Journal cover Journal topic
Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
doi:10.5194/hess-2016-473
© Author(s) 2016. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
27 Sep 2016
Review status
This discussion paper has been under review for the journal Hydrology and Earth System Sciences (HESS). The manuscript was not accepted for further review after discussion.
Bias correction of daily satellite-based rainfall estimates for hydrologic forecasting in the Upper Zambezi, Africa
Rodrigo Valdés-Pineda1, Eleonora M. C. Demaría2,1, Juan B. Valdés1, Sungwook Wi3,1, and Aleix Serrat-Capdevilla4,1 1Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, 85721, Arizona, USA
2Southwest Watershed Research Center, USDA-ARS, Tucson, 85719, Arizona, USA
3Department of Civil and Environmental Engineering, University of Massachusetts, Amherst, 01003, Massachusetts, USA
4Global Water Practice, The World Bank, Washington, 20433, Washington DC, USA
Abstract. The Zambezi Basin is located in the semi-arid region of southern Africa and is one of the largest basins in Africa. The Upper Zambezi River Basin (UZRB) is sparsely gauged (only 11 rain gauges are currently accessible), and real-time rainfall estimates are not readily available. However, Satellite Precipitation Products (SPPs) may complement that information, thereby allowing for improved real-time forecasting of streamflows. In this study, three SPPs for the UZRB are bias-corrected and evaluated for use in real-time forecasting of daily streamflows: (1) CMORPH (Climate Prediction Center’s morphing technique), (2) PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks), and (3) TRMM-3B42RT (Tropical Rainfall Measuring Mission). Two approaches for bias correction (Quantile Mapping and a Principal Component-based technique) are used to perform Bias Correction (BC) for the daily SPPs; for reference data, the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) was used. The two BC approaches were evaluated for the period 2001–2016. The bias-corrected SPPs were then used for real-time forecasting of streamflows at Katima Mulilo in the UZRB. Both BC approaches significantly improve the accuracy of the streamflow forecasts in the UZRB.

Citation: Valdés-Pineda, R., Demaría, E. M. C., Valdés, J. B., Wi, S., and Serrat-Capdevilla, A.: Bias correction of daily satellite-based rainfall estimates for hydrologic forecasting in the Upper Zambezi, Africa, Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2016-473, 2016.
Rodrigo Valdés-Pineda et al.
Rodrigo Valdés-Pineda et al.

Viewed

Total article views: 358 (including HTML, PDF, and XML)

HTML PDF XML Total BibTeX EndNote
295 61 2 358 3 3

Views and downloads (calculated since 27 Sep 2016)

Cumulative views and downloads (calculated since 27 Sep 2016)

Viewed (geographical distribution)

Total article views: 358 (including HTML, PDF, and XML)

Thereof 355 with geography defined and 3 with unknown origin.

Country # Views %
  • 1

Saved

Discussed

Latest update: 23 Mar 2017
Publications Copernicus
Download
Short summary
The Upper Zambezi River Basin (UZRB) is sparsely gauged and real-time rainfall estimates are not readily available. Satellite Precipitation Products (SPPs) may complement that information, thereby allowing for improved real-time forecasting of streamflows. In this study, three SPPs for the UZRB are corrected and evaluated for use in real-time forecasting of daily streamflows. The applied approaches revealed significant improvements in the accuracy of the streamflow forecasts in the UZRB.
The Upper Zambezi River Basin (UZRB) is sparsely gauged and real-time rainfall estimates are not...
Share