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.
Highlights
The growing demand for water supply and the undesirable impact on the resources entails efficient management and detailed comprehension of hydrological cycle components [1,2,3,4]
In conjunction with the main objective, this work explored the versatility of the SWAT-MODFLOW algorithms to conceptualize watershed processes, which have a high density of urban and irrigation groundwater abstraction wells in multiple watersheds characterized by humid climate, complex topography, and detail LULC and soil classes
The model performance is verified based on RSR (the ratio of root mean square error (RMSE) and standard deviation of observed data), Nash–Sutcliffe efficiency (NSE), and percentage bias (PBIAS) values [48]
Summary
The growing demand for water supply and the undesirable impact on the resources entails efficient management and detailed comprehension of hydrological cycle components [1,2,3,4]. In conjunction with the main objective, this work explored the versatility of the SWAT-MODFLOW algorithms to conceptualize watershed processes, which have a high density of urban and irrigation groundwater abstraction wells in multiple watersheds characterized by humid climate, complex topography, and detail LULC and soil classes. One of the improvements of the current version of the SWAT-MODFLOW model over the previous versions is handling large-scale study areas with big data size, and, this study assessed this improvement as well This comprehensive application of SWAT-MODFLOW scrutinized the flexibility of the model to conceptualize and compute complex watershed processes efficiently. The SWAT model needs to be calibrated extensively to reduce the gap between measured and computed data In this process, the groundwater recharge and other water balance segments can be affected, principally in groundwater-dominated watersheds. The SWAT model reportedly has low performance in low flow computation [40]
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