[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-5009":3,"related-5009":89},{"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":24,"tags":26,"primary_topic":9,"secondary_topics":32,"classification":33,"search_phrases":63,"slug":66,"view_count":22,"doi":67,"paper":68,"created_at":88},5009,"Integrated assessment of meteorological drought impacts on terrestrial water storage and vegetation dynamics in East Africa","https:\u002F\u002Fdoi.org\u002F10.1002\u002Frvr2.70072","Abstract Water is essential for life, and effective hydrological management is crucial for economic stability and quality of life. Poor water resource governance can lead to scarcity, displacement, or even fatal consequences. Hydrological conditions in East Africa are influenced by drivers such as demographic expansion, industrialization, droughts, and vegetation dynamics. This study explores how total water storage in the region responds to drought intensity and vegetation variability. To analyze drought conditions, the study employs CHIRPS satellite‐derived precipitation data (1982–2019) and calculates the 1‐ and 3‐month Standardized Precipitation Index (SPI) (2000–2019). Vegetation trends are assessed using MODIS‐derived Normalized Difference Vegetation Index (NDVI) over this same period. Variations in total water storage (2002–2019) are examined using Gravity Recovery and Climate Experiment (GRACE) and GRACE‐FO datasets. Results indicate increased drought severity from 2000 to 2005, followed by a decline until 2019. In 2002, approximately 7.6 × 10 5 km 2 of land was affected by drought, reducing to 4.2 × 10 5 km 2 by 2019. Concurrently, vegetation cover expanded from 1.73 × 10 6 km 2 (2002) to 2.06 × 10 6 km 2 (2019). GRACE‐derived terrestrial water storage anomalies exhibited substantial temporal variability throughout the study period, with prolonged storage deficits during major drought episodes and pronounced recovery during wetter climatic conditions. The observed TWSA patterns showed strong correspondence with variations in precipitation and vegetation dynamics across East Africa. Statistical analysis reveals a pronounced inverse relationship linking SPI and terrestrial water storage anomalies (TWSAs) ( r = −0.998) and a strong positive correlation between NDVI and TWSA ( r = +0.985). These statistical relationships demonstrate the coordinated response of terrestrial water storage and vegetation dynamics to regional precipitation variability. The findings highlight the imperative for sustainable land and water governance frameworks to counteract drought effects and strengthen hydrological resilience in East Africa.","摘要 水是生命之源，有效的水文管理对经济稳定和生活质量至关重要。水资源治理不善可能导致水资源短缺、人口流离失所，甚至造成致命后果。东非的水文状况受到人口扩张、工业化、干旱和植被动态等驱动因素的影响。本研究探讨了该地区总储水量如何响应干旱强度和植被变异性。为分析干旱状况，本研究采用CHIRPS卫星降水数据（1982—2019年），并计算了1个月和3个月尺度的标准化降水指数（SPI）（2000—2019年）。植被趋势则通过同期MODIS衍生的归一化植被指数（NDVI）进行评估。总储水量变化（2002—2019年）利用重力恢复与气候实验（GRACE）及其后续任务GRACE-FO数据集进行考察。结果表明，2000年至2005年干旱严重程度增加，随后至2019年呈下降趋势。2002年约有7.6 × 10⁵ km²的土地受干旱影响，到2019年减少至4.2 × 10⁵ km²。与此同时，植被覆盖面积从1.73 × 10⁶ km²（2002年）扩展至2.06 × 10⁶ km²（2019年）。GRACE衍生的陆地水储量异常在整个研究期内表现出显著的时间变异性，在重大干旱事件期间出现持续的水储量亏缺，而在较湿润的气候条件下则呈现明显的恢复。观测到的陆地水储量异常（TWSA）模式与东非降水及植被动态的变化高度一致。统计分析揭示了标准化降水指数与陆地水储量异常之间显著的负相关关系（r = −0.998），以及归一化植被指数与陆地水储量异常之间强烈的正相关关系（r = +0.985）。这些统计关系表明，陆地水储量与植被动态对区域降水变率具有协同响应。研究结果凸显了建立可持续土地和水治理框架的紧迫性，以抵消干旱影响并增强东非的水文韧性。",null,"River","2026-10-13T00:00:00Z","论文",10,false,71,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},12,21,17,13,8,1,"基于GRACE、CHIRPS与MODIS多源遥感的东非干旱—水储量—植被耦合研究，方法扎实、数据跨度长，对农业水资源韧性治理有参考价值，但属区域基础研究，公共影响有限。",[25],{"name":10,"url":6},[27,28,29,30,31],"水资源管理","遥感监测","植被动态","干旱预警","东非农业",[],{"status":34,"locked":14,"version":35,"method":36,"evidence":37},"needs_review","2026-10-22.2","rules",{"candidates":38,"agricultural_evidence":14,"reason":62},[39,48,56],{"code":40,"score":41,"supported":42,"title":43,"abstract":45,"tags":47},"H7",15,true,[44],"drought",[46,44],"干旱",[30],{"code":49,"score":50,"supported":42,"title":51,"abstract":52,"tags":55},"H3",7,[],[53,54],"水资源","water resource",[27],{"code":57,"score":58,"supported":14,"title":59,"abstract":60,"tags":61},"I3",2,[],[],[29,28],"农业相关性需要复核",[64,65],"GRACE 陆地水储量 东非","SPI NDVI 干旱监测","GRACE陆地水储量东非-5009","10.1002\u002Frvr2.70072",{"doi":67,"openalex_id":69,"authors":70,"venue":10,"cited_by_count":79,"oa_url":80,"card":81,"direction":85,"ingested_from":87},"W7221658579",[71,74,77],{"name":72,"orcid":73},"Mekuanint Eresho Wollebo","https:\u002F\u002Forcid.org\u002F0009-0009-5502-4775",{"name":75,"orcid":76},"Yohannes Mehari Andiye","https:\u002F\u002Forcid.org\u002F0009-0007-7153-5474",{"name":78,"orcid":9},"Tulu Besha Bedada",0,"https:\u002F\u002Fonlinelibrary.wiley.com\u002Fdoi\u002Fpdfdirect\u002F10.1002\u002Frvr2.70072",{"tldr":82,"method":83,"finding":84,"direction":85,"opportunity":86},"评估东非气象干旱对陆地水储量和植被动态的影响。","用CHIRPS、MODIS NDVI、GRACE\u002FGRACE-FO数据及SPI指","干旱面积减少、植被扩张，SPI与TWSA强负相关，NDVI与TWSA强正相关。","农业遥感与作物表型","可结合多源遥感与机器学习，构建干旱-水储量-植被耦合的早期预警模型。","openalex","2026-10-15T23:30:30.980660Z",{"total":90,"page":22,"page_size":90,"items":91},6,[92,183,246,316,395,468],{"id":93,"title":94,"url":95,"summary":96,"summary_zh":97,"content":9,"source_name":98,"source_url":95,"published_at":99,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":100,"score_detail":101,"sources":105,"tags":107,"primary_topic":110,"secondary_topics":115,"classification":125,"search_phrases":159,"slug":162,"view_count":22,"doi":163,"paper":164,"created_at":182},4030,"Enhancing Drought Monitoring Using Integrated Remote Sensing and Ground-Based Indices","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jastp.2026.106987","ABSTRACT Accurate and timely drought monitoring is essential for sustainable water resource management, particularly in semi-arid regions where meteorological observations are sparse and spatially heterogeneous. This study presents an integrated evaluation of drought conditions by applying established individual and composite drought indices within a unified multi-source framework that combines ground-based meteorological data with satellite-derived datasets, including MODIS land surface products and GPM\u002FTRMM precipitation estimates, and is implemented on the Google Earth Engine platform. A set of drought indicators representing vegetation condition, thermal stress, precipitation deficit, and soil moisture variability was analyzed alongside five composite indices to provide a multi-dimensional assessment of drought dynamics. The analysis was conducted across monthly, seasonal, and annual timescales for Tehran, Iran, over the period 2000–2022. In addition, trend significance was assessed using the Mann–Kendall test and Sen’s slope estimator to quantify long-term changes in drought behavior. The results indicate that composite indices provide a more coherent representation of drought evolution and are more effective in capturing the interaction among key climatic drivers. In particular, the analysis reveals a transition from precipitation-driven droughts (e.g., 2008 and 2016) to increasingly temperature-driven drought conditions (e.g., 2022), associated with elevated potential evapotranspiration and thermal stress. This highlights the growing importance of atmospheric evaporative demand in intensifying drought severity under warming conditions. From an applied perspective, the proposed framework supports drought early warning, spatial risk assessment, and informed decision-making in water resource management and agricultural planning. However, the reliability of the results depends on data quality, spatial resolution, and the representation of key drought drivers and should therefore be interpreted with these limitations in mind. The study demonstrates that the integrated application of multi-source data and multi-scale drought indices provides a robust basis for understanding and monitoring drought dynamics in semi-arid urban environments.","准确的干旱监测对于可持续水资源管理至关重要，尤其是在气象观测稀疏且空间异质性强的半干旱地区。本研究在统一的多源框架内，应用已有的单一和综合干旱指数对干旱状况进行综合评估，该框架将地面气象数据与卫星遥感数据集（包括MODIS地表产品和GPM\u002FTRMM降水估算）相结合，并在Google Earth Engine平台上实现。研究分析了表征植被状况、热胁迫、降水亏缺和土壤湿度变率的干旱指标集以及五种综合指数，以对干旱动态进行多维评估。分析在月、季和年尺度上针对伊朗德黑兰2000—2022年期间开展。此外，采用Mann–Kendall检验和Sen斜率估计器评估趋势显著性，以量化干旱行为的长期变化。结果表明，综合指数能更一致地表征干旱演变，且更能有效捕捉关键气候驱动因子之间的相互作用。具体而言，分析揭示了从降水驱动型干旱（如2008年和2016年）向日益增强的温度驱动型干旱（如2022年）的转变，这与潜在蒸散和热胁迫升高有关。这凸显了在变暖条件下大气蒸发需求在加剧干旱严重程度方面日益重要的作用。从应用角度看，所提出的框架可支持干旱预警、空间风险评估以及水资源管理和农业规划中的知情决策。然而，结果的可靠性取决于数据质量、空间分辨率以及关键干旱驱动因子的表征，因此在解读时应考虑这些局限性。本研究表明，多源数据与多尺度干旱指数的综合应用为理解和监测半干旱城市环境中的干旱动态提供了稳健基础。","Journal of Atmospheric and Solar-Terrestrial Physics","2026-10-01T00:00:00Z",74,{"impact":102,"substance":18,"depth":103,"authority":20,"freshness":21,"relevant":22,"comment":104},14,18,"多源遥感与地面指数融合的干旱监测框架，方法扎实、结论有新意，但属区域案例研究，产业影响有限。",[106],{"name":98,"url":95},[108,27,28,109,30],"农业气象","Google Earth Engine",{"code":40,"slug":111,"name":112,"path":113,"parent_code":114},"climate","气候适应与防灾减灾","\u002Ftopic\u002Fenvironment\u002Fclimate","H",[116,121],{"code":57,"slug":117,"name":118,"path":119,"parent_code":120},"remote-sensing","遥感与农情监测","\u002Ftopic\u002Fdigital-agriculture\u002Fremote-sensing","I",{"code":49,"slug":122,"name":123,"path":124,"parent_code":114},"irrigation","水资源与灌溉","\u002Ftopic\u002Fenvironment\u002Firrigation",{"status":126,"locked":14,"version":35,"method":36,"evidence":127},"classified",{"candidates":128,"agricultural_evidence":42},[129,134,140,145,152],{"code":40,"score":130,"supported":42,"title":131,"abstract":132,"tags":133},16,[44],[46,44],[108,30],{"code":57,"score":20,"supported":42,"title":135,"abstract":137,"tags":139},[136],"remote sensing",[138],"遥感",[109,28],{"code":49,"score":13,"supported":42,"title":141,"abstract":142,"tags":144},[],[53,54,143],"evapotranspiration",[27],{"code":146,"score":90,"supported":42,"title":147,"abstract":148,"tags":151},"H2",[],[149,150],"土壤","soil",[],{"code":153,"score":154,"supported":42,"title":155,"abstract":156,"tags":158},"J1",3,[],[157],"农业规划",[],[160,161],"MODIS GPM 干旱指数","德黑兰 干旱监测 遥感","MODISGPM干旱指数-4030","10.1016\u002Fj.jastp.2026.106987",{"doi":163,"openalex_id":165,"authors":166,"venue":98,"cited_by_count":79,"oa_url":95,"card":177,"direction":85,"ingested_from":87},"W7215092640",[167,170,172,174],{"name":168,"orcid":169},"Hadi Siasar","https:\u002F\u002Forcid.org\u002F0000-0002-9323-4345",{"name":171,"orcid":9},"Mahboube Ebrahimi",{"name":173,"orcid":9},"Mehdi Bahrami",{"name":175,"orcid":176},"Hossein Hamidifar","https:\u002F\u002Forcid.org\u002F0000-0001-9054-0120",{"tldr":178,"method":179,"finding":180,"direction":85,"opportunity":181},"整合遥感与地面数据，在GEE上评估德黑兰2000–2022年多尺度干旱动态。","MODIS、GPM\u002FTRMM与气象数据，构建5种复合干旱指数，Mann-Kend","复合指数更一致；干旱由降水驱动转向温度驱动，蒸散需求加剧干旱。","可引入机器学习融合多源指数，提升半干旱区干旱预警的时空精度与驱动归因。","2026-10-02T23:30:24.756475Z",{"id":184,"title":185,"url":186,"summary":187,"summary_zh":188,"content":9,"source_name":189,"source_url":186,"published_at":190,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":191,"sources":193,"tags":195,"primary_topic":197,"secondary_topics":198,"classification":200,"search_phrases":216,"slug":219,"view_count":58,"doi":220,"paper":221,"created_at":245},2674,"Bi-decadal drought assessment in Northwestern Algeria: Integrating meteorological and remote sensing indices","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs00704-026-06526-y","Abstract Drought is an escalating hazard in arid and semi‑arid regions with significant implications for agriculture, ecosystems, and water resources. This study presents a 2003–2023 integrated assessment of meteorological and vegetation-based drought across northwest Algeria, using the Climate Hazards group Infrared Precipitation with Stations (CHIRPS) dataset and Moderate Resolution Imaging Spectroradiometer (MODIS) remotely‑sensed products. Meteorological drought was quantified with the Standardized Precipitation Index (SPI) approximated using standardized precipitation anomalies, at 3‑, 6‑, and 12‑month timescales, whereas vegetation and thermal stress were assessed with MODIS‑derived Vegetation Condition Index (VCI), Temperature Condition Index (TCI), and Vegetation Health Index (VHI). Temporal trends were evaluated using the Mann–Kendall test and Sen’s slope estimator, and relationships between precipitation and vegetation were examined with Pearson correlation. We identified recurrent drought episodes in 2007–2009, 2011–2012, and a pronounced dry phase from 2020–2023. Mann–Kendall results indicated widespread drying across all SPI timescales, with 56% of the study area showing significant negative trends at SPI‑3 (mean Sen’s slope = − 0.10 yr⁻ 1 ). Vegetation indices mirrored these changes, with VHI showing substantially more degraded area than improvement (4.89% vs 0.51% of the domain), while VCI and TCI responses were spatially heterogeneous. The correlation analysis showed moderate but statistically significant relationships between SPI and VHI at the short-term scale (SPI-3 vs. VHI, r = 0.567, p = 0.007), followed by SPI-6 ( r = 0.509, p = 0.019), indicating that vegetation response is more strongly associated with short- to medium-term precipitation variability. These results demonstrate the value of combining meteorological and satellite vegetation indices for regional drought monitoring and early warning, and underscore an ongoing shift toward increased aridity with implications for water management and agricultural adaptation.","摘要 干旱是干旱和半干旱地区日益加剧的灾害，对农业、生态系统和水资源具有重大影响。本研究利用气候灾害组红外降水与站点数据（CHIRPS）数据集和中分辨率成像光谱仪（MODIS）遥感产品，对阿尔及利亚西北部2003—2023年气象干旱和基于植被的干旱进行了综合评估。气象干旱采用标准化降水指数（SPI）量化，该指数通过标准化降水距平在3个月、6个月和12个月时间尺度上近似计算；植被和热胁迫则通过MODIS衍生的植被状态指数（VCI）、温度状态指数（TCI）和植被健康指数（VHI）进行评估。采用Mann–Kendall检验和Sen斜率估计器评估时间趋势，并使用Pearson相关分析检验降水与植被之间的关系。我们识别出2007—2009年、2011—2012年的反复干旱事件，以及2020—2023年显著的干旱阶段。Mann–Kendall结果表明，所有SPI时间尺度上均呈现大范围干旱化趋势，研究区56%的面积在SPI-3上表现出显著负趋势（Sen斜率均值 = −0.10 yr⁻¹）。植被指数反映了这些变化，VHI显示退化面积远大于改善面积（分别占研究区的4.89%和0.51%），而VCI和TCI的响应在空间上具有异质性。相关分析表明，SPI与VHI在短期尺度上存在中等但统计显著的关系（SPI-3与VHI，r = 0.567，p = 0.007），其次为SPI-6（r = 0.509，p = 0.019），表明植被响应与短期至中期降水变率的关系更为密切。这些结果证明了结合气象指标和卫星植被指数进行区域干旱监测与预警的价值，并凸显了干旱化持续加剧的趋势及其对水资源管理和农业适应的影响。","Theoretical and Applied Climatology","2026-09-15T00:00:00Z",{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":192},"基于CHIRPS与MODIS的阿尔及利亚西北部20年干旱综合评估，方法整合气象与遥感指标，结论对区域干旱监测与农业适应有参考价值，但属境外区域研究，国内产业影响有限。",[194],{"name":189,"url":186},[108,27,28,196,30],"植被指数",{"code":40,"slug":111,"name":112,"path":113,"parent_code":114},[199],{"code":57,"slug":117,"name":118,"path":119,"parent_code":120},{"status":126,"locked":14,"version":35,"method":36,"evidence":201},{"candidates":202,"agricultural_evidence":42},[203,207,211],{"code":40,"score":130,"supported":42,"title":204,"abstract":205,"tags":206},[44],[46,44],[108,30],{"code":57,"score":20,"supported":42,"title":208,"abstract":209,"tags":210},[136],[138],[196,28],{"code":49,"score":212,"supported":42,"title":213,"abstract":214,"tags":215},4,[],[53],[27],[217,218],"水资源管理 农业气象 干旱预警 植被指数","水资源管理 农业气象","水资源管理农业气象干旱预警植被指数-2674","10.1007\u002Fs00704-026-06526-y",{"doi":220,"openalex_id":222,"authors":223,"venue":189,"cited_by_count":79,"oa_url":186,"card":240,"direction":85,"ingested_from":87},"W7213346236",[224,227,230,233,235,238],{"name":225,"orcid":226},"Ramzi Benhizia","https:\u002F\u002Forcid.org\u002F0000-0002-8967-2051",{"name":228,"orcid":229},"Brahim Abdelkebir","https:\u002F\u002Forcid.org\u002F0000-0002-8761-8537",{"name":231,"orcid":232},"Behnam Ata","https:\u002F\u002Forcid.org\u002F0000-0002-9690-7269",{"name":234,"orcid":9},"Mukovhe Vele Singo",{"name":236,"orcid":237},"Kwanele Phinzi","https:\u002F\u002Forcid.org\u002F0000-0003-1865-7011",{"name":239,"orcid":9},"György Szabó",{"tldr":241,"method":242,"finding":243,"direction":85,"opportunity":244},"整合气象与遥感指数评估阿尔及利亚西北部2003–2023年干旱演变。","CHIRPS降水与MODIS植被指数，SPI、VCI、TCI、VHI，Mann-","全区普遍变干，SPI-3显著负趋势占56%，VHI退化面积远大于改善，短期降水与植被相关性最强。","可引入机器学习融合多源遥感与气象数据，构建区域干旱预警与作物适应性决策模型。","2026-09-16T23:30:30.795285Z",{"id":247,"title":248,"url":249,"summary":250,"summary_zh":251,"content":9,"source_name":252,"source_url":249,"published_at":253,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":79,"score_detail":254,"sources":256,"tags":258,"primary_topic":9,"secondary_topics":260,"classification":261,"search_phrases":285,"slug":288,"view_count":79,"doi":289,"paper":290,"created_at":315},5189,"Remote Multispectral Sensing for Spatial and Temporal Analysis and Location Selection of a Reservoir on the Zhabay River, Kazakhstan","https:\u002F\u002Fdoi.org\u002F10.3390\u002Fsu182010542","This study aims to develop a methodology for identifying potential reservoir sites along the Zhylandy River, a right-bank tributary of the Zhabay River, using multispectral remote sensing data. The relevance of this work stems from the need to adapt Kazakhstan’s water resource management system to changing climate conditions and to ensure sustainable development of the region. To reconstruct the dynamics of water-surface extent across the entire river basin, a time series of Landsat-8, and Landsat-9 Level-2 scenes acquired between 2020 and 2026 was processed. The resulting water occurrence frequency maps were integrated with digital elevation data from the Shuttle Radar Topography Mission (SRTM) within a multi-criteria GIS analysis to assess site suitability. The key criteria included a stable water occurrence frequency, suitable valley geometry (slope \u003C 5°), and minimal conflicts with existing land use. Three promising sites were identified: Site 105 near the village of Novoselovka (potential storage volume ~75.6 million m3), Site 104 in the upper reaches of the Zhylandy River (~30.01 million m3), and Site 1A near Khlebnoye (~52.4 million m3). Validation against high-resolution imagery showed an overall accuracy of 87%, producer’s accuracy of 85.2%, user’s accuracy of 89.0%, Kappa of 0.74, and F1-score of 0.87. The proposed methodology provides a scientifically grounded basis for sustainable water resource management and flood risk reduction in data-scarce basins, contributing to the achievement of sustainable development goals under climate change.","本研究旨在开发一种方法，利用多光谱遥感数据在扎拜河（Zhabay River）右岸支流日兰迪河（Zhylandy River）沿线识别潜在水库坝址。本工作的现实意义源于哈萨克斯坦水资源管理系统适应气候变化条件并保障区域可持续发展的需要。为重建全流域水面范围的动态变化，研究处理了2020年至2026年间获取的Landsat-8和Landsat-9 Level-2影像时间序列。将所得水体出现频率图与航天飞机雷达地形测绘任务（SRTM）的数字高程数据在多准则GIS分析中集成，以评估坝址适宜性。关键准则包括稳定的水体出现频率、适宜的河谷几何形态（坡度\u003C5°）以及与现有土地利用的最小冲突。研究识别出三个有前景的坝址：新谢洛夫卡村（Novoselovka）附近的105号坝址（潜在库容约7560万m³）、日兰迪河上游的104号坝址（约3001万m³）以及赫列布诺耶（Khlebnoye）附近的1A号坝址（约5240万m³）。基于高分辨率影像的验证结果显示，总体精度为87%，生产者精度为85.2%，用户精度为89.0%，Kappa系数为0.74，F1分数为0.87。所提出的方法为数据稀缺流域的可持续水资源管理和洪水风险降低提供了科学依据，有助于在气候变化背景下实现可持续发展目标。","Sustainability","2026-10-16T00:00:00Z",{"impact":79,"substance":79,"depth":79,"authority":79,"freshness":79,"relevant":79,"comment":255},"该研究聚焦哈萨克斯坦河流水库选址，虽用多光谱遥感方法，但与三农、农业信息化、数字乡村无直接关联，不达相关性门槛。",[257],{"name":252,"url":249},[27,28,259],"多光谱遥感",[],{"status":34,"locked":14,"version":35,"method":36,"evidence":262},{"candidates":263,"agricultural_evidence":14,"reason":62},[264,269,273,279],{"code":57,"score":103,"supported":42,"title":265,"abstract":267,"tags":268},[266],"multispectral",[138,136,266],[28],{"code":49,"score":50,"supported":42,"title":270,"abstract":271,"tags":272},[],[53,54],[27],{"code":40,"score":90,"supported":42,"title":274,"abstract":275,"tags":278},[],[276,277],"气候变化","climate change",[],{"code":280,"score":154,"supported":42,"title":281,"abstract":282,"tags":284},"I4",[],[283],"GIS",[],[286,287],"Zhabay River 水库选址","Landsat 多光谱 遥感","ZhabayRiver水库选址-5189","10.3390\u002Fsu182010542",{"doi":289,"openalex_id":291,"authors":292,"venue":252,"cited_by_count":79,"oa_url":249,"card":309,"direction":314,"ingested_from":87},"W7222647076",[293,296,299,302,304,306],{"name":294,"orcid":295},"Baurzhan Yessenzholov","https:\u002F\u002Forcid.org\u002F0000-0002-8851-2224",{"name":297,"orcid":298},"Ivan Plachinta","https:\u002F\u002Forcid.org\u002F0000-0002-5735-1288",{"name":300,"orcid":301},"Anuarbek A. Kakabayev","https:\u002F\u002Forcid.org\u002F0000-0002-3825-0625",{"name":303,"orcid":9},"Gulzhan Dankina",{"name":305,"orcid":9},"Suraganov Miras",{"name":307,"orcid":308},"Gulmira Kyzdarbekova","https:\u002F\u002Forcid.org\u002F0000-0001-9982-9027",{"tldr":310,"method":311,"finding":312,"direction":85,"opportunity":313},"用多光谱遥感与GIS多准则分析在哈萨克斯坦Zhabay河选定三处水库坝址。","Landsat-8\u002F9时序水体频率图叠加SRTM高程，做多准则GIS选址并高分辨","识别出三处候选坝址，总精度87%、Kappa 0.74，可支撑缺水流域水资源管理。","可将该水体频率+地形选址框架迁移到缺资料农业流域的灌溉蓄水与旱涝风险规划。","数字乡村与农业信息化","2026-10-17T23:30:39.503932Z",{"id":317,"title":318,"url":319,"summary":320,"summary_zh":321,"content":9,"source_name":322,"source_url":319,"published_at":323,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":324,"score_detail":325,"sources":327,"tags":329,"primary_topic":9,"secondary_topics":332,"classification":333,"search_phrases":361,"slug":364,"view_count":58,"doi":365,"paper":366,"created_at":394},4902,"Delineation of groundwater potential zones in Chalan Beel (inland wetland) for sustainable ecosystem in Lower Atrai River Basin NW Bangladesh","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs44288-026-00768-z","Groundwater plays a critical role in sustaining the ecological integrity and water security of the Chalan Beel, the largest inland wetland (5097 km2) in the Lower Atrai River Basin of northwestern Bangladesh. This study delineates groundwater potential zones (GWPZs) using an integrated Geographic Information System (GIS), Remote Sensing (RS), and Analytical Hierarchy Process (AHP) approach. Seventeen hydrogeological, topographic, climatic, and environmental thematic layers, including rainfall, soil type, soil permeability, groundwater level, aquifer depth, land use\u002Fland cover, geomorphology, drainage density, NDVI, and NDWI, were analyzed to evaluate groundwater recharge and storage potential. The AHP results indicate that rainfall (20%), soil type (16%), and soil permeability (13%) are the most influential factors controlling groundwater occurrence and recharge. The generated GWPZ map classified the study area into three categories: very high (65 km2, 1%), medium (3933 km2, 77%), and low (1099 km2, 22%) potential zones. Temporal NDVI analysis (1990–2024) revealed substantial changes in vegetation and moisture conditions, with the moderate NDVI class increasing from 45 to 67%, indicating improved vegetation cover and its strong association with groundwater recharge potential. The identified high- and moderate-potential zones provide important information for groundwater development, irrigation planning, and ecosystem conservation. The study offers a scientific basis for sustainable groundwater-dependent ecosystem (SGDE) management and supports informed decision-making for water-resource planning under increasing climatic variability and anthropogenic pressures in northwestern Bangladesh.","地下水在维持孟加拉国西北部阿特拉伊河下游流域最大内陆湿地——查兰比尔湿地（5097平方公里）的生态完整性和水安全方面发挥着关键作用。本研究采用地理信息系统（GIS）、遥感（RS）和层次分析法（AHP）相结合的综合方法，圈定地下水潜力区（GWPZs）。通过分析十七个水文地质、地形、气候和环境专题图层，包括降雨量、土壤类型、土壤渗透性、地下水位、含水层深度、土地利用\u002F土地覆盖、地貌、河网密度、归一化植被指数（NDVI）和归一化水体指数（NDWI），评估地下水补给和储存潜力。层次分析法结果表明，降雨量（20%）、土壤类型（16%）和土壤渗透性（13%）是控制地下水赋存和补给的最主要因素。生成的地下水潜力区图将研究区划分为三类：极高潜力区（65平方公里，1%）、中等潜力区（3933平方公里，77%）和低潜力区（1099平方公里，22%）。时序NDVI分析（1990—2024年）揭示了植被和湿度条件的显著变化，中等NDVI等级从45%增至67%，表明植被覆盖改善及其与地下水补给潜力的密切关联。所识别的高潜力和中等潜力区为地下水开发、灌溉规划和生态系统保护提供了重要信息。本研究为可持续地下水依赖型生态系统（SGDE）管理提供了科学依据，并为孟加拉国西北部在气候变率加剧和人为压力增大背景下的水资源规划提供了知情决策支持。","Discover Geoscience","2026-10-12T00:00:00Z",67,{"impact":21,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":326},"该研究运用GIS、遥感和AHP方法评估孟加拉国湿地地下水潜力，方法新颖、数据详实，对农业水资源管理和生态保护有参考价值，但地域性较强，影响范围有限。",[328],{"name":322,"url":319},[27,28,283,330,331],"地下水潜力","湿地生态",[],{"status":34,"locked":14,"version":35,"method":36,"evidence":334},{"candidates":335,"agricultural_evidence":14,"reason":62},[336,342,348,352,356],{"code":49,"score":337,"supported":42,"title":338,"abstract":339,"tags":341},11,[],[340,53,122],"灌溉",[330,27],{"code":280,"score":13,"supported":42,"title":343,"abstract":344,"tags":347},[],[345,283,346],"地理信息","geographic information",[283],{"code":57,"score":50,"supported":42,"title":349,"abstract":350,"tags":351},[],[138,136],[28],{"code":146,"score":90,"supported":42,"title":353,"abstract":354,"tags":355},[],[149,150],[],{"code":357,"score":22,"supported":14,"title":358,"abstract":359,"tags":360},"H6",[],[],[331],[362,363],"Chalan Beel 湿地 地下水","孟加拉国 地下水潜力 遥感","ChalanBeel湿地地下水-4902","10.1007\u002Fs44288-026-00768-z",{"doi":365,"openalex_id":367,"authors":368,"venue":322,"cited_by_count":79,"oa_url":388,"card":389,"direction":85,"ingested_from":87},"W7221572372",[369,371,374,377,380,382,384,386],{"name":370,"orcid":9},"Wahedul Alam",{"name":372,"orcid":373},"Iftekharul Islam","https:\u002F\u002Forcid.org\u002F0000-0002-8025-5729",{"name":375,"orcid":376},"Chowdhury Sarwar Jahan","https:\u002F\u002Forcid.org\u002F0009-0008-1316-4684",{"name":378,"orcid":379},"Md. Nahid Hassan","https:\u002F\u002Forcid.org\u002F0009-0000-9210-383X",{"name":381,"orcid":9},"Mostofa Kamal",{"name":383,"orcid":9},"Fayed Islam Tishad",{"name":385,"orcid":9},"Quamrul Hasan Mazumder",{"name":387,"orcid":9},"Md. Golam Mostafa","https:\u002F\u002Flink.springer.com\u002Fcontent\u002Fpdf\u002F10.1007\u002Fs44288-026-00768-z.pdf",{"tldr":390,"method":391,"finding":392,"direction":85,"opportunity":393},"用GIS、遥感和AHP划分孟加拉Chalan Beel湿地地下水潜力区，支持可持续生态系统管理。","集成GIS、RS与AHP，分析17个水文地质、地形、气候和环境图层。","降雨、土壤类型和渗透性最关键；高潜力区仅1%，中潜力区占77%。","可结合时序遥感与机器学习提升GWPZ动态制图精度，并耦合灌溉与生态需水决策。","2026-10-14T23:30:30.477606Z",{"id":396,"title":397,"url":398,"summary":399,"summary_zh":400,"content":9,"source_name":401,"source_url":398,"published_at":402,"category":12,"cover_url":9,"hotness":13,"is_selected":42,"score":403,"score_detail":404,"sources":409,"tags":411,"primary_topic":9,"secondary_topics":414,"classification":415,"search_phrases":430,"slug":433,"view_count":58,"doi":434,"paper":435,"created_at":467},4590,"Earlier green-up exacerbates northern vegetation sensitivity to flash drought","https:\u002F\u002Fdoi.org\u002F10.1038\u002Fs41467-026-78296-0","Flash drought–induced relative reduction in vegetation activity and canopy functioning, referred to as vegetation sensitivity, is a crucial measure of drought impacts. While climatic factors influencing vegetation sensitivity are well recognized, the role of phenological shifts remains poorly understood. Using multiple satellite-derived vegetation proxies (NDVI, LAI, SIF, and VOD) during 2001–2021, we show that earlier green-up dates (GUD) exacerbate vegetation sensitivity to flash droughts across 61.2–84.1% of the Northern Hemisphere (>23.5°N). Earlier GUDs enhance pre-drought vegetation growth, especially during the early growing season. Such amplified vegetation growth exacerbates sensitivity by accelerating soil moisture depletion and respiration cost, outweighing the benefit of increased subsequent net carbon assimilation. The contribution of GUD to vegetation sensitivity is comparable to that of major climatic factors. Ignoring phenological changes may lead to underestimation of long-term trends in vegetation sensitivity. These findings underscore the necessity of incorporating the interactions between phenology and flash droughts into projections of ecosystem resistance and resilience. Flash droughts can rapidly reduce vegetation growth, but the role of spring phenology is unclear. The authors show that earlier green-up increases vegetation sensitivity to flash drought across much of the Northern Hemisphere ecosystems.","闪旱导致的植被活动与冠层功能相对下降，即植被敏感性，是衡量干旱影响的关键指标。尽管影响植被敏感性的气候因素已被广泛认识，但物候偏移的作用仍知之甚少。利用2001—2021年多颗卫星衍生的植被代用指标（NDVI、LAI、SIF和VOD），我们发现，在北半球（>23.5°N）61.2%—84.1%的区域，提前的返青期（GUD）加剧了植被对闪旱的敏感性。较早的GUD增强了干旱前的植被生长，尤其是在生长季早期。这种放大的植被生长通过加速土壤水分消耗和呼吸成本加剧了敏感性，其效应超过了随后净碳同化增加带来的益处。GUD对植被敏感性的贡献与主要气候因子相当。忽视物候变化可能导致对植被敏感性长期趋势的低估。这些发现强调了将物候与闪旱之间的相互作用纳入生态系统抵抗力和恢复力预估的必要性。闪旱可迅速降低植被生长，但春季物候的作用尚不清楚。作者表明，在北半球大部分生态系统中，较早的返青增加了植被对闪旱的敏感性。","Nature Communications","2026-10-08T00:00:00Z",86,{"impact":405,"substance":406,"depth":407,"authority":41,"freshness":50,"relevant":22,"comment":408},22,23,19,"基于多源卫星遥感揭示春季提前返青加剧北半球植被对骤发干旱的敏感性，方法扎实、结论新颖，对农业干旱监测预警有参考价值。",[410],{"name":401,"url":398},[276,28,412,30,413],"植被物候","生态遥感",[],{"status":34,"locked":14,"version":35,"method":36,"evidence":416},{"candidates":417,"agricultural_evidence":14,"reason":62},[418,422,426],{"code":40,"score":130,"supported":42,"title":419,"abstract":420,"tags":421},[44],[46,44],[30,276],{"code":146,"score":90,"supported":42,"title":423,"abstract":424,"tags":425},[],[149,150],[],{"code":57,"score":58,"supported":14,"title":427,"abstract":428,"tags":429},[],[],[413,28],[431,432],"北半球 植被 干旱 敏感性","NDVI LAI SIF VOD 遥感","北半球植被干旱敏感性-4590","10.1038\u002Fs41467-026-78296-0",{"doi":434,"openalex_id":436,"authors":437,"venue":401,"cited_by_count":79,"oa_url":461,"card":462,"direction":85,"ingested_from":87},"W7115172292",[438,441,444,447,450,453,455,458],{"name":439,"orcid":440},"Wenrui Bai","https:\u002F\u002Forcid.org\u002F0009-0009-4885-3348",{"name":442,"orcid":443},"Quansheng Ge","https:\u002F\u002Forcid.org\u002F0000-0001-8712-8565",{"name":445,"orcid":446},"Constantin M. Zohner","https:\u002F\u002Forcid.org\u002F0000-0002-8302-4854",{"name":448,"orcid":449},"Jun Wang","https:\u002F\u002Forcid.org\u002F0009-0005-5869-832X",{"name":451,"orcid":452},"Shaozhi Lin","https:\u002F\u002Forcid.org\u002F0000-0002-8975-281X",{"name":454,"orcid":9},"Yani Liang",{"name":456,"orcid":457},"Yongshuo H. Fu","https:\u002F\u002Forcid.org\u002F0000-0002-9761-5292",{"name":459,"orcid":460},"Huanjiong Wang","https:\u002F\u002Forcid.org\u002F0000-0002-2325-0120","https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fs41467-026-78296-0_reference.pdf",{"tldr":463,"method":464,"finding":465,"direction":85,"opportunity":466},"利用多源卫星数据揭示北半球早绿期加剧植被对骤旱的敏感性。","2001–2021年NDVI、LAI、SIF、VOD等卫星植被指标分析。","早绿期通过加速土壤水分消耗和呼吸成本，放大植被对骤旱的敏感性。","可探究不同生态系统和气候区中物候-骤旱交互的差异，并纳入陆面模型改进干旱预警。","2026-10-10T23:30:28.234091Z",{"id":469,"title":470,"url":471,"summary":472,"summary_zh":473,"content":9,"source_name":474,"source_url":471,"published_at":475,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":476,"score_detail":477,"sources":479,"tags":481,"primary_topic":485,"secondary_topics":490,"classification":492,"search_phrases":520,"slug":523,"view_count":22,"doi":524,"paper":525,"created_at":543},4527,"Socio‐Economic Impact of Sustainable Development of Water Resources in the Semi‐Arid Regions of Village Raleras, Maharashtra: A Case Study Using Machine Learning Techniques","https:\u002F\u002Fdoi.org\u002F10.1111\u002F1477-8947.70100","ABSTRACT From a socio‐economic perspective, it is of interest to find out whether sustainable water resources can truly sustain rural livelihoods. Based on historical research, it is known that an improvement on resilient economic indicators such as ground water is often correlated with socio‐economic improvements and other aspects of rural livelihoods. The extent of factors affecting livelihood sustenance and improvement in the village of Raleras, Maharashtra, aids in creating a definite understanding of the facets correlating with groundwater restoration. Subsistence channels, arising as an outcome of the created impoundment structures, are tested for their impact on income gains and livelihood improvement. Examination on collected opinion was carried out to provide insights into the ‘before’ and ‘after’ (2015–2023) conditions. A five‐capitals framework has been employed for the interpretation of these results, along with a multivariate analysis to predict a causal framework for the improvement of livelihoods in agrarian economies through creation of check dams and watershed management. Time series study shows that there is greater variance in the NDVI progressively from 2021 to 2023 with values ranging from 0.25 to 0.50 in 2015, to 0.50–0.75 by 2021. Further increase in green patches in 2023 indicates enhanced vegetation health especially in the northern regions. Alternately, NDWI values elaborate initial severe water stress (−0.25 to 0.00) with progressive improvements in localized areas. The spatial variation map shows that eventually there is a notable improvement with more land supporting shrubbery along with more water bodies. The prominent increase in vegetation particularly in the later years can be attributed to water management initiatives undertaken in Raleras. The distributions of the annual average revenue from agricultural operations in 2015 (M = 146,907, SD = 95445.8) and 2023 (M = 706860.5, SD = 655748.3) showed a statistically significant improvement [ t (214) = 13.06, p \u003C 0.001]. The low p ‐value of 0.001205 ( p \u003C 0.05) of the educational facilities utilised indicates a statistically significant result, proving the association between educational quality and improved water facilities. All of the variables under evaluation, including the respondents' vehicle type, landholding type, and house type, have large and positive chi‐squared values, suggesting that the ‘before’ and ‘after’ distributions for each of these variables differ. Principal Component Analysis is used to summarise correlated livelihood indicators and reveals that income growth and livelihood improvement is multi‐dimensional. Multiple pathways to income change are identified through Partial Least Squares Regression, including agriculture and market‐linked channels. A Random Forest Regression Model is utilised to assess the relative importance of livelihood channels and baseline characteristics. Results indicate that improvement in irrigation access, crop diversification, housing quality, livestock ownership and female literacy are strongly associated with higher income gains. Hence, it may be said that the groundwater recharge as a result of construction of check dams must have improved agricultural activity or agricultural output in a material manner, and accordingly all capitals for Raleras have improved.","从社会经济视角来看，探究可持续水资源能否真正维持农村生计具有重要意义。基于历史研究可知，地下水等韧性经济指标的改善往往与社会经济进步及农村生计的其他方面相关联。马哈拉施特拉邦拉莱拉斯村影响生计维持与改善的因素程度，有助于明确理解与地下水恢复相关的各个维度。作为所建蓄水设施产物的生计渠道，其对面收入增长和生计改善的影响得到了检验。对收集到的意见进行了考察，以深入了解“之前”和“之后”（2015—2023年）的状况。研究采用了五资本框架来解读这些结果，并结合多变量分析，预测通过修建拦水坝和流域管理来改善农业经济生计的因果框架。时间序列研究表明，从2021年到2023年，NDVI的变异性逐渐增大，2015年数值范围为0.25至0.50，到2021年升至0.50至0.75。2023年绿色斑块进一步增加，表明植被健康状况改善，尤其是在北部地区。另一方面，NDWI值显示初期存在严重的水分胁迫（−0.25至0.00），后在局部地区逐步改善。空间变异图显示，最终出现了显著改善，更多土地能够支持灌木生长，同时水体也有所增加。植被的显著增加，尤其是在后期，可归因于拉莱拉斯村所实施的水资源管理举措。2015年（M = 146,907，SD = 95445.8）和2023年（M = 706860.5，SD = 655748.3）农业经营年均收入的分布显示出统计学上显著的改善[t(214) = 13.06，p \u003C 0.001]。所利用教育设施的p值为0.001205（p \u003C 0.05），表明结果具有统计学显著性，证明了教育质量与改善的供水设施之间的关联。所有受评估变量，包括受访者的车辆类型、土地持有类型和房屋类型，均具有较大且正向的卡方值，表明这些变量各自的“之前”和“之后”分布存在差异。","Natural Resources Forum","2026-10-07T00:00:00Z",73,{"impact":17,"substance":405,"depth":103,"authority":20,"freshness":21,"relevant":22,"comment":478},"以机器学习与遥感数据量化印度半干旱村庄水资源可持续性对生计的影响，方法扎实、结论具体，但属境外案例研究，对国内三农信息化仅有方法借鉴价值。",[480],{"name":474,"url":471},[482,483,27,28,484],"乡村振兴","机器学习","灌溉农业",{"code":486,"slug":487,"name":488,"path":489,"parent_code":120},"I2","agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai",[491],{"code":49,"slug":122,"name":123,"path":124,"parent_code":114},{"status":126,"locked":14,"version":35,"method":36,"evidence":493},{"candidates":494,"agricultural_evidence":42},[495,501,505,511,516],{"code":486,"score":496,"supported":42,"title":497,"abstract":499,"tags":500},9,[498],"machine learning",[],[483],{"code":49,"score":21,"supported":42,"title":502,"abstract":503,"tags":504},[],[53,122],[27,484],{"code":506,"score":154,"supported":42,"title":507,"abstract":508,"tags":510},"C",[],[509],"livestock",[],{"code":512,"score":22,"supported":14,"title":513,"abstract":514,"tags":515},"G",[],[],[482],{"code":57,"score":22,"supported":14,"title":517,"abstract":518,"tags":519},[],[],[28],[521,522],"Raleras 马哈拉施特拉 水资源","check dam 地下水 生计","Raleras马哈拉施特拉水资源-4527","10.1111\u002F1477-8947.70100",{"doi":524,"openalex_id":526,"authors":527,"venue":474,"cited_by_count":79,"oa_url":9,"card":537,"direction":542,"ingested_from":87},"W7220922038",[528,531,533,535],{"name":529,"orcid":530},"Papiya Deb","https:\u002F\u002Forcid.org\u002F0000-0002-6554-5111",{"name":532,"orcid":9},"Roopsha Deb",{"name":534,"orcid":9},"Udaysinh Bhosale",{"name":536,"orcid":9},"Vemula Sai Vikas",{"tldr":538,"method":539,"finding":540,"direction":314,"opportunity":541},"用机器学习评估印度半干旱村庄水资源可持续开发对农村生计的社会经济影响。","NDVI\u002FNDWI遥感、五资本框架、多元分析与卡方检验，2015–2023数据。","水管理举措显著提升植被覆盖与农业收入，教育设施改善与水资源改善显著相关。","可结合遥感时序与农户调查，量化水利工程对生计的因果效应并推广至其他半干旱区。","农业人工智能与决策模型","2026-10-09T23:30:50.079298Z"]