Abstract
The quantification of uncertainty in the ensemble-based predictions of climate change and the corresponding hydrological impact is necessary for the development of robust climate adaptation plans. Although the equifinality of hydrological modeling has been discussed for a long time, its influence on the hydrological analysis of climate change has not been studied enough to provide a definite idea about the relative contributions of uncertainty contained in both multiple general circulation models (GCMs) and multi-parameter ensembles to hydrological projections. This study demonstrated that the impact of multi-GCM ensemble uncertainty on direct runoff projections for headwater watersheds could be an order of magnitude larger than that of multi-parameter ensemble uncertainty. The finding suggests that the selection of appropriate GCMs should be much more emphasized than that of a parameter set among behavioral ones. When projecting soil moisture and groundwater, on the other hand, the hydrological modeling equifinality was more influential than the multi-GCM ensemble uncertainty. Overall, the uncertainty of GCM projections was dominant for relatively rapid hydrological components while the uncertainty of hydrological model parameterization was more significant for slow components. In addition, uncertainty in hydrological projections was much more closely associated with uncertainty in the ensemble projections of precipitation than temperature, indicating a need to pay closer attention to precipitation data for improved modeling reliability. Uncertainty in hydrological component ensemble projections showed unique responses to uncertainty in the precipitation and temperature ensembles.
Highlights
General circulation models (GCMs) have been developed by many national and international research institutions and agencies and served as useful, and probably the only kind of tools to predict future climate[1,2]
The annual average precipitation of the Ohio River watersheds was projected to increase by 6.8% and 8.8% from 2020 to 2099 under the Representative Concentration Pathway (RCP)
The results showed that the uncertainty of general circulation models (GCMs) projections are dominant for relatively rapid hydrological components while the uncertainty of parameterization is more significant for slow components
Summary
General circulation models (GCMs) have been developed by many national and international research institutions and agencies and served as useful, and probably the only kind of tools to predict future climate[1,2]. Climate model selection is a watershed modeler’s first decision in a hydrological analysis of climate change, but it is one of the most critical ones. Multi-GCM ensembles have served as a framework for accommodating probabilistic approaches in interpreting climate predictions and developing climate adaptation plans, and many studies have attempted to quantify uncertainty with www.nature.com/scientificreports/. Simpler models are preferable as long as they can predict hydrological variables and components of interest at the required levels of accuracy and detail, especially when the overall far future hydrological responses of a watershed are of interest
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