Abstract
Abstract. In this study a method for propagating the hydrological model uncertainty in discharge predictions of ungauged Mediterranean catchments using a model parameter regionalization approach is presented. The method is developed and tested for the Thau catchment located in Southern France using the SWAT hydrological model. Regionalization of model parameters, based on physical similarity measured between gauged and ungauged catchment attributes, is a popular methodology for discharge prediction in ungauged basins, but it is often confronted with an arbitrary criterion for selecting the "behavioral" model parameter sets (Mps) at the gauged catchment. A more objective method is provided in this paper where the transferrable Mps are selected based on the similarity between the donor and the receptor catchments. In addition, the method allows propagating the modeling uncertainty while transferring the Mps to the ungauged catchments. Results indicate that physically similar catchments located within the same geographic and climatic region may exhibit similar hydrological behavior and can also be affected by similar model prediction uncertainty. Furthermore, the results suggest that model prediction uncertainty at the ungauged catchment increases as the dissimilarity between the donor and the receptor catchments increases. The methodology presented in this paper can be replicated and used in regionalization of any hydrological model parameters for estimating streamflow at ungauged catchment.
Highlights
Hydrological models are generally calibrated against observation variable(s), typically streamflow, to estimate some parameters that cannot be measured directly and to achieve a reliable prediction of the watershed response
This paper aims to contribute to this challenge by addressing the following question: how can model parameter sets (Mps) uncertainty of donor catchments be propagated through regionalization schemes based on the similarity approach, and how does it affect the prediction uncertainty in ungauged catchments? Specific questions are as follows: (1) is the selected hydrological model suitable for reproducing the hydrology in the ungauged catchment? (2) How does parameter uncertainty affect model prediction uncertainty in the ungauged catchment through the regionalization scheme?
The reasons can be attributed to several uncertainty sources and to the subjectivity in the GLUE method involved at each modeling step (Xiong and O’Connor, 2008; Shrestha et al, 2009)
Summary
Hydrological models are generally calibrated against observation variable(s), typically streamflow, to estimate some parameters that cannot be measured directly and to achieve a reliable prediction of the watershed response. Various regionalization techniques have been developed to estimate streamflow in ungauged catchments including methods based on a similarity approach (Vandewiele and Elias, 1995; Idrissi et al, 1999; Merz and Blöschl, 2004; McIntyre et al, 2005; Oudin et al, 2008) and/or a statistical approach (Sivapalan et al, 2003; Yadav et al, 2007) The latter approach consists of deriving statistical relationships between catchment attributes (CAs), such as topography, soil, drainage area, etc., and the optimized model parameters (Mps). It can be considered as the most common regionalization approach for ungauged catchment (Wagener and Wheater, 2006), statistical approaches were deeply criticized due to the assumption that most statistical models consider linearity between CAs and optimized Mps
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