Quantifying agricultural groundwater abstraction using an integrated watershed modeling approach, Mississippi Delta, USA

Authors: BAILEY, RYAN - Colorado State University; ABBAS, SALAM - Colorado State University; CERKASOVA, NATALJA - Texas A&M Agrilife; Arnold, Jeffrey; White, Michael; MAJUMDAR, SAYANTAN - Desert Research Institute; SMITH, RYAN - Colorado State University

Submitted to: Hydrogeology Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/2/2025
Publication Date: 7/15/2025
Citation: Bailey, R.T., Abbas, S., Cerkasova, N., Arnold, J.G., White, M.J., Majumdar, S., Smith, R. 2025. Quantifying agricultural groundwater abstraction using an integrated watershed modeling approach, Mississippi Delta, USA. Hydrogeology Journal. https://doi.org/10.1007/s10040-025-02922-2.
DOI: https://doi.org/10.1007/s10040-025-02922-2

Interpretive Summary: In this study, the SWAT+ hydrologic model was integrated with the gwflow subroutine, and this system was used to estimate groundwater pumping volumes for irrigation in the Mississippi Delta. This approach addresses both demand (based on crop growth and soil moisture) and supply (considering groundwater storage). The model's accuracy was validated against various system responses such as streamflow, crop yield, evapotranspiration, groundwater levels, and recorded pumping volumes for 2000-2020, showing good general agreement. This method not only provides accurate estimates of annual groundwater pumping where such data are limited but also aids in understanding the driving factors impacting groundwater depletion. This technique may be employed to derive valuable potential management strategies under future land use, population, and climate scenarios.

Technical Abstract: Estimates of groundwater pumping volumes for irrigation are essential for water management and water supply forecasting, particularly for regions with declining groundwater levels. In this study we present an integrated modeling approach to quantify spatio-temporal field-level pumping rates and volumes at a regional scale. The approach is both demand-driven, using simulated crop growth algorithms and soil moisture conditions to trigger irrigation events, and supply-constrained, using simulated groundwater storage in the unconfined aquifer to constrain irrigation extraction. The approach uses the SWAT+ hydrologic model, with the use of the gwflow subroutine for simulating spatially distributed groundwater storage, flow, and interaction with the soil profile, channels, and lakes. The modeling approach is demonstrated for the Mississippi Delta (northwest Mississippi, USA), a region of high groundwater irrigation and associated groundwater depletion, for the period 2000-2020. The model is corroborated using key system responses that constrain both soil moisture and groundwater storage: streamflow at multiple gaging sites; crop yield for soybean and corn; crop ET for fields; groundwater head and head change at thousands of monitoring wells; and annual pumping volumes recorded for fields throughout the Delta. Results show good agreement for all system responses, with groundwater head changes matching groundwater depletion magnitudes in the central region of the Big Sunflower Watershed. Simulated annual pumping volumes generally match measured volumes on an average and frequency basis, although underestimation of 20% occurs for one year (2015). This underestimation likely is due to the soil moisture trigger within the model, as irrigation events occur as needed, rather than based on available water supply. Therefore, in addition to providing accurate annual volumes of groundwater pumping for most years, the model can also be used to quantify the volume of irrigation over-application, and hence the volume of groundwater depletion that can be prevented. In general, this integrated modeling approach can be used to estimate historical pumping rates for a groundwater-irrigated region and predict pumping rates and groundwater storage trends for scenarios of future changes in land use, population, and management practices.