Multimodel evaluation of twenty lumped hydrological models under contrasted climate conditions

Abstract

Abstract. This paper investigates the temporal transposability of hydrological models under contrasted climate conditions and evaluates the added value of using an ensemble of model structures for flow simulation. This is achieved by applying the Differential Split Sample Test procedure to twenty lumped conceptual models on a catchment in the Province of Québec (Canada) and another one in the State of Bavaria (Germany). First, a calibration/validation procedure was applied on four historical non-continuous periods with contrasted climate conditions. Then, model efficiency was quantified individually (for each model) and collectively (for the model ensemble). The individual analysis evaluated model performance and robustness. The ensemble investigation, based on the average of simulated discharges, focused on the twenty-member ensemble and all possible model subsets. Results showed that using a single model may provide hazardous results when the model is to be applied in contrasted conditions. Overall, some models turned out as a good compromise in terms of performance and robustness, but generally not as much as the twenty-model ensemble. Model subsets offered yet improved performance over the twenty-model ensemble, but at the expanse of spatial transposability (i.e. need of site-specific analysis).

Climate change impacts on the hydrologic regime of a Canadian river: comparing uncertainties arising from climate natural variability and lumped hydrological model structures

“…The interquartile range is more uniform from one model to the other than in Fig. 8, but M08 differs (18.1 %) in that regard -M08 was already identified with poor transposability on the same catchment by Seiller et al (2012). The lowest inner sensitivity is achieved by M11 (10.9 %).…”

“…Such methodology assumes that the parameter sets are compatible for current and future climatic conditions, addressing the issue of transposability. Transposability in time, on contrasted climatic conditions, is discussed for the same catchment and models in Seiller et al (2012). T is temperature, P is total precipitation, P L is liquid precipitation, P G is solid precipitation, and M is snowmelt.…”

“…In some cases, when the sensitivity was considered small, their designers have fixed some of their parameters in order to favour the parsimony of the models, reducing computation time and equifinality issues. These models, or part of, were exploited by Velázquez et al (2010) for exploring multimodel ensemble forecasting and by Seiller et al (2012) for assessing the robustness of the ensemble under contrasted climate.…”

“…from 1975 to 2003) -differential split sample tests were performed in Seiller et al (2012). It relies on the Shuffled Complex Evolution (SCE) algorithm (Duan and Gupta, 1992;Duan et al, 1994), a robust heuristic automatic optimisation tool (error minimisation) that is common in hydrological sciences and is known for its performance (e.g.…”

Identification of hydrological model parameter variation using ensemble Kalman filter

“…In hydrological modeling, parameters are usually assumed to be stationary; i.e., the calibrated parameters are constants during the calibration period, and have extrapolative ability outside the range of the observations used for parameter estimation (Merz et al, 2011). The estimated parameters usually depend on the calibration period since the calibration period may contain different climatic conditions and hydrological regimes compared to the simulation period (Merz et al, 2011;Zhang et al, 2011;Coron et al, 2012;Seiller et al, 2012;Westra et al, 2014;Patil and Stieglitz, 2015). The model parameters may change as a response to the variations in climatic conditions and catchment properties.…”