Abstract
The Nyabarongo basin in Rwanda is subjected to hydrometeorological hazards, particularly floods, which are the most prevailing and devastating. Therefore, understanding flood-controlling factors is so pertinent for the development of scientifically driven flood prevention strategies. This study aimed at exploring a form of pixel-based information value model integrated with remote sensing techniques and geo-information system to assess the probability of flood incidence and geo-visualize prone areas at basin’s scale. To do this, a flood inventory was initially generated using 226 past flooded locations, which were split into a 75:25 ratio for model training and validation, respectively. Fourteen flood-controlling factors were selected after a multicollinearity diagnosis. The results unveiled that more than half of the basin’s surface area is covered by very high (8.6%) and high (21.5%) to medium (31.8%) probability of flood incidence. This dispersion was mainly influenced by rainfall, proximity to rivers, Land Use/Land Cover, elevation, and SPI which influence the basin’s hydrological behavior. The evaluated accuracy of the applied model using the Area Under Curve of the Receiver Operating Characteristics (AUC–ROC) highlighted a commendable and accurate performance of 0.883 and 0.828 for success and prediction rate, respectively. The study’s findings provide a scientifically driven reference for flood mitigation plans and act as a benchmark for decision-making and policy updates regarding flood risk management toward the Nyabarongo basin and other basins with similar characteristics nationally or regionally.
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Availability of data and materials
The data and materials that support the findings of this study will be made available by the corresponding author (Dr. Lanhai Li) upon reasonable request.
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Acknowledgements
The authors express ample gratitude addressed to the Alliance of International Science Organization (ANSO) under the Chinese Academy of Sciences (CAS), for the doctoral scholarship award. The Xinjiang Institute of Ecology and Geography (XIEG), the University of Lay Adventists of Kigali (UNILAK) and the University of Rwanda (UR-Huye) are also acknowledged for providing a peaceful and conducive environment for conducting my research. In addition, I appreciate the opportunity to utilize their advanced laboratory facilities, which have greatly contributed to the success of this research project.
Funding
The study was funded and supported by the key program for international cooperation of the Bureau of International Cooperation, Chinese Academy of Sciences (Grant Number:151542KYSB20200018), and the Sino-Africa Joint Research Center of Chinese Academy of Sciences (Grant Number: SAJC202107).
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Conceptualization: RM and LL. Data curation: RM and PMK. Formal analysis: RM and PMK. Funding acquisition: LL. Investigation: LL, MM, CM, and JH. Methodology: RM and PMK. Software: PMK and RM. Supervision: LL. Validation: RM. Visualization: PMK, MM, CM, and JH. Roles/writing—original draft: RM. Writing—review and editing: LL, MM, and CM.
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Mind’je, R., Li, L., Kayumba, P.M. et al. Exploring a form of pixel-based information value model for flood probability assessment and geo-visualization over an East African basin: a case of Nyabarongo in Rwanda. Environ Earth Sci 82, 402 (2023). https://doi.org/10.1007/s12665-023-11088-7
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DOI: https://doi.org/10.1007/s12665-023-11088-7