Flash flood-risk areas zoning using integration of decision-making trial and evaluation laboratory, GIS-based analytic network process and satellite-derived information

Abstract

Assessing areas prone to flash floods is crucial for effective disaster management and mitigation. This study proposes a framework for mapping flood-prone areas by integrating geographic information system (GIS), remote sensing data, and multi-criteria decision-making (MCDM) techniques. The hybrid MCDM model combines the decision-making trial and evaluation laboratory (DEMATEL) with GIS-based analytic network process (ANP) to evaluate flood vulnerability in Golestan province, Iran. Fourteen criteria related to flood potential, including elevation, slope, aspect, vegetation density, soil moisture, flow direction, river distance, rainfall and runoff, flow time, geomorphology, drainage density, soil type, lithology, and land use, were considered. In areas where official data was lacking, a questionnaire was administered to gather information from 15 specialists, experts, and 20 local managers. The relationships between criteria were analyzed using the DEMATEL method, and their weights were determined using the ANP method. Topography was found to have the greatest impact on flood risk, followed by the type of surface and vegetation cover. Hydrographic, soil and geology, climatic also influence flooding in the region. The study identified the northern and central parts of the study area being at higher risk of flooding compared to the southern part. Based on the flood intensity map, 68 villages (50% of all villages in the Qarasu watershed) with a population of approximately 83,595 were identified as at risk of flooding. The proposed GIS-DANP model provides a valuable tool for flood management and decision-making, aiding in risk reduction and minimizing casualties.

Assessing the Influence of Land Cover and Climate Change Impacts on Runoff Patterns Using CA-ANN Model and CMIP6 Data

“…The precipitation data is adjusted based on the antecedent moisture condition (AMC) criteria (AMC I, AMC II, and AMC III). Subsequently, inverse distance weighting (IDW) technique was leveraged, and precipitation maps are generated, each corresponding to distinct AMC conditions [53]. Furthermore, hydrologic soil group (HSG), CN, and weighted CN are derived for each LULC class based on the corresponding soil type.…”

Copula-Probabilistic Flood Risk Analysis with an Hourly Flood Monitoring Index

“…Flooding is a catastrophic natural disaster progressively increasing in frequency and severity, primarily attributed to climate change-induced phenomena such as increased rainfall intensity. Generally, there are three prevalent flood types: fluvial or river floods, pluvial or flash floods, and coastal floods [1,2]. A flash flood is a sudden and severe local inundation often resulting from high-intensity rainfall (e.g., tropical cyclones, slow-moving tropical depressions, or thunderstorms) within a short period (usually less than six hours) and/or may also be caused by sudden discharge of impounded water (e.g., dam or levee failures, ice jam release, or a glacier lake outburst) [3,4].…”