Authors: Parthkumar Modi, Sifan Koriche, Steven Burian – University of Alabama
Presentation Type: Poster Presentation
Title: Investigating the Impacts of Forcing Heterogeneities in the Next Generation Water Resources Modeling Framework
Presentation Type: Poster Presentation
Abstract: Hydrological model accuracy is strongly influenced by how meteorological forcing is represented, yet commonly used forcing products smooth the inherent space–time variability of precipitation. This loss of variability can lead to biased streamflow simulations, especially during extreme localized storm events. We hypothesize that integrating high-resolution space–time forcing into the NextGen Water Resources Modeling Framework will significantly improve simulated peak flows and reduce bias. To test this hypothesis, we develop a reproducible workflow within NextGen that enables parallel simulations driven by uniform and distributed forcing. Calibrated models are applied across selected hydroclimatic regions during periods characterized by extreme localized precipitation events. Model outputs are evaluated against U.S. Geological Survey streamflow observations, with emphasis on total bias, peak flow magnitude, and peak timing accuracy. This work provides a targeted assessment of forcing-resolution impacts within NextGen and advances guidance for improving hydrologic prediction of extreme events using next-generation frameworks.