Among natural hazards and disastrous outcomes, floods have tremendous impacts on infrastructure as well as on humans. In the present study, we determined flood hazard using several hydro-geomorphic factors in the Darab watershed. For this purpose, the Analytical Hierarchical Process (AHP) and fuzzy logic were used in the initial phase of the mapping process to overlap layers. The kernel density and zonal statistics were employed to calculate flood hazard density and flood hazard zones, respectively. In addition, the spatial statistics were considered to identify floods with high and low clusters in flood hazardous zones using ArcGIS Pro. The results showed that the Gamma operator (0.9) with the AUC value of 0.8924 was the optimal operator for flood zonal statistics. Only 26.45% of the study area had high flood intensity, and only two high-hazard flooding clusters were detected in the Darab watershed. The heighest value of flood was recognized in the north and northeast of the study area, which corresponded to small towns with less than 5000 inhabitants. Our experiments demonstrated that the integration of geospatial analysis with spatial statistics may provide a reliable method to assess flood hazard.
An integrated geospatial and statistical approach for flood hazard assessment / Shariati, Mohsen; Kazemi, Mohamad; Naderi Samani, Reza; Kaviani Rad, Abdullah; Kazemi Garajeh, Mohammad; Kariminejad, Narges. - In: ENVIRONMENTAL EARTH SCIENCES. - ISSN 1866-6280. - 82:16(2023). [10.1007/s12665-023-11077-w]
An integrated geospatial and statistical approach for flood hazard assessment
Kazemi Garajeh, Mohammad;
2023
Abstract
Among natural hazards and disastrous outcomes, floods have tremendous impacts on infrastructure as well as on humans. In the present study, we determined flood hazard using several hydro-geomorphic factors in the Darab watershed. For this purpose, the Analytical Hierarchical Process (AHP) and fuzzy logic were used in the initial phase of the mapping process to overlap layers. The kernel density and zonal statistics were employed to calculate flood hazard density and flood hazard zones, respectively. In addition, the spatial statistics were considered to identify floods with high and low clusters in flood hazardous zones using ArcGIS Pro. The results showed that the Gamma operator (0.9) with the AUC value of 0.8924 was the optimal operator for flood zonal statistics. Only 26.45% of the study area had high flood intensity, and only two high-hazard flooding clusters were detected in the Darab watershed. The heighest value of flood was recognized in the north and northeast of the study area, which corresponded to small towns with less than 5000 inhabitants. Our experiments demonstrated that the integration of geospatial analysis with spatial statistics may provide a reliable method to assess flood hazard.File | Dimensione | Formato | |
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