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Spatio-Temporal Discretization Uncertainty of Distributed Hydrological Models
  • Siavash Pouryousefi-Markhali,
  • Annie Poulin,
  • Marie-Amélie Boucher
Siavash Pouryousefi-Markhali
École de technologie supérieure

Corresponding Author:[email protected]

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Annie Poulin
École de Technologie Supérieure
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Marie-Amélie Boucher
Universite de Sherbrooke
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Quantifying the uncertainty linked to the degree to which the spatio-temporal variability of the catchment descriptors (CDs), and consequently calibration parameters (CPs), represented in the distributed hydrology models and its impacts on the simulation of flooding events is the main objective of this paper. Here, we introduce a methodology based on ensemble approach principles to characterize the uncertainties of spatio-temporal variations. We use two distributed hydrological models (WaSiM and Hydrotel) and six catchments with different sizes and characteristics, located in southern Quebec, to address this objective. We calibrate the models across four spatial (100, 250, 500, 1000 $m^2$) and two temporal (3 hours and 24 hours) resolutions. Afterwards, all combinations of CDs-CPs pairs are fed to the hydrological models to create an ensemble of simulations for characterizing the uncertainty related to the spatial resolution of the modeling, for each catchment. The catchments are further grouped into large ($>1000 km^2$), medium (between 500 and 1000 $km^2$) and small ($<500km^2$) to examine multiple hypotheses. The ensemble approach shows a significant degree of uncertainty (over $100\%$ error for estimation of extreme streamflow) linked to the spatial discretization of the modeling. Regarding the role of catchment descriptors, results show that first, there is no meaningful link between the uncertainty of the spatial discretization and catchment size, as spatio-temporal discretization uncertainty can be seen across different catchment sizes. Second, the temporal scale plays only a minor role in determining the uncertainty related to spatial discretization. Third, the more physically representative a model is, the more sensitive it is to changes in spatial resolution. Finally, the uncertainty related to model parameters is dominant larger than that of catchment descriptors for most of the catchments. Yet, there are exceptions for which a change in spatio-temporal resolution can alter the distribution of state and flux variables, change the hydrologic response of the catchments, and cause large uncertainties.
28 Sep 2021Submitted to Hydrological Processes
29 Sep 2021Submission Checks Completed
29 Sep 2021Assigned to Editor
04 Oct 2021Reviewer(s) Assigned
09 Dec 2021Review(s) Completed, Editorial Evaluation Pending
09 Dec 2021Editorial Decision: Revise Major
12 Feb 20221st Revision Received
14 Feb 2022Submission Checks Completed
14 Feb 2022Assigned to Editor
14 Feb 2022Reviewer(s) Assigned
18 Apr 2022Review(s) Completed, Editorial Evaluation Pending
20 Apr 2022Editorial Decision: Revise Minor
08 May 20222nd Revision Received
10 May 2022Submission Checks Completed
10 May 2022Assigned to Editor
10 May 2022Reviewer(s) Assigned
11 May 2022Review(s) Completed, Editorial Evaluation Pending
11 May 2022Editorial Decision: Revise Minor
31 May 20223rd Revision Received
08 Jun 2022Reviewer(s) Assigned
08 Jun 2022Submission Checks Completed
08 Jun 2022Assigned to Editor
08 Jun 2022Review(s) Completed, Editorial Evaluation Pending
09 Jun 2022Editorial Decision: Accept