LONG-FURROW IRRIGATION SYSTEM PERFORMANCE UNDER THE CONDITIONS OF NORTH AND SOUTH SINAI-EGYPT

Document Type : Original Article

Abstract

ABSTRACT
Field experiments were conducted along two successive seasons of summer 2012 and 2013 at two private farms located in the Sinai Peninsula of Egypt. The first field is denoted as (F1) located in South Sinai, Ras Sudr; and the second field denoted as (F2) located in NorthSinai, El Tina Plain, to estimate the potential implement development of surface irrigation approaches in the North and South Sinai for forage sorghum production. The experiments carried out in a randomized complete block design with four replicates. Each experiment contains two longitudinal soil surface slopes (0.1 and 0.16%) namely: S1, and S2, respectively, and two irrigation water inflow rates were represented q1, and q2 as in an average of 180 and 108 liter min-1 furrow-1, respectively.The irrigation performance was evaluated through application efficiency (AE%), low-quarter distribution uniformity (DUlq) and deep percolation percent (Dp%).Furrow irrigation management, operation, and some design variables (Inflow discharge, furrow slope, and irrigation cutoff time) were correlated which estimated related to water management by studding different treatments in both sitesusing WinSRFR 4.1.3, Program. Average yield of forage sorghum and crop water productivity (CWP) were estimated.
The obtained results indicated that under the conditions of each farm, the AE% was directly proportional to the length of the run and inversely proportional to the inflow discharge and the time of irrigation cutoff where q2 obtained the highest average values 93.1 and 93.8% with F1S1 and F2S2 treatments, respectively. The Minimum average values of DP% obtained by q2, it was 6.9 and 6.2% with F1S1 and F2S2treatments, respectively. The highest average values of DUlq obtained by S1, it were 0.85 and 0.83 with F1q1 and F2q2 treatments, respectively. The highest average values of forage sorghum yield obtained 59464 and 61068kg ha-1 inF1S1q2 and F2S2q1 treatments, respectively. The highest average values of crop water productivity obtained by S1q1 treatment, it was 4.25 and 5.4 kg m-3 in farms F1 and F2, respectively.
 

Keywords


Egypt. J. of Appl. Sci., 34 (9) 2019                                                294-316

long-furrow irrigation system performance under the conditions of North and south sinai-egypt

Hiekal, H.A.M.

Soil Cons. Dept., Desert Res. Center, Cairo, Egypt

Corresponding author: hmhekal@gmail.com

Key Words: long furrows - irrigation performance – design variables - development - forage sorghum – water productivity

ABSTRACT

Field experiments were conducted along two successive seasons of summer 2012 and 2013 at two private farms located in the Sinai Peninsula of Egypt. The first field is denoted as (F1) located in South Sinai, Ras Sudr; and the second field denoted as (F2) located in NorthSinai, El Tina Plain, to estimate the potential implement development of surface irrigation approaches in the North and South Sinai for forage sorghum production. The experiments carried out in a randomized complete block design with four replicates. Each experiment contains two longitudinal soil surface slopes (0.1 and 0.16%) namely: S1, and S2, respectively, and two irrigation water inflow rates were represented q1, and q2 as in an average of 180 and 108 liter min-1 furrow-1, respectively.The irrigation performance was evaluated through application efficiency (AE%), low-quarter distribution uniformity (DUlq) and deep percolation percent (Dp%).Furrow irrigation management, operation, and some design variables (Inflow discharge, furrow slope, and irrigation cutoff time) were correlated which estimated related to water management by studding different treatments in both sitesusing WinSRFR 4.1.3, Program. Average yield of forage sorghum and crop water productivity (CWP) were estimated.

The obtained results indicated that under the conditions of each farm, the AE% was directly proportional to the length of the run and inversely proportional to the inflow discharge and the time of irrigation cutoff where q2 obtained the highest average values 93.1 and 93.8% with F1S1 and F2S2 treatments, respectively. The Minimum average values of DP% obtained by q2, it was 6.9 and 6.2% with F1S1 and F2S2treatments, respectively. The highest average values of DUlq obtained by S1, it were 0.85 and 0.83 with F1q1 and F2q2 treatments, respectively. The highest average values of forage sorghum yield obtained 59464 and 61068kg ha-1 inF1S1q2 and F2S2q1 treatments, respectively. The highest average values of crop water productivity obtained by S1q1 treatment, it was 4.25 and 5.4 kg m-3 in farms F1 and F2, respectively.

 

295                                                      Egypt. J. of Appl. Sci., 34 (9) 2019                                             

INTRODUCTION

Irrigation is a strategy aimed at maximizing profitability as opposed to yield, and results in improvements in water use efficiency.Optimum management of water resources at the farm- level is needed in view of increasing water demands, limited resources, and aquifer contamination (Kumar and Singh, 2003). For the long term sustainability of an irrigation system, improvements in the performance of the current water application and on-farm water management practices seem to be more necessary than any other practice, an important aspect that has been considered in several studies is to design efficient irrigation systems at the farm-level (Feyen and Zerihun, 1999; Sarwar et al., 2001, Zerihun et al., 2001; Hillel and Vlek, 2005; Khan et al., 2006; Hsiao et al., 2007 and Hiekalet al., 2016).

The performance of an irrigation method is affected by: rate of infiltration of water into the soil; the inflow rate of the water; slope of the field; time of irrigation; time of recession of water from the soil surface; soil moisture prior to irrigation; spatial variability of the soil; climatic conditions; and furrow shape. The performance of irrigation parameters has been analyzed by various researchers (Holzapfel et al., 1985; Heermann et al., 1990; Burt et al., 1997; Hsiao et al., 2007). However, problems have been encountered in the effective evaluation of the performance of an irrigation method, owing to difficulties in identifying inadequacies in operation, management or design (Feyen and Zerihun, 1999), which irrigation performance can mainly be determined by using conjunctively various parameters, because one is not capable to describe if the irrigation has satisfied the plant water requirements and environmental effects.The On-Farm Irrigation Committee of the Irrigation and Drainage Division of ASCE (1978) defined water application efficiency (AE%) as the ratio among the volume of water retained in the root zone after irrigation and the total volume of water delivered or applied to an irrigated field. Water-application efficiency describes only the fraction of applied water stored within the root zone that is potentially accessible for evapotranspiration. It is not adequate for describing the overall performance of an irrigation, because the water application efficiency does not specify the uniformity of the irrigation. It is significant to improve the crop water productivity (CWP). Where, CWP is defined as the marketable crop yield over the seasonal water use by actual evapotranspiration (ET), Kijne et al., (2003). Increasing CWP is particularly appropriate where water is scarce compared with other resources involved in the production. For the rural poor, more productive

Egypt. J. of Appl. Sci., 34 (9) 2019                                        296

use of water can mean better nutrition for families, more income and productive employment.In general, furrow irrigation has become important because of the high cost of energy in pressurized irrigation methods and the incorporation of automation in its operation.The performance of irrigation parameters has been analyzed by various researchers (Holzapfel et al., 1985; Heermann et al., 1990; Burt et al., 1997; Hsiao et al., 2007; and Adamala et al. 2014). However, problems have been encountered in the effective evaluation of the performance of an irrigation method, owing to difficulties in identifying inadequacies in operation, management or design (Feyen and Zerihun, 1999).In furrow irrigation in clayey soil, Eldeiry et al. (2004) found that furrow length and application discharge arethe main management and design parameters affecting application efficiency. Lazarovitch et al. (2009) studythe moment analysis technique describes spatial and temporal subsurface wetting patterns resulting fromfurrow infiltration and redistribution that contribute to improve irrigation management. Numerical simulation techniques are common for irrigation analysis and were successfully applied to simulate steady and unsteady flow with solute transport in furrow irrigation (Burguete et al., 2009a).In the past three decades considerable research has been conductedto develop mathematical models for simulating surface irrigationperformance. These models depend on several interactingfactors such as field dimensions, field slope, flow rate, cutoff time,soil infiltration characteristics and flow resistance. The presence ofa large number of variables makes the design of surface irrigationquite complex. The selection of the available methods and management approaches depends on factors such as water availability, crop type, soil characteristics, land topography, and associated cost. Surface irrigation are characterized by their operation simplicity; however, design and management are complicated (Burguete et al., 2009b). Some of those models have been implemented to simulate the advance phase in furrow irrigation. Holzapfel et al. (1984) showed that the kinematic-wave and volume-balance models closely predicted the advance and recession phases.Bautistaet al. (2009) concluded that optimized design and operation of surface irrigation systems translate into high levels of performance. With WinSRFR, the analyst can visualize the range of solutions that will result in near optimal performance, find one that will meet practical constraints, and study the sensitivity of the recommended design or operational strategy. Bautista et al. (2012)reported that WinSRFR is a software package for the hydraulic analysis of surface irrigation systems. The software integrates four different components: 1) an unsteady flow simulation  engine that can be used to predict the surface and subsurface flow of water for a known system geometry, infiltration and roughness conditions, and boundary conditions; 2) tools for evaluating the performance of irrigation systems and for estimating infiltration and roughness conditions from field-measured data; 3) tools for designing irrigation systems, and 4) tools for  optimizing the operation of existing irrigation systems.Soil erosion is the process by which material is dislodged, transported and deposited elsewhere in the landscape via the effects of wind or water. For water erosion, the severity of erosion is determined by the soil particle size, field slope and water flow velocity. In furrow irrigation, maximum flow velocity is realized close to the inlet and gradually declines over the furrow length. Hence, the sediment load generally increases throughout the first quarter of the field length and steadily declines over the second half of the field (Trout, 1996). Some of the eroded material may be removed in the tail water but a majority of the suspended load is deposited before the water reaches the end of the field. Despite this, erosion is usually only considered a problem where soil material is removed from the field even though any degree of erosion along the furrow length will result in non-uniform re-distribution of soil particles.

297                                                      Egypt. J. of Appl. Sci., 34 (9) 2019                                     

In this study,estimation thelong furrows irrigation performance: application efficiency (AE%),low-quarter distribution uniformity (DUlq) and deep percolation percent (Dp%)in farm sites at South and North Sinai conditions. In addition, to estimateandexamine the relationship between performed irrigation parameters and the surface-irrigation design variables (inflow discharge, length of the run, surface slope and time of irrigation cut-off) and between the performed irrigation parameters and crop yield of forage sorghum and the average water productivity throughout the two seasons of cultivations.

MATERIALS AND METHODS

Sitesdescription:

The study sites consist of two independentprivate farms located in Sinai Peninsula of Egypt. One is denoted as (F1) located in South (longitude 32° 43' 10.73"E, latitude 29° 37' 54.46"N, Ras Sudr); and the second denoted as (F2) located in North (longitude 32° 29' 28.26"E, latitude 31° 0' 41.88"N, Sahl El-Tina).

Egypt. J. of Appl. Sci., 34 (9) 2019                                        298

Representative soil samples were collected before sowingfor determination of some physical properties according to the methods described by Klute (1986) and some chemical properties determined according to the methods described by Black (1965). Some physical and chemical properties of the soil experimental sites are shown in Tables (1 and 2). The soil experimental at F1sitewas deep, well-drained calcareous loamy sand in texture and saline, while at F2 site was sandy loam in texture and saline.

Table (1): Some physical properties of experimental soil atF1 and F2.

Site

Soil

Particle size distribution (%)

Texture$

Dp

Db

*KSat.

F.C.

W.P

A.W

depth

Class

(g cm-3)

(g cm-3)

(cm h-1)

(W%)

(W%)

(W%)

(cm)

Coarse

Fine

Silt

Clay

 

 

 

 

 

 

 

 

Sand

Sand

 

 

 

 

 

 

 

F1

0 - 20

53.21

27.88

9.06

9.85

LS

2.32

1.56

3.77

19.90

10.07

9.83

20-40

60.12

24.94

7.59

7.35

LS

2.33

1.57

4.81

18.54

9.40

9.14

40-60

47.47

34.39

10.23

7.91

LS

2.34

1.59

3.83

17.16

11.00

6.16

60-80

51.02

30.55

10.11

8.32

LS

2.34

1.60

3.30

17.83

10.90

6.93

F2

0 - 20

28.21

33.58

19.25

18.96

SL

2.48

1.46

3.54

19.94

9.01

10.93

20-40

22.48

32.34

22.53

22.65

SCL

2.34

1.51

2.32

20.47

8.3

12.17

40-60

37.26

32.72

15.53

14.46

SL

2.36

1.55

3.25

18.97

10.25

8.72

60-80

29.32

31.42

23.00

16.30

SL

2.37

1.51

3.85

20.67

9.81

10.86

* k sat.= Saturated hydraulic conductivity,  Db= Bulck density, W.P= Permanent wilting point at 15 bar,

A.W= Available water

$ LS=Loamy sand; SL =Sandy loam; and SCL= Sandy clay loam.

 

 

 

Table (2): Some chemical properties of experimental soil at F1 and F2.

Site

Soil depth (cm)

CaCo3

Total N

pH

OM

SAR

EC

Soluble Cations

Soluble Anions

(%)

(ppm)

(%)

(dS m-1)

(meq l-1)

(meq l-1)

Ca++

Mg++

Na+

K+

Co3=

HCo3-

Cl-

So4=

F1

0 – 20

42.44