Journal cover Journal topic
Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
doi:10.5194/hess-2016-642
© Author(s) 2016. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
22 Dec 2016
Review status
A revision of this discussion paper is under review for the journal Hydrology and Earth System Sciences (HESS).
Characterizing and reducing equifinality by constraining a distributed catchment model with regional signatures, local observations, and process understanding
Christa Kelleher1,2, Brian McGlynn2, and Thorsten Wagener3,4 1Department of Earth Sciences, Syracuse University, Syracuse, NY, 13244, USA
2Department of Earth and Ocean Sciences, Nicholas School of the Environment, Duke University, Durham, NC, 27706, USA
3Department of Civil Engineering, University of Bristol, Bristol, BS8 1TR, UK
4Cabot Institute, University of Bristol, Bristol, BS8 1TR, UK
Abstract. Distributed catchment models are widely used tools for predicting hydrologic behaviour. While distributed models require many parameters to describe a system, they are expected to simulate behaviour 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 ‘behavioural’ sets that fit observations (typically streamflow). In this study, we investigate the extent to which equifinality impacts a typical distributed modelling application. We outline a hierarchical approach to reduce the number of behavioural 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 ‘behavioural’ parameter sets and increased certainty in spatio-temporal simulations, simulating a well-studied headwater catchment, Stringer Creek, MT 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 further reduced the number of behavioural 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 behavioural parameter sets can reduce equifinality and bolster more careful application and simulation of spatio-temporal processes via distributed modelling at the catchment scale.

Citation: Kelleher, C., McGlynn, B., and Wagener, T.: Characterizing and reducing equifinality by constraining a distributed catchment model with regional signatures, local observations, and process understanding, Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2016-642, in review, 2016.
Christa Kelleher et al.
Christa Kelleher et al.
Christa Kelleher et al.

Viewed

Total article views: 763 (including HTML, PDF, and XML)

HTML PDF XML Total BibTeX EndNote
705 53 5 763 3 11

Views and downloads (calculated since 22 Dec 2016)

Cumulative views and downloads (calculated since 22 Dec 2016)

Viewed (geographical distribution)

Total article views: 763 (including HTML, PDF, and XML)

Thereof 762 with geography defined and 1 with unknown origin.

Country # Views %
  • 1

Saved

Discussed

Latest update: 30 Mar 2017
Publications Copernicus
Download
Short summary
Models are tools for understanding how watersheds function and may respond to land cover and climate change. Before we can use models towards these purposes, we need to ensure that a model adequately represents watershed-wide observations. In this paper, we propose a new way to evaluate whether model simulations match observations, using a variety of information sources. We show how this information can reduce uncertainty in inputs to models, leading to greater certainty in our predictions.
Models are tools for understanding how watersheds function and may respond to land cover and...
Share