of the Plain (Mazroei, 2002). The values of transmissivity and storage coefficient for the aquifer ranges from 25 to 870 m2d-1 and 3 to 5 percent respectively.


Groundwater level fluctuations Groundwater level fluctuations can result from a wide variety of hydrological phenomena, some natural, such as groundwater recharge, evaporation, and meteorological phenomena, and some man-induced, such as groundwater pumping, deep well injection, artificial recharge and agricultural irrigation and drainage (Todd, 1980). In many cases, there may be more than one mechanism operating simultaneously, therefor, it is important that the various phenomena be understood.The time variations in groundwater level can be considered as (a) long-term, (b) seasonal, and (a) short-term duration (Rushton, 2003). In overdeveloped basins, where extraction exceeds recharge, a drawdown trend in groundwater levels may continue for many years. The seasonal fluctuations usually result from influences of rainfall, bank storage, and irrigation pumping, all of which follow well-defined seasonal cycles. Monthly fluctuations of groundwater level have been measured in the Azarshahr alluvial aquifer for a long time. Figure 6 shows the locations of the 16 monitoring wells for groundwater level measurements in this aquifer. Long term and seasonal average areal water level fluctuations recorded in above mentioned monitoring wells are plotted in figure 7. The mean values are calculated from creating Tessen polygons for the some of monitoring wells. The seasonal fluctuations and long term declining of groundwater levels in the area is obviously shown in this average areal well hydrograph (about 3 meters during 10 years).

Groundwater budget For a given period of time, the total incoming groundwater is balanced by the total outgoing groundwater plus or minus changes in groundwater storage. This balance expresses a groundwater budget and may be stated as:

I = O ± S

Where I is total recharge to groundwater, O= total outputs and S = change in storage. Groundwater budget for the study area is calculated for a period of one year (2002). Among the recharge elements, to the aquifer as a budget area, the groundwater flow into the aquifer from the aquifer borders, the irrigation and municipal used-water return flow, the effective infiltration from precipitation and influent seepage from river are the most important sources of recharge in the area. Artificial withdrawal, groundwater outflow and evapotranspiration make up the larger components of groundwater discharge. The groundwater under flow into the aquifer and direct infiltration from precipitation were estimated from the Darcy’s law and river water hydrographs analysis respectively. Water returned from irrigation activities to the groundwater resources depends on the type of soil, irrigation method etc. Irrigation in the area is carried out June to October when the precipitation is insignificant and soil moisture deficits are high and most of the crops need to be irrigated. During the irrigation period any water in excess of filed capacity infiltrates down to the groundwater resources as irrigation return flow. The irrigation return flow for the area was estimated 30 percent of the used water. According to the ARWA, the amount of water that is withdrawn from groundwater resources during the year 2002 is 71.6 M m3. The groundwater budget for the Azarshahr plain aquifer is shown in Table 1. Therefore, the amount of total groundwater recharge for year 2002 is less than the amount of groundwater discharges from the aquifer (-1.64 Mm3/year). Using average areal long-term hydrograph and mean storage coefficient of the area, the same value of change in storage can be obtained.


Groundwater quality The chemical and biological characteristics of groundwater determine its usefulness for industry, agriculture and the home. The study of groundwater chemistry provides important clues on the geological history of the water bearing layers, gives some indication of groundwater recharge, and the velocity and direction of flow patterns and storage (Freeze and Cheery 1979). Groundwater samples have been collected twice a year from about 25 selected points including 7 deep wells, 6 shallow wells and 12 qanats distributed over the Azarshahr Plain aquifer, during June and October by ARWA. Also 34 water samples were collected from low lands pumping wells and qanats of Azarshahr plain (June 2002) by University of Tabriz and analyzed to determine the main physicochemical components (Rajabpor 2003). 15 of these water samples were collected from the same points as the ARWA for comparing the changes of salinity (compare table 2 and 3). As these tables show the amounts of salinity (TDS) considerably were increased in most of the wells from 1993 to 2002. These data are shown in figure 8 for better comparison of the variations. Also electrical conductivity data for year 1987 and 2002 are countered in Figure 9, which shows highly variations in amount of EC during this period. Because of over-exploitation from fresh water aquifer, not only the groundwater flow to the low lands is diminished but also the saline water intrusion into this aquifer from salty flat plain area highly increased in recent years. The higher value of salinity (TDS) in flat plain area resulted from (a) flatness of the ground surface, (b) shallow depth of groundwater, (c) a boundary of silt and clay at the outlet of groundwater flow from the aquifer, and (d) leakage of saline water from the river Aji Chay into the aquifer.

ConclusionsThe groundwater budget of the study area shows that the recharge components into the aquifer are less than those components, which naturally and artificially discharge from the aquifer. As well as the seasonal and long-term average areal well hydrograph show that the water level in the area declined during the past ten years. Therefore, due to this over-exploitation from fresh water aquifer, saline water intrusion into this aquifer is highly increased in recent years and some of abstraction wells have been abandoned. The main source of the saline water is the Aji Chay and Orumiyeh Lake salty flat plain, which are located in west and northwest side of the study area.

References Abkav Consulting Engineers (1976) Geo-electrical and seismic refraction survey in Azarshahr, Mamaghan, Khosrowshahr, Sardrud, Basmenj and Bostanabad area. ARWA, 2003. Detailed data collection from discharges of pumping wells and qanats in the Azarshahr Plain. (Report in Persian). Asghari Moghaddam, A. (1991) The hydrogeology of the Tabriz area, Iran. Unpublished Ph.D thesis. Freeze, R. A. and Cherry, J. A. (1979) Groundwater, Prentice Hall, New Jersey, 604p. Issar,A., (1969) The groundwater provinces of Iran. Bulletin of the International Association of Scientific Hydrology. XIV,1. Mazroei, A. (2003) Study of groundwater resoures of Azarshahr plain using mathematical model. Unpublished M.Sc thesis. Moinvaziri, H. and Aminsobhani, I. (1978) Volcanological and volcanosedimentological study of Sahand Mountain. University of Tarbeyat Moallim, Tehran, Report in Persian. Rajabpor, H. (2003) Hydrochemistry of the Azarshar Plain groundwater. Unpublished M.Sc thesis. Rushton, K. R. (2003) Groundwater hydrology, conceptual and computational models. John Wiley & Sons Inc. 416 p.


Table 1: Estimated values of the main components of groundwater budget of the study area.Input components Input amounts

(M m3/year) Output

Components Output amounts

(Mm3/year) Groundwater under flow 26.9 Groundwater under flow 0.1

Irrigation return Flow 20.78 Shallow wells 10.7

Municipal return flow 4.87 Deep wells 45.2

Influent seepage From river 13.5 Qanats and springs 16.52

Direct effective infiltration 5.55 Evapotranspiration .72

Total 71.6 Total 73.24

Table 2: Chemical analysis results of selected samples of Azarshahr plain groundwater (June 2002).

Cation (meq l-1) Anion (meq l-1)Sam. No.

UTM (X)

UTM (Y)

PH TDS mg l-1

Ca2+ Mg2+ Na+ K+ HCO3- SO4

2+ Cl-

1 583799 4187281 6.8 3986 25.9 11.8 18.7 0.4 8.1 11.7 37.4 2 582578 4186235 6.2 6834 52.1 12.3 43.8 0.6 7.2 10.2 91.5 3 580242 4184837 6.2 3624 21.5 13.3 16.9 0.5 7.2 14.2 31.8 4 579395 4185188 6.2 5594 40.6 18.6 20.2 0.4 8.7 16.8 55.4 5 580287 4182406 7.2 867 8.0 2.0 3.5 0.1 5.6 2.18 5.8 6 579911 4183896 6.5 3296 20.7 9.0 17.4 0.3 8.24 5.6 33.7 7 579700 4182600 7.3 772 6.7 3.1 2.26 0.1 5.9 3.5 2.8 8 577300 4181250 7.5 2032 17.0 7.5 6.9 0.2 7.0 8.48 16.15 9 577650 4181650 7.5 4553 36.0 13.4 19.8 0.3 5.3 15.7 48.6

10 578889 4179886 6.0 3417 17.9 11.2 19.2 0.5 7.8 13.4 29.0 11 583626 4179600 6.0 1088 9.5 3.0 3.4 0.1 9.3 3.1 3.7 12 577344 4183197 6.3 6867 45.3 20.9 34.1 0.5 9.7 12.5 79.6 13 577968 4182756 6.4 8140 39.5 30.6 47.0 0.5 10.1 12.7 96.2 14 582572 4183178 6.7 1943 11.1 4.3 11.6 0.4 8.9 11.6 8.1 15 588000 4179950 8.0 791 6.0 2.6 3.8 0.1 5.6 3.9 3.0

Table 3: Chemical analysis results of selected samples of Azarshahr plain groundwater (June 1993).

Cation (meq l-1) Anion (meq l-1)Sam. No.

UTM (X)

UTM (Y)

PH TDS mg l-1 Ca2+ Mg2+ Na+ HCO3

- SO42+ Cl-

1 583799 4187281 7.0 3174 29.0 8.2 12.0 3.7 25.0 20.0 2 582578 4186235 6.5 1813 12.8 10.4 4.8 6.2 9.2 12.5 3 580242 4184837 5.7 2196 17.0 9.8 7.0 12.0 4.5 17.5 4 579395 4185188 6.5 4245 35.9 20.1 13.0 8.0 9.6 50.0 5 580287 4182406 6.8 669 6.0 2.1 2.4 6.7 2.1 1.8 6 579911 4183896 5.6 922 9.0 1.9 3.5 10.2 0.2 4.0 7 579700 4182600 6.5 671 6.4 1.6 2.4 6.1 2.1 2.3 8 577300 4181250 6.5 1246 13.3 1.9 4.1 11.5 0.4 7.5 9 577650 4181650 6.5 563 6.0 3.5 4.5 10.8 0.3 3.0

10 578889 4179886 5.8 1113 10.2 2.6 4.9 12.4 0.4 4.8 11 583626 4179600 6.9 338 3.8 0.2 1.1 4.5 0.2 0.5 12 577344 4183197 6.6 4429 43.0 19.0 10.0 7.1 17.7 45.0 13 577968 4182756 6.2 5317 44.1 21.4 26.0 10.0 15.1 62.5 14 582572 4183178 7.0 1279 9.5 4.5 5.1 5.5 8.9 4.8 15 588000 4179950 6.1 431 4.2 1.0 1.5 5.4 0.8 0.6


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Fig. 5 Isopach map of the Azarshahr plain aquifer.


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Markov processes in a problem of the Caspian sea level forecasting Mikhail V. Bolgov1

1- Water problems institute Russian Academy of Science,119991, Russia, Moscow, Gubkin st., 3,E-mail: [email protected]

Abstract In hydrological applications, the problem of the definition of a type of the stochastic model of the process under investigation and its parameters estimation is important. One of the most interesting cases is the closed water body level forecasting. Being the integrated characteristic, the level of a closed water body is rather sensitive to the behavior of the processes determining the inflow and the outflow components of the water balance on long time intervals. To solve the problem of forecasting of the Caspian Sea level fluctuations, both Langevin approach to the solution of the stochastic water balance equation and the diffusion theory of Fokker-Planck- Kolmogorov are used. For the description of river runoff fluctuations there are used: - the solution of Markov equation in the form of the bilinear decomposition on systems of

orthogonal functions; - stochastic differential equations (SDE) in the form Ito or Stratonovich; - diffusion equations of Fokker-Planck- Kolmogorov;

Key Words: Caspian Sea, Water level fluctuations, Markov equation.

Introduction In hydrological applications, the problem of the definition of a type of the stochastic model of the process under investigation and its parameters estimation is important. One of the most interesting cases is the closed water body level forecasting. Being the integrated characteristic, the level of a closed water body is rather sensitive to the behavior of the processes determining the inflow and the outflow components of the water balance on long time intervals. The researches carried out during recent decades have shown the description of the runoff fluctuations as the simple Markov chain to be acceptable.. To solve the problem of forecasting of the Caspian Sea level fluctuations, both Langevin approach to the solution of the stochastic water balance equation and the diffusion theory of Fokker-Planck- Kolmogorov are used. For the description of river runoff fluctuations there are used: - the solution of Markov equation in the form of the bilinear decomposition on systems of

orthogonal functions; - stochastic differential equations (SDE) in the form Ito or Stratonovich; - diffusion equations of Fokker-Planck- Kolmogorov;

Let us consider the listed problems in more detail.

The solution of Markov equation in the form of bilinear decomposition on systems of orthogonal polynoms.

The two-dimensional density satisfies to Markov equation (under some conditions) if it the sum of the following kind [3]:

+= ∑∞

=

− )()(1)()(),,(1

yxeypxpyxtp kkk

tk ϕϕλ (1)


where λk are positive numbers, so as 0 < λ1 ≤ λ2 ≤ λ...≤ λk.<...,

and ϕk(x) andϕk(y) form the system of orthogonal functions with the weight p(x) Generalization of (1) on the case of the so-called two-parametric gamma distribution has been developed by E.S.Blohinov and O.V.Sarmanov. The two-dimensional density for

xexГ

xp γγγ

γγ −−= 1

)()( will be written as [1]:

+= ∑=

−−n

ikk

k yLxLRypxpyxf1

11 )()(1)()(),( γγ γγ , (2)

where)1(!)1(~

+Γ++Γ⋅=

αααα

nnLL nn .

Diffusion processes. The transition probability density f that satisfies to Markov equation also satisfies to the inverse Fokker-Planck-Kolmogorov (FPK) equation, which looks like:

2

2

2),(

),(xfxsb

xfxsa

sf

∂∂−

∂∂−=

∂∂

,

(3) Where a (s, x) is called a drift coefficient, and b (s, x) - a diffusion coefficient. The two-dimensional density that represents the solution of the equation (3) generates the diffusion Markov process. The stochastic differential equations. Following [4], let us consider the case when some system is described by the following differential equation:

)(),(),( tnthgthfdtdh ⋅+= ,

(4) with the given initial conditions: h(t0) = h0 , n(t) is normal white noise.

If h(t) is the diffusion Markov process with drift coefficients a (h, t) and diffusion coefficients b (h, t), then for the stochastic differential equation (SDE) the following relations are true:

a(h,t) = f(h,t)+h

thgthgN∂

∂ ),(),(

40

(5) b(h,t) = N0 g2(h,t)/2

(6) Here N0 is the white noise intensity. The solution of SDE, received in such a way, can be obtained by two methods. The first method named the Langevin one assumes the notation of SDE solution by quadratures and the consideration of this solution as some operator, transforming the input random process into the output one.

The other idea will consist in an identification of the written equation of the system with the stochastic differential equation and in the calculation of the FPK equation coefficients with its subsequent solution.


Markov process with two-parametrical a priori gamma- distribution. Having got two-dimensional density, let us receive corresponding coefficients of the FPK

equation and then SDE. So, for the one-dimensional distribution law

xexГ

xp γγγ

γγ −−= 1

)()(

(7) Let us calculate the drift coefficient in the FPK equation:

)1()( −−= xxa µ (8)

γµxxb 2

)( =

(9) Let us write the stochastic differential equation as

=dtdx

)1( −− xµ -γµ2 0

2Nx

γµ+ n(t)

(10)

Modelling of pseudo-random variables according to the scheme of the Markov gamma-process. Let us further consider the third approach based on the difference approximation of the solution of the stochastic differential equation [4]:

+∆∆

∂∂+

∂∂+

∂∂+∆

∂∂+∆+∆+=+ i

iiiii

iiiiiii vt

tg

hgf

hfgv

hggvgtfhh

21

21 2

1

32

22

2

211

ii

ii

i vhgg

hgg

u∆

∂∂+

∂∂

(11)

For calculations using (11) it is necessary to calculate derivatives on each time step and to simulate the sequence of Wiener process increments with the given parameters.

The solution of the stochastic differential equation of the Caspian Sea water balance. The differential equation of water balance of Caspian Sea looks like [2]:

)()( tgthdtdh +−= α , (12)

where h -is the sea level; α - is the parameter dependent on the coast steepness and g is the resulting of the processes of inflow and evaporation from sea surface minus the precipitation on its surface. It is supposed also, that g is the stationary Markov process with autocorrelation coefficient and a dispersion known. The solution of the equation (12) is possible to be found in two ways. One of them is the


already mentioned Langevin approach considered in [2] in detail. At realization of Langevin approach it is difficult to receive a form of conditional distribution because the corresponding equations are written for parameters (moments) of distribution. For the numerical solution of the equation (12) let us use its difference approximation and the corresponding algorithm considered above. Using random numbers generation algorithm, let us receive realizations of the sea level course for 50 years forward with the same initial condition. The results of such numerical experiment are presented in table 1. The comparison of the results of two approaches applied to the solution of the probability forecasting problem of the Caspian sea level shows, that the limitation by Markov approximation results in regular overestimate of conditional dispersion for the forecasting period about 10 years and less. At big time period the results practically coincide, that as a whole corresponds to the assumptions made earlier.

Conclusions.1) For modelling the runoff and evaporation processes, the stochastic differential equation is

offered generating the so-called Markov gamma- process with the linear regression equation. 2) The description of the Caspian sea level dynamics in frameworks of the diffusion

approximation (Fokker-Planck-Kolmogorov equation) is acceptable for forecast time of more than 10 years.

References 1. Blohinov E.G., Sarmanov O.V. (1968) Gamma-correlation and its use for calculations of

long-term river runoff regulation. Tr. GGI.-I. 14, Gidrometeoizdat, Leningrad, 52-75 (in Russian).

2. Muzylev S.V., Privalskij V.N., Ratkovytch D.Ja. (1982) Stochastic models in engineering hydrology. Nauka, Moscow (in Russian).

3. Sarmanov O.V. (1961) The research of stationary Markov processes by method of decomposition on eigen functions. Tr. MIAN, 239-261 (in Russian).

4. Tihonov V.I., Mironov M.A. (1977) Markov processes. Sovietskoe radio, Leningrad (in Russian).

Tables Legends Table 1. Results of numerical solution of CDE of the Caspian Sea balance (38)

with initial condition H0 =1 m. Time period, years 1 5 10 20 30 40 50 Conditional average 0.77 0.69 0.58 0.45 0.32 0.23 0.16 Conditional mean square deviation (MSD)

0.21 0.43 0.57 0.71 0.74 0.79 0.80

Asymmetry 0.02 0.06 0.02 -0.01 -0.01 -0.04 0.07 Conditional MSD for Langevin approach [2]

0.13 0.39 0.54 0.69 0.76 0.79 0.81


Water Deficit and Drought Forecast by a Markov-Chain Model: Case Study in Central Iran

Peyman Daneshkar Arasteh1 and Masoomeh Mianehrow2

1- Hydrology Department, Soil Conservation and Watershed Management Research Institute (SCWMRI), Tehran, Iran. P.O.Box: 13445-1136, Tehran, Iran Phone: 0098-21-4901240 ~ 47 Fax: 0098-21-4905709 E-mail: [email protected]; 2- Former graduate student of Climatology E-mail: [email protected]

Abstract Deserts emerge and expand as a result of destruction of vegetation cover. If the plant is watered and irrigated enough, in the proper time and place, the vegetation cover is firmed and desertification is stopped. If the time and magnitude of watering with the peak of water consumption of plant are unbalanced, the vegetation cover is weakened and if this shortage continues, the vegetation will be destroyed. Water deficit due to drought accelerates this vegetative destruction. In this research the Thornthwait Moisture Index (TMI) is used to foresee the drought. According to run theory, a threshold was determined and on the basis of this threshold, in respect to the gained index, the system is divided into three conditions: normal, water excess and water shortage. In addition to have a quantity, the above-mentioned threshold, needs a definition of a period of continuation. In this research, a band with a width of two times of standard deviation as threshold and a three-year continuation period are used. On this basis, if the TMI is in this band, the region is in normal condition, if not, provided that the index is out of the band for three years, depending on the absolute value of the index, the system is either improving or being destroyed. Using the achieved definitions of the system’s condition on the basis of the TMI and mentioned continuation period, the transition and static probability matrices were calculated according to forecast the long time probability of regional desertification as normal, excessive or short, is represented in this paper. The research was carried out on the Central Basin of Iran (CBI) and iso-probability maps of water deficit are provided. The maps show that the study area will be in normal condition with a probability of 50 to 60 percent and dry out with probability of 38 to 50 percent in future. Only with a maximum probability of 2 percent state of the CBI changes to improve. Drying gradually increases and is fixed after 25 to 40 months.

Key Words: Iran, Markov Chain, Thornthwait Moisture Index, TPSS, Water Deficit

Introduction Desertification is the degradation of drylands. It involves the loss of biological or economical productivity and complexity in croplands, pastures, and woodlands. If the time of watering and peak of water consumption of plant are unbalanced, the vegetation cover is weakened and if this water shortage continues, the vegetation will be destroyed. It is due mainly to climate variability and unsustainable human activities. Drylands respond quickly to climatic fluctuations and have limited freshwater supplies. Precipitation can vary greatly during the year. In addition to this seasonal variability, wide rainfall depth fluctuations occur over years and decades, frequently leading to drought. In the other hand, land degradation affects the quantity and quality of freshwater supplies too. Drought and desertification are associated with low water levels in rivers, lakes, and aquifers. Success in combating desertification will require an improved understanding of its causes and impacts. There is still much to learn about the linkages between desertification and climate, soils, water, plants, animals, and, in particular, people.


Drought is an environmental phenomenon and an integrated part of climate variability. It is also an inherent, normal, recurrent feature of climate (Wilhite, 1997; Dupigny-Giroux, 2001). Drought occurs everywhere and causes intense water shortage but its characteristics vary significantly from one region to another (Baren, 1985). There are several classifications of drought among different disciplines. A popular and world-wide accepted disciplinary perspective classification, classifies droughts into meteorological, hydrological, agricultural and socio-economical drought (Dracup et al. 1980a). In order to analyze drought, an index is required to determine wet and dry spells clearly. Many researchers have proposed several drought indices. Among these indices, the most commonly used are Bhalme and Mooley Drought Index, BMDI (Bhalme and Mooley 1980), Crop Moisture Index, CMI (Palmer, 1968), Deciles (Gibbs and Maher 1967), Palmer Drought Severity Index, PDSI (Palmer 1965), Percent of Normal, PN (Willke et al. 1994), Reclamation Drought Index, RDI (Weghorst 1996), Standardized Precipitation Index, SPI (Makee et al. 1993,1995), Surface Water Supply Index, SWSI (Shafer and Dezman 1982), Thornthwait Moisture Index, TMI (Subrahmanyam, 1985). In this paper, how the climate causes desertification in Central Basin of Iran (CBI) and how desertification border by climatic factors fluctuations could be predicted, is represented. In this regard, Thornthwait Moisture Index (TMI) was used. It is the algebraic sum of humidity and aridity indices that both are the ratio of available water (precipitation) to consumptive water (potential evaporation), respectively in two periods of wetness and dryness (water excess and shortage durations). Also, a linear Markov’s process was applied to forecast the situation of CBI in future.

Materials and Methods Study AreaThe study area has been located between 48o 27’ to 61o 29’ eastern longitudes and between 27o 12’ to 36o 41’ northern latitudes including all or some parts of 14 provinces of Iran. These provinces are Zanjan, Hamadan, Qazvin, Tehran, Semnan, Khorasan, Isfahan, Yazd, Fars, Hormozgan, Sistan and Baloochestan, Kerman, Qom and Central Province. The CBI is the largest watershed of Iran with an area about 50% of the area of the country. Lack of precipitation causes few permanent rivers in this watershed. River flow regime in high lands is snowy and in low land is rainy. Climate of CBI in Thornthwait classification varies form EB’2c’1d in high lands of northwest to EA’b’1d in low lands of southeast of CBI (Mianehrow, 2002). Several investigations about drought extend zonation has been carried out in CBI. Mianehrow (2002) and Mianehrow et al. (2003) studied the drought, spatially in CBI by time series modeling and Razi et al. (2003) determined the SPI distribution over Yazd Province in central part of CBI. Also, Shokoohi et al. (2002) studied drought occurrence in southeast of Iran by Z-score. In this research to study the climatic behavior of the CBI, 29 synoptic stations of National Weather Organization (Fig. 1) with data length of 30 years from 1971 to 2000 were used. Ambrothermic diagrams show large temporal variation in temperature and rainfall in the study area. For example Fig. 2 shows one of these diagrams for Yazd synoptic station. As this diagram shows, seasonal variation of temperature is large and precipitation concentrates in a period from late autumn to early spring. CBI is a sensitive watershed and is under desertification and dryland degradation impacts. Across the CBI, these diagrams show different spatial behavior of temperature and rainfall. MethodologyIn this research, it was assumed that water shortage investigation could be used to predict sensitivity of vegetation cover to water deficit and to forecast desertification extend. To study


the trend of desertification and vegetation destruction, Thornthwait Moisture Index (TMI) was used and required data was achieved from synoptic stations spread over CBI. TMI as Thornthwait defined in 1948 (Subrahmanyam, 1985) is the difference between humidity and aridity indices, which are defined as the ratios of excess and deficit in annual water supply (i.e. difference between precipitation and evaporation to annual potential evaporation). Bearing the run theory in mind, a threshold was determined and on the basis of this threshold, in respect to the gained index, the system is divided into three conditions: normal, water excess and water shortage. In addition to have a quantitative magnitude, the above-mentioned threshold, needs a definition of a period of continuation. In principle, the threshold and its continuation must be determined in respect to the dominant type of the regional vegetation cover and the representative types’ tolerance against water deficit. For all stations, TMI time series was derived and a band of normality was defined about the mean as truncation level on the base of run theory (Sharma, 2000, Moye et al., 1988). Outside this band (threshold) water excess or shortage situations are specified. Width of this band was selected two times of standard deviation of TMIs for each station as Shokoohi et al. (2002) and Razi et al. (2002) introduced for drought indices for east and southeast of Iran and a three-year continuation period, are used, without considering the biological factors and with reliance on statistical deductions. To predict the future situation of CBI a stochastic modeling was conducted. As shokoohi et al. (2002) confirmed, a first order Markov-chain was used to predict the probability of occurrence of each state on a stepwise manner.

ResultsAfter forming TMIs time series on monthly basis and considering the state of each month according to the normal band and recognizing its state, probability of moving from each state to others (water shortage to normal and excess, normal state to shortage and excess states and excess to shortage and normal states) was determined. To form the Markov-chains, transition probability matrices (TPMs) must be computed as mentioned above. The TPMs and initial state probability vectors (ISPVs) for each time series was determined. Table 1 and Fig. 3 show TPM and TMI time series diagram for Yazd, respectively.

DiscussionObservation of time series shows normal state for all regions of CBI in 1997. So the ISPV for all time series was considered as [0 1 0]. It means the state of CBI has been normal before starting the modeling. The TPMs show that in most regions of CBI like Yazd, there are only two states of shortage and normal and in western and northwestern parts of CBI, the TPM is a trapping one. A trapping TPM causes the steady state probability vector (SSPV) becomes similar to ISPV. It means for every ISPV, the given ISPV repeats for SSPV. For example if ISPV in a region is normal, its SSPV will also be in normal condition. Stochastic modeling with linear Markov-chain was carried out for all 29 stations until 2005. It was shown that steady state or smoothing condition accurse after 25 to 40 months. Table 2 and Fig. 4 show this smoothness for Yazd station. After forecasting SSPVs for all stations, interpolation procedure was done to map the sensitive area to water deficit. On the base of Mahdian et al. (2001) investigation, a thin plate smoothing spline interpolator (TPSS) with a weight of two was applied to interpolate point SSPVs to an aerial extend raster map by ArcView GIS. Three contour maps of different states were inferred (Figs. 5 to 7). They showed normal state is the major condition of CBI and its occurrence probability is between 50 to 60 percent (Fig. 6). Water shortage state occurs with probability of 38 to 50 percent (Fig. 5) and occurrence of less water deficit, which was called excess state in this paper, has a probability less than 2 percent (Fig. 7).


ConclusionCentral Basin of Iran (CBI) is a sensitive region and desertification in this area is active now. A study was conducted to show if desertification has a climatological cause or another factors cause this phenomenon. In this regard, Thornthwait Moisture Index (TMI) and its temporal variations were selected as time series. On the base of run theory three states of water shortage and excess, and normal were recognized. A linear Markov process was applied to forecast the steady state probability of each state in long times. It was shown that steady states would occur after 25 to 40 months. And aridity is the nature of CBI and occurrence of water deficit in 50 to 60 percent of times is normal and in 38 to 50 percent of times, water deficit is drought and is not a normal event. Only less than 2 percent, it is expected to improve the state and less water deficit takes place. Also, spatial distribution of steady state probability (iso-probability maps) showed that central parts of CBI are in high risk of drylands degradation. So the climatic parameters are principle factors of desertification in long time and some other factors like human activities increase the speed of desert development and have short time impacts.

References 1.Bhalme HN, Mooley DA (1980) Large-scale drought/floods and monsoon circulation. Monthly

Weather Review 108: 1197-1211 2.Baren MA (1985) Hydrological aspects of droughts. UNESCO/WMO London UK 3.Dracup JA, Lee KS, Paulson EGJr (1980) On the statistical characteristics of drought events. Water

Resources Research 16(2): 289-296 4.Dupigny-Giroux LA (2001) Towards characterizing and planning for drought in Vermont-Part I: A

climatological perspective. Journal of America Water Resources Association 37(3): 505-525 5.Gibbs WJ, Maher JV (1967) Rainfall deciles as drought indicators. Bureau of Meteorology Bulletin

No. 48 Commonwealth of Australia Melbourne Australia 6.Mahdian MH, Hosseini SAC, Fatehi A., Vahhabi J (2001) Determination of suitable interpolating

method for rainfall and temperature in dry, semi-dry and humid climates of Iran. Research No. 77-051030100000-17 Soil Conservation and Watershed Management Research Center Tehran Iran (in Persian)

7.McKee TB, Doesken NJ, Kleist J (1993) The relationship of drought frequency and duration to time scales. Proceeding of the 8th Conference on Applied Climatology 17-22 January Anaheim CA USA 179-184

8.McKee TB, Doesken NJ, Kleist J (1995) Drought monitoring with multiple time scales. Proceeding of the 9th Conference on Applied Climatology 15-20 January Dallas TX USA 233-236

9.Mianehrow M (2002) Determination of desertification trend in affected regions of Iran by climatic indices and mathematical modeling. MSc. Thesis Free University Rey Branch Tehran Iran

10. Mianehrow M, Arasteh PD, Shokoohi AR (2003) Identification and prediction of desertification by time series analysis in Central Watershed of Iran. Proceeding of the 7th International Conference on Development of Dry Lands Tehran Iran

11. Moye LA, Kapadia AS, Cech IM, Hardy RJ (1988) The theory of runs with applications to drought prediction. Journal of Hydrology 103: 127-137

12. Palmer WC (1965) Meteorological drought. Research Paper No. 45 U.S. Department of Commerce Weather Bureau Washington D.C. USA

13. Palmer WC (1968) Keeping track of crop moisture conditions, nationwide: the new Crop Moisture Index. Weatherwise 21: 156-161

14. Razi T, Saghafian B, Shokoohi AR (2003) Drought monitoring and management based on SPI index. Proceeding of the 7th International Conference on Development of Dry Lands Tehran Iran

15. Razi T, Shokoohi AR, Saghafian B, Arasteh PD, Daneshvar S (2002) Derivation of drought severity-duration-frequency curves and development of drought iso-severity maps in southeast of Iran. Proceeding of the 1st national conference on water crisis mitigation strategies Zabol Iran (in Persian)


16. Shafer BA, Dezman LE (1982) Development of a Surface Water Supply Index (SWSI) to assess the severity of drought conditions in snow pack runoff areas. Proceedings of the Western Snow Conference 164-175

17. Sharma TC (2000) Drought parameters in relation to truncation levels. Hydrologic Processes 14: 1779-1788

18. Shokoohi AR, Saghafian B, Razi T, Arasteh PD (2002) Drought severity forecast in southeast of Iran by stochastic modeling. Proceeding of the 1st national conference on water crisis mitigation strategies Zabol Iran (in Persian)

19. Subrahmanyam VP (1985) Water balance approach to the study of aridity and drought with special reference to India In: vander Beken A, Herrman A (eds.) New approach in water balance computations IAHS Publication No. 148

20. Weghorst KM (1996) The reclamation drought index: Guidelines and practical applications. Bureau of Reclamation Denver Colorado USA 6 pp

21. Wilhite DA (1997) Responding to drought: Common threads from the past, Visions for the future. Journal of America Water Resources Association 33(5): 951- 959

22. Willeke G, Hosking JRM, Wallis JR, Guttman NB (1994) The national drought atlas. Institute for water resources report 94-NDS-4 U.S. Army Corps of Engineers

Table 1. Transition probability matrix Yazd (%). Station State Shortage Normal Excess

Shortage 78.1 21.9 0.0 Normal 22.6 77.4 0.0 Yazd Excess 0.0 0.0 0.0

Table 2. Smoothness of state probability vector in Yazd station. Month 1 2 3 4 5 6 7 8 9 10

S 0.1421 0.23516 0.29611 0.33602 0.36216 0.37928 0.39049 0.39783 0.40264 0.40579N 0.8579 0.76484 0.70389 0.66398 0.63784 0.62072 0.60951 0.60217 0.59736 0.59421

Month 11 12 13 14 15 16 17 18 19 20 S 0.40785 0.4092 0.41009 0.41067 0.41105 0.4113 0.41146 0.41157 0.41164 0.41168N 0.59215 0.5908 0.58991 0.58933 0.58895 0.5887 0.58854 0.58843 0.58836 0.58832

Month 21 22 23 24 25 26 27 28 29 30 S 0.41171 0.41173 0.41174 0.41175 0.41176 0.41176 0.41176 0.41176 0.41176 0.41176N 0.58829 0.58827 0.58826 0.58825 0.58824 0.58824 0.58824 0.58824 0.58824 0.58824

r

r

r

r

rr

r

r

rr

r

r

r

r

r

r

r

r

r

r

r

r

r

r

r

r

r

r

r

Bam

Arak

Yazd

Baft

Anar

Tabas

Zabol

Khash

Khoor-e-Biabanak

Semnan

Qazvin

Kashan

Kerman

Zanjan

Shiraz

Abadeh

Sirjan

Esfehan Birjand

Hamedan

Zahedan

Kahnooj

Torbat-e-Heydarieh

Tehran

SabzevarShahrood

Iranshahr

Nehbandan

Shahr-e-Kord

400 0 400 800 Kilometers

Fig. 1. Central Watershed of Iran and location of synoptic stations.


Fig. 2. Ambrothermic diagram for Yazd.

Fig. 3. TMI time series of Yazd.

Fig. 4. Smoothness of state probability vector in Yazd.


Fig. 5. Spatial distribution of SSPVs of water shortage state across CBI (%).

Fig. 6. Spatial distribution of SSPVs of normal state across CBI (%).

Fig. 7. Spatial distribution of SSPVs of less water deficit (excess) across CBI (%).


Social and Economical Evaluation of Rainfall Catchments in Larestan Region

3Shahvali.and M2Shirani ., M1Fatahi.R1- Assistant professor, Shahrekord university, E-mail: [email protected] 2- instructor, University of Applied Science and Technology, E-mail: [email protected] 3- Assistant professor, Shiraz university

Abstract: Deficit and unsuitable time distribution of rainfall in most parts of Iran cause both drought and flood as two serious problems in the country. Residents of those areas have used rainfall catchment in a wide range to adapt with nature and overcome the water shortage. The residents of Larestan region in south west of Iran have overcome water shortage and soil salinity using this method. The main objective of this study was economical and social evaluation of these water supply systems. The results show that the mentioned rainfall catchments are sustainable from social and economical point of view. The results also show that traditional water-harvesting systems are in accordance with socio-economic aspects in the region.

Key words: rainfall catchment, Socio-economic, sustainabity, water storage

Introduction Applying new technologies to use natural resources has terrible results on environment. In addition the tendency to transfer and apply modern science and technology to get more and more from natural resources cause deterioration of the human kind and its surrounding environment.Looking for sustainable approaches in developed and developing countries indicates that human kind realized its mistakes and try to accept a new and special philosophy to face environmental issues so called “past modernism”. This new vision is returning to past social values, cultures, views and methods and review and adapts them for modern life criteria. In other words this new vision is to scope on local knowledge, which means a kind of sustainable development that is in accordance with culture, social system and other characteristics that has roots in historical heritage of the society. To accept and apply sustainable development in a region the historical, cultural, social and economical records of the region must be considered. It means that the approaches to achieve the sustainable development may be different in each region or country than other places around the world. As an example we can refer to the adaptation of the people in desert that results from their survival with nature and their serious participation to undertake great attempts for survival. The most important achievement of this adaptation is providing water requirements as the critical factor to survive in the desert. It has been done by digging a chain of wells connected to each other by underground tunnels (Qanat) and collecting water by construction of rainfall catchment and preserve them till now. The world wide variations of rainfall catchment is the main reason for investigators and water resource specialists to search ways to renew the traditional methods of direct use of rainfall. The overall objective of these researches is to increase the water security which is cutting down day by days. The main goal of this paper is to evaluate social and economical aspects of rainfall catchment and to present policies of supporting and improving their negative features. In this paper the rainfall catchment is equal to water reservoir and its catchment area.1.1. Importance of rainfall catchment systems


Perhaps the history of water catchment systems in arid and semi-arid areas backs to many years ago. Yu-si-fok [14] in a research from china reported that using rainfall is an essential way to supply irrigation and drinking water in arid and semi-arid regions of china. He noted that construction and maintaining traditional water-collector systems helped the improvement of rural sanitary and increases the agriculture products in those areas. He concluded that the main reason of succession of these systems is the public participation in all phases of projects and it is a key element in such systems everywhere can be found. Rainfall catchment systems can also find in Tahar desert of India, where water stored in reservoirs called “Kand”[9]. These systems have been by participation of all users from local material and technology and or in some cases the rich people made them for rural people. These systems could provide fresh water to drink and saved people’s time and energy otherwise they have to travel for hours to get water. Ferrokh, L. and C. Sweden [4]have studied the water supply systems in India and found that the most common ways of water supply in this country are traditional systems and the sustainability of these systems is due to adaptation by culture, construction methods and social systems of local residents. Andrew [1] mentioned that using rainfall is essential to achieve sustainable water resource development. He noted that water rainfall catchment are small scales and economical ways to supply water demands in arid and semi-arid areas and hence help to protect the environment. Bidokhti [13] reported that the water catchment systems play an important role in sustainable economic development in Fars province because the stored water has been used in agriculture and increase productions. He also mentioned that this water is usually cheaper than water from other resources such as ground water or dams. Water catchment systems in this region decrease people immigration and affected social and personal behavior of the people. The relation between people gathered around water reservoir get better, therefore the social relations have been improved. Finally he concluded that by using new technology and improving the performance of water catchment systems they could be suitable for sustainable development.Ghodosi [5] in his paper wrote that establishment of large water supply systems is impossible in some places or should have negative impacts on environment. He also concluded that using regional rainfall is a good solution to reach sustainable development. The water catchment systems have these capabilities. 1.2. Water catchment systems and sustainability Sustainable water resource systems are those which designed and managed so that provide society needs in the present and future meanwhile keeping the stability and equilibrium of environmental and hydrological parameters [7]. To achieve high level of sustainability in renewed water resource systems the renewed capacity of those systems to supply enough water with desirable quality and to support environment and relayed ecosystems must be taken into consideration and try to increase this capacity. Undoubtedly it is the precondition for such systems to provide future generation needs [2]. Based on ideas and definitions of sustainable development four main aspects of sustainable water resources can be presented as: social, economical, technical and environmental sustainability. Therefore to reach sustainable development in water resources a special programming, design, operation and maintaining must be followed. According to Pitter Laks[10] sustainable water resources must have the following criteria: − Technically: effective design and management to make balance between demands and supply. − Environmentally: negligible or no long term negative effects on environment − Economically: total costs of development and management can be returned − Socially: support by society and its tendency to pay for provided services.


There are also other opinions about water resources sustainability, presented by specialists, which may be summarized as Keeping, improving and providing: − better life conditions for every one in society − better environmental conditions − better economical conditions in which equality, self dependence and enough productivity to provides needs must be considered.Water catchment systems have the following characteristics that well matched the criteria for sustainable water resource development: − They are in accordance with regional environment and have long life period. − They can be applied in both small and large scales. − They can be constructed by local materials and simple traditional methods. − They have been managed by local culture.

Materials and methods: The main objective of present research was social and economical evaluation of water catchment systems in Larestan region. Two specified goals were considered: − Social and economical evaluation of water catchment systems in the region − Introducing policies to improve their performance and support them The region has been faced by water shortage due to intensive evaporation imposed by climatologic conditions, water salinity imposed by geological and Hydrological conditions and population increase. The investigated area consists of four regions that are Lar, Ovez, khonj, and Grash. The research has been done by surveying the regions, which is one of subset of descriptive research methods. In this method the aim of investigation is to find the reasons of pre recognized phenomena and explain them. As the goal of this research was to explain the economical and social aspects of water catchment systems, the survey method was selected. Economical sustainability factors of water catchment systems are the beneficiary use of the stored water for agriculture, livestock and drinking, considering the construction, maintenance, and repairing costs. The effects and proportionality of these systems by families and social economic conditions and their capability to provide water demands in drought periods must be taken into accounts.Social sustainability factors are participation on decision and management of water catchment systems, improvement of social relations due to systems, immigration of rural people due to water shortage and people satisfaction of the systems. 1. The scores of questions related to social and economical sustainability were computed separately in such way that the sum of average scores for each category indicates the total sustainability of that category. 2. To investigate the simultaneous effect of social and economical aspects the multi variable regression for each category and sum of two categories was used. The investigated community was the users of water catchment systems in the regions. 25 sample from each region (100 in the whole area) were selected randomly and they were asked to fill out a questionnaire or answer oral questions asked by interviewer. As we were looking for water catchment knowledge more than 60 percent of samples were above 50 years old. The samples contain 30% of 49 years and the rest was younger. Each question in the questionnaire has a score ranging between 1 for very low to 5 for very high. Content validity of the questionnaire was established by a panel of experts in the field of agriculture, economists, socialist and water management. It was also tested by face validity method and approved by experts. To evaluate validity of the questionary a pilot study was conducted to establish reliability of the instrument for the population of interest. The questionnaire was filled out by 20 interviewees and tested by Cronbach’s alpha (a reliability


coefficient) method. After doing this test some modification has been made to the questionnaire in order to increase its validity. The reliability coefficient for the questions within questionnaire to measure social and economical variables of sustainability in this research were as follows: − Social variables = 0.5 − Economical variables = 0.77 − Validity coefficient for whole questionary = 0.63 According to Pedhazur (1982), a reliability coefficient of above 0.5 is acceptable for a non-experimental study. Data were gathered by interviewing residents and completing the questionnaires. A uniform technique of interviewing was adopted, in order to reduce data collection errors. Since data gathering was done in person the response biases of those participant conducted earlier and later. Comparing the responses of those contacted earlier with the later responses on the dependent variables showed no statistically significant differences. Data collected from the participants were analyzed using SPSS (standard version 9.0 for windows).

Discussion and ResultsBased on social sustainability indices it is clear that more public participation will result in more social sustainability. The aid and accompany of local leaderships to establish water catchment systems and their attitude to solve the problems of community will be replied by people appreciation and increase the responsibility among the member of society to maintain the systems more efficiently. The community should admire the system and try to increase its sustainability. More public and local leaderships participation in decision making on related aspects of rainfall catchment should result more sustainability. The results also show that the effectiveness of stored water in the systems during drought periods to supply water deficit is another reason of social sustainability of the systems, which cause water user satisfaction and prevent people immigration from rural areas. Briefly one can conclude that the improvement of social relations increases the social sustainability of the water catchment systems that is in agreement with previous results in Iran [11] and Brazil [2]. Economical sustainability indices show that more withdrawal of stored water to provide drinking water, agriculture and livestock uses will increase economical sustainability of water catchment systems. This study also shows that above mentioned indices and their effects on economical sustainability are in agreement with previous results of Andrew [1], Pandey [9] and Sethcook [12]. The coexistence of rainfall catchment systems with governing environmental conditions and their positive effects on environment such as reduction of natural deteriorative phenomena, prevention of rainfall water losses and supply good quality water are the main reasons of their environmental sustainability. These results also are in agreement with previous studies of Gnadlinger [6] and Andrew [1] about environmental sustainability of traditional rainfall catchment systems. Other indices to measure the sustainability are the long lifetime period and using of local material in construction that reduces the cost of water supply.

Conclusions

The final conclusions and suggestions from this study are as follow: 1. Traditional water supply systems keep their capacity to overcome water shortage in rural areas till now and must be revised in order to provide more water safety. 2. In the new visions the public participation in development is a key factor and must be taken into account to all development programs.


3. To increase the water quality in rainfall catchment systems the pollutant sources must be controlled.4. There are several regions with similar traditional water supply systems around the country such as Yazd and Khorasan provinces which must be studied in order to make a national decision to improve their efficiency. 5. As most of communities in arid zones are among the low-income people the government investment is essential to the construction and maintenance of rainfall catchment systems as an effective way to supply water.

References

1. Andrew, F. (2000). A Simulation model of flood runoff utilization in Taiwan. www.rainwaterharvesting.com/pdf

2. Anonymous.( 2002). Aguadas, centes and chituns. Available in: www.water.history.ury/h:stories/ayuuads.

3. Bozorgzadeh, M. A., Jahani, G., (1993) “Water and population”, special publication on water and development, 2(10-51).

4. Davis, J. A. (1970) Elementary Survey Analysis. Englewood Cliffs, NJ. Prentice-Hall.5. Ferrokh, L. and C. Sweden. (1998) Indigenous knowledge of water management.

www.findarticels.com6. Ghodosi, J. (1997)Environment, Water and Life, Journal of Rout, 34 ( 4-6).7. Gnadlinger, J. (2000) Rainwater harvesting for household and agriculture use in rural

areas. Available in: www.ircsa.org/meeting/reports8. Miller, L. E., and Smith, K. (1983).Handling Non-Response Issue. J. Extention,

21(45):38 9. Mousavi, F. (2000) Sustainable management of water resources. Journal of water and

wastewater, 33( 52-57). 10. Naser, M. (1999). Assessing desertification and water harvesting in the middle east

and north Africa: policy impliciations. Available in: http://www .zef.de11. Pandey, D. (2001). Sacred water and sanctified vegetation: tanks and trees in India.

Available in: www.eapri.cyiar/pdf/capriwp18.pdf.12. Lax, P. (1994): “water management and sustainable development”, water and

development,3(2):6-15. (translated from English to Persian by jamali) 13. Saarvi, M. (1997). Investigations on rainfall collection techniques for water supply in

north east of Iran. Journal of Agriculture and natural resources, 3(1) 50-63.14. Li, S. (2000) Rain water harvesting agriculturel in Gansa.province, People s Republic

of China. Journal of soil and water conservation. ( 112-114). 15. Talebbeydokhti, N. (2000) Abanbars as a trustable method of water harvesting.

Available in: Html://www.Google.Com16. Yu-si-fok. (2000). Prospects of 21 century rainwater utilization in East Asia.

Available in: www.ircsa.org/meeting%20report/east%20asia.17. Zaare, M., Farhoodi, J. (2000) Proceeding of Iran Geology Conf., Shiraz University.


Table. 1. Compare average social and economical sustainability in the regions. (One way variance analysis)

Variable Lar Grash Ovez Khonj F P

Social sus. 4.41 a 4.43 a 4.8 b 4.5 a 7.98 0.0

Economic. sus. 4.11 a 4.27 a 4.3 a 4.23 a 2.145 0.1

** similar letters (a, b) shows no significant difference between averages.

Table. 2. Multivariate Linear regression Analysis to find simultaneous effects of social factors on Social sustainability

Regressions coefficientsVariables Adjusted r2

β B SignificanceImprovement of social relations 0.228 0.365 1.45 0.0People relaxation 0.268 0.235 2.482 0.0Participatory decision making 0.299 0.189 2.033 0.033People satisfactions 0.326 0.183 2.042 0.034

Constant = 0.46 F = 12.58 sig. F= 0.00

Table. 3. Multi variables regression to find the simultaneous effective of economical and social factors on Socio-economic sustainability

Regressions coefficientsVariables

Adjustedr2 β B Significance

Beneficial features of systems 0.084 0.241 0.563 0.00Livestock water supply 0.163 0.223 0.503 0.009People participation on system construction 0.212 0.23 0.52 0.007People participation on decision making 0.265 0.26 0.45 0.006Livestock water supply during drought 0.298 0.286 0.691 0.002Using non-local material in construction 0.348 -0.204 -0.83 0.001Agriculture water supply during drought 0.372 0.218 0.545 0.019Improvement of public relations 0.403 0.225 0.399 0.01

Constant = 0.54 F = 11.31 sig. F= 0.00

Table. 4. Characterization of correlation strength (source: Davis 1971)

The magnitude

of correlation r20.7

0.5 to

0.69

0.3 to

0.49

0.1 to

0.29

0.01 to

0.090.00

Characterization Very strong

association

Substantial

association

Moderate

association

Low

association

Negligible

association

No

association


A Study on The Effect of Manure And Different Rate of Boron Application on Alfalfa Crop Yield

Roohallah Fatahi Nafchi1, Kamran Parvanak Borujeni2, ,Mehdi Pakbaz3, , and Rayhaneh Amooaghaie4

1-Assistant prof. Shahrekord University, 2- Islamic Azad University, Branch of Yadgar Emam, 3 - Msc. Of Soil Science4-Biology Department , Shahrekord University

Abstract:The effect of animal manure on amelioration of physical properties and improvement of soil fertility level is well known. Moreover boron requirement of Lucerne is comparatively higher than of other field crops. Hence, to obtain maximum Lucerne yield, estimation of boron fertilizer level based on field trial for each area is needed. The objective of this study was to estimate the effects of manure and optimum level of boron for maximum yield of Lucerne. The results showed that the treatments had significant effect on yield, P, Ca, Cu, Zn and B in the plant tissues concentration. Nevertheless maximum B, Zn, Ca, Cu concentration was brought by T7 but the highest level of P concentration with no significant difference with the effect of T2, T5, and T7 recorded for T6 treatment. Maximum yield, protein content and nutrient uptakes were obtained by T6 treatment. It is suggested that for yield increasing of alfalfa in Arjena spread 20-t/ha animal fertilizers and 20-kg/ha boric acid should be added to basic fertilizers and mix with soil before the last plow.

Key words: Alfalfa, boron, fertilizer, manure, nutrient,

Introduction: Population increase and improvement of life standards increases the demand for food and animal proteins products. Meanwhile the food supply for livestock feed inside the country is less than the demands and the import of forage imposes significant cost on the annual country budget. To provide the demanded forage inside the country the grass yield production per unit area must be increased. Among the grass crops, Alfalfa (Medicago Sativa) has the largest cultivation area and it is the most important grass inside the country. The lack of attention to soil nutrition and fertility in alfalfa farms by farmers and researchers and the number of annual harvesting in long period undoubtedly decreases the absorptivity of soil elements and reduces the quantity and quality of alfalfa yield. The effect of manure will improve physical and biological conditions of the soils hence increases the yield production is evident. At the same time the Alfalfa is among the most sensitive crop to boron deficiency. It is known that the band between maximum (toxic threshold) and minimum (deficiency threshold) of this microelement for agriculture crops is narrow. Therefore determination of appropriate amount of Boron based on field experiments for each location is necessary in order to achieve the maximum potential yield. Refer to aforementioned conditions and needs this experimental study was conducted in Arjena area to determine the effect of manure and different rate of boron application on alfalfa yield and to determine the optimum amount of Boron fertilizer to be added the soil so that the highest yield from alfalfa farms can be harvested.

Materials and Methods To investigate the effect of different boron levels on the macro elements concentration and the production of alfalfa, an experimental fields in the central part of Shahrekord plain so-called “Arjena Plain” was selected. The field then divided into ten equal area blocks


containing seven treatments with three replications via a full random block layout. The experiments were carried out by 2002 growth season. The treatments consists of: T1= testifier, T2= 20 tons of decomposed manure per hectare, T3= T2 + 5 kilograms boric acid per hectare, T4= T2 + 10 kilograms boric acid per hectare, T5= T2 + 15 kilograms boric acid per hectare, T6= T2 + 20 kilograms boric acid per hectare and T7= T2 + 25 kilograms boric acid per hectare. The selected farm was plowed, leveled, and then formed as basins. Each basin had dimensions of 3*2 meter and the borders between blocks had 1 meter width. The space between blocks was selected to be 1.5 meters. The customary fertilizers applied to the field before the last tillage based on soil tests. The distribution of treatments cited based on full random block method. The seed of Hamadani Alfalfa cultivars, which was confirmed by Shahrekord agriculture research center, was selected and cultivated as 60 kg per hectare. By this base rate the amount of seed per each basin was calculated and applied. The day after sowing all of the basins were irrigated and the irrigation intervals was once per 6 days. To obtain the maximum forage quality the harvesting was done by 10% flowering and the samples was taken within a 70*70 cm quarter in the center of each basin. The samples then dried by air and were weighted. These measurements were used to calculate the dry mass yield per unit area. Some parts of forage, which dried by air separately, were powdered in order to measure the macro and micro elements concentration within plant tissues. Nitric, perchloric, and solphoric acids mixed with powdered samples and these samples then were digested by wet digesting method. Nutrition elements concentration were measured using Koldal method for N, Olson method for P, film photometer for K, titration by EDTA for Caand Mg, Atomic absorption for Fe, Zn, Mn, Cu, and spectra photometer for B. Finally the results were analyzed with MSTAT statistical software and presented hereunder.

Discussions and Results: The results of soil tests on the experiment field are presented in Table.1. This table shows that the soils were generally heavy with PH around 7 and without any alkalinity or salinity restrictions. The organic matter and nitrogen content of soil were very low and the Boron concentration in both examined depth was below the critical level for Alfalfa crop. The results also showed that the phosphorus and potassium concentrations were high enough and with no limitation for crop growth. The results of physical and chemical analysis of soils in two depths are given in Table.1.

3.1. Effects of manure and B application on P, N, Ca and MgThe results of manure and different level of B applications on P, N, Ca and Mg concentration in Alfalfa crop are presented in Table.2. This table shows that although the application of manure and different dosage of B have no significant and differentiable effects on N, K, and Mg concentration in the plant tissues, these treatments statistically have significant and distinguishable effects on P and Ca concentration in the plant tissues within 5% (*) and 1% (**) confidence levels respectively. 3.2. Effects of manure and B application on PTo discuss the aforementioned results the graphical presentation of data is shown in Fig.1. The Donken test shows that the T6 treatment had the maximum P concentration and demonstrates 93% more P concentration within plant compared with testifier treatment. Although this treatment doesn’t show significant difference with T2, T5, and T5 treatments but statistically it has shown significant difference with T1, T3 and T4. To describe the different reaction of P concentration to the manure and B application the absorption of B by iron and aluminum hydroxides or creating a covering layer of organic substances over this hydroxides and preventing to substitute hydroxides by P ions and hence increasing the concentration of this element in soil solution is the most probable process [7]. It can be concluded that


increasing B application should increase the extractable P within soil solution and hence increases its up take by plant. This conclusion is in agreement with previous results from Porard et al. 1977 [6]. 3.3. Effects of manure and B application on CaBased on the presented results in Table. 2 and Fig.2 and comparing the average effects of manure and different level Boron application, T7 treatment with 35% increase in Ca concentration in plant tissue compared with testified treatment is the most efficient treatment in capturing Ca from the soil. This difference is not significant in comparison with T6

treatment but it shows significant difference with other treatments. These experiments and the results show that application of 20 tons manure per heater has no significant effects on Ca concentration in Alfalfa plant and increasing of Ca concentration is mainly due to B application which is facilitied the translocation of Ca within aerial parts of plant tissues. This conclusion is in agreement with the pervious results from Ramon et. al 1990[7]. 3.4. Effects of manure and B application on Cu, Fe, Zn, Mg and BThe results of statistical analysis of measurements are shown in Table3. These results suggest that there are no significant differences among treatments with different levels of manure and boron application considering the concentration of, Fe, Mg. However these treatments have significant differences considering Cu, Zn and B concentration in alfalfa plant. 3.4.1- Effects of manure and B application on CuThe results on Table.3 and statistical analysis with Donken test indicates that the T7 treatment has received the maximum Cu concentration of 42% more than testified treatment in comparison with other treatments. Although the difference between this treatment with T6

and T5 statistically is not significant but there is undeniable significant distinction when comparing them with T1-T4 treatments. Meanwhile the T1-T4 treatments are similar in capturing Cu from the soil during growth season. The observed differences can be explained in such way that the application of B increases the concentration of extractable B in the soil solution thus it will hasten root cell dividing [1,2,4] hence more root development should took place. The expanded root system will surround more soil volume therefore the plant could absorbed more extractable elements like Cu from the soil.

3.4. 2 - Effects of manure and B application on ZnThe measurements of Zn within plant tissues treated under different circumstances of soil fertilizers indicate significant differences. It is clear from table. 3 and graphical presentation of statistical analysis in the Fig.4 that T7 treatment with 20 tons of decomposed manure and 25 kilograms boric acid per hectare absorbed 70% more Zn in comparison with T1 treatment (testified). Although T6 and T7 show approximately similar Zn concentration but the effects more evident in T7 treatment. The differences on Zn absorption of T2-T5 treatments with testified treatment are not significant. In other words those treatments show similar effects under different fertilizing patterns. The reason for increasing Zn within aerial part of plant tissues due to application of different level of B can be related to more root development and facilitating absorption of this element from the soil. 3.4. 3 - Effects of manure and B application on B in plant tissue The results in Table.3 and Fig.5 indicate that the T7 treatment captured 300% more Bcompared with testified treatment. This difference is significant within 0.01 confidence level. Statistical analysis also shows that other treatments except T2 and T3 have demonstrated significant differences considering B concentration in plant tissues. Based on elaboration of measurements and from the view point of B absorption the treatments can be ranked as follows: T7> T6> T5> T4> T3= T2 > T1.


The increasing of B concentration under different level of boron application is not unpredictable. In fact the increase of B concentration in the soil plant should be responded by absorption of more amounts of this element. 3.5. - Effects of manure and B application on Alfalfa yield The results of this study show substantial differences of alfalfa yield under different fertilization patterns. Yield data in table. 4 and Fig. 6 show that application of manure and different dosage of boron has significant changes on Alfalfa yield within 0.01-confidence level.Statistical comparison of 7 treatments shows that the yield of T6 treatment has increased 150% compared with testified treatment. As it can be seen from Fig.6 the yield improvement of this treatment also is statistically significant comparing other treatments. The effect of other treatments on alfalfa yield is in such way that except T7 and T4 other treatments demonstrated significant and noticeable improvement. The yield Improvement of T2, T3, T4,T5, T6 and T7 are 121, 92,73,25,155,86 percent respectively. The reduction of yield improvement in T7 treatments is due to the increase of B within plant tissues and passing the toxicity level of this element for alfalfa. Since the zone between toxicity and adequacy is narrow [5] the increase of B concentration from 94.67 to 110 mg/kg caused boron toxic and decreased the yield. The yield improvement in T2-T6 can be related to the increase of B concentration in the soil thus facilitating its absorption by plant and expediting of cell division in aerial parts of plant and more root development comparing testified treatment. Moreover the yield improvement can also be explained considering augmentation of the concentration of other elements such as Ca, P, Zn and Cu in the soil and plant tissues. Finally it can be concluded that the concentration increase of this element improves the efficiency of plant nutrition and metabolism and it is reflected as yield improvement. These results and conclusions are in agreement with previous reported researches by Li.Y and Liang 1997[3].

References:1- Albert. L .S, (1965). Ribonucleic acid content, boron defficiency system and elongation of tomato root tipe, Plant physi, 40 ( 649 – 652 ) 2- Le Noble. N ,D. G. Blevins, and R. J. Miles, (1996) Prevention of alluminiom toxcicity with supplemental boron. II. Stimulation of root growth in an acidic high allominium subsoil, plant cell enviroment, 19 ( 1143 – 1148)

3- Li. Y. and H. Liang, (1999) Soil boron content and the effect of boron application on yield of Maize, Soybean, Rice and sugerbeet in heilongjiang province P. R. China, in boron in soil and plants. Ed. By. Bell and Rerkasem Academic publisher ( 17 – 21).

4- Marschner, h., (1995) Mineral nutrition of higher plant, Second ed., (381-395). 5- Porard. A. S, A. K. J. Parr, and B. C. Loughman, (1977). Boron in relation to membrance function in hihgher plants, J. Eup. Bot., 28 ( 831 – 841).

6- Ramon. A. M, A. Carpena-Ruiz, and A. Garate. (1990) The effect of short term dificiency of boron on potassium, calsium and magnesium distribution in leavs and roots of tomato plants.

Plant Nutrition-Physiology and Application Kluwer Academic( 287 – 290). 7- Tisdale. S. L, W. L. Nelson, and S. D. Beaton, (1985) Soil fertility and fertilizer, Forth ed

Maemillan Publishing Company, New York,


Table. 1. Physical and chemical properties of soils in experimental field.

TextureClay %

Silt%

Sand %

O.C%T.N.VPH

Ece ds/mDepth

cm

Silty clay loam 3745180.50739.57.70.440-30

Silty clay4140190.497437.750.5330-60

Bppm

Cu ppm

Mn ppm

Zn ppm

Fe ppm

Mgmeq/L

Cameq/L

K avappm

P avappm

N Total

%Depth

cm

0.720.492.980.725.74.72.640218.20.0530-30

0.690.432.50.675.24.62.4406.6160.05130-60

Table.2. Average square effects of effects of manure and different level of B application P, N, Ca and Mg in Alfalfa crop

Average squares MgCaKPN

source

0.002

0.103

0.054

0.044*0.156Replication

0.027

0.406*

*

0.275

0.033*0.132Treatment

0.011

0.036

0.249

0.0080.054Error

16.64

6.75

11.81

22.087.41Variations coefficient

%

(*)5% and (**)1% confidence levels Table.4 Average square effects of manure and different level of boron on Alfalfa yield

Average squaresYeild

Source

1215.47Replication476532.93Treatment

1441.86Error

2.83Variation coefficient

Table.3 Average square effects of manure and different level of boron on


Cu, Fe, Zn, Mg and B in plant tissues Mean squares

BMnZnCuFeSource

3.18389.1970.572.7688706.4Replication 28.1818**61.13826.56**21.602**3166.5Treatments

42.755102.542.5752.335827.4Error

10.239.998.968.720.06Variations coefficient %

0

0.1

0.2

0.3

0.4

0.5

0.6

T1 T2 T3 T4 T5 T6 T7

Treatment

P (

% )

c

abc

c

bcabc

a ab

Figure 1. The effect of manure and different B levels on P concentration in Alfalfa

Treatments

0.5

Ca

( %

)

cc

b b

ab a

T1 T2 T3 T4 T5 T6 T70.0

1.0

1.5

2.0

2.5

3.0

3.5

c

Figure 2. The effect of manure and different B levels on Ca concentration in Alfalfa

0

5

10

15

20

25

Treatments

Cu

( m

g/kg

)

T1 T2 T3 T4 T5 T6 T7

bb b

a a a

b

Figure 3. The effect of manure and different B levels on Cuconcentration in Alfalfa


Treatments

Zn

(mg/

Kg

)

T1 T2 T3 T4 T5 T6 T70

5

10

15

20

25

bc

cbc

bc

aba

c

Figure 4. The effect of manure and different B levels on Zn concentration in Alfalfa

0

500

1000

1500

2000

Yie

ld (

Kg/

ha )

T1 T2 T3 T4 T5 T6 T7

e

dc

b

a

c

f

Treatments

Figure 6. The effect of manure and different B levels on Alfalfa yield per heater

Treatments

0

20

40

60

80

100

120

B (

mg/

kg )

T1 T2 T3 T4 T5 T6 T7

efe

d

c

b

a

f

Figure 5. The effect of manure and different B levels on B concentration in Alfalfa


Dams and Development in Iran and The Main Concerns

Rohollah Fatahi Nafchi1

Assistant Prof. Sharekord University, [email protected].

Abstract Land and water development in Iran is required to take care of the population pressures and the poverty level of society. As development reduces the poverty level and improves the standard of living mainly by providing employment generation, this in itself has positive effects. While large quantities of fresh water are yet flowing to seas through rivers, scarcity is engulfing many parts of the country. Dozen of dams are still to be built to store water and make it available, during the next century across the country. As a conclusion, it is stressed that dams have played and will continue to play an important role in the development of water resources, in developing countries. In order to develop and operate successful projects, a balance has to be struck between the requirements based on the needs of society, acceptable side effects and a sustainable environment.

Key words: dam, development, flood, sustainability, rivers, reservoirs, water

Introduction Although dams have been built in Iran during the past decades, large dam construction was not possible though needed, earlier because of lack of adequate design knowledge, construction equipment, and technology of construction. Also, economic conditions and institutional capacity existing in country did not enable authorities to take them up. The large dam construction became possible during the last two decades mainly because of advances made in science and technology, which enabled mechanization of construction processes and speedier construction. Improved design procedures and new construction materials enabled the design of larger dams and their components to take on much higher loads and stresses. Large dams, distinct from smaller ones, enable larger storage of water at suitable places, thus saving on multiplicity of efforts, which would be needed to construct several smaller ones. Larger water reservoirs were also found to be necessary by the society in response to the needs of the growing urban and industrial centers, generation of hydropower and for agricultural support as well. Land and water development in Iran is required to take care of the population pressures and the poverty level of society. As development reduces the poverty level and improves the standard of living mainly by providing employment generation, this in itself has positive effects. While adverse impacts of a dam can be taken care of, the availability of freshwater on the other hand reduces environmental degradation. The positive impacts on environment are manifold. In absence of a dam or a water withdrawing facility, the environmental degradation continues unabated especially in less developed regions because of population pressures. Dams have played and will continue to play an important role in the development of water resources in Iran. In order to develop and operate successful projects, a balance has to be struck between the requirements based on the needs of society, acceptable side effects and a sustainable environment.1. Dam as a tool for development The large dams enable harnessing of large water resources potentials, where and when available, to meet needs of fast growing society across the country: food, energy, industry, drinking water, sanitation, fish production, and others [21,22]. After several years of evolving dam construction activity, even today’s needs are far from satisfied in many part of the country. The people of the country comprising, farmers who grow food; industries, municipal institutions who use water stored behind the dams, besides the governments who promote water resources development are major stakeholders in dams which have been so far


built. The need for more dams, especially in populated regions of the country, is still enormous. Societies for whom these dams are crucial for existence have therefore to be considered as the most important stakeholders. The welfare of the people and preservation of nature are at the heart of concerns [14,24]. Dams of all sizes - small, medium and large are an essential component of overall and integrated water management systems. They divert water, they retain it over long periods of time to use it effectively and they attenuate floods and alleviate impacts of droughts. They relieve drainage congestion, and they provide for the timely and continuous supply of irrigation water needed to meet the demands of crops and livestock. Existing and new dams will continue to play a major role in the management systems. There are people and organizations who feel strongly that not enough is being done by governments and society while building dams to mitigate their hardships and conserve or improve the environment and ecology. The affected people, undoubtedly, have to be considered major stakeholders along with those who are benefited from the dams. 2. Some contradictory aspects of dams: A major portion of water stored behind dams in the world is withdrawn for irrigation that mostly comprises consumptive use, that is, evapotranspiration (ET) needs of irrigated crops and plantations. On the submerged land, there are often possibilities for seasonal irrigation [6,7,10,16]. A much smaller portion of storage is withdrawn from reservoirs and supplied for drinking, municipal and industrial purposes, hydropower generation, etc. Of this withdrawal, only a very small portion is consumed by evapotranspiration. A larger portion is not consumed and is returned to the system. Drinking water requirement is given top priority by most of the countries in their policy documents. Similarly, use of stored or diverted waters for hydropower generation is considered most Eco-friendly, because of its non-consumptive nature and because the resource is renewable and can be used again and again in the downstream for power generation [1,4]. The total quantum of flow and size and frequency of peak floods in the flood season reduce in the downstream due to a dam, reducing flood hazard due to inundation of land, crop and property which might result into economic upheavals. It also reduces congestion of runoff in plains and coastal lands. Intensive economic developments have been realized, in the several areas, only because of flood protection by the dams [12,15,17]. Every dam causes partly temporary and partly permanent submergence of land in the upstream and displacement of resident persons and their property generally, along-with submergence of plant life and disruption to animal life [8,16,18]. As reservoir levels recede, the submerged land - rich with fertile soil and silt deposits can produce valuable crops. Also downstream of dams, such effects are caused by ancillary facilities on a similar but much smaller scale. The consequent social and economic loss is generally assessed and compared with benefits due to the dam. The downstream uses are met with mostly from flow by gravity or regulated releases into the river, whereas in the upstream, lifting of water is involved. All these advantages and disadvantages have to be assessed in advance to plan ameliorative measures. During implementation of the plan and during operation, each disadvantage calls for careful management and monitoring. 3. The Size Of Dams Under what situations large reservoirs are necessary and feasible for promoting irrigation, drainage or flood control vary according to agro-climatic setting. All dams store behind them floodwaters, primarily for the benefit of human beings. Large dams defines as those more than 15 m in height, while including smaller dams up to 10 m height as well, if they are otherwise significant with respect to storage volume, density of population, etc. Due to the effects of scale the larger a dam is, the lower will be the cost of a unit of water stored.


The choice of large or small dams and location for each dam depends on several factors including technical feasibility, location of water deficit regions that need to be serviced and alternatives available for the purpose [10,21]. Besides, the balance of advantages and disadvantages due to a particular dam in socio-economic and environmental aspects helps in decision making. Not all the water stored behind dams is withdrawn for use. A top depth varying from 1 to 2 meters depending on local climate, is annually lost to atmosphere due to evaporation. At the bottom, some depth serves as a dead storage for accommodating sediment brought in by inflow. Similarly some silt does accumulate in higher reaches where inflows merge into the reservoir periphery, gradually building up small deltas of sediment. Gated crests obviate this loss of storage to a significant extent by allowing opening of gates when inflows contain higher levels of sediment. The remaining volume minus the seepage from the bed of the reservoir and that across the dam foundation and body is available for transport and supply for different beneficial uses. Dead storage size depends upon the catchment area characteristics but similar to evaporation losses, tends to be proportionately more in case of a smaller dam. 4. Sustainability of Development due to dams The subject of sustainability of development has been extensively debated over the last two decades. Dams have solved many problems of communities served and have provided basis for economic development that has sustained itself. Employment opportunities have been generated, incidence of poverty has been reduced, rural population including nomads has been stabilized locally and migration of rural unemployed population to urban centers has been reversed. Food security to ever growing population, protection from floods and droughts to chronically vulnerable areas and generation of the cleanest form of energy, namely hydropower, are some other benefits of water resources development. Many urban and industrial centers have been provided with water supply for consumption and transport of waste for treatment. Gated reservoirs provide for less submergence in totality of long term sustainability of the irrigation service by avoiding excessive silting above the crest of the spillway. A substantial part of that storage quantity stands almost perpetually guaranteed. Navigation, fishery, irrigated forestry, recreation and leisure are some other obvious benefits. The overall development due to dams is there for everybody to see. Benefits, costs and risks undoubtedly increase with size of a dam. Efforts are made by dam planners to maximize benefits, minimize costs and build in defensive measures in dam components to take care of risks by deploying appropriate technology and design features. Incidents involving dam failures are decreasing from decade to decade and the safety record is likely to be better than in many other sectors of infrastructure development. Dam safety concerns and policies have been incorporated in dam engineering from concept to O&M stage and this has shown positive effects on the performance of dams. Thus, structural safety of high dams is no longer a real concern [1,5,9,13]. 5. Assessment of options and decision-making framework Sustainability has become the touchstone for development effort since last decade. Although its definition has had different connotations for various development sectors, it means that fruits of development ought to be of sustained nature to meet needs of future generations as well, and should not be of transient nature to address only present day concerns. Recently, the following definition of Integrated Water Resources Management has came up, ”a process which aims to ensure the co-ordinates development and management of water, land and related resources to maximize social and economic welfare without compromising the sustainability of vital ecosystems”[21,22]. Appropriate policies and guidelines also on sustainability aspects of dams need to be fully developed, and where developed they need to be uniformly applied. Basically dams stores flood runoff of the rivers and make the storage available for withdrawal to meet with


beneficial needs. Within the range of variability of availability, appropriate withdrawals are designed to import sustained supplies and hence sustained productivity. The waters of a basin thus get redistributed at minimum economic cost and hence ensure sustenance of the source as well as fruits for development. Micro-development schemes ought to be considered and conceptually developed for areas that will remain rain feed as part of an integrated evaluation process that progresses toward an optimized river basin development scheme. It is considered to be shortsightedness, as also inappropriate, to reject large dams, or any other component of a proposed river basin development scheme without even-handed and comprehensive analyses of overall relevant social, economic and environmental considerations [7,16]. Socio-economic impacts of large dams and alternatives of micro river basin development have to be studied extensively. As mentioned earlier, the larger a facility, the benefits, costs, and risks are usually larger. But while planning a facility, effort is made for maximizing benefits and minimizing costs and risks. A view is taken, on the balance, of advantages to the community. The benefit cost (BC) analysis has to include social benefit-and cost streams to expand it to Social Benefit Cost Analysis (SBCA). It is difficult to accurately quantify secondary and incidental benefits and costs. The SBCA essentially helps a planner to priorities projects for implementation besides improving dimensioning of a scheme and selection of the best alternative [13,14,23]. For many parts of the country, all the planned storage facilities are required and still the level of water supply may remain short of their ultimate requirements. In such cases, the BC analysis does not help beyond prioritization in face of resource crunch, because even the most expensive facility may have to be put in place to meet the needs of society. A sovereign country no doubt will preserve its basic right of deciding its own priority of developmental needs and most suited options. Water resources development and utilization is of utmost importance for the socio-economic uplift, poverty alleviation programs and food security. 6. Adverse impacts with and without a dam Land and water development in Iran is required to take care of the population pressures and the poverty level of society. As development reduces the poverty level and improves the standard of living mainly by providing employment generation, this in itself has positive effects. While adverse impacts of a dam can be taken care of, the availability of freshwater on the other hand reduces environmental degradation. The positive impacts on environment are manifold. In absence of a dam or a water withdrawing facility, the environmental degradation continues unabated especially in less developed regions because of population pressures. Environmental impact studies therefore have to be carried out for both, with and without dam scenarios. The environmental cost of constructing a dam is normally smaller than that in a situation without the dam, if the continued degradation in absence of a dam due to poverty and population pressures during the life of the dam, is considered. It is often to be concluded that the environmental cost of building and using a dam in a developing country is smaller than that of not doing that dam project. The extent of submergence and evaporation loss from a large storage project is lesser than that from a series of equivalent small storage projects.Apart from assessment of adverse impacts with and without a dam, it is sometimes required to carry out the assessment for situations before and after completion of a dam project as one time exercise. Both assessments are important as they provide important insight into the environmental concerns and their containment. 7. Compensation For Affected Population The adversely affected people due to a dam comprise those who are displaced due to inundation in the reservoir or due to ancillary structures. Some people dependent on those displaced are also incidentally affected. Some farms develop water logging due to canal


waters and the concerned farmers are also affected. These people have to be rehabilitated and resettled with due compensation and recognition for their sacrifice. Such rehabilitation and resettlement effected in their consultation and with their consent can also include partnership and ownership in the facilities and provide them economic benefits flowing from the water resources development. Very liberal policies/guidelines have been framed by several developing countries which provide for appropriate compensation measures for the project affected population[17, 24]. 8. Effectiveness of Dams For Development Large or small dams, if built without adequate preparatory work, can fail to deliver expected results. Any dam could thus prove less effective than planned. It is therefore necessary to select cases of success or failure of both large and small dams. Lessons are to be drawn from failures to guide future action. If a new dam is identified, a benchmark status if not available at the time of construction, might have to be ascertained to realistically assess its effectiveness. Where much depends on how the delivery system is operated, the dam is hardly the reason for any loss of efficiency. Greater attention is necessary in the irrigation sector to bring about and maintain perfection in the delivery systems. Reservoirs of various magnitudes are a requirement for practically whole of the country and dams of various sizes fulfill that necessity. It is therefore, imperative that such a development process is supported by effective procedures to minimize negative effects, if any, and enhance benefits. Large dams contribute significantly to the productive efficiency of irrigation, in addition to giving ancillary and intangible benefits. The large dams built in the past have provided water supplies to needy areas for growing food, for drinking water, for reducing flooding, and for generation of hydropower at lowest of costs from amongst various options. Smaller a dam, more is the cost per unit of water stored, but every size has its role in development of basin resources. They are complementary to each other. They cannot replace each other.

ConclusionWhile large quantities of fresh water are yet flowing to seas through rivers, scarcity is engulfing many parts of the country. Dozen of dams are still to be built to store water and make it available, during the next century across the country. The needs of growing populations, the pace of urbanization and industrialization, and the urgent need to improve the standard and quality of life of poorer strata of the society calls for urgent steps to build these facilities. It is an enormous challenge to decision-makers, developers and designers to develop economically required capacity in an environmentally sound and sustainable way. One principle that ought to be followed is that all those who are benefited or who are adversely affected by dam projects are made stakeholders of the project so that they get a share in the benefits equitably. The standard of living and quality of life of those adversely affected due to a dam, should be brought up to a level higher than what it was prior to the dam project. Risks to the structure due to deficiency in planning, implementation or natural hazards have to be evaluated and integrated in the cost streams, which should include ample defensive and mitigation measures. They have to be appropriately worked out and provided in the overall planning of the area. An appropriate assessment of the status of society with and without dams has therefore to be made, according to already well defined assessment procedures whose implementation has to be pursued by all responsible segments of society. As a conclusion, it is stressed that dams have played and will continue to play an important role in the development of water resources, in developing countries. In order to develop and operate successful projects, a balance has to be struck between the requirements based on the needs of society, acceptable side effects and a sustainable environment.


References: 1. Baxter, R.M. (1977) Environmental effects of dams and impoundments. Annual Review of Ecology and Systematics 8: 255-283. 2. Dez Irrigation Project Stage 1 Feasibility Report Supplement (D & R) September 1968 3. Gleick, P. (1993) Water in crisis. (A guide to the world’s fresh water resources). Oxford University Press, New York, USA. 4. Goldemberg, J.,(1995) Energy needs in developing countries and sustainability. Science. 5. Goodland, R., (1993) Environmental sustainability in energy systems. International Journal on Sustainable Development.1( 4). 6. Goodland, R., (1995) The Big dam controversy: killing hydro projects promotes coal and nukes. GTE-Technology and Ethics Series, Michigan Technological University. Houghton, MI, USA,. 7. Goodland, R., (1996) The environmental sustainability challenge for the hydro industry. International Journal on Hydropower & Dams, 1(1). 8. Gupta, P.N. and Le Moigne, G., (1996) The World Bank’s approach to environmentally sustainable dam projects. International Journal on Hydropower & Dams. 3(5) 9. Gupta, P.N.,(1996) Dams and development and experience of the World Bank in implementation of dams safety. International Symposium on Safety of Dams. INCOLD, Trivandrum, India,. 10. Gupta, P.N.,(1995) Environmentally sustainable dam projects and experience of World Bank in dams safety. Conference on Geotechnical Engineering in the Infrastructure Improvements and Dams. Hershey Park, Pennsylvania, USA,. 11. Long Term Operation and Capabilities of Dez Dam and Reservoir on The Dez River in Khuzestan July 1971 (KWP). 12. Moog, O. (1993) Quantification of daily peak hydropower effects on aquatic fauna and management to minimize environmental impacts. Regulated Rivers: Researchand Management 8: 5-14.13. Rosenberg, D.M., et.all.(1997) Large-scale impacts of hydroelectric development. Environment Research 5: 27-54. 14. Rosenberg, D.M., R.A. Bodaly & P.J. Usher. (1995) Environmental and social impacts of large scale hydroelectric development: who is listening? Global Environmental Change 5: 127-148. 15. Rozengurt, M.A. & J.W. Hedgpeth. (1989) The impact of altered river flow on the ecosystem of the Caspian Sea. Reviews in Aquatic Science 1: 337-362. 16. Shuman, J.R. (1995) Environmental considerations for assessing dam removal alternatives for river restoration. Regulated Rivers: Research and Management 11: 249-261. 17. Sklar, L. and McCully, P., (1994) Damming the Rivers. Working Paper No. 5, International Rivers Network, California, USA,. 18. Stanley, D.G. & A.G. Warne. (1993) Nile delta: recent geological evolution and human impact. Science (Washington, D.C.) 260: 628-634. 19. The unified development Of the Natural Resources Of the Khuzestan Region (D & R) March 195920. Varma, C.V.J., (1996) The Role of hydro in future power scenario and the need for accelerated development. India Power. 21. Veltrop, J.A., (1996) Future challenges in the sustainable use of water resources. International Journal of Hydropower & Dams; Issue One,. 22. Veltrop, J.A., (1995) River Basins and Sustainable Use of Water Resources: A Challenge, Also for ICOLD. USCOLD ,No. 107,. 23. Volovik, S.P. (1994) The effects of environmental changes caused by human activities on the biological communities of the River Don (Azov Sea Basin). Water, Science and Technology. 29: 43-47.24. White, G.F. (1988) The environmental effects of the High Dam at Aswan. Environment 30: 5-11, 34-40.


An Experimental Study of Soil-gravel Interface Hydraulic Gradient

R.Fatahi Nafchi1

1- Assistant prof. Shahrekord University, e-mail:[email protected]

Abstract When water nears the drain-pipes covered by the gravel envelope abrupt transition occurs when water flows from a medium of relatively low hydraulic conductivity (soil) into a region of much higher conductivity, at the soil-gravel interface. To better understand the nature of this phenomenon, an upward-flow permeameter test apparatus was designed. The data from permeameter measurements in this study suggest that water leaving the soil and entering a perforated pipe or very permeable pipe envelope demonstrates an excess energy loss, the effects of which are evident not only at the interface itself, but which project into the soil away from the interface.

Keywords: Drain, Gravel, Envelope, entrance resistance, Porous media.

Introduction The first layer placed around the drain pipes, the gravel envelope, is a layer of porous material which performs one or more of the following functions[4,7,11]: Soil retention function: to provide mechanical support or restraint of the soil, to prevent or limit the movement of soil particles into the perforated pipe where they may settle and eventually clog the pipe (or, in some cases, changes the water quality). Hydraulic function: to provide a porous medium of relatively high permeability around the pipe and thus reduce entrance resistance at, or near, the pipe perforations. Mechanical function: to provide passive mechanical support to the pipe, providing a stable base to support it. When water nears the drain-pipes covered by the gravel envelope, the flow is approximately radial [1,3,8]. Convergence of the streamlines results in a piezometric head-loss in addition to that, which would occur if the flow paths were parallel. Further head loss results from the fact that the streamlines converge toward a finite number of perforations, and also from the abrupt transition which occurs when water flows from a medium of relatively low hydraulic conductivity (soil) into a region of much higher conductivity, at the soil-gravel interface [2,6,9,13]. Several studies have been published where the entrance-resistance factor for various types of drainage pipes has been determined experimentally, or by analytical and numerical solutions to the equations governing flow to the drain openings (5, 10,12). The objective of this study was the investigation of the effect of the soil-gravel interface; a series of laboratory experiments on this aspect were carried out. To better understand the nature of this phenomenon, an upward-flow permeameter test apparatus was designed. This apparatus allowed various materials for both envelope and base soil to be tested in different combinations, and the effect of the soil-gravel interface to be determined. The measurements and results of this series of investigations are presented in this paper. Material and Methods The test apparatus was a permeameter, designed to simulate the condition in which water flows vertically upward into the soil and then into the several envelope materials. To adequately study the situation the soil and gravel column had to be high enough to permit observation of the transition from the constant hydraulic gradient characteristic of uniform flow through a porous medium to the steeper gradient characteristic of flow across the interface between two dissimilar media.


The permeameter column was made of clear Plexiglas with an internal diameter of 195 mm, and was 600 mm high (Fig. 1). At nine selected levels piezometric taps were inserted through the column wall. From one to three piezometers were placed at each measurement level, with the number of piezometers at any level being determined by the difficulty of obtaining precise information at that level. For example, only one piezometer was used to measure piezometric head at the inflow, because this reading was not subject to error. Three piezometers were inserted in the levels near the interface and near to the mid-point of the cylinder. The length of piezometric taps, where only one piezometer was used, was chosen to ensure that the measurement point was far away from the permeameter wall (75 mm). The vertical distances, number of taps, and the tap lengths for each level are given in Table.1. The porous base materials selected for use in this study were three types of sand with different particle size. The mean particle diameter was, respectively, 1.62 mm (Cs, coarse sand), 1.14 mm (Ms, medium sand) and 0.63 mm (Fs, fine sand); the gradation curves for the selected base materials are shown in Fig .2.The envelope materials selected for study were three types of gravel with mean particle diameter of, respectively, 10.14 mm (Cg, coarse gravel), 6.3 mm (Mg, medium gravel) and 3.29mm (Fg, fine gravel); the gradation curves for three envelope materials are shown in Fig. 3. As can be seen from Figs. 2 and 3 both the sand and the gravel samples were approximately uniform in particle size. In the apparatus, upward flow is applied, the piezometric head of which is controlled by an adjustable head-supply pot. At the top of the column a downward force is applied via a perforated disk with a fine screen supported by five legs pushing down the sand and gravel. Thus it is assured that even if sand migrates through the gravel envelope and top perforated plate, the sand and gravel remain firmly compressed. Moreover, the fine metal screen used below the top plate minimizes such migration. Water manometers connected to the piezometric board measure the piezometric head of water flowing at the different levels.Each test was begun with the apparatus loaded entirely with the selected type of sand without gravel. Time, temperature and flow rate readings were taken and the piezometric elevations were recorded. After the first set of readings had been recorded, the flow rate through the sample was slowly increased, the piezometers were allowed a period of at least one hour to reach equilibrium and a new set of readings was taken at the higher flow rate. This sequence was continued until maximum flow was attained. In the next phase of the experiment all material above the piezometers at level 6 was carefully removed, and replaced by a sample of gravel. The detailed procedure was as follows. First the flow rate through the sample was reduced so that, while the direction of the flow remained unchanged, the velocity was so low as to pose no risk to the structure of the sample. The second step was to remove the top plate and the material above the piezometers at level 6 and replace the gravel from level 7 up to level 9 (total 106 mm thickness). A new series of readings was then taken, using the permeameter loaded with the new combination of sand and gravel. Results and Discussion Table. 2 shows the values of hydraulic gradient measured between the piezometers at levels 1 and 6, for selected flow rates used in experiments. These flow rates were selected from the measured data, or in some cases using interpolation. The three respective values chosen are, representative flow rates for all 5 tests in each group. Table.2 is arranged in three horizontal blocks, one for each of the sand samples used as base material. Each block contains four rows. The first row shows the results with the permeameter filled entirely with sand; the other three rows show the results with water passed through the undisturbed sand in the lower part, then through the upper gravel layer (between piezometers level 6-9, Fig.1). Because of variation in the packing density of the sand within the permeameter column, hydraulic gradients for a given flow-rate vary somewhat between different pairs of adjacent piezometer levels. The permeameter was designed with the


intention that the piezometric head loss of the flow through the sand-gravel interface could be measured directly by using the piezometers at levels 6 and 7 in the (Fig.1). Measurements however, showed that the magnitude of the piezometric head loss between these two closely-spaced positions was small and unpredictable, and was affected by mixing of the two materials on both sides of the nominal interface. However, there is a significant head drop (high hydraulic gradient) near the interface region. The important information in Table.2 comes from comparing the gradients recorded for “homogenous” and “non-homogenous” sets of readings. Beginning near the bottom of the permeameter, in the zone between piezometer levels 1-2, 2-3, 3-4, (columns 4, 5 and 6 in the Table. 2) gradients observed for “non-homogenous” sets are almost identical to those observed for “homogenous” sets. From the zone between piezometer levels 4-5 upward (columns 7 and 8 in the Table. 2), gradients recorded for the “non-homogenous” sets were higher than those recorded for “homogenous” sets. The difference between the measured gradients depends on the difference between the two materials in the lower and upper parts of the column. These hydraulic gradient differences are much more pronounced for the last block of Table.2, where fine sand was the base material. In order to elucidate the effect of the gradual transition found in the practical situation, further experiments are required with more closely spaced piezometers in the transition region on the low-conductivity (soil or sand) side of the interface. The principal conclusion drawn from these experiments is that the piezometric head loss for water-flow in soil is greater at interfaces, and it depends on the ratio between the grain sizes of the soil and the gravel materials. Water leaving the soil and entering a very permeable envelope demonstrates an excess energy loss, the effect of which is measurable in the soil further back from the interface as is seen in the last column of Table. 2. Conclusions The data from permeameter measurements in this study suggest that water leaving the soil and entering very permeable pipe envelope demonstrates an excess energy loss, the effects of which are evident not only at the interface itself, but which project into the soil away from the interface. A practical consequence of this phenomenon is that high hydraulic gradients at the interface of a porous medium may mean that hydraulic failure gradients (leading to destructive changes in the filtering layer) can occur under flow conditions that would theoretically be stable. More experiments are needed to determine the extent of the affected region in the soil away from the interface. While the flow direction from soil to gravel envelope in the case of perforated pipe systems is downward and the gravity plays an important role in the flow domain therefore it is suggested to arrange a downward flow permeameter to simulate the conditions. However in field drainage, the actual movement of ground water into the drains is primarily through the bottom and sides of the drain or drain envelope, therefore the results of this investigation are partly valid for field drainage. While the results of this study do not constitute an analysis of the hydrodynamics of the flow in porous media, they do suggest that the practical questions about the mechanics of porous media flow can be answered by studying in detail the case of flow across interfaces.

References [1] Bonnel, R.B., Broughton, R.S., Bolduc, G.F. 1986: Hydraulic Failure of the Soil-Drain Envelope Interface of Subsurface Drains, Canadian Water Resources Journal. Vol., 11, No 3., pp. 24-34.[2] Davenport, M. S., Skaggs, R. W. 1990: Effects of Drain slope and Envelope on Performance of Drainage-Subirrigation Systems, Trans. ASAE, 32(2), pp. 493-500. [3] Dierickx, W. 1980: Electronic Analogue Study of The Effect of Opening and Surrounds of Various Permeabilities on The Performance of Field Drainage Pipes. Commun. Nat. Inst. Agric. Engrg. Merelbeke, Belgium, 77.


[4] Dierickx, W. 1993: Research and Developments in Selecting Drainage Materials. Irrigation and Drainage Systems, Vol. 6, No 4, pp. 291-310. [5] Fatahi, R. 2000: A Complex Discharge Factor for Perforation Covered with Gravel Envelope in Perforated pipe Systems, 4th International Conference on Water Supply and Water quality, Krakow, Poland, September 2000. [6] Leatherwood, F. N., Peterson, D. F. 1954: Hydraulic Head Loss at the Interface Between Uniform Sands of Different Sizes, ASCE, Vol.35, pp. 165-169. [7] Lennoz-Gratin, C. 1989: Effect of Envelope on Flow Patterns Near Drain Pipes, J. Irrig. Drain., ASCE, Vol. 115, No.4, pp. 626-641. [8] Miller, D. W. 1981: Head Loss Across Soil-Envelope Interfaces, Thesis Presented to Utah State University, at Logan, in partial fulfillment of the requirements for the degree of Master of Science.[9] Miller, D. W., and L. S. Willardson 1983: Head Loss at Soil-Drain Envelope Interfaces, J. Irrig. Drian., ASCE, Vol. 109, No. 2, pp.211-220. [10] Mohammad, F. S., R. W. Skaggs. 1984: Drain Tube Opening Effects on Drain Inflow, J. Irrig. Drain., ASCE, 109(4), pp. 333-403. [11] Samani, Z. A., Willardson, L. S. 1981: Soil Hydraulic Stability in a Subsurface Drainage System, Transaction, American Society of Agricultural Engineers, Vol. 24, No. 3, pp. 666-669. [12] Skaggs, R. W. 1978: Effect of Drain Tube Openings on Water Table Drawdown, J. Irrig. Drain., ASCE, 104(1), pp. 13-21.

Table ....1. Details of piezometric taps at each level in the permeameter column (see Fig.1)

Level 1 2 3 4 5 6 7 8 9Intervals 1-2 2-3 3-4 4-5 5-6 6-7 7-8 8-9 --

Distance (mm) 41.8 41.3 92 82.5 75.2 16.4 42.9 41.2 --

Number of taps

1 1 3 1 1 3 3 1 1

taps length (mm)

32.5 75 95,75,32.5 95 75 95,75,

32.595,75,

32.5 32.5 32.5


Table.2. Hydraulic gradients between piezometer locations for selected flow rates Hydraulic gradient for piezometer position*Flow rate

(cm3/s)(1)

material codes

(2)

Gravel-soil ratio dG/dS

(3)1-2(4)

2-3(5)

3-4(6)

4-5(7)

5-6(8)

Base material coarse sand (dm= 1.62mm)Cs No gravel 0.49 0.51 0.51 0.50 0.51

Cs-Cg 6.25 0.44 0.45 0.45 0.46 0.50Cs-Mg 3.88 0.43 0.44 0.44 0.45 0.50

80

Cs-Fg 2.03 0.49 0.45 0.46 0.43 0.48Base material medium sand (dm= 1.14 mm)

Ms No gravel 0.67 0.68 0.68 0.69 0.68Ms-Cg 8.89 0.65 0.65 0.66 0.67 0.78Ms-Mg 5.52 0.66 0.67 0.70 0.73 0.78

80

Ms-Fg 2.88 0.63 0.64 0.65 0.69 0.71Base material fine sand (dm=0.36 mm)

Fs No gravel 1.64 1.74 1.79 1.77 1.75Fs-Cg 16.09 1.61 1.61 1.74 1.80 2.08Fs-Mg 10 1.79 1.77 1.81 1.85 1.98

10

Fs-Fg 5.22 1.57 1.59 1.63 1.80 1.93*Note: a Hydraulic gradient between the piezometers at levels 7-8 (gravel layer) was approximately zero. For gradient between positions 6-7, see text.

1

2

7

3

4

8

5

9

6

Toward piezometric board

Soil

Gravel

Adjustable overflow pot

Flow measurement

Perforated disk

Perforateddisk

Water supply

Figure.1. Schematic diagram of permeameter


0

10

20

30

40

50

60

70

80

90

100

0.010.1110100Grain size (mm)

Per

cent

sm

alle

r %

FSMSCS

Figure.2. Grain-size distribution of sand samples

Figure.3. Grain-size distribution of gravel samples

0

10

20

30

40

50

60

70

80

90

100

0.010.1110100Grain size (mm)

Per

cent

age

smal

ler

%

FG

MG

CG


Biological Method For Controlling Gully Erosion By Using Fast Growing Species Of Salix Spp .

HOSEINPOUR, Reza1 ; GODDOUSY , Jamal2 .1_Associate members of the Natural Resources and Animal Affair Research Center Of The W .AZ Address: P. O .Box 669 Uremia – Iran / Tel No: 098 441 2777662/ Fax No: 098 441 2775430 / E-mail: [email protected] 2_ Associate members of the soil conservation and watershed Institute – Tehran_ Iran

Abstract: For studying the rate of survival and the role of fast growing species of Salix tree in controlling and improving the longitudinal profile of gullies (gully erosion) and presenting a biological method for controlling gully erosion in west Azerbaijan province and other areas with similar climates, fast growing species of Sallix ( S . Alba , S . aegyptiaca ) was used by selecting 6 gullies in a way that have enough resistance against mud runoffs in gullies in watershed baron which is located in W.notht of Iran that is called West Azerbaijan province . This was carried out with 9 repeats in each type and at the end of first year active growth period, the results were analyzed using K square and X ^ 2 analysis for survival of these two types. The results showed that in % 5 levels there are significant differences between these two types. S.alba with %78 higher survival adaptability and stability than the other type, has a significant ability in controlling and prevention of gully erosions.

Key words: Biology; Gully Erosion; Salix Spp; west Azerbaijan province

Introduction:Existence of abundant gully erosions at west Azerbaijan watersheds-Iran, which is due to overgrazing of rangeland, has decreased the plant coverage severely. This in turn has decreased water penetration into the land causing a significant reduction in fodder provision, useful dam life and soil preservation. The limited useful life, applicability and high expenses of dams increases the importance and necessity of using biological method for controlling gully erosions .In this watershed the average annual precipitation in about 542 mm.

Materials and Methods: Based on our goals and methods of the project, first a network of gullies, which had 6 sud – gullies with maximum depth of 1 meter, was selected. The natural habitat of Salix in the area and neighborhood areas of similar hypsometric and climatic condition was identified in order to provide and use the native fresh materials. Therefore, Salix Alba and Salix aegyptiaca, which can spread their roots very quickly into the soil and economically is a source of income for the local inhabitants, were selected from Uremia. At the beginning of growth season some poles of 250 to 300 cm. Long with diameters of 2.5 to 3.5 cm. And some stocks of about 150cm. long with diameters of to 2 cm. were provided. First with a slope of 3% 3 cross sections at the height of 80-100 cm. along the Gullies so these cross sectioned a pole which had been sharpened at the ends were set the sides of the Gullies so that they from a bridge from one side to the other. These would be a support, which would be planned in the bed of the Gullies and were in danger of washouts. The poles would strength the sides by rooting across the sides. Then the stock were planted in the bed in the bed of the Gullies in diagonal from perpendicular to the direction of water in 30 to 40 cm. depth. The top of stock was tied to the poles at the touching point the bark of both stock and pole was removed so that the unbarkd parts could touch each other and from a graft. To germinate young plants, such plants constructions in 18 biological structures with 9 constructions from each species mentioned with 3 repeat for each on 20th of forwarding 1374


were accomplished (figure 1). They were inspected on 10/2/74 – 1/3/740-1/4/74-10/5/74 for germination. After classifying the data collected, they were analyzed by x^ 2 test and software of Spss . The analyses showed a significant difference of five percent survival rate between two species of S.alba and S.aegyptica . The statistical variance analysis showed that the S.alba apecies at the level of five percent has 78 percent more chance of survival and stability during the first year.

Results and Analysis:Considering the results achieved from the data analysis , the chance of survival of S.alba species is greater than the chance of survival of S.aegyptiaca during the first year after plantation . This is because S.alba species is a native plant of the area of Baron water shed and naturally has grown in considerable masses inside the seasonal water paths of northern aspects. Since the stocks penetrate thirty to forty centimeters in soil inside the bed of gullies , where it is always wet during the whole year or at least during the growth season , they quickly spread there roots through the soil and create a protective network to prevent erosion , while the S.aegyptiaca species , in spite of having characteristics in commin with the S.alba and economical benefit in “ Bidmeshk” extract production and provision of plentiful pollen for honey bees , has got less chance of survival (22percent) compared to S.alba . This is because this species is not native plant of the Baron area and there is a climatic difference between its natural habitat and Baron.

References: 1 _ F.A.o .1370. Translated by A.Abassi. 2_ 1373. Consultant Bureau of Water and land . Acomperhensive survey of Boran watershed .The coordinating Bureau of forests and Pasturage of Iran. 3 _ Mansoorfar K. 1371 . Statstical methods , Tehran university. 4 _ W.S.Van krayenoord and R.l Hat . 1986 . Plant materials handbook for soil conservation , soil conservation center , Aokautere ministry of work and development , willington , 255 pp.

Figure 1


78

2222

78

0

10

20

30

40

50

60

70

80

90

1 2

surviabilityperish

Diagram 1

Table 1 :The surviablity and perish of different spiceis of different

1 2 3Gully no

Plant matter

dateSurvivalof structure 1

Survivalof structure 1








10/2/74 + + + + + + + + +

10/3/74 + + + + + + + + +

10/4/74 + + + - + + + + +

Salix alba

10/5/74 + + + - + + + + -

10/2/74 + + + + + + + + -

10/3/74 + - + + + + - + -

10/4/74 - - - - + - - + -

Salix aegyptiaca

10/5/74 - - - - + - - + -


Numerical Simulation of Barrier Slope effect on Orographic Rainfall

Dr.H.Khaleghi zavareh1, F.Mohamadi2

1-Department of Irrigation, Shahrekord University.phone: +98-311-2251294, Email:[email protected]; 2-Iranian Meteorological Organization, phone: +98-21-6004799

AbstractIn this paper a two-dimensional, time dependent and non-hydrostatic orographic rainfall Model is presented. Using a terrain-following sigma coordinate conveniently incorporates the effect of topography. Cloud physical processes included in the model are condensation, evaporation, autoconversion, accretion and terminal fall velocity of raindrops relative to the air. The model also incorporates the effects of non-uniformities in surface temperature. The model was used to study the dependence of the orographically induced cloud and rainfall on the characteristics of the mountain as well as the vertical profiles of the ambient or prevailing flow, moisture and temperature. The results show that the characteristics of orographic cloud and rainfall depend on the height of mountain ridge, steepness of its slope and the asymmetry of the mountain. A higher mountain and a steeper slope generate amore intense cloud. The asymmetry was shown in the distribution of rainfall over an asymmetrical mountain. The steeper slope received more accumulated rainfall amount.

Keywords: Orographic, model, rainfall, and simulation

Introduction The mountains with various scales on earth play very important roles in influencing and forcing atmospheric motions ranging from planetary to subsynoptic systems. In general the orographic effects can be classified as either dynamical, thermal or frictional. Mountains act as high level heat and moisture sources. During daytime upslope wind occurs due to inhomogeneous surface heating. If the upslope air is moist enough it might reach the condensation level as it rises. Thereby causing the condensation of water vapor and the subsequent formation of clouds. Depending on the stability moisture and wind field of the environmental atmosphere and the interactions between dynamical, thermodynamical and microphysical processes the clouds may develop further gaining sufficient depth and resulting in the occurrence of precipitation. It is evident that clouds are initiated by the mountain upslope wind. The local circulation was described in detail by Atkinson[1] and Burman[3]. The observed features of this circulation have been studied by means of models [2,6,7,8] to simulate the mesoscale surface wind. The results of both observational and modeling studies have helped to understand mechanisms of initiation and development of terrain induced cloudiness and rainfall. These studies indicate that: at daytime due to inhomogeneous surface heating the upslope winds will be observed over mountains. A low level convergence zone exists due to the interaction of environmental wind and upslope wind. It is established that the horizontal distribution of rainfall is closely associated with topography due to orographic lifting. Several investigators have studied the relationship between rainfall and surface convergence zone. Ulanski and Garstang [9] showed that the rainfall amount was proportional to the horizontal gradient and to the horizontal area covered by the surface convergence zone. Chen and Orville [4] found that clouds, which formed in runs with convergence, have deeper and broader features than clouds formed in runs without convergence.


FORMULATION OF NUMERICAL MODELS

This model is tow dimensional with a terrain following coordinate in the vertical (σ) and the usual horizontal coordinate x. The vertical “sigma” coordinate is defined as:

Where z is the height of a grid point, H is height of the top of domain and h (x) is height of the terrain varying along x.

1.1. The Hydrodynamical Equations

1.1.1. Continuity Equation of Air The equation of continuity for incompressible fluid adopted in sigma coordinate is:

Which implies the existence of a streamfunction given by:

1.1.2. Vorticity Equation

Where: u and σ° are components of the velocity along x and σ, θv0 and θv are initial and present virtual potential temperature, l is liquid water content, ρ0 is horizontal average density of undisturbed dry air, g is gravity and:

The σ° is related to the vertical velocity in the z coordinate by the expression:

And:

)1()(

)(

xhH

xhzH

−−=σ

)2(x

h

hH

u

x

u

∂∂

−−

∂∂+

∂∂ οοο ρ

σσρρ

)3(,xhH

H

hH

Hu

∂∂

−−=

∂∂

−= ψρ

σψρ οο

( )

( ) ( ) ( ) )4(2

1

11

2

2

121

ζζσρ

ρσ

ρζσ

σρσσ

σσθθ

θνρζ

σFFuCuC

uCuCl

x

lgC

xg

dt

d

x

vv

++∂

∂

∂∂−++

∂++

∂∂−

∂∂+

∂∂

+∂

∂−= •

ο

οο

ο

οο

)5(, 21 x

h

hH

HC

hH

HC

∂∂

−−=

−= σ

[ ]xhuCwC ∂

∂−= 31οσ


The term on the left hand side of Equ.4 is total change with time of vorticity, the first term on the right hand side of equ.4 represents the buoyancy force due to the horizontal gradient of virtual potential temperature, the second term represents the buoyancy force due to horizontal gradient of liquid water, the third and fourth terms represents the effect of the variation of density (ρ0) with height and the last two terms are eddy diffusion terms along x and σ axis, respectively.

1.2. Thermodynamic Equation The thermodynamic equation is written as:

The first and second terms on the right hand side are the advection of temperature; the third is the heating rate due to condensation and evaporation of water vapor or cloud droplets and raindrops respectively. It is positive during condensation and negative during evaporation. The forth term is radiative cooling which is assumed to be 2°K/day. The last two terms are thermal eddy diffusions.

1.3. Continuity Equations of Water vapor, Cloud droplets and Radiation The water vapor mixing ratio (Qv), cloud droplets mixing ratio (QC) and raindrops mixing ratio (Qr) are predicted by the following continuity equations:

Where Lv is latent heat of evaporation, Cp is specific heat of air at constant pressure, Qv, Qc

and Qr are mixing ratio of water vapor cloud droplets and raindrops, VT is terminal velocity of raindrops, Pı, P2, P3 and P4 are microphysical processes (condensation, autoconversion from cloud droplets to raindrops evaporation of cloud droplets and rain raindrops, respectively). The value of Cp for the dry air is equal to 1004.67(m²s¯²K¯¹) while for the moist air it is computed by the following formula:

1.4. The Accumulated Rainfall The resulting orographic accumulated rainfall at the ground surface is computed by the following formulas:

)7(3 H

HC

σ−=

( ) ( ) ( )( ) )8(321 θθθσθσθθ

σν FFradPPP

C

L

xu

t xp

++−−−+∂∂−

∂∂−=

∂∂ ο

( ) ( ) ( )

( ) ( ) ( )

( ) ( )11

10

9

242

321

321

∂∂+

∂∂−−+

∂∂−

∂∂−=

∂∂

++−−+∂∂

−∂

∂−=

∂∂

++++−∂∂

−∂

∂−=

∂∂

σρ

ρσσ

σσ

σσ

σ

νσνννν

TrrT

rrr

ccxccc

x

VQ

x

QVCPP

Q

x

Qu

t

Q

QFQFPPPQ

x

Qu

t

Q

QFQFPPPQ

x

Qu

t

Q

ο

ο

ο

ο

ο

( ) ( )1284.0.1 vpdpm QCC +=

( )13tQVDR rT ∆= ορ


Where DR is the amount of rainfall reaching the ground during each time integration, RR is total accumulated rainfall (mm) and n is the number of integration. The value of Qr is the mixing ratio of raindrops reaching the ground surface at the present integration time.

2. Numerical Scheme and Boundary Conditions

2.1. Grid Domain and Numerical Scheme The domain under consideration is rectangular with 250 km in the horizontal and 10 km in the vertical direction. The mesh size is 5 km in ∆x and 0.5 km in ∆σ. A theoretical symmetric triangular mountain ridge is used. It is located in the middle of the domain with a maximum ridge height of 1 km. The width of the base of the barrier is 100 km. The time step is 30 sec. For the numerical integration of the differential equations, the forward in time and upstream in space differencing schemes is used.

2.2. Initial and Boundary Conditions In this model the boundary conditions are similar to the boundary conditions which were used by Orville and Kopp [5]. The summery of the model domain, initial and boundary conditions is presented in Fig.1.

u,ψ, ς, θ, Qv=constant, Qc, Qr and σ° =0 10 km

0 km σ° = 0 u, ψ, ζ =constant, Qc=0 and Qr =Qr at j=2

Fig.1: Summary of numerical scheme and boundary conditions.

Results and Discussion In order to study the effects of steepness of the mountain, two experiments have been made. Experiments a and b are designed to determine the effect of slight slope and steep mountain which are 4 and 6 percent, respectively. The width of the mountain in two experiments is equal. The prevailing flow is calm. The results of the experiments are shown in Figs. 2 to 7. In conclusion it is clear that with a steepness mountain, a stronger vertical circulation is expected. Clouds form earlier and develop faster. The rain also starts earlier. However it has a shorter duration which may be due to the effect of the heavier weight of the column with liquid water content. The updraft motion becomes weaker at earlier time compared to its feature at the corresponding time in the slight Slope Mountain.

References 1- Atkinson, B.W.1981. Meso-scale Atmospheric Circulation’s. Academic Press, pp.

215-279.

( )141∑=

n

DRRR

[ ] 0,,,,, =∂∂

rcv QQQux

θϕ


2- Banta, R. M. 1985. Daytime Boundary Layer over Mountainous Terrain. Part II: Numerical Studies of Upslope Flow Duration. Mon. Wea. Rev. 112, 340-356.

3- Burman, E. a. 1969. Local wind. Gidrometeoizdat Leningrad. Pp. 112-184. 4- Chen, C. H. and H. D. Orville. 1979. Effect of Mesoscale Convergence on Cloud

Convection. J. Appl. Met. 191, 256-274. 5- Orville, H. D and F.J. Kopp. 1977. Numerical Simulation of Life History of a

Hailstorm. J. Atmos. Sci. 34, 1596-1618. 6- Pielke, R.A. 1984. Mesoscale Meteorological Modeling. Academic Press, 61 p. 7- Somieski, F. 1984. Numerical Simulation of Mesoscale Flow over Ramp-Shape

Orography with Application of a Special Lateral Boundary Scheme. Mon. Wea. Rev.113, 2293-2302.

8- Tripoli, G. J., P. J. Flatau and W.R. Cotton. 1988. Generalized Microphysics Scheme for use in Mesoscale Cloud Models.Preprint 10th International Cloud Physics Conf. 15-20 Aug. 1988, Bad Hamburg, FRG, and IAMP.

9- Ulanski, S. L. and M. Garstang. 1978. Role of Surface Divergence and Vorticity in the Life of Convective Rainfall.Part I: Observation and Analysis. J. Atmos. Sci. 35, 1047-1062.

Fig. 2 : Vertical Motion Pattern of Slight Slope Motion


Fig. 3 : Vertical Motion Pattern of Steep Mountain


Fig. 4 : Potential Temperature Pattern of Slight Slope Mountain

Fig . 5 : Potential Temperature Pattern of Steep Mountain


Fig. 6 : Accumulate Rainfall Pattern of Slight slope Mountain

Fig. 7 : Accumulate Rainfall Pattern of Steep Mountain


Estimating crop areas and cropping patterns of Zayandeh-Rud irrigation networks in Iran using GIS

Ali R. Mamanpoush 1, Nader Heydari2, Hilmy Sally3

1-Isfahan Agricultural Research Center, Isfahan, Iran. Phone +98-311-7760061 Email: [email protected]; 2- Iranian Agricultural Engineering Research Institute, Karaj, Iran. Phone +98-261-2705320 Email: [email protected]; 3- International Water Management Institute (IWMI), Colombo, SriLanka. Phone +94-1-787404 Email: [email protected]

Abstract Determination of water supply and demand is a major issue in irrigation schemes. A good indicator of irrigation system performance is degree of matching of supply and demand. However determination of demand for this purpose has proved to be more difficult. It requires data on irrigation area, cropping pattern and intensity, and crop water requirement. In the water stressed Zayandeh Rud Basin in central part of Iran there are six major irrigation networks, which cover 238,000 Ha of command areas. The information regarding the above data for this area is provided both by the Ministry of Agriculture and Planning and Budget Organization which are based on administrative-district level and village-level respectively. As these districts are not coinciding with irrigation system command areas, problem arise in the compilation of crop data for each command area. This research was conducted in order to convert village level and administrative- district level data on cropping area and cropping intensity to irrigation scheme level using GIS, Land use map, and Map overlaying method. Cropping patter were determined using both village level and administrative-district level data.Results provided indicated that using administrative-district level data, the values obtained for cropped areas and cropping intensities are much more realistic in comparison to village level method, and have been obtained with far less time and effort. Furthermore, the results obtained show fairly good agreement with estimates of irrigated areas made using NOAA images and NDVI values for February or September 1995.

Key words: Administrative- district, Cropping pattern, GIS, Irrigation scheme, Map overlaying, Zayandeh-Rud Basin,

Introduction Water supply and demand comparison is one of the most basic ways of describing irrigation system performance. However, the estimation of the water demand has proved to be more difficult. In order to do this, we first require data on irrigated areas, types of crops, cropping calendars, and water requirement for each crop. It will then be possible to calculate the total crop water requirement for each system, and to compare this with the overall water diverted at the head of the system. The design command area is usually determined based on such factors as water availability, crops planned, topography, etc. The design data are quite important because they provide information on the overall per hectare water availability for each system. The ratio of irrigation water deliveries to the respective design command area can enable us to compare the water availability for the different systems. In the Zayandeh-Rud river basin there are six irrigation networks (Gieske et al., 2002) which cover almost 238,000 Ha of command areas (Fig.1). The information regarding the above data for this area is provided both by the Ministry of Agriculture and Planning and Budget Organization annually and every ten year respectively. These data are based on


administrative-district level and village-level respectively. As these districts are not coinciding with irrigation system command areas, problem arise in the compilation of crop data for each command area. The main objective of this research is to convert administrative-district level and village level data on cropping area and cropping intensity to irrigation scheme level using GIS, Land use map, and Map overlaying method.

Materials and Methods Data on cropping pattern, cropping calendars and estimated cropping intensities were available at the provincial offices of the Ministry of Agriculture. The data are typically organized by village and then aggregated into homogeneous agricultural zones and administrative districts. As these data are collected annually, therefore to reduce the work the village data are collected in random and using statistical analysis the district level data were obtained.The Planning and Budget Organization collects these data from every village but the frequency of collection is every ten year. In the following parts the methodology for the convert of village level data and administrative-district level data to irrigation scheme level are explained.

1. Estimate of cropping patterns using village- level data

The land use and the irrigation networks maps were scanned and then were digitized using ILWIS software. By overlaying of irrigation networks and land use maps (Fig. 2) the number of villages in each irrigation network were determined. Then using village-level data collected by Budget and Planning Organization, it was attempted to determine the cropping patterns for the different irrigation networks. This turned out to be a very time-consuming and fastidious task. Because of this fact, this was done only for the four major irrigation networks in the basin, i.e., Nekoabad (Right and Left), Abshar (Right and Left) (Fig.1). In Table (1) a sample sheet of data collected for villages located in irrigation networks is provided.

2. Estimate of cropping patterns using administrative-district level data

In light of the above situation, it was considered worthwhile attempting to verify if the use of the aggregated administrative district level data would give better estimates for cropping patterns with less time and effort. These data are collected annually therefore are more updated than data used in village level method. The irrigation networks and administrative district boundaries maps were overlaid (Fig.3) using their available ILWIS maps to determine the proportion of area of each system that belonged to each of the administrative districts in the Zayandeh-Rud basin. This enabled to determine a coefficient for each irrigation system belonging to a particular district, which when applied to the crop area of that district will result in the crop area for irrigation networks considered. The assumptions here are that (a) all the crop area in a given district can be attributed to one or more of the irrigation systems, and (b) the crop areas are distributed among the irrigation systems in a particular district in the same proportion as their overall boundary areas. But, the first assumption is not unreasonable given that almost all crops in the basin are irrigated. As for the second assumption, the degree of uncertainty would not be any worse than that associated with using the basic village-level data, especially taking into account the large saving of time and effort.


Results and Discussions In Table (2) some analysis conducted on the cropping pattern finally developed for 1991-92 (using the last ten years frequency village level data available) is given. Based on this cropping pattern, the cropping intensities (C.I.) obtained are extremely low (except for Abshar Right). On the other hand, the equivalent water depths delivered to the different systems seem to be unreasonably high compared to the water availability for that particular year. Thus the results obtained seem to indicate that the cropping patterns determined by this approach (village-level) are probably not reliable. Given the total number of villages and crops involved, it is possible that some villages and crops get left out and the contribution of villages to the irrigation schemes do not get properly included. The results obtained from administrative district- level data are provided in Tables (3), (4). The more than 40 crops included in the district-level information were re-arranged into ten categories of representative crops (more categories may be selected, if necessary). The overall-cropping pattern for years1995-96 estimated by this approach, is provided in Table (5).

ConclusionUsing administrative district-level data, the values obtained for cropped areas and cropping intensities are much more realistic, and have been obtained with far less time and effort. Furthermore, the results obtained show fairly good agreement with estimates of irrigated areas made using NOAA images and NDVI values for February or September 1995 (Gieske et al., 2002). The areas for the four schemes obtained through satellite imagery were: Nek LB = 30,320 ha; Nek LB = 16,675; Abs LB = 39,013 ha; Abs RB = 16,238 ha (Gieske et al., 2002).Therefore, this approach seems to be more promising and can be adopted to determine the cropping patterns for the 12-year period 1987-88 to1998-99. The values obtained will be compared with the results of analysis of satellite images, both NOAA and Landsat, wherever possible. We will then be in a better position to judge the validity of this administrative district based approach for estimating cropping patterns in the irrigation systems.

References Gieske A, Toomanian N, Akbari M (2002) Irrigated area by NOAA-Landsat up-scaling techniques :

Zayandeh-Rud Basin, Iran. IAERI-IWMI Res. Rep. No.10, Iranian Agr. Eng. Res. Ins., Karaj, Iran.

ILWIS3 (2001) User guide ILWIS 3.0 Academic, ITC, The Netherlands, 530 pp. Integrated Agricultural Planning of Zayandeh-Rud Basin (1992), Isfahan Agr. Res. Cent. , Isfahan,,

Iran Land use Atlas of Isfahan province Based on satellite data, July 1997, ministry of Agriculture Deputy

of planning and Management support. Salemi HR, Mamanpoush AR, Miranzadeh M, Akbari M, Torabi M, Toomanian N, Murray-Rust H,

Droogers P, Sally H and Gieske A.(2000) Water Management for Sustainable Irrigated Agriculture in the Zayandeh Rud Basin, Esfahan Province, Iran, IAERI-IWMI, Res. Report No.1.

Sally H, Mamanpoush AR (2000) Estimating Crop Areas and Cropping Patterns in Zayandeh Rud Basin (IWMI Progress Report No. 7.


Sally H, Murray-Rust H, Mamanpoush AR, Akbari M (2001) Water supply and demand in four major irrigation systems in the Zayandeh-Rud Basin, Iran. IAERI-IWMI Res. Rep. No. 8.

Statistic book, Cropping years 1992-2000, Planning Office of Isfahan Agricultural Organization, Planning office, Isfahan, Iran.

Table (1) A sample sheet of village-level data for cropping pattern determination

Wheat Barely Paddy Millet Fallow(Irr.)

Nocultivated

Doublecropping

8 0 6 0 0 0 2340 15 3 0 0 0 27410 5 5 0 0 0 8256 64 32 0 0 0 28.830 0 0 0 0 0 0140 70 0.5 0 0 0 140 0 0 0 0 0 0-- -- -- -- -- -- --

Area cultivated under each crop (ha)Village name

etc.Basiri

Molana SafiArghavanieh

AjekRahnan

MahmodiehAminabad

Table (2) Estimated scheme-level cropping pattern derived from village-level data

(ha) Nek-Left Nek-Right Absh-Left Absh-Right

Wheat 2807 1803 4542 5235 Percentages 20.6% 19.5% 43.8% 36.9% Barley 921 1730 1207 1562 Percentages 6.8% 18.7% 11.7% 11.0% Rice 1771 2844 387 2398 Percentages 13.0% 30.7% 3.7% 16.9% Vegetable 2635 1416 1366 1978 Percentages 19.4% 15.3% 13.2% 14.0% Fodder 1762 842 2854 2954 Percentages 12.9% 9.1% 27.6% 20.8% Trees 3714 629 2 48 Percentages 27.3% 6.8% 0.0% 0.3% Total (ha) 13610 9264 10359 14176 Design area (ha) 48000 13500 15000 15000 Annual C.I. (%) 28.35% 68.63% 69.06% 94.51% Water issues (MCM) 467.78 208.26 193.34 220.54 Equiv. depth (mm) 3437 2248 1866 1556

Depth related to

design area (mm) 975 1543 1289 1470


Table (3) Coefficients to distribute district-level crop area data among irrigation schemes within that district

Administrative district

Irrigation schemes within the district

Proportion of cropped area of the district attributable to the different irrigation

schemes (ha) (%)Borkhavan Borkhar 58775 100

Esfahan Nekouabad Right Bank 75 0.05 Borkhar 19475 11.77 Abshar Left Bank 52250 31.57 Abshar Right Bank 22475 13.58 Rudasht West 24750 14.95 Rudasht East 22675 13.70 Mahyar 23800 14.38

Shahreza Mahyar 17500 100.00

Mobarakeh Lenjanat 21500 64.52 Nekouabad Right Bank 9575 28.73 Nekouabad Left Bank 575 1.73 Mahyar 1675 5.03

Lenjanat Lenjanat 20300 97.95 Nekouabad Left Bank 425 2.05

Khomeynishar Nekouabad Right Bank 375 3.38 Nekouabad Left Bank 5050 45.50 Borkhar 5675 51.13

Najafabad Nekouabad Left Bank 20075 100.00

Flavarjan Nekouabad Right Bank 10375 44.43 Nekouabad Left Bank 12975 55.57


Table (4): Coefficients to transform administrative district-level crop area data to scheme level

City Gross Area(ha)

% Area Scheme City Gross Area (ha)

% Area Scheme

Borkhavan 58775 1.00 Borkhar Mobarakeh 575 0.02 Nek LB Esfahan 75 0.00 Nek RB 1675 0.05 Mahyar

19475 0.12 Borkhar Lenjanat 20300 0.98 Lenjanat 52250 0.32 Absh LB 425 0.02 Nek LB 22475 0.14 Absh RB Khomeynishar 375 0.03 Nek RB 24750 0.15 Rud W 5050 0.45 Nek LB 22675 0.14 Rud E 5675 0.51 Borkhar 23800 0.14 Mahyar Najafabad 20075 1.00 Nek LB

Shahreza 17500 1.00 Mahyar Flavarjan 10375 0.44 Nek RB Mobarakeh 21500 0.65 Lenjanat 12975 0.56 Nek LB

9575 0.29 Nek RB

Table (5) Overall cropping patterns in four major irrigation systems in Zayendeh-Rud basin, 1995-96 (the study year)

System Alfalfa Barley Fodder Orchard Onion Potato Rice S-beet Wheat Other TOTAL

Nek LB 2412 3429 490 8269 786 2798 6123 190 7906 7425 39828

Nek RB 878 1543 90 1165 460 963 4129 106 2810 2859 15002

Abs LB 2999 5051 2084 759 452 267 1231 1105 9787 4287 28023

Abs RB 1290 2173 896 327 194 115 530 475 4210 1844 12054 (units: ha)

Tehran

Turkmenistan

Afghanistan

Paki-stan

PersianGulfSaudi

Arabia

Kuwait

Iraq

0 0 0

0 500 km

EsfahanZayandehRud

AbsharLeft

AbsharRight

Borkhar

Mahyar

NekouabadLeft

Lenjanat

NekouabadRight

RudashtEast

RudashtWest

ChadeganReservoir

GavkhuniSwamp

Fig.1The six major irrigation networks in the Zayandeh-Rud River basin

Fig.2 Overlaying of land use and irrigation networks maps


Fig.3 Overlaying of administrative district boundaries and irrigation networks maps


The comparison of hydraulic behavior of conventional furrow irrigation with cyclic furrow irrigation

Bita Moravejalahkami1 and Behrouz Mostafazadeh2

1- Graduate Student, Irrigation Department, College of Agriculture, Isfahan University of Technology, Isfahan, Iran. Phone: +98-311-5554229 Email: [email protected]; 2- Associate Professor, Irrigation Department, College of Agriculture, Isfahan University of Technology, Isfahan, Iran. Phone: +98-311-391-3430 Email: [email protected]

Abstract Cyclic (snake shape) furrow irrigation (Gholam dar gardeshy) is a modified form of furrow irrigation which has being used in Iran traditionally for a long time in order to have better distribution of water along the field. However to date no research has being done about the hydraulic behavior of this ancient method of irrigation. Specially for soils with heavy texture and for fields with steep slope. The results of this method of irrigation can differ significantly in comparison to the conventional furrow irrigation method. To measure the performance of this method of irrigation and to compare the results with the conventional furrow irrigation method an experimental field with sandy clay loam soil was designed and equipments including constant head water delivery system to the furrows were installed in the experimental field. To determine the parameters of the Kostiakov-Lewis infiltration equation, volume balance method was used. Field data including furrow inflow hydrograph, furrow outflow hydrograph, advance and infiltrated water along the furrows were determined for both methods. The results showed that the intake opportunity time is lower and water loss as runoff is higher for conventional furrow irrigation as compared to the cyclic furrow irrigation. As the slope of the field increases the differences between the infiltrated water along the field for two methods decreases.

Keyword: furrow irrigation, cyclic furrow irrigation, efficiency

Introduction Furrow irrigation is one of the oldest methods of irrigation in which soil surface is used to convey and infiltrate water (Mostafazadeh and Walker, 1981; Walker and Skogerboe, 1981; Walker, 1989). This method of irrigation as compared with sprinkler or trickle methods is inexpensive. Therefore, more attention is being paid to improve the efficiency of this method of irrigation. For instance runoff recovery, cutback technology and surge irrigation have been studied to reduce losses (Benham et al., 2003; Gaton, 1966; Mostafazadeh and Mosavi, 1989; Walker, 1989). A number of mathematical models of surface irrigation have been developed to simulate the depth of flow, advance, recession, infiltrated volume, runoff and deep percolation (Mostafazadeh et al., 1991). For instance the sirmod model can be used to evaluate, simulate and design the surface irrigation (Walker, 2003). The efficient application and distribution of water by furrow irrigation is highly dependent on parameters such as input flow, advance time, soil texture, soil infiltration, plant coverage, roughness coefficient, field shape, irrigation management and ect. The use of other method of furrow irrigation for example cyclic furrow that is named "Gholam dar gardeshy" effects the improvement of hydraulic behavior of furrow irrigation. Cyclic furrow irrigation is a modified form of furrow irrigation which has being used in Iran traditionally for a long time. In this method of irrigation water moves in furrows in snaky shape which results the advance velocity of water to be decreased and consequently cause higher opportunity time for infiltration. In general the use of this method of furrow irrigation in heavy


soils and steep slopes in comparison to use furrow irrigation can improve the hydraulic behavior and needs less investment as compared to the sprinkler and trickle systems in some fields. The focus of this study is to compare the hydraulic behavior including infiltration, runoff and velocity of advance for both conventional furrow irrigation and cyclic furrow irrigation for an experimental plot having three different field slopes with sandy clay loam soil.

Materials and methods In these tests a constant head water delivery system to the furrows as shown in Figure 1 was installed in an experimental furrow irrigation field. Parshall flumes were used to measure inflow and outflow for each furrow. Control valves were used to adjust the furrow inflow rate at desired level. The experimental field having sandy clay loam soil was located in Isfahan University of Technology. The field was irrigated for the first time with no plant. Table 1 shows the soil and furrow characteristics for the experimwental field. The tests started with non erosive discharge that was delivered to each furrow. Advance time was measured at different distances along the field for both methods. The test was continued untill constant outflow hydrograph was achieved. Inflow, outflow, advance and furrow geometry were measured for both methods. Three replications were used for each measurement and the irrigation time and inflow discharge were the same for both methods. A schematic drawing of the experimental field is shown in Figure 2. The furrow geometry functions were determined for each test as follow:

21

σσ yA = (1) 2

1γγ yWP = (2)

Where A is cross section area, cm2; WP is wetted perimeter, cm; y is water depth, cm;

2121 ,,, σσγγ are equation parameters as shown in Table 3. The trajectory of advance of the water front in a furrow can be described as the simple power function as follow:

rptx = (3) Where x is advance distance, m; t is advance time, min; p and r are equation parameters. The basic infiltration rate (f0), can be determined using inflow-outflow hydrographs as follow:

LQQf outin −

=0 (4)

Where f0 is basic infiltration rate, m3/min/m; Qin is inflow discharge, m3/min; Qout is outflowdischarge, m3/min; L is furrow length, m. The volume balance equation was used to compute the parameters of the Kostiakov-Lewis infiltration equation as shown bellow:

tfKtZ a0+= (5)

Where Z is the cumulative infiltration, m3/min/m; t is the opportunity time, min; K and a are equation parameters.

The volume balance equation is as follow:

)1/(000 rxtfKtxAtQ xa

xzyx +++= σσ (6)

Where Q0 is inflow per unit width or per furrow at the upstream end of field, m3/min; tx is time water advanced to the distance x, min; σy is surface flow shape factor, which is between 0.7 and 0.8; A0 is flow area at the upstream end, m2; σz is subsurface shape factor, defined as:

)1)(1(1)1(

aaara

z +++−+=σ (7)

Results


The infiltration equation has an important role in design and simulation of surface irrigation. Using volume balance method the Kostiakov-Lewis infiltration equation was determined for conventional furrow irrigation for each experimental plot as follow:

ttZ 00119.0005.0 35.0 += (8) ttZ 00048.00043.0 45.0 += (9) ttZ 000108.00033.0 51.0 += (10)

Where equation 8 is for plot 1, equation 9 is for plot 2 and equation 10 is for plot 3. The results show as the slope of the field increases the flow depth and the wetted perimeter decrease which result in lower cumulative infiltration as can be computed by equations 8 to 10. Also as the slope of the field increases, the basic infiltration rate (f0) decreases as shown in equations 8 to 10. These results are shown in Tables 2 and 3. In Table 3 the parameters K, a and f0 are assumed are the same for both methods and the parameters γ1, γ2, σ1 and σ2 are for conventional furrow irrigation which are similar to the values for cyclic furrow irrigation. The infiltrated depth can be determined using equations 8 to 10. These results are shown in Figure 3. This Figure shows that as the slope of the field increases the differences between the infiltrated water along the field for conventional furrow irrigation and cyclic furrow irrigation decreases (Figure 3A as compared to Figure 3C). Also as Figures 3A to 3C show as the slope increases the distribution of water along the field is nearly more uniform for cyclic furrow irrigation.The water advance curves and equations were determined for both methods as shown in Figure 4. For both methods the velocity of advance was determined in longitudal direction (in field slope direction). This Figure shows that for the same furrow discharge and irrigation time the velocity of advance is higher for conventional furrow irrigation as compared to the cyclic furrow irrigation.Inflow and outflow hydrographs are shown in Figure 5. As the slope of the field increases tail water runoff increases for conventional furrow irrigation but in cyclic furrow irrigation this parameter is zero for three experimental plots. Since the flow rate was the same for both methods the inflow hydrographs were the same for both methods. In cyclic furrow irrigation since water moves in snaky shape the velocity of advance of water decreased and no runoff was observed. The cross-sections for conventional furrow and cyclic furrow irrigation are shown in Figure 6. This Figure shows that both methods have almost the same furrow cross-section. As the slope of the field increases the velocity advance of water increases which results in lower wetted perimeter, because of lower depth of water. These results are shown in Figure 7.

DiscussionThis paper demonstrated comparison of the hydraulic behavior including measured infiltration, runoff and velocity of advance for both conventional furrow irrigation and cyclic furrow irrigation for an experimental plot having different field slopes. It was assumed that the measured infiltration equations can be applied for both methods. The results show that as the slope of the field increases, the velocity advance of water increases which results in lower flow depth and consequently lower wetted perimeter. The differences between the infiltrated water along the field for both methods decreases and tail water runoff increases for conventional furrow irrigation but in cyclic furrow irrigation this parameter is zero for three experimental plots. Also for the same furrow discharge and irrigation time the velocity of measured water advance is higher for conventional furrow irrigation as compared to the cyclic furrow irrigation and both methods have almost the same furrow cross-section.


References 1- Benham BL, Eisenhauer DE, Yonts CD, Varners D (2003) Managing furrow irrigation systems.

Available at: www. ianr. unl. edu/ pubs/ irrigation/ g1338. htm. 2- Gaton JE (1966) Designing an automatic cut-back furrow irrigation system. Oklahoma Agric. Exp. Sta.

Bull. B- 651. 3- Mostafazadeh B, Mosavi SF (1989) The comparison of water infiltrated to furrow under surge and

continuous flow in three field of Isfahan. J. Agric. Sci. and Technol., Vol 3(2): 35-44.(In Persian). 4- Mostafazadeh B, Mosavi SF, Fatahi R (1991) Use of Kinematic-wave model in evaluating furrow

irrigation system. Iranian J. Agric. Sci., Vol 27(3): 45-53. .(In Persian). 5- Mostafazadeh B, Walker WR (1981) Furrow geometry under surge and continuous flow. Iran Agric.

Res. Vol 6(2): 57-71. 6- Walker WR, Skogerboe GV (1981). Surface irrigation., theory and practice. Prentice- Hall, Inc.,

Englewood Ciffs, New jersey: 142-141. 7- Walker WR (1989) Advantage and disadvantage of surface irrigation: Guidelines for designing and

evaluating surface irrigation systems. Utah State University, Logan, Utah, USA, Available at: www. fao. org/ docrep/ to23leo4. htm.

8-Walker WR (2003) SirmodIII: Surface irrigation simulation, evaluation and design. Utah State University, Logan, Utah, U. S. A. Available at: www. Irri- net. org/ sirmod/ -9k.

Table 1. Soil and furrow characteristics for the experimental plots (Soil contains small rocks).

Plot Slope (%)

Soil texture Bulk density (g/cm3)

Sand(%)

Silt(%)

Clay (%)

1 0.3 Sandy clay loam 1.45 48 24 28 2 1 Sandy clay loam 1.45 48 24 28 3 2 Sandy clay loam 1.45 48 24 28

Table 2. Wetted perimeter and infiltration for conventional furrow irrigation.Slope(%)

x(m)

y(cm)

WP (cm)

Z(m3/m)

0.3 15 12.3 48.77 0.0928 1 15 10.31 44.64 0.0576 2 15 9.6 43.47 0.0404

Table 3. Parameters from analysis of collected data from experimental plotsPlot K a f0 σ1 σ2 γ1 γ2

1 0.005 0.35 0.00119 0.81 1.5 1.86 0.621 2 0.0043 0.45 0.00048 0.785 1.49 1.73 0.58 3 0.0042 0.5 0.000108 0.78 1.46 1.65 0.56


Figure 1. Schematic of constant head water delivery system to the furrows

PVC Tee (160mm)PVC pipe

(160mm) PVC belt (160mm)

Control valve

Furrows

Flow Direction

End plug

Channel

Excess water

PumpReservoir


Figure 2. Schematic of one of the experimental field test

Proc

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Time (min)

Furr

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Time (min)

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. Inf

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Figu

re 4

. Adv

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cur

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for

conv

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Infl

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0.6

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0

Tim

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Infl

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.886

R2 =

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297

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010

2030

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Cro

ss d

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(cm

)

Furrow depth (cm)

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.15

R2 =

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Figu

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Bacterial contamination of ground water supplies in Chahaar- Mahaal province (Iran)

Hamdollah Moshtaghi Dept. of Food Hygiene,faculty of Veterinary Medicine,Shahrekord University,Shahrekord,Iran, Tel: +98 913 181 2815, Fax: +98 381 4424427, E.mail: [email protected]

Abstract Occurrence and distribution of coliform bacteria in drinking water from different sources is investigated. One hundred water samples , collected from wells, rivers and springs in shahrekord district of Chahar-Mahal province (Iran), were microbiologically examined for total coliforms and recovery of Escherichia coli using a multiple tube test. Coliform spp.formed 58.3, 100 and 22.2%, respectively, for ground water supplies, rivers and springs. Water samples from most of the well sources and all the river sources were regarded as unsuitable for human consumption.

Key Words: water, coliform spp., multiple tube test.

Introduction The bacteriological examination of water is particularly important as it remains the most sensitive method for detecting faecal and, therefore, potentially dangerous contamination. The key criteria for ideal bacterial indicators of faecal pollution are that they are universally present in large numbers in the faeces of human and other warm-blooded animals. They should also be present in sewage effluent, be readily detectable by simple methods and should not grow in natural waters. Ideally, they should also be of exclusive faecal origin and be present in greater numbers than faecally transmitted pathogens. No single indicator organism fulfils all these criteria, but the member of the coliform group that satisfies most of the criteria for the ideal indicator organism in temperate climates is E. coli. This organism is widely distributed in the intestine of humans and warm-blooded animals and is the predominant facultative anaerobe in the bowel and part of the essential intestinal flora that maintains the physiology of the healthy host (5). The most important of these are the Vero-cytotoxin-producing E. coli (VTEC), in particularVTEC of serogroup O157, but other E. coli serogroups may contain VTEC members. Typical symptoms of people infected with E. coli O157 range from mild diarrhoea, fever and vomiting to severe, bloody diarrhoea and painful abdominal cramps. In 10-15% of cases, a condition known as haemolytic uraemic syndrome which can result in kidney failure. Individuals of all ages can be affected but children up to ten years old and the elderly are most at risk. The infectious dose for E. coli O157 is relatively low compared with other bacterial causes of gastro-enteritis, perhaps as low as 10 organisms. VTEC may not be isolated or may not be recognised by the normal analytical methods forE. coli, and specific isolation methods are required. However, if E. coli isdetected in a water supply it should be assumed that VTEC could also be present (2,3 ,7 ,11). The use of indicator organisms, in particular the coliform group, as a means of assessing the potential presence of water-borne pathogens has been paramount to protecting public health.

Materials and Methods In this investigation 100 samples of water ( well, 36; river, 46 and spring, 18 ) are aseptically collected in sterilized bottles from different areas in Chahaar- Mahaal province. Samples transferred immediately to dark storage conditions and kept at temperatures between 2 - 8 °C for transport to the laboratory and analysed as soon as practicable on the day of collection.


The 5-tube MPN method is used for water examinations (1).Inoculated tubes were incubated at 35 +/- 0.5oC. After 24 +/- 2h for heavy growth, gas, and acidic reaction and, if no gas or acidic growth was formed, reincubated and reexamined at the end of 48 +/- 3h. Production of gas or acidic growth in the tubes within 48 +/- 3h constituted a positive presumptive reaction. Tubes with a positive presumptive reaction submitted to the confirmed phase. The absence of acidic growth or gas formation at the end of 48 +/- 3h of incubation constituted a negative test. For positive tests brilliant green lactose bile broth fermentation tubes used for the confirmed phase.

ResultsThe details of results have come in Table1. Out of 100 sample of water, Coliform spp isolated from 71 samples,which in biochemical tests 56 samples showed the presence of E.coli and 15 samples, Klebsiella. The number of positive samples for E.coli in well water samples was 18, river water samples, 34 and spring water samples was 4. Klebsiella isolated from 3 well water and 12 river water samples, but did not isolate from spring water samples. River water was the most contaminated followed by well water and then spring water samples.

DiscussionE. coli occurs in the faeces of all mammals, often in high numbers (up to 109 per gram of faeces). This widespread faecal occurrence, coupled with methods that for the recovery and enumeration of E. coli are relatively simple to conduct, has contributed to the detection of this bacterium as the cornerstone of microbiological water quality assessment for over 100 years (6,12). The quality of many source waters will depend upon geology, soil type, natural vegetation, climate and run-off characteristics. Disruption of natural geology and heavy rainfall can dramatically affect water quality. Wild animals and birds can also be natural sources of zoonotic pathogens. All types of water sources may be subjected to contamination by agricultural activity .In an investigation in 1994, Pathak et al.,reported that 41-67% of water samples open water sources in India contained coliform and/or faecal coliform bacteria (9). In this investigation 22.2-100% of water samples contained coliform bacteria. Free range animals may excrete faeces into water, and animals like cattle have a habit of wading into water and stirring up sediments. Rainfall can result in the run-off of faecal matter from agricultural and other rural lands into rivers, lakes, reservoirs and springs. Much can be done to reduce the risk of water contamination from slurry spillage, or the use of slurry on land followed by surface run-off, by the adoption of appropriate agricultural practices and aquifer protection policies. Recreational activity may cause pollution through direct contamination of water with faecal material or indirectly by faulty drainage or leakage from sewers and septic tanks provided as part of public access facilities. In a study in Canada, in 1993, Shadix et al., reported out of 119 positive coliform colonies which isolated from 15 water sources ( including a lake,3 rivers, 2 springs, 6 creeks, 2 sewage effluents, and a well) 115 (96.6%) were identified as E.coli (10) .In my study 86.5% of coliforms were E.coli Proper control of recreational activities or treatment commensurate with the recreational use of water should give adequate protection. Where the public has access to reservoirs, consideration should be given to the provision of toilets and hand-washing facilities.The discharge of effluents from sewage treatment works, septic tanks and cesspools can dramatically increase the microbial content of surface waters. The installation of septic tanks and cesspools should be in accordance with national standards. The discharge of industrial effluents, particularly from abattoirs and cattle markets,


may also contain large numbers of pathogenic micro-organisms which increase the risk of contamination. Slurries and solid waste from sewage treatment and animal waste should be spread on land only with strict control (4).

References 1- American Public Health Association (1998). Standard Methods for the Examination of Water and

Wastewater, 20th ed. APHA, Washington, DC. 2- Anderson Y, Ziese J, Dejong B and Rahborg M (1996 ).Outbreak of Escherchia coli O157 in

Sweden. J. Euro. Surveill. 1: 2-3. 3- Bopd DJ and Saunder BO (2003).Detection, isolation and molecular subtyping of Escherchia coli

O157: H7 and campylobacter jejuni associated with alaege water borne outbreak. J. Cli. Micro.41:171–180.

4- Code of Practice for the Agricultural Use of Sewage Sludge. Department of Environment London, 1996, Stationery Office Ltd. 5- Gibson GR and Macfarlane GT (1995). Microbial ecology of the human large intestine. CRC Press,

Boca Raton, FL. 6- Edberg SC, Rice E W, Karlin R J, and Allen MJ( 2000). Escherichia coli: the best biological

drinking water indicator for public health protection. Journal of Applied Microbiology. 88: 106-116. 7- Harudey SE, Pyment P, Huck PM and Gillham RW (2003 ). A fetal waterborne disease epidemic

in Ontario, comparison with other waterborne outhreak in the developed world. Water Science Technology. 47 (3): 7 –14.

8- Neill MA, Tarr PI, Taylor DN and Trofa AF (1994). Escherichia coli. In Foodborne Disease Handbook, Y. H. Hui, J. R. Gorham, K. D. Murell, and D. O. Cliver, eds. Marcel Decker, Inc. New York. pp. 169-213.

9- Pathak SP and kumar SM (1994). Potability of water source in relation to metal and bacterial contamination in some northern and northeasetern districts of India. J. Enviromental – monitorring and Assesment. 32(2): 151-160.

10- Shadix LC, Dunningan ME and Rice EW (1993). Detection E.coli by the nutrient agar plus – 4 methyl – umbeliferyl – beat – D – glucornid (MUG) memberane filter method. Canadian J. Microbiol. 39 (11): 1066 –1070.

11- Tanegu N, Ramarao DS, Jain N, Singh M and Sharma M (2003). Nosocomial outbreak of diarrhea by enterotoxigenic Escherchia coli among preterm neonates in a tertiary care hospital in India. J. Hosp. Infect. 53 (3): 193- 197.

12- WHO (1993). Guidelines for Drinking Water Quality Recommendations.Volume 1 Second edition. Geneva, World Health Organisation.

Table 1: distribution of coliform bacteria in drinking water from different sources in Chahar- Mahal province

Source No. of samples

No. of Coliform

spp.

Coliformspp.%

E.coli %

Klebsiella %

Well 36 21 58.3 85.7 14.3 River 46 46 100 73.9 26.1 Spring 18 4 22.2 100 - Total 100 71 65.7 86.5 13.5


Water table profile under subsurface drainage system

Behrouz Mostafazadeh1, Monireh Faramarzi2, Farhad Mousavi3 and Abdolmajid Liaghat4

1- Associate Professor, Irrigation Department, Isfahan University of Technology, Isfahan, Iran. Phone: +98-311-3913430, E-mail: [email protected]; 2- Former Graduate Student, Irrigation Department, Isfahan University of Technology, Isfahan, Iran. Phone: +98-311-3912659, E-mail: [email protected]; 3- Professor, Irrigation Departmetn, Isfahan University of Technology, Isfahan, Iran. Phone: +98-311-3913435, E-mail: [email protected]; 4- Associate Professor, University of Tehran, Tehran, Iran. Phone: +98-261-224022, E-mail: [email protected]

Abstract In the arid and semi-arid areas, it is important to consider salinity problems of agricultural soils. Results of different researches have shown that it is beneficial if crop rotation is considered for land reclamation programs to decrease the salinity of the soils. As water requirements of crops in crop rotation systems are different, discharge rate (can be equal to drainage coefficient) and the required water table height will be different in a drainage network. So, it is important to study the effects of discharge rate on water table height which influences soil salinity and crop yield. In this research, in order to have different discharge rates and water table profiles under steady-state conditions, a sand-box model (100×90×200cm) was constructed. The model nearly simulated field conditions and was filled with a loamy sand soil to a depth of 1.5 m. Bulk density of the soil was 1.4 g/cm3 and its saturated hydraulic conductivity was nearly 0.5 m/day. Piezometric tubes were placed along the side of sand-box at equal intervals from the drain tube. Discharge of the drain tube was recorded for 19 water table positions at different time periods. After analyzing the data with Minitab and SAS softwares, the corresponding equation for water table profile was obtained. This equation, which relates height of water table and discharge rate, is a polynomial of order 6 and predicts water table profile between two parallel drain tubes with R2 =0.92.

Key words: Subsurface drainage, water table profile, discharge rate.

Introduction Since water table height affects crop yield, and discharge or recharge rate is effective on water table, different researches have been conducted worldwide on this topic (Tabrizi and Skaggs 1983, Withers and Vipond, 1974; Prasher et al., 1997; Sands et al., 2003). Luthin and Worstell (1959) showed that there is a linear relation between drainage discharge and water table height created between two drains. Salihu and Rafindadi (1987) reported a parabolic water table profile in a sand box study. Different factors are effective on water table rise and profile. Salihu and Rafindadi (1989) showed that distance between drains, recharge rate, discharge rate and head of water inside the drains affect water table. Also, there are some studies on the effect of evapotranspiration on water table fluctuation in subsurface drainage systems (Kruse et al., 1993). Collector drains are another factor to be considered in water table calculation. Azari (2001) reported that collector drains affected water table height on both sides to a distance of minimum 100 m and maximum 140 m. Local variations of saturated hydraulic conductivity on water table profile is studied by different researchers using numerical solution of Boussinesq transient equation (Gullichand et al., 1991; Salihu and Rafindadi, 1989; Zurker and Brown, 2002). Drainage coefficient is the amount of water to be drained in 24 hours to control water table height and leach extra salts from soil. Drainage coefficient which can be equal to discharge or recharge rate can be calculated from the following relations: a) In steady- state conditions:


q = Rf + Sc + Si - Dn [1]

where q = drainage coefficient, mm/day, Rf = deep percolation and groundwater recharge, mm/day, Sc = seepage from canals, mm/day, Si = groundwater seepage to drains, mm/day, and Dn = natural drainage from the region, mm/day. b) If drainage coefficient is mainly from irrigation and other components of Eq. (1) assumed negligible , then:

.q = t

Dp [2]

where Dp = deep percolation from irrigation or rainfall, mm, and t = irrigation interval, day. The purpose of present research was to use a physical sand–box model to investigate the effect of drainage coefficient (discharge rate) on water table profile and its fluctuations, and to develop the related equations. These equations could be used in drainage systems design.

Materials and methods A sand-box model as shown in Figures 1 and 2, with double-layer sidewalls, was designed to conduct the experiment. Small pipe-outlets (orifices) located in the sidewalls was used to control water table height at desired position. The drain was a standard PVC pipe-drain, with a diameter of 12 cm and length of 100 cm and was covered with geotextile filter. To measure the water table height, seven piezometers, with a spacing of 10 cm, were installed inside the box. To read the water table, an electric profilemeter was used. To reduce the dimension of the sand box, drain tube was placed 20 cm from the bottom of the box which the bottom of the box act as an impermeable layer. The model was filled with a loamy sand soil to a depth of 150 cm. Bulk density of the soil was 1.4 gr/cm3 and saturated hydraulic conductivity was nearly 0.5 m/day. Different discharge or recharge rates were created by controlling water table height using sidewall outlets. Water was delivered to the sidewalls of the model using two valves located at the bottom of the model. Inflow to the model and outflow to the model was adjusted to reach desired water table profile. After 4 to 6 hours, the water table and drainage outflow became constant. After reaching steady-state conditions, water table profiles and discharge rates were determined. This experiment was performed for 19 different positions of water table. To obtain different water table positions for the sand-box model, the recharge rate ranged from 0.44 to 4.04 m/day was used. These values are high compared to the actual field conditions because to be able to form different water table heights the diameter of the drain tube including the filter was not selected on scale. Since several orifices with equal distance were made on the sidewalls of the sand-box, by opening the orifices, the appropriate water table height could be obtained. To derive equation of water table profile, correlation and multiple regression technique was used. Data were analyzed with Minitab and SAS softwares. Standard and mean errors were calculated by the following equations:

[3]

0.5ni

1i

2ii

1pn

)y(ySE

−−

∑∧

−=

=

=

100)y

yy(

n

1ME

ni

1i i

ii ×∑

∧−=

=

= [4]


where yi = measured water table height at a distance of x from the drain, ∧i

y = predicted

water table height, n = total no. of data and p = no. of parameters in the regression equation.

ResultsData collected from the sand box model were analyzed for 15 different water table profiles under different recharge rates. Different statistical models using Minitab and SAS softwares were studied to find the best statistical model that fits the measured water table profiles under different recharge rates. Then, the model with the highest correlation coefficient and least standard error was selected. The selected model is a polynomial of order 6 which predicts water table profile between two parallel drain tubes for different recharge rates with R2 =92.1%. The selected model is described by the following equation:

632 )LX

6.04()LX

20.2()LX

14.2(Kq

222.3430dY +−++−=∧

[5]

where∧Y = water table height at a distance of X from drain tube, cm, d = distance from the

center of the drain tube to impermeable layer (base of the sand box model), cm, q = recharge or discharge rate, cm/sec, K = soil hydraulic conductivity, m/day, and L = distance between two drain tubes, cm. It should be noted that d and L are constants. The results of the statistical analysis of Eq. 5 are given in Tables 1 and 2. These tables show that values of P (probability) are less than 0.05 and 0.01. Therefore, at probability levels of 5% and 1%, the assumption H0 (rejection of the parameters) is not applicable, and all parameters in Eq. 5 are necessary and none of them should be deleted. To evaluate the linear independency of independent variables given in Eq. 5, the tolerance index was used, and the results are shown in Table 3. In Table 3, tolerance, P, standard

deviation and degree of freedom for different )L

X( ratios with related exponents used in Eq. 5

are given. Table 3 indicates that tolerance indices for independent variables used in Eq. 5 are

negligible and there is no linear correlation among the variables. According to Table 3, K

q

which is dependent variable has high tolerance. In order to show that residuals from predicted values of Eq. 5 are normal, Figure 3 was prepared. This figure shows that residuals follow a normal distribution. Therefore, Eq. 5 was selected as the best model. Comparison of measured versus predicted values of water table profiles for different drainage discharges are shown in Figures 4 to 7. As shown in these figures, water table profiles for each drainage discharge can be predicted closely by Eq. 5 and the differences between measured and predicted values are small. The mean squared error (MSE) of Eq. 5 was found to be 0.035. So, this equation is able to predict water table profile for different drainage discharges at different distances from drain tube with 3.89% average error and 3.78% standard error.

DiscussionIn designing subsurface drainage systems, the depth and spacing of drains that provide suitable water table profile under a recharge rate for optimum soil moisture and salinity level at root zone are important. If the drain installed in the field does not provide suitable water table profile, either stress or water-logging conditions will occur for plants, which results in


reduction of crop yield. To overcome these problems, study of water table profile between parallel tube drains for actual field conditions is important. A sand-box model was designed to study water table profiles between two drain tubes under different discharge or recharge rates for conditions similar to field conditions. The statistical analysis of the collected data of water table profiles for 19 different recharge rates showed that water table positions and recharge rates can be related with a sixth order polynomial with R2 = 92.1%. Based on this equation, water table height can be predicted for a given recharge rate which is important for designing subsurface drainage systems. The Hooghoudt equation is used generally to compute drain spacing for field conditions. In this equation, parameters such as water table height in midpoint between drains, drainage coefficient, soil hydraulic conductivity, drain depth and depth to impermeable layer are used. After the installation of drains in the field, the applied drain spacing might not provide the required water table height in midpoint between the drains and cause either water-logging conditions or stress for plants. Therefore, it is recommended, before drain installation in the field, to do a field research similar to this study to determine the relationship between water table heights between drains, recharge rate, and drain spacing. Then, based on the obtained results, the drains be installed in the field such that proper water table profile occurs under actual crop grown in the area and the related recharge rate.

References 1. Azari, A (2001) The effect of absorbent collector drains on drainage coefficient in Dasht-

Moghan subsurface drainage network. MSc. Thesis, College of Agriculture, Isfahan University of Ttechnology, Isfahan, Iran. (In Persian with english abstract), 142p.

2. Gullichand, J, SO Prasher and D Marcott. (1991) Kriging of hydraulic conductivity for subsurface drainage. ASCE, J. Irrig. and Drain. Eng.117 (5): 667-681.

3. Kruse, EG, DF Champoin, DL Cuevas, RE Yoder and D Young (1993) Crop water use from shallow, saline water tables. Trans. ASAE 36 (3): 697-707.

4. Luthin, JN and RV Worstell (1959) The falling water table in tile drainage. III. factors affecting the rate of fall. Trans. ASAE 2 (1): 45-47.

5. Prasher, SO, M Singh, AK Maheshwari and RS Clemente (1997) Effect of spatial variability in hydraulic conductivity on water table drawdown. Trans. ASAE 40(2): 371-375.

6. Salihu, M and NA Rafindadi (1989) Nonlinear steady state seepage into drains. ASCE, J. Irrig. and Drain. Eng. 115(3): 358-376.

7. Sands, GR, J Wiersma and Z Fore. Determinig the feasibility of subsurface (tile) drainage for improving wheat and soybean yield and profitability in northwest Minnesota. Available at: www.smallgrains.org. Accessed 27 July 2003.

8. Tabrizi, AN and RW Skaggs (1983) Variation of saturated hydraulic conductivity within a soil series. Microfiche, (Fiche No. 83-2044).

9. Withers, B and S Vipond (1974) Irrigation Design and Practice. B. T. Bastford Limited, London, 306 p.

10. Zurker, LA and LC Brown (2002) The Ohio State University, Extension Bulletin, Agricultural Drainage, No. 871-98.


Table 1. Regression analysis for Eq. 5. Predictor Coefficient of

variables Standard deviation t-Ratio P-Values

Constant -0.343 0.044 -7.810 0.0001 (X/L)2 14.220 0.691 20.590 0.0001 (X/L)3 -20.169 1.047 -19.260 0.0001 (X/L)6 6.040 0.413 14.630 0.0001

q/K 222.0 7.086 31.370 0.0001

Table 2. Analysis of variance for Eq. 5. Source of variations

Degree of freedom

Sum of squares Average of squares

F P-values

Regression 4.0 54.954 13.738 394.47 0.000 Error 13.0 4.539 0.035 Total 134.0 59.493

Table 3. The collinearity of Eq. 5. Predictor Degree of freedom Standard deviation P-values Tolerance Constant 1.0 0.040 0.0001

(X/L)2 1.0 0.700 0.0001 0.005 (X/L)3 1.0 1.060 0.0001 0.003 (X/L)6 1.0 0.420 0.0001 0.015

q/K 1.0 7.150 0.0001 0.940

Inner-wall holes

Front wall (Plexiglass)

Bolt

Figure 1. Details of sand box model (units in cm)


0.350.250.150.05-0.050.15--0.25-0.35-0.45-0.55

0.999

0.990

0.950

0.8

0.5

0.2

0.05

0.01

0.001

Residuals

Prob

abili

ty

Figure 3. Evaluation of normality for residuals in Eq. 5

Figure 4. Water table profile between two drain tubes for q = 0.0022 cm/s.

0

5

10

15

20

25

30

35

40

45

0 20 40 60 80 100

Measured

Predicted

Wat

er le

vel a

bove

dra

in tu

be (

cm)

Distance from drain tube (cm), with symmetric assumption


0

10

20

30

40

50

60

0 20 40 60 80 100

Distance from drain tube (cm

Measured Predicted

Wat

er le

vel a

bove

dra

in tu

be (

cm)


0

10

20

30

40

0 20 40 60 80 100

Distance from drain tube(cm)

Measured Predicted

Wat

er le

vel a

bove

dra

in tu

be (

cm)

0

10

20

30

40

50

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0 20 40 60 80 100

Measured

Predicted

Wat

er le

vel a

bove

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in tu

be (

cm)



Distance from drain tube (cm), with symetric assumption




Water Spreading Impact on Ground Water Resourcesin Part of the Zanjan Plain, Iran

Farzad Bayat Movahhed1

1. Research Center of Agriculture and Natural Resources, No. 1216, 6th street, Phase 3, Shahrak Karmandan, Zanjan, IRAN. E-mail: [email protected]

Abstract: Today’s, decreasing of ground water level and lack of existing enough water for agricultural activities is the most important factor which limits the sustainable development. Having knowledge of the function of water spreading systems and their effects on the ground water resources is one of the most important activities that could be assessed in managing water spreading and aquifers recharge projects. The study area is located in the part of the Zanjan plain, in northwest of Zanjan city that has been covered by quaternary deposition. In this study, the impact of amount of spreaded floodwater on water quantity changes of a qanat located in the spreading area has been investigated and compared with a qanat as control. Also changes of water table of 2 pizometric wells have been surveyed during 1996–2003. For this purpose, the amount of rainfall and diverted floodwater to the station were monitored and measured during all flooding time. Although during most of the study years, the amount of rainfall was about 30 % less than mean annual precipitation of a period 32 year, floodwater was harvested and spreaded 7 times. Comparing two qanats showed that one located in spreading area was completely affected by water spreading and had extreme changes on spreading times (from 2.1 to 32 lit/s). Whereas the control one which has larger basin had not got much changes. This study also showed that not only the decreasing of water table in this part of area was stopped, but also some increasing on water table in wells around the spreading area (about 3 meters) was observed.

Keywords: Water table, Floodwater spreading, Qanat, Zanjan plain, Iran.

Introduction More than 90 % of Iran is located in arid and semi-arid area and faces the problem of water shortage. The limited annual precipitation is mainly changed into floods. Therefore, to overcome this problem, care should be taken for optimal use of floodwater as one of the main water resources. Floodwater harvesting and its utilization was developed in arid and semi-arid regions receiving limited rainfall that falls during short, intense storms resulting in runoff. For this purpose, floodwater-spreading projects can be useful as one of the most suitable methods in most regions throughout the country via utilization of floodwater. It is a form of flood irrigation whereby the runoff of sloping areas is diverted from their natural course and spreaded over adjacent flood plain to allow infiltrate it into the ground (NRCS, 2002). This water are deep percolated into pore spaces of alluvial deposition for storage it for other uses. There are many extensive aquifers in Iran with much porosity in which there is possibility of storage and usage of water for long time.Unfortunately, because of over extraction from ground water resources and intensive reduction of water table, water supply for agriculture has become as most important limitative factor for developing projects. There are some reports about the reduction of ground water levels from Iran. For example, a 13 m was reported for Lar plain (Fars province) from 1970 to 1982 (Kowsar, 1995), about 7 m for Abarghoo plain (Yazd province) from 1973 to1982 (Kowsar, 1995), and about 7 m for Zanjan plain during 1995-2000 (Abdi, 2000). This problem also causes an important reduction in number of qanats and their discharge in Zanjan plain and other areas of Iran.


In some reports improving the ground water resource conditions has been reported after flood spreading. For example, Sanjari and Zoraghi (2001) from Paskuh Saravan, Iran, have reported the flood spreading result in 15 cm meanly increasing the ground water table of that plain. The objective of this research is to evaluate the impact of floodwater spreading project of Sohrain on ground water level of a part of the Zanjan plain.

Materials and Methods -Study area

The study area is located in northwest of Zanjan city, Iran (Fig. 1). This plain is located between two rivers of Sohrain and Gharecharian. The most of the plain area is under dry land farming, also fallow and released dry lands. Livestock production and their grazing also is one of the main activities of villagers in the plain.

Dominant slope of this region varied between 2 and 5%. The plain has been covered by quaternary deposition. The thickness of deposits varies from 80 to120 m. The depth of ground water is ranged from 40 to 60 m. The porosity of these depositions varied between 20 and 30 percent. Climate of the study area is semi-arid, mean annual rainfall is about 297 mm that most of them comes on spring, mean temperature is 10.7 oC having the mean maximum and the minimum of 17.5 and 3.9 oC, respectively. The elevation of the study area is about 1800 m above sea level.

-Field measurements Water tables in 14 pizometric wells in this part of the Zanjan plain were recorded

during 7 years and based on area for each well the mean ground water table of this part of the plain were calculated. Also discharge of two qanats, one near the spreading area and another far from the area, were measured during the study period. The amount of diverted floodwater to the station was also measured at all flooding time.

Results-Precipitation

The rainfall was monitored during the study period (i.e. 1996-2003). In addition, rainfall data was collected for a period of 32 years (Figure 2). Based on this data, rainfall in 6 years of 8 years was less than the mean annual rainfall, which indicates that these years can be considered as drought period. In the study period 40 % of precipitation fell on spring and April, May and March had most precipitation with 17.3, 14.9, and 11 %, respectively.

-Diverted floodwater The amount of diverted floodwater and its changes has been shown in Figure 3. During the

study period, diversion of flood was occurred 7 times. The smallest one has had a volume about 35000 m3 on November 1997 and the largest one occurred on May and April 2004 with a volume more than 9100000 m3.

-Qanat discharge Fiqure 4 shows the variation of qanat discharge during the study period. As this figure

shows, there are some considerable differences between the discharge of the qanat, which is located near to spreading area and the one that is very far from floodwater spreading station has been considered as reference point. Based on these observations, at the time of flood utilization, discharge of the observation qanat showed a rapid response to floodwater and its discharge increases rapidly. After the end of flood, the discharge of qanat decreased gradually. Whereas, the discharge of the Qanat that has been considered as control, remained relatively constant and there were only some changes in wet seasons.


-Ground water tableThe average of ground water level of two pizometric wells that are near the spreading

area can be seen in figure 5. This Figure shows that ground water table in this area increased gradually especially in the last years of study. The average of ground water table of the plain using 14 pizometric wells for each year was calculated and their changes has been shown in Figure 6. This figure shows the ground water table of the plain stopped decreasing and started to increase after implementation of floodwater spreading project. the reduction of the

Discussion:Based on the results obtained in this research, although the annual precipitation during

1996 – 2003 was about 30 % less than the mean annual amount, but diverted floodwater and its spreading could prevent the effects of drought on ground water resources. It also caused an remarkable increase of qanat discharge located in spreading area, whereas the discharge reference Qanat did not show a significant change. The writer has also found the good correlation between the amount of harvested floodwater and total discharge of the qanat (B. Movahhed, 2002). Also the impact of flood spreading on qanat discharge increasing has been reported from Yazd, Iran (Danaeian, 2001).

Increasing of the ground water level in two pizometric wells near the spreading area and the trend of ground water table changes show that the ground water table of the plain is improving. It results in construction of 10 exploitation wells in three last years in the down land of spreading areas.

Acknowledgement: I would like to express my sincere thanks to Mr. G. Mojtahedi and H. Shami, the my colleagues in Research Center of Agriculture and Natural Resources in Zanjan, for helping in data collection.

References: 1-Abdi P, (2000) Evaluating of geological characteristics of quaternary deposits in Zanjan

plain. Tehran University. p. 240. 2-Danaian MR, (2001) Impact of Miankuh flood spreader on water resources.

Proceeding 2th conference of flood spreading stations results. Tehran. pp. 1-16. 3-Kowsar SA, (1995) An introduction to flood mitigation and optimization of

floodwater utilization. Research Institute of Forests and Rangelands. No. 150, p. 522.

4-Movahhed FB, (2002) Study of the Impact of floodwater spreading on quantity changes of the qanat discharge in Zanjan. Journal of Soil and Water Science. 16: 251-258.

5-NATURAL RESOURCES CONSERVATION SERVICE, (2002) Conservation Practice Standard for Water spreading. Washington D. C., P. 4.

6-Sangari GR, and Zoraghi G H, (2001) The study of the effect of water spreading on the fluctuation of ground water table of Paskuh aquifers. Journal of Pajouhesh and Sazandegi. 50:54-57.


Fig. 1) The location of study area

0

50

100

150

200

250

300

350

400

1996 1997 1998 1999 2000 2001 2002 2003

mm

Annual Rainfall Mean the 8 years period Mean the 32 years period

Fig. 2) Precipitation in study years from 1996 to 2003 and in a period of 32 years


Fig. 3) Amount of harvested floodwater in study years from 1997 to 2003.

Fig. 4) Discharge of the observation qanat and the control one in study years from 1998 to 2003


Fig. 5) Mean changes of the ground water level of two wells from 1996 to 2003

Fig. 6) Mean changes of the ground water table of the plain from 1996 to 2003


A Case Study on Morphological Characteristics of Gully Erosion in the Northern Sub Basins of Karoon River

Nekooeimehr, M.1 , Fatahi, R.2

1-Researcher, Agriculture research center, Shahrekord, E-mail: [email protected] ; 2- Assistant prof. Shahrekord University, E-mail: [email protected]: Daily progressive and intensifying of gully erosion in Karoon watershed has been caused serious damages to the agricultural land, soil resources and downstream water resource infrastructures. To prevent gully erosion initiation and expansion there is a need to collect some basic knowledge about types, adaphic and geomorphologic characteristics, land use and damage evaluation of gully erosion through applied researches. The results of this research indicates that the most sensitive location to gully erosion are the south and southwest part of the study area ,and along the natural drainage network of the watershed. Plan shap of gullies are linear with medium depth of (1-10) meters. Mean dip of gullies facies are (4-19) percent in landscapes and 25 percent in marginal slopes. Most of the gullies are continuous with trapezoid cross section. The analysis of soil samples from gully sections shows that many of the gullies in this watershed have emerged on the moderate to heavy texture bare soils with high level of exchangeable sodium rate. The gathered data suggest that two main reasons for gully erosion are natural phenomena and human activities.

Keywords: Gully erosion,Karoon River,Morphological characteristics

Introduction: The soils are among the high value natural resources in a country. Nowadays in many parts of the world the soil erosion is the most undesirable phenomenon for sustainable life of human kind. This phenomenon moves the fertile soils from the agricultural lands, pastures and forest , thus decreases the land productivity. Moreover the eroded soil particles finally will be settled down within waterways, irrigation and drainage channels and reservoirs and it cases reduction in their life time and performance. One of the most devastator water erosion types is gully erosion ,which can be observed worldwide and the soil conservation specialists take it as indices of soil erosion status. In the past it was believed that gullies are formed from the expansion of rill erosion but today it has been realized that the formation of this kind of erosion has a complicated process.The earliest investigations about gully erosion were scoped on the technical and structural aspects of gullies but since 1950 more researches have been done in USA, Europe, and Australia by focusing on the initiation and expansion mechanisms of gullies. The effects of physicochemical and mechanical soil characteristics in gully erosion process also took in consideration in latest studies. Deploey (1973) distinguished three types of gullies in Tonisia region as V or U shape with one head, Vor U shape with more than one head and bank gullies (according to Gaffari ,1990). Imeson et al. (1982) detected three types of gullies in Moroco region as U shape, V shape and U shape formed by tunnel erosion . Planchon et al. (1987) categorized gullies based on the longitudinal profile slopes as three groups, firstly those emerging on the fast slopes and affected by surface runoff and surface soil layer quality, secondly deep gullies emerging by tunnel erosion on the moderate slopes and thirdly downstream gullies emerging on the fine clay sediments (according to Gaffari,1990) . Poesen and Govers (1986) investigated the relation between gully shapes and climate-adaphic factors. They concluded that it is possible to identify the initiation and expansion parameters from the geometrical shape of gully sections. Balling and Wells (1990) stated that however the majority of gullies emerged due to unsuitable uses from ecosystems but there are gullies


were no human contribution exist, thus the gullies can be formed due to intrinsic Geo-Climate conditions.Ghodoosi (1994) investigated the gully expansion and the role of flow with solution material within. He concluded that the initiation and expansion of gullies have direct relation with the salt content of soil solution, surface runoff concentration, characteristics of soil layers , rainfall intensity, vegatative cover density, geological formations, soil type, slope, and land use. According to Ahmadi (1995) the main factors in creating gully erosion are sensitiveness of geo-formations, change in land use, intensive farming and cultivation, overgrazing of pastures, increasing surface runoff and climate changes. Soofi (1999) focused on some characteristics of gully erosion in Iran . He found that mean dip of gully facies are below 15% . Plan shape of gullies are digitated with U shape cross section . These gullies formed around drylands , with medium depth of (1-10) meters . According to aforementioned discussions, it can be realized that the gully erosion is a site-specific process which is in turn different in accordance with climatological, geological, pedological and topographic conditions in each region. In the other word to evaluate the erosion potential and its causes for a region , there is substantial need to carry out special investigations about ecological conditions. Therefore the present study has been done in the sub-basins watershed of Karoon river within Chahar-mahal and Bakhtiari province territory. Through this research basic information about type, adaphical and morphological characteristics of gullies, land use and potential damages were collected in order to undertake necessary actions to prevent extension and daily progressive gully erosion in this region.

Material and Methods Chahar- Mahal and Bakhtiari province comprises 16533 km2 , located on the central zone of Zagros mountains. This region geographically located between 32o, 9’ to 32o, 48’ N latitudes and 49o, 30’ to 51o, 26’ E longitudes. More than 80% of this area is occupied by mountains and hills. Based on climatological studies this region has seven climates that are dry, semi-dry, mediterranean, semi-humid, humid, very humid type A and very humid type B. Most of the irrigated lands (plains) in this region covered with deep heavy soils and 83% of pastures are in poor to very poor status. In this investigation after primarily studies by field observations, areal photos, and available information , the location of more than 100 gullies were distinguished over the rigion using GPS (Fig.1). In the next step the territory of each gully rigion which was at least 500 hectares, was determined on 1/25000-scaled maps. The De Martonn climetological map was prepared using GIS techniques and meteorological data from the nearest stations (Table.1 and Fig.2) . As a result four climates namely, mediterranean, semi-humid, humid and very humid type A , were defined. Two gullying regions were selected for each climate zone and in each region the classification of gullies based on location (on the slope- on the plain) maturity period (continuous or discontinuous), general plan shape (digitated-linear-parallel-bobbled-composite) and average depth (shallow, d< 1 m -intermediate, 1<d<10m- deep, d>10m ) was done. At each region three representative gullies were selected. A representative gully was defined so that its characteristics like length, width, depth, land use, general plan shape and the head of gully can be considered as general status comparing most of the gullies in the region. Other deterministic and descriptive information such as elevation from sea level, side slopes, the vertical profile of head, section shape, and…. were also collected and recorded. The gully soil samples from the representative locations were collected in order to determine the soil texture, Ph, EC, CEC, ESP, SP, and soil aggregates stability(by modified Emerson method). The samples were taken from right and left sides in 25%, 50% and 75% of gullies


length. In order to measure the gully development four benchmarks were established in an appropriate distance from the gully sections.

Results and DiscussionThe Results of this study indicate that although the gully erosion is evident all over the province but geographically in the south, southwest and west more gullies can be observed. Through this investigation 8 critical sub regions with intense gully erosion so called Armand, Sarghaleh, Sarkhoon, Barz-Showarz, Lahderaz, Bardbor, Kaj and Bazoft were identified. The classification of gullies within study regions shows that the gullies are more frequent in sloping lands and along the natural drainage networks. Plan shape of gullies are linear with trapezoid cross section and intermediate depth of (1-10) meters. From the point of the view of maturity period , most of the gullies are continuous.The results of gully classification in study regions are presented in table 2. Soil samples analysis shows that the majority of gullies were emerged on soils with moderate (loam) to heavy (clay) textures and the percentage of silt was high (40 to 65)% in all the samples. In fact the higher percentage of silt increases the erodilibity of the soils. The exchangeable sodium percentage (ESP) is varied from 2.1 to 6.2 percent and the more erosion was observed in the soils with higher ESP. The laboratory experiments show that other soil parameters like Ph (7.3-7.8), CEC (12-15)%, SP (38-52)% and EC (< 1 ds/m) were within normal range and with no restrictions. The measurements of soil aggregates stability indicat that most of the samples are in class 2 or 3.Pasture lands, low density forest (hilly soils) and sloping rain feed lands are the places where the most detrimental gullies has been formed, thus it can be concluded that the non appropriate land use has great influence on the formation of gully erosion. Some of observed gullies have been initiated from the furrows which were established during plowing of the lands. The frequency of gullies on the hilly lands with Quaternary, Bakhtiari, Asmari and Aghajari formations are more than other parts. The average land slope where the gullies exist was (4-19)% in the longitudinal and the average side slopes of about 25%. The profile of gully heads were inclined to vertical. Briefly the most important natural factors in gully erosion are, soils erodilibity, sensitiveness of surface geological layers, slope and its direction, vegatative cover density, rainfall intensities and runoff discharges. To close the conclusion it must be mentioned that human factors such as change the land use, intensify cultivation, road construction, play important role in gully erosion initiation and expansion processes. This study still is going on in another regions and more results should came soon.

References: 1. Ahmadi, H. (1995) Applied Geomorphology, Tehran University ,(in persian). 2. Balling, R.C. and S. G. Wells, (1990) Historical rainfall patterns and arroyo activity within the Zuni River drainage basin , New Mexico , Annals of the Assoc.of Am. Geogr.,80(4),603-617

3. Crouch, R.J. and R.J. Blong, (1989) Gully sidewall classification, Zeitschrift fur Geomorphologie, N.F.Supplement Band, 33(3):291-305.

4. Gaffari, A., (1990) Aerospace techniques applied to gully erosion studies in Sahrekord, Iran.

5. Ghodoosi, J., (1994) Gullies expansion and development, Rangeland and Forest Research Institute,(in persian).

6. Imeson, A.C. and F.G. Kwaad , (1980) Gully types and gully prediction. KNAG Geografisch Tijdschrift, 5 , 430-441.

7. Poesen, J. and G. Govers (1990) Gully erosion in the loam belt of Belgium, soil erosion on agricultural land. Wiley, Chichester, k, pp. 513-530.

8. Soofi, M. (1999) Iran soil erosion and sediment committee technical report.


Ministry of Jihad-e-Sazandegi,(in persian).

Table.1- Meteorological data in the study regions

Meteorological station Average annual rainfall (mm)

Average annual temprature oC

Shahrekord 340.1 11.9 Lordegan 532.8 14.9 Brojen 250.8 10.3 Emamghies 605.3 10.2

Esfahan

Khoozestan

Lorestan

Kohgiloyeh& Boyr Ahmad

Shahrekord

Lordegan

Brojen

Kohrang

Farsan

Nor

th

Fig. 1. Chahar Mahal & Bakhtiari Province and the location of studied Gullies

Gullies Cities Region border

Ardal


Fig.2. Climatology map of Chaharmahal and Bakhtiyari province


Table2. Gully classification on the study regions with different climate conditions.

Climate Selected region

Gullies classification

Armand Location in watershed: along the natural drainage net worksMaturity period: continuous General plan shape: linear Average depth: intermediate (1-10 m)

Mediterranean

Sarghaleh Location in watershed: along the natural drainage net worksMaturity period: continuous General plan shape: linear and digitated Average depth: intermediate (1-10 m)

Sarkhoon Location in watershed: along the natural drainage net worksMaturity period: continuous General plan shape: linear Average depth: intermediate (1-10 m)

Semi-humid

Barz & Shuarz

Location in watershed: on the sloping lands. Maturity period: continuous General plan shape: linear Average depth: intermediate (1-10 m)

Lahderaz Location in watershed: along the natural drainage net worksMaturity period: discontinuous General plan shape: linear Average depth: intermediate (1-10 m)

Humid

Bardbor Location in watershed: along the natural drainage net worksMaturity period: continuous General plan shape: linear Average depth: intermediate (1-10 m)

Kajj Location in watershed: along the natural drainage net worksMaturity period: discontinuous General plan shape: linear Average depth: intermediate (1-10 m)

Very humid type A

Bazoft Location in watershed: along the natural drainage net worksMaturity period: continuous General plan shape: linear Average depth: intermediate (1-10 m)

using gis to derivation of gamma giuh, khanmirza watershed...

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