@article{Kazma2026a,
abstract = {Quantifying uncertainty propagation in coupled hydrologic and hydrodynamic systems is critical for reliable design and operation of water resources infrastructure. Most existing approaches rely on Monte Carlo simulation or assume specific input distributions, which limits their scalability and applicability. This paper develops a distribution-agnostic state space framework for analyzing uncertainty propagation in coupled hydrologic and hydrodynamic systems. The proposed approach combines a nonlinear state space representation of the coupled dynamics with moment-based uncertainty propagation, and does not require assumptions on the distribution of the input uncertainty. Numerical case studies on benchmark watershed and river network models illustrate the accuracy and computational scalability of the framework compared to Monte Carlo baselines.},
archivePrefix = {arXiv},
arxivId = {2603.05740},
author = {Kazma, Mohamad H. and Taha, Ahmad F.},
doi = {10.1016/j.advwatres.2026.105389},
eprint = {2603.05740},
journal = {Advances in Water Resources},
title = {{Exploring Uncertainty Propagation in Coupled Hydrologic and Hydrodynamic Systems via Distribution-Agnostic State Space Analysis}},
url = {http://arxiv.org/abs/2603.05740},
year = {2026}
}