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The emerging role of satellite rainfall data in improving the hydro-political situation of flood monitoring in the under-developed regions of the world

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  • Faisal Hossain
  • Nitin Katiyar
  • Yang Hong
  • Aaron Wolf

Abstract

The systematic decline of in situ networks for hydrologic measurements has been recognized as a crucial limitation to advancing hydrologic monitoring in medium to large basins, especially those that are already sparsely instrumented. As a collective response, sections of the hydrologic community have recently forged partnerships for the development of space-borne missions for cost-effective, yet global, hydrologic measurements by building upon the technological advancements since the last two decades. In this article, we review the state-of-the-art on flood monitoring in medium and large ungauged basins where satellite remote sensing can facilitate development of a cost-effective mechanism. We present our review in the context of the current hydro-political situation of flood monitoring in flood-prone developing nations situated in international river basins (IRBs). Given the large number of such basins and the difficulty in acquisition of multi-faceted geophysical data, we argue that the conventional data-intensive implementation of physically based hydrologic models that are complex and distributed is time-consuming for global assessment of the utility of proposed global satellite hydrologic missions. A more parsimonious approach is justified at the tolerable expense of accuracy before such missions begin operation. Such a parsimonious approach can subsequently motivate the identified international basins to invest greater effort in conventional and detailed hydrologic studies to design a prototype flood forecasting system in an effort to overcome the hydro-political hurdles to flood monitoring. Through a modeling exercise involving an open-book watershed concept, we demonstrate the value of a parsimonious approach in understanding the utility of NASA-derived satellite rainfall products. It is critical now that real-world operational flood forecasting agencies in the under-developed world come forward to collaborate with the research community in order to leverage satellite rainfall data for greater societal benefit for inhabitants in IRBs. Copyright Springer Science+Business Media, Inc. 2007

Suggested Citation

  • Faisal Hossain & Nitin Katiyar & Yang Hong & Aaron Wolf, 2007. "The emerging role of satellite rainfall data in improving the hydro-political situation of flood monitoring in the under-developed regions of the world," 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. 43(2), pages 199-210, November.
  • Handle: RePEc:spr:nathaz:v:43:y:2007:i:2:p:199-210
    DOI: 10.1007/s11069-006-9094-x
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    References listed on IDEAS

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    1. Faisal Hossain, 2006. "Towards Formulation of a Space-borne System for Early Warning of Floods: Can Cost-Effectiveness Outweigh Prediction Uncertainty?," 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. 37(3), pages 263-276, March.
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    Cited by:

    1. Woo Han & Steven Burian & J. Shepherd, 2011. "Assessment of satellite-based rainfall estimates in urban areas in different geographic and climatic regions," 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. 56(3), pages 733-747, March.
    2. Md Abul Ehsan Bhuiyan & Feifei Yang & Nishan Kumar Biswas & Saiful Haque Rahat & Tahneen Jahan Neelam, 2020. "Machine Learning-Based Error Modeling to Improve GPM IMERG Precipitation Product over the Brahmaputra River Basin," Forecasting, MDPI, vol. 2(3), pages 1-19, July.
    3. Mahmood, Asif & Hossain, Faisal, 2017. "Feasibility of managed domestic rainwater harvesting in South Asian rural areas using remote sensing," Resources, Conservation & Recycling, Elsevier, vol. 125(C), pages 157-168.

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