[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-4597":3,"related-4597":130},{"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":79,"doi":80,"paper":81,"created_at":129},4597,"Evaluating OpenET evapotranspiration estimates in California vineyards: Insights from the GRAPEX experiment","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.agrformet.2026.111505","California agriculture faces escalating water-management challenges from drought and heat while adapting to groundwater-sustainability policies. Accurate field-scale evapotranspiration (ET) values are essential for irrigation decisions and water conservation. OpenET integrates six satellite-based ET models in Google Earth Engine to provide near–real-time actual ET (ET a ) at 30 m and daily resolution. We evaluated OpenET against eddy-covariance ET a from 11 wine-grape vineyards monitored by the Grape Remote sensing Atmospheric Profile & Evapotranspiration eXperiment (GRAPEX). We compared individual-model and ensemble ET a to tower ET a and conducted site-focused analyses to diagnose performance under key microclimate and management conditions. The OpenET ensemble ET a value closely matched tower ET a (daily R 2 = 0.82; MAE = 0.63 mm d -1 ; monthly R 2 = 0.89; MAE = 14.8 mm month -1 ) with negligible bias and generally outperformed individual models. Performance improved with temporal aggregation, consistent with reduced sensitivity to Landsat overpass timing and reference ET-based interpolation at the daily timestep. Skill was highest at monthly and seasonal scales, while daily errors increased during advective conditions and short-lived irrigation deficits, and tower energy-balance closure influenced inferred bias at advection-prone sites. Controlled experiments showed that thermal-based models detected imposed vine water-stress responses directionally (but were dampened in the ensemble) and that winter cover crops, and vine-row orientation produced consistent ET a shifts that propagated into thermal-based OpenET values. These results quantify when OpenET is most reliable for precision viticulture and provide guidance for using satellite ET a to support irrigation scheduling and water accounting in practice.","加利福尼亚农业在适应地下水可持续性政策的同时，面临着干旱和高温带来的日益加剧的水资源管理挑战。准确的田块尺度蒸散发（ET）值对于灌溉决策和节水至关重要。OpenET在Google Earth Engine中集成了六个基于卫星的ET模型，以30米空间分辨率和日时间分辨率提供近实时的实际蒸散发（ETa）。我们利用葡萄遥感大气廓线与蒸散发实验（GRAPEX）监测的11个酿酒葡萄园的通量观测ETa对OpenET进行了评估。我们将单个模型和集合ETa与塔站ETa进行了比较，并开展了站点聚焦分析，以诊断其在关键微气候和管理条件下的表现。OpenET集合ETa值与塔站ETa高度吻合（日尺度R²=0.82；MAE=0.63 mm d⁻¹；月尺度R²=0.89；MAE=14.8 mm month⁻¹），偏差可忽略不计，且总体优于单个模型。性能随时间聚合而提升，这与日时间步长下对Landsat过境时间和基于参考ET插值的敏感性降低相一致。在月和季节尺度上表现最佳，而日尺度误差在平流条件和短期灌溉亏缺期间增大，塔站能量平衡闭合影响了易发生平流站点推断偏差。控制实验表明，基于热红外的模型能够方向性地检测到施加的葡萄藤水分胁迫响应（但在集合中被削弱），且冬季覆盖作物和葡萄行向产生了持续的ETa变化，并传递至基于热红外的OpenET值中。这些结果量化了OpenET在精准葡萄栽培中最可靠的时机，并为在实践中利用卫星ETa支持灌溉调度和水核算提供了指导。",null,"Agricultural and Forest Meteorology","2026-10-08T00:00:00Z","论文",10,false,80,{"impact":17,"substance":18,"depth":17,"authority":19,"freshness":20,"relevant":21,"comment":22},18,22,14,8,1,"基于GRAPEX试验11个葡萄园涡度相关数据系统评估OpenET蒸散发产品精度，为卫星遥感支撑精准灌溉与农业水核算提供实证依据，方法扎实、结论可靠，对智慧农业水资源管理有参考价值。",[24],{"name":10,"url":6},[26,27,28,29,30],"农业水资源","遥感","葡萄园","蒸散发","智慧灌溉",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},"H3","irrigation","水资源与灌溉","\u002Ftopic\u002Fenvironment\u002Firrigation","H",[],{"status":39,"locked":14,"version":40,"method":41,"evidence":42},"classified","2026-10-22.2","rules",{"candidates":43,"agricultural_evidence":46},[44,53,61,67],{"code":32,"score":45,"supported":46,"title":47,"abstract":49,"tags":52},20,true,[48],"evapotranspiration",[50,51,29,33,48],"灌溉","水资源",[26,30,29],{"code":54,"score":55,"supported":46,"title":56,"abstract":57,"tags":60},"B2",7,[],[58,59],"葡萄","grape",[28],{"code":62,"score":55,"supported":46,"title":63,"abstract":64,"tags":66},"I3",[],[27,65],"remote sensing",[27],{"code":68,"score":69,"supported":46,"title":70,"abstract":71,"tags":74},"H7",6,[],[72,73],"干旱","drought",[],[76,77],"OpenET 蒸散发 葡萄园","GRAPEX 加州 葡萄园","OpenET蒸散发葡萄园-4597",0,"10.1016\u002Fj.agrformet.2026.111505",{"doi":80,"openalex_id":82,"authors":83,"venue":10,"cited_by_count":79,"oa_url":6,"card":122,"direction":126,"ingested_from":128},"W7221033125",[84,87,89,91,93,95,97,99,101,103,105,108,110,112,114,116,118,120],{"name":85,"orcid":86},"Kyle  R. Knipper","https:\u002F\u002Forcid.org\u002F0000-0003-0889-8129",{"name":88,"orcid":9},"N. Bambach",{"name":90,"orcid":9},"M. Anderson",{"name":92,"orcid":9},"W. Kustas",{"name":94,"orcid":9},"A. J. McElrone",{"name":96,"orcid":9},"M. Swintek",{"name":98,"orcid":9},"F. Melton",{"name":100,"orcid":9},"D. Salazar-Martinez",{"name":102,"orcid":9},"L. Hipps",{"name":104,"orcid":9},"J. Alfieri",{"name":106,"orcid":107},"John H. Prueger","https:\u002F\u002Forcid.org\u002F0000-0002-7768-5760",{"name":109,"orcid":9},"L. McKee",{"name":111,"orcid":9},"S. Castro",{"name":113,"orcid":9},"P. Tolentino",{"name":115,"orcid":9},"I. Wright",{"name":117,"orcid":9},"A. Gal",{"name":119,"orcid":9},"N. Dokoozlian",{"name":121,"orcid":9},"M.M. Alsina",{"tldr":123,"method":124,"finding":125,"direction":126,"opportunity":127},"评估OpenET在加州葡萄园的蒸散发估算精度，并与涡度协方差观测对比。","利用GRAPEX实验11个葡萄园的涡度协方差数据，对比六种卫星模型及集合的ET。","OpenET集合在月\u002F季尺度精度高，日尺度在平流和灌溉亏缺时误差增大。","农业遥感与作物表型","可研究平流条件下卫星ET校正方法，或融合地面微气象数据提升日尺度精度。","openalex","2026-10-10T23:30:31.071040Z",{"total":69,"page":21,"page_size":69,"items":131},[132,218,298,386,461,504],{"id":133,"title":134,"url":135,"summary":136,"summary_zh":137,"content":9,"source_name":138,"source_url":135,"published_at":139,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":140,"score_detail":141,"sources":147,"tags":149,"primary_topic":152,"secondary_topics":153,"classification":154,"search_phrases":197,"slug":200,"view_count":79,"doi":201,"paper":202,"created_at":217},4683,"Linking NDVI to METRIC‐Based Stress‐Adjusted Crop Coefficients ( K c_adj ) for Operational Evapotranspiration Estimation Under Semiarid Conditions","https:\u002F\u002Fdoi.org\u002F10.1002\u002Fird.70246","ABSTRACT Accurate estimation of evapotranspiration (ET) is essential for sustainable water management, particularly in arid and semiarid regions. This study aimed to establish relationships between the normalised difference vegetation index (NDVI) derived from satellite imagery and stress‐adjusted crop coefficients ( K c_adj ) obtained using the METRIC (mapping ET at high resolution with internalised calibration) model and to develop efficient models for rapid ET estimation. The study was conducted during the 2023 and 2024 growing seasons in Ergani (Diyarbakır, Türkiye). The water stress coefficient ( K s ) was derived from METRIC‐based ET and used to obtain K c_adj values. Regression analysis was performed to quantify the relationships between NDVI and K c_adj , and NDVI‐based K c ( K c_NDVI ) values were developed. The results indicated strong relationships between NDVI and K c_adj for maize and tobacco ( R 2 = 0.90–0.93 and 0.89–0.95, respectively), whereas the resulting NDVI‐based ET estimates showed strong internal consistency with the METRIC‐informed stress‐adjusted estimates. Conversely, weaker relationships were observed for potato and onion ( R 2 = 0.52–0.58 and 0.0003–0.56, respectively), likely driven by planting–harvest timing heterogeneity, incomplete satellite coverage and the influence of stress factors. Overall, the approach is most suitable for crops showing strong and stable NDVI– K c_adj relationships under adequate temporal data coverage conditions.","精确估算蒸散发（ET）对于可持续水资源管理至关重要，尤其是在干旱和半干旱地区。本研究旨在建立由卫星影像获取的归一化差异植被指数（NDVI）与利用METRIC（高分辨率内部校准蒸散发制图）模型得到的胁迫调整作物系数（K_c_adj）之间的关系，并开发用于快速估算蒸散发的有效模型。研究于2023年和2024年生长季在埃尔加尼（土耳其迪亚巴克尔）开展。水分胁迫系数（K_s）由基于METRIC的蒸散发推导得出，并用于获取K_c_adj值。通过回归分析量化NDVI与K_c_adj之间的关系，并建立了基于NDVI的作物系数（K_c_NDVI）值。结果表明，玉米和烟草的NDVI与K_c_adj之间存在强相关关系（R²分别为0.90–0.93和0.89–0.95），而由此得到的基于NDVI的蒸散发估算值与METRIC-informed胁迫调整估算值之间表现出较强的内部一致性。相反，马铃薯和洋葱的关系较弱（R²分别为0.52–0.58和0.0003–0.56），这可能由种植—收获时间异质性、卫星覆盖不完整以及胁迫因素的影响所致。总体而言，该方法最适用于在充足时间数据覆盖条件下表现出强且稳定NDVI–K_c_adj关系的作物。","Irrigation and Drainage","2026-10-09T00:00:00Z",71,{"impact":142,"substance":143,"depth":144,"authority":145,"freshness":20,"relevant":21,"comment":146},12,21,17,13,"基于METRIC模型与NDVI建立胁迫调整作物系数关系，为半干旱区精准灌溉提供新方法，但属细分领域研究，公共影响有限。",[148],{"name":138,"url":135},[150,27,29,30,151],"精准农业","作物系数",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":155},{"candidates":156,"agricultural_evidence":46},[157,162,169,176,183,188,193],{"code":32,"score":158,"supported":46,"title":159,"abstract":160,"tags":161},19,[48],[51,29,48],[30,29],{"code":163,"score":69,"supported":46,"title":164,"abstract":165,"tags":168},"A3",[],[166,167],"玉米","maize",[],{"code":170,"score":69,"supported":46,"title":171,"abstract":172,"tags":175},"A5",[],[173,174],"马铃薯","potato",[],{"code":177,"score":69,"supported":46,"title":178,"abstract":179,"tags":182},"A6",[],[180,181],"烟草","tobacco",[],{"code":68,"score":184,"supported":46,"title":185,"abstract":186,"tags":187},3,[],[72],[],{"code":189,"score":21,"supported":14,"title":190,"abstract":191,"tags":192},"I1",[],[],[150],{"code":62,"score":21,"supported":14,"title":194,"abstract":195,"tags":196},[],[],[27],[198,199],"METRIC 模型 NDVI 蒸散发","Ergani Diyarbakır 作物系数","METRIC模型NDVI蒸散发-4683","10.1002\u002Fird.70246",{"doi":201,"openalex_id":203,"authors":204,"venue":138,"cited_by_count":79,"oa_url":211,"card":212,"direction":126,"ingested_from":128},"W7221125586",[205,208],{"name":206,"orcid":207},"Kıvanc Hayri Doganay","https:\u002F\u002Forcid.org\u002F0000-0002-6977-4982",{"name":209,"orcid":210},"Bekir S. KARATAŞ","https:\u002F\u002Forcid.org\u002F0000-0002-1424-8870","https:\u002F\u002Fonlinelibrary.wiley.com\u002Fdoi\u002Fpdfdirect\u002F10.1002\u002Fird.70246",{"tldr":213,"method":214,"finding":215,"direction":126,"opportunity":216},"建立NDVI与METRIC模型应力调整作物系数Kc_adj的关系，实现半干旱区蒸散发快速估算。","2023-2024年土耳其半干旱区玉米、烟草等作物，用METRIC模型和NDVI","玉米和烟草的NDVI-Kc_adj关系强（R²达0.90-0.95），马铃薯和洋葱较弱。","可探索多源遥感与时间序列数据融合，提升异质性作物NDVI-Kc_adj关系的稳健性。","2026-10-11T23:30:31.633015Z",{"id":219,"title":220,"url":221,"summary":222,"summary_zh":223,"content":9,"source_name":224,"source_url":221,"published_at":225,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":226,"score_detail":227,"sources":231,"tags":233,"primary_topic":237,"secondary_topics":238,"classification":249,"search_phrases":281,"slug":284,"view_count":79,"doi":285,"paper":286,"created_at":297},5552,"INTEGRATING IoT, REMOTE SENSING, AND ARTIFICIAL INTELLIGENCE FOR SMART IRRIGATION: A REVIEW OF ARCHITECTURES, METHODS, AND CHALLENGES","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23531020","This research paper reviews the integration of Internet of Things (IoT), remote sensing, and Artificial Intelligence (AI) in smart irrigation systems. It discusses system architectures, intelligent irrigation techniques, automated water management, key challenges, and future research opportunities to improve water-use efficiency and promote sustainable agriculture.","本文综述了物联网（Internet of Things, IoT）、遥感与人工智能（Artificial Intelligence, AI）在智能灌溉系统中的融合应用，探讨了系统架构、智能灌溉技术、自动化水资源管理、关键挑战及未来研究方向，以提升用水效率并促进可持续农业发展。","Zenodo (CERN European Organization for Nuclear Research)","2026-10-21T00:00:00Z",75,{"impact":17,"substance":45,"depth":228,"authority":142,"freshness":229,"relevant":21,"comment":230},16,9,"系统综述物联网、遥感与AI融合的智能灌溉架构与方法，属智慧农业细分领域有实质增量的国际综述，值得入选。",[232],{"name":224,"url":221},[234,235,27,30,236],"农业人工智能","农业物联网","节水农业",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[239,245],{"code":240,"slug":241,"name":242,"path":243,"parent_code":244},"I5","agricultural-iot","物联网传感与边缘计算","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-iot","I",{"code":62,"slug":246,"name":247,"path":248,"parent_code":244},"remote-sensing","遥感与农情监测","\u002Ftopic\u002Fdigital-agriculture\u002Fremote-sensing",{"status":39,"locked":14,"version":40,"method":41,"evidence":250},{"candidates":251,"agricultural_evidence":46},[252,256,263,268,274],{"code":32,"score":158,"supported":46,"title":253,"abstract":254,"tags":255},[33],[50,51,33],[30,236],{"code":240,"score":17,"supported":46,"title":257,"abstract":259,"tags":262},[258],"IoT",[260,261,258],"物联网","internet of things",[235],{"code":62,"score":264,"supported":46,"title":265,"abstract":266,"tags":267},15,[65],[27,65],[27],{"code":269,"score":142,"supported":46,"title":270,"abstract":272,"tags":273},"I2",[271],"artificial intelligence",[271],[234],{"code":275,"score":69,"supported":46,"title":276,"abstract":277,"tags":280},"H8",[],[278,279],"可持续农业","sustainable agriculture",[],[282,283],"IoT 遥感 AI 智能灌溉","农业人工智能 农业物联网 智慧灌溉 节水农业","IoT遥感AI智能灌溉-5552","10.5281\u002Fzenodo.23531020",{"doi":285,"openalex_id":287,"authors":288,"venue":224,"cited_by_count":79,"oa_url":221,"card":291,"direction":295,"ingested_from":128},"W7223090389",[289],{"name":290,"orcid":9},"Patil",{"tldr":292,"method":293,"finding":294,"direction":295,"opportunity":296},"综述物联网、遥感与人工智能融合的智能灌溉系统架构、方法与挑战。","文献综述，梳理IoT、遥感与AI集成的系统架构与智能灌溉技术。","融合三者可提升用水效率并推动可持续农业，但仍面临关键挑战。","智慧农业 \u002F 农业物联网","可针对多源数据融合的实时灌溉决策模型与边缘部署开展实证研究。","2026-10-22T11:20:18.028252Z",{"id":299,"title":300,"url":301,"summary":302,"summary_zh":303,"content":9,"source_name":304,"source_url":301,"published_at":305,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":306,"score_detail":307,"sources":309,"tags":311,"primary_topic":315,"secondary_topics":316,"classification":323,"search_phrases":350,"slug":353,"view_count":354,"doi":355,"paper":356,"created_at":385},4085,"Seasonal Snow Water Resources and Spring Runoff Harvesting Potential in the North Kazakhstan Region: An Integrated Remote Sensing and GIS-Based Multi-Criteria Assessment","https:\u002F\u002Fdoi.org\u002F10.3390\u002Fearth7050163","Seasonal snow is a critical water resource in Northern Kazakhstan, where spring snowmelt dominates surface runoff and agricultural water supply. However, traditional rainwater harvesting frameworks often neglect snow water equivalent (SWE), limiting their applicability in cold, snow-dominated steppe environments. This study develops an integrated remote sensing and GIS-based approach to identify potential sites for spring runoff harvesting. Using Sentinel-2 imagery, snow cover fraction (SCF) was derived and combined with a digital elevation model (DEM) to estimate snow depth through a quadratic regression model, validated against in situ data from 23 meteorological stations. Snow water equivalent was then calculated by incorporating field-measured snow density. Alongside SWE, six additional parameters—slope, drainage density, land use\u002Fland cover (LULC), and soil texture (sand, silt, clay)—were integrated within an Analytical Hierarchy Process (AHP) multi-criteria decision analysis. Results show that SWE, drainage density, and LULC collectively contributed 75% of the weight in site suitability, underscoring their dominant role in snowmelt-driven hydrology. The final suitability map indicates that 28.03% of the region falls into the “Very High” class, concentrated in central and northwestern districts. Developing just 30% of these potential zones could yield approximately 4.2 × 108 m3 of usable meltwater, supporting up to 105,000 ha under full irrigation or 280,000 ha under deficit irrigation. The study demonstrates that integrating high-resolution SWE with MCDA provides a scalable framework for enhancing agricultural resilience, mitigating floods, and strengthening water security in cold, semi-arid landscapes.","季节性积雪是哈萨克斯坦北部的重要水资源，春季融雪主导着地表径流和农业供水。然而，传统的雨水收集框架往往忽视雪水当量（SWE），限制了其在寒冷、以积雪为主的草原环境中的适用性。本研究开发了一种集成遥感和GIS的方法，用于识别春季径流收集的潜在场址。利用Sentinel-2影像提取积雪覆盖率（SCF），并结合数字高程模型（DEM）通过二次回归模型估算雪深，利用23个气象站的实地数据进行验证。随后，结合实地测量的雪密度计算雪水当量。除SWE外，还将坡度、河网密度、土地利用\u002F土地覆盖（LULC）以及土壤质地（砂、粉砂、黏土）等六个附加参数纳入层次分析法（AHP）多准则决策分析。结果表明，SWE、河网密度和LULC在场地适宜性评价中合计贡献了75%的权重，凸显了它们在融雪驱动水文中的主导作用。最终适宜性图显示，该区域28.03%的面积属于“极高”等级，集中在中部和西北部地区。仅开发这些潜在区域的30%，即可产生约4.2 × 10⁸ m³的可用融水，可支持多达105,000公顷的充分灌溉或280,000公顷的亏缺灌溉。本研究表明，将高分辨率SWE与多准则决策分析相结合，为增强农业韧性、减轻洪水和加强寒冷半干旱地区的水安全提供了一个可扩展的框架。","Earth","2026-10-02T00:00:00Z",77,{"impact":228,"substance":143,"depth":17,"authority":145,"freshness":229,"relevant":21,"comment":308},"该研究将遥感与GIS多准则评估结合，量化了北哈萨克斯坦融雪水资源与灌溉潜力，方法新颖、数据扎实，对寒区农业水资源管理有参考价值，但地域性较强，属细分领域进展。",[310],{"name":304,"url":301},[26,312,27,313,314],"哈萨克斯坦","GIS","融雪灌溉",{"code":62,"slug":246,"name":247,"path":248,"parent_code":244},[317,322],{"code":318,"slug":319,"name":320,"path":321,"parent_code":244},"I4","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":324},{"candidates":325,"agricultural_evidence":46},[326,330,334,339,346],{"code":62,"score":264,"supported":46,"title":327,"abstract":328,"tags":329},[65],[27,65],[27],{"code":318,"score":142,"supported":46,"title":331,"abstract":332,"tags":333},[313],[313],[313],{"code":32,"score":13,"supported":46,"title":335,"abstract":336,"tags":338},[],[50,51,33,337],"water resource",[26],{"code":340,"score":69,"supported":46,"title":341,"abstract":342,"tags":345},"H2",[],[343,344],"土壤","soil",[],{"code":68,"score":184,"supported":46,"title":347,"abstract":348,"tags":349},[],[72],[],[351,352],"北哈萨克斯坦 融雪 灌溉潜力","Sentinel-2 雪水当量 遥感","北哈萨克斯坦融雪灌溉潜力-4085",5,"10.3390\u002Fearth7050163",{"doi":355,"openalex_id":357,"authors":358,"venue":304,"cited_by_count":79,"oa_url":301,"card":380,"direction":126,"ingested_from":128},"W7216430083",[359,362,365,367,369,371,374,377],{"name":360,"orcid":361},"Zhanassyl Teleubay","https:\u002F\u002Forcid.org\u002F0000-0003-4783-5489",{"name":363,"orcid":364},"Erkin Ussalinov","https:\u002F\u002Forcid.org\u002F0000-0003-1907-9532",{"name":366,"orcid":9},"Laura Ryskulbekova",{"name":368,"orcid":9},"Asset Arystanov",{"name":370,"orcid":9},"Ibragim Seitassanov",{"name":372,"orcid":373},"Улжан Онласын","https:\u002F\u002Forcid.org\u002F0000-0001-5789-5464",{"name":375,"orcid":376},"Nuray Kutymova","https:\u002F\u002Forcid.org\u002F0009-0000-7214-1708",{"name":378,"orcid":379},"Farabi Yermekov","https:\u002F\u002Forcid.org\u002F0000-0002-0290-3866",{"tldr":381,"method":382,"finding":383,"direction":126,"opportunity":384},"结合遥感与GIS评估哈萨克斯坦北部季节性雪水资源及春季径流收集潜力。","Sentinel-2与DEM估算雪深和SWE，结合AHP多准则决策分析选址。","SWE、河网密度和土地利用贡献75%权重，28%区域为极高适宜区。","可将SWE驱动的选址框架推广至其他寒旱区，并耦合气候情景与灌溉效率优化。","2026-10-03T23:30:32.427699Z",{"id":387,"title":388,"url":389,"summary":390,"summary_zh":391,"content":9,"source_name":392,"source_url":389,"published_at":393,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":394,"score_detail":395,"sources":397,"tags":399,"primary_topic":403,"secondary_topics":404,"classification":409,"search_phrases":432,"slug":435,"view_count":184,"doi":436,"paper":437,"created_at":460},3790,"Evaluation of the accuracy and response to recorded irrigation events of remote sensing and reanalysis soil moisture products in a typical irrigation district","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.agwat.2026.110822","Soil moisture (SM) plays a critical role in the land–atmosphere water cycle and agricultural water resource management. However, the applicability of prevalent SM products in typical irrigation districts remains insufficiently assessed. In this study, two in situ SM observation networks—an automatic meteorological station network (AMS) and an agro-meteorological experimental station network (AES)—were used to comprehensively evaluate the accuracy and irrigation-associated response characteristics of seven microwave and reanalysis SM products in the North China Plain. The results indicated that: (1) AES-based evaluations generally showed a higher overall correlation (R = 0.58) and smaller errors with the SM products than AMS-based evaluations (R = 0.54). However, when restricted to common observation dates, the correlation coefficients decreased while the biases were close to zero in the AES-based evaluation. (2) Significant differences were observed among the evaluated products under different monitoring objectives. The ERA5-Land reanalysis product performed best for continuous SM monitoring, while the European Space Agency Climate Change Initiative (ESA CCI) Passive product achieved the highest correlation coefficient with in situ observations (R = 0.69) and the lowest unbiased root mean square error (ubRMSE = 0.043 m 3 m −3 ) on recorded irrigation days and exhibited a comparatively pronounced positive SM response under precipitation-controlled conditions, indicating greater sensitivity to short-term irrigation-associated wetting. (3) Strict precipitation control substantially affected the interpretation of irrigation-associated responses. ERA5-Land and GLDAS-Noah showed little systematic positive change when precipitation was controlled using both station observations and model precipitation forcing, while threshold-based probability of detection (POD) varied substantially with the selected SM response threshold. These findings demonstrate that product suitability depends on the monitoring objective and that precipitation attribution and threshold sensitivity should be explicitly considered when using SM products for irrigation-related applications.","土壤水分（SM）在陆气水循环和农业水资源管理中起着至关重要的作用。然而，主流SM产品在典型灌区的适用性仍缺乏充分评估。本研究利用两套原位SM观测网络——自动气象站网络（AMS）和农业气象实验站网络（AES），综合评估了七种微波和再分析SM产品在华北平原的精度及与灌溉相关的响应特征。结果表明：（1）基于AES的评估总体上显示出比基于AMS的评估更高的整体相关性（R = 0.58）和更小的误差（R = 0.54）。然而，当限定于共同观测日期时，基于AES的评估中相关系数下降，而偏差接近于零。（2）在不同监测目标下，所评估产品之间存在显著差异。ERA5-Land再分析产品在连续SM监测中表现最佳，而欧洲空间局气候变化倡议（ESA CCI）被动产品在记录灌溉日与原位观测的相关系数最高（R = 0.69），无偏均方根误差最低（ubRMSE = 0.043 m³ m⁻³），并在降水控制条件下表现出相对明显的SM正响应，表明其对短期灌溉相关增湿具有更高的敏感性。（3）严格的降水控制显著影响了对灌溉相关响应的解释。当利用站点观测和模型降水强迫控制降水时，ERA5-Land和GLDAS-Noah几乎未表现出系统性正变化，而基于阈值的检测概率（POD）随所选SM响应阈值的变化而显著变化。这些发现表明，产品适用性取决于监测目标，且在将SM产品用于灌溉相关应用时，应明确考虑降水归因和阈值敏感性。","Agricultural Water Management","2026-09-28T00:00:00Z",74,{"impact":142,"substance":18,"depth":17,"authority":19,"freshness":20,"relevant":21,"comment":396},"基于华北平原实测网络的七种土壤水分产品评估，为灌溉监测产品选型提供实证依据，专业价值较高但属细分领域研究。",[398],{"name":392,"url":389},[26,27,400,401,402],"土壤墒情","灌溉管理","华北平原",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[405,408],{"code":340,"slug":344,"name":406,"path":407,"parent_code":36},"土壤健康与改良","\u002Ftopic\u002Fenvironment\u002Fsoil",{"code":62,"slug":246,"name":247,"path":248,"parent_code":244},{"status":39,"locked":14,"version":40,"method":41,"evidence":410},{"candidates":411,"agricultural_evidence":46},[412,416,420,425],{"code":32,"score":158,"supported":46,"title":413,"abstract":414,"tags":415},[33],[50,51,33,337],[26,401],{"code":340,"score":264,"supported":46,"title":417,"abstract":418,"tags":419},[344],[343,344],[400],{"code":62,"score":142,"supported":46,"title":421,"abstract":422,"tags":424},[65],[423],"估产",[27],{"code":68,"score":229,"supported":46,"title":426,"abstract":427,"tags":431},[],[428,429,430],"气候变化","农业气象","climate change",[],[433,434],"ESA CCI 土壤水分 灌溉","华北平原 土壤水分 遥感","ESACCI土壤水分灌溉-3790","10.1016\u002Fj.agwat.2026.110822",{"doi":436,"openalex_id":438,"authors":439,"venue":392,"cited_by_count":79,"oa_url":454,"card":455,"direction":126,"ingested_from":128},"W7214549221",[440,443,445,447,449,451],{"name":441,"orcid":442},"Rui Zhu","https:\u002F\u002Forcid.org\u002F0000-0002-6114-6412",{"name":444,"orcid":9},"Yu Li",{"name":446,"orcid":9},"Jiawei Lv",{"name":448,"orcid":9},"Lei Wang",{"name":450,"orcid":9},"Zhiqing Cheng",{"name":452,"orcid":453},"Dong Wu","https:\u002F\u002Forcid.org\u002F0000-0002-3202-255X","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS0378377426007043\u002Fpdf",{"tldr":456,"method":457,"finding":458,"direction":126,"opportunity":459},"评估七种遥感与再分析土壤湿度产品在典型灌区的精度及对灌溉事件的响应。","用自动气象站与农业气象站两套实测网络，对比七种微波\u002F再分析产品。","ESA CCI Passive对灌溉日响应最灵敏，ERA5-Land适合连续监测，降水控制影响响应判","可针对灌溉事件构建降水控制下的阈值自适应土壤湿度响应检测方法，提升灌区遥感监测可靠性。","2026-09-29T23:30:28.424080Z",{"id":462,"title":463,"url":464,"summary":465,"summary_zh":9,"content":466,"source_name":467,"source_url":9,"published_at":468,"category":469,"cover_url":9,"hotness":13,"is_selected":14,"score":470,"score_detail":471,"sources":474,"tags":476,"primary_topic":479,"secondary_topics":480,"classification":481,"search_phrases":498,"slug":501,"view_count":502,"doi":9,"paper":9,"created_at":503},3222,"深化南北科技协作 共促智慧节水农业发展——河北省水资源研究与水利技术试验推广中心一行到江苏里下河所调研交流","https:\u002F\u002Fyz.jaas.ac.cn\u002Fxww\u002Fxwzx\u002Fart\u002F2026\u002Fart_685e5e43f9554e108a96b2b38a2110e2.html","9-21 河北省水资源研究与水利技术试验推广中心（河北省灌溉中心试验站）副主任贾志军一行3人来江苏里下河地区农业科学研究所调研交流。调研组一行在资源与环境研究室主任寇祥明等陪同下，实地考察樊川基地，现场观摩智慧灌溉、虫情监测及土壤墒情在线监测等智慧农业应用场景。双方围绕农业水资源高效利用、智慧灌溉技术研发及科研基地建设等主题进行深入交流，重点围绕深化南北区域农业节水科技协作达成共识，一致认为应充分发挥各自在农业水资源利用、稻麦栽培和智慧农业等方面的科研与平台优势，协同开展黄淮海地区和里下河地区稻麦高效节水智慧灌溉技术研究，探索构建适应不同生态区的智慧灌溉技术模式与技术标准。","深化南北科技协作 共促智慧节水农业发展—河北省水资源研究与水利技术试验推广中心一行来我所调研交流\n\n作者：资源与环境研究室 文章来源：里下河所 点击数：次 更新时间：2026-09-21 18:02\n\n9月21日，河北省水资源研究与水利技术试验推广中心（河北省灌溉中心试验站）副主任贾志军一行3人来我所调研交流。扬州大学水利科学与工程学院副教授张超、江苏艺米科技产业有限公司王娟参加调研，我所资源与环境研究室相关科技人员参加交流。\n\n调研组一行在资源与环境研究室主任寇祥明等陪同下，实地考察我所樊川基地，现场观摩智慧灌溉、虫情监测及土壤墒情在线监测等智慧农业应用场景。座谈会上，双方围绕农业水资源高效利用、智慧灌溉技术研发及科研基地建设等主题进行深入交流，分别介绍了各自团队的科研方向、技术优势与试验基地建设情况，并结合黄淮海地区和里下河地区水资源条件及农业生产特点，就不同区域稻麦节水高效生产面临的关键问题展开探讨。双方重点围绕深化南北区域农业节水科技协作达成共识，一致认为应充分发挥各自在农业水资源利用、稻麦栽培和智慧农业等方面的科研与平台优势，协同开展黄淮海地区和里下河地区稻麦高效节水智慧灌溉技术研究，探索构建适应不同生态区的智慧灌溉技术模式与技术标准。\n\n[![Image 1: 2.jpg](https:\u002F\u002Fyz.jaas.ac.cn\u002Fcms_files\u002Ffilemanager\u002F99318008\u002Fpicture\u002F20268\u002FS7ab29cbc247748b8b1c3a335f0b41404-800.jpg)](https:\u002F\u002Fyz.jaas.ac.cn\u002Fcms_files\u002Ffilemanager\u002F99318008\u002Fpicture\u002F20268\u002F7ab29cbc247748b8b1c3a335f0b41404.jpg)[](https:\u002F\u002Fyz.jaas.ac.cn\u002Fxww\u002Fxwzx\u002Fart\u002F2026\u002Fart_685e5e43f9554e108a96b2b38a2110e2.html)\n\n[![Image 2: 1(1).jpg](https:\u002F\u002Fyz.jaas.ac.cn\u002Fcms_files\u002Ffilemanager\u002F99318008\u002Fpicture\u002F20268\u002FS080985d3c19546bcb9b4ed2013226f82-800.jpg)](https:\u002F\u002Fyz.jaas.ac.cn\u002Fcms_files\u002Ffilemanager\u002F99318008\u002Fpicture\u002F20268\u002F080985d3c19546bcb9b4ed2013226f82.jpg)[](https:\u002F\u002Fyz.jaas.ac.cn\u002Fxww\u002Fxwzx\u002Fart\u002F2026\u002Fart_685e5e43f9554e108a96b2b38a2110e2.html)","江苏里下河地区农业科学研究所","2026-09-21T00:00:00Z","报道",58,{"impact":142,"substance":19,"depth":142,"authority":472,"freshness":229,"relevant":21,"comment":473},11,"省级科研机构间的南北节水协作调研，有实地观摩与共识方向，但属常规交流通稿，增量有限。",[475],{"name":467,"url":464},[26,30,236,477,478],"南北科技协作","稻麦生产",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":482},{"candidates":483,"agricultural_evidence":46},[484,489,493],{"code":32,"score":45,"supported":46,"title":485,"abstract":486,"tags":488},[51],[50,51,487],"农业节水",[26,30,236],{"code":340,"score":184,"supported":46,"title":490,"abstract":491,"tags":492},[],[343],[],{"code":189,"score":184,"supported":46,"title":494,"abstract":495,"tags":497},[],[496],"智慧农业",[],[499,500],"河北水资源中心 里下河所 智慧灌溉","黄淮海 里下河 稻麦节水","河北水资源中心里下河所智慧灌溉-3222",2,"2026-09-23T00:04:29.727008Z",{"id":505,"title":506,"url":507,"summary":508,"summary_zh":509,"content":9,"source_name":510,"source_url":507,"published_at":511,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":394,"score_detail":512,"sources":514,"tags":516,"primary_topic":518,"secondary_topics":519,"classification":521,"search_phrases":551,"slug":554,"view_count":502,"doi":555,"paper":556,"created_at":567},2667,"A systematic review of remote sensing applications for agricultural water management in a water-stressed South Africa","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs43621-026-04728-y","Abstract Recent advancements in earth observation and computational technologies have enabled the prudent use of remote sensing (RS) for monitoring and managing water resources. RS is a spatially explicit and effective approach for field-level to large-scale monitoring through data-driven insights on key agricultural water management (AWM) aspects of water consumption, productivity, agricultural drought and irrigated area extent mapping. However, the progress made in the South African context is not well documented. Hence, this review aimed to assess how RS is utilized for AWM in South Africa. Article search was conducted in the Scopus and Web of Science databases using keywords remote sensing, earth observation, agricultural water management, irrigation, evapotranspiration, water use, water productivity, agricultural drought, and South Africa. The bibliometric analysis from 165 articles revealed that number of publications have a 8.3% annual growth over 26 years. RS data have been utilized to assess evapotranspiration (ET), crop water productivity (CWP), agricultural drought, scheme performance, and irrigation water quality. Data limitations, insufficient technical capacity, and limited computational infrastructure were the notable challenges. Future research should focus on integrated use of multi-temporal and multi-source data to minimize gaps across sensors and improve accuracy. Overall, RS has substantial potential to address water management issues in the agricultural sector of South Africa. Addressing the challenges through continued innovation, data integration, and capacity building is key to utilizing RS for sustainable agriculture and water security.","摘要 地球观测与计算技术的最新进展使得遥感（RS）能够被审慎地应用于水资源监测与管理。遥感是一种空间显式且有效的方法，可通过数据驱动的洞察，从田块尺度到大规模监测农业水资源管理（AWM）的关键方面，包括耗水量、生产力、农业干旱及灌溉面积范围制图。然而，南非在这一领域的进展尚未得到充分记录。因此，本综述旨在评估遥感在南非农业水资源管理中的应用情况。研究在Scopus和Web of Science数据库中使用遥感、地球观测、农业水资源管理、灌溉、蒸散发、用水量、水分生产力、农业干旱和南非等关键词进行文献检索。对165篇文章的文献计量分析显示，过去26年间发表数量年增长率为8.3%。遥感数据已被用于评估蒸散发（ET）、作物水分生产力（CWP）、农业干旱、灌区性能及灌溉水质。数据局限性、技术能力不足和计算基础设施有限是显著挑战。未来研究应侧重于多时相和多源数据的集成使用，以缩小传感器之间的差距并提高精度。总体而言，遥感在解决南非农业部门水资源管理问题方面具有巨大潜力。通过持续创新、数据集成和能力建设来应对这些挑战，是利用遥感实现可持续农业和水安全的关键。","Discover Sustainability","2026-09-15T00:00:00Z",{"impact":228,"substance":45,"depth":144,"authority":145,"freshness":20,"relevant":21,"comment":513},"以南非为对象的遥感农业水资源管理系统性综述，方法规范、数据规模明确，对干旱区灌溉与遥感应用有参考价值，但属区域案例研究，公共影响层级有限。",[515],{"name":510,"url":507},[496,26,27,401,517],"农业干旱",{"code":62,"slug":246,"name":247,"path":248,"parent_code":244},[520],{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},{"status":39,"locked":14,"version":40,"method":41,"evidence":522},{"candidates":523,"agricultural_evidence":46},[524,528,532,536,540,547],{"code":62,"score":264,"supported":46,"title":525,"abstract":526,"tags":527},[65],[27,65],[27],{"code":32,"score":472,"supported":46,"title":529,"abstract":530,"tags":531},[],[50,51,29,33,48],[26,401],{"code":68,"score":69,"supported":46,"title":533,"abstract":534,"tags":535},[],[72,73],[],{"code":275,"score":69,"supported":46,"title":537,"abstract":538,"tags":539},[],[278,279],[],{"code":541,"score":69,"supported":46,"title":542,"abstract":543,"tags":546},"I7",[],[544,545],"文献计量","bibliometric",[],{"code":189,"score":21,"supported":14,"title":548,"abstract":549,"tags":550},[],[],[496],[552,553],"农业水资源 农业干旱 智慧农业 灌溉管理","农业水资源 农业干旱","农业水资源农业干旱智慧农业灌溉管理-2667","10.1007\u002Fs43621-026-04728-y",{"doi":555,"openalex_id":557,"authors":558,"venue":510,"cited_by_count":79,"oa_url":507,"card":562,"direction":126,"ingested_from":128},"W7213266434",[559],{"name":560,"orcid":561},"Yilkal Gebeyehu Mekonnen","https:\u002F\u002Forcid.org\u002F0000-0001-9450-1081",{"tldr":563,"method":564,"finding":565,"direction":126,"opportunity":566},"系统综述遥感在南非农业水资源管理中的应用进展与挑战。","Scopus与Web of Science检索165篇文献，做文献计量分析。","遥感用于蒸散、水分生产力、干旱与灌溉监测，但受数据与能力限制。","多源多时相遥感数据融合以填补传感器空缺、提升精度，是值得切入的方向。","2026-09-16T23:30:29.241938Z"]