Evaluation of pre- and post-fire flood risk by analytical hierarchy process method: a case study for the 2021 wildfires in Bodrum, Turkey

• Published in: Landscape and ecological engineering Vol. 19; no. 2; pp. 271 - 288
• Main Authors: Yilmaz, Osman Salih, Akyuz, Dilek Eren, Aksel, Murat, Dikici, Mehmet, Akgul, Mehmet Adil, Yagci, Oral, Balik Sanli, Fusun, Aksoy, Hafzullah
• Format: Journal Article
• Language: English
• Published: Tokyo Springer Japan 01.04.2023; Springer Nature B.V
• Subjects: Analytic hierarchy process; Biomedical and Life Sciences; case studies; Civil Engineering; Environmental Management; Environmental risk; Floods; Forest fires; Forests; Geographic information systems; Hierarchies; Land cover; Land use; land use and land cover maps; Landscape Ecology; Landscape/Regional and Urban Planning; landscapes; Life Sciences; Lithology; Mediterranean region; Model accuracy; Natural disturbance; Nature Conservation; Original Paper; Plant Ecology; prediction; rain; Rainfall; risk; Risk analysis; streams; topography; Wildfires; Turkey; Mediterranean region; GIS; Bodrum; Wildfire; Analytical hierarchy process; Flood vulnerability
• ISSN: 1860-1871; 1860-188X
• DOI: 10.1007/s11355-023-00545-x

Wildfires are regarded as one of the devastating natural disturbances to natural ecosystems, and threatening the lives of many species. In July 2021, a wildfire took place in the Mediterranean region of Turkey in multiple areas. In Bodrum, a town with high touristic value and attraction, approximately 17,600 hectares of forest have been affected by the wildfire. In this study, the fire-affected areas were determined using an analytical hierarchy process (AHP) and geographical information system (GIS). Rainfall, slope, distance from the stream, pre- and post-fire land use and land cover, elevation, curvature, topographic wetness index, and lithology were selected as the governing variables for the AHP model. The contribution of each variable was determined from the literature. Based on the model, it was found that the area with a very high flood risk increased from 8.6 to 18.4%, implying flood risk in a particular region doubled following the wildfire. Immediately after the forest fire, floods occurred in Mazikoy in the region and its surroundings. The model accuracy was tested by using randomly selected 61 points in and around the flooded area. The model accuracy was quantified by the receiver operating characteristic (ROC) curves method. Pre- and post-fire areas under curve (AUC) values were found 0.925 and 0.933, respectively, which implies that the prediction ability of the model is acceptably accurate. The study revealed that the model could quantify the increased flood risk for vulnerable areas after a forest fire. Such knowledge may aid local authorities in determining the priorities of the precautions that need to be taken after a forest fire.