Evaluation of Global Water Resources Reanalysis Runoff Products for Local Water Resources Applications: Case Study-Upper Blue Nile Basin of Ethiopia


The increasing availability of global observation datasets, both from in situ and remote sensors, and advancements in earth system models and data assimilation algorithms have generated a number of water resources reanalysis products that are available at global scale and high spatial and temporal resolutions. These products hold great potential for water resources applications, but their levels of uncertainty need to be evaluated at local scale. In this work, we evaluate the runoff product from two multi-model global water resources reanalyses (WRRs), available at 0.5° (WRR1) and 0.25° (WRR2) grid resolutions, which were produced within the framework of a European Union project (eartH2Observe) in the upper Blue Nile basin. Analysis indicates that the recently released WRR2 UniK product exhibits consistently better performance statistics than the earlier coarser-resolution WRR1 and the rest of the WRR2 products at all ranges of temporal and spatial scale evaluated. Streamflow simulations based on gauged rainfall forcing and the locally set hydrological model CREST outperforms all the other products, including UniK. Global hydrological products can be a data source for various water resources planning and management applications in data-scarce areas of Africa. This study cautions against using available global hydrological products without prior uncertainty evaluation.

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  1. Adler RF et al (2003) The Version-2 global precipitation climatology project (GPCP) monthly precipitation analysis (1979–present). J Hydrometeorol 4(6):1147–1167

    Article  Google Scholar 

  2. Alcamo J, Henrichs T, Rösch T (2000) Global modeling and scenario analysis. In: Rijsberman F (ed) World water scenarios – analyses. Earthscan Publications, London

    Google Scholar 

  3. Allen RG, Pereira LS, Raes D, Smith M (1998) Crop evapotranspiration - Guidelines for computing crop water requirements - FAO Irrigation and drainage paper 56, FAO Irrigation and drainage paper 56. Food and Agriculture Organization of the United Nations, Rome. ISBN 92-5-104219-5

  4. Balsamo G, Beljaars A, Scipal K, Viterbo P, van den Hurk B, Hirschi M, Betts AK (2009) A revised hydrology for the ECMWF model: verification from field site to terrestrial water storage and impact in the integrated forecast system. J Hydrometeorol 10(3):623–643

    Article  Google Scholar 

  5. Beck H, van Dijk A, Levizzani V, Schellekens J, Miralles D, Martens B, Roo A (2017a) MSWEP: 3-hourly 0.25° global gridded precipitation (1979–2015) by merging gauge, satellite, and reanalysis data, 589–615 pp

  6. Beck H, van Dijk AIJM, de Roo A, Dutra E, Fink G, Orth R, Schellekens J (2017b) Global evaluation of runoff from 10 state-of-the-art hydrological models. Hydrol Earth Syst Sci 21(6):2881–2903

    Article  Google Scholar 

  7. Burek P, Roo A, van der Knijff J (2013) LISFLOOD - distributed water balance and flood simulation model - revised user manual

  8. Dantec-Nédélec S et al (2017) Testing the capability of ORCHIDEE land surface model to simulate Arctic ecosystems: sensitivity analysis and site-level model calibration. Journal of Advances in Modeling Earth Systems 9(2):1212–1230

    Article  Google Scholar 

  9. Doell P, Alcamo J, Henrichs T, Kaspar F, Lehner B, Rösch T, Siebert S (2001) The global integrated water model WaterGAP 2.1

  10. Donaldson RJ, Dyer RM, Krauss M (1975) An objective evaluator of techniques for predicting severe weather events. Preprints, Ninth Conf. on Severe Local Storms, Amer. Meteor. Soc., Norman, OK, pp 321–326

  11. Doswell C, Davies-Jones R, Keller DL (1990) On summary measures of skill in rare event forecasting based on contingency tables

  12. Duan Q, Sorooshian S, Gupta V (1992) Effective and efficient global optimization for conceptual rainfall-runoff models. Water Resour Res 28

  13. Ducoudré NI, Laval K, Perrier A (1993) SECHIBA, a new set of parameterizations of the hydrologic exchanges at the land-atmosphere Interface within the LMD atmospheric general circulation model. J Clim 6(2):248–273

    Article  Google Scholar 

  14. El-Sadek A, Bleiweiss M, Shukla M, Guldan S, Fernald A (2011) Alternative climate data sources for distributed hydrological modelling on a daily time step. Hydrol Process 25(10):1542–1557

    Article  Google Scholar 

  15. Elshamy ME, Seierstad IA, Sorteberg A (2009) Impacts of climate change on Blue Nile flows using bias-corrected GCM scenarios. Hydrol Earth Syst Sci 13(5):551–565

    Article  Google Scholar 

  16. Haberlandt U, Kite GW (1998) Estimation of daily space–time precipitation series for macroscale hydrological modelling. Hydrol Process 12(9):1419–1432

    Article  Google Scholar 

  17. Hwang S, Graham WD, Adams A, Geurink J (2013) Assessment of the utility of dynamically-downscaled regional reanalysis data to predict streamflow in west Central Florida using an integrated hydrologic model. Reg Environ Chang 13(S1):69–80

    Article  Google Scholar 

  18. Kanamaru H, Kanamitsu M (2007) Fifty-seven-year California reanalysis downscaling at 10 km (CaRD10). Part II: comparison with north American regional reanalysis. J Clim 20(22):5572–5592

    Article  Google Scholar 

  19. Krinner G, Viovy N, de Noblet-Ducoudré N, Ogée J, Polcher J, Friedlingstein P, Ciais P, Sitch S, Prentice IC (2005) A dynamic global vegetation model for studies of the coupled atmosphere-biosphere system. Glob Biogeochem Cycles 19(1)

  20. Lakew HB, Moges SA, Asfaw DH (2017) Hydrological evaluation of satellite and reanalysis precipitation products in the upper Blue Nile Basin: a case study of Gilgel Abbay. Hydrology 4(3):39

    Article  Google Scholar 

  21. Le Moigne P (2009) SURFEX scientific documentation, 211 pp

  22. Nash JE, Sutcliffe JV (1970) River flow forecasting through conceptual models part I — a discussion of principles. J Hydrol 10(3):282–290

    Article  Google Scholar 

  23. Peña-Arancibia J, van Dijk A, Stenson M, Viney NR (2011) Opportunities to evaluate a landscape hydrological model (AWRA-L) using global data sets

  24. Petrescu AMR, van Beek LPH, van Huissteden J, Prigent C, Sachs T, Corradi CAR, Parmentier FJW, Dolman AJ (2010) Modeling regional to global CH4 emissions of boreal and arctic wetlands. Glob Biogeochem Cycles 24(4):GB4009

    Article  Google Scholar 

  25. Schellekens J et al (2017) A global water resources ensemble of hydrological models: the eartH2Observe Tier-1 dataset. Earth Syst Sci Data 9(2):389–413

    Article  Google Scholar 

  26. Shen X, Hong Y (2014) CREST Coupled Routing and Excess STorage CREST user manual v2.1. University of Oklahoma (OU) HyDROS Lab. http://hydro.ou.edu. Accessed 14 Nov 2017

  27. Sutcliffe JV, Parks YP (1999) The hydrology of the Nile, xi + 179 pp. IAHS Press, Wallingford

  28. Taylor KE (2001) Summarizing multiple aspects of model performance in a single diagram. J Geophys Res: Atmos 106(D7):7183–7192

    Article  Google Scholar 

  29. van den Hurk B, Viterbo P (2003) The Torne-Kalix PILPS 2(e) experiment as a test bed for modifications to the ECMWF land surface scheme. Glob Planet Chang 38(1):165–173

    Article  Google Scholar 

  30. van Dijk A, Renzullo L (2011) The role of satellite observation in Australian water resources monitoring, 10–15 pp

  31. Wang J et al (2011) The coupled routing and excess storage (CREST) distributed hydrological model. Hydrol Sci J 56(1):84–98

    Article  Google Scholar 

  32. Weedon GP, Gianpaolo B, Nicolas B, Sandra G, J BM, Pedro V (2014) The WFDEI meteorological forcing data set: WATCH forcing data methodology applied to ERA-interim reanalysis data. Water Resour Res 50(9):7505–7514

    Article  Google Scholar 

  33. Wilk MB, Gnanadesikan R (1968) Probability plotting methods for the analysis for the analysis of data. Biometrika 55(1):1–17

    Google Scholar 

  34. World Bank (2018) http://www.worldbank.org/en/topic/water/overview. In: World Bank edited by W. Bank. Accessed 14 Nov 2017

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This work is supported by the EU-funded eartH2Observe (ENVE.2013.6.3-3) project. The authors would like to thank the Ethiopian Ministry of Water, Irrigation, and Electricity for the updated observed river runoff data. This study is coordinated by Addis Ababa University, School of Civil and Environmental Engineering.

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Correspondence to Haileyesus Belay Lakew.

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Lakew, H.B., Moges, S.A., Anagnostou, E.N. et al. Evaluation of Global Water Resources Reanalysis Runoff Products for Local Water Resources Applications: Case Study-Upper Blue Nile Basin of Ethiopia. Water Resour Manage 34, 2157–2177 (2020). https://doi.org/10.1007/s11269-019-2190-y

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  • Blue Nile
  • eartH2Observe
  • Water resource reanalysis
  • Error characterization