Simulating the impacts of irrigation levels on soybean production in Texas High Plains to manage diminishing groundwater levels

Authors: SHARDA, VAISHALI - Kansas State University; Gowda, Prasanna; Marek, Gary; KISEKKA, ISAYA - University Of California, Davis; RAY, CHITTARANJAN - University Of Nebraska; ADHIKARI, PRADIP - The Ohio State University

Submitted to: Journal of the American Water Resources Association
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/5/2018
Publication Date: 2/1/2019
Citation: Sharda, V., Gowda, P.H., Marek, G.W., Kisekka, I., Ray, C., Adhikari, P. 2019. Simulating the impacts of irrigation levels on soybean production in Texas High Plains to manage diminishing groundwater levels. Journal of the American Water Resources Association. 55(1): 56-69. https://doi.org/10.1111/1752-1688.12720.
DOI: https://doi.org/10.1111/1752-1688.12720

Interpretive Summary: Ogallala aquifer is one of the largest freshwater aquifers in the world used for irrigated agriculture in the Texas High Plains. Soybean is one of the major irrigated crops grown in the region. Due to changing climate and inconsistent growing season rainfall, groundwater levels in the underlying Ogallala aquifer depleting at an unsustainable rate. Therefore, it is important to improve water use efficiency and crop water productivity for sustainable for crop production in the Texas High Plains. In this study, a crop growth simulation model was used to evaluate the effect of five different soil water thresholds on biomass and yield using long term climatic data. The crop growth model was calibrated and validated using lysimetric data for this purpose. Results indicated that soybean can be irrigated at 50% or 65% with minimum or no yield loss as compared to prevailing irrigation soil water threshold of 80%, thus reducing groundwater withdrawals from the Ogallala aquifer.

Technical Abstract: The study of declining groundwater levels in the Ogallala aquifer region has become a continuous effort for the scientific community over the past decade. There is an increasing need to strategize and plan irrigation systems under varied climatic conditions to support efficient irrigation practices while maintaining and improving the sustainability of groundwater systems. This study was undertaken to simulate the growth and production of soybean [Glycine max (L.)] under different irrigation scenarios. The objectives of this study were to calibrate and validate the CROPGRO-Soybean model in DSSAT-CSM v4.6 under Texas High Plains’ climatic conditions and to apply the calibrated model to simulate the impacts of different irrigation levels and triggers on soybean production. The methodology involved combining short-term experimental data with long-term historical weather data (1951-2012), and use of mechanistic crop growth simulation algorithms to determine optimum irrigation management strategies. Irrigation scheduling based on five different soil water thresholds (ITHR) were tested with the levels set at 20%, 35%, 50%, 65% and 80% ITHR. The calibrated CROPGRO-Soybean model was able to satisfactorily reproduce measured leaf area index, biomass and ET for soybean, indicating that it can be used for investigating different strategies for irrigating soybean in the Texas High Plains. Calculations of crop water productivity for both biomass and yield along with irrigation water use efficiency indicated that soybean can be irrigated at ITHR set at 50% or 65% with minimal yield loss as compared to 80% ITHR, thus conserving water and contributing toward lower groundwater withdrawals.