4.6 Article Proceedings Paper

Investigations of uncertainty in SWAT hydrologic simulations: a case study of a Canadian Shield catchment

Journal

HYDROLOGICAL PROCESSES
Volume 29, Issue 18, Pages 4000-4017

Publisher

WILEY
DOI: 10.1002/hyp.10477

Keywords

SWAT; uncertainty; GLUE; snow water equivalent; Harp Lake

Funding

  1. Ontario Ministry of Research and Innovation (MRI) Post Doctoral Fellowship Round 4
  2. Nipissing University
  3. Canada Foundation of Innovation Leaders Opportunity Fund
  4. Canada Research Chair Program

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Uncertainty analysis is an integral part of hydrological modelling. We investigated uncertainty from model structure and parameters in the soil and water assessment tool (SWAT) hydrologic simulations for a Canadian Shield catchment (5.4 km(2)) in south central Ontario. We investigated influences of model structure on parameter identifiability and prediction uncertainty by comparing model performance of SWAT (version 2009.10.1 Beta3) and SWAT-CS (a version representing hydrological processes in Canadian Shield catchments). Equifinality was found to exist for many parameters in process modules of snow water equivalent (SWE), streamflow and lake outflow. For SWAT, there are clearly identifiable parameters from process modules of snowmelt, overland flow, lateral flow and groundwater flow, while snowmelt parameters and lateral flow travel time are the only clearly identifiable parameters in SWAT-CS. Model structure also notably influenced the optimum parameter values. Only 50-55% of observed SWE and 27-43% of observed streamflow were bracketed by the corresponding 95% confidence interval. The prediction uncertainty for SWE was mainly caused by the inaccuracy in timing of simulated snowmelt. This, along with use of a daily time step that is not able to capture the subdaily rainfall on snow pack, the limited capability of simulating groundwater by SWAT and the close-to-zero streamflow during dry seasons at the study catchment, could all contribute to the prediction uncertainty in streamflow. Comparatively, more reasonable model structure (SWAT-CS) was shown to reduce prediction uncertainty. Copyright (c) 2015 John Wiley & Sons, Ltd.

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