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Climatic Change

, Volume 141, Issue 3, pp 547–560 | Cite as

Adjustment of global precipitation data for enhanced hydrologic modeling of tropical Andean watersheds

  • Michael Strauch
  • Rohini Kumar
  • Stephanie Eisner
  • Mark Mulligan
  • Julia Reinhardt
  • William Santini
  • Tobias Vetter
  • Jan Friesen
Article

Abstract

Global gridded precipitation is an essential driving input for hydrologic models to simulate runoff dynamics in large river basins. However, the data often fail to adequately represent precipitation variability in mountainous regions due to orographic effects and sparse and highly uncertain gauge data. Water balance simulations in tropical montane regions covered by cloud forests are especially challenging because of the additional water input from cloud water interception. The ISI-MIP2 hydrologic model ensemble encountered these problems for Andean sub-basins of the Upper Amazon Basin, where all models significantly underestimated observed runoff. In this paper, we propose simple yet plausible ways to adjust global precipitation data provided by WFDEI, the WATCH Forcing Data methodology applied to ERA-Interim reanalysis, for tropical montane watersheds. The modifications were based on plausible reasoning and freely available tropics-wide data: (i) a high-resolution climatology of the Tropical Rainfall Measuring Mission (TRMM) and (ii) the percentage of tropical montane cloud forest cover. Using the modified precipitation data, runoff predictions significantly improved for all hydrologic models considered. The precipitation adjustment methods presented here have the potential to enhance other global precipitation products for hydrologic model applications in the Upper Amazon Basin as well as in other tropical montane watersheds.

Keywords

Hydrologic Model Tropical Rainfall Measure Mission Cloud Forest TMPA Tropical Montane Cloud Forest 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

We would like to thank Stephan Thober for his mathematical support in developing the TRMM normalization scheme as well as Valentina Krysanova and Fred Hattermann for coordinating the regional water sector within ISI-MIP2.

Supplementary material

10584_2016_1706_MOESM1_ESM.docx (66.1 mb)
ESM 1 (DOCX 67660 kb)

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Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  • Michael Strauch
    • 1
  • Rohini Kumar
    • 2
  • Stephanie Eisner
    • 3
  • Mark Mulligan
    • 4
  • Julia Reinhardt
    • 5
  • William Santini
    • 6
    • 7
  • Tobias Vetter
    • 5
  • Jan Friesen
    • 8
  1. 1.Department of Computational Landscape EcologyUFZ - Helmholtz-Center for Environmental ResearchLeipzigGermany
  2. 2.Department of Computational HydrosystemsUFZ - Helmholtz-Center for Environmental ResearchLeipzigGermany
  3. 3.Center for Environmental Systems ResearchUniversity of KasselKasselGermany
  4. 4.Department of GeographyKing’s College LondonLondonUK
  5. 5.Potsdam Institute for Climate Impact Research – PIKPotsdamGermany
  6. 6.Institut de Recherche pour le Développement – IRDLimaPeru
  7. 7.Géosciences Environnement Toulouse – GETLimaPeru
  8. 8.Department of Catchment HydrologyUFZ - Helmholtz-Center for Environmental ResearchLeipzigGermany

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