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https://doi.org/10.5194/hess-2016-473
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-2016-473
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
27 Sep 2016
Status: this discussion paper is a preprint. It 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
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.
How to cite. 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. [preprint], https://doi.org/10.5194/hess-2016-473, 2016.
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AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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RC1: 'Bias correction by Valdés-Pineda at al.', Anonymous Referee #1, 20 Nov 2016
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AC1: 'Bias correction of daily satellite-based rainfall estimates for hydrologic forecasting in the Upper Zambezi', Rodrigo Valdés-Pineda, 09 Jan 2017
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AC1: 'Bias correction of daily satellite-based rainfall estimates for hydrologic forecasting in the Upper Zambezi', Rodrigo Valdés-Pineda, 09 Jan 2017
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RC2: 'Review on “Bias correction of daily satellite-based rainfall estimates for hydrologic forecasting in the Upper Zambezi, Africa” by Valdés-Pineda et al.', Anonymous Referee #2, 11 Dec 2016
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AC2: 'Bias correction of daily satellite-based rainfall estimates for hydrologic forecasting in the Upper Zambezi, Africa', Rodrigo Valdés-Pineda, 09 Jan 2017
-
AC2: 'Bias correction of daily satellite-based rainfall estimates for hydrologic forecasting in the Upper Zambezi, Africa', Rodrigo Valdés-Pineda, 09 Jan 2017
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
- Printer-friendly version
- Supplement
-
RC1: 'Bias correction by Valdés-Pineda at al.', Anonymous Referee #1, 20 Nov 2016
-
AC1: 'Bias correction of daily satellite-based rainfall estimates for hydrologic forecasting in the Upper Zambezi', Rodrigo Valdés-Pineda, 09 Jan 2017
-
AC1: 'Bias correction of daily satellite-based rainfall estimates for hydrologic forecasting in the Upper Zambezi', Rodrigo Valdés-Pineda, 09 Jan 2017
-
RC2: 'Review on “Bias correction of daily satellite-based rainfall estimates for hydrologic forecasting in the Upper Zambezi, Africa” by Valdés-Pineda et al.', Anonymous Referee #2, 11 Dec 2016
-
AC2: 'Bias correction of daily satellite-based rainfall estimates for hydrologic forecasting in the Upper Zambezi, Africa', Rodrigo Valdés-Pineda, 09 Jan 2017
-
AC2: 'Bias correction of daily satellite-based rainfall estimates for hydrologic forecasting in the Upper Zambezi, Africa', Rodrigo Valdés-Pineda, 09 Jan 2017
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Cited
23 citations as recorded by crossref.
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- Evaluating the Benefits of Merging Near-Real-Time Satellite Precipitation Products: A Case Study in the Kinu Basin Region, Japan N. Mastrantonas et al. 10.1175/JHM-D-18-0190.1
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- Performance evaluation of CMORPH satellite precipitation product in the Zambezi Basin W. Gumindoga et al. 10.1080/01431161.2019.1602791
- Improving CHIRPS Daily Satellite-Precipitation Products Using Coarser Ground Observations W. Li et al. 10.1109/LGRS.2019.2907532
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- Application of Satellite Rainfall Products for Flood Inundation Modelling in Kelantan River Basin, Malaysia . Tam et al. 10.3390/hydrology6040095
- The Temporal Variability of Rainfall and Streamflow into Lake Nakuru, Kenya, Assessed Using SWAT and Hydrometeorological Indices A. Kimaru et al. 10.3390/hydrology6040088
- Performance of bias-correction schemes for CMORPH rainfall estimates in the Zambezi River basin W. Gumindoga et al. 10.5194/hess-23-2915-2019
- Assessment of GPM Satellite Precipitation Performance after Bias Correction, for Hydrological Modeling in a Semi-Arid Watershed (High Atlas Mountain, Morocco) M. Benkirane et al. 10.3390/atmos14050794
- Hydrologic evaluation of bias corrected CMORPH rainfall estimates at the headwater catchment of the Zambezi River W. Gumindoga et al. 10.1016/j.pce.2019.11.004
- Hydrological Evaluation of PERSIANN-CDR Rainfall over Upper Senegal River and Bani River Basins K. Bâ et al. 10.3390/rs10121884
- Improving Operational Short- to Medium-Range (SR2MR) Streamflow Forecasts in the Upper Zambezi Basin and Its Sub-Basins Using Variational Ensemble Forecasting R. Valdés-Pineda et al. 10.3390/hydrology8040188
- Application of Random Forest Algorithm for Merging Multiple Satellite Precipitation Products across South Korea G. Nguyen et al. 10.3390/rs13204033
- Which rainfall score is more informative about the performance in river discharge simulation? A comprehensive assessment on 1318 basins over Europe S. Camici et al. 10.5194/hess-24-4869-2020
- Bias correction method of high-resolution satellite-based precipitation product for Peninsular Malaysia Z. Iqbal et al. 10.1007/s00704-022-04007-6
- Product- and Hydro-Validation of Satellite-Based Precipitation Data Sets for a Poorly Gauged Snow-Fed Basin in Turkey G. Uysal 10.3390/w14172758
- Evaluating the necessity of post-processing techniques on d4PDF data for extreme climate assessment L. Maneechot et al. 10.1007/s11356-023-29572-9
- Long-term trends in rainfall and temperature using high-resolution climate datasets in East Africa S. Gebrechorkos et al. 10.1038/s41598-019-47933-8
Latest update: 18 Apr 2024
Rodrigo Valdés-Pineda
Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, 85721, Arizona, USA
Eleonora M. C. Demaría
Southwest Watershed Research Center, USDA-ARS, Tucson, 85719, Arizona, USA
Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, 85721, Arizona, USA
Juan B. Valdés
Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, 85721, Arizona, USA
Sungwook Wi
Department of Civil and Environmental Engineering, University of Massachusetts, Amherst, 01003, Massachusetts, USA
Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, 85721, Arizona, USA
Aleix Serrat-Capdevilla
Global Water Practice, The World Bank, Washington, 20433, Washington DC, USA
Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, 85721, Arizona, USA
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...