The rapid acceleration of urbanization, combined with the proliferation of impervious surfaces and the inherently low permeability of soil layers, has worsened urban waterlogging. This study explores the layout of filter element seepage wells within a sponge city framework to enhance rainwater infiltration and reduce surface water accumulation, proposing an optimized method for determining well spacing and depth. The optimization uses a multi-objective genetic algorithm to target the construction cost, seepage velocity, total head, and pore water pressure. A combined weighting method assigns weights to each aim, while the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) determines the perfect spacing and depth. The results show that the optimal spacing and depth of the filter element seepage wells are 1.572 m and 2.794 m, respectively. Compared to the initial plan, the optimized scheme reduces construction costs by 21.31%, increases the rainwater infiltration efficiency by approximately 200%, raises the total hydraulic head by 17.23%, and decreases the pore water pressure by 5.73%. Sensitivity analysis shows that the optimized scheme remains stable across different weight combinations. This optimized layout significantly improves both the infiltration capacity and cost-effectiveness.

Mismanagement and human activities in the environment have a significant effect on increasing the loss of soil. Therefore, the current research is planned to incorporate management responses in the direction of soil erosion changes from the past (2011), the current situation (2021), and the future (2031) through the RUSLE and DPSIR models. In this regard, first, the Landsat 5 and 8 satellite images of 2011 and 2021 have been used to prepare the land cover map of the Eskandari Watershed. Then, the prediction of land cover change was done using the Markov model, and soil erosion was calculated with RUSLE. Then, by organizing a workshop with the presence of stakeholders and experts, the driving force-pressures-state-impacts-responses (DPSIR) were investigated in the direction of soil erosion changes. Finally, the stakeholder's responses were ranked and components were prioritized by the TOPSIS method. The results show that soil erosion in 2011, 2021, and 2031 is 4.49, 7.13, and 11.44 ton/h/y, respectively. In addition, the main driver for increasing soil erosion in the region is the expansion of agricultural land (82.0%). The pressure of destruction and change of land use (90.1%) is one of the most important reasons for the development of improper agriculture (86.5%) in the region, which has the most main effect on the increase of flood and erosion damage (82.5%). In this regard; strengthening of supervisory and executive mechanisms and modification of laws with a score of 0.741 is an appropriate management response in the Eskandari Watershed. Also, the implementation of comprehensive watershed management programs (0.694) and management and organizational cohesion (0.551) are assigned the next priorities respectively. Finally; the results of prioritization based on the weights obtained regarding the contribution of the components in the direction of increasing soil erosion showed that the pressure component (0.302) has the highest contribution and the impact (0.24), driver (0.231) and state (0.227) components are respectively in the next priorities. While; the suggested with the implementation of management responses; the contribution of pressure, impact, state, and driver components on soil erosion in the watershed should be reduced to 0.396, 0.272, 0.247, and 0.085 respectively. In this regard; the current research is significant in terms of the attention of managers and experts in the implementation of corrective management based on the results obtained. So; to prevent the increase of soil loss and improve the watershed situation, the policies of the land sector should be carried out in a larger context and with internal and external cooperation.

Uncontrolled wildfires pose a significant threat, potentially causing extensive damage to biodiversity, soil quality and human resources. It's crucial to swiftly detect and predict these wildfires to minimize their catastrophic consequences. To address this, our research introduces a wildfire prediction model that ranks cities based on risk leveraging multi-criteria decision-making (MCDM) to systematically assess conflicting factors in decision-making. This model integrates wildfire risks into a city's resilience strategy, utilizing fuzzy set theory to manage imprecise data and uncertainties. As part of this approach, we compile a new dataset encompassing weather patterns, vegetation types, terrain features and population density across various Californian cities. Ultimately, the model assesses and ranks the wildfire risk for each city in California.

为解决松嫩平原碳酸盐渍土对工程的不利影响，且削弱季节冻土区冻融循环对碳酸盐渍土带来的损伤，采用无机材料石灰和粉煤灰对碳酸盐渍土进行改良。研究了不同改良方案下碳酸盐渍土抗剪强度的变化及其抵抗冻融循环的能力；通过熵权-TOPSIS模型对各改良方案进行评价。结果表明：石灰和粉煤灰均会提升碳酸盐渍土的抗剪强度，但是石灰的改良效果远胜于粉煤灰，石灰会使得碳酸盐渍土的应力-应变曲线变成应变软化型；粉煤灰在提升碳酸盐渍土抵抗冻融损伤能力上表现得比较突出；而双掺石灰和粉煤灰明显兼顾了强度和抵抗冻融损伤能力这2个指标；在考虑力学性能、抗冻融能力以及经济等因素时，石灰和粉煤灰的掺量均为12%的方案最优。

为合理全面确定各影响因子及其权重,客观分析青藏铁路冻土路基安全性,基于ANP结构模型和扩展TOPSIS方法建立青藏铁路冻土路基安全性分析模型。模型选取7个典型监测断面,确定17个主要影响因子,利用ANP结构模型并基于Super Decision软件分析各因子权重,然后基于扩展TOPSIS方法计算各监测断面的灰色关联度,得出各监测断面的安全性排序。将分析结果与已有成果进行对比,结果基本一致;将评价结果与实际对比分析可知,7个监测断面的安全性与现场情况高度吻合。利用所提出的模型进行路基安全性分析是有效的。