Integrating Multi-Source Geospatial Data and AHP for Flood Susceptibility Mapping in Ain Smara, Constantine, Algeria

By Vladimir CvetkovicNews

Authors

  • Nouh RebouhCentre de Recherche en Aménagement de Territoire (CRAT), Campus Zouaghi Slimane, Route de Ain el Bey, 25000 Constantine, Algérie
  • Faicel ToutCentre de Recherche en Aménagement de Territoire (CRAT), Campus Zouaghi Slimane, Route de Ain el Bey, 25000 Constantine, Algérie
  • Haythem DinarCentre de Recherche en Aménagement de Territoire (CRAT), Campus Zouaghi Slimane, Route de Ain el Bey, 25000 Constantine, Algérie
  • Yacine BenzidCentre de Recherche en Aménagement de Territoire (CRAT), Campus Zouaghi Slimane, Route de Ain el Bey, 25000 Constantine, Algérie
  • Zakaria ZouakCentre de Recherche en Aménagement de Territoire (CRAT), Campus Zouaghi Slimane, Route de Ain el Bey, 25000 Constantine, Algérie

DOI: 

https://doi.org/10.18485/ijdrm.2024.6.2.16

Keywords: 

flood susceptibility, geographic information system (GIS), analytical hierarchy process (AHP), google earth engine (GEE), Ain Smara

Abstract

Mapping flood susceptibility is essential for identifying flood-prone areas and informing flood risk management strategies. This study applies a multi-criteria decision-making approach to assess flood vulnerability in Ain Smara and its surrounding areas in Constantine, Algeria, which are highly susceptible to flooding. The analysis combines the Analytical Hierarchy Process (AHP), Geographic Information System (GIS), Remote Sensing (RS), and the Google Earth Engine (GEE) platform. Ten key flood-related criteria were selected, including the Topographic Wetness Index, Elevation, Slope, Precipitation, Land Cover/Land Use, Normalized Difference Vegetation Index (NDVI), Distance from Rivers, Distance from Roads, Drainage Density, and Lithology, along with more than 25 sub-criteria. A pairwise comparison matrix (PCM) was used to assign relative importance to each criterion based on its impact on flood susceptibility. The Topographic Wetness Index was identified as the most significant criterion, while Distance from Roads was deemed the least significant. The results reveal that approximately 4.00% of the area is classified as having high to very high flood susceptibility, particularly near the Rhumel River. Roughly 30% of the area has low to very low susceptibility, and the remaining 66% is categorised as moderately susceptible to flooding. Notably, most of the identified flood-prone zones correspond with areas that experienced flooding events in 2019, 2020, and 2021, predominantly within 1,000 meters of river courses. These findings demonstrate the GIS-AHP technique’s effectiveness in generating reliable flood susceptibility maps, especially when numerous criteria are considered.

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2024-12-25

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Rebouh, N., Tout, F., Dinar, H., Benzid, Y., & Zouak, Z. (2024). Integrating Multi-Source Geospatial Data and AHP for Flood Susceptibility Mapping in Ain Smara, Constantine, Algeria. International Journal of Disaster Risk Management, 6(2), 245–264. https://doi.org/10.18485/ijdrm.2024.6.2.16More Citation Formats

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