4.7 Article

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

Journal

WATER RESOURCES MANAGEMENT
Volume 34, Issue 7, Pages 2157-2177

Publisher

SPRINGER
DOI: 10.1007/s11269-019-2190-y

Keywords

Blue Nile; eartH2Observe; Water resource reanalysis; Error characterization

Ask authors/readers for more resources

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 degrees (WRR1) and 0.25 degrees (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.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available