A Simplified Approach to Modelling Groundwater Dynamics in Complex, Data-Scarce Semi-Arid Basins

Groundwater is a vital component of the global hydrological cycle, supporting stream flows, vegetation, and serving as a critical water source during droughts. In semi-arid regions, where rainfall is erratic and surface water resources are limited, groundwater plays a key role in sustaining agriculture and economic activities. However, these regions face compounded challenges due to climatic variability and human activities, leading to significant groundwater stress. Large-scale hydrological models offer insights into broad-scale dynamics but often lack the resolution needed to address region-specific issues, particularly in data-scarce areas where human influences like groundwater extraction significantly alter the hydrological cycle. These limitations underscore the need for localized models that integrate detailed information on human water use and extraction to enhance understanding of groundwater dynamics. The semi-arid Noyil River Basin, characterized by intense human activity and climatic stress, is used in this study to demonstrate the proposed modeling methods. Developing groundwater models in this data-scarce environment is particularly challenging due to insufficient data on recharge and extraction, as well as the complexity of accounting for diverse land-use types. To address these challenges, this study employs a water table fluctuation-based conceptual model (AMBHAS-1D) to estimate recharge and groundwater draft. The outputs from this model are then integrated into numerical transient groundwater model built using MODFLOW, enabling detailed simulations of aquifer responses to climatic and anthropogenic pressures. The study demonstrates how calibrated time series outputs from a simple 1-D model can serve as effective inputs for a more sophisticated transient numerical model. The transient model operates without additional calibration, relying solely on the 1-D model’s outputs, making it particularly suitable for data scarce basins with unpredictable rainfall and significant groundwater reliance. The approach allows for detailed analysis of groundwater dynamics, including flow behavior during dry periods and the impacts of human extraction and climatic variability. The study highlights the importance of incorporating fine-scale human water use, which is often overlooked in data-limited regions. By addressing the challenges of modeling in data-scarce, water-stressed basins, this study provides a framework for more effective groundwater management, particularly in regions where groundwater serves as the primary water source during drought periods.