Characterizing and reducing equifinality by constraining a distributed catchment model with regional signatures, local observations, and process understanding

Christa Kelleher, Brian McGlynn, Thorsten Wagener

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

Distributed catchment models are widely used tools for predicting hydrologic behavior. While distributed models require many parameters to describe a system, they are expected to simulate behavior that is more consistent with observed processes. However, obtaining a single set of acceptable parameters can be problematic, as parameter equifinality often results in several "behavioral" sets that fit observations (typically streamflow). In this study, we investigate the extent to which equifinality impacts a typical distributed modeling application. We outline a hierarchical approach to reduce the number of behavioral sets based on regional, observation-driven, and expert-knowledge-based constraints. For our application, we explore how each of these constraint classes reduced the number of "behavioral" parameter sets and altered distributions of spatiotemporal simulations, simulating a well-studied headwater catchment, Stringer Creek, Montana, using the distributed hydrology-soil-vegetation model (DHSVM). As a demonstrative exercise, we investigated model performance across 10 000 parameter sets. Constraints on regional signatures, the hydrograph, and two internal measurements of snow water equivalent time series reduced the number of behavioral parameter sets but still left a small number with similar goodness of fit. This subset was ultimately further reduced by incorporating pattern expectations of groundwater table depth across the catchment. Our results suggest that utilizing a hierarchical approach based on regional datasets, observations, and expert knowledge to identify behavioral parameter sets can reduce equifinality and bolster more careful application and simulation of spatiotemporal processes via distributed modeling at the catchment scale.

Original languageEnglish (US)
Pages (from-to)3325-3352
Number of pages28
JournalHydrology and Earth System Sciences
Volume21
Issue number7
DOIs
StatePublished - Jul 5 2017

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catchment
snow water equivalent
parameter
hydrograph
headwater
modeling
simulation
streamflow
hydrology
time series
groundwater
vegetation
soil

ASJC Scopus subject areas

  • Water Science and Technology
  • Earth and Planetary Sciences (miscellaneous)

Cite this

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