Flood hazard has resulted in the loss of thousands of lives and large-scale damage to properties. This study has explored, analyzed, and categorized the flood hazard and risk levels of Arba Minch City in South Ethiopia by integrating geospatial and Analytical Hierarchy Process techniques. Data were acquired from DEM with 12.5 m resolution, Landsat 8 OLI, ortho-rectified, and surveyed data from the Municipality. Slope, Elevation, Rainfall, Aspect, Curvature, Topographic Wetness Index, Topographic Roughness Index, Drainage Density, Distance from River, Soil Types, Land Use Land Cover, and Population Density parameters were used. Standard classification criteria were set based on literature and experts' judgment. Data were rasterized, resampled, and reclassified into five classes through the natural break method and readjustment. The flood hazard map was produced using the weighted overlay technique with hazard levels of low (7.39%), moderate (56.13%), and high (36.48%). Whereas, very low and very high remained nil. The flood risk levels were produced ascendingly as 2.4%, 17.3%, 17%, 44%, and 19.4%, respectively. The validity of the model was confirmed by the ROC-AUC Value of 0.923 being fitted with flood damage sites of Shara, Limat, Airport, Agriculture Research Center, Konso Sefer, Ashewamado, Gurba, and Arba Minch University campuses. Slope, elevation, rainfall, aspect and curvature were the top priority flood hazard parameters. The hazard map, population density, and land use land cover inputs have significant weights for flood risks. Thus, the study findings urge that the stakeholders should take integrated and consistent flood risk reduction and management measures.

This paper has attempted to determine the weighting levels of the soil and ground motion parameters (engineering bedrock depth (EBd), average shear wave velocity (Vs30), fundamental frequency (f0), peak ground acceleration (PGA), Joyner-Boore distance (Rjb), and epicenter distance (Repi)) in reflecting the actual damage status after the 2023 Kahramanmara & scedil; earthquakes, which have a wide impact area of 11 provinces. The analytical hierarchy method (AHP), a multi-criteria decision-making (MCDM) process, was used to analyze these parameter data sets obtained from 44 Disaster and Emergency Management Presidency of T & uuml;rkiye (AFAD) stations (Gaziantep, Hatay, Kahramanmara & scedil;, and Osmaniye). The priority order of the parameters before the analysis was systematically collected. These parameters were categorized into soil, ground motion and earthquake source-path properties. Considering the literature, these characteristics and their combined effects were systematically weighted with AHP under five groups. According to the weighted groups in the scope of the study, the actual damage data can be determined with a minimum accuracy rate of 70% (Group 1). In comparison, the best performance evaluation was 82% (Group 5). The parameter order and weights in the actual damage data evaluation are suggested as EBd-%28, PGA-%24, Vs30-%19, Rjb-%14, f0-%10, and Repi-%5 considering the very high accuracy rate of Group 5. This suggested weighting allows the rapid and effective estimation of the damage distribution after a possible earthquake only with soil, ground motion and earthquake source-path characteristics, even in cases where reliable structure data cannot be obtained.

Landslides are significant geological hazards in mountainous regions, arising from both natural forces and human actions, presenting serious environmental challenges through their extensive damage to properties and infrastructure, often leading to casualties and alterations to the landscape. This study employed GIS-based techniques to evaluate and map the landslide susceptibility in the Bekhair structure located within the Zagros mountains of Kurdistan, northern Iraq. An inventory map containing 282 landslide occurrences was compiled through intensive field investigations, as well as the interpretation of remote sensing data and Google Earth images. Ten potential influencing factors, including elevation, rainfall, lithology, slope, curvature, aspect, LULC, NDVI, distance to roads and rivers, were selected to construct susceptibility maps by integrating the frequency ratio (FR) and analytical hierarchy process (AHP) approaches, with the goal of understanding how these factors relate to landslides occurrence. The Bekhair core area was divided into 5 hazard zones on the landslide susceptibility maps. The regions classified as very low and low hazard zones are mainly occur in flat or gently sloping plains that characterized by resistant rocks, dense vegetation, minimal rainfall, shallow valleys, and are distant from riverbanks and roads. The areas designated as high and very high hazard zones are found in steep slopes and rough terrain with bare soil, intense weathering, high rainfall, sparse vegetation, highly fractured rocks, deep valleys, and close proximity to construction projects. The moderate hazard zones are mainly located between the other 4 zones across the Bekhair anticline. Results of the susceptibility analysis indicate that the occurrence of landslides in Kurdistan mountains are primarily controlled by factors related to the tectonic structure, surface characteristics and environmental conditions, such as rock lithology (competency), terrain slope, rainfall intensity, and human impacts. The delineation of landslide hazard zones offers important guides for government decision-makers engaged in regional planning, infrastructure development, and the formulation of strategies to mitigate landslides and protect lives and properties in Kurdistan. The accuracy of susceptibility maps was evaluated using the R-index and the AUC-ROC curve. The landslide susceptibility index (LSI) values allocated to different susceptibility classes derived from both FR and AHP models are consistent with the values obtained from the R-index. Moreover, the FR model demonstrated superior performance compared to the AHP model, with a success rate of 85.3% and a predictive rate of 81.2%, in contrast to the AHP model's success rate of 75.2% and predictive rate of 72.4%.

The 2022 flood events in Quetta, Pakistan, caused severe damage to the economy, properties, and lives. Therefore, flood risk mapping to identify flood-prone areas is essential for planners and decision-makers to take critical protective measures to control the effects of flooding. This study focuses on mapping flood-prone regions in the Quetta district of Pakistan using an analytical hierarchy process (AHP) and a geographic information system (GIS). The factors influencing flood used in the present study were topographic witness index (TWI), elevation, slope, land use, land cover, precipitation, stream distance, drainage density, and soil type. Weights and ranks were allocated separately to all factors through AHP and were interpreted in a GIS environment. The produced flood hazard model of the study area depicted four zones. These zones ranged from low (19.49%), moderate (43.34%), high (28.30%), to very high (8.87%). The model was further validated through previous flood events in the study area. Around 90% of flood hazard events in the past took place mainly in the produced model's very high and high zones, which is why the current model is reliable. Finally, integrating geospatial approaches with AHP in flood hazard mapping is a quick, reliable, and affordable method that may be utilized in the area.

Frequent extreme weather events result in substantial economic losses for farming communities, posing a significant threat to the livelihood security of smallholder farmers in the Sundarbans region of India. Various agricultural enterprises in this area are continually at risk due to saline water intrusion, crop damage from heavy rainfall, and flooding. We examine the strategies farmers have adopted to sustain their livelihoods in the face of these extreme weather events. We collected primary data from a randomly selected sample of 1,200 farmers across six blocks in the Sundarbans region, focussing on farm households engaged in diverse agricultural enterprises, including field crop cultivation, livestock rearing, and fish farming. We used the Analytical Hierarchy Process (AHP) to prioritize the coping mechanisms adopted by these farming communities. The assessment of coping mechanisms was based on four criteria: ease of implementation, cost, effectiveness, and durability for long-term application. Effectiveness got the highest weights of 0.492 followed by the durability of the coping strategy weights of 0.309. Coping mechanisms pertaining to managing soil health against soil salinity, raising livestock and fish species as well as cultivating field crops were identified and prioritized according to their perceived efficacy against extreme weather events. Our results can inform the formulation of robust and sustainable development policies for agricultural and allied sectors in the Indian Sundarbans.