Assessing Agriculture Conservation Practice Impacts on Groundwater Levels at Watershed Scale

Xiaojing Ni (), Prem B. Parajuli and Ying Ouyang
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Xiaojing Ni: Mississippi State University
Prem B. Parajuli: Mississippi State University
Ying Ouyang: USDA Forest Service, Center for Bottomland Hardwoods Research

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2020, vol. 34, issue 4, No 16, 1553-1566

Abstract: Abstract Over the last several decades, increased groundwater usage by agriculture with a consequence of groundwater resource depletion has motivated the discussion of sustainability of groundwater resource. In this study, to investigate the impacts of agricultural best management practices (BMPs) on groundwater level, two kinds of conservation practices and five scenarios of tail water recovery pond and crop rotation were simulated by various groundwater recharge and pumping plans in Soil and Water Assessment Tool (SWAT) and MODFLOW models in an agriculture watershed in Mississippi, U.S.. The calibrated and validated ground water model indicated coefficient of determination (R2) of 0.81 and Nash–Sutcliffe model efficiency coefficient (NSE) of 0.79 respectively. The results from this study showed that the groundwater recharge changed with irrigation plans and surface hydrological impact of management practices. In addition, it determined that tail water recovery pond could help mitigate groundwater depletion. The groundwater recharge due to continuous corn crop scenario was 7% higher in average than that of the continuous soybean. Non-growing season groundwater recharge may be critical for groundwater recovery. The average groundwater level was increased continuous corn scenario by 15%, continuous soybean by 13%, and corn-soybean by 14% as compare to the baseline scenario with rice planted. Results of this study can be helpful for planning on how various BMPs impact on groundwater.

Keywords: BMPs; Groundwater; MODFLOW; SWAT; Tail water recovery pond (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s11269-020-02526-3

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