Improving SWAT auto-irrigation functions for simulating agricultural irrigation management using long-term lysimeter field data

Authors: CHEN, YONG - Texas A&M University; Marek, Gary; MAREK, THOMAS - Texas Agrilife Research; Brauer, David; SRINIVASAN, RAGHAVAN - Texas A&M University

Submitted to: Journal of Environmental Modeling and Software
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/29/2017
Publication Date: 10/16/2017
Citation: Chen, Y., Marek, G.W., Marek, T.H., Brauer, D.K., Srinivasan, R. 2017. Improving SWAT auto-irrigation functions for simulating agricultural irrigation management using long-term lysimeter field data. Journal of Environmental Modeling and Software. 99:25-38. https://doi.org/10.1016/j.envsoft.2017.09.013.
DOI: https://doi.org/10.1016/j.envsoft.2017.09.013

Interpretive Summary: Decreased irrigation system capacities due to declining groundwater levels have resulted in irrigation strategies that allow for partial depletion of soil plant available water. Use of this management allowed depletion (MAD) approach may help extend limited water resources by reducing excess irrigation and maximizing soil water under limited irrigation. Models such as the Soil and Water Assessment Tool (SWAT) are increasingly being used to assess the impacts of such strategies. However, recent research has illustrated deficiencies in SWAT's ability to simulate representative irrigation practices. Scientists from ARS and Texas A&M AgriLife developed and tested an alternative MAD-based auto-irrigation algorithm using data from a lysimeter field at the USDA-ARS Conservation and Production Research Laboratory at Bushland, TX. Results showed improved simulation of both irrigation and evapotranspiration (ET) using the alternative algorithm.

Technical Abstract: The Texas High Plains is one of the most productive U.S. agricultural regions. However, decreasing groundwater availability has resulted in the adoption of limited irrigation strategies such as the management allowed depletion (MAD) concept of plant available water. Simulation models such as the Soil and Water Assessment Tool are a cost-effective and time saving method commonly used to evaluate best management practices and their effect on water balance. However, some studies have suggested that the irrigation algorithms in SWAT are inadequate for evaluation of representative irrigation practices. Consequently, auto-irrigation algorithms were developed based on 1) a single season MAD level and 2) growth stage-specific MAD levels for seasonal crop growth partitioning based on both scheduled date and accumulated heat units. Comparisons with observed data from an irrigated lysimeter field at the USDA-ARS Conservation and Production Research Laboratory at Bushland, Texas resulted in improved representation and simulation of irrigation and evapotranspiration.