Are we using the right fuel to drive hydrological models? A climate impact study in the Upper Blue Nile

dc.bibliographicCitation.firstPage2163eng
dc.bibliographicCitation.issue4eng
dc.bibliographicCitation.volume22eng
dc.contributor.authorLiersch, S.
dc.contributor.authorTecklenburg, J.
dc.contributor.authorRust, H.
dc.contributor.authorDobler, A.
dc.contributor.authorFischer, M.
dc.contributor.authorKruschke, T.
dc.contributor.authorKoch, H.
dc.contributor.authorHattermann, F.F.
dc.date.accessioned2020-07-27T12:26:32Z
dc.date.available2020-07-27T12:26:32Z
dc.date.issued2018
dc.description.abstractClimate simulations are the fuel to drive hydrological models that are used to assess the impacts of climate change and variability on hydrological parameters, such as river discharges, soil moisture, and evapotranspiration. Unlike with cars, where we know which fuel the engine requires, we never know in advance what unexpected side effects might be caused by the fuel we feed our models with. Sometimes we increase the fuel's octane number (bias correction) to achieve better performance and find out that the model behaves differently but not always as was expected or desired. This study investigates the impacts of projected climate change on the hydrology of the Upper Blue Nile catchment using two model ensembles consisting of five global CMIP5 Earth system models and 10 regional climate models (CORDEX Africa). WATCH forcing data were used to calibrate an eco-hydrological model and to bias-correct both model ensembles using slightly differing approaches. On the one hand it was found that the bias correction methods considerably improved the performance of average rainfall characteristics in the reference period (1970-1999) in most of the cases. This also holds true for non-extreme discharge conditions between Q20 and Q80. On the other hand, bias-corrected simulations tend to overemphasize magnitudes of projected change signals and extremes. A general weakness of both uncorrected and bias-corrected simulations is the rather poor representation of high and low flows and their extremes, which were often deteriorated by bias correction. This inaccuracy is a crucial deficiency for regional impact studies dealing with water management issues and it is therefore important to analyse model performance and characteristics and the effect of bias correction, and eventually to exclude some climate models from the ensemble. However, the multi-model means of all ensembles project increasing average annual discharges in the Upper Blue Nile catchment and a shift in seasonal patterns, with decreasing discharges in June and July and increasing discharges from August to November.eng
dc.description.versionpublishedVersioneng
dc.identifier.urihttps://oa.tib.eu/renate/handle/123456789/5134
dc.identifier.urihttps://doi.org/10.34657/3763
dc.language.isoengeng
dc.publisherGöttingen : Copernicus GmbHeng
dc.relation.doihttps://doi.org/10.5194/hess-22-2163-2018
dc.relation.ispartofseriesHydrology and Earth System Sciences 22 (2018), Nr. 4eng
dc.rights.licenseCC BY 3.0 Unportedeng
dc.rights.urihttps://creativecommons.org/licenses/by/3.0/eng
dc.subjectCatchmentseng
dc.subjectClimate changeeng
dc.subjectDigital storageeng
dc.subjectEarth (planet)eng
dc.subjectFuelseng
dc.subjectRunoffeng
dc.subjectSoil moistureeng
dc.subjectWater managementeng
dc.subjectBias-correction methodseng
dc.subjectClimate simulationeng
dc.subjectEco-hydrological modelseng
dc.subjectExtreme dischargeseng
dc.subjectHydrological modelseng
dc.subjectHydrological parameterseng
dc.subjectRainfall characteristicseng
dc.subjectRegional climate modelseng
dc.subjectClimate modelseng
dc.subject.ddc550eng
dc.titleAre we using the right fuel to drive hydrological models? A climate impact study in the Upper Blue Nileeng
dc.typearticleeng
dc.typeTexteng
dcterms.bibliographicCitation.journalTitleHydrology and Earth System Scienceseng
tib.accessRightsopenAccesseng
wgl.contributorPIKeng
wgl.subjectUmweltwissenschafteneng
wgl.typeZeitschriftenartikeleng
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