Incorporating Uncertainty Into Multiscale Parameter Regionalization to Evaluate the Performance of Nationally Consistent Parameter Fields for a Hydrological Model

Rosanna A. Lane*, Jim E. Freer, Gemma Coxon, Thorsten Wagener

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

Abstract

Spatial parameter fields are required to model hydrological processes across diverse landscapes. Transfer functions are often used to relate parameters to spatial catchment attributes, introducing large uncertainties. Quantifying these uncertainties remains a key challenge for large-scale modeling. This paper extends the multiscale parameter regionalization (MPR) technique to consider parameter uncertainties. We evaluate this method of producing nationally consistent parameter fields, which maintain a constant relationship between model parameters and catchment attributes, across 437 catchments in Great Britain (GB). By sampling multiple transfer function parameters, we produce thousands of possible model parameter fields which are constrained within an uncertainty framework. This is compared to spatially homogeneous parameter sets constrained for individual catchments. The nationally consistent MPR parameter fields perform well (KGE* > 0.75) across 60% of catchments. Performance is similar or better than catchment-constrained parameters (KGE* drop < 0.1) across 82% of catchments. Advantages of our national parameter fields include (a) improved representation of flows within catchments, (b) more robust performance between calibration and evaluation periods, and (c) spatial parameter fields reflecting hydrologically meaningful variation in catchment characteristics. By including uncertainties, we show that hydrographs produced using MPR have smaller uncertainty bounds which are better able to encompass flows. As the first application of MPR to both the DECIPHeR modeling framework and GB, we developed transfer functions and identified key catchment attributes to constrain model parameters, which are transferrable to other models alongside the addition of uncertainty. Methodologies presented here are informative for future regionalization efforts in GB and elsewhere.

Original languageEnglish
Article numbere2020WR028393
JournalWater Resources Research
Volume57
Issue number10
DOIs
Publication statusPublished - 1 Oct 2021

Bibliographical note

Funding Information:
Rosanna A. Lane was funded as part of the Water Informatics Science and Engineering Center for Doctoral Training (WISE CDT) under a grant from the Engineering and Physical Sciences Research Council (EPSRC; Grant No. EP/L016214/1). Gemma Coxon was supported by NERC MaRIUS: Managing the Risks, Impacts, and Uncertainties of droughts and water Scarcity, Grant No. NE/L010399/1. Jim Freer was partly funded for his time by the Global Water Futures program, University of Saskatchewan. Funding for Thorsten Wagener came from the Alexander von Humboldt Foundation in the framework of the Alexander von Humboldt Professorship endowed by the German Federal Ministry of Education and Research.

Funding Information:
Rosanna A. Lane was funded as part of the Water Informatics Science and Engineering Center for Doctoral Training (WISE CDT) under a grant from the Engineering and Physical Sciences Research Council (EPSRC; Grant No. EP/L016214/1). Gemma Coxon was supported by NERC MaRIUS: Managing the Risks, Impacts, and Uncertainties of droughts and water Scarcity, Grant No. NE/L010399/1. Jim Freer was partly funded for his time by the Global Water Futures program, University of Saskatchewan. Funding for Thorsten Wagener came from the Alexander von Humboldt Foundation in the framework of the Alexander von Humboldt Professorship endowed by the German Federal Ministry of Education and Research.

Publisher Copyright:
© 2021. American Geophysical Union. All Rights Reserved.

Keywords

  • DECIPHeR
  • Great Britain
  • hydrological modeling
  • parameterization
  • regionalization
  • uncertainty

Fingerprint

Dive into the research topics of 'Incorporating Uncertainty Into Multiscale Parameter Regionalization to Evaluate the Performance of Nationally Consistent Parameter Fields for a Hydrological Model'. Together they form a unique fingerprint.

Cite this