Development of a Web-Based Early-Warning System for Seasonal Hydrogeological Drought Prediction and Assessment of Water Resource Resilience in a Transboundary Karst System

Quantification and prediction of droughts have mainly been focused on the surface and/or meteorological components of the water cycle due to the complex nature of subsurface processes and limited observational data on the hydrogeological component of the water cycle. A web-based Early Warning System (EWS) has been developed to predict seasonal hydrogeological droughts and to assess the resilience of subsurface water resources in the West Bank transboundary karst system, which encompasses the territories of Israel and the Palestinian regions of the West Bank. This innovative tool integrates the monthly-released seasonal weather prediction data from the Copernicus Climate Change Service with a surrogate hydrogeological model to predict the functioning of the karst hydrogeological system and characterize its potential drought conditions. A multi-model ensemble (MME) of daily seasonal predictions has been considered to quantify the spatiotemporal uncertainty of daily climatic variables, which subsequently translates to recharge, storage, and discharge in the subsurface, to be highlighted as the ranges of hydrogeological drought indices. The surrogate deep auto-regressive neural network model (Deep-AR-Net), is utilized to reduce the computational burden of a process-based variably-saturated double-permeability model of the region. The EWS incorporates multiple variables of the MME, including precipitation and temperature, along with flow observations on groundwater levels and spring discharges, to predict hydrogeological conditions during the upcoming six months via Deep-AR-Net. The EWS presents results through an interactive map interface and graphical displays, allowing water resource managers to visualize potential droughts and compare predictions against established drought index thresholds. The development of the EWS is a significant advancement in hydrogeological drought prediction and water resource management for karst systems in arid and semi-arid region. By providing a shared platform for data analysis and visualization, it facilitates collaborative decision-making and helps to prevent potential conflicts related to water use in this sensitive region, which has always been under significant water stress and political tension. More specifically, it will support water managers and policymakers as a powerful instrument to enhance drought preparedness, optimize water allocation, and implement timely mitigation strategies in the face of increasing climate variability and water scarcity.