Ensemble methods for history matching and uncertainty quantification with a watershed model

Journal of the American Water Resources Association
By: , and 

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Abstract

History matching of large hydrologic models is challenging due to data sparsity and non-unique process combinations (and associated parameters) that can produce similar model predictions. We develop an ensemble-based history matching (and uncertainty quantification) approach using an iterative ensemble smoother (iES) method for three cutouts of the National Hydrologic Model (NHM) and qualitatively compare the results and performance to the stepwise history matching approach. In the latter approach, subsets of parameters and observations were sequentially calibrated to a diverse range of observations to mitigate non-uniqueness and local minima. In iES, localization simulates the same causal connections between parameters and observations without the need (and computational cost) of sequential history matching steps. iES uses a weighted sum-of-squared-errors objective function which allows differential weighting of multiple data sources. Formal adoption of range observation also pushes results to within ranges of observation values rather than discrete values. Overall, the ensemble approach performs similarly to the stepwise approach. Both approaches performed poorly for the cutout representing a snowmelt-dominated watershed, indicating a structural issue in the process representation of the model. The main advantage of iES is quantification of uncertainty in both the history matching and the predictions of interest.

Suggested Citation

Fienen, M., Long, A.J., Markovich, K.H., Haj, A.E., Barker, M., 2026, Ensemble methods for history matching and uncertainty quantification with a watershed model: Journal of the American Water Resources Association, v. 62, no. 1, e70086, 18 p., https://doi.org/10.1111/1752-1688.70086.

Study Area

Publication type Article
Publication Subtype Journal Article
Title Ensemble methods for history matching and uncertainty quantification with a watershed model
Series title Journal of the American Water Resources Association
DOI 10.1111/1752-1688.70086
Volume 62
Issue 1
Publication Date February 04, 2026
Year Published 2026
Language English
Publisher Wiley
Contributing office(s) Upper Midwest Water Science Center
Description e70086, 18 p.
Country United States
Additional publication details