ORIGINAL PAPER

Soil management and traffic effects on infiltration of irrigationwater applied using sprinklers

Hakim Boulal • Luciano Mateos •

Helena Gomez-Macpherson

Received: 1 July 2010 / Accepted: 18 November 2010 / Published online: 11 December 2010

� Springer-Verlag 2010

Abstract Zero tillage and controlled traffic have been

proposed as means for more productive and sustainable

irrigated farming. Both practices affect soil infiltration

characteristics and, therefore, should have effects on

sprinkler irrigation performance. This study compared

water infiltration and runoff in three sprinkler irrigation

tests performed on an alluvial loam soil at different times

during a maize (Zea mays L.)–cotton (Gossypium hirstium

L.) rotation under two soil managements: permanent beds

with crop residue retention (PB: planting beds maintained

unaltered from year to year) and conventional beds with

residues incorporated with tillage (CB: disc and chisel

ploughing followed by rotavator pass and bed forming

every year). Traffic was controlled and two types of fur-

rows were distinguished in both tillage systems: with (?T)

and without (-T) wheel traffic. The irrigation tests were

performed on maize at full cover, on bare soil just before

cotton sowing and on cotton with 50% ground cover.

Infiltration and runoff were affected notably by both traffic

and soil management. The soil under PB infiltrated more

water than under CB, and -T furrows more than ?T

furrows. Considering the combined treatments, -T furrows

in the CB system infiltrated more water than ?T furrows in

the PB system. A sprinkler irrigation model for simulating

water application and soil infiltration and runoff was for-

mulated. The model was used to analyse irrigation per-

formance under infiltration characteristic of the CB and PB

systems in trafficked and non-trafficked furrows. Five

irrigation performance indicators were used to assess the

various combinations of tillage and traffic: Wilkox–Swa-

iles coefficient of uniformity; application efficiency; deep

percolation ratio; tail water ratio; and adequacy. The model

was used to develop operation diagrams and provided

guidelines for making irrigation decisions in the new

controlled traffic/permanent bed system and in a standard

conventional system.

Introduction

Conservation tillage combined with controlled traffic

provides opportunities for more productive and sustain-

able farming (Tullberg et al. 2007). Conservation tillage

may enhance physical and biological soil conditions

(Hulugalle et al. 2007; Verhulst et al. 2010), save energy

by the reduction of soil preparation requirements

(Hernanz et al. 1995), improve irrigation water use

(Tennakoon and Hulugalle 2006) and, in certain envi-

ronments, double cropping is enabled by shortening the

fallow period between crops (Braunack et al. 1995;

Rawson et al. 2007).

Bed or ridge planting is widely used on irrigated land,

especially on levelled soils adapted to furrow irrigation

(Sayre and Moreno 1997). If the field is sprinkler irrigated,

bed planting is less common but sometimes used, as for

low energy precision water application (LEPA systems).

Communicated by T. Trooien.

H. Boulal � L. Mateos (&) � H. Gomez-Macpherson

Instituto de Agricultura Sostenible,

Consejo Superior de Investigaciones Cientıficas,

Alameda del Obispo, 14071 Cordoba, Spain

e-mail: ag1mainl@uco.es

H. Boulal

Departamento de Agronomıa,

Universidad de Cordoba,

Campus Universitario de Rabanales,

14071 Cordoba, Spain

123

Irrig Sci (2011) 29:403–412

DOI 10.1007/s00271-010-0245-1

The advantages of bed or ridge planting include (Unger and

Musick 1990; Sayre and Moreno 1997) the following:

better irrigation efficiency; improved traffic control;

opportunity for precision planting and for planting in moist

soil without placing the seeds too deeply; control of water

logging during germination and emergence; and potential

for decreasing erosion.

In Southern Spain, a combination of sprinkler irriga-

tion and a permanent bed planting system with con-

trolled traffic has been developed successfully at a

commercial farm in the Guadalquivir Valley (Gomez-

Macpherson et al. 2009). In this new system, maize and

cotton crops are rotated on permanent beds, crop resi-

dues are maintained mostly in the bottom of furrows (to

where they are displaced mechanically before planting)

and controlled wheel traffic is followed during all

operations. The aim is maintaining crop residues on the

soil surface and restricting tillage to furrows that are

compacted, i.e., trafficked furrows are deep-ripped when

excessive compaction is observed only, which happens

particularly if cotton harvest takes place when the soil is

wet due to early autumn rains.

An initial evaluation of the new system showed a

tendency for reducing required applied irrigation without

yield penalty (Gomez-Macpherson et al. 2009). Effec-

tively, transformation into a permanent raised bed system

and cumulating crop residues in the furrow bed is

expected to enhance infiltration (Boulal et al. 2008) and

reduce soil evaporation. On the other hand, infiltration in

trafficked furrows would be expected to be less than in

non-trafficked ones, as it has been reported in furrow

irrigation experiments (Kemper et al. 1982; Allen and

Musick 1992; Undersander and Regier 1988). Therefore,

the innovative soil management system described earlier

has implications on irrigation water infiltration and run-

off—and thus on irrigation performance—that must be

examined before providing irrigation advice. Further-

more, the infiltration variability introduced by controlled

traffic (that compacts wheel furrows while non-trafficked

furrows remain unaltered) adds to the natural variability

of the infiltration characteristics of irrigated land

(Oyonarte et al. 2002), which in turn depends on the soil

management system.

The objectives of this research were, firstly, to assess

experimentally the effects of permanent beds versus con-

ventional-till beds, both with controlled traffic, on sprinkler

irrigation infiltration and runoff, and, secondly, to simulate

sprinkler irrigation performance under the soil conditions

derived from the previously compared soil managements.

Complementarily, the paper also provides diagrams for the

operation of irrigation (determination of water depth and

application rate) under conventionally tilled and permanent

raised bed systems, the last under controlled traffic.

Materials and methods

Experimental field, tillage systems and controlled

traffic

The tests were performed at the Alameda del Obispo

experimental farm (latitude 38�N, longitude 5�W, altitude

110 m), Cordoba, Spain. The climate is Mediterranean

with mean annual rainfall of 595 mm. The soil at the

experimental farm was a Typic Xerofluvent (Soil Survey

Staff 2010), with loam texture, and without apparent

restriction for root growth to 3 m depth. Estimated water

content at field capacity was 0.24 cm3 cm-3, and at wilting

point, 0.12 cm3 cm-3. Typical irrigation depth in this soil

is 80 mm. Greater depths lead to significant runoff due to

infiltration restrictions caused by soil surface sealing.

The experimental field (144 9 54 m) was divided into

three 144-m-long, 18-m-wide blocks (replications).

A cotton (Gossypium hirstium L.)–maize (Zea mays L.)–

cotton rotation was followed in an experimental field dur-

ing 2007, 2008 and 2009 with clean fallow periods between

crops. The field was ploughed (a double pass of discs, a

single pass of chisel and a single pass of rotavator) on 20

April 2007, and beds were put in place three days later.

Cotton was sown on 9 May and hand-picked on 27 Sep-

tember of the same year; 4 months after the cotton harvest,

the standing residues were chopped. In February 2008,

each of the three blocks was divided into two plots, each

consisting of ten 0.85-m-spaced furrow/bed sets, and two

tillage treatments, permanent beds system (PB) and con-

ventional beds system (CB), were established using a

randomised block experimental design with three replica-

tions. In the PB system, crop residues were left on the soil

surface after harvest, and the planting beds were main-

tained unaltered from year to year; in the CB system, the

soil was ploughed and crop residues incorporated, and the

beds formed every year. The CB plots were then ploughed

(a double pass of discs followed by a single pass of chisel)

and the beds formed (on 13 February 2008). Maize was

sown on 19 March 2008 and machine harvested on 17

September 2008. In late February 2009, crop residues were

chopped and left on the soil surface in PB while, in CB,

they were incorporated in the soil (a pass of chisel followed

by rotavator) before forming the beds on 16 March 2009. A

second cotton crop was sown on 14 May and hand-picked

on 29 September 2009.

Traffic was controlled. Since the separation between

tractor wheels was 1.70 m, twice the separation between

furrows, furrows with wheel traffic (?T) alternated with

furrows without (-T). In PB, non-traffic furrows (PB-T)

were not travelled by wheels during the whole experi-

mental period. In CB, soil was tilled every year but,

nonetheless, the two types of furrows were demarcated

404 Irrig Sci (2011) 29:403–412

123

after the beds were formed, that is, CB-T furrows were not

travelled during the season until soil preparation the fol-

lowing year.

Not all trafficked furrows supported the same number of

tractor wheel passes: all ?T furrows supported soil culti-

vation, sowing, residues chopping and harvesting opera-

tions, while only some were travelled also when spraying

the crop. The number of wheel passes per year in trafficked

furrows was between 5 and 9.

Irrigation tests

Three sprinkler irrigation tests were carried out in the

central block of the experimental field on the following

dates: 6 August 2008 (Test 1), when the maize crop was

close to maturity; 23 April 2009 (Test 2), with bare soil

recently prepared for cotton sowing; and 13 July 2009

(Test 3), when the cotton crop had an average ground cover

of 50%.

The slope of the test block was 0.8%. Three irrigation

laterals were used, two along the borders of the block and

the third down the centre. Laterals were spaced 9 m with

sprinklers at 12 m. The sprinklers (VYR-60) had two

nozzles of 4.36 and 2.38 mm in diameter. The sprinklers

reached 24 m and discharged 1,560 L h-1, at a pressure of

3.45 kg cm-1. The sprinklers in the laterals along the

border were set to operate with an angle of 1808, with the

wet semicircle towards the test block.

Applied depth was measured using 40 catch containers

distributed in five transects across the block. An ane-

mometer installed next to the experimental field automat-

ically recorded wind speed and direction during the

irrigation tests. Application rate varied slightly from test to

test: 0.28, 0.26 and 0.30 mm min-1 in Tests 1, 2 and 3,

respectively. The duration of the three irrigation tests were

as follows: 745 min (Test 1), 300 min (Test 2) and

513 min (Test 3).

Runoff rate was measured periodically using long-

throated flumes of trapezoidal cross-section with sill width

equal to 100 mm (Clemmens et al. 1984). The flumes were

installed near the tail of every furrow (132 m from the

head) except borders, i.e., there were 8 monitored furrows

per treatment, 4 in non-traffic furrows and 4 in traffic

furrows. The replications of CB?T and CB-T that were

located at the eastern side of the experimental block were

discarded in Test 2 due to wind blowing from the east that

reduced precipitation rate on those furrows. In fact, Test 2

lasted 5 h only because of wind persistence.

Cumulative infiltration was obtained from the difference

between water application (obtained from measured aver-

age applied depth and irrigation time) and runoff.

Note that the irrigation tests were performed in the central

block of the experiment. Therefore, the randomised block

design was not applicable to the statistical analysis of infil-

tration and runoff data. However, having 8 controlled fur-

rows (four trafficked and 4 non-trafficked) in the two soil

management plots allowed performing statistical analysis

based on the factorial approach (Snedecor and Cochran

1980), with two factors: soil management (PB or CB) and

furrow traffic (-T or ?T), and four replications (furrows)

per treatment. Pairwise comparison tests of infiltration,

runoff and time to runoff initiation for the soil management

and traffic treatments were performed using the freeware

statistical analysis program Statistix 9 (http://www.statistix.

com/).

Irrigation performance simulation

Several sprinkler irrigation simulation models have been

reported in the literature (e.g., Carrion et al. 2001; Mateos

1998; Andrade and Allen 1999). All of them dealt with

water distribution but not with infiltration once water

reaches the soil, making them unsuitable for the purpose of

this study. Therefore, a new model that simulates sprinkler

irrigation in two steps, (1) application and (2) infiltration,

was developed.

The simulated field application distribution resulted

from overlapping the precipitation patterns of individual

sprinklers in a fixed system. The sprinklers were VYR-60

as those used in the experimental study. The sprinkler

laterals were spaced 11.9 m (14 furrows separated 0.85 m)

and the sprinklers along the laterals, 12 m. The distribution

pattern of single sprinklers was assumed to match shape 3

of Appendix A in Mateos (1998). The application rate was

calculated at 1-m intervals along each furrow in each

simulated field.

The hypothetical field consisted of alternating traffic and

non-traffic furrows. Both permanent and conventional bed

systems were simulated.

When infiltration was supply controlled (i.e., while the

application rate was less than the potential infiltration rate),

cumulative infiltration (I, mm) was calculated as the

application rate (r, mm min-1) times the irrigation time (t,

min). Once the application rate exceeded the potential

infiltration rate (which occurred at time t = tro, being trothe time to runoff initiation), I resulted from adding to the

cumulative infiltration at tro (i.e., r 9 tro) the difference

between cumulative infiltration at the time considered and

cumulative infiltration at tro. Using Horton’s equation,

I was expressed as:

I ¼ rt if t\tro ð1aÞ

Irrig Sci (2011) 29:403–412 405

123

I¼ rtroþ if t� troð Þþ r0 � ifk

e�k tro�t0roð Þ�e�k t�t0roð Þh i

if t� tro

ð1bÞ

where r (mm min-1) is the application rate for a particular

simulation; r0 (mm min-1) is the application rate during the

experimental test used for adjusting the parameters in

Horton’s equation; t0ro (min) is the time at which runoff

started during that experimental test; if (mm min-1) is the

steady-state potential infiltration rate; and k is a dimen-

sionless soil parameter that describes the rate of decrease in

potential infiltration rate.

An infiltration equation was assigned to each 1-m fur-

row segment. Furrow-averaged if was generated randomly

using the Monte Carlo method assuming a normal fre-

quency distribution with mean and standard deviation

obtained in the experimental tests. Furrow segment if was

generated using the same method although entering in the

simulation of random values the previously obtained fur-

row-averaged if and a standard deviation obtained in the

same experimental field by Oyonarte et al. (2002). Since

t0ro presented some correlation with if (Fig. 1), for sim-

plicity, t0ro was calculated from if. Note that data from Test

2 were not used in this relationship because irrigation time

in this test was not long enough for the infiltration rate

achieving steady state. The parameter k was then computed

for each furrow segment as:

k ¼ 1

t0roln

io � if

r0 � ifð2Þ

where io (mm min-1) is the initial potential infiltration rate.

For simplicity, a constant value of io = 1 mm min-1 was

chosen for all furrow types after fitting all experimental

data simultaneously.

Cumulated runoff was calculated over time and for each

simulated furrow by adding, if positive, the difference

between application rate and infiltrability in each furrow

segment.

Five irrigation performance indicators were then com-

puted: Wilkox–Swailes coefficient of uniformity

(WSCU = 1 - CV, with CV the coefficient of variation of

infiltrated depth; Wilcox and Swailes 1947); application

efficiency (AE); deep percolation ratio (DPR); tail water

ratio (TWR); and, adequacy (Ad). AE is defined as the

fraction of applied water stored in the root zone. DPR and

TWR are the fractions of applied water going to percola-

tion and tail water runoff, respectively. Adequacy, Ad, is

the fraction of the root zone that is filled to field capacity

with irrigation water. The numerator of DPR was calcu-

lated by cumulating the values of the positive differences

between the infiltrated depths and the required depth (Dreq).

WSCU was computed for both applied water (WSCUapp)

and infiltrated water (WSCUinf).

AE and Ad are key irrigation performance indicators

that are widely used (e.g., Burt et al. 1997). DPR and TWR

are suitable indicators for determining the fate of water

losses (Walker and Skogerboe 1987). Uniformity is com-

monly expressed as distribution uniformity based on the

low-quarter depth (Burt et al. 1997); however, WSCU was

preferred because it has more statistical meaning than other

uniformity indicators (Mateos 2006).

Operation diagrams were produced by running the

model multiple times, varying application depths and rates,

and computing the five performance indicators. Isolines of

selected values of the performance indicators were gener-

ated by triangulation with linear interpolation, using the

Surfer 9.2 surface mapping software (Golden Software

Inc., Golden, Colorado, US).

Results and discussion

Experimental results

In Test 1, cumulative infiltration increased more rapidly in

furrows with no wheel traffic than with traffic and more

rapidly in PB than in CB. Thus, at the end of the test, the

total cumulative infiltration was highest in PB-T and

lowest in CB?T (Table 1). Comparison assuming a 2 9 2

factorial design showed that the difference between

cumulative infiltration at the end of the test was statistically

significant for both tillage systems (P \ 0.05) and furrow

traffic (P \ 0.01). Interestingly, wheel traffic resulted in

similar infiltration in PB?T, after 2 years of traffic and

leaving crop residues on the soil surface, and in CB?T,

after only 1 year of operations but incorporating residues in

the soil (158 and 149 mm, respectively).

In Test 2, when irrigation was applied on bare soil just

before cotton sowing, the effect of the tillage system was

t' ro (min) = 2533.3 i f (mm min-1

) - 117.37

r2 = 0.6062

0

100

200

300

400

500

600

700

0.05 0.10 0.15 0.20 0.25

Final infiltration rate (mm min-1)

Ru

no

ff in

itia

tio

n t

ime

(min

)

Test 1

Test 3

Fig. 1 Relationship between the time to runoff initiation and the

steady-state potential infiltration rate during Test 1 and Test 3

406 Irrig Sci (2011) 29:403–412

123

evident in trafficked furrows but inappreciable in non-

trafficked ones: CB?T produced considerable runoff,

while CB-T did not produce any runoff; PB?T produced

little runoff and PB-T did not produce any runoff

(Table 1). Irrigation duration in Test 2 was only 5 h, the

shortest of the three tests (Table 1), due to excessive wind.

It is likely that longer irrigation duration would have pro-

duced some runoff in non-trafficked furrows also. Despite

its short duration, however, the test was capable of

detecting statistically significant infiltration increases as a

consequence of either having permanent beds or preventing

wheel traffic (P \ 0.05 and P \ 0.01, respectively).

In Test 3, where crop cover was 50%, the infiltration rate

was smaller and runoff initiation began earlier than in Test

1 (Table 1). Otherwise, the four tillage–traffic combina-

tions were similar in both tests. At the end of Test 3

(duration 513 min), the trafficked furrows had accumulated

25 and 33% less infiltration than the non-trafficked furrows

in PB and CB, respectively (differences significant at

P \ 0.01); and the CB system had cumulated 21 and 12%

less infiltration than the PB system in ?T and -T,

respectively (differences significantly different with

P \ 0.01).

It is important to note that in none of the three tests was

a tillage system/furrow traffic interaction detected.

Runoff starting time varied from test to test (Table 1). If

we look first at the tests performed in the presence of a crop

(Tests 1 and 3), runoff started later under the maize crop

than under the cotton (Table 1). Application rate was

slightly greater during Test 3, which may explain at least

part of this difference. However, final infiltration rate was

greater in Test 1 than in Test 3 in all treatments except

PB-T, and therefore, factors other than application rate

differentiated these two tests.

Residues in the furrows should retard water runoff and

facilitate infiltration (Green et al. 2003). In our case, the

amount of residues on the PB furrows was greater during

Test 3 than during Test 1 (maize produced more residues

than cotton) but its benefits might have been cancelled by

reduced infiltration with surface compaction in PB?T.

Because of their dissimilar architecture, one could

expect that maize plants would concentrate on the plant

bed more precipitation than cotton plants (Bui and Box

1992; Dekker and Ritsema 1997; Levia and Frost 2003). If

infiltration rate on the plant bed was greater than on the

furrow bottom (Paltineanu and Starr, 2000), then infiltra-

tion under maize would be greater than under cotton,

explaining differences between Tests 1 and 3.

Additionally, soil conditions were likely different in

Tests 1 and 3. Untouched furrows (PB-T) maintained their

final infiltration rate; but final infiltration rate decreased in

PB?T and CB from Tests 1–3. Tillage and wheel traffic

history must have affected final infiltration rate in PB?T

and CB, but our data were insufficient to discern the par-

ticular physical mechanisms that operated in the soil in

these treatments.

Irrigation performance simulation results

Simulations were run for the soil conditions in Test 3.

Simulated cumulated infiltrations for the four tillage/traffic

combinations were 121, 153, 99 and 129 mm in PB?T,

PB-T, CB?T and CB-T, respectively. The similarity of

these values with the corresponding measured values

(Table 1) gave confidence for using the model to simulate

alternative irrigation conditions.

Table 2 presents the selected performance indicators

computed for four irrigation conditions: relatively low and

high application rates (0.15 and 0.4 mm min-1) combined

with two applied depths (D, mm). The depths were D = 76

and D = 137 mm, the first being close to the required

depth (80 mm) and the second 70% higher than the

Table 1 Irrigation duration,

time to runoff initiation (t0ro),

total runoff, total infiltration and

steady-state potential infiltration

rate (if) in the four combination

of tillage (permanent bed, PB,

and conventional bed, CB,

systems) and furrow wheel

traffic (with traffic, ?T, and

without traffic, -T) tested

Values are average; standard

errors are in brackets

Test Duration

(min)

Treatment t0ro(min)

Runoff

(mm)

Infiltration

(mm)

if(mm min-1)

Test 1 745 PB?T 188 (24) 53 (8) 158 (8) 0.20 (0.02)

PB-T 608 (108) 8 (3) 202 (3) 0.23 (0.01)

CB?T 241 (30) 61 (14) 149 (14) 0.13 (0.03)

CB-T 433 (98) 23 (13) 182 (13) 0.19 (0.02)

Test 2 300 PB?T 113 (1) 4 (1) 72 (1) 0.24 (0.02)

PB-T – – 77 (0) –

CB?T 112 (15) 19 (8) 58 (8) 0.14 (0.03)

CB-T – – 77 (0) –

Test 3 513 PB?T 189 (35) 46 (21) 110 (21) 0.13 (0.08)

PB-T 412 (46) 13 (9) 147 (10) 0.23 (0.07)

CB?T 120 (8) 69 (24) 87 (24) 0.10 (0.07)

CB-T 290 (54) 26 (7) 130 (7) 0.14 (0.04)

Irrig Sci (2011) 29:403–412 407

123

required depth. Simulations were run for these four irri-

gation conditions and the four possible tillage/traffic

combinations as well as alternating furrows-type combi-

nations (PB-T?T and CB-T?T).

Simulated WSCUapp was 0.957, a constant value for the

sprinkler type and layout used. WSCUapp was equal to

WSCUinf only in PB-T, the treatment where infiltration was

most favoured, and in CB-T with D = 76 mm. With low r,

low applied depth and high soil infiltration capacity, infil-

tration tends to be supply controlled, and therefore, infiltra-

tion uniformity is basically determined by the application

distribution uniformity. At the extreme, infiltration unifor-

mity equals application distribution uniformity.

Conversely, infiltration is soil controlled with high r,

high D and low soil infiltration capacity. Under these

irrigation conditions, infiltration uniformity is determined

by the variability of soil hydraulic properties, the shape of

the potential infiltration rate curve, and the application

distribution uniformity. [Note that for homogeneous water

application, high or relatively high r (thus r [ if) and long

irrigation duration, infiltration variability would tend to

equal the variability of if.] Therefore, in these circum-

stances, irrigation infiltration uniformity is the result of the

combined effects of irrigation and soil management.

Moreover, controlled traffic introduces further variation.

In consequence, the lowest WSCUinf of the four irrigation

conditions compared in Table 2 occurred in CB-T?T with

r = 0.40 mm min-1 and D = 137 mm (WSCUinf =

0.837). Observe that this uniformity was lower than the

uniformity for the same planting system and irrigation con-

ditions with either all trafficked (CB?T) or non-trafficked

furrows (CB-T).

When infiltration is predominantly supply controlled, a

great part of the applied water infiltrates and little runoff is

produced. DPR becomes important when D is high, and

even more when combined with low r as in the case of

r = 0.15 mm min-1 and D = 137 mm in Table 2. In these

conditions, the soil basically did not intervene in the

Table 2 Infiltration Wilkox–Swailes coefficient of uniformity

(WSCUinf); application efficiency (AE); deep percolation ratio

(DPR); tail water ratio (TWR); and adequacy (Ad) for the four

irrigation conditions resulting from combining application rates 0.15

and 0.4 mm min-1 and applied depths 76 and 137 mm, and two soil

managements (permanent, PB, and conventional beds, CB) either

with only one type of furrow wheel traffic (?T) or without (-T) or

with both types (?T-T)

WSCUinf AE

0.15,76 0.15,137 0.40,76 0.40,137 0.15,76 0.15,137 0.40,76 0.40,137

PB-T 0.957 0.957 0.957 0.958 0.995 0.585 0.995 0.585

PB?T 0.937 0.912 0.930 0.882 0.971 0.584 0.957 0.582

PB-T?T 0.943 0.920 0.937 0.871 0.983 0.585 0.976 0.584

CB-T 0.957 0.944 0.957 0.922 0.990 0.585 0.982 0.585

CB?T 0.910 0.895 0.902 0.865 0.895 0.584 0.869 0.573

CB-T?T 0.913 0.878 0.903 0.837 0.942 0.584 0.926 0.579

DPR Ad

0.15,76 0.15,137 0.40,76 0.40,137 0.15,76 0.15,137 0.40,76 0.40,137

PB-T 0.005 0.415 0.005 0.395 0.946 1.000 0.946 1.000

PB?T 0.002 0.341 0.001 0.223 0.922 1.000 0.910 0.996

PB-T?T 0.004 0.378 0.003 0.309 0.934 1.000 0.928 0.998

CB-T 0.003 0.381 0.002 0.270 0.940 1.000 0.933 1.000

CB?T 0.000 0.219 0.000 0.092 0.850 0.999 0.826 0.981

CB-T?T 0.002 0.300 0.001 0.181 0.895 1.000 0.880 0.990

TWR

0.15,76 0.15,137 0.40,76 0.40,137

PB-T 0.000 0.000 0.000 0.020

PB?T 0.027 0.075 0.042 0.195

PB-T?T 0.013 0.037 0.021 0.107

CB-T 0.007 0.034 0.016 0.145

CB?T 0.105 0.197 0.131 0.335

CB-T?T 0.056 0.116 0.073 0.240

408 Irrig Sci (2011) 29:403–412

123

control of infiltration in the treatment where infiltration was

most favoured (PB-T). On the contrary, under predomi-

nantly soil-controlled infiltration, high D and r will

increase runoff. TWR was insignificant in PB-T and

highest in CB?T with r = 0.40 mm min-1 and

D = 137 mm. In the controlled traffic systems (-T?T),

TWR took intermediate values between the corresponding

hypothetical systems with all furrows either trafficked

(?T) or non-trafficked (-T) (Table 2).

As expected, the two irrigation variables (r and D) pri-

marily affected AE. AE took high values when D = 76 mm

and a low but constant value when D = 137 mm but,

interestingly, AE was little affected by soil management. In

the soil management treatments in which deep percolation

was important, runoff was insignificant, and vice versa, when

runoff was important deep percolation was insignificant,

resulting therefore in similar AE (Table 2).

Globally, Ad was high (Table 2). Only the CB?T and

CB-T?T treatments with D = 76 mm resulted in

Ad \ 0.9. Given the infiltration limitation due to the soil

surface conditions, an applied depth of 76 mm was insuf-

ficient to fill the soil profile up to field capacity.

The simulation results discussed earlier helped to under-

stand the interaction between soil and irrigation management

but were restricted to very specific conditions. More practical

simple calculations (done using common computer spread-

sheets) can be used to develop operation diagrams for irri-

gation management under different soil management

systems. Example diagrams are presented in Figs. 2, 3 and 4

for the new permanent bed/controlled traffic system

(PB?T-T) and for the extended conventional bed system

(CB?T). The soil conditions were the same as in the

experimental field and the sprinkler spacing as in the previ-

ous simulations. The operation diagrams were developed for

practical ranges of application rate and applied depth and for

a required depth equal to 80 mm. This depth is appropriate

for the deep loamy soils of the Guadalquivir valley and

practical for summer crops in this climate since it results in

irrigation intervals between 10 and 15 days and in irrigation

durations typically between 6 and 8 h. The diagrams present

isolines for WSCUinf, TWR and DPR (Figs. 2, 3 and 4,

respectively). Grey colour indicates the region in the dia-

grams where adequacy is less than 0.95 and, therefore, the

combinations of operation variables that should be avoided if

deficit irrigation is not desired. The un-shaded area repre-

sents the conditions of adequate irrigation.

An example of how the diagrams may be used follows. In

either PB?T-T or CB?T, maximum uniformity may be

achieved with low application rate only (Fig. 2). In addition,

adequate irrigation in CB?T may be achieved with values of

D close to the required depth only if r is small (Fig. 2b).

However, farmers prefer application rates that allow com-

pleting the irrigation in a short time. For instance, applying

90 mm at a rate of 0.15 mm min-1 would take 10 h but the

same depth applied at 0.25 mm min-1 would take 6 h only

(points marked with 9 in Figs. 2, 3, 4). In CB?T, the

reduction of irrigation time would be at the cost of increasing

TWR from 0.13 to 0.19 and entering into the grey region

where irrigation is inadequate (Fig. 3b); on the other hand,

deep percolation would be slightly reduced, from 0.03 to

about 0.02 (Fig. 4b). The farmer would then need to take

environmental considerations in the decision: First, will the

Fig. 2 Isolines of the Wilkox–Swailes coefficient of uniformity for

infiltrated water (WSCUinf) in the applied depth-application rate plan

for a the controlled traffic and permanent bed system (PB-T?T) and

b the conventional bed system (CB?T). Grey area indicates the

region where adequacy is less than 0.95, assuming required depth is

80 mm. Sprinklers spacing: 11.9 9 12 m; sprinkler type: VYR-60

Irrig Sci (2011) 29:403–412 409

123

runoff rate cause erosion if r = 0.25 mm min-1? Second, is

preserving groundwater more important than preserving

surface water?

The answer to the first question would be positive more

likely under CB?T than under PB?T-T. Moreover, the

same combination of r and D in PB?T-T would result in

lower TWR and higher DPR than in CB?T. Given that

PB?T-T should cause less erosion than CB?T, r could be

further increased because for D & 90 mm DPR is rather

insensitive to r, and it will take a constant value of about

0.09 (Fig. 4a). By increasing r, TWR would increase

slightly (Fig. 3a), but irrigation duration would reduce

proportionally to the increase in r while WSCUinf would

stay in the interval 0.92–0.93 (Fig. 2a).

Although r may be varied within certain limits by modi-

fying working pressure or substituting sprinkler nozzles, the

Fig. 3 Isolines of the tail water ratio (TWR) in the applied depth-

application rate plan for a the controlled traffic and permanent bed

system (PB-T?T) and b the conventional bed system (CB?T). Greyarea indicates the region where adequacy is less than 0.95, assuming

required depth is 80 mm. The two 9 marks in each figure indicate the

location of the points discussed in the text. Sprinklers spacing:

11.9 9 12 m; sprinkler type: VYR-60

Fig. 4 Isolines of the deep percolation ratio (DPR) in the applied

depth-application rate plan for a the controlled traffic and permanent

bed system (PB-T?T) and b the conventional bed system (CB?T).

Grey area indicates the region where adequacy is less than 0.95,

assuming required depth equal to 80 mm. The two 9 marks in each

figure indicate the location of the points discussed in the text.

Sprinklers spacing: 11.9 9 12 m; sprinkler type: VYR-60

410 Irrig Sci (2011) 29:403–412

123

range of variation is narrow unless sprinkler spacing is

modified. But if so, the application distribution pattern would

change. We acknowledge that the r-D region represented in

the operation diagrams goes beyond what in reality may be

achieved without modifying the sprinkler spacing.

Conclusions

Infiltration and runoff were affected notably by traffic and

soil management. More water infiltrated the soil in per-

manent than in conventionally tilled beds that are reformed

each year. Regardless of tillage system, water infiltration

was reduced by traffic.

Therefore, irrigation management practices that have

been identified as appropriate for a soil management that

does not introduce soil infiltration variation across the field

should not be applied under this new system of permanent

beds with controlled traffic. Controlled traffic is an addi-

tional source of infiltration variability that complicates

identifying the best irrigation management practice for

given soil management conditions.

Farmers have to evaluate sprinkler irrigation conditions

(namely application rate and duration) that lead to irriga-

tion adequacy and application efficiency. Moreover, simi-

lar application efficiency may be achieved either by

minimising deep percolation or tail water runoff. And,

therefore, the decision has to balance the environmental

effects of each scenario. The operation diagrams developed

as part of this study provide technically sound guidelines

for making such decisions for both conventionally tilled

and permanent raised bed systems with controlled traffic.

Acknowledgments This research was funded by a grant from the

Spanish Ministry of Education and Science, project AGL2005-05767.

H. Boulal received a grant from the Spanish Agency of International

Cooperation and Development (AECID). We thank I. Carmona, M.

Salmoral, R. Luque, A. Cornejo and O. Medina for field assistance.

References

Allen RR, Musick JT (1992) Furrow traffic and ripping for control of

irrigation intake. Trans ASAE 8:243–248

Andrade CLT, Allen RG (1999) SPRINKMOD—pressure and

discharge simulation model for pressurized irrigation systems

1. Model development and description. Irrig Sci 18:141–148

Boulal H, Gomez-Macpherson H, Gomez JA (2008) Water infiltration

and soil losses in a permanent bed irrigated system in Southern

Spain. 10th Congress of the European society for agronomy,

15–19 September 2008, Bologna, Italy. Italian J Agron 3:45–46

Braunack MV, McPhee JE, Reid DJ (1995) Controlled traffic to

increase productivity of irrigated row crops in the semi-arid

tropics. Aust J Exp Agric 35:503–513

Bui EN, Box JE (1992) Stemflow, rain throughfall, and erosion under

canopies of corn and sorghum. Soil Sci Soc Am J 56:242–247

Burt CM, Clemmens AJ, Strelkoff TS, Solomon KH, Bliesner RD,

Hardy LA, Howell TA, Eisenhauer DE (1997) Irrigation

performance measures: efficiency and uniformity. J Irrig Drain

Eng 123:423–442

Carrion P, Tarjuelo JM, Montero J (2001) SIRIAS: a simulation

model for sprinkler irrigation. Irrig Sci 20:73–84

Clemmens AJ, Bos MG, Replogle JA (1984) Portable RBC flumes for

furrow and earthen channels. Trans ASAE 27:1016–1026

Dekker LW, Ritsema CJ (1997) Effect of maize canopy and water

repellency on moisture patterns in a Dutch black plaggen soil.

Plant Soil 195:339–350

Gomez-Macpherson H, Boulal H, Mrabet R, Gonzalez E (2009)

Rational and application of CA for irrigated production in

Southern Europe and North Africa. Proceedings of the 4th world

congress on conservation agriculture, 4–7, February 2009, New

Delhi, India, pp 129–135

Green TR, Ahuja LR, Benjamin JG (2003) Advances and challenges

in predicting agricultural management effects on soil hydraulic

properties. Geoderma 116:3–27

Hernanz JL, Giron VS, Cerisola C (1995) Long-term energy use and

economic evaluation of three tillage systems for cereal and

legume production in central Spain. Soil Tillage Res 35:183–198

Hulugalle NR, McCorkell BE, Weaver TB, Finlay LA, Gleeson J

(2007) Soil properties in furrows of an irrigated Vertisol sown

with continuous cotton (Gossypium hirsutum L.). Soil Tillage

Res 97:162–171

Kemper WD, Ruffing BJ, Bondurant JA (1982) Furrow intake rates

and water management. Trans ASAE 25:333–339, 343

Levia DF, Frost EE (2003) A review and evaluation of stemflow

literature in the hydrologic and biogeochemical cycles of

forested and agricultural ecosystems. J Hydrol 274:1–29

Mateos L (1998) Assessing whole field uniformity of stationary

sprinkler irrigation systems. Irrig Sci 18:73–81

Mateos L (2006) A simulation study of comparison of the evaluation

procedures for three irrigation methods. Irrig Sci 25:75–83

Oyonarte NA, Mateos L, Palomo MJ (2002) Infiltration variability in

furrow irrigation. J Irrig Drain Eng 128:26–33

Paltineanu IC, Starr JL (2000) Preferential water flow through corn

canopy and soil water dynamics across rows. Soil Sci Soc Am J

64:44–54

Rawson HM, Gomez-Macpherson H, Hossain ABS, Saifuzzaman M,

ur-Rashid H, Sufian MA, Samad MA, Sarker AZ, Ahmed F,

Talukder ZI, Rahman M, Siddique MMAB, Ammin M (2007)

On-farm wheat trials in Bangladesh: a study to reduce perceived

constraints to yield in traditional wheat areas and southern lands

that remain fallow during the dry season. Expl Agric 43:21–40

Sayre KD, Moreno OH (1997) Application of raised-bed planting

systems to wheat. Wheat Special Report no 31. CIMMYT,

Mexico DF

Snedecor GW, Cochran WG (1980) Statistical methods, 7th edn. The

Iowa State University Press, Ames

Staff SoilSurvey (2010) Keys to soil taxonomy, 11th edn. United

State Department of Agriculture, Natural Resources Conserva-

tion Service, Washington DC

Tennakoon SB, Hulugalle NR (2006) Impact of crop rotation and

minimum tillage on water use efficiency of irrigated cotton in a

vertisol. Irrig Sci 25:45–52

Tullberg JN, Yule DF, McGarry D (2007) Controlled traffic

farming—From research to adoption in Australia. Soil Tillage

Res 97:272–281

Undersander DJ, Regier C (1988) Effect of tillage and furrow

irrigation timing on efficiency of preplant irrigation. Irrig Sci

9:57–67

Unger PW, Musick JT (1990) Ridge tillage for managing irrigation

water on US Southern Great Plains. Soil Tillage Res 18:267–282

Irrig Sci (2011) 29:403–412 411

123

Verhulst N, Govaerts B, Verachtert E, Castellanos-Navarrete A,

Mezzalama M, Wall P, Deckers J, Sayre KD (2010) Conserva-

tion agriculture, improving soil quality for sustainable produc-

tion systems? In: Lal R, Stewart BA (eds) Advances in soil

science: food security and soil quality. CRC Press, Boca Raton,

pp 137–208

Walker WR, Skogerboe GV (1987) Surface irrigation. Theory and

practice. Prentice Hall, Englewood Cliffs

Wilcox JC, Swailes GE (1947) Uniformity of water distribution by

some undertree orchard sprinklers. Sci Agric 127:565–583

412 Irrig Sci (2011) 29:403–412

123