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Vegetation‐related processes, such as evapotranspiration (ET), irrigation water withdrawal, and groundwater recharge, are influencing surface water (SW)—groundwater (GW) interaction in irrigation districts. Meanwhile, conventional numerical models of SW‐GW interaction are not developed based on satellite‐based observations of vegetation indices. In this paper, we propose a novel methodology for multivariate assimilation of Sentinel‐based leaf area index (LAI) as well as in‐situ records of streamflow. Moreover, the GW model is initially calibrated based on water table observations. These observations are assimilated into the SWAT‐MODFLOW model to accurately analyze the advantage of considering high‐resolution LAI data for SW‐GW modeling. We develop a data assimilation (DA) framework for SWAT‐MODFLOW model using the particle filter based on the sampling importance resampling (PF‐SIR). Parameters of MODFLOW are calibrated using the parameter estimation (PEST) algorithm and based on in‐situ observation of the GW table. The methodology is implemented over the Mahabad Irrigation Plain, located in the Urmia Lake Basin in Iran. Some DA scenarios are closely examined, including univariate LAI assimilation (L‐DA), univariate streamflow assimilation (S‐DA), and multivariate streamflow‐LAI assimilation (SL‐DA). Results show that the SL‐DA scenario results in the best estimations of streamflow, LAI, and GW level, compared to other DA scenarios. The streamflow DA does not improve the accuracy of LAI estimation, while the LAI assimilation scenario results in significant improvements in streamflow simulation, where, compared to the open loop run, the (absolute) bias decreases from 75% to 6%. Moreover, S‐DA, compared to L‐DA, underestimates irrigation water use and demand as well as potential and actual crop yield. Key Points Using source code modification, SWAT‐MODFLOW is connected to sequential DA Multivariate assimilation of streamflow, GW‐level and leaf area index (LAI) shows the best results Streamflow data assimilation does not improve LAI simulation, while LAI data assimilation improves streamflow simulation

To precisely delineate the transformation dynamics across several temporal and spatial scales in the middle and lower portions of the Songhua River basin in Heilongjiang Province, China, characterized by numerous irrigation zones and frequent transitions from surface water to groundwater. The SWAT-MODLFOW model, developed on the QSWATMOD2 platform, was validated using river runoff data and groundwater level observations. Consequently, the delay of precipitation on groundwater levels and the correlation between surface water and groundwater dynamics in the middle and lower portions of the Songhua River basin were modeled. The findings indicate: (1) The coefficient of calibration and Nash coefficient for monthly runoff during the calibration and validation periods yielded R 2  ≥ 0.86, NSE ≥ 0.87, R 2  ≥ 0.76, and NSE ≥ 0.77, respectively. Furthermore, the discrepancy between the simulated and actual groundwater table values is within 0.6 m, with R² values of 0.97 and 0.98 for the periodic and verification phases, respectively. The simulation outcomes of this test model are satisfactory and fulfill the criteria for scientific research. (2) The groundwater level in the research area typically declines from west-northwest to northeast and from south to east. The groundwater level lag time influenced by precipitation in Jiamusi, Fujin, and Tongjiang cities is around 10.56 days, 10.58 days, and 3.15 days, respectively. (3) The river channels facilitating surface water recharge to groundwater constitute 41.75% of the entire length of the Jiamusi-Tongjiang stretch of the Songhua River, with the annual average recharge representing 50.84% of the total exchanged water. Seasonally, the peak recharge value for each river section occurred in August, while the lowest recharge value was recorded in April. The peak recharge happened in 2009, while the lowest recharge was in 2014. The contribution of groundwater to surface water exhibits significant fluctuations, with seasonal variance between − 52% and 55%, and inter-annual variation between − 35% and 52%.

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.

This research delves into the crucial role of groundwater in underpinning ecosystems and human resilience amidst drastic and unpredictable climate change, particularly as water resources face increasing sustainability concerns due to population surges and climate change. Utilizing a combined approach of SWAT-MODFLOW models, we estimate the streamflow discharge and groundwater recharge in the Choushui River Alluvial Fan, Taiwan. These models allow evaluation of the distribution and proportion of recharge areas as well as the accuracy and the potential influence of future climate change scenarios on groundwater recharge. The findings show a strong correlation between the simulation and actual observations, evidenced by the Nash–Sutcliffe model efficiency coefficients (NSE) of 0.920 and 0.846 for calibration and validation in the Choushui River, and 0.549 and 0.548 for the Pei-Kang River, respectively. The model demonstrates a reliable representation of the watershed response, supported by robust statistical performance. The analysis reveals the variable impacts of climate change on groundwater recharge, dependent on the chosen scenario and period. Some scenarios indicate that the maximum observed increase in groundwater recharge is 66.36% under the RCP2.6 scenario in the long-term period (2061–2080), while the minimum observed increase is 29.67% under the RCP4.5 scenario in the initial time frame; however, all demonstrate a decrease ranging from 23.05% to 41.92% across different RCPs in the impact of climate change over time, suggesting a potential long-term decrease in the impact of climate change on groundwater recharge. This study provides indispensable insights into the spatial hotspots in the top fan and the potential range of impact rates of climate change on groundwater recharge, underscoring the importance of continuous research and the thorough evaluation of multiple scenarios. Moreover, we establish a primary framework for using a top-ranked MIROC5 projection of general circulation models (GCMs) to delineate an essential premise that facilitates the advanced exploration of alternative scenario augmentations, bolstering the comprehensive investigation of climate change impacts on groundwater recharge. It is proposed that these findings serve as a guidepost for sustainable water resource management and policy-making in the face of climate change and escalating water demand.

Quantifying the spatiotemporal variations of basin-scale surface water (SW)–groundwater (GW) interactions is vital for the conjunctive management of water resources in the basin. In this study, an integrated hydrological model (SWAT-MODFLOW) is used to simulate the SW–GW system in the Huashan Basin. The numerical model was calibrated and validated using the streamflow observations of the watershed outlet and the groundwater levels of the long-term monitoring wells from 2016 to 2020 in the study area. The model results show that the SWAT–MODFLOW can achieve a better fit for the streamflow discharge, compared with the results in the single SWAT model, with R2 (coefficient of correlation) and NSE (Nash-Sutcliffe efficiency coefficient) of 0.85 and 0.83, respectively. The water table fitting results indicate that R2 and RMSE can reach 0.95 and 0.88, respectively. The water budgets analysis demonstrates that the average rate (0.5281 m3/s) of GW abstraction to SW is larger than the rate (0.1289 m3/s) of SW recharge to GW. Moreover, the exchange rate of SW and GW gradually reaches a peak value from June to August, and the lowest value is shown in April, for each hydrological year. Based on the IPPC6 CanESM5 dataset supplied by the Canadian Climate Centre, the regional precipitation scenario subject to climate change was predicted by the ASD (Auto Statistical Downscaling Model) a statistical downscaling method, under the climate scenarios of SSP2_4.5 and SSP5_8.5. The SW–GW interaction pattern was modeled under the future scenarios in the study area. The current (2016–2020) average annual rate of the SW–GW interaction is considered as the base value. Subject to the SSP2_4.5 scenario, the average exchange rate of the SW recharge to GW is 0.1583 m3/s, which is an increase of 22.8%. The average exchange rate of the GW discharge to SW is 0.5189 m3/s which is a reduction of 0.017%. Subject to the SSP5_8.5 scenario, the average exchange rate of SW recharge to GW is 0.1469 m3/s, which is an increase of 14.7%. The average exchange rate of the GW discharge to SW is 0.5953 m3/s, which is an increases of 12.7%. The results can assist in water resource management in the basin, by identifying potential locations of nutrient transport from the aquifer to the river, as well as changes in spatial variability under future climatic conditions.

The Ethiopian government has selected Lake Tana basin as a development corridor due to its water resources potential. However, combined use of groundwater (GW) and surface water (SW) is still inadequate due to knowledge gaps about the flow dynamics of GW and SW. Mostly, there is no information about groundwater use. Therefore, this study aims to investigate the dynamics of GW-SW interactions on a spatio-temporal basis in three of the main catchments (Gilgelabay, Gumara and Ribb) that drain into Lake Tana. To this end, the SWAT-MODFLOW model, which is an integration of SWAT (Soil and Water assessment Tool) and MODFLOW, is used. The results reveal strong hydraulic connection between the GW and SW in all the three catchments. In the Gilgelabay catchment, the flow from the aquifer to the river reaches dominates (annual discharge from the aquifer varies from 170 to 525,000 m3/day), whereas in Gumara (annual exchange rate between −6,530 and 1,710 m3/day) and Ribb (annual exchange rate between −8,020 and 1,453 m3/day) the main flow from the river reaches to the aquifer system. The flow pattern differs in the three catchments due to variations of the aquifer parameters and morphological heterogeneity. Overall, this study improves our understanding of GW-SW flow dynamics and provides insights for future research works and sustainable water management in the Nile region.

This study explores spatio-temporal patterns of surface water-groundwater interactions in the Yom and Nan River basins, a vulnerable and essential agricultural region in northern Thailand, under various future climate conditions. The SWAT-MODFLOW model performs the coupled simulation of surface/subsurface hydrological processes in the watershed, with projected climate conditions from the three Global Climate Models (MIROC5, CNRM-CM5, and MPI-ESM-MR) under the minimum and maximum Green House Gas emission scenarios, represented as the RCPs 2.6 and 8.5. The results demonstrate that, in the near future (2026–2045) under the two scenarios, a raised air temperature at 0.5–1.0 °C with a 2–16% increment of annual rainfall cause a 7–20% decrease in groundwater recharge from surface water percolation, followed by a 11–21% depletion of groundwater flow to river, while aquifer recharge from the river change negligibly. In the intermediate future (2051–2070) and far future (2076–2095), changes in surface water-groundwater interactions under RCP 2.6 are rather similar to the near future because of insignificant differentiation in climate conditions. Whereas, under RCP 8.5, annual rainfall increases by 26% and produces 4–14% increments of groundwater recharging and groundwater discharge to streamflow, while river seepage increases by 1–18%. These provide key insights into northern Thailand watershed systems to deal with future impacts of climate change on water supply.

To keep groundwater levels stable, Jinan’s government has implemented several water management measures. However, considerable volumes of dissolved organic carbon (DOC) can enter groundwater via water exchange, impacting groundwater stability. In this study, a SWAT-MODFLOW-RT3D model designed specifically for the Yufu River Basin is developed, and part of the code of the RT3D module is modified to simulate changes in DOC concentrations in groundwater under different artificial recharge scenarios. The ultimate objective is to offer valuable insights into the effective management of water resources in the designated study region. The modified SWAT-MODFLOW-RT3D model simulates the variations of DOC concentration in groundwater under three artificial recharge scenarios, which are (a) recharged by Yellow River water; (b) recharged by Yangtze River water; and (c) recharged by Yangtze River and Yellow River water. The study shows that the main source of groundwater DOC in the basin is exogenous water. The distribution of DOC concentration in groundwater in the basin shows obvious spatial variations due to the influence of infiltration of surface water. The area near the upstream riverbank is the earliest to be affected. With the prolongation of the artificial recharge period, the DOC concentration in groundwater gradually rises from upstream to downstream, and from both sides of the riverbank to the surrounding area. By 2030, the maximum level of DOC in the basin will exceed 6.20 mg/l. The Yellow River water recharge scenario provides more groundwater recharge and less DOC input than the other two scenarios. The findings of this study indicate that particularly when recharge water supplies are enhanced with organic carbon, DOC concentrations in groundwater may alter dramatically during artificial recharge. This coupled modeling analysis is critical for assessing the impact of recharge water on groundwater quality to guide subsequent recharge programs.

Climate change is progressing and is now one of the most important global challenges for humanities. Water resources management is one of the key challenges to reduce disaster risk. In Northern Thailand, flood and drought have always occurred because of the climate change impact and non-systematic management in the conjunctive use of both sources of water. Therefore, this study aims to assess the climate change impact on surface water and groundwater of the Yom and Nan river basins, located in the upper part of Thailand. The surface water and groundwater regimes are generated by a fully coupled SWAT-MODFLOW model. The future climate scenarios are considered from the Representative Concentration Pathways (RCPs) 2.6 and 8.5, presented by the Coupled Model Intercomparison Project Phase 5 (CMIP5), in order to mainly focus on the minimum and maximum Green House Gas (GHG) emissions scenarios during the near future (2021–2045) periods. The results show that the average annual air temperature rises by approximately 0.5–0.6 °C and 0.9–1.0 °C under the minimum (RCP 2.6) and maximum (RCP 8.5) GHG emission scenarios, respectively. The annual rainfall, obtained from both scenarios, increased by the same range of 20–200 mm/year, on average. The summation of surface water (water yield) and groundwater recharge (water percolation) in the Yom river basin decreased by 443.98 and 316.77 million m3/year under the RCPs 2.6 and 8.5, respectively. While, in the Nan river basin, it is projected to increase by 355 million m3/year under RCP 2.6 but decrease by 20.79 million m3/year under RCP 8.5. These quantitative changes can directly impact water availability when evaluating the water demand for consumption, industry, and agriculture.

With increasing shallow groundwater use for agricultural purposes, understanding the spatiotemporal variability in recharge rates, storage capacity, and its interaction with surface waters becomes crucial for its sustainable management. An integrated SWAT–MODFLOW model is developed to assess shallow groundwater availability in the Borkena catchment. The model is calibrated using streamflow and static groundwater level data. Results show that groundwater recharge in the catchment is 85 mm/a, representing 11% of the mean annual rainfall. Shallow groundwater resources exist across nearly 42% of the Borkena catchment. The percentage of shallow groundwater withdrawal to groundwater recharge is very low (0.1%), signifying the potential for increased shallow groundwater development. However, caution must be taken as its uncontrolled expansion may result in a high risk of depletion. This integrated modeling is one of the few efforts conducted to provide important information regarding shallow groundwater potential in the Borkena catchment, which is essential for the resilience of small-scale producers in the continued growing water demand and climate change.