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Assessment of Groundwater Recharge in Agro-Urban Watersheds Using Integrated SWAT-MODFLOW Model

Author

Listed:
  • Bisrat Ayalew Yifru

    (Department of Land, Water and Environment Research, Korea Institute of Civil Engineering and Building Technology, Goyang 10223, Korea
    Department of Civil and Environmental Engineering, University of Science and Technology, Daejeon 34113, Korea)

  • Il-Moon Chung

    (Department of Land, Water and Environment Research, Korea Institute of Civil Engineering and Building Technology, Goyang 10223, Korea
    Department of Civil and Environmental Engineering, University of Science and Technology, Daejeon 34113, Korea)

  • Min-Gyu Kim

    (Department of Land, Water and Environment Research, Korea Institute of Civil Engineering and Building Technology, Goyang 10223, Korea)

  • Sun Woo Chang

    (Department of Land, Water and Environment Research, Korea Institute of Civil Engineering and Building Technology, Goyang 10223, Korea
    Department of Civil and Environmental Engineering, University of Science and Technology, Daejeon 34113, Korea)

Abstract

Numerical models are employed widely to evaluate the hydrological components of a watershed but, traditionally, watershed models simplify either surface or subsurface flow module. In this setup, as a bridge between groundwater and surface water regimes, aquifer recharge is the most affected segment of the water balance. Since the watershed processes are increasingly changed, the need for a comprehensive model with detailed conceptualizing capacity of both groundwater and surface water flow systems is growing. This work focuses on the spatiotemporal groundwater recharge assessment in gauged and ungauged agro-urban watersheds in South Korea using the updated SWAT-MODFLOW model, which integrates the Soil and Water Assessment Tool (SWAT2012) and Newton–Raphson formulation for Modular Finite Difference Groundwater Flow (MODFLOW-NWT) in a single executable code. Before coupling, the setup, calibration, and verification of each model were performed separately. After integration, irrigation pumps and drain cells mapping to SWAT auto-irrigation and subbasins were initiated. Automatic calibration techniques were used for SWAT and MODFLOW-NWT models, but a manual calibration was used for the integrated model. A physical similarity approach was applied to transfer parameters to the ungauged watershed. Statistical model performance indicators revealed that the low streamflow estimation was improved in SWAT-MODFLOW. The spatiotemporal aquifer recharge distribution from both the stream seepage and precipitation showed a substantial change, and most of the aquifer recharge occurs in July–September. The areal annual average recharge reaches about 18% of the precipitation. Low-lying areas receive higher recharge consistently throughout a year. Overall, SWAT-MODFLOW exhibited reasonable versatility in evaluating watershed processes and produced valuable results with reasonable accuracy. The results can be an important input for policymakers in the development of sustainable groundwater protection and abstraction strategies for the region.

Suggested Citation

  • Bisrat Ayalew Yifru & Il-Moon Chung & Min-Gyu Kim & Sun Woo Chang, 2020. "Assessment of Groundwater Recharge in Agro-Urban Watersheds Using Integrated SWAT-MODFLOW Model," Sustainability, MDPI, vol. 12(16), pages 1-18, August.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:16:p:6593-:d:399081
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    References listed on IDEAS

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    1. Meredith, Elizabeth & Blais, Nicole, 2019. "Quantifying irrigation recharge sources using groundwater modeling," Agricultural Water Management, Elsevier, vol. 214(C), pages 9-16.
    2. Hydar Ebrahimi & Reza Ghazavi & Haji Karimi, 2016. "Estimation of Groundwater Recharge from the Rainfall and Irrigation in an Arid Environment Using Inverse Modeling Approach and RS," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(6), pages 1939-1951, April.
    3. Zhang, Dejian & Chen, Xingwei & Yao, Huaxia & Lin, Bingqing, 2015. "Improved calibration scheme of SWAT by separating wet and dry seasons," Ecological Modelling, Elsevier, vol. 301(C), pages 54-61.
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    1. Vladimir Mirlas & Vitaly Kulagin & Aida Ismagulova & Yaakov Anker, 2022. "MODFLOW and HYDRUS Modeling of Groundwater Supply Prospect Assessment for Distant Pastures in the Aksu River Middle Reaches," Sustainability, MDPI, vol. 14(24), pages 1-28, December.
    2. Huawei Li & Guohe Huang & Yongping Li & Jie Sun & Pangpang Gao, 2021. "A C-Vine Copula-Based Quantile Regression Method for Streamflow Forecasting in Xiangxi River Basin, China," Sustainability, MDPI, vol. 13(9), pages 1-22, April.
    3. Rumph Frederiksen, Rasmus & Molina-Navarro, Eugenio, 2021. "The importance of subsurface drainage on model performance and water balance in an agricultural catchment using SWAT and SWAT-MODFLOW," Agricultural Water Management, Elsevier, vol. 255(C).

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