[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2007":3,"related-2007":110},{"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":31,"secondary_topics":37,"classification":38,"search_phrases":78,"slug":81,"view_count":82,"doi":83,"paper":84,"created_at":109},2007,"AIDspat: Introduction of a model framework to estimate spatio-temporal agricultural irrigation demands – A study area in Germany","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.agwat.2026.110730","In the face of ongoing climate change, information about agricultural water usage is crucial for policymakers and planners. This study introduces the AIDspat model, a new framework for estimating agricultural irrigation demand (AID). The model combines an existing soil water balance model with the principle of irrigation scheduling. In addition to location-based climate, soil and land use data, the model takes into account general crop-specific parameters, irrigation techniques and farmers’ irrigation management decisions. This enables an objective determination of AID. The model enables scenario-based calculations with low computational cost across various scales, ranging from the field to the national level and spanning both past and future time periods. Integrating crop-specific differences through intra-annual dynamic plant development and considering irrigation techniques enhances the model’s accuracy and practical applicability. The model’s ability to capture the spatial and temporal dynamics of AID provides valuable insights for the sustainable management of agricultural water. Calibrated and validated for a study area in southern Germany, the model demonstrates a high degree of alignment between modeled values and literature benchmarks for a variety of agricultural crops. The modeled results show a good agreement with measured irrigation volumes, with yearly percentage differences ranging from -17.2% to +47% and a mean absolute percentage error (MAPE) of approximately 16.9% over the period from 2017 to 2023. Thus, the model provides planners and policymakers with an irrigation decision support system to analyze the impact of agricultural systems, climatic changes and agricultural decision-making processes, thereby facilitating sustainable agricultural irrigation management.","面对持续的气候变化，农业用水信息对政策制定者和规划者至关重要。本研究引入了AIDspat模型，这是一个估算农业灌溉需求（AID）的新框架。该模型将现有的土壤水平衡模型与灌溉调度原理相结合。除了基于位置的气候、土壤和土地利用数据外，模型还考虑了通用的作物特定参数、灌溉技术以及农民的灌溉管理决策。这使得AID能够被客观地确定。该模型支持基于情景的计算，计算成本低，可适用于从田间到国家层面的各种尺度，并涵盖过去和未来的时间段。通过年内动态植物发育整合作物特异性差异，并考虑灌溉技术，增强了模型的准确性和实际应用性。模型捕捉AID时空动态的能力为农业水资源的可持续管理提供了宝贵的见解。该模型在德国南部的一个研究区域进行了校准和验证，显示出模拟值与多种农作物的文献基准高度一致。模拟结果与实测灌溉量吻合良好，2017年至2023年间年度百分比差异范围为-17.2%至+47%，平均绝对百分比误差（MAPE）约为16.9%。因此，该模型为规划者和政策制定者提供了一个灌溉决策支持系统，用于分析农业系统、气候变化和农业决策过程的影响，从而促进可持续的农业灌溉管理。",null,"Agricultural Water Management","2026-09-08T00:00:00Z","论文",10,false,75,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},18,22,19,14,2,1,"提出AIDspat模型，结合土壤水平衡与灌溉调度，实现时空尺度农业灌溉需水估算，对可持续水资源管理有参考价值。",[25],{"name":10,"url":6},[27,28,29,30],"智慧农业","农业灌溉","水资源管理","模型模拟",{"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":45},[44,51,59,66,73],{"code":32,"score":17,"supported":45,"title":46,"abstract":47,"tags":50},true,[33],[48,49,33],"灌溉","水资源",[29],{"code":52,"score":53,"supported":45,"title":54,"abstract":55,"tags":58},"H2",6,[],[56,57],"土壤","soil",[],{"code":60,"score":53,"supported":45,"title":61,"abstract":62,"tags":65},"H7",[],[63,64],"气候变化","climate change",[],{"code":67,"score":68,"supported":45,"title":69,"abstract":70,"tags":72},"I2",4,[],[71],"decision support",[30],{"code":74,"score":22,"supported":14,"title":75,"abstract":76,"tags":77},"I1",[],[],[27],[79,80],"水资源管理 农业灌溉 智慧农业 模型模拟","水资源管理 农业灌溉","水资源管理农业灌溉智慧农业模型模拟-2007",5,"10.1016\u002Fj.agwat.2026.110730",{"doi":83,"openalex_id":85,"authors":86,"venue":10,"cited_by_count":101,"oa_url":6,"card":102,"direction":106,"ingested_from":108},"W4412168598",[87,89,91,93,95,98],{"name":88,"orcid":9},"Jacob Jeff Bernhardt",{"name":90,"orcid":9},"Frank Potts",{"name":92,"orcid":9},"Jan Bug",{"name":94,"orcid":9},"Maximilian Zinnbauer",{"name":96,"orcid":97},"Max Eysholdt","https:\u002F\u002Forcid.org\u002F0000-0001-9761-2991",{"name":99,"orcid":100},"Jochen Hack","https:\u002F\u002Forcid.org\u002F0000-0002-8060-7990",0,{"tldr":103,"method":104,"finding":105,"direction":106,"opportunity":107},"提出AIDspat模型，结合土壤水平衡与灌溉调度，估算时空农业灌溉需求。","结合土壤水平衡模型与灌溉调度原理，考虑气候、土壤、作物参数及灌溉管理决策。","模型在德国南部验证良好，MAPE约16.9%，能捕捉灌溉需求的时空动态。","农业人工智能与决策模型","可扩展至不同气候区，集成遥感数据或优化灌溉管理决策，提升模型适用性。","openalex","2026-09-09T23:30:46.078172Z",{"total":53,"page":22,"page_size":53,"items":111},[112,181,255,315,392,463],{"id":113,"title":114,"url":115,"summary":116,"summary_zh":117,"content":9,"source_name":118,"source_url":115,"published_at":119,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":120,"score_detail":121,"sources":124,"tags":126,"primary_topic":130,"secondary_topics":131,"classification":138,"search_phrases":156,"slug":159,"view_count":22,"doi":160,"paper":161,"created_at":180},3332,"Solar-powered irrigation adoption in South Asia: opportunities, challenges, and policy implications","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1892056","Solar irrigation technologies offer potential sustainable and cost-effective solutions, though their environmental sustainability depends critically on institutional and regulatory frameworks to address social and environmental challenges in regions with vast solar and agricultural potential such as south Asia. This review paper evaluates (1) technological innovations, (2) opportunities and fundamental challenges and policy frameworks, and (3) socio-economic, and environment impacts on south Asia countries including Bangladesh, India, Nepal, and Pakistan. The review results indicated that solar irrigation systems demonstrated advantage in reducing operational costs compared to diesel alternatives and contributed significantly to carbon abatement. In addition, these systems provided consistent water supply independent of erratic grid power and compatible with irrigation systems for efficiency. Surplus electricity generated by solar irrigation systems can be sold back to the grid, increasing farmer income. Reliable water access can drive a transition from subsistence farming to cash crop cultivation. However, solar irrigation system’s performance is weather-dependent and without energy storage, they cannot support nighttime irrigation. When integrated with battery storage and advanced technologies such as the Internet of Things (IoT), these systems can provide irrigation during non-sunlight hours while enabling efficient, automated water management that optimizes water use and enhances crop productivity. This review highlighted key research gaps, including the need for long-term climate-informed modeling of solar irrigation systems, empirical hydrological studies of institutional models, and deeper analysis of tenancy and gender dynamics. Addressing these gaps improves solar irrigation by enabling more accurate water-resource planning under future climate conditions, strengthening institutional and groundwater management, and ensuring more equitable access for user. In conclusion, solar irrigation in South Asia should be seen as a sustainability tool that balances technological expansion with water conservation and social equity.","太阳能灌溉技术提供了潜在的可持续且具有成本效益的解决方案，但其环境可持续性在很大程度上取决于制度和监管框架，以应对南亚等太阳能与农业潜力巨大地区所面临的社会和环境挑战。本文综述评估了（1）技术创新，（2）机遇、根本性挑战与政策框架，以及（3）对孟加拉国、印度、尼泊尔和巴基斯坦等南亚国家的社会经济和环境影响。综述结果表明，太阳能灌溉系统在降低运行成本方面相较于柴油替代方案具有优势，并对碳减排有显著贡献。此外，这些系统提供了不依赖不稳定电网电力的稳定供水，并与灌溉系统兼容以提高效率。太阳能灌溉系统产生的盈余电力可回售给电网，增加农民收入。可靠的水源获取可以推动从自给农业向经济作物种植的转变。然而，太阳能灌溉系统的性能受天气影响，且在没有储能的情况下，无法支持夜间灌溉。当与电池储能和物联网（IoT）等先进技术集成时，这些系统可以在非日照时段提供灌溉，同时实现高效、自动化的水资源管理，从而优化用水并提高作物生产力。本综述指出了关键研究空白，包括需要对太阳能灌溉系统进行长期气候信息建模、对制度模式进行实证水文研究，以及对租佃和性别动态进行更深入分析。弥补这些空白可以改进太阳能灌溉，具体途径包括：在未来气候条件下实现更准确的水资源规划，加强制度和地下水管理，并确保用户更公平地获取水资源。总之，南亚的太阳能灌溉应被视为一种可持续性工具，在技术扩展与水资源保护和社会公平之间取得平衡。","Frontiers in Sustainable Food Systems","2026-09-23T00:00:00Z",80,{"impact":17,"substance":18,"depth":17,"authority":20,"freshness":122,"relevant":22,"comment":123},8,"系统综述南亚四国光伏灌溉的技术、政策与社会环境效应，指出物联网与储能结合方向及研究空白，对农业信息化与智慧灌溉有参考价值。",[125],{"name":118,"url":115},[27,127,29,128,129],"农业物联网","光伏灌溉","南亚农业",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[132],{"code":133,"slug":134,"name":135,"path":136,"parent_code":137},"I5","agricultural-iot","物联网传感与边缘计算","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-iot","I",{"status":39,"locked":14,"version":40,"method":41,"evidence":139},{"candidates":140,"agricultural_evidence":45},[141,145,152],{"code":32,"score":17,"supported":45,"title":142,"abstract":143,"tags":144},[33],[48,49,33],[29],{"code":133,"score":13,"supported":45,"title":146,"abstract":147,"tags":151},[],[148,149,150],"物联网","internet of things","IoT",[127],{"code":74,"score":22,"supported":14,"title":153,"abstract":154,"tags":155},[],[],[27],[157,158],"南亚 光伏灌溉","农业物联网 水资源管理 光伏灌溉 南亚农业","南亚光伏灌溉-3332","10.3389\u002Ffsufs.2026.1892056",{"doi":160,"openalex_id":162,"authors":163,"venue":118,"cited_by_count":101,"oa_url":115,"card":174,"direction":178,"ingested_from":108},"W7214072186",[164,167,169,172],{"name":165,"orcid":166},"Younsuk Dong","https:\u002F\u002Forcid.org\u002F0000-0003-2400-1916",{"name":168,"orcid":9},"Heesun Jang",{"name":170,"orcid":171},"Najme Yazdanpanah","https:\u002F\u002Forcid.org\u002F0000-0003-2554-7005",{"name":173,"orcid":9},"Yadu Pokhrel",{"tldr":175,"method":176,"finding":177,"direction":178,"opportunity":179},"综述南亚太阳能灌溉的技术、政策与社会环境影响，指出其可持续性取决于制度与监管框架。","文献综述，覆盖孟加拉国、印度、尼泊尔、巴基斯坦的技术、政策与影响分析。","太阳能灌溉降低运营成本并助力碳减排，但依赖天气，需储能与物联网支持夜间灌溉。","农业绿色发展与碳","可开展气候情景下太阳能灌溉的长期水文建模，并研究租佃与性别差异对公平获取的影响。","2026-09-24T23:30:07.037091Z",{"id":182,"title":183,"url":184,"summary":185,"summary_zh":186,"content":9,"source_name":187,"source_url":184,"published_at":188,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":189,"sources":193,"tags":195,"primary_topic":199,"secondary_topics":200,"classification":204,"search_phrases":232,"slug":235,"view_count":68,"doi":236,"paper":237,"created_at":254},3190,"Comparing Irrigation Identification Methods in Colorado: Limitations of Downscaled SMAP Soil Moisture","https:\u002F\u002Fdoi.org\u002F10.3390\u002Frs18183223","With limited freshwater resources and growing water demands, it is imperative to identify and monitor water needs. Agricultural irrigation is the world’s largest water user, comprising 45–90% of freshwater withdrawals. Identifying and tracking changes in irrigated land is necessary for sustainable water management and forecasting agricultural water needs and patterns; however, the low resolution of available remote sensing observations hinders field-scale analysis. Downscaling soil moisture observations has been offered as a solution to this problem. Our study compares the performance of five irrigation identification methods using a newly developed downscaled deep soil moisture extrapolation method used to estimate Soil Moisture Active Passive (SMAP) soil moisture (SM) at a spatial resolution of 400 m for 5 cm, 20 cm, and 50 cm depths. Using this data along with Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) precipitation and Landsat Normalized Difference Vegetation Index (NDVI), we evaluate these methods with respect to crop type, irrigation type, and observation depth on agricultural fields in Colorado using the irrigation maps provided by the Colorado Decision Support System from 2015 through 2024. With no crop\u002Firrigation type–observation depth combination exceeding an F1 score of 0.149 or MCC value of 0.163, we find that none of the methods can accurately identify irrigated land regardless of crop type, irrigation type, and observation depth. Because these methods succeeded in earlier small-area studies, and because the classified maps resolved into large, spatially uniform blocks, we interpret this as a limitation specific to field-scale detection over large, heterogeneous regions rather than a defect in the dataset. These findings highlight a limitation of this downscaled SM dataset and raise the question of whether other downscaled soil moisture products share this limitation.","在淡水资源有限且用水需求不断增长的背景下，识别和监测水资源需求势在必行。农业灌溉是全球最大的用水部门，占淡水取水量的45%–90%。识别和追踪灌溉土地的变化对于可持续水资源管理以及预测农业用水需求和模式至关重要；然而，现有遥感观测的低分辨率阻碍了田块尺度的分析。土壤湿度观测数据的降尺度被提出作为解决这一问题的方法。本研究比较了五种灌溉识别方法的性能，所用数据基于新开发的降尺度深层土壤湿度外推方法，用于估算土壤湿度主动被动（SMAP）卫星在400 m空间分辨率下5 cm、20 cm和50 cm深度的土壤湿度（SM）。利用该数据以及气候灾害组红外降水与站点数据（CHIRPS）降水和Landsat归一化植被指数（NDVI），我们结合科罗拉多决策支持系统提供的2015年至2024年灌溉地图，在科罗拉多州的农田上就作物类型、灌溉类型和观测深度对这些方法进行了评估。在没有任何作物\u002F灌溉类型–观测深度组合的F1分数超过0.149或MCC值超过0.163的情况下，我们发现无论作物类型、灌溉类型和观测深度如何，这些方法均无法准确识别灌溉土地。由于这些方法在早期小区域研究中取得了成功，且分类地图呈现为大的、空间均一的斑块，我们将此解释为大规模异质区域上田块尺度检测所特有的局限性，而非数据集本身的缺陷。这些发现凸显了该降尺度SM数据集的局限性，并提出其他降尺度土壤湿度产品是否也存在这一局限性的问题。","Remote Sensing","2026-09-19T00:00:00Z",{"impact":190,"substance":18,"depth":17,"authority":20,"freshness":191,"relevant":22,"comment":192},12,9,"该研究通过大区域对比实验揭示降尺度SMAP土壤水分在田块尺度灌溉识别上的局限，方法严谨、结论明确，对农业遥感与水资源管理有参考价值，但属细分领域学术进展，公共影响有限。",[194],{"name":187,"url":184},[27,196,29,197,198],"遥感","土壤水分","灌溉识别",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[201],{"code":52,"slug":57,"name":202,"path":203,"parent_code":36},"土壤健康与改良","\u002Ftopic\u002Fenvironment\u002Fsoil",{"status":39,"locked":14,"version":40,"method":41,"evidence":205},{"candidates":206,"agricultural_evidence":45},[207,211,216,223,228],{"code":32,"score":17,"supported":45,"title":208,"abstract":209,"tags":210},[33],[48,49,33],[29],{"code":52,"score":212,"supported":45,"title":213,"abstract":214,"tags":215},15,[57],[56,57],[197],{"code":217,"score":218,"supported":45,"title":219,"abstract":220,"tags":222},"I3",7,[],[196,221],"remote sensing",[196],{"code":67,"score":224,"supported":45,"title":225,"abstract":226,"tags":227},3,[],[71],[],{"code":74,"score":22,"supported":14,"title":229,"abstract":230,"tags":231},[],[],[27],[233,234],"SMAP 土壤水分 灌溉识别","科罗拉多 灌溉制图 遥感","SMAP土壤水分灌溉识别-3190","10.3390\u002Frs18183223",{"doi":236,"openalex_id":238,"authors":239,"venue":187,"cited_by_count":101,"oa_url":184,"card":248,"direction":252,"ingested_from":108},"W7213934204",[240,243,245],{"name":241,"orcid":242},"Annelise M. Turman","https:\u002F\u002Forcid.org\u002F0009-0000-2392-3631",{"name":244,"orcid":9},"Bin Fang",{"name":246,"orcid":247},"V. Vijaya Lakshmi","https:\u002F\u002Forcid.org\u002F0000-0001-9522-7897",{"tldr":249,"method":250,"finding":251,"direction":252,"opportunity":253},"比较五种灌溉识别方法，发现降尺度SMAP土壤湿度在科罗拉多田间尺度无法准确识别灌溉。","用400米降尺度SMAP土壤湿度、CHIRPS降水和Landsat NDVI，对","所有方法F1最高仅0.149，无法准确识别灌溉地，归因于大区域异质性而非数据缺陷。","农业遥感与作物表型","可检验其他降尺度土壤湿度产品是否同样受大区域异质性限制，并探索融合多源数据提升田间尺度灌溉识别。","2026-09-22T23:30:26.627420Z",{"id":256,"title":257,"url":258,"summary":259,"summary_zh":260,"content":9,"source_name":10,"source_url":258,"published_at":261,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":262,"sources":264,"tags":266,"primary_topic":269,"secondary_topics":270,"classification":271,"search_phrases":289,"slug":291,"view_count":224,"doi":292,"paper":293,"created_at":314},1831,"Water-yield supply–demand relationships in Northwest China three water lines region: An InVEST–glacier assessment","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.agwat.2026.110752","Water scarcity poses a major challenge to sustainable development in arid regions, particularly where agricultural irrigation dominates water consumption. In glacier-influenced regions, conventional water yield assessments may underestimate water availability by neglecting glacier meltwater contributions. This study developed an InVEST–Glacier framework to quantify water yield service supply and demand in Northwest China Three Water Lines region (TWL region) and identify their dominant driving factors. The results showed that low water-yield areas (0–25 mm) accounted for 60.06%–70.19% of the region, while high water-yield areas were concentrated in mountainous regions. Glacier meltwater contributed more than 70% of water yield in most inland basins of the Tarim Basin and exceeded 90% in some years, but contributed less than 10% in the Yellow River and Datong River. Water demand was highly concentrated in irrigated plains and urbanized areas. The supply–demand relationship exhibited a pattern of “widespread surplus with localized stress”, with areas of ESDR \u003C 0.2 increasing from 67.59% to 79.50%, while areas with ESDR > 0.8 accounted for 14.68%–23.90%. Natural factors dominated the spatial differentiation of ESDR, with elevation, precipitation, and NDVI showing the highest integrated driving scores.These findings highlight the stage-dependent buffering role of glacier meltwater and the need for differentiated water-resource management in glacier-dependent and water-stressed regions.","水资源短缺对干旱地区的可持续发展构成重大挑战，尤其是在农业灌溉占用水主导地位的地区。在受冰川影响的区域，传统的水资源评估方法可能因忽略冰川融水贡献而低估水资源可用性。本研究构建了InVEST–冰川（InVEST–Glacier）框架，用以量化中国西北“三水线”区域（TWL区域）的水资源供给服务与需求，并识别其主导驱动因素。结果表明，低产水区（0–25毫米）占区域面积的60.06%–70.19%，而高产水区集中于山区。在塔里木盆地大部分内陆流域，冰川融水对产水量的贡献超过70%，部分年份甚至超过90%，但在黄河及大通河流域其贡献不足10%。水资源需求高度集中于灌溉平原和城市化区域。供需关系呈现“整体盈余、局部紧张”的格局，其中生态系统服务供需比（ESDR）小于0.2的区域面积从67.59%增加至79.50%，而ESDR大于0.8的区域占14.68%–23.90%。自然因素主导了ESDR的空间分异，其中海拔、降水和归一化植被指数（NDVI）的综合驱动得分最高。这些发现凸显了冰川融水在阶段性上的缓冲作用，以及在依赖冰川和缺水地区实施差异化水资源管理的必要性。","2026-09-05T00:00:00Z",{"impact":17,"substance":18,"depth":17,"authority":20,"freshness":224,"relevant":22,"comment":263},"研究提出InVEST-冰川框架量化水资源供需，对干旱区农业水资源管理有重要参考价值。",[265],{"name":10,"url":258},[28,267,29,268],"遥感评估","西北地区",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":272},{"candidates":273,"agricultural_evidence":45},[274,278,284],{"code":32,"score":13,"supported":45,"title":275,"abstract":276,"tags":277},[],[48,49,33],[29],{"code":279,"score":224,"supported":45,"title":280,"abstract":281,"tags":283},"H6",[],[282],"生态系统服务",[],{"code":60,"score":224,"supported":45,"title":285,"abstract":286,"tags":288},[],[287],"干旱",[],[290,80],"水资源管理 农业灌溉 西北地区 遥感评估","水资源管理农业灌溉西北地区遥感评估-1831","10.1016\u002Fj.agwat.2026.110752",{"doi":292,"openalex_id":294,"authors":295,"venue":10,"cited_by_count":101,"oa_url":308,"card":309,"direction":252,"ingested_from":108},"W7208829734",[296,298,300,302,304,306],{"name":297,"orcid":9},"Yingying Gai",{"name":299,"orcid":9},"Shnhong Mo",{"name":301,"orcid":9},"Peng Li",{"name":303,"orcid":9},"Mingjiang Deng",{"name":305,"orcid":9},"Hui Sun",{"name":307,"orcid":9},"Tao Zhou","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS0378377426006335\u002Fpdf",{"tldr":310,"method":311,"finding":312,"direction":178,"opportunity":313},"开发InVEST-冰川框架评估西北三线区域水资源供需，发现冰川融水贡献显著但区域差异大。","InVEST-冰川框架，结合冰川融水估算，分析供需及驱动因素。","冰川融水在塔里木盆地贡献超70%，供需总体盈余但局部紧张，自然因素主导空间分异。","可研究冰川融水对农业灌溉的缓冲作用及气候变化下的水资源管理策略，结合农业需水预测。","2026-09-07T23:30:23.347697Z",{"id":316,"title":317,"url":318,"summary":319,"summary_zh":320,"content":9,"source_name":321,"source_url":318,"published_at":322,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":120,"score_detail":323,"sources":325,"tags":327,"primary_topic":331,"secondary_topics":336,"classification":339,"search_phrases":362,"slug":365,"view_count":224,"doi":366,"paper":367,"created_at":391},1383,"Pareto-front-based optimization of irrigation and nitrogen application schedule in Sandy-soil maize: Trade-offs among yield, water productivity, nitrogen physiological efficiency, and grain nitrogen concentration","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.agsy.2026.104953","Context Developing appropriate irrigation and nitrogen application schedules (INASs) is essential for maize production on sandy soils, where low water-retention and nutrient-holding capacities make crop performance highly sensitive to within-season water and nitrogen management. However, most crop-model-based optimization studies have focused mainly on yield and resource-use efficiency, while grain nutritional quality and the economic qualifications of optimized schedules have received less attention. Objective This study aimed to develop a CERES-Maize–NSGA-III framework to optimize INASs for shallow-buried drip-irrigated maize on sandy soil, while clarifying trade-offs among yield, crop water productivity (WP c ), nitrogen physiological efficiency (PE N ), and grain nitrogen concentration (GNC), and evaluate the economic performance of selected candidate schedules through partial-budget analysis. Methods CERES-Maize was calibrated and validated using two years of field observations and then coupled with NSGA-III to optimize irrigation timing, irrigation amount, nitrogen application timing, and nitrogen rate. Pareto-optimal schedules were further evaluated through candidate-schedule selection, weather-year stress testing, and partial-budget economic sensitivity analysis. Results and conclusions CERES-Maize reproduced maize growth, yield, seasonal water use, and total nitrogen uptake with acceptable accuracy. The Pareto front revealed clear trade-offs among yield, WP c , PE N , and GNC. The 16 high-yield (HY) candidates selected using the historical farmer-yield benchmark exceeded the corresponding weather-matched farmer yield in all five annual simulations and maintained positive ΔPNR across all tested price–cost combinations. Among these candidates, HY01 showed the strongest combined yield and partial-budget performance, with the highest five-year mean simulated yield (12,003.2 kg\u002Fha) and the highest mean ΔPNR relative to the corresponding farmer-managed schedules (1307.83 yuan\u002Fha) across the tested weather-year and price–cost combinations. In contrast, the distance-to-utopia compromise schedule produced lower yield than the corresponding farmer-managed schedule in each weather year and showed weather- and price–cost-dependent economic performance. Significance The proposed framework provides a biophysical optimization tool for generating candidate INASs and clarifying trade-offs among yield, WP c , PE N , and GNC in sandy-soil maize. Weather variability was evaluated only through ex-post simulations of selected candidates and was not incorporated directly into the optimization. Further field-level, operational, economic, and environmental validation is therefore required before practical implementation.","背景 制定合理的灌溉与施氮方案（INASs）对砂质土壤上的玉米生产至关重要，因为砂质土壤的保水性和保肥能力较低，作物表现对季内水分和氮素管理高度敏感。然而，大多数基于作物模型的优化研究主要关注产量和资源利用效率，而籽粒营养品质及优化方案的经济可行性受到的关注较少。目的 本研究旨在构建CERES-Maize–NSGA-III耦合框架，优化砂质土壤浅埋滴灌玉米的灌溉与施氮方案，明确产量、作物水分生产力（WPc）、氮素生理效率（PEN）和籽粒氮浓度（GNC）之间的权衡关系，并通过部分预算分析评估所选候选方案的经济表现。方法 利用两年田间观测数据对CERES-Maize模型进行校准和验证，随后与NSGA-III算法耦合，优化灌溉时间、灌溉量、施氮时间和施氮量。对Pareto最优方案进一步开展候选方案筛选、天气年胁迫测试和部分预算经济敏感性分析。结果与结论 CERES-Maize模型能够以可接受的精度再现玉米生长、产量、季节性水分利用和总氮吸收量。Pareto前沿揭示了产量、WPc、PEN和GNC之间明显的权衡关系。以历史农户产量基准筛选出的16个高产（HY）候选方案在全部五个模拟年份中均超过了相应天气匹配的农户产量，并在所有测试的价格—成本组合下保持正的ΔPNR。在这些候选方案中，HY01表现出最强的产量和部分预算综合表现，其五年平均模拟产量最高（12,003.2 kg\u002Fha），且在测试的天气年和价格—成本组合下，相对于相应农户管理方案的平均ΔPNR最高（1,307.83元\u002Fha）。相比之下，距离理想点折中方案在每个天气年的产量均低于相应的农户管理方案，且其经济表现依赖于天气和价格—成本条件。意义 所提出的框架为砂质土壤玉米生成候选灌溉施氮方案并阐明产量、WPc、PEN和GNC之间的权衡关系提供了生物物理优化工具。天气变异性","Agricultural Systems","2026-09-02T00:00:00Z",{"impact":17,"substance":18,"depth":17,"authority":20,"freshness":122,"relevant":22,"comment":324},"研究提出CERES-Maize-NSGA-III框架优化沙土玉米水氮管理，兼顾产量、水氮效率与品质，方法新颖，结论可靠，对精准农业有参考价值。",[326],{"name":321,"url":318},[27,328,329,330,30],"玉米","水肥优化","多目标优化",{"code":332,"slug":333,"name":328,"path":334,"parent_code":335},"A3","maize","\u002Ftopic\u002Ffield-crops\u002Fmaize","A",[337,338],{"code":52,"slug":57,"name":202,"path":203,"parent_code":36},{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},{"status":39,"locked":14,"version":40,"method":41,"evidence":340},{"candidates":341,"agricultural_evidence":45},[342,346,350,354,358],{"code":332,"score":212,"supported":45,"title":343,"abstract":344,"tags":345},[333],[328,333],[328],{"code":52,"score":20,"supported":45,"title":347,"abstract":348,"tags":349},[57],[56,57],[],{"code":32,"score":20,"supported":45,"title":351,"abstract":352,"tags":353},[33],[48,33],[],{"code":74,"score":22,"supported":14,"title":355,"abstract":356,"tags":357},[],[],[27],{"code":67,"score":22,"supported":14,"title":359,"abstract":360,"tags":361},[],[],[30],[363,364],"多目标优化 智慧农业 模型模拟 水肥优化","多目标优化 智慧农业","多目标优化智慧农业模型模拟水肥优化-1383","10.1016\u002Fj.agsy.2026.104953",{"doi":366,"openalex_id":368,"authors":369,"venue":321,"cited_by_count":101,"oa_url":318,"card":386,"direction":106,"ingested_from":108},"W7205003045",[370,372,375,378,380,381,383,385],{"name":371,"orcid":9},"Yongqiang Wang",{"name":373,"orcid":374},"Fugui Wang","https:\u002F\u002Forcid.org\u002F0000-0002-8349-8398",{"name":376,"orcid":377},"Lanfang Bai","https:\u002F\u002Forcid.org\u002F0000-0001-7862-2844",{"name":379,"orcid":9},"Zhen Wang",{"name":379,"orcid":9},{"name":382,"orcid":9},"Haofang Yan",{"name":384,"orcid":9},"Zhigang Wang",{"name":384,"orcid":9},{"tldr":387,"method":388,"finding":389,"direction":106,"opportunity":390},"构建CERES-Maize-NSGA-III框架，优化沙土玉米灌溉施氮方案，权衡产量、水生产力、氮效","CERES-Maize模型与NSGA-III多目标优化，结合田间数据校准验证，并","高产候选方案在产量和经济效益上优于农民方案，但折中方案表现不稳定。","可探索将多目标优化与实时气象预测结合，开发动态灌溉施氮决策支持系统，兼顾产量、品质与经济效益。","2026-09-02T23:30:05.454493Z",{"id":393,"title":394,"url":395,"summary":396,"summary_zh":9,"content":9,"source_name":397,"source_url":395,"published_at":398,"category":12,"cover_url":9,"hotness":399,"is_selected":14,"score":400,"score_detail":401,"sources":404,"tags":408,"primary_topic":411,"secondary_topics":416,"classification":419,"search_phrases":445,"slug":448,"view_count":22,"doi":449,"paper":450,"created_at":462},1255,"Optimizing Water Management in Agriculture: The Role of IoT-Powered Smart Irrigation Systems in Addressing Global Food Security and Water Scarcity","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.21413238","Objective: This study aims to explore the impact of IoT-powered smart irrigation systems on optimizing water management in agriculture, with a specific focus on addressing global food security and mitigating water scarcity challenges. Materials and Methods: The research employs a mixed-methods approach, combining quantitative data analysis from agricultural case studies and qualitative interviews with farmers and agricultural experts. The study assesses the effectiveness of smart irrigation technologies, including soil moisture sensors, weather forecasting tools, and automated irrigation systems, in improving water use efficiency and crop yields. Results and Discussion: The findings indicate that IoT-powered smart irrigation systems significantly enhance water management practices in agriculture. These systems result in a reduction of up to 30% in water usage, while simultaneously increasing crop productivity by 15-20%. Additionally, the integration of real-time data analytics allows for more precise irrigation scheduling, which contributes to sustainable agricultural practices and improved food security. Conclusions: This research contributes to the existing literature by providing empirical evidence of the benefits of IoT technologies in agriculture. It highlights the potential of smart irrigation systems as a viable solution to the dual challenges of food security and water scarcity. The findings emphasize the need for policy interventions and investment in technology to facilitate the adoption of these systems in farming practices worldwide.","Zenodo (CERN European Organization for Nuclear Research)","2026-08-30T00:00:00Z",25,70,{"impact":17,"substance":18,"depth":402,"authority":190,"freshness":21,"relevant":22,"comment":403},16,"论文实证智能灌溉节水30%增产20%，对农业水资源管理有参考价值，但时效性较低。",[405,406],{"name":397,"url":395},{"name":397,"url":407},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.21413237",[27,409,410,29],"粮食安全","智能灌溉",{"code":412,"slug":413,"name":414,"path":415,"parent_code":335},"A8","yield-food-security","单产提升与粮食安全","\u002Ftopic\u002Ffield-crops\u002Fyield-food-security",[417,418],{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},{"code":133,"slug":134,"name":135,"path":136,"parent_code":137},{"status":39,"locked":14,"version":40,"method":41,"evidence":420},{"candidates":421,"agricultural_evidence":45},[422,427,432,437,441],{"code":32,"score":423,"supported":45,"title":424,"abstract":425,"tags":426},13,[33],[33],[410,29],{"code":412,"score":190,"supported":45,"title":428,"abstract":430,"tags":431},[429],"food security",[429],[409],{"code":133,"score":433,"supported":45,"title":434,"abstract":435,"tags":436},11,[150],[150],[],{"code":52,"score":224,"supported":45,"title":438,"abstract":439,"tags":440},[],[57],[],{"code":74,"score":22,"supported":14,"title":442,"abstract":443,"tags":444},[],[],[27],[446,447],"水资源管理 智慧农业 智能灌溉 粮食安全","水资源管理 智慧农业","水资源管理智慧农业智能灌溉粮食安全-1255","10.5281\u002Fzenodo.21413238",{"doi":449,"openalex_id":451,"authors":452,"venue":397,"cited_by_count":101,"oa_url":395,"card":456,"direction":460,"ingested_from":108},"W7169531097",[453],{"name":454,"orcid":455},"Mahdi Sabati Gavgani","https:\u002F\u002Forcid.org\u002F0000-0002-4585-9199",{"tldr":457,"method":458,"finding":459,"direction":460,"opportunity":461},"研究物联网智能灌溉系统优化农业用水，提升粮食安全与缓解水资源短缺。","混合方法：案例定量分析与农户专家定性访谈，评估传感器、天气预报和自动灌溉技术。","智能灌溉节水30%，增产15-20%，实时数据分析优化灌溉调度。","智慧农业 \u002F 农业物联网","可探索智能灌溉系统在不同作物、气候和农户采纳障碍下的适应性，以及政策激励对推广的影响。","2026-09-01T04:03:11.304099Z",{"id":464,"title":465,"url":466,"summary":467,"summary_zh":468,"content":9,"source_name":397,"source_url":466,"published_at":469,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":470,"score_detail":471,"sources":473,"tags":475,"primary_topic":480,"secondary_topics":481,"classification":486,"search_phrases":506,"slug":509,"view_count":101,"doi":510,"paper":511,"created_at":523},5591,"Hierarchical Conformal Risk Control for Artificial Intelligence Agriculture Irrigation Scheduling Under Unmodeled Infiltration: A Computer Safety-Guarantee Evaluation","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23543665","Irrigation scheduling algorithms that rely on soil-moisture forecasts are vulnerable to unmodeled infiltration, the process by which water bypasses the root zone through preferential pathways that resistance-based soil models cannot represent. The framework is evaluated through a replication-based design study that characterises the operating characteristics of the before-after-control-impact estimator used to audit scheduler performance, under a declared variance structure with between-cluster standard deviation 6.0, residual standard deviation 4.5 and intraclass correlation 0.64. Power was estimated across 2000 design cells spanning cluster counts of 8, 16, 24 and 32 and effect sizes of 3, 5 and 8 percentage points. The analysis indicates that 54 clusters are required to detect a 5-percentage-point effect at 80% power, and that the minimum detectable effect declines steeply as cluster count rises from 8 to 32. The contribution is a formal safety guarantee for irrigation decision support that remains valid when the infiltration model is wrong, together with an audit design that makes the guarantee empirically checkable.","依赖土壤湿度预报的灌溉调度算法容易受到未建模入渗的影响，即水分通过优先路径绕过根区的过程，而基于阻力的土壤模型无法表征这一过程。该框架通过一项基于重复的设计研究进行评估，该研究刻画了用于审计调度器性能的前后对照影响估计量的运行特性，其所依据的声明方差结构为：组间标准差6.0、残差标准差4.5、组内相关系数0.64。功效估计覆盖2000个设计单元，涵盖聚类数8、16、24和32以及效应量3、5和8个百分点。分析表明，在80%功效下检测5个百分点效应需要54个聚类，且最小可检测效应随聚类数从8增至32而急剧下降。本文的贡献在于为灌溉决策支持提供了一种正式的安全保证，该保证在入渗模型错误时仍然有效，同时提出了一种使该保证可经实证检验的审计设计。","2026-10-21T00:00:00Z",69,{"impact":122,"substance":18,"depth":17,"authority":190,"freshness":191,"relevant":22,"comment":472},"该研究提出在入渗模型失配条件下仍有效的灌溉决策安全保证框架，并给出可审计的试验设计，方法新颖、结论可靠，但属细分方法学研究，产业影响有限，适合作为专业精选而非头条。",[474],{"name":397,"url":466},[27,476,477,478,479],"农业人工智能","灌溉决策","安全保证","试验设计",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[482],{"code":67,"slug":483,"name":484,"path":485,"parent_code":137},"agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai",{"status":39,"locked":14,"version":40,"method":41,"evidence":487},{"candidates":488,"agricultural_evidence":45},[489,493,498,502],{"code":32,"score":212,"supported":45,"title":490,"abstract":491,"tags":492},[33],[48,33],[477],{"code":67,"score":190,"supported":45,"title":494,"abstract":496,"tags":497},[495],"artificial intelligence",[71],[476],{"code":52,"score":53,"supported":45,"title":499,"abstract":500,"tags":501},[],[56,57],[],{"code":74,"score":22,"supported":14,"title":503,"abstract":504,"tags":505},[],[],[27],[507,508],"灌溉调度 安全保证","农业人工智能 安全保证 智慧农业 灌溉决策","灌溉调度安全保证-5591","10.5281\u002Fzenodo.23543665",{"doi":510,"openalex_id":512,"authors":513,"venue":397,"cited_by_count":101,"oa_url":466,"card":518,"direction":106,"ingested_from":108},"W7223131205",[514,516],{"name":515,"orcid":9},"Nassima Benkhelifa",{"name":517,"orcid":9},"Yacine Aït Ahmed",{"tldr":519,"method":520,"finding":521,"direction":106,"opportunity":522},"提出分层保形风险控制，为未建模入渗下的灌溉调度提供安全保证。","分层保形风险控制与基于重复设计的BACI审计，2000个设计单元功效分析。","检测5个百分点效应需54个集群，最小可检测效应随集群数增加陡降。","可将保形风险控制扩展到其他未建模扰动下的农业决策安全保证与审计设计。","2026-10-22T11:21:10.283561Z"]