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Remote Sens. 2016, 8(8), 676; doi:10.3390/rs8080676

Thermal Imagery-Derived Surface Inundation Modeling to Assess Flood Risk in a Flood-Pulsed Savannah Watershed in Botswana and Namibia

1
Department of Earth and Ocean Sciences, University of North Carolina Wilmington, 601 S College Rd., Wilmington, NC 28403, USA
2
Department of Mathematics and Statistics, University of North Carolina Wilmington, 601 S College Rd., Wilmington, NC 28403, USA
1
School Teacher, Etomba, Namibia
1
MET, KAZA, Windhoek, Namibia
1
The Department of Water Affairs, Kasane, Botswana
*
Authors to whom correspondence should be addressed.
Academic Editors: Yuei-An Liou, Chyi-Tyi Lee, Yuriy Kuleshov, Jean-Pierre Barriot, Chung-Ru Ho, Magaly Koch and Prasad S. Thenkabail
Received: 22 April 2016 / Revised: 4 August 2016 / Accepted: 15 August 2016 / Published: 20 August 2016
(This article belongs to the Special Issue Earth Observations for a Better Future Earth)
View Full-Text   |   Download PDF [6996 KB, uploaded 20 August 2016]   |  

Abstract

The Chobe River Basin (CRB), a sub-basin of the Upper Zambezi Basin shared by Namibia and Botswana, is a complex hydrologic system that lies at the center of the world’s largest transfrontier conservation area. Despite its regional importance for livelihoods and biodiversity, its hydrology, controlled by the timing and relative contributions of water from two regional rivers, remains poorly understood. An increase in the magnitude of flooding in this region since 2009 has resulted in significant displacements of rural communities. We use an innovative approach that employs time-series of thermal imagery and station discharge data to model seasonal flooding patterns, identify the driving forces that control the magnitude of flooding and the high population density areas that are most at risk of high magnitude floods throughout the watershed. Spatio-temporal changes in surface inundation determined using NASA Moderate-resolution Imaging Spectroradiometer (MODIS) thermal imagery (2000–2015) revealed that flooding extent in the CRB is extremely variable, ranging from 401 km2 to 5779 km2 over the last 15 years. A multiple regression model of lagged discharge of surface contributor basins and flooding extent in the CRB indicated that the best predictor of flooding in this region is the discharge of the Zambezi River 64 days prior to flooding. The seasonal floods have increased drastically in magnitude since 2008 causing large populations to be displaced. Over 46,000 people (53% of Zambezi Region population) are living in high magnitude flood risk areas, making the need for resettlement planning and mitigation strategies increasingly important. View Full-Text
Keywords: inundation modeling; MODIS thermal imagery; flood-pulsed savanna; Africa inundation modeling; MODIS thermal imagery; flood-pulsed savanna; Africa
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Burke, J.J.; Pricope, N.G.; Blum, J. Thermal Imagery-Derived Surface Inundation Modeling to Assess Flood Risk in a Flood-Pulsed Savannah Watershed in Botswana and Namibia. Remote Sens. 2016, 8, 676.

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