Analysis of Groundwater Systems Using Lumped and Distributed Hydrological Models: Applications in Indian Tropical Region

Abstract

Groundwater is a critical resource for meeting agriculture, domestic, and industrial water demand, particularly in tropical regions of India. However, increasing groundwater extraction, erratic monsoonal rainfall, and inadequate recharge have led to widespread groundwater depletion, necessitating improved assessment and management strategies. This research employs lumped and distributed hydrological models to enhance the understanding of groundwater recharge mechanisms, assess the effectiveness of Managed Aquifer Recharge (MAR) interventions, and refine integrated distributed hydrological model calibration techniques. The study investigates episodic high recharge events and their association with high-intensity rainfall events, emphasizing the need to capture indirect recharge processes in hydrological models. It further evaluates MAR interventions, including the rehabilitation of minor irrigation (MI) tanks in Andhra Pradesh and indirect recharge using treated wastewater in Kolar, Karnataka, demonstrating their potential to significantly enhance groundwater availability. Furthermore, an integrated distributed hydrological model (VIC-AMBHAS) is used to model the hydrological response of a tropical watershed. The study employs time-varying and time-aggregated sensitivity analyses to identify and rank the most important model parameters along with most sensitive calibration variables. To improve model accuracy, a multivariate-multisite calibration framework is employed, reducing uncertainties in groundwater predictions and improving long-term resource assessment. This approach is tested in the Berambadi watershed, addressing challenges related to data scarcity in model calibration and validation using a multivariate approach. By integrating field data, remote sensing datasets, and numerical modeling, this study provides valuable insights for sustainable groundwater management, supporting informed decision-making in irrigation planning, policy formulation, and large-scale water conservation strategies.