Sponsor
This research was supported by the U.S. Army Corps of Engineers Risk Management Center.
Published In
Water
Document Type
Article
Publication Date
3-7-2026
Subjects
Flood Frequency Analysis -- Texas, Urban floods; Bayesian analysis; nonstationarity; land use change; uncertainty; risk assessment; open-source software
Abstract
Urban flood frequency analysis faces unique challenges as land development alters watershed hydrology, producing nonstationary flood records. This study demonstrates nonstationary flood frequency analysis (NSFFA) using RMC-BestFit, an open-source Bayesian software, through two Texas case studies. Brays Bayou at Houston (96 years of record) exemplifies an urbanized watershed with increasing flood trends; a step-logistic model captures both the abrupt increase in mean flood magnitude around 1968 and the progressive decrease in log-space variance as urbanization homogenized runoff response. O.C. Fisher Reservoir (169 years of record) exhibits decreasing trends attributed to brush encroachment and groundwater extraction; despite a sinusoidal model achieving best information criteria, a step function was selected based on physical reasoning, demonstrating that statistical fit alone should not dictate model selection. Results reveal contrasting frequency curve patterns: at O.C. Fisher, stationary and nonstationary curves differ uniformly (53% reduction in 100-year flood), while at Brays Bayou, curves differ substantially for frequent events (48% increase in 2-year flood) but converge in the extreme tail due to opposing trends in location and scale parameters. These findings underscore that NSFFA relevance depends on decision context. Bayesian methods offer key advantages including flexible integration of diverse data sources, comprehensive uncertainty quantification, and principled model comparison. Open-source software democratizes access to these methods, promoting transparency and reproducibility.
Rights
Copyright (c) 2026 The Authors
This work is licensed under a Creative Commons Attribution 4.0 International License.
Locate the Document
DOI
10.3390/w18050636
Persistent Identifier
https://archives.pdx.edu/ds/psu/44542
Citation Details
Smith, C. H., Skahill, B., & Margo, D. A. (2026). Nonstationary Flood Frequency Analysis for Urban Watersheds Using Open-Source Bayesian Software: Contrasting Case Studies from Texas. Water, 18(5), 636.