Identification and mapping of multi-type flood hotspots using an ensemble technique in the transboundary of Kabul River Basin

The Kabul River Basin (KRB), located in the eastern Hindukush region, is a transboundary basin shared by Afghanistan and Pakistan. This study aims to identify and map hotspots for five major flood types: ephemeral, fluvial, flash, urban, and glacial lake outburst floods (GLOFs) using three models: the Frequency Ratio (FR), Expert Opinion-based Analytical Hierarchy Process (EO-AHP), and Prediction Rate-based Analytical Hierarchy Process (PR-AHP). By analyzing 620 flood locations and 18 flood predictors, we found that 14 %, 20 %, and 15 % of the study area derived from FR, EO-AHP, and PR-AHP models were highly susceptible to multi-type floods, respectively, highlighting susceptible hotspots of different floods in the KRB. This study provides a comprehensive multi-type flood susceptibility map for the KRB. The findings of this study are crucial for effective flood management, as they identify and integrate multi-type floods into a single map. The study helps relevant authorities in prioritizing resource allocation, improving early warning systems, and implementing sustainable land use planning, ultimately improving flood preparedness and building resilience through risk-informed policy-making. • Identify and map multi-type flood hotspots in the Kabul River Basin using three models. • Assess susceptibility to ephemeral, fluvial, flash, urban, and glacial lake outburst floods. • 14 %, 20 %, and 15 % of the study area is susceptible to multi-type floods. • An innovative ensemble prediction rate-based analytical hierarchy process model has been introduced.

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Publication Details

Journal
Journal of Hydrology Regional Studies
Published
2025-05-22
DOI
https://doi.org/10.1016/j.ejrh.2025.102468
Citations
6
Primary Topic
Flood Risk Assessment and Management
Type
article
Field-Weighted Citation Impact
6.63
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article

Identification and mapping of multi-type flood hotspots using an ensemble technique in the transboundary of Kabul River Basin

Muhammad Hussain, Safi Ullah, Meimei Zhang, Peyman Yariyan et al.
6 citations
Journal of Hydrology Regional Studies
Flood Risk Assessment and Management
6.63
article

Identification and mapping of multi-type flood hotspots using an ensemble technique in the transboundary of Kabul River Basin

Muhammad Hussain, Safi Ullah, Meimei Zhang, Peyman Yariyan, Jiahua Zhang, Fang Chen, Zahoor Ahmad, Zahid Ur Rahman
article en
6 citations

Abstract

The Kabul River Basin (KRB), located in the eastern Hindukush region, is a transboundary basin shared by Afghanistan and Pakistan. This study aims to identify and map hotspots for five major flood types: ephemeral, fluvial, flash, urban, and glacial lake outburst floods (GLOFs) using three models: the Frequency Ratio (FR), Expert Opinion-based Analytical Hierarchy Process (EO-AHP), and Prediction Rate-based Analytical Hierarchy Process (PR-AHP). By analyzing 620 flood locations and 18 flood predictors, we found that 14 %, 20 %, and 15 % of the study area derived from FR, EO-AHP, and PR-AHP models were highly susceptible to multi-type floods, respectively, highlighting susceptible hotspots of different floods in the KRB. This study provides a comprehensive multi-type flood susceptibility map for the KRB. The findings of this study are crucial for effective flood management, as they identify and integrate multi-type floods into a single map. The study helps relevant authorities in prioritizing resource allocation, improving early warning systems, and implementing sustainable land use planning, ultimately improving flood preparedness and building resilience through risk-informed policy-making. • Identify and map multi-type flood hotspots in the Kabul River Basin using three models. • Assess susceptibility to ephemeral, fluvial, flash, urban, and glacial lake outburst floods. • 14 %, 20 %, and 15 % of the study area is susceptible to multi-type floods. • An innovative ensemble prediction rate-based analytical hierarchy process model has been introduced.

Journal of Hydrology Regional StudiesVol. 60
Qingdao University (CN), Northeast Normal University (CN), Chinese Academy of Sciences (CN), University of Tabriz (IR), Beijing Institute of Big Data Research (CN), Aerospace Information Research Institute (CN), University of Chinese Academy of Sciences (CN), King Abdullah University of Science and Technology (SA)
Climate action
Openalex Percentile: Top 3%
Flood Risk Assessment and Management
6.63
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