[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-4560":3,"related-4560":101},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":23,"tags":25,"primary_topic":31,"secondary_topics":37,"classification":38,"search_phrases":75,"slug":78,"view_count":21,"doi":79,"paper":80,"created_at":100},4560,"Assessment of Flood Impacts, Losses and Adaptation Practices in Bhajani Municipality, Kailali District, Nepal","https:\u002F\u002Fdoi.org\u002F10.3126\u002Futjliast.v2i3.101085","Floods are the most frequent and damaging hydro-meteorological hazard in the Terai region of Nepal, yet municipal-scale evidence that links hazard mapping, community perception, historical losses and local adaptation remains scarce. This study assesses flood impacts, losses, and adaptation practices in Bhajani Municipality, Kailali District, Sudurpashchim Province, a low-lying municipality with nine wards (176.25 km²) and crossed by the Mohana, Kandra, Kanda (Kadha), and Patharaiya rivers. A mixed-methods design combined a questionnaire survey of 156 respondents (Slovin’s formula, e = 8%), focus group discussions, in-depth interviews, field observation and desk review of the Local Disaster and Climate Resilience Plan (LDCRP). The Relative Importance Index (RII) was used to rank 16 flood-related problems, their causes and effects, and 12 adaptation measures rated on a five-point Likert scale; 64 Chi-square tests of independence examined whether perceptions differ by gender, age, occupation and education, and a GIS-based Weighted Multi-Criteria Decision Analysis (WMCDA) using distance from rivers (30%), Topographic Wetness Index (25%), slope (25%) and Height Above Nearest Drainage (20%) produced a flood hazard map. Wards 3, 5, 7 and 8 were classified as very high flood-risk areas, wards 6 and 9 as high, wards 1 and 2 as moderate and ward 4 as low–moderate; 85 settlements and hamlets are potentially exposed. Sixteen flood events recorded in municipal and community records affected 5,140 households, displaced 598 households, destroyed 188 houses, damaged about 1,695 bighas of cultivable land, caused an estimated loss of NPR 702.4 million and claimed 10 lives. Agriculture damage (RII = 0.863) and livestock damage (0.846) ranked as the most important problems. Non-compliance with flood-resistant building standards (0.914), waterlogging from slow runoff (0.891), insufficient investment in early warning systems (0.854) and weak institutional capacity (0.854) were the leading perceived causes, while displacement of local communities (0.905) and high livestock mortality (0.862) were leading effects. Perceptions were largely homogeneous: 62 of 64 tests (96.9%) showed no demographic association, with age linked only to views on public awareness and physical infrastructure. Strengthening river management and flood-control infrastructure (0.803) was the highest-rated adaptation measure, followed by climate-smart agriculture (0.760). A case study contrasts the slow-onset, long-duration Kandra floods with the rapid, short-warning Kadha flash floods. Flood risk in Bhajani is multidimensional, combining physical exposure, socio-economic vulnerability, infrastructure deficiencies, institutional weaknesses and climatic variability. Ward-prioritized embankment and drainage works, community-based early warning, enforcement of flood-resilient construction, climate-smart agriculture and ecosystem-based watershed management are recommended.","洪水是尼泊尔特莱地区最频繁且破坏性最强的水文气象灾害，然而，将灾害制图、社区感知、历史损失与地方适应相联系的市镇尺度证据仍然匮乏。本研究评估了苏杜尔帕希姆省凯拉利县巴贾尼市的洪水影响、损失与适应实践。该市地势低洼，下辖9个区（176.25平方公里），莫哈纳河、坎德拉河、坎达河（卡达河）和帕塔拉伊亚河穿境而过。研究采用混合方法设计，结合了156名受访者的问卷调查（Slovin公式，e = 8%）、焦点小组讨论、深度访谈、实地观察以及对《地方灾害与气候韧性计划》（LDCRP）的案头审查。采用相对重要性指数（RII）对16项洪水相关问题及其成因与影响、以及12项适应措施进行排序，评分采用五点李克特量表；通过64项卡方独立性检验考察感知是否因性别、年龄、职业和教育程度而异；并运用基于GIS的加权多准则决策分析（WMCDA），以距河流距离（30%）、地形湿度指数（25%）、坡度（25%）和距最近排水沟高度（20%）为因子，生成了洪水灾害图。第3、5、7和8区被划为极高洪水风险区，第6和9区为高风险区，第1和2区为中等风险区，第4区为低至中等风险区；85个居民点和村落可能受到影响。市镇和社区记录中记载的16次洪水事件共影响5，140户家庭，使598户家庭流离失所，摧毁188栋房屋，损坏约1，695比加耕地，造成约7.024亿尼泊尔卢比的估计损失，并导致10人丧生。农业损失（RII = 0.863）和牲畜损失（0.846）被列为最重要的问题。不遵守抗洪建筑标准（0.914）、径流缓慢导致的内涝（0.891）、预警系统投资不足（0.854）和机构能力薄弱（0.854）是主要的感知成因，而当地社区流离失所（0.905）和高牲畜死亡率（0.862）是主要影响。感知在很大程度上具有同质性：64项检验中有62项（96.9%）未显示人口统计学关联，年龄仅与对公众意识和物质基础设施的看法相关。加强河流管理和防洪基础设施（0.803）是评分最高的适应措施，其次是气候智慧型农业（0.760）。一项案例研究对比了缓发性",null,"Universal Technical Journal of Lumbini International Academy of Science and Technology","2026-10-09T00:00:00Z","论文",10,false,61,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":17,"relevant":21,"comment":22},8,22,17,6,1,"尼泊尔市级洪水风险与农业损失实证研究，方法扎实数据翔实，但属境外地方案例，对国内三农信息化参考价值有限。",[24],{"name":10,"url":6},[26,27,28,29,30],"气候适应","遥感监测","洪水风险","尼泊尔","农业减灾",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},"H7","climate","气候适应与防灾减灾","\u002Ftopic\u002Fenvironment\u002Fclimate","H",[],{"status":39,"locked":14,"version":40,"method":41,"evidence":42},"classified","2026-10-22.2","rules",{"candidates":43,"agricultural_evidence":45},[44,51,58,64,70],{"code":32,"score":17,"supported":45,"title":46,"abstract":47,"tags":50},true,[],[48,49],"climate resilience","waterlogging",[26,28],{"code":52,"score":53,"supported":45,"title":54,"abstract":55,"tags":57},"C",3,[],[56],"livestock",[],{"code":59,"score":53,"supported":45,"title":60,"abstract":61,"tags":63},"I1",[],[62],"smart agriculture",[],{"code":65,"score":53,"supported":45,"title":66,"abstract":67,"tags":69},"I4",[],[68],"GIS",[],{"code":71,"score":21,"supported":14,"title":72,"abstract":73,"tags":74},"I3",[],[],[27],[76,77],"Bhajani Municipality 洪水风险","Kailali 农业损失 适应","BhajaniMunicipality洪水风险-4560","10.3126\u002Futjliast.v2i3.101085",{"doi":79,"openalex_id":81,"authors":82,"venue":10,"cited_by_count":91,"oa_url":6,"card":92,"direction":98,"ingested_from":99},"W7221076000",[83,85,87,89],{"name":84,"orcid":9},"Anesh Shrestha",{"name":86,"orcid":9},"Khet Raj Dahal",{"name":88,"orcid":9},"Sujeet Dhakal",{"name":90,"orcid":9},"Sagar Sedhain",0,{"tldr":93,"method":94,"finding":95,"direction":96,"opportunity":97},"评估尼泊尔Bhajani市洪水影响、损失与适应实践，并绘制洪水风险图。","混合方法：156份问卷、RII排序、卡方检验与GIS加权多准则决策分析。","第3、5、7、8区为极高风险；农业与牲畜损失最重，河流管理是最受认可的适应措施。","农业绿色发展与碳","可延伸至社区感知与GIS风险图耦合的适应策略优化，及气候智慧型农业的落地评估。","智慧农业 \u002F 农业物联网","openalex","2026-10-10T23:30:07.730161Z",{"total":20,"page":21,"page_size":20,"items":102},[103,169,284,346,407,468],{"id":104,"title":105,"url":106,"summary":107,"summary_zh":108,"content":9,"source_name":109,"source_url":106,"published_at":110,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":111,"score_detail":112,"sources":118,"tags":120,"primary_topic":124,"secondary_topics":125,"classification":126,"search_phrases":147,"slug":150,"view_count":143,"doi":151,"paper":152,"created_at":168},4593,"Climate Resilience and the Hydro-Vegetal Paradox in El Bayadh Province (Algeria, 1984-2023)","https:\u002F\u002Fdoi.org\u002F10.56093\u002Faaz.v65i3.177509","The decade 2010 to 2020 was the warmest ever recorded in the Mediterranean basin (+1.5°C), exceeding the global average. North Africa, identified as a vulnerability hotspot by the IPCC AR6, experiences intensified droughts and ecosystem degradation. This study presents the first quantitative assessment of climate resilience in El Bayadh Province (Algeria), revealing an unexpected hydro-vegetal paradox. A comparative multi-index methodology (restricted climate index vs. global index integrating 7 variables) was applied to 22 municipalities over the period of 1984 to 2023. The results showed a universal degradation of water balance (-8.2 to -21.4 mm yr-1) and widespread warming (+0.8 to +2.1°C decade-1). Paradoxically, 73 to 77% of municipalities showed improvement in vegetation indices (NDVI, SAVI), suggesting ecological adaptation. Principal component analysis (PCA-99%) variance explained) identified water stress as the main differentiating factor, and clustering distinguishes 5 territorial profiles (silhouette = 0.521). The global index proves more discriminant than the restricted index for capturing the complexity of socio-ecological dynamics. This study highlights the need for differentiated adaptation policies addressing challenges related to water, food security, and migration.","2010年至2020年是有记录以来地中海盆地最暖的十年（升温+1.5°C），超过了全球平均水平。北非被IPCC第六次评估报告（AR6）确定为脆弱性热点地区，正经历着加剧的干旱和生态系统退化。本研究首次对阿尔及利亚埃尔贝伊德省（El Bayadh Province）的气候韧性进行了定量评估，揭示了一个意想不到的水文-植被悖论。研究采用比较多指标方法（限制性气候指数与整合7个变量的全局指数），对22个市镇在1984年至2023年期间进行了分析。结果表明，水平衡普遍退化（-8.2至-21.4 mm yr⁻¹），且普遍升温（+0.8至+2.1°C decade⁻¹）。悖论的是，73%至77%的市镇植被指数（NDVI、SAVI）有所改善，表明存在生态适应。主成分分析（PCA，方差解释率达99%）确定水分胁迫为主要区分因子，聚类分析区分出5种地域类型（轮廓系数=0.521）。在捕捉社会-生态动态复杂性方面，全局指数比限制性指数更具判别力。本研究强调了制定差异化适应政策的必要性，以应对与水、粮食安全和移民相关的挑战。","Annals of Arid Zone","2026-10-08T00:00:00Z",74,{"impact":113,"substance":18,"depth":114,"authority":115,"freshness":116,"relevant":21,"comment":117},12,18,13,9,"基于22个市镇40年多指标遥感数据的干旱区气候韧性定量研究，方法新颖、结论有反差价值，但属区域案例研究，公共影响层级有限。",[119],{"name":109,"url":106},[121,26,27,122,123],"NDVI","干旱区农业","水资源安全",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":127},{"candidates":128,"agricultural_evidence":45},[129,135,142],{"code":32,"score":130,"supported":45,"title":131,"abstract":132,"tags":134},16,[48],[133,48],"干旱",[122,26],{"code":136,"score":20,"supported":45,"title":137,"abstract":138,"tags":141},"A8",[],[139,140],"粮食安全","food security",[],{"code":71,"score":143,"supported":14,"title":144,"abstract":145,"tags":146},2,[],[],[121,27],[148,149],"El Bayadh 阿尔及利亚 气候韧性","NDVI 植被指数 干旱区","ElBayadh阿尔及利亚气候韧性-4593","10.56093\u002Faaz.v65i3.177509",{"doi":151,"openalex_id":153,"authors":154,"venue":109,"cited_by_count":91,"oa_url":161,"card":162,"direction":166,"ingested_from":99},"W7220949140",[155,158],{"name":156,"orcid":157},"Lakhdar Guérine","https:\u002F\u002Forcid.org\u002F0000-0003-0836-2703",{"name":159,"orcid":160},"Naîmi Bendouina","https:\u002F\u002Forcid.org\u002F0000-0002-9776-1660","http:\u002F\u002Fepubs.icar.org.in\u002Findex.php\u002FAAZ\u002Farticle\u002Fdownload\u002F177509\u002F68050",{"tldr":163,"method":164,"finding":165,"direction":166,"opportunity":167},"首次量化阿尔及利亚El Bayadh省1984-2023年气候韧性，揭示水-植被悖论。","多指标对比法（限制性气候指数与7变量全球指数），对22个市镇做PCA和聚类。","水均衡普遍恶化、升温显著，但73-77%市镇植被指数改善，呈生态适应悖论。","农业遥感与作物表型","可探究干旱区NDVI改善的驱动机制（灌溉、物种更替或遥感尺度效应），并耦合社会经济数据。","2026-10-10T23:30:29.597640Z",{"id":170,"title":171,"url":172,"summary":173,"summary_zh":174,"content":9,"source_name":175,"source_url":172,"published_at":176,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":177,"score_detail":178,"sources":181,"tags":183,"primary_topic":188,"secondary_topics":189,"classification":200,"search_phrases":255,"slug":258,"view_count":91,"doi":259,"paper":260,"created_at":283},5483,"Soil Salinity under Climate Change in Pakistan: Emerging Challenges and Sustainable Management Approaches for Agriculture","https:\u002F\u002Fdoi.org\u002F10.71317\u002Fkjard.2.10.2026.883","Soil salinity is a major constraint to agricultural productivity, soil health, and food security in Pakistan, particularly under changing climatic conditions. Rising temperatures, increased evapotranspiration, irregular precipitation, droughts, flooding, and sea-level rise can intensify salt accumulation and alter soil–water interactions. This review examines the emerging challenges associated with climate change and soil salinity in Pakistan, focusing on their impacts on soil properties, crop physiology, agricultural production, and rural livelihoods. It discusses the mechanisms of soil salinity and sodicity, their spatial distribution, and the interactions among climate variability, irrigation practices, groundwater quality, and secondary salinization. Furthermore, sustainable management approaches are evaluated, including gypsum application, organic amendments, integrated nutrient management, efficient irrigation, drainage improvement, and appropriate leaching strategies. Climate-resilient approaches, such as conventional crop breeding, modern biotechnology, halophyte utilization, plant growth-promoting microorganisms, and mycorrhizal associations, are also explored. The review highlights the potential of remote sensing, geographic information systems, precision agriculture, and predictive modelling to support salinity monitoring and site-specific management. Despite these opportunities, important challenges remain, including insufficient long-term monitoring, limited region-specific data, economic constraints, and gaps in farmer awareness and institutional coordination. Addressing these challenges requires integrated research, effective agricultural policies, improved extension services, and collaboration among researchers, policymakers, and farming communities. Prioritizing locally adapted, economically feasible, and environmentally sustainable interventions can strengthen agricultural resilience, restore salt-affected soils, and protect freshwater resources. Overall, integrating climate adaptation with sustainable soil and water management is essential for maintaining agricultural productivity and improving long-term food security in Pakistan.","土壤盐渍化是制约巴基斯坦农业生产力、土壤健康和粮食安全的主要因素，在气候变化条件下尤为突出。气温升高、蒸散加剧、降水不规律、干旱、洪水以及海平面上升可能加剧盐分积累并改变土壤—水相互作用。本文综述了巴基斯坦气候变化与土壤盐渍化相关的新兴挑战，重点关注其对土壤性质、作物生理、农业生产和农村生计的影响。文章讨论了土壤盐渍化和钠质化的机制、其空间分布，以及气候变率、灌溉实践、地下水质量和次生盐渍化之间的相互作用。此外，评估了可持续管理途径，包括施用石膏、有机改良、综合养分管理、高效灌溉、排水改良和适宜的淋洗策略。还探讨了气候韧性方法，如常规作物育种、现代生物技术、盐生植物利用、植物促生微生物和菌根共生。本文强调了遥感、地理信息系统、精准农业和预测建模在支持盐渍化监测和因地制宜管理方面的潜力。尽管存在这些机遇，重要挑战依然存在，包括长期监测不足、区域特定数据有限、经济制约以及农民意识和制度协调方面的差距。应对这些挑战需要综合研究、有效的农业政策、改进的推广服务以及研究人员、政策制定者和农业社区之间的协作。优先采取适应当地、经济可行且环境可持续的干预措施，可增强农业韧性、修复盐渍化土壤并保护淡水资源。总体而言，将气候适应与可持续水土管理相结合，对于维持巴基斯坦农业生产力和改善长期粮食安全至关重要。","Kashmir Journal of Academic Research and Development","2026-10-20T00:00:00Z",66,{"impact":115,"substance":114,"depth":179,"authority":113,"freshness":17,"relevant":21,"comment":180},15,"综述性论文，系统梳理气候变化下巴基斯坦土壤盐渍化成因与可持续治理路径，兼具遥感与精准农业视角，对盐碱地治理议题有参考价值，但属区域性综述、非突破性成果。",[182],{"name":175,"url":172},[184,185,27,186,187],"气候变化","盐碱地治理","智慧灌溉","土壤盐渍化",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[190,195],{"code":191,"slug":192,"name":193,"path":194,"parent_code":36},"H2","soil","土壤健康与改良","\u002Ftopic\u002Fenvironment\u002Fsoil",{"code":196,"slug":197,"name":198,"path":199,"parent_code":36},"H3","irrigation","水资源与灌溉","\u002Ftopic\u002Fenvironment\u002Firrigation",{"status":39,"locked":14,"version":40,"method":41,"evidence":201},{"candidates":202,"agricultural_evidence":45},[203,208,213,220,227,231,237,243,249],{"code":32,"score":114,"supported":45,"title":204,"abstract":206,"tags":207},[205],"climate change",[184,26,133,205],[184],{"code":191,"score":179,"supported":45,"title":209,"abstract":210,"tags":212},[192],[211,192],"土壤",[185],{"code":196,"score":13,"supported":45,"title":214,"abstract":215,"tags":219},[],[216,217,197,218],"灌溉","水资源","evapotranspiration",[186],{"code":71,"score":221,"supported":45,"title":222,"abstract":223,"tags":226},7,[],[224,225],"遥感","remote sensing",[27],{"code":136,"score":20,"supported":45,"title":228,"abstract":229,"tags":230},[],[139,140],[],{"code":59,"score":20,"supported":45,"title":232,"abstract":233,"tags":236},[],[234,235],"精准农业","precision agriculture",[],{"code":65,"score":20,"supported":45,"title":238,"abstract":239,"tags":242},[],[240,241],"地理信息","geographic information",[],{"code":244,"score":53,"supported":45,"title":245,"abstract":246,"tags":248},"F3",[],[247],"养分管理",[],{"code":250,"score":53,"supported":45,"title":251,"abstract":252,"tags":254},"J1",[],[253],"农业政策",[],[256,257],"巴基斯坦 土壤盐渍化","盐碱地 遥感监测","巴基斯坦土壤盐渍化-5483","10.71317\u002Fkjard.2.10.2026.883",{"doi":259,"openalex_id":261,"authors":262,"venue":175,"cited_by_count":91,"oa_url":172,"card":278,"direction":166,"ingested_from":99},"W7222999158",[263,265,267,269,271,273,276],{"name":264,"orcid":9},"Asifa Naz",{"name":266,"orcid":9},"Muhammad Abu Baker Siddiq",{"name":268,"orcid":9},"Syed Asghar Hussain Shah",{"name":270,"orcid":9},"Shahrish Nawaz",{"name":272,"orcid":9},"Muhmmad Irfan",{"name":274,"orcid":275},"Rizwana Kausar","https:\u002F\u002Forcid.org\u002F0000-0002-1339-3312",{"name":277,"orcid":9},"Muhammad Nouman Khalid",{"tldr":279,"method":280,"finding":281,"direction":166,"opportunity":282},"综述气候变化下巴基斯坦土壤盐渍化的挑战与可持续管理途径。","文献综述，整合盐渍化机制、空间分布及遥感GIS与预测模型应用。","需将气候适应与水土管理结合，优先本地化、经济可行的干预措施。","可填补长期盐渍化监测与区域数据空白，发展遥感+预测模型的精准分区治理。","2026-10-21T23:30:23.059448Z",{"id":285,"title":286,"url":287,"summary":288,"summary_zh":289,"content":9,"source_name":290,"source_url":287,"published_at":291,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":91,"score_detail":292,"sources":294,"tags":296,"primary_topic":300,"secondary_topics":305,"classification":311,"search_phrases":328,"slug":331,"view_count":91,"doi":332,"paper":333,"created_at":345},5326,"Flood Hazard and Vulnerability Assessment of Chitrakoot District, Uttar Pradesh: An Integrated Geographical, GIS and Remote Sensing Approach","https:\u002F\u002Fdoi.org\u002F10.36948\u002Fijfmr.2026.v08i05.89708","Flood is one of the most important hydro-meteorological hazards affecting human settlements, agriculture, infrastructure and regional economies. Chitrakoot district of Uttar Pradesh presents a distinctive case of hydro-climatic vulnerability because it belongs to the drought-prone Bundelkhand region but simultaneously experiences recurrent riverine and flash-flood conditions during intense monsoon rainfall. The present study assesses the spatial characteristics and determinants of flood hazard and vulnerability in Chitrakoot district using an integrated geographical, GIS and remote sensing approach. The analysis incorporates the Digital Elevation Model (DEM), drainage network, physiography, river proximity, historical flood information, satellite-based flood observations and socio-economic exposure. The district's DEM indicates a marked elevation gradient, approximately from 66 m to 451 m, with relatively higher terrain in the southern part and lower terrain towards the northern Yamuna valley. This topographic configuration facilitates rapid surface runoff from elevated southern terrain towards comparatively low-lying riverine areas. The drainage system is dominated by the Yamuna and Mandakini\u002FPaisuni systems along with Baghain, Gunta, Bardaha and smaller tributaries. The Uttar Pradesh Flood Hazard Atlas identifies 5,114 ha of flood-hazard area in Chitrakoot for 1998–2020, of which 4,129 ha (81%) falls in the very-low hazard category and 985 ha (19%) in the low-hazard category. However, the historical classification does not fully represent the potential consequences of extreme rainfall events. The August 2026 flood provides compelling evidence: the Mandakini at Chitrakoot reached a reported new high flood level of 145.60 m on 29 August 2026, approximately 2.95 m above the previous reported high level, while the water level rose by about 7.5 m within six hours. The study concludes that flood risk in Chitrakoot is spatially concentrated around river corridors, low-elevation areas, floodplains, agricultural land, settlements and tourism infrastructure. A shift from conventional relief-oriented flood management towards integrated floodplain regulation, watershed management, GIS-based risk zonation, real-time monitoring and community-based preparedness is therefore essential.","洪水是影响人类住区、农业、基础设施和区域经济的最重要的水文气象灾害之一。北方邦吉德古德（Chitrakoot）县在水文气候脆弱性方面呈现出独特案例，因为它属于易受干旱影响的本德尔坎德（Bundelkhand）地区，但同时在强季风降雨期间反复遭遇河流洪水和山洪状况。本研究采用地理学、地理信息系统（GIS）和遥感相结合的综合方法，评估吉德古德县洪水灾害与脆弱性的空间特征及其决定因素。分析纳入了数字高程模型（DEM）、河网、地貌、距河流远近、历史洪水信息、基于卫星的洪水观测以及社会经济暴露度。该县的DEM显示出明显的高程梯度，大约从66米到451米，南部地形相对较高，向北部的亚穆纳（Yamuna）河谷地势降低。这种地形格局促使地表径流从较高的南部地形快速流向相对低洼的河流区域。排水系统以亚穆纳河和曼达基尼\u002F派苏尼（Mandakini\u002FPaisuni）水系为主，另有巴盖恩（Baghain）、贡塔（Gunta）、巴尔达哈（Bardaha）及较小支流。北方邦洪水灾害图集确认，1998—2020年吉德古德县洪水灾害面积为5，114公顷，其中4，129公顷（81%）属于极低灾害类别，985公顷（19%）属于低灾害类别。然而，历史分类并不能充分反映极端降雨事件的潜在后果。2026年8月的洪水提供了有力证据：据报道，2026年8月29日吉德古德的曼达基尼河达到145.60米的新高洪水位，比此前报告的高水位高出约2.95米，而水位在六小时内上升了约7.5米。研究得出结论，吉德古德的洪水风险在空间上集中于河流廊道、低海拔地区、洪泛平原、农业用地、住区和旅游基础设施周围。因此，必须从传统的以救济为导向的洪水管理转向洪泛平原综合调控、流域管理、基于GIS的风险区划、实时监测和社区为基础的备灾。","International Journal For Multidisciplinary Research","2026-10-17T00:00:00Z",{"impact":91,"substance":91,"depth":91,"authority":91,"freshness":91,"relevant":91,"comment":293},"该研究聚焦印度北方邦的洪水灾害评估，虽涉及GIS与遥感方法，但与三农、农业信息化、智慧农业等主题无直接关联，不建议进入每日精选。",[295],{"name":290,"url":287},[297,27,298,299],"防灾减灾","洪水风险评估","GIS应用",{"code":71,"slug":301,"name":302,"path":303,"parent_code":304},"remote-sensing","遥感与农情监测","\u002Ftopic\u002Fdigital-agriculture\u002Fremote-sensing","I",[306,310],{"code":65,"slug":307,"name":308,"path":309,"parent_code":304},"gis","GIS与空间分析","\u002Ftopic\u002Fdigital-agriculture\u002Fgis",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},{"status":39,"locked":14,"version":40,"method":41,"evidence":312},{"candidates":313,"agricultural_evidence":45},[314,318,323],{"code":71,"score":179,"supported":45,"title":315,"abstract":316,"tags":317},[225],[224,225],[27],{"code":65,"score":319,"supported":45,"title":320,"abstract":321,"tags":322},14,[68],[240,68],[],{"code":32,"score":17,"supported":45,"title":324,"abstract":325,"tags":327},[],[133,326],"drought",[298,297],[329,330],"Chitrakoot 洪水风险 GIS","Yamuna 洪水脆弱性 遥感","Chitrakoot洪水风险GIS-5326","10.36948\u002Fijfmr.2026.v08i05.89708",{"doi":332,"openalex_id":334,"authors":335,"venue":290,"cited_by_count":91,"oa_url":339,"card":340,"direction":166,"ingested_from":99},"W7222885988",[336],{"name":337,"orcid":338},"Birendra Yadav","https:\u002F\u002Forcid.org\u002F0009-0007-0864-474X","https:\u002F\u002Fwww.ijfmr.com\u002Fpapers\u002F2026\u002F5\u002F89708.pdf",{"tldr":341,"method":342,"finding":343,"direction":166,"opportunity":344},"用GIS与遥感综合评估Chitrakoot区洪水灾害与脆弱性空间分布。","DEM、河网、历史洪水与卫星观测及社会经济数据叠加分析。","洪水风险集中于河谷低地、农田与居民点，历史分级低估极端降雨风险。","可结合时序遥感与水文模型，构建极端降雨情景下的农田洪涝风险动态制图与预警。","2026-10-19T23:30:24.356743Z",{"id":347,"title":348,"url":349,"summary":350,"summary_zh":9,"content":9,"source_name":351,"source_url":9,"published_at":352,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":111,"score_detail":353,"sources":356,"tags":358,"primary_topic":363,"secondary_topics":369,"classification":371,"search_phrases":393,"slug":396,"view_count":21,"doi":9,"paper":397,"created_at":406},5304,"Front. Sustain. Food Syst.:数字农业技术推广与贵州辣椒种植户极端气候适应技术采纳","https:\u002F\u002Fscienmag.com\u002Fdigital-agricultural-extension-linked-to-climate-adaptation-among-chili-farmers-in-mountainous-china","Gao H, Han H (2026) 在Frontiers in Sustainable Food Systems发表论文,以贵州辣椒种植户为研究对象,发现数字农业技术推广(DATP)对极端气候适应技术采纳呈显著正相关,通过更广泛信息渠道、信息信任和应用能力发挥作用,益处与风险预期确认起调节作用;数字信息素养较高种植户DATP效应更强(系数0.326、0.408 vs. 低素养0.084、0.133),规模化种植户效应同样更强。","Frontiers in Sustainable Food Systems(2026,Article 1914305)","2026-10-13T00:00:00Z",{"impact":130,"substance":354,"depth":114,"authority":115,"freshness":20,"relevant":21,"comment":355},21,"基于贵州辣椒种植户实证数据，揭示数字农业推广对气候适应技术采纳的调节机制，结论具体且具政策参考价值，值得入选。",[357],{"name":351,"url":349},[359,360,361,26,362],"数字农业","智慧农业","数字素养","辣椒种植",{"code":364,"slug":365,"name":366,"path":367,"parent_code":368},"B1","vegetables","蔬菜","\u002Ftopic\u002Fhorticulture\u002Fvegetables","B",[370],{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},{"status":39,"locked":14,"version":40,"method":41,"evidence":372},{"candidates":373,"agricultural_evidence":45},[374,378,382,388],{"code":59,"score":115,"supported":45,"title":375,"abstract":376,"tags":377},[359],[359],[359,360],{"code":32,"score":113,"supported":45,"title":379,"abstract":380,"tags":381},[26],[26],[26],{"code":364,"score":383,"supported":45,"title":384,"abstract":386,"tags":387},11,[385],"辣椒",[385],[],{"code":389,"score":21,"supported":14,"title":390,"abstract":391,"tags":392},"I6",[],[],[361],[394,395],"贵州 辣椒种植户 数字农业技术推广","极端气候适应 技术采纳 数字素养","贵州辣椒种植户数字农业技术推广-5304",{"doi":9,"openalex_id":9,"authors":398,"venue":9,"cited_by_count":91,"oa_url":9,"card":399,"direction":403,"ingested_from":405},[],{"tldr":400,"method":401,"finding":402,"direction":403,"opportunity":404},"研究数字农业技术推广对贵州辣椒种植户采纳极端气候适应技术的影响。","基于贵州辣椒种植户调查数据，采用回归分析检验中介与调节效应。","数字农业技术推广显著促进适应技术采纳，信息渠道、信任与应用能力起中介作用，数字素养和规模起调节作用。","数字乡村与农业信息化","可探究数字推广服务对不同作物、不同气候区农户适应行为的差异化机制与长期效果。","agent","2026-10-19T00:07:48.767992Z",{"id":408,"title":409,"url":410,"summary":411,"summary_zh":412,"content":9,"source_name":413,"source_url":410,"published_at":414,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":111,"score_detail":415,"sources":417,"tags":419,"primary_topic":423,"secondary_topics":424,"classification":425,"search_phrases":440,"slug":443,"view_count":91,"doi":444,"paper":445,"created_at":467},5172,"Forest green-up in the Pearl River Basin: trends, driving factors, and relationships with net primary productivity","https:\u002F\u002Fdoi.org\u002F10.1080\u002F17538947.2026.2738487","The spring green-up date (GUD), a critical indicator of ecosystem response to climate change, profoundly influences terrestrial productivity. However, the complex drivers of GUD remain elusive, while the contentious relationship between GUD and net primary productivity (NPP) challenges the universal validity of the hypothesis that earlier green-up enhances productivity. Using MODIS NDVI data (2000-2020), we quantified forest GUD dynamics in the Pearl River Basin and combined random forest, SHAP, and structural equation modelling to identify drivers and assess GUD-NPP relationships. GUD was advanced by approximately 5 days, with 81.8% of forestland pixels advancing and 18.2% delaying. Only 5.39% of advances showed significant trends, whereas 30.45% of delays were concentrated near croplands and developed areas. The random forest model explained 58.2% of GUD variation. Elevation, precipitation, and soil potassium and phosphorus were dominant; elevation-induced thermal gradients outweighed ambient temperature effects, with elevations above 1,200 m exhibiting markedly delayed GUD. Spatially, GUD had a positive correlation with NPP, indicating that later GUD was associated with higher forest NPP, possibly because of early-spring cold snaps and frost. Temporally, areas with stronger GUD delays tended to show greater NPP increases. This study identified key controls on subtropical forest phenology and revealed a GUD-NPP trade-off.","春季返青期（GUD）是生态系统响应气候变化的关键指标，深刻影响陆地生产力。然而，GUD的复杂驱动机制仍不明确，且GUD与净初级生产力（NPP）之间存在争议性关系，挑战了“提前返青提高生产力”这一假说的普适性。本研究利用MODIS NDVI数据（2000—2020年），量化了珠江流域森林GUD动态，并结合随机森林、SHAP和结构方程模型识别驱动因子并评估GUD-NPP关系。GUD整体提前约5天，其中81.8%的林地像元提前、18.2%推迟。仅5.39%的提前像元呈显著趋势，而30.45%的推迟像元集中在农田和建成区附近。随机森林模型解释了58.2%的GUD变异。海拔、降水以及土壤钾和磷为主导因子；海拔引起的热梯度效应超过环境温度的影响，海拔1200 m以上区域GUD显著推迟。空间上，GUD与NPP呈正相关，表明GUD越晚森林NPP越高，这可能与早春寒潮和霜冻有关。时间上，GUD推迟越强的区域往往表现为NPP增加越大。本研究识别了亚热带森林物候的关键控制因子，揭示了GUD-NPP之间的权衡关系。","International Journal of Digital Earth","2026-10-15T00:00:00Z",{"impact":113,"substance":18,"depth":114,"authority":319,"freshness":17,"relevant":21,"comment":416},"基于MODIS长时序数据的区域森林物候研究，方法组合新颖、结论有增量，但属区域基础研究，产业与政策影响有限，可作专业补充而非每日精选头条。",[418],{"name":413,"url":410},[184,27,420,421,422],"植被生产力","森林物候","珠江流域",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":426},{"candidates":427,"agricultural_evidence":45},[428,432,436],{"code":32,"score":221,"supported":45,"title":429,"abstract":430,"tags":431},[],[184,205],[184],{"code":191,"score":20,"supported":45,"title":433,"abstract":434,"tags":435},[],[211,192],[],{"code":71,"score":21,"supported":14,"title":437,"abstract":438,"tags":439},[],[],[27],[441,442],"珠江流域 森林 返青期","MODIS NDVI 植被生产力","珠江流域森林返青期-5172","10.1080\u002F17538947.2026.2738487",{"doi":444,"openalex_id":446,"authors":447,"venue":413,"cited_by_count":91,"oa_url":461,"card":462,"direction":166,"ingested_from":99},"W7221897424",[448,451,453,455,457,459],{"name":449,"orcid":450},"Shijie Yang","https:\u002F\u002Forcid.org\u002F0009-0001-7573-5509",{"name":452,"orcid":9},"Zhaoju Zheng",{"name":454,"orcid":9},"Xueming Zhao",{"name":456,"orcid":9},"Zhipeng Zhang",{"name":458,"orcid":9},"Xiaohui Cui",{"name":460,"orcid":9},"Yuan Zeng","https:\u002F\u002Fwww.tandfonline.com\u002Fdoi\u002Fpdf\u002F10.1080\u002F17538947.2026.2738487?needAccess=true",{"tldr":463,"method":464,"finding":465,"direction":166,"opportunity":466},"基于MODIS NDVI量化珠江流域森林返青期动态，并解析其驱动因子及与NPP的关系。","MODIS NDVI（2000-2020）、随机森林、SHAP与结构方程模型。","返青期整体提前约5天，但延迟区NPP更高，揭示返青期与NPP的权衡关系。","可探究早春寒潮霜冻对返青-NPP权衡的调控机制，并拓展至其他亚热带流域验证普适性。","2026-10-17T23:30:29.750744Z",{"id":469,"title":470,"url":471,"summary":472,"summary_zh":473,"content":9,"source_name":474,"source_url":471,"published_at":414,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":475,"score_detail":476,"sources":479,"tags":481,"primary_topic":485,"secondary_topics":486,"classification":487,"search_phrases":508,"slug":511,"view_count":21,"doi":512,"paper":513,"created_at":526},5087,"Method for ten-day assessment of the contribution of agrometeorological conditions to expected winter grain crop productivity based on satellite and ground-based information","https:\u002F\u002Fdoi.org\u002F10.37162\u002F2618-9631-2026-3-167-183","The paper presents a developed and tested method for 10-day assessment of the contribution of agrometeorological factors to winter grain crop productivity. The method is based on an integrated analysis of satellite spectral indices and ground-based meteorological data for the North Caucasus, Volga and Central Black Earth regions. Satellite data from MODIS (Terra satellite) and VIIRS (SUOMI NPP satellite) radiometers were used to calculate the NDVI, VCI, and VCNI vegetation indices. Ground-based information includes meteorological and agrometeorological indicators reflecting temperature and humidity conditions. The algorithm and software modules developed within the study allow for automated tracking of 10-day changes in agrometeorological conditions and quantitative ranking of factors based on their contribution to the expected winter grain crop yield, providing an information basis for informed planning of agricultural measures.","本文提出并验证了一种用于每旬评估农业气象因素对冬粮作物生产力贡献的方法。该方法基于对北高加索、伏尔加河沿岸和中央黑土区卫星光谱指数与地面气象数据的综合分析。利用MODIS（Terra卫星）和VIIRS（SUOMI NPP卫星）辐射计的卫星数据计算NDVI、VCI和VCNI植被指数。地面信息包括反映温湿状况的气象和农业气象指标。研究开发的算法和软件模块能够自动跟踪农业气象条件的每旬变化，并根据各因素对预期冬粮作物产量的贡献进行定量排序，为农业措施的合理规划提供信息依据。","Hydrometeorological research and forecasting",70,{"impact":113,"substance":477,"depth":19,"authority":115,"freshness":17,"relevant":21,"comment":478},20,"方法新颖、数据扎实的区域性遥感估产研究，对农业信息化有参考价值，但属细分领域学术成果，公共影响有限。",[480],{"name":474,"url":471},[360,482,27,483,484],"农业气象","冬小麦","作物估产",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":488},{"candidates":489,"agricultural_evidence":45},[490,495,499,504],{"code":32,"score":491,"supported":45,"title":492,"abstract":493,"tags":494},4,[],[482],[482],{"code":71,"score":143,"supported":14,"title":496,"abstract":497,"tags":498},[],[],[484,27],{"code":500,"score":21,"supported":14,"title":501,"abstract":502,"tags":503},"A2",[],[],[483],{"code":59,"score":21,"supported":14,"title":505,"abstract":506,"tags":507},[],[],[360],[509,510],"MODIS VIIRS 冬小麦 遥感估产","农业气象 冬谷类作物 产量评估","MODISVIIRS冬小麦遥感估产-5087","10.37162\u002F2618-9631-2026-3-167-183",{"doi":512,"openalex_id":514,"authors":515,"venue":474,"cited_by_count":91,"oa_url":471,"card":521,"direction":166,"ingested_from":99},"W7221991562",[516,519],{"name":517,"orcid":518},"A. D. Kleshchenko","https:\u002F\u002Forcid.org\u002F0000-0002-4200-6668",{"name":520,"orcid":9},"O. V. Savitskaya",{"tldr":522,"method":523,"finding":524,"direction":166,"opportunity":525},"提出一种基于卫星与地面数据每十天评估农业气象因子对冬粮作物产量贡献的方法。","用MODIS和VIIRS计算NDVI、VCI、VCNI，结合气象与农业气象指标做","可自动追踪十天农业气象变化并量化排序各因子对预期产量的贡献。","可扩展至多作物多区域，融合机器学习提升因子贡献动态预测精度。","2026-10-16T23:30:26.817010Z"]