Continuous streamflow prediction in ungauged basins: The effects of equifinality and parameter set selection on uncertainty in regionalization approaches

Abstract

This paper focuses on evaluating the uncertainty of three common regionalization methods for predicting continuous streamflow in ungauged basins. A set of 268 basins covering 1.6 million km 2 in the province of Quebec was used to test the regionalization strategies. The multiple linear regression, spatial proximity, and physical similarity approaches were evaluated on the catchments using a leave-one-out cross-validation scheme. The lumped conceptual HSAMI hydrological model was used throughout the study. A bootstrapping method was chosen to further estimate uncertainty due to parameter set selection for each of the parameter set/regionalization method pairs. Results show that parameter set selection can play an important role in regionalization method performance depending on the regionalization methods (and their variants) used and that equifinality does not contribute significantly to the overall uncertainty witnessed throughout the regionalization methods applications. Regression methods fail to consistently assign behavioral parameter sets to the pseudoungauged basins (i.e., the ones left out). Spatial proximity and physical similarity score better, the latter being the best. It is also shown that combining either physical similarity or spatial proximity with the multiple linear regression method can lead to an even more successful prediction rate. However, even the best methods were shown to be unreliable to an extent, as successful prediction rates never surpass 75%. Finally, this paper shows that the selection of catchment descriptors is crucial to the regionalization strategies' performance and that for the HSAMI model, the optimal number of donor catchments for transferred parameter sets lies between four and seven.

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“…Snowpacks in continental climates tend to be much more polythermal and less dense than snowpacks in maritime climates (Armstrong and Armstrong, 1987;DeWalle and Rango, 2008;Barry, 2008). Higher densities in maritime snowpacks are partially caused by atmospheric conditions Figure 2.…”

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Generation of Natural Runoff Monthly Series at Ungauged Sites Using a Regional Regressive Model

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Evaluation of Regionalization Methods for Hourly Continuous Streamflow Simulation Using Distributed Models in Boreal Catchments

“…Merz and Blöschl, 2004;Parajka et al, 2005) or multi-donor nearby catchments (e.g. Parajka et al, 2005;Oudin et al, 2008;Samuel et al, 2011;Arsenault and Brissette, 2014).…”

“…Kokkonen et al, 2003;McIntyre et al, 2005;Parajka et al, 2005;Oudin et al, 2008;Reichl et al, 2009;Zhang and Chiew, 2009;Samuel et al, 2011;Arsenault and Brissette, 2014), which is based on the assumption that similarity in some physical attributes that govern the runoff response could explain the hydrological similarity. This method is also based on either a single-donor catchment or multi-donor catchments.…”