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1000 Titel
  • The critical role of the routing scheme in simulating peak river discharge in global hydrological models
1000 Autor/in
  1. Zhao, Fang |
  2. Veldkamp, Ted I. E. |
  3. Frieler, Katja |
  4. Schewe, Jacob |
  5. Ostberg, Sebastian |
  6. Willner, Sven |
  7. Schauberger, Bernhard |
  8. Gosling, Simon N. |
  9. Müller Schmied, Hannes |
  10. Portmann, Felix T. |
  11. Leng, Guoyong |
  12. Huang, Maoyi |
  13. Liu, Xingcai |
  14. Tang, Qiuhong |
  15. Hanasaki, Naota |
  16. Biemans, Hester |
  17. Gerten, Dieter |
  18. Satoh, Yusuke |
  19. Pokhrel, Yadu |
  20. Stacke, Tobias |
  21. Ciais, Philippe |
  22. Chang, Jinfeng |
  23. Ducharne, Agnes |
  24. Guimberteau, Matthieu |
  25. Wada, Yoshihide |
  26. Kim, Hyungjun |
  27. Yamazaki, Dai |
1000 Erscheinungsjahr 2017
1000 LeibnizOpen
1000 Art der Datei
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2017-06-28
1000 Erschienen in
1000 Quellenangabe
  • 12(7):075003
1000 FRL-Sammlung
1000 Copyrightjahr
  • 2017
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1088/1748-9326/aa7250 |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • Global hydrological models (GHMs) have been applied to assess global flood hazards, but their capacity to capture the timing and amplitude of peak river discharge—which is crucial in flood simulations—has traditionally not been the focus of examination. Here we evaluate to what degree the choice of river routing scheme affects simulations of peak discharge and may help to provide better agreement with observations. To this end we use runoff and discharge simulations of nine GHMs forced by observational climate data (1971–2010) within the ISIMIP2a project. The runoff simulations were used as input for the global river routing model CaMa-Flood. The simulated daily discharge was compared to the discharge generated by each GHM using its native river routing scheme. For each GHM both versions of simulated discharge were compared to monthly and daily discharge observations from 1701 GRDC stations as a benchmark. CaMa-Flood routing shows a general reduction of peak river discharge and a delay of about two to three weeks in its occurrence, likely induced by the buffering capacity of floodplain reservoirs. For a majority of river basins, discharge produced by CaMa-Flood resulted in a better agreement with observations. In particular, maximum daily discharge was adjusted, with a multi-model averaged reduction in bias over about 2/3 of the analysed basin area. The increase in agreement was obtained in both managed and near-natural basins. Overall, this study demonstrates the importance of routing scheme choice in peak discharge simulation, where CaMa-Flood routing accounts for floodplain storage and backwater effects that are not represented in most GHMs. Our study provides important hints that an explicit parameterisation of these processes may be essential in future impact studies.
1000 Fachgruppe
  1. Umweltwissenschaften |
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://frl.publisso.de/adhoc/creator/WmhhbywgRmFuZw==|https://frl.publisso.de/adhoc/creator/VmVsZGthbXAsIFRlZCBJLiBFLg==|https://frl.publisso.de/adhoc/creator/RnJpZWxlciwgS2F0amE=|https://frl.publisso.de/adhoc/creator/U2NoZXdlLCBKYWNvYg==|https://frl.publisso.de/adhoc/creator/T3N0YmVyZywgU2ViYXN0aWFu|https://frl.publisso.de/adhoc/creator/V2lsbG5lciwgU3Zlbg==|https://frl.publisso.de/adhoc/creator/U2NoYXViZXJnZXIsIEJlcm5oYXJk|https://frl.publisso.de/adhoc/creator/R29zbGluZywgU2ltb24gTi4=|http://orcid.org/0000-0001-5330-9923|https://frl.publisso.de/adhoc/creator/UG9ydG1hbm4sIEZlbGl4IFQu|https://frl.publisso.de/adhoc/creator/TGVuZywgR3VveW9uZw==|https://frl.publisso.de/adhoc/creator/SHVhbmcsIE1hb3lp|https://frl.publisso.de/adhoc/creator/TGl1LCBYaW5nY2Fp|https://frl.publisso.de/adhoc/creator/VGFuZywgUWl1aG9uZw==|https://frl.publisso.de/adhoc/creator/SGFuYXNha2ksIE5hb3Rh|https://frl.publisso.de/adhoc/creator/QmllbWFucywgSGVzdGVy|https://frl.publisso.de/adhoc/creator/R2VydGVuLCBEaWV0ZXI=|https://frl.publisso.de/adhoc/creator/U2F0b2gsIFl1c3VrZQ==|https://frl.publisso.de/adhoc/creator/UG9raHJlbCwgWWFkdQ==|https://frl.publisso.de/adhoc/creator/U3RhY2tlLCBUb2JpYXM=|https://frl.publisso.de/adhoc/creator/Q2lhaXMsIFBoaWxpcHBl|https://frl.publisso.de/adhoc/creator/Q2hhbmcsIEppbmZlbmc=|https://frl.publisso.de/adhoc/creator/RHVjaGFybmUsIEFnbmVz|https://frl.publisso.de/adhoc/creator/R3VpbWJlcnRlYXUsIE1hdHRoaWV1|https://frl.publisso.de/adhoc/creator/V2FkYSwgWW9zaGloaWRl|https://frl.publisso.de/adhoc/creator/S2ltLCBIeXVuZ2p1bg==|https://frl.publisso.de/adhoc/creator/WWFtYXpha2ksIERhaQ==
1000 Förderer
  1. Leibniz Gemeinschaft
  2. European Commission
  3. German Federal Ministry of Education and Research (BMBF)
  4. Biological and Environmental Research Division of Office of Science, US Department of Energy (DOE)
  5. Battelle Memorial Institute
  6. European Research Council
1000 Fördernummer
  1. -
  2. FP7–603864-2
  3. 01LS1201A1; 01LS1201A2
  4. -
  5. DE-AC05-76RL01830
  6. -
1000 Förderprogramm
  1. Leibniz Competition (SAW-2013 P IK-5); Open Access Fund
  2. EU FP7 project HELIX
  3. -
  4. Integrated Assessment Research program through the Integrated Multi-sector, Multi-scale Modeling (IM3) Scientific Focus Area (SFA)
  5. -
  6. Synergy grant ERC-2013-SyG 610028-IMBALANCE-P
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1000 Objektart article
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1000 Erstellt am 2018-06-18T12:35:48.993+0200
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