Leveraging satellite data for enhanced uncertainty reduction in hydrological modeling: Implications for water resources management

WaterALLOC, developed by RTI International, is a modeling framework which couples a hydrologic modeling system with a water allocation and river operations modeling system. The two systems are the HydroBID rainfall-runoff model, which estimates the availability of surface water at the regional, basin, and sub-basin scales, and the MODSIM model, for river basin operation and planning. The MODSIM model includes features for water allocation, water accounting, and reservoir operations. WaterALLOC provides a set of useful tools for calibrating the hydrologic model and simulate scenarios for water resources management. Uncertainties in model calibration can pose challenges for water resources planning and water allocation analyses, especially in data scarce regions. The water allocation uncertainty factors include model calibration parameters, climate factors, water use, river and reservoir operations, population growth, land use changes, policy changes, technology changes, and water consumption changes. A tool has been created within WaterALLOC to automate the retrieval and processing of satellite-based precipitation and temperature estimate from NASA POWER. The data is globally available from January 1981 to near-real time. This study focuses on (1) evaluating the performance of the WaterALLOC modeling system with satellite data compared to traditional processing of local precipitation and temperature local point data and (2) comparing the uncertainty of the climate sources with the uncertainty of the various model parameters and factors related to anthropogenic effects in estimating historical natural flows. This research contributes to the broader understanding of source of uncertainty for water resources planning, especially utilizing satellite data in river basin modeling and highlights the potential of WaterALLOC as a cost-effective and flexible modeling system that can adapt to evolving water supply challenges and future decision-making needs.