modelling of floods - hm · pdf file · 2012-09-20provided spreadsheet( design...

MODELLING OF FLOODS Dunsop at Foot Holme

1

Halim Maamari

2 …………………………………………………..24

1.1 FLOOD MODELING:

1.2 CATCHMENT DESCRIPTION:

1. INTRODUCTION

2. FLOOD HYDROGRAPH GENERATION 2.1 FEH RAINFALL –RUNOFF METHOD:

2.2 STATISTICAL METHOD:

2.3 CONTINUOUS SIMULATION OUTPUTS-SHETRAN:

2.4 HYDROGRAPH SUMARRY:

3.1 MODEL CALIBRATION:

3. RIVER MODELLING

3.2.1 RETENTION WALL CONSTRUCTION:

3.2 MODEL SIMULATION:

3.2.2 RECTANGULAR SECTIONS:

3.2.3 DELETING THE BRIDGE:

3.2.4 WETLAND CONSTRUCTION:

3.2.5 DIVERSION CHANEL CONSTRUCTION:

4. CONCLUSION

6. REFERENCES

5. APPENDICES

TABLE OF CONTENT

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1. INTRODUCTION

Flood modeling is the science of understanding, analyzing and graphically representing the mechanism of flood events in order to find solutions for complex hydrological systems using historical, gauged and physical data. The main mean of processing these information is by computational models.

The task is to develop a plan of flood alleviation by modeling the water level situations of the river Dunsop at Footholme.

The situation will require the estimation of the extreme discharge occurring from the catchment

as a result, a 100 year return period shall be used for generating discharge hydrographs.

Three methods shall be used for this purpose:

-FEH rainfall-runoff method.

-FEH statistical method.

-Continuous simulation method.

Once the three are generated they shall be incorporated into a 1D Modelling system(NOAH) in order to mitigate flooding of the residential areas along the river(Village A and Village B).

Fig.1Dunsop river

Fig.1

The catchment of the river Dunsop is located in the north of England in the forest of Bowland. It has an area of 25,5 KM2 and has a steep slope which gave him a characteristic of being highly responsive to water runoff. Due to the history of flooding in the area, the highest one ,was on the 8 th of August 1967 (117 mm of precipitation), some flood control measures are being taken to alleviate flooding risks.

1.1 Flood modeling:

1.2 Catchment description:

There are three rain gauges in the site and the river gauging station is known as Footholme Flume.

The main three elements that will be the center of our study are, the villages along the river(Village A &B) as well as the bridge(See Fig.1.1).

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Fig.1.1 Dunsop Bridge

Fig.1.1

2. FLOOD HYDROGRAPH GENERATION 2.1 FEH RAINFALL –RUNOFF METHOD:

The Rainfall runoff method is used to derive design flow estimates for catchments using catchment descriptors and precipitation data as it is a method that converts rainfall information into discharge information.

A storm event hydrograph for input is generated ,for a return period (T) of 100 years, from the provided spreadsheet( design storm.xls) and the following steps were followed:

Determination of duration, D: From FEH, the properties of the catchment are extracted then used as input in the PCD (Physical Catchment Descriptors) sheet. Tp was extracted and then the duration D was calculated using the following equation: 𝐷=𝑇𝑝 *(1+𝑆𝐴𝐴𝑅(Standard Average Annual Rainfall)/1000 ) The result is D=4.25 hr (Rounded up value to 4.4).

Determination of depth of precipitation: The following equation was used in order to calculate the depth of precipitation P: 𝑃=𝑅𝐷𝐷𝐹(Point estimate of the design rainfall obtained from the FEH DDF model) *𝐴𝑅𝐹(Areal reduction factor transforming point rainfall to catchment average rainfall) *𝑆𝐶𝐹(Seasonal correction factor transforming annual maximum rainfall to seasonal maximum rainfall). From the FEH DDF model, for T=100 years and D = 4.25 hr; RDDF was computed to be 90 mm(See Fig.2). From the FSR areal reduction factors curves, a value of ARF = 0.93 was approximated. A value of SCF = 0.89 was taken based from ReFH calculations. Finally, after incorporating all the necessary correction factors, the depth of precipitation P has been computed to be 74.5 mm.

0

25

50

75

100

125

150

0 1 2 3 4 5 6

Rain

fall

(m

m)

Reduced Variate

DDF curves Fig.2

4

90 MM

Fig.2DDF Curve

2. FLOOD HYDROGRAPH GENERATION

0.0

2.0

4.0

6.0

8.0

10.0

12.0

0.00 0.25 0.50 0.75 1.00 1.25 1.50 1.75 2.00 2.25 2.50 2.75 3.00 3.25 3.50 3.75 4.00

RA

INF

AL

L (

mm

)

HOUR

Design storm Fig.3

Derivation of unit hydrograph: Based on the given catchment physical characteristic, three parameters are calculated Tp (Time of peak) Up (Peak ordinate) and Tb (Base length), using the triangular FEH Rainfall-Runoff method(See Fig 5), the unit Hydrograph is derived (See Fig.4).

0.0

0.5

1.0

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3.5

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

UH

Hour

Unit Hydrograph

Unit Hydrograph

Fig.4 Fig.5

Fig.5 Triangular unit hydrograph

To derive the unit hydrograph, a triangular approximation implemented by the FEH method is adopted.

Derivation of storm profile:

A symmetric standard storm profile was applied to obtain the ordinates of the design(See Fig.3).

The selection of the profile is mainly dues to the season and the location of the catchment.

Since that the Dunsop catchment is located in a rural area (URBEXT1990 = 0.000 <0.125), (flooding normally occurs during the winter seasons, as a result, a 75 % winter profile is chosen, as per FEH’s recommendations.

P(74.5mm) is multiplied with each ordinate of the unit profile in order to obtain the design storm graph (See Fig.3).

It can be noticed from the graph that the design rainfall is symmetrical having a centered peak .

5

Fig.3 Design storm profile

Fig.4 Unit Hydrograph


Derivation of total design flood hydrograph:

The losses due to interception, infiltration,…were taken into consideration by multiplying the ordinates of the design storm profile by the percentage runoff.

The percentage runoff which is taken is 67% of the total rainfall. This meant that the total rainfall was reduced by 33% in order to estimate the effective rainfall (See Fig 6).

The direct runoff hydrograph was generated by multiplying the effective rainfall for each 15 minute increment by the unit hydrograph ordinates to compute for the direct runoff hydrograph for each period. The response for each 15-minute period of precipitation was tabulated, then shifting each of the next responses with respect to the previous ones, and finally summing all individual periods together to get the total response.

Finally In order to obtain the total runoff (total flood) hydrograph, the base flow which has a constant value of 6 m3/s was added (See Appendix-A).

0.0

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1 2 3 4 5 6 7 8 9 10 11 12

Rain

fall (

mm

)

Hour

Losses

rain

net rain

0

20

40

60

80

100

120

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8 8.5

Rainfall Runoff

Fig.6

Fig.7

Fig6 Losses graph showing difference between effective rain (net rain) and total rain.

Fig7 Final rainfall runoff hydrograph that will be used as an input for flood simulation.

The peak discharge is 104.5 cumecs.

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2.2 STATISTICAL METHOD:

The statistical method uses historical data gathered from the region surrounding the concerned basin where catchment have more or less same characteristics (Donor Catchments).

The way to process these information is to use WINFAP-FEH which is a flood estimation software based on the FEH statistical method.

Two methods are available in the software package:

1-The single site analysis, as the name implies, the flood frequency estimation is done on a single gauged site having the required data.

2-Pooling group analysis, where we can benefit from the data of other similar locations in order to increase the data pool of a particular site.

Single site analysis:

As shown in the Table below , Dunsop at Footholne has an AM (Annual Maxima is the single highest rainfall event recorded in a particular year) record of 13 years which implies that these records are not enough to produce a hydrograph of 100 years return period.

The highest flow recorded is on October 27, 1998 ( 58.20 cumecs) and lowest on May 22, 2003 ( 23.70 cumecs).

QMED which is the mean flow value, is used in statistical method .The advantage of using QMED is that it is a more robust index as it is not affected by the magnitude of any extreme floods in the record.

For the Dunsop catchment, QMED is 42.5 cumecs.

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Fig.7

Fig.7 Flood frequency curve generated using the Generalized Logistic (GL) distribution and L-moments technique for fitting.

Pooling group analysis:

Since that our site (Dunsop) has a short record of annual peak values we will need the data of donor catchments to create a pooling group(See Fig 8) ,” Jessica” is chosen as name of the group.

Dunsop

Fig.8 Pooling group list Series ,consisting of approximately 500 (5*T) station years Data from similar basins, will allow us to derive the QMED and the Growth Curve(GC) whereas QMED*GC=Flood Frequency Curve . Fig.9 Catchment location The program automatically advises on the catchments having similar characteristics to the studied site (i.e. Dunsop at Footholme). Fig.8 Fig.9

As a result of the frequency curve (See Fig.7) and from the direct calculation in WINFAP, the 100 year flood is estimated to be 72 cumecs However it should be noted that; the asterisk is a reminder that the result of the single site flood frequency curve could not be sufficient for a 100 year return period and that the 95 % confidence limits have a (56.300-90.700 cumecs) flow interval, for this, a pooling group analysis is necessary.

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The pooling is done with WINFAP-FEH that automatically determines the group of sites and data from other gauging stations, with the nearest attributes of the target location.

Furthermore some stations where also deleted from the group as having short data or for being far from the site, they were omitted from the group and replaced with the next nearest ones having longer records. This was done by inspecting the discordance and diagnostic graphs.

The pooling group was then adjusted until a “possibly heterogeneous” group was achieved.

Finally the peak flow was deducted from the new Pooling group flood frequency curve for Dunsop at Footholme(See fig 10) .

Fig.10

Fig.10 Pooling group flood frequency curve showing a peak flow of 95.701 M3/s for a 100 year return period.

From the result of the FFC curve obtained from Winfap, the hydrograph(See Fig 11) was obtained for input and simulation.

0

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120

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0.5

1

1.5

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6.5 7

7.5

8

8.5

Winfap Runoff

Fig.11 . Winfap hydrograph is obtained by rescaling the values of the rainfall runoff hydrograph obtained in section 2.1, it has been rescaled (Values multiplied by 0.912 due to comparison of peak values).

Fig.11

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2.3 CONTINUOUS SIMULATION OUTPUTS-SHETRAN:

Shetran is an integrated surface and subsurface modeling system with additional features of incorporating sediment and contaminant transport.

The School of Civil Engineering and Geosciences in Newcastle University provided the FFC curve(See Fig.11) from which the peak discharge was extracted .

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60

70

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34

Ru

no

ff(C

um

ecs)

Time(Hours)

Shetran Runoff

Fig.11 Fig.11 Shetran FFC curve Shetran was run for 240 year event based on the data from 1961-1990 and the annual maxima discharges have been extracted. From the FFC curve a 100 year return period is selected to extract the corresponding annual maxima discharges of 60 cumecs.

After selecting the peak discharge of a 100 year return period, the final hydrograph(See Fig. 12) is generated for input and flood simulation.

Fig.12 Hydrograph From SHETRAN 10 years hourly time series output, a suitable length of record has been extracted which includes the peak value corresponding to 1% AEP.

Fig.12

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RAINFALL RUNOFF HYDROGRAPH

WINFAP RUNOFF HYDROGRAPH(POOLING)

WINFAP RUNOFF HYDROGRAPH(SINGLE)

SHERTAN RUNOFF HYDROGRAPH

PEAK FLOW

(CUMECS) 104.9 95.7 72 60.8

From the summary table below, it is clear that the rainfall-runoff method yielded the highest peak value of 104.9 m3/s while the continuous simulation has the lowest peak of 60.8 m3/s.

The peak of the statistical methods lie in between, but comparing the two techniques in WINFAP-FEH, the result from the pooling group (95.7 m3/s) is comparably higher than that of the single site analysis (72 m3/s) which is not a reliable value as it is resulting from only 13 years of data.

From the shape of hydrographs(See Fig 13) we can notice that the rainfall runoff and the statistical method are almost similar naturally because the Winfap was rescaled from the rainfall runoff hydrograph. However, the continuous simulation method shows a flatter graph implying a slower rise of the discharge leading to a more attenuated flooding. As for the Winfap and the Rainfall runoff the peak of flood is reached faster ,this could be resulting from the fact that the catchment have a steep slope.

Fig.13 Hydrograph comparison plot

Fig.13

2. FLOOD HYDROGRAPH GENERATION 2.4 HYDROGRAPH SUMARRY:

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3. RIVER MODELLING

3.1 MODEL CALIBRATION:

Calibration is the process of fine tuning the model; the main calibration parameter being considered in the Dunsop river model is the Manning‟s roughness coefficient

The first step after Model setup is estimating the manning coefficient and roughness of the river

It is an extremely essential task as the fluctuating manning values of any flooding project would create a large variation in results.

The given data are the time series flow upstream the river at node 1 and the related water height at Village B(See Fig 14).

The modeling of the river will be done using NOAH (Newcastle Object-oriented Advanced Hydro-informatics) software.

It is a 1 dimensional hydrodynamic model assuming flow 1D, no vertical accelerations, small bottom channel slope, hydrostatics pressure distribution, boundary friction and turbulence represented as a resistance force and uniform velocity distribution along the cross section.

The main inaccuracy in NOAH is that it cannot model flows in different directions than parallel to the downstream flow.

Fig.14

The Task is to simulate the model with various manning coefficients in order to achieve the closest given water heights at Village B.

Several trials were done and the following graph shows the various water height at village B, where the simulation is done from for the first 4 hours (0 to 36000) seconds(See Fig 15).

Fig.14 Schematic layout of the Dunsop river

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46.1

46.2

46.3

46.4

46.5

46.6

46.7

46.8

0 50000 100000 150000 200000 250000 300000 350000

Hei

ght(

m)

Time(S)

Manning Calibration Plots Given data

Manning:0.03

Manning:0.033

Manning:0.034

Manning:0.035

3. RIVER MODELLING

Fig.15 Manning calibration plots

Plots of water level in Village B with several manning trials.

The comparison with given level data led to the preliminary selection of 2 manning coefficients (0.035 and 0.034).

Fig.15

46

46.2

46.4

46.6

46.8

47

47.2

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47.6

0 50000 100000 150000 200000 250000 300000 350000 400000

Hei

ght(

m)

Time(s)

Manning Verification chart

Given Data

Manning:0.035

Manning:0.34

Manning:0.033

A further selection between the 2 values was achieved with validation and verification of the coefficients. To validate the data another time series varying from (2862000 to 3222000) seconds was considered and the same was done(See Fig 16). The end result of the selection was a manning of 0.34.

Fig.16

Fig.16 Manning calibration plots The 0.034 Manning coefficient is chosen as it was more coherent with the selected data .

An additional reason for this preference is that an increase of manning coefficient can alleviate the flooding effect ,not recommended for flood risk studies.

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3. RIVER MODELLING 3.2 MODEL SIMULATION:

48

49

50

51

52

53

54

55

56

0 1000 2000 3000 4000 5000

HEI

GH

T(M

)

CHAINAGE(M)

RAINFALL RUNOFF

WINFAP RUNOFF

SHEETRAM RUNOFF

In order to observe the effect of the derived hydrographs, a simulation of the three hydrographs with Noah was done and brought us to the expected conclusion that the highest water level in all the sections is due to the Rainfall Runoff Hydrograph.

For this, we will only consider the Rainfall Runoff Hydrograph for further stimulations and flood mitigation as it shows the worst case scenario, recommended for flood studies (See Fig.16).

Fig.16 Plot of Water Height Vs

Chainages for all three hydrographs.

Fig.16

Fig.17 Maximum water elevation for the section at Villages A and B.(Simulation prior to any intervention)

The simulation with the Rainfall Runoff Hydrograph led to flooding of 1.13 m and 1.034 m respectively for villages A and B (See Fig 17) the Winfap and Shetran hydrograph both created flooding but on a lower degree.

Fig.17

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The water level in A is 53.800 m, as for B ,it is 50.145 m.

3. RIVER MODELLING

3.2.1 RETENTION WALL CONSTRUCTION:

NEW WALL

NEW WALL

WATER LEVEL

WATER LEVEL

The banks of the river in both villages A and B were raised in a way to create a wall that stands vertically and upward on both sides of the river. The height of the wall was selected randomly in order to observe the water level of both villages after the simulation. With trial and error the wall selected had an minimum wall height that would not allow any flooding on the villages.

Fig.18 Retention wall construction for the villages at Chn 2051.000 m ,Maximum water level Value : 53.938 m Chn 3763.000 m , Maximum water level Value : 50.403 m

Fig.18

The new wall heights are 53.935 m for Village A(an increase of approximately 1.2m) and 50.50 m for village B (an increase of 1.45 m). Summary: The retention walls is a good solution for flood mitigation at villages A and B however flood still persist in the upstream and downstream sections of the villages. It is highly recommended that the new constructions are homogeneous with the surrounding landscape (See Fig 19 &20) keeping in mind a not to obstruct the interaction of the local population with the river.

Fig.19 Fig.20

Fig.19 Planted Berms are an alternative solution to walls as being more organic. However since no information is provided on the actual location of A and B it will not be wise to specify them as they need space.

Fig.20 River Retention walls

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3. RIVER MODELLING 3.2.2 RECTANGULAR SECTIONS: An attempt to canalize the river along the villages was taken into consideration in the hope of mitigating the flood. The limitation of this experiment was that the excavations of the rivers had to be done vertically as no information was provided concerning the actual location of both villages, for this reason the horizontal excavation was neglected. The second limitation is that it was necessary to respect (to a certain extent) the invert levels of both villages ,the downstream section inverts of both villages set the boundaries concerning the depth of the excavation (See Fig.21&23).

Fig.21

Fig.21 Final Invert levels

Village B Village A Bridge Section 8

Invert level:49.05

Invert level:49.1

Invert level:45.90 Invert

level:45.10

WATER LEVEL WATER LEVEL

The results of the simulation showed a minor water level attenuation of (0.136m)for village A and (0.032m) for village B(See Fig.22)

Fig.22

Fig.22 Rectangular channel construction for the villages at Chn 2051.000 m ,Maximum water level Value : 53.664 m Chn 3763.000 m , Maximum water level Value : 50.113 m

Summary:

Flooding still persist for both rivers this solution should not be taken into consideration mainly because the flood attenuation is minor, it is costly solution as it can have major environmental repercussions especially during the execution stage since that the water flow will need to be controlled upstream the excavations .

Fig.23 Final river profile

Fig.23

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3. RIVER MODELLING

3.2.3 DELETING THE BRIDGE:

An attempt to delete the bridge was made with a flood alleviation in Village A but an increase in water height in village B(See Fig 23.2).

Fig.23.2

Fig.23.2 Village A&B section after deleting the bridge Chn 2051.000 m ,Maximum water level Value : 53.02 m Chn 3763.000 m , Maximum water level Value : 50.191 m

When the bridge section was made wider to a 20 m width, water level in village A decreased to 53.286 m as for the Village B it increased to a level of 50.203 m. However when the bridge width was made 40 m inundations stopped in village A as for village B the water level kept on rising(See Fig 23.3).

Fig.23.3 Village A&B sections (40 m bridge width) Chn 2051.000 m ,Maximum water level Value : 52.681 m Chn 3763.000 m , Maximum water level Value : 50.203 m

Fig.23.3



Summary: Deleting the bridge or increasing the width of the bridge section is not an option to be considered by itself ,it solves the problem at Village A but in village B the problem is exaggerated. It may be considered as a good option if retaining walls were built along village B but again, altering the traffic circulation at the bridge will have huge cost implications since that alternative vehicular routes must be planned.

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3. RIVER MODELLING 3.2.4 WETLAND CONSTRUCTION:

Section 1

Section 2

Section 3

Village A

Bridge

Section 6

Section A

Section B

Section C

Section D

Section E

Village B

Section 8

Section 9

The concept for constructing the wetland is to divert part of the flow going through section number 2 into a wetland that will act as a storage . In order to design the wetland, five rectangular sections were created all along the new lake, this is done for the purpose of determining the width the depth and size of the storage area(See Fig.24).

WETLAND SECTIONS PROPERTIES

SECTIONA SECTION B SECTION C SECTIOND SECTION E

CHAINAGE 50 100 250 650 850

WIDTH 27 175 550 800 75

INVERT 59.05 50 50 49 52

Fig.24 Fig.24 Schematic wetland layout

At first, random inverts ,depths and chainages values were considered in order to observe the result of the simulation , these values were then adjusted to control flooding in the villages with a minimum wetland volume. The final properties of the sections (see table above) eliminated inundation in the villages and reduced the water level of 1.17 m for village A and 1.36 m for village B(See Fig.25).


Fig.25 Schematic wetland layout Chn 2051.000 m ,Maximum water level Value : 52.628 m Chn 3763.000 m , Maximum water level Value : 48.785 m

Fig.25

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3. RIVER MODELLING Summary: Connecting a wetland to the river is a good option (if the budget permits) as it provides natural flood control by dissipating river energy . It could also be a sustainable solution if planned accordingly, as it could act as an additional life system support for both humans and animals. Their is no doubt that It can play a major role in the beautification of the area(See fig 26), one of the major benefits could be an increase in ecotourism or even an additional storage capacity for irrigation of surrounding agricultural lands.

Fig.26

Fig.26 Beijing wetland project

With proper landscape planning, the wetland could even act as an artificial bioswale whenever precipitation and runoff is low, it may also have a negative slope draining excess water back to the river once the storm is over.

Fig.27

Fig.27 Vegetated Bioswale

In all cases proper measures must be taken to reduce pollution of stagnating water in a water storage situation.

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3. RIVER MODELLING 3.2.5 DIVERSION CHANEL CONSTRUCTION:

Section 1

Section 2

Section 3 Village A

Bridge

Section 6

Section A

Village B

Section 8

Section 9

Section B

A diversion channel , partially re-routing the flow from the upstream part of village A to the downstream part of village B(See Fig 28) could be a good solution for controlling the inundations at the villages.

Fig.28

Fig.28 Schematic layout of diversion channel

DIVERSION CHANEL SECTIONS PROPERTIES

SECTION A SECTION B

CHAINAGE 0 3800

WIDTH 10 10

INVERT 49.05 44.9

Fig.28 Schematic layout of diversion channel Two sections were created ,Section A and B. The purpose of those is to determine the size, depth and length of the diversion channel.

The width of the channel is chosen to be 10 m since that section number 3 width is approximately 9.18 m as for the invert levels it was selected to be compatible with the respective invert levels of 49.1 for Section number 3 and 44.9 for section number 8.(See above table, Diversion channel sections properties). The manning coefficient is kept 0.034, and the length of the new channel was considered longer that the distance between sections 3 & 8 (3022 m) to allow some flexibility in routing between the villages.

Section 3 Section 8

3800m

Fig.29

Fig.29 Longitudinal profile

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3. RIVER MODELLING The simulation in NOAH showed no inundation in village A with a water level drop of 1.4 m however in village B flooding persisted with water level attenuation of (0.2 m) . This can be attributed to the backwater effect occurring downstream(see fig 30).

Fig.30

Fig.30 Water levels at villages A and B having at: Chn 2051.000 m ,Maximum water level Value : 52.396 m Chn 3763.000 m , Maximum water level Value : 49.956 m

Summary: After simulating the model using the hydrograph resulting of Shetran, inundation in village B was controlled and flooding was stopped, for this; it will be wise to keep channel diversion as an option for flood mitigation. However special care must be taken for the control of erosion and sedimentation processes (See Fig 31) along the banks.

Fig.31 Erosion and deposition process

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Even if the channel was made of concrete, sediments accumulations will modify the roughness of the river, for this, proper maintenance must be taken into consideration.

Fig.31

4. CONCLUSION

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In this document three methods were used to generate a 100 year return period hydrograph. It is difficult to select a preferred method since that all three of them have advantages and disadvantages, however flood estimation is not an easy task mainly due to : -Lack of data. -Large variety of factors affecting water runoff. For this, it will be wise ,whenever possible, to generate hydrographs resulting from several methods in order to compare the values and deduct a reliable result. The rainfall runoff method is the most conventional, as it is based on catchment characteristics data and rainfall precipitation, it is highly beneficial especially for flood warnings as it generate a full flood hydrograph where the time to peak could provide crucial information for evacuations. The WINFEP Statistical method is a more direct method as it immediately provides information on the flow peak; if enough valid data are available; pooling will generate a Flood Frequency Curve with a more accurate peak flow estimate even for return periods beyond the recorded flood events, however only the peak values are generated in this method as no information is given for the full hydrograph. The capacity of sheetran to continuously simulate flow data of the catchment, using integrated sets of models, is extremely beneficial , this technology is rapidly developing and could become the preferred method of flood estimation. NOAH 1D is an extremely effective tool for generating hydroinformatic simulations and results, however nowadays presenting the information is as important as the information by itself and 2D or 3D images should complement the information provided by NOAH . The preferred method for flood alleviation is the construction of retaining walls, it gave good results in stopping the inundations at the villages as it is probably the most cost effective solution ; however renewing a wetland eliminated flooding at the villages and should be also considered for several socio-economic purposes.

5. APPENDICES

UH 0.0 0.5 1.0 1.5 2.0 2.5 3.0 2.7 2.3 2.0 1.7 1.4 1.0 0.7 0.4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Tot= 23 Units (cumecs/mm)

Tutorial 1132.5

Hour

Eff

Rainfall

(mm) check sum

0 0.64 0.0 0.3 0.6 1.0 1.3 1.6 1.9 1.7 1.5 1.3 1.1 0.9 0.7 0.5 0.2 0.0 0.0 0.0 0.0 0.0 0.0

1 0.90 0.0 0.4 0.9 1.3 1.8 2.2 2.7 2.4 2.1 1.8 1.5 1.2 0.9 0.6 0.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

2 1.25 0.0 0.6 1.3 1.9 2.5 3.1 3.8 3.3 2.9 2.5 2.1 1.7 1.3 0.9 0.5 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0

3 1.75 0.0 0.9 1.7 2.6 3.5 4.4 5.2 4.7 4.1 3.5 2.9 2.4 1.8 1.2 0.6 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0

4 2.42 0.0 1.2 2.4 3.6 4.8 6.1 7.3 6.5 5.7 4.9 4.1 3.3 2.5 1.7 0.9 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0

5 3.35 0.0 1.7 3.4 5.0 6.7 8.4 10.1 8.9 7.8 6.7 5.6 4.5 3.5 2.3 1.2 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0

6 4.61 0.0 2.3 4.6 6.9 9.2 11.5 13.8 12.3 10.8 9.3 7.7 6.2 4.7 3.2 1.7 0.2 0.0 0.0 0.0 0.0 0.0 0.0

7 6.25 0.0 3.1 6.2 9.4 12.5 15.6 18.7 16.7 14.6 12.6 10.5 8.4 6.4 4.4 2.3 0.2 0.0 0.0 0.0 0.0 0.0

8 7.57 0.0 3.8 7.6 11.3 15.1 18.9 22.7 20.2 17.7 15.2 12.7 10.2 7.8 5.3 2.8 0.3 0.0 0.0 0.0 0.0 0.0

9 6.25 0.0 3.1 6.2 9.4 12.5 15.6 18.7 16.7 14.6 12.6 10.5 8.4 6.4 4.4 2.3 0.2 0.0 0.0 0.0 0.0 0.0

10 4.61 0.0 2.3 4.6 6.9 9.2 11.5 13.8 12.3 10.8 9.3 7.7 6.2 4.7 3.2 1.7 0.2 0.0 0.0 0.0 0.0 0.0

11 3.35 0.0 1.7 3.4 5.0 6.7 8.4 10.1 8.9 7.8 6.7 5.6 4.5 3.5 2.3 1.2 0.1 0.0 0.0 0.0 0.0

12 2.42 0.0 1.2 2.4 3.6 4.8 6.1 7.3 6.5 5.7 4.9 4.1 3.3 2.5 1.7 0.9 0.1 0.0 0.0 0.0 0.0

13 1.75 0.0 0.9 1.7 2.6 3.5 4.4 5.2 4.7 4.1 3.5 2.9 2.4 1.8 1.2 0.6 0.1 0.0 0.0 0.0 0.0

14 1.25 0.0 0.6 1.3 1.9 2.5 3.1 3.8 3.3 2.9 2.5 2.1 1.7 1.3 0.9 0.5 0.1 0.0 0.0 0.0

15 0.90 0.0 0.4 0.9 1.3 1.8 2.2 2.7 2.4 2.1 1.8 1.5 1.2 0.9 0.6 0.3 0.0 0.0 0.0

16 0.64 0.0 0.3 0.6 1.0 1.3 1.6 1.9 1.7 1.5 1.3 1.1 0.9 0.7 0.5 0.2 0.0 0.0 0.0

Totals 49.91 0.0 0.3 1.1 2.5 4.8 8.2 13.4 20.3 29.6 41.7 55.4 69.4 82.3 92.6 98.6 99.0 94.8 87.4 77.6 66.4 54.5 42.7 31.5 21.8 14.6 9.4 5.8 3.4 1.8 0.8 0.3 0.0 0.0 0.0 0.0 1132.5

6.0 6.3 7.1 8.5 10.8 14.2 19.4 26.3 35.6 47.7 61.4 75.4 88.3 98.6 104.6 105.0 100.8 93.4 83.6 72.4 60.5 48.7 37.5 27.8 20.6 15.4 11.8 9.4 7.8 6.8 6.3 6.0 6.0 6.0 6.0

APPENDIX -A Convolution method for rainfall-runoff hydrograph

APPENDIX -B Pooled Method Graphical Results

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6. REFERENCES

Kilsby, C., 2012. CEG8515 Flood Modelling. February 2012. Newcastle University Vedrana, K., 2012. CEG8515 Flood Modelling. February 2012. Newcastle University Gomez,M,.2011. Surface Hydrology Lecture Notes. September 2011.UPC Barcelona Han, Dawei & Ventus Publishing.,2010. Concise Hydrology. ISBN 978-97-7681-3 Boughton, W., Droop, O., 2003. Continuous simulation for design flood estimation – a review. Environmental Modelling & Software 18, 309–318 . World Meteorigical organisation,1994, Guide to Hydrological practces, WMO-No. 168 http://geobytesgcse.blogspot.com/2006/11/hydrographs-and-river-discharge.html

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