Uncertainty in high‐resolution hydrological projections: Partitioning the influence of climate models and natural climate variability
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- doi: 10.1002/hyp.14695
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Water Science and TechnologySujets proches
Science of climate Climate Climate scienceCiter ce document
Jorge Sebastián Moraga et al., « Uncertainty in high‐resolution hydrological projections: Partitioning the influence of climate models and natural climate variability », Serveur académique Lausannois, ID : 10.1002/hyp.14695
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A major challenge in assessing the impacts of climate change on hydrological processes lies in dealing with large degrees of uncertainty in the future climate projections. Part of the uncertainty is owed to the intrinsic randomness of climate phenomena, which is considered irreducible. Additionally, modelling the response of hydrological processes to the changing climate requires the use of a chain of numerical models, each of which contributes some degree of uncertainty to the final outputs. As a result, hydrological projections, despite the progressive increase in the accuracy of the models along the chain, still display high levels of uncertainty, especially at small temporal and spatial scales. In this work, we present a framework to quantify and partition the uncertainty of hydrological processes emerging from climate models and internal variability, across a broad range of scales. Using the example of two mountainous catchments in Switzerland, we produced high-resolution ensembles of climate and hydrological data using a two-dimensional weather generator (AWE-GEN- 2d) and a distributed hydrological model (TOPKAPI-ETH). We quantified the uncertainty in hydrological projections towards the end of the century through the estimation of the values of signal-to-noise ratios (STNR). We found small STNR absolute values (