Determining and characterising locations vulnerable to flooding can help in reducing damage and the number of fatalities. During the monsoon season, East India's Subarnarekha River frequently floods to a significant degree. In current work, we suggest a unique hybrid strategy for preparing the entire catchment's Flood Susceptibility Mapping (FSM). The study area's FSM was conducted by considering 10 flood conditioning factors utilising the Best-Worst Method (BWM) and a multi-parametric Analytical Hierarchy Process (AHP) as per expert knowledge. Meanwhile, the proposed strategy incorporates a Decision Making Trial and Evaluation Laboratory (DEMATEL) for examining causal linkages and dependencies between different elements affecting the flooding process. Several statistical matrices were used to compare the suggested strategy of BWM and AHP. Based on our findings, we concluded that the integration of DEMATEL with AHP and BWM (ID BWM, ID AHP) was more effective than alternative strategies. The findings show that out of 10 flood conditioning factors, slope, elevation, distance from the river, drainage density, Topographic wetness Index (TWI), Land Use Land Cover (LULC), Normalised Difference Vegetation Index (NDVI), precipitation, soil texture, and curvature, factors that have the biggest effects on the local flooding phenomenon are elevation, slope, precipitation, and distance from the river. For validating the efficacy of the flood susceptibility map, Area under the Receiver Operating Characteristic Curve (AUC-ROC) was adopted and demonstrated, showing a pretty high accuracy of (0.92 or 92% and 0.94 or 94%) for ID AHP and ID BWM, respectively. Our research findings provide a highly affordable and useful answer to the flooding problems of basin Subarnarekha.

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.

Identifying soil erosion-prone zones in an ungauged river basin is crucial for devising and implementing timely soil protection measures to mitigate soil degradation and protect soil quality. Soil erosion damages the fragile ecosystem, decreases soil fertility, and reduces reservoir water storage, thereby impacting food production. The prime motive of the current research work is to assess and categorize on the basis of priority the sub-watersheds (SWs) susceptible to substantial soil erosion in the Ponnaniyar River basin (an ungauged river basin) based on the morphometric parameters that impact soil erosion. To achieve this research objective, four multi-criteria decision-making (MCDM) approaches based on the outranking approach and synthesis method are adopted to facilitate the decision-making process by considering an integrated and balanced assessment of multiple complex parameters for devising effective soil conservation measures to minimize soil erosion. Cartosat-1 digital elevation model (DEM) is employed to extract eighteen morphometric parameters under linear, shape, areal, relief and hypsometric aspects. The priority of SWs obtained by different MCDM techniques is evaluated using percentage of variation and intensity of variation. The outcomes show that the MABAC method is effective in prioritizing SWs with the least percentage of variation (59.61%) and intensity of variation (4.397). It is also found to be the best method for integration with the RSS method for determining SW priority with a root sum of squares value of 43. SW1 is identified to be highly vulnerable to soil erosion with a grade average value of 1.00 followed by SW2 (3.00), SW3 (3.25) and SW13 (5.00), requiring immediate implementation of watershed planning and management measures to control the extent of soil erosion and safeguard soil resources.

The identification of areas prone to soil erosion in ungauged river basins is crucial for timely preventive measures, as erosion causes significant damage by lowering soil productivity and filling reservoirs with sedimentation. This study proposes a novel approach to prioritize sub-watersheds (SWs) in Ponnaniyar river basin. It utilizes different combinations of five objective-based weighting methods and seven Multi-criteria Decision Making (MCDM) techniques under outranking and synthesis methods with soil loss, morphometry, land use/land cover (LULC), and topography parameters. The results obtained from different hybrid models are validated using metrics like percentage and intensity of change. The findings reveal that MW-PROMETHEE (53.85%) and CRITIC-WASPAS (8.31) perform best in prioritizing areas based on morphometry, while CRITIC-TOPSIS (48.35% and 7.58) is more effective in prioritizing areas based on land use/land cover (LULC) and topography. The grade average method is used to integrate the rankings from 71 models: 35 based on morphometry, 35 based on LULC, and 1 based on the RUSLE model. The analysis identifies SW2 with a grade value of 4.34 as severely affected by soil erosion, followed by SW11 (5.45), SW5 (5.56), and SW9 (5.68), all falling within the very high priority level. This study recommends implementing appropriate water harvesting structures, which might be helpful in mitigating soil degradation, promoting soil conservation, and ensuring sustainable agricultural productivity.

Timber extraction is a time-consuming and difficult stage of producing the wood-based forest products, involving economic and ecological sensitivity. In this study, it was aimed to determine the optimum extraction methods in terms of productivity and environmental effects by integrating the analytical hierarchy process (AHP) method with geographic information systems (GIS). The study was implemented in the coniferous stands located within the borders of Baharlar Forest Enterprise Chief (FEC) in Ayvac & imath;k Forest Enterprise Directorate (FED) in Bal & imath;kesir in T & uuml;rkiye. The main criteria in AHP were slope, skidding (transporting) distance, soil factor, stand age and yield. In the study, tractor skidding, tractor winching, chute system and skyline yarding methods were evaluated by considering environmental effects including residual tree damage and potential impacts on forest soil. In the solution phase, a total of eight suitability maps were produced for four extraction methods for productivity and environmental effects assessment. After the suitability maps were generated, digital data layers of working time were produced for each extraction method using equations about machine working times obtained from previous studies. As a result of the study, it was determined that skidding distance and slope were the criteria with the highest impact in almost all extraction methods for productivity and environmental aspects. In tractor skidding, it was found that soil factor and skidding distance have the highest impact in terms of environmental effects. When considering productivity, the results showed that the most commonly preferred extraction method was the tractor winching (43.30%), followed by the tractor skidding (25.34%). While the chute system was preferred in approximately 20.92% of the area, the least preferred method was the skyline yarding (10.44%). When evaluated in terms of environmental effects, it was determined that tractor skidding (34.02%) was widely preferred, followed by chute system (26.95%), tractor winching (20.96%) and skyline yarding (18.07%).

游客满意度是衡量旅游地竞争力的关键因素之一，已受到众多旅游研究者的关注。在其热点研究中，有关冰川旅游游客满意度及不同游客属性间满意度差异的研究鲜见。选取达古冰川与海螺沟冰川为研究区，通过对游客属性细分，运用模糊多准则决策法（F-MCDM）及引入需求弹性理论对冰川旅游游客满意度进行了综合评价和敏感性分析，探讨了提升冰川旅游游客满意度的对策建议。结果表明：达古冰川游客实际满意度总体高于海螺沟冰川，两地均以管理与服务的满意度最高，消费状况与交通的满意度最低。就游客属性的相对满意度而言，两地均呈现男性满意度高于女性，高消费游客满意度高于低消费游客，高忠诚度游客满意度高于低忠诚度游客；两地相对满意度的差异表现在年龄、受教育程度、客源地和到访次数方面。相较于达古冰川，海螺沟冰川满意度敏感性更高，同等改进力度下游客满意度的提高更为明显高效，就两地满意度敏感性最高的景观特色而言，达古冰川1%的改善将提升游客满意度0.30%，而海螺沟冰川可提升0.45%；对于不同游客属性的满意度敏感性，两地均以不愿推荐、不愿重游和未达到期望的游客最高。最后依据满意度敏感性分析结果，为两地冰川旅游发展提出了关键属性改进、...