An integrated modeling approach to simulate human-crop-groundwater interactions in intensively irrigated regions
Global food security is threatened by aquifer depletion in arid and semi-arid regions. Ensuring aquifer sustainability while minimizing farmers' costs requires effective groundwater management policies, which are informed by hydro-economic models. However, the reliability of these models is typ...
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Veröffentlicht in: | Environmental modelling & software : with environment data news 2024-08, Vol.179, p.106120, Article 106120 |
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Sprache: | eng |
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Zusammenfassung: | Global food security is threatened by aquifer depletion in arid and semi-arid regions. Ensuring aquifer sustainability while minimizing farmers' costs requires effective groundwater management policies, which are informed by hydro-economic models. However, the reliability of these models is typically compromised by oversimplifications. This study introduces a hydro-economic modeling framework (ABM-MODFLOW), applied in the U.S. High Plains, overcoming previous models’ shortcomings. It employs an interdisciplinary approach, simulating real-world farming decisions and the resultant impacts on groundwater systems. Model validation indicates satisfactory performance in reproducing historical data and trends, outperforming the standalone groundwater model. Results show that agents with high irrigation capacities and fine soils earn the highest profits, whereas those with low irrigation capacities and coarse soils achieve the lowest profits. This modeling framework provides an advanced approach for simulating interactions between human decisions, crops, and groundwater in heavily stressed aquifers globally, supporting the development of effective groundwater management policies.
•Hydro-economic models of groundwater systems are often oversimplified.•These hydro-economic models also lack robust model validation.•A hydro-economic model is developed via interdisciplinary collaboration.•Developed hydro-economic model undergoes comprehensive validation.•Model effectively simulates coevolution of human decisions, crops, and groundwater. |
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ISSN: | 1364-8152 1873-6726 |
DOI: | 10.1016/j.envsoft.2024.106120 |