Assessing the effectiveness of irrigator-driven groundwater conservation programs to drought: A case study of the northwestern Kansas Local Enhanced Management Areas

Groundwater pumping for irrigation has led to declining groundwater levels in agricultural areas around the world, including the U.S. High Plains Aquifer. Here, we used a process-based crop model, AquaCrop, to assess the effectiveness of different irrigation management strategies during a synthetic multi-year drought. We focused on the Groundwater Management District 4 Local Enhanced Management Area (GMD-4 LEMA), a regional groundwater conservation program in the northwestern Kansas portion of the High Plains Aquifer. We first calibrated corn and sorghum AquaCrop models to simulate yield and irrigation using the Particle Swarm Optimization algorithm, and then applied a novel difference-based bias correction method to improve performance. We found that the corn models outperformed the sorghum models, likely due to limited observational sorghum data. However, both models performed satisfactorily during drought periods. We then evaluated the effectiveness of the groundwater conservation program in reducing water use during a synthetic five-year drought under three irrigation strategies. During the synthetic drought, corn irrigation requirements were roughly double those of sorghum. However, even simulated corn irrigation needs were generally less than current water allocations, supporting past work that suggests the current GMD-4 LEMA water allocations are ineffective for conserving water. Model simulations also indicated that water conservation strategies could reduce annual irrigation requirements without a substantial reduction in crop yield through improved water use efficiency, suggesting that lower allocations would be a feasible approach to reduce irrigation and slow groundwater decline rates. • Evaluated groundwater conservation program in heavily-stressed High Plains aquifer. • We used difference-based bias correction to improve AquaCrop model performance. • Bias-corrected corn and sorghum models used to assess management effectiveness. • Current pumping allocations make GMD-4 LEMA ineffective for conserving water. • Improved water use efficiency can lower water use, even during drought.

Authors

Institutions

Publication Details

Journal
Agricultural Water Management
Published
2025-08-18
DOI
https://doi.org/10.1016/j.agwat.2025.109735
Primary Topic
Irrigation Practices and Water Management
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Assessing the effectiveness of irrigator-driven groundwater conservation programs to drought: A case study of the northwestern Kansas Local Enhanced Management Areas

Samuel C. Zipper, Wayne Ndlovu, Timothy Foster
Agricultural Water Management
Irrigation Practices and Water Management
article

Assessing the effectiveness of irrigator-driven groundwater conservation programs to drought: A case study of the northwestern Kansas Local Enhanced Management Areas

Samuel C. Zipper, Wayne Ndlovu, Timothy Foster
article en

Abstract

Groundwater pumping for irrigation has led to declining groundwater levels in agricultural areas around the world, including the U.S. High Plains Aquifer. Here, we used a process-based crop model, AquaCrop, to assess the effectiveness of different irrigation management strategies during a synthetic multi-year drought. We focused on the Groundwater Management District 4 Local Enhanced Management Area (GMD-4 LEMA), a regional groundwater conservation program in the northwestern Kansas portion of the High Plains Aquifer. We first calibrated corn and sorghum AquaCrop models to simulate yield and irrigation using the Particle Swarm Optimization algorithm, and then applied a novel difference-based bias correction method to improve performance. We found that the corn models outperformed the sorghum models, likely due to limited observational sorghum data. However, both models performed satisfactorily during drought periods. We then evaluated the effectiveness of the groundwater conservation program in reducing water use during a synthetic five-year drought under three irrigation strategies. During the synthetic drought, corn irrigation requirements were roughly double those of sorghum. However, even simulated corn irrigation needs were generally less than current water allocations, supporting past work that suggests the current GMD-4 LEMA water allocations are ineffective for conserving water. Model simulations also indicated that water conservation strategies could reduce annual irrigation requirements without a substantial reduction in crop yield through improved water use efficiency, suggesting that lower allocations would be a feasible approach to reduce irrigation and slow groundwater decline rates. • Evaluated groundwater conservation program in heavily-stressed High Plains aquifer. • We used difference-based bias correction to improve AquaCrop model performance. • Bias-corrected corn and sorghum models used to assess management effectiveness. • Current pumping allocations make GMD-4 LEMA ineffective for conserving water. • Improved water use efficiency can lower water use, even during drought.

Agricultural Water ManagementVol. 318
United States Geological Survey (US), University of Kansas (US), University of Manchester (GB)
National Science Foundation, National Aeronautics and Space Administration, U.S. Department of Agriculture, UK Research and Innovation, European Commission, National Institute of Food and Agriculture, Innovate UK
Life in Land
Openalex Percentile: Top 73%
Irrigation Practices and Water Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.