Abstract
This study aimed to investigate the influence of hydrological model calibration/validation on discharge projections for three large river basins (the Rhine, Upper Mississippi and Upper Yellow). Three hydrological models (HMs), which have been firstly calibrated against the monthly discharge at the outlet of each basin (simple calibration), were re-calibrated against the daily discharge at the outlet and intermediate gauges under contrast climate conditions simultaneously (enhanced calibration). In addition, the models were validated in terms of hydrological indicators of interest (median, low and high flows) as well as actual evapotranspiration in the historical period. The models calibrated using both calibration methods were then driven by the same bias corrected climate projections from five global circulation models (GCMs) under four Representative Concentration Pathway scenarios (RCPs). The hydrological changes of the indicators were represented by the ensemble median, ensemble mean and ensemble weighted means of all combinations of HMs and GCMs under each RCP. The results showed moderate (5–10%) to strong influence (> 10%) of the calibration methods on the ensemble medians/means for the Mississippi, minor to moderate (up to 10%) influence for the Yellow and minor (< 5%) influence for the Rhine. In addition, the enhanced calibration/validation method reduced the shares of uncertainty related to HMs for three indicators in all basins when the strict weighting method was used. It also showed that the successful enhanced calibration had the potential to reduce the uncertainty of hydrological projections, especially when the HM uncertainty was significant after the simple calibration.
Highlights
IntroductionEspecially at the regional scale, are of particular importance for developing climate adaptation strategies for different water-related sectors, such as water supply, hydropower production and agriculture
Reliable hydrological projections, especially at the regional scale, are of particular importance for developing climate adaptation strategies for different water-related sectors, such as water supply, hydropower production and agriculture
The bias-corrected climate scenarios based on the EWEMBI dataset include only 2 Representative Concentration Pathway scenarios (RCPs) and 4 global circulation models (GCMs) (Huang et al 2019), so they do not provide enough climate projections for a robust uncertainty analysis
Summary
Especially at the regional scale, are of particular importance for developing climate adaptation strategies for different water-related sectors, such as water supply, hydropower production and agriculture. The hydrological projections are usually generated following a complex modelling chain, including the Representative Concentration Pathway (RCP) scenarios, global circulation models (GCMs), statistical or dynamical downscaling, bias correction methods and hydrological models (HMs) (Olsson et al 2016 and Krysanova et al 2016). This modelling chain can lead to large uncertainty of hydrological projections, depending on the selection of the climate scenarios, climate and hydrological models as well as the downscaling and bias correction methods (Kundzewicz et al 2017). The results showed that the largest uncertainty was generally attributed to GCMs for most river basins while the HMs contributed notably to the uncertainty of projections for some snow-dominant basins or for low flows (Vetter et al 2017, Pechlivanidis et al 2017)
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