Application of SWAT Model with a Modified Groundwater Module to the Semi-Arid Hailiutu River Catchment, Northwest China

Ecological Impact Prediction of Groundwater Change in Phreatic Aquifer under Multi-Mining Conditions

In aeolian sandy grass shoal catchment areas that rely heavily on groundwater, mining-induced geological deformation and aquifer drainage are likely to cause irreversible damage to natural groundwater systems and affect the original circulation of groundwater, thus threatening the ecological environment. This study aimed to predict the impact of groundwater level decline on vegetation growth in the Hailiutu River Basin (HRB), which is a coal-field area. Based on remote-sensing data, the land use/cover change was interpreted and analyzed, and the central areas of greensward land in the basin were determined. Subsequently, the correlation between groundwater depth and grassland distribution was analyzed. Then, the groundwater system under natural conditions was modeled using MODFLOW, and the groundwater flow field in 2029 was predicted by loading the generalized treatment of coal mine drainage water to the model. The change in groundwater depth caused by coal mining and its influence on the grassland were obtained. The results show that coal mining will decrease the groundwater depth, which would induce degradation risks in 4 of the original 34 aggregation centers of greensward land that originally depended on groundwater for growth in HRB because they exceeded the groundwater threshold. The prediction results show that the maximum settlement of groundwater level can reach 5 m in the northern (Yinpanhao), 6 m in the eastern (Dahaize), and 10 m in the southern (Balasu) region of HRB. Attention should be paid to vegetation degradation in areas where groundwater depth exceeds the minimum threshold for plant growth.

Modelling groundwater quality of the Athabasca River Basin in the subarctic region using a modified SWAT model

Groundwater is a vital resource for human welfare. However, due to various factors, groundwater pollution is a paramount environmental concern. It is challenging to simulate groundwater quality dynamics with the Soil and Water Assessment Tool (SWAT) because it does not adequately model nutrient percolation processes in the soil. The objectives of this study were to extend the SWAT module to simulate groundwater quality for the parameters nitrate and Total Dissolved Solids (TDS). The results of the SWAT model for the Athabasca River Basin in Canada revealed a linear relationship between observed and calculated groundwater quality. This result achieved satisfactory values for coefficient of determination (R²), Nash-Sutcliffe efficiency (NSE), and percent bias (PBIAS). For nitrate, the model performance measures R² ranged from 0.66–0.83 during calibration and NSE from 0.61–0.83. R² is 0.71 during validation and NSE ranged from 0.69–0.75. Likewise, for TDS, the model performance measures R² ranged from 0.61–0.82 during calibration and from 0.58–0.62 during validation. When coupled with soil zone and land surface processes, nitrate and TDS concentrations in groundwater can be simulated with the SWAT model. This indicated that SWAT may be helpful in evaluating adaptive management scenarios. Hence, the extended SWAT model could be a powerful tool for regional-scale modelling of nutrient loads, and to support and effective surface and groundwater management.

Afforestation of Degraded Croplands as a Water-Saving Option in Irrigated Region of the Aral Sea Basin

Climate change is likely to decrease surface water availability in Central Asia, thereby necessitating land use adaptations in irrigated regions. The introduction of trees to marginally productive croplands with shallow groundwater was suggested for irrigation water-saving and improving the land’s productivity. Considering the possible trade-offs with water availability in large-scale afforestation, our study predicted the impacts on water balance components in the lower reaches of the Amudarya River to facilitate afforestation planning using the Soil and Water Assessment Tool (SWAT). The land-use scenarios used for modeling analysis considered the afforestation of 62% and 100% of marginally productive croplands under average and low irrigation water supply identified from historical land-use maps. The results indicate a dramatic decrease in the examined water balance components in all afforestation scenarios based largely on the reduced irrigation demand of trees compared to the main crops. Specifically, replacing current crops (mostly cotton) with trees on all marginal land (approximately 663 km2) in the study region with an average water availability would save 1037 mln m3 of gross irrigation input within the study region and lower the annual drainage discharge by 504 mln m3. These effects have a considerable potential to support irrigation water management and enhance drainage functions in adapting to future water supply limitations.

Assessment of the Future Climate Change Projections on Streamflow Hydrology and Water Availability over Upper Xijiang River Basin, China

Hydrological models are widely applied for simulating complex watershed processes and directly linking meteorological, topographical, land-use, and geological conditions. In this study, the Soil and Water Assessment Tool (SWAT) was calibrated at two monitoring stations, which improved model performance and increased the reliability of flow predictions in the Upper Xijiang River Basin. This study evaluated the potential impacts of climate change on the streamflow and water yield of the Upper Xijiang River Basin using Arc-SWAT. The model was calibrated (1991–1997) and validated (1998–2001) using the Sequential Uncertainty Fitting Algorithm (SUFI-2). Model calibration and validation suggest a good match between the measured and simulated monthly streamflow, indicating the applicability of the model for future daily streamflow predictions. Large negative changes of low flows are projected under future climate scenarios, exhibiting a 10% and 30% decrease in water yield over the watershed on a monthly scale. Overall, findings generally indicated that winter flows are expected to be affected the most, with a maximum impact during the January–April period, followed by the wet monsoon season in the May–September period. Water balance components of the Upper Xijiang River Basin are expected to change significantly due to the projected climate change that, in turn, will seriously affect the water resources and streamflow patterns in the future. Thus, critical problems, such as ground water shortages, drops in agricultural crop yield, and increases in domestic water demand are expected at the Xijiang River Basin.

A Novel Approach for the Integral Management of Water Extremes in Plain Areas

: Due to the socioeconomical impact of water extremes in plain areas, there is a considerable demand for suitable strategies aiding in the management of water resources and rainfed crops. Numerical models allow for the modelling of water extremes and their consequences in order to decide on management strategies. Moreover, the integration of hydrologic models with hydraulic models under continuous or event-based approaches would synergistically contribute to better forecasting of water extreme consequences under different scenarios. This study conducted at the Santa Catalina stream basin (Buenos Aires province, Argentina) focuses on the integration of numerical models to analyze the hydrological response of plain areas to water extremes under different scenarios involving the implementation of an eco-efficient infrastructure (i.e., the integration of a green infrastructure and hydraulic structures). The two models used for the integration were: the Soil and Water Assessment Tool (SWAT) and the CELDAS8 (CTSS8) hydrologic-hydraulic model. The former accounts for the processes related to the water balance (e.g., evapotranspiration, soil moisture, percolation, groundwater discharge and surface runoff), allowing for the analysis of water extremes for either dry or wet conditions. Complementarily, CTSS8 models the response of a basin to a rainfall event (e.g., runoff volume, peak flow and time to peak flow, flooded surface area). A 10-year data record (2003–2012) was analyzed to test different green infrastructure scenarios. SWAT was able to reproduce the waterflow in the basin with Nash Sutcliffe (NS) efficiency coefficients of 0.66 and 0.74 for the calibration and validation periods, respectively. The application of CTSS8 for a flood event with a return period of 10 years showed that the combination of a green infrastructure and hydraulic structures decreased the surface runoff by 28%, increased the soil moisture by 10% on an average daily scale, and reduced the impact of floods by 21% during rainfall events. The integration of continuous and event-based models for studying the impact of water extremes under different hypothetical scenarios represents a novel approach for evaluating potential basin management strategies aimed at improving the agricultural production in plain areas.