Flood susceptibility prediction using MaxEnt and frequency ratio modeling for Kokcha River in Afghanistan
Qasimi, Abdul Baser ; Isazade, Vahid and Berndtsson, Ronny LU
(2023)
In Natural Hazards
- Abstract
Flooding is a natural but unavoidable disaster that occurs over time. Flooding threatens human life, property, and resources and affects regional and national economies. Through frequency ratio and MaxEnt modeling, flood sensitivity was determined in the Amu Darya River Basin in Badakhshan Province, Afghanistan. Slope, plan curvature, distance to river, rainfall, aspect, land use, elevation, Normalized Difference Vegetation Index (NDVI), soil type, lithology, Topographic Humidity Index (TWI), and drainage density were used to quantify flood susceptibility. In total, 88 flood points collected from Google Earth were used to train the frequency ratio model to predict flood susceptibility, and 34 GPS-recorded points of the flooded area were... (More)
Flooding is a natural but unavoidable disaster that occurs over time. Flooding threatens human life, property, and resources and affects regional and national economies. Through frequency ratio and MaxEnt modeling, flood sensitivity was determined in the Amu Darya River Basin in Badakhshan Province, Afghanistan. Slope, plan curvature, distance to river, rainfall, aspect, land use, elevation, Normalized Difference Vegetation Index (NDVI), soil type, lithology, Topographic Humidity Index (TWI), and drainage density were used to quantify flood susceptibility. In total, 88 flood points collected from Google Earth were used to train the frequency ratio model to predict flood susceptibility, and 34 GPS-recorded points of the flooded area were used to evaluate the model’s performance. The frequency ratio model displayed a success rate of above 86%. However, using a jackknife entropy test, the MaxEnt model yielded a 97% success rate. The results showed that rainfall, land use, distance to river, and soil type were the most important parameters for evaluating flood sensitivity. The developed models can help planners and decision-makers perform flood susceptibility mapping in the region by determining locations of flooding sensitivity.
(Less)
- author
- Qasimi, Abdul Baser
; Isazade, Vahid
and Berndtsson, Ronny
LU
- organization
- publishing date
- 2023
- type
- Contribution to journal
- publication status
- epub
- subject
- keywords
- Afghanistan, Flood, Frequency ratio, Jackknife test, Kokcha River, MaxEnt model
- in
- Natural Hazards
- pages
- 28 pages
- publisher
- Springer
- external identifiers
-
- scopus:85174849633
- ISSN
- 0921-030X
- DOI
- 10.1007/s11069-023-06232-2
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © 2023, The Author(s), under exclusive licence to Springer Nature B.V.
- id
- bc6c57e8-5952-4764-8bbd-b4a6555044fb
- date added to LUP
- 2023-11-06 09:18:00
- date last changed
- 2023-12-18 14:41:06
@article{bc6c57e8-5952-4764-8bbd-b4a6555044fb,
abstract = {{<p>Flooding is a natural but unavoidable disaster that occurs over time. Flooding threatens human life, property, and resources and affects regional and national economies. Through frequency ratio and MaxEnt modeling, flood sensitivity was determined in the Amu Darya River Basin in Badakhshan Province, Afghanistan. Slope, plan curvature, distance to river, rainfall, aspect, land use, elevation, Normalized Difference Vegetation Index (NDVI), soil type, lithology, Topographic Humidity Index (TWI), and drainage density were used to quantify flood susceptibility. In total, 88 flood points collected from Google Earth were used to train the frequency ratio model to predict flood susceptibility, and 34 GPS-recorded points of the flooded area were used to evaluate the model’s performance. The frequency ratio model displayed a success rate of above 86%. However, using a jackknife entropy test, the MaxEnt model yielded a 97% success rate. The results showed that rainfall, land use, distance to river, and soil type were the most important parameters for evaluating flood sensitivity. The developed models can help planners and decision-makers perform flood susceptibility mapping in the region by determining locations of flooding sensitivity.</p>}},
author = {{Qasimi, Abdul Baser and Isazade, Vahid and Berndtsson, Ronny}},
issn = {{0921-030X}},
keywords = {{Afghanistan; Flood; Frequency ratio; Jackknife test; Kokcha River; MaxEnt model}},
language = {{eng}},
publisher = {{Springer}},
series = {{Natural Hazards}},
title = {{Flood susceptibility prediction using MaxEnt and frequency ratio modeling for Kokcha River in Afghanistan}},
url = {{http://dx.doi.org/10.1007/s11069-023-06232-2}},
doi = {{10.1007/s11069-023-06232-2}},
year = {{2023}},
}