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Evaluation of the real-time TRMM-based multi-satellite precipitation analysis for an operational flood prediction system in Nzoia Basin, Lake Victoria, Africa

Author

Listed:
  • Li Li
  • Yang Hong
  • Jiahu Wang
  • Robert Adler
  • Frederick Policelli
  • Shahid Habib
  • Daniel Irwn
  • Tesfaye Korme
  • Lawrence Okello

Abstract

Many researchers seek to take advantage of the recently available and virtually uninterrupted supply of satellite-based rainfall information as an alternative and supplement to the ground-based observations in order to implement a cost-effective flood prediction in many under-gauged regions around the world. Recently, NASA Applied Science Program has partnered with USAID and African-RCMRD to implement an operational water-hazard warning system, SERVIR-Africa. The ultimate goal of the project is to build up disaster management capacity in East Africa by providing local governmental officials and international aid organizations a practical decision-support tool in order to better assess emerging flood impacts and to quantify spatial extent of flood risk, as well as to respond to such flood emergencies more expediently. The objective of this article is to evaluate the applicability of integrating NASA’s standard satellite precipitation product with a flood prediction model for disaster management in Nzoia, sub-basin of Lake Victoria, Africa. This research first evaluated the TMPA real-time rainfall data against gauged rainfall data from the year 2002 through 2006. Then, the gridded Xinanjiang Model was calibrated to Nzoia basin for period of 1985–2006. Benchmark streamflow simulations were produced with the calibrated hydrological model using the rain gauge and observed streamflow data. Afterward, continuous discharge predictions forced by TMPA 3B42RT real-time data from 2002 through 2006 were simulated, and acceptable results were obtained in comparison with the benchmark performance according to the designated statistic indices such as bias ratio (20%) and NSCE (0.67). Moreover, it is identified that the flood prediction results were improved with systematically bias-corrected TMPA rainfall data with less bias (3.6%) and higher NSCE (0.71). Although the results justify to suggest to us that TMPA real-time data can be acceptably used to drive hydrological models for flood prediction purpose in Nzoia basin, continuous progress in space-borne rainfall estimation technology toward higher accuracy and higher spatial resolution is highly appreciated. Finally, it is also highly recommended that to increase flood forecasting lead time, more reliable and more accurate short- or medium-range quantitative precipitation forecasts is a must. Copyright Springer Science+Business Media B.V. 2009

Suggested Citation

  • Li Li & Yang Hong & Jiahu Wang & Robert Adler & Frederick Policelli & Shahid Habib & Daniel Irwn & Tesfaye Korme & Lawrence Okello, 2009. "Evaluation of the real-time TRMM-based multi-satellite precipitation analysis for an operational flood prediction system in Nzoia Basin, Lake Victoria, Africa," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 50(1), pages 109-123, July.
  • Handle: RePEc:spr:nathaz:v:50:y:2009:i:1:p:109-123
    DOI: 10.1007/s11069-008-9324-5
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    Citations

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    Cited by:

    1. Saeed Golian & Saber Moazami & Pierre-Emmanuel Kirstetter & Yang Hong, 2015. "Evaluating the Performance of Merged Multi-Satellite Precipitation Products Over a Complex Terrain," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(13), pages 4885-4901, October.
    2. T. P. Singh & Vidya Kumbhar & Sandipan Das & Mangesh M. Deshpande & Komal Dhoka, 2020. "Comparison of TRMM multi-satellite precipitation analysis (TMPA) estimation with ground-based precipitation data over Maharashtra, India," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(6), pages 5539-5552, August.
    3. A. Awadallah & D. Tabet, 2015. "Estimating flooding extent at high return period for ungauged braided systems using remote sensing: a case study of Cuvelai Basin, Angola," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 77(1), pages 255-272, May.

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