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DIVISION S-1—SOIL PHYSICS

Evaluation of a Model for Irrigation Management Under Saline Conditions

II. Salt Distribution and Rooting Pattern Effects

^a Soil and Water Science Unit, Univ. of California, Riverside, CA 92521
^b Inst. of Soils, Water, and Environmental Sci., Volcani Center, ARO, P.O. Box 6, Bet Dagan, Israel

* Corresponding Author (john.letey{at}ucr.edu)

	ABSTRACT

TOP ABSTRACT INTRODUCTION EXPERIMENTAL DESCRIPTION AND... RESULTS AND DISCUSSION REFERENCES

 
Increasing salinity is a significant factor affecting the future agricultural productivity in semiarid irrigated regions of the world. Computer simulation models, which can be used to evaluate the consequences of differing management strategies on crop yield and salt distribution in the soil profile, would be valuable. Simulated results from models must be compared with measured results from field experiments to establish their validity. The simulated salt distribution from the ENVIRO-GRO model were compared with measured distribution at the end of the growing season from an experiment that had treatment variables of irrigation water electrical conductivity (EC) of 1.7, 4.0, 5.0, 8.0, and 10.2 dS m^-1 and average irrigation intervals of 3.5, 7, 14, and 21 d. Root distribution is an input variable to the model. Therefore, a second objective of the study was to test the sensitivity of the model results to the root distribution. In general, the agreement between measured and simulated salt distributions were better for the longer than for the shorter irrigation intervals. For the shorter irrigation intervals, the measured salt concentration near the soil surface was greater than was simulated. This result is explained by the fact that the model does not separate the transpiration (T) from the evaporation (E) component of evapotranspiration (ET), and assumes that all water is lost by T. The E:T ratio would be expected to increase as the irrigation frequency increases, and E would carry salts to the soil surface. Except for nonsaline conditions with frequent irrigation, the simulated yields were increased by having a deeper root distribution. The effect of a deep root system was greater for the longer irrigation interval when the water storage capacity within the root zone becomes more important.

Abbreviations: E, evaporation component of evapotranspiration • ET, evapotranspiration • EC, electrical conductivity • T, transpiration component of evapotranspiration

	INTRODUCTION

TOP ABSTRACT INTRODUCTION EXPERIMENTAL DESCRIPTION AND... RESULTS AND DISCUSSION REFERENCES

 
SALINITY is a significant factor in many irrigated, semiarid lands. The potential effects of salinity are not only on crop yield but also on factors such as salinization of lands, degrading ground and surface waters, and the underground migration of salts from salt-laden geologic strata to rivers. All of these factors should be considered in developing irrigation strategies.

Reliable models which accurately simulate the consequences of irrigation management on crop yield, salt, and water distribution in the soil profile, and the amount and concentration of water percolating below the root zone have great utility in developing optimal irrigation strategies. Cardon and Letey (1992) developed a modified van Genuchten–Hanks model to simulate crop production under various irrigation regimes including saline conditions. That model was modified by Pang and Letey (1998) to allow the plant to compensate for water stress by removing extra water from the root zone where water is not deficient and by incorporating a threshold for matric and osmotic stress below which plant growth was not affected.

Very few experiments have been conducted in which the irrigation water salinity and the amounts and timing of irrigation were included as variables. One experiment was conducted in Israel which included five levels of salt concentration in the irrigation water and four irrigation intervals (Shalhevet et al., 1986). Results from that experiment can be used to compare computer model simulation results with measured results. Feng et al. (2003) reported good agreement between the measured and simulated relative yields of a corn crop. One purpose of the present paper is to compare the simulated with the measured salt distribution in the profile at the end of a season. A second purpose is to investigate the effect of different root distributions on relative yield and salt distribution under irrigation-salinity and irrigation-interval variables. Although the model also simulates the amount and concentration of water percolating below the root zone, these data were not measured during the experiment so no evaluation of the model results can be made.

	EXPERIMENTAL DESCRIPTION AND SIMULATION PROCEDURES

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Salt distribution before and after growing sweet corn (Zea mays ‘Jubilee’) in an experiment at Gilat Agricultural Experimental Station in the northern Negev of Israel (Shalhevet et al., 1986) were used in the simulation. The salt distribution at the beginning of the experiment were used as the initial conditions in the model. Simulations and the measured salt distribution at the end of the growing season were used to compare measured and simulated results. Salt concentrations are reported in mass of salt per unit mass of soil to avoid ambiguity with soil water content. Comparable water contents would be required to report the results in solution concentrations.

The experiment was a split-plot design with five levels of ECs of irrigation water (EC_i = 1.7, 4.0, 5.0, 8.0, and 10.2 dS m^-1) as main treatments and four irrigation intervals (3.5, 7, 14, and 21 d) as subtreatments and three replicates. The 3.5-d treatment reports the average interval between irrigations, which varied slightly during the course of the experiment.

Prior to the initiation of the salinity and irrigation interval treatments, all plots received three uniform irrigations until 37 d after planting. The initial salt distribution in the soil profile prior to planting was quite uniform through the soil. The concentration was 1.25 cmol kg^-1 to a depth of 90 cm and then 1.0 cmol kg^-1 at greater depths. The root distribution was not measured in the experiment, so values reported by Bar Yosef (1999) from an experiment on corn in Israel was selected as being representative of the experimental situation for comparing simulated with measured results.

Four different rooting patterns were artificially selected to determine the effect of rooting pattern on simulated results in a separate study. Maximum rooting depths selected were 60 and 120 cm; and for a given maximum length, a shallower and deeper distribution were formulated (Fig. 1) . For purposes of reporting, these treatments will be identified as 60s, 60d, 120s, and 120d, where the number refers to the maximum depth of root penetration and the letter refers to whether the root distribution was more shallow (s) or deep (d). The root distribution patterns are illustrated in Fig. 1. A description of the soil properties, hydraulic function values used in the model, crop sensitivity to salinity, and matric stress values and other details of the simulation are presented in detail elsewhere (Feng et al., 2003).

View larger version (25K): [in this window] [in a new window]   Fig. 1. Root distributions used in the simulations. The numbers in the key refer to the maximum depth of root penetration and the letters refer to whether the roots were predominantly shallow (s) or deep (d) within the depth of penetration.

	RESULTS AND DISCUSSION

TOP ABSTRACT INTRODUCTION EXPERIMENTAL DESCRIPTION AND... RESULTS AND DISCUSSION REFERENCES

 
The measured and simulated salt distributions at the end of the experiment are presented in Fig. 2 for a range of irrigation water salinities for the four irrigation interval treatments. Both the measured and simulated salt concentration in the soil profile increased as the irrigation water salinity increased as would be expected. A general trend in results is that for the 3.5- and 7-d irrigation intervals, the measured salt concentration near the soil surface was greater than was simulated. The agreement between the measured and the simulated salt distributions are better for the 14- and 21-d irrigation intervals.

View larger version (41K): [in this window] [in a new window]   Fig. 2. The measured (Meas., solid symbol) and simulated (Sim., open symbol) salt distribution at the end of the growing season for irrigation water salinities (dS m-1) as specified by the numbers. The results are for irrigation intervals of (A) 3.5, (B) 7, (C) 14, and (D) 21 d.

Because the model allows root water uptake from nonstressed root zone to compensate for reduced water uptake from the stressed portion of the root zone, the discrepancy between the measured and simulated salt distribution in the soil profile were not reflected in the crop production results (Feng et al., 2003).

The effects of the artificially imposed root distributions on simulated relative yield of corn are summarized in Table 1. Although the simulations were conducted across a 5-yr period, only the first 2-yr results are presented, because the results in successive years were very similar to those achieved in the second year. In other words, steady state conditions had been achieved by the second growing season.

The general results of the simulation are consistent with results reported by Timlin et al. (2001). They investigated the relationships between corn grain yield and weather over a range of soil rooting depths with and without irrigation. The grain yields from the irrigated plots were not sensitive to soil depth. However, on the nonirrigated plots, the grain yield increased with increasing soil depth.

The simulated salt distributions for the artificially imposed root distributions are presented in Fig. 3 for the field experimental treatments of 3.5-d irrigation interval and irrigation water salinities of 1.7 and 9.5 dS m^-1. The main effect was to have the salt transported deeper into the soil profile with the deeper root system. This result is consistent with the expected zones of water extraction by the roots. The deeper root system would extract water at deeper depths than the shallow root system. Therefore, at irrigation the infiltrated water would move deeper into the soil profile to replace the extracted water under the deep root system. The flow of water to the deeper zones would transport salt deeper into the profile.

View larger version (28K): [in this window] [in a new window]   Fig. 3. The simulated salt distribution at the beginning (initial) and end of the growing season for four root distributions. The numbers in the key refer to the maximum depth of root penetration and the letters refer to whether the roots were predominantly shallow (s) or deep (d) within the depth of penetration. The irrigation water salinities were (A) 1.75 dS m-1 and (B) 9.5 dS m-1.

Having a deeper root system is preferable from two points of view. First, a larger water storage capacity available to plants exists with the deeper root systems, placing less importance on the timing of irrigation. Second, the deeper root system, by extracting water at the greater depths, creates a situation toward increasing the depth of salt leaching by irrigation. The rooting depth is particularly important under saline conditions. With proper irrigation timing and amount of nonsaline irrigation water, approximately equal yields can be achieved regardless of root distribution. However, when irrigating with saline waters, the rooting depth becomes more important.

Received for publication March 5, 2002.

	REFERENCES

TOP ABSTRACT INTRODUCTION EXPERIMENTAL DESCRIPTION AND... RESULTS AND DISCUSSION REFERENCES

 

• Bar-Yosef, B. 1999. Advances in fertigation. p. 1–77. In D.L. Sparks (ed.) Advances in Agronomy. Vol. 65. Academic Press, New York.
• Cardon, G.E., and J. Letey. 1992. Soil-based irrigation and salinity management model: I. Plant water uptake calculations. Soil Sci. Soc. Am. J. 56:1881–1887.[Abstract/Free Full Text]
• Feng, G.L., A. Meiri, and J. Letey. 2003. Evaluation of a model for irrigation management under saline conditions: I. Effects on plant growth. Soil Sci. Soc. Am. J. 67:71–76 (this issue).[Abstract/Free Full Text]
• Pang, X.P., and J. Letey. 1998. Development and evaluation of ENVIRO-GRO, an integrated water, salinity, and nitrogen model. Soil Sci. Soc. Am. J. 62(5):1418–1427.[Abstract/Free Full Text]
• Shalhevet, J., A. Vinten, and A. Meiri. 1986. Irrigation interval as a factor in sweet corn response to salinity. Agron. J. 78:539–545.[Abstract/Free Full Text]
• Timlin, D.J., Y. Pachepsky, V.A. Snyder, and R.B. Bryant. 2001. Water budget approach to quantify corn grain yields under variable rooting depths. Soil Sci. Soc. Am. J. 65:1219–1226.[Abstract/Free Full Text]

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This Article Abstract Figures Only Full Text (PDF) Free Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in ISI Web of Science Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via ISI Web of Science (4) Citing Articles via Google Scholar Google Scholar Articles by Feng, G. L. Articles by Letey, J. Search for Related Content PubMed Articles by Feng, G. L. Articles by Letey, J. Agricola Articles by Feng, G. L. Articles by Letey, J. Related Collections Irrigation Other Environmental Contamination Soil Models Other Models Root Growth