TY - JOUR

T1 - Assessing risk-prone areas in the Kratovska Reka catchment (North Macedonia) by integrating advanced geospatial analytics and flash flood potential index

AU - Aleksov, Bojana

AU - Milevski, Ivica

AU - Mijalov, Risto

AU - Slobodan, Marković

AU - Cvetković, Vladimir

AU - Lukić, Tin

N1 - Publisher Copyright: © 2024 the author(s), published by De Gruyter.

PY - 2024/8/30

Y1 - 2024/8/30

N2 - This study presents a comprehensive analysis of flash flood susceptibility in the Kratovska Reka catchment area of Northeastern North Macedonia, integrating Geographic Information System, remote sensing, and field survey data. Key factors influencing flash flood dynamics, including Slope, Lithology, Land use, and Vegetation index, were investigated to develop the Flash Flood Potential Index (FFPI). Mapping slope variation using a 5-m Digital Elevation Model (DEM) revealed higher slopes in eastern tributaries compared to western counterparts. Lithological units were classified based on susceptibility to erosion processes, with clastic sediments identified as most prone to flash floods. Land use analysis highlighted non-irrigated agricultural surfaces and areas with sparse vegetation as highly susceptible. Integration of these factors into the FFPI model provided insights into flash flood susceptibility, with results indicating a medium risk across the catchment. The average value of the FFPI is 1.9, considering that the values range from 1 to 5. Also, terrains susceptible to flash floods were found to be 49.34%, classified as medium risk. Field survey data validated the model, revealing a significant overlap between hotspot areas for flash floods and high-risk regions identified by the FFPI. An average FFPI coefficient was calculated for each tributary (sub-catchment) of the Kratovska Reka. According to the model, Latišnica had the highest average coefficient of susceptibility to potential flash floods, with a value of 2.16. These findings offer valuable insights for spatial planning and flood risk management, with implications for both local and national-scale applications. Future research directions include incorporating machine learning techniques to enhance modeling accuracy and reduce subjectivity in assigning weighting factors.

AB - This study presents a comprehensive analysis of flash flood susceptibility in the Kratovska Reka catchment area of Northeastern North Macedonia, integrating Geographic Information System, remote sensing, and field survey data. Key factors influencing flash flood dynamics, including Slope, Lithology, Land use, and Vegetation index, were investigated to develop the Flash Flood Potential Index (FFPI). Mapping slope variation using a 5-m Digital Elevation Model (DEM) revealed higher slopes in eastern tributaries compared to western counterparts. Lithological units were classified based on susceptibility to erosion processes, with clastic sediments identified as most prone to flash floods. Land use analysis highlighted non-irrigated agricultural surfaces and areas with sparse vegetation as highly susceptible. Integration of these factors into the FFPI model provided insights into flash flood susceptibility, with results indicating a medium risk across the catchment. The average value of the FFPI is 1.9, considering that the values range from 1 to 5. Also, terrains susceptible to flash floods were found to be 49.34%, classified as medium risk. Field survey data validated the model, revealing a significant overlap between hotspot areas for flash floods and high-risk regions identified by the FFPI. An average FFPI coefficient was calculated for each tributary (sub-catchment) of the Kratovska Reka. According to the model, Latišnica had the highest average coefficient of susceptibility to potential flash floods, with a value of 2.16. These findings offer valuable insights for spatial planning and flood risk management, with implications for both local and national-scale applications. Future research directions include incorporating machine learning techniques to enhance modeling accuracy and reduce subjectivity in assigning weighting factors.

KW - FFPI

KW - flash floods risk

KW - geospatial analytics

KW - GIS

KW - Kratovska Reka

KW - natural hazards

KW - Remote Sensing

UR - https://www.degruyter.com/document/doi/10.1515/geo-2022-0684/html#Vancouver

UR - http://www.scopus.com/inward/record.url?scp=85202958344&partnerID=8YFLogxK

U2 - 10.1515/geo-2022-0684

DO - 10.1515/geo-2022-0684

M3 - Article

VL - 16.2024

JO - Open Geosciences

JF - Open Geosciences

SN - 2391-5447

IS - 1

M1 - 20220684

ER -