Impacts of Incorporating Anthropogenic Water Use in a High-Resolution Spatially Distributed Hydrological Model on Simulated Basin-Scale Discharges

Abstract

Including anthropogenic water use in hydrological models is important for basin water management. However, the conditions under which this complexity improves the accuracy of discharge simulation remain poorly understood. Using the Rhine basin as a case study, this study evaluates how explicitly accounting for abstraction and return flows affects simulated hydrological processes at ∼1 km resolution. Two model experiments, with and without anthropogenic water use, are evaluated against daily discharge observations from 116 gauging stations over the period 1990–2020 using KGE and its components. Extreme flow analysis is applied at selected stations to evaluate changes in simulated extremes. Simulated total water abstraction shows stronger agreement with reported sub-national statistics at coarser spatial scales ((Formula presented.) = 0.88) but deteriorates at finer scales ((Formula presented.) = 0.43) due to downscaling uncertainties and the use of coarse demand data. The overall impact on discharge performance is modest and spatially heterogeneous, with no significant improvement at the basin scale ((Formula presented.), rank-biserial (Formula presented.)). At larger rivers, including anthropogenic water use yields a small median improvement by reducing high-flow overestimation through increased storage capacity ((Formula presented.) = 0.036). Small-to-moderate rivers respond more strongly to water demand inputs, particularly during summer low-flow periods. Simulated low-flow extremes remain difficult to constrain without more detailed observational data, suggesting that current assumptions do not hold uniformly across the basin. These findings indicate that improving the accuracy of modeled anthropogenic water use requires advances in return flow process representation, demand allocation, and water use observations.