Spatio‐temporal discretization uncertainty of distributed hydrological models

• Published in: Hydrological processes Vol. 36; no. 6
• Main Authors: Markhali, Siavash P., Poulin, Annie, Boucher, Marie‐Amélie
• Format: Journal Article
• Language: English
• Published: Hoboken, USA John Wiley & Sons, Inc 01.06.2022; Wiley Subscription Services, Inc
• Subjects: Calibration; Catchment area; Catchments; Discretization; distributed model; ensemble approach; flood modeling; flood modelling; Flooding; Hydrologic models; Hydrology; Modelling; Parameters; Resolution; Simulation; Spatial discrimination; Spatial resolution; spatio‐temporal discretization; Stream discharge; Stream flow; Temporal resolution; Temporal variability; Temporal variations; Uncertainty; Water balance
• ISSN: 0885-6087; 1099-1085
• DOI: 10.1002/hyp.14635

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 (water balance simulation model 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 and 1000 m2) and two temporal (3 and 24 h) 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 modelling, for each catchment. The catchments are further grouped into large (>1000 km2), medium (between 500 and 1000 km2) and small (<500 km2) 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 modelling. Regarding the role of CDs, 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 larger than that of CDs 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. A significant degree of uncertainty linked to the spatio‐temporal discretization of distributed hydrology models for estimation of extreme streamflow and other hydrological variables was observed. A meaningful link between the uncertainty of the spatio‐temporal discretization and catchment size could not be found, as the uncertainty can be seen across different catchment sizes. The temporal scale plays only a minor role in determining such uncertainty. The more physically representative a model is, the more sensitive it is to changes in spatio‐temporal resolution.