[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-5482":3,"related-5482":92},{"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":31,"classification":32,"search_phrases":68,"slug":71,"view_count":72,"doi":73,"paper":74,"created_at":91},5482,"A Conceptual Framework for Aquifer Delineation and Managed Aquifer Recharge in Deccan Trap Basaltic Terrain of Drought-Prone Area","https:\u002F\u002Fdoi.org\u002F10.71097\u002Fijaidr.v17.i2.2197","Drought-prone regions underlain by Deccan Trap basalt face persistent challenges in groundwater availability due to highly heterogeneous aquifer properties, limited natural recharge, variable fracture networks, and increasing groundwater demand. This study proposes a conceptual framework for aquifer delineation and Managed Aquifer Recharge (MAR) in basaltic terrain by integrating geological, hydrogeological, geophysical, topographical, and remote sensing information. The framework conceptualises aquifer systems through the identification of weathered zones, fractured basalt, vesicular horizons, joints, lineaments, and geological contacts that influence groundwater occurrence and movement. Spatial datasets are integrated within a Geographic Information System to delineate groundwater potential zones and identify suitable locations for MAR interventions. The proposed framework further links aquifer characteristics with recharge structures such as check dams, recharge shafts, percolation tanks, recharge trenches, and injection-based systems according to local hydrogeological conditions. Groundwater-level monitoring, aquifer response assessment, and periodic evaluation are incorporated to support adaptive recharge management. The framework provides a systematic basis for moving from aquifer characterization to site-specific recharge planning and monitoring. It can support sustainable groundwater management in drought-prone Deccan Trap landscapes by improving understanding of aquifer connectivity, recharge potential, and groundwater storage dynamics. The framework is particularly relevant for water-stressed regions where conventional groundwater development alone cannot ensure long-term water security.","以德干暗色岩玄武岩为基底的干旱易发地区，由于含水层特性高度非均质、天然补给有限、裂隙网络多变以及地下水需求不断增加，面临着地下水可获得性方面的持续挑战。本研究提出一个概念框架，通过整合地质、水文地质、地球物理、地形和遥感信息，在玄武岩地区进行含水层圈定与地下水人工补给（Managed Aquifer Recharge, MAR）。该框架通过识别影响地下水赋存与运动的风化带、裂隙玄武岩、气孔状层位、节理、线理和地质接触带，对含水层系统进行概念化。空间数据集在地理信息系统内进行整合，以圈定地下水潜力区并确定适合MAR干预的位置。所提出的框架进一步将含水层特征与补给结构（如拦水坝、补给井、渗滤池、补给沟和注入式系统）依据当地水文地质条件相联系。框架纳入了地下水位监测、含水层响应评估和定期评价，以支持适应性补给管理。该框架为从含水层表征转向特定场地的补给规划与监测提供了系统基础。通过增进对含水层连通性、补给潜力和地下水储存动态的理解，该框架可支持干旱易发德干暗色岩景观区的可持续地下水管理。该框架尤其适用于仅靠常规地下水开发无法确保长期水安全的水资源紧张地区。",null,"Journal of Advances in Developmental Research","2026-10-19T00:00:00Z","论文",10,false,49,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},8,18,14,6,3,1,"该论文提出玄武岩地区含水层划分与地下水回补的概念框架，方法有一定参考价值，但属概念性研究、缺乏实证数据，且来源期刊影响力有限、时效偏旧，不宜进入每日精选。",[25],{"name":10,"url":6},[27,28,29,30],"遥感","干旱区农业","地下水管理","水资源安全",[],{"status":33,"locked":14,"version":34,"method":35,"evidence":36},"needs_review","2026-10-22.2","rules",{"candidates":37,"agricultural_evidence":14,"reason":67},[38,47,54,61],{"code":39,"score":40,"supported":41,"title":42,"abstract":44,"tags":46},"H7",15,true,[43],"drought",[45,43],"干旱",[28],{"code":48,"score":49,"supported":41,"title":50,"abstract":51,"tags":53},"I3",7,[],[27,52],"remote sensing",[27],{"code":55,"score":20,"supported":41,"title":56,"abstract":57,"tags":60},"I4",[],[58,59],"地理信息","geographic information",[],{"code":62,"score":21,"supported":41,"title":63,"abstract":64,"tags":66},"H3",[],[65],"水资源",[],"农业相关性需要复核",[69,70],"Deccan Trap 玄武岩 含水层","managed aquifer recharge 干旱区","DeccanTrap玄武岩含水层-5482",0,"10.71097\u002Fijaidr.v17.i2.2197",{"doi":73,"openalex_id":75,"authors":76,"venue":10,"cited_by_count":72,"oa_url":82,"card":83,"direction":89,"ingested_from":90},"W7222957903",[77,80],{"name":78,"orcid":79},"Muneeb Ur Rahman","https:\u002F\u002Forcid.org\u002F0000-0001-9713-4598",{"name":81,"orcid":9},"K.M. Wanjarwadkar -","https:\u002F\u002Fwww.ijaidr.com\u002Fpapers\u002F2026\u002F2\u002F2197.pdf",{"tldr":84,"method":85,"finding":86,"direction":87,"opportunity":88},"提出整合多源信息的玄武岩地区含水层圈定与人工补给概念框架。","融合地质、水文地质、地球物理、地形与遥感数据，在GIS中集成分析。","框架可将含水层特征与补给设施匹配，支持自适应地下水管理。","其他","可在中国玄武岩或干旱区验证该框架，并耦合遥感与AI提升补给选址精度。","智慧农业 \u002F 农业物联网","openalex","2026-10-21T23:30:11.716732Z",{"total":20,"page":22,"page_size":20,"items":93},[94,163,232,286,357,422],{"id":95,"title":96,"url":97,"summary":98,"summary_zh":99,"content":9,"source_name":100,"source_url":97,"published_at":101,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":72,"score_detail":102,"sources":104,"tags":106,"primary_topic":9,"secondary_topics":107,"classification":108,"search_phrases":126,"slug":129,"view_count":72,"doi":130,"paper":131,"created_at":162},5169,"A multi-scale framework for identifying and validating managed aquifer recharge sites in semi-arid Kazakhstan","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffrwa.2026.1932313","Managed Aquifer Recharge (MAR) has emerged as an effective approach for enhancing groundwater resources in water-scarce regions under increasing climate variability and growing water demand. However, most GIS-based MAR studies are limited to regional suitability mapping, whereas the hydrogeological feasibility of identified sites is rarely verified under field conditions. This study presents a multi-scale framework integrating regional GIS-based screening with detailed site-scale verification to improve the reliability of MAR suitability assessment in southeastern Kazakhstan. This research was conducted within the Zhetysu Alatau–Balkhash First-Order Hydrogeological Basin to develop and evaluate a multi-scale framework for identifying suitable MAR sites. Regional suitability assessment combined Geographic Information Systems (GIS), the Analytic Hierarchy Process (AHP), Monte Carlo simulation, Fuzzy Gamma analysis, remote sensing, and regional hydrochemical data. Based on the regional assessment, the Byzhy River Basin was selected as a representative site for detailed hydrological, hydrogeological, hydrochemical, LiDAR-based, and field investigations to verify regional suitability under actual hydrogeological conditions. The regional suitability assessment identified 21.82% (58.41 km 2 ) of the representative study area as highly suitable for MAR, while Monte Carlo simulation and Fuzzy Gamma analysis confirmed the robustness of the suitability model. Hydrological assessment indicated a positive long-term mean potential water balance of 27.69 mm·year −1 , suggesting sufficient water resources for MAR. Three double-ring infiltration tests yielded a mean field-saturated hydraulic conductivity of 1.92 m·day −1 (range: 1.86–1.96 m·day −1 ), indicating high infiltration capacity of the Quaternary alluvial deposits. Groundwater mineralization remained below 1 g·L −1 , and hydrogeological investigations confirmed a 50 m thick Quaternary alluvial aquifer suitable for MAR. Long-term daily river discharge records indicated a potential annual recharge volume of 17.44 million m 3 , representing only 2.33% of the effective aquifer storage capacity (746.8 million m 3 ), demonstrating substantial storage potential. The close agreement between the regional suitability assessment and field investigations demonstrates that the multi-scale framework substantially reduces uncertainty in GIS-based MAR site identification. By integrating regional suitability mapping with hydrological, hydrogeological, hydrochemical, LiDAR, and field investigations, the framework provides a transferable methodology for identifying and verifying MAR sites in arid and semi-arid regions, supporting groundwater management and long-term water resource planning.","在气候变率加剧和水需求持续增长的背景下，管理含水层补给（Managed Aquifer Recharge, MAR）已成为增强缺水地区地下水资源的一种有效途径。然而，大多数基于GIS的MAR研究仅限于区域适宜性制图，而已识别场地的水文地质可行性鲜有在野外条件下得到验证。本研究提出了一种多尺度框架，将基于GIS的区域筛选与详细的场地尺度验证相结合，以提高哈萨克斯坦东南部MAR适宜性评估的可靠性。本研究在Zhetysu Alatau–Balkhash一级水文地质盆地内开展，旨在开发并评估用于识别适宜MAR场地的多尺度框架。区域适宜性评估综合了地理信息系统（GIS）、层次分析法（AHP）、蒙特卡洛模拟、模糊伽马分析、遥感以及区域水化学数据。基于区域评估结果，选取Byzhy河流域作为代表性场地，开展详细的水文、水文地质、水化学、基于LiDAR的以及野外调查，以在实际水文地质条件下验证区域适宜性。区域适宜性评估确定代表性研究区中有21.82%（58.41 km²）为高度适宜MAR区域，蒙特卡洛模拟和模糊伽马分析证实了适宜性模型的稳健性。水文评估表明长期平均潜在水量平衡为正值，达27.69 mm·年⁻¹，表明水资源足以支撑MAR。三次双环入渗试验得出的平均野外饱和导水率为1.92 m·天⁻¹（范围：1.86–1.96 m·天⁻¹），表明第四系冲积沉积物具有高入渗能力。地下水矿化度保持在1 g·L⁻¹以下，水文地质调查确认存在厚度为50 m的第四系冲积含水层，适宜开展MAR。长期日河流流量记录表明潜在年补给量为1744万m³，仅占有效含水层储水容量（74680万m³）的2.33%，显示出巨大的储水潜力。区域适宜性评估与野外调查之间的高度一致性表明，该多尺度框架大幅降低了基于GIS的MAR场地识别中的不确定性。通过将区域适宜性制图与水文","Frontiers in Water","2026-10-16T00:00:00Z",{"impact":72,"substance":72,"depth":72,"authority":72,"freshness":72,"relevant":72,"comment":103},"该研究聚焦哈萨克斯坦半干旱区地下水回灌选址，属于水文地质领域，与三农、农业信息化、智慧农业无直接关联，不建议进入每日精选。",[105],{"name":100,"url":97},[27,65,29],[],{"status":33,"locked":14,"version":34,"method":35,"evidence":109},{"candidates":110,"agricultural_evidence":14,"reason":67},[111,117,122],{"code":55,"score":112,"supported":41,"title":113,"abstract":114,"tags":116},9,[],[58,115,59],"GIS",[],{"code":62,"score":49,"supported":41,"title":118,"abstract":119,"tags":121},[],[65,120],"water resource",[65],{"code":48,"score":49,"supported":41,"title":123,"abstract":124,"tags":125},[],[27,52],[27],[127,128],"哈萨克斯坦 地下水回灌","Zhetysu Alatau 含水层","哈萨克斯坦地下水回灌-5169","10.3389\u002Ffrwa.2026.1932313",{"doi":130,"openalex_id":132,"authors":133,"venue":100,"cited_by_count":72,"oa_url":155,"card":156,"direction":161,"ingested_from":90},"W7222733682",[134,137,140,143,146,149,152],{"name":135,"orcid":136},"Zhuldyzbek Onglassynov","https:\u002F\u002Forcid.org\u002F0000-0002-3587-5996",{"name":138,"orcid":139},"S. A. Kulbekova","https:\u002F\u002Forcid.org\u002F0000-0001-9796-7338",{"name":141,"orcid":142},"Raushan Amanzholova","https:\u002F\u002Forcid.org\u002F0000-0001-9129-1074",{"name":144,"orcid":145},"Aldiyar Abyshev","https:\u002F\u002Forcid.org\u002F0000-0001-9788-7485",{"name":147,"orcid":148},"Айгерим Алимгазина","https:\u002F\u002Forcid.org\u002F0009-0002-9966-5549",{"name":150,"orcid":151},"И.К. Рахметов","https:\u002F\u002Forcid.org\u002F0000-0002-6269-7734",{"name":153,"orcid":154},"Malis K. Absametov","https:\u002F\u002Forcid.org\u002F0000-0003-2520-6294","https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fwater\u002Farticles\u002F10.3389\u002Ffrwa.2026.1932313\u002Fpdf",{"tldr":157,"method":158,"finding":159,"direction":87,"opportunity":160},"构建多尺度框架，结合GIS筛选与野外验证，识别哈萨克斯坦半干旱区地下水回补场地。","GIS-AHP、蒙特卡洛模拟、模糊伽马分析、遥感、LiDAR与野外入渗试验。","区域高适宜区占21.82%，野外验证入渗能力高、含水层厚50米，回补潜力大。","可将多尺度“筛选—验证”范式迁移至农业区地下水回补与灌溉补水选址，结合作物需水与遥感蒸散。","农业遥感与作物表型","2026-10-17T23:30:28.555087Z",{"id":164,"title":165,"url":166,"summary":167,"summary_zh":168,"content":9,"source_name":169,"source_url":166,"published_at":170,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":171,"score_detail":172,"sources":177,"tags":179,"primary_topic":183,"secondary_topics":188,"classification":189,"search_phrases":211,"slug":214,"view_count":207,"doi":215,"paper":216,"created_at":231},4593,"Climate Resilience and the Hydro-Vegetal Paradox in El Bayadh Province (Algeria, 1984-2023)","https:\u002F\u002Fdoi.org\u002F10.56093\u002Faaz.v65i3.177509","The decade 2010 to 2020 was the warmest ever recorded in the Mediterranean basin (+1.5°C), exceeding the global average. North Africa, identified as a vulnerability hotspot by the IPCC AR6, experiences intensified droughts and ecosystem degradation. This study presents the first quantitative assessment of climate resilience in El Bayadh Province (Algeria), revealing an unexpected hydro-vegetal paradox. A comparative multi-index methodology (restricted climate index vs. global index integrating 7 variables) was applied to 22 municipalities over the period of 1984 to 2023. The results showed a universal degradation of water balance (-8.2 to -21.4 mm yr-1) and widespread warming (+0.8 to +2.1°C decade-1). Paradoxically, 73 to 77% of municipalities showed improvement in vegetation indices (NDVI, SAVI), suggesting ecological adaptation. Principal component analysis (PCA-99%) variance explained) identified water stress as the main differentiating factor, and clustering distinguishes 5 territorial profiles (silhouette = 0.521). The global index proves more discriminant than the restricted index for capturing the complexity of socio-ecological dynamics. This study highlights the need for differentiated adaptation policies addressing challenges related to water, food security, and migration.","2010年至2020年是有记录以来地中海盆地最暖的十年（升温+1.5°C），超过了全球平均水平。北非被IPCC第六次评估报告（AR6）确定为脆弱性热点地区，正经历着加剧的干旱和生态系统退化。本研究首次对阿尔及利亚埃尔贝伊德省（El Bayadh Province）的气候韧性进行了定量评估，揭示了一个意想不到的水文-植被悖论。研究采用比较多指标方法（限制性气候指数与整合7个变量的全局指数），对22个市镇在1984年至2023年期间进行了分析。结果表明，水平衡普遍退化（-8.2至-21.4 mm yr⁻¹），且普遍升温（+0.8至+2.1°C decade⁻¹）。悖论的是，73%至77%的市镇植被指数（NDVI、SAVI）有所改善，表明存在生态适应。主成分分析（PCA，方差解释率达99%）确定水分胁迫为主要区分因子，聚类分析区分出5种地域类型（轮廓系数=0.521）。在捕捉社会-生态动态复杂性方面，全局指数比限制性指数更具判别力。本研究强调了制定差异化适应政策的必要性，以应对与水、粮食安全和移民相关的挑战。","Annals of Arid Zone","2026-10-08T00:00:00Z",74,{"impact":173,"substance":174,"depth":18,"authority":175,"freshness":112,"relevant":22,"comment":176},12,22,13,"基于22个市镇40年多指标遥感数据的干旱区气候韧性定量研究，方法新颖、结论有反差价值，但属区域案例研究，公共影响层级有限。",[178],{"name":169,"url":166},[180,181,182,28,30],"NDVI","气候适应","遥感监测",{"code":39,"slug":184,"name":185,"path":186,"parent_code":187},"climate","气候适应与防灾减灾","\u002Ftopic\u002Fenvironment\u002Fclimate","H",[],{"status":190,"locked":14,"version":34,"method":35,"evidence":191},"classified",{"candidates":192,"agricultural_evidence":41},[193,199,206],{"code":39,"score":194,"supported":41,"title":195,"abstract":197,"tags":198},16,[196],"climate resilience",[45,196],[28,181],{"code":200,"score":20,"supported":41,"title":201,"abstract":202,"tags":205},"A8",[],[203,204],"粮食安全","food security",[],{"code":48,"score":207,"supported":14,"title":208,"abstract":209,"tags":210},2,[],[],[180,182],[212,213],"El Bayadh 阿尔及利亚 气候韧性","NDVI 植被指数 干旱区","ElBayadh阿尔及利亚气候韧性-4593","10.56093\u002Faaz.v65i3.177509",{"doi":215,"openalex_id":217,"authors":218,"venue":169,"cited_by_count":72,"oa_url":225,"card":226,"direction":161,"ingested_from":90},"W7220949140",[219,222],{"name":220,"orcid":221},"Lakhdar Guérine","https:\u002F\u002Forcid.org\u002F0000-0003-0836-2703",{"name":223,"orcid":224},"Naîmi Bendouina","https:\u002F\u002Forcid.org\u002F0000-0002-9776-1660","http:\u002F\u002Fepubs.icar.org.in\u002Findex.php\u002FAAZ\u002Farticle\u002Fdownload\u002F177509\u002F68050",{"tldr":227,"method":228,"finding":229,"direction":161,"opportunity":230},"首次量化阿尔及利亚El Bayadh省1984-2023年气候韧性，揭示水-植被悖论。","多指标对比法（限制性气候指数与7变量全球指数），对22个市镇做PCA和聚类。","水均衡普遍恶化、升温显著，但73-77%市镇植被指数改善，呈生态适应悖论。","可探究干旱区NDVI改善的驱动机制（灌溉、物种更替或遥感尺度效应），并耦合社会经济数据。","2026-10-10T23:30:29.597640Z",{"id":233,"title":234,"url":235,"summary":236,"summary_zh":9,"content":9,"source_name":237,"source_url":235,"published_at":238,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":239,"score_detail":240,"sources":244,"tags":246,"primary_topic":9,"secondary_topics":250,"classification":251,"search_phrases":269,"slug":272,"view_count":21,"doi":273,"paper":274,"created_at":285},3175,"Assessing the reliability of remote sensing-based evapotranspiration models for enhanced water management under center-pivot irrigation system in arid region. Case study: East Oweinat, Egypt","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs40899-026-01401-0","Assessing the reliability of remote sensing-based evapotranspiration models for enhanced water management under center-pivot irrigation system in arid region. Case study: East Oweinat, Egypt。Sustainable Water Resources Management","Sustainable Water Resources Management","2026-09-21T00:00:00Z",71,{"impact":173,"substance":241,"depth":242,"authority":175,"freshness":112,"relevant":22,"comment":243},20,17,"埃及干旱区中心支轴灌溉下遥感蒸散发模型可靠性评估，方法扎实但属区域案例研究，对国内智慧灌溉有参考价值。",[245],{"name":237,"url":235},[27,247,248,249,28],"水资源管理","精准灌溉","蒸散发",[],{"status":33,"locked":14,"version":34,"method":35,"evidence":252},{"candidates":253,"agricultural_evidence":14,"reason":67},[254,261,265],{"code":62,"score":255,"supported":41,"title":256,"abstract":259,"tags":260},25,[257,258],"irrigation","evapotranspiration",[257,258],[247,248,249],{"code":48,"score":173,"supported":41,"title":262,"abstract":263,"tags":264},[52],[52],[27],{"code":39,"score":22,"supported":14,"title":266,"abstract":267,"tags":268},[],[],[28],[270,271],"East Oweinat 中心支轴灌溉","遥感 蒸散发 模型 灌溉管理","EastOweinat中心支轴灌溉-3175","10.1007\u002Fs40899-026-01401-0",{"doi":273,"openalex_id":275,"authors":276,"venue":237,"cited_by_count":72,"oa_url":9,"card":9,"direction":161,"ingested_from":90},"W7213900869",[277,279,281,283],{"name":278,"orcid":9},"Hadeel A. Ibrahim",{"name":280,"orcid":9},"Mohamed H. Elgamal",{"name":282,"orcid":9},"Ashraf M. Ghanem",{"name":284,"orcid":9},"Mohamed H. Nour","2026-09-22T23:30:23.383931Z",{"id":287,"title":288,"url":289,"summary":290,"summary_zh":291,"content":9,"source_name":292,"source_url":289,"published_at":293,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":294,"score_detail":295,"sources":297,"tags":299,"primary_topic":9,"secondary_topics":303,"classification":304,"search_phrases":340,"slug":343,"view_count":207,"doi":344,"paper":345,"created_at":356},2168,"From soil loss to sediment delivery: GeoAI-enhanced RUSLE modeling of erosion and sediment dynamics in a hyper-arid watershed","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffeart.2026.1893163","In the delineated watershed containing Wadi Samnan near Az Zulfi, Saudi Arabia, soil erosion is a local management concern because sparse vegetation, erodible sandy surface materials, escarpment-influenced terrain, and episodic rainfall events can concentrate runoff and sediment movement along wadi channels and drainage corridors. These conditions make it difficult to identify erosion-prone zones using field observations alone, particularly in data-scarce hyper-arid environments. This study presents a GeoAI-enhanced RUSLE-based framework to model water-induced soil loss and sediment delivery dynamics in the study watershed. The Revised Universal Soil Loss Equation (RUSLE) was integrated with geospatial datasets, remote sensing products, digital elevation model-derived terrain attributes, and machine-learning-based spatial analysis to estimate the spatial distribution of water-induced erosion risk. Rainfall erosivity, soil erodibility, topographic influence, land-cover conditions, and conservation-practice factors were derived and mapped within a GIS environment. In addition, the Sediment Delivery Ratio (SDR) was incorporated to evaluate relative sediment-delivery potential and improve the interpretation of how estimated hillslope soil loss may be transferred into sediment yield within the drainage system. The results show that RUSLE-derived potential soil-loss estimates ranged from 0 to 319.5 t ha -1 yr -1 , with the slight erosion class covering 43.2% of the watershed and modeled severe-erosion hotspots covering 10.9%. High-risk areas were mainly concentrated along steep slopes, drainage corridors, sparsely vegetated surfaces, and erodible sandy soils. SDR results indicated low overall sediment connectivity, with approximately 85%–99% of eroded material likely retained locally within the watershed, depending on the spatially varying SDR values. The Random Forest internal consistency analysis explained 81.73% of the variance in RUSLE-derived soil-loss estimates, indicating that the input factors captured much of the modeled spatial variability; however, this result should not be interpreted as independent field validation. Overall, the integration of RUSLE, SDR, remote sensing, GIS, and GeoAI provides a useful framework for identifying erosion-prone zones, distinguishing soil-loss potential from sediment-delivery potential, prioritizing conservation interventions, and supporting sustainable watershed management in hyper-arid environments.","在沙特阿拉伯祖尔菲附近萨姆南干谷所在的划定流域内，土壤侵蚀是当地管理关注的问题，因为稀疏植被、易侵蚀的砂质表层物质、受崖坡影响的地形以及偶发性降雨事件会将径流和泥沙运动集中沿干谷河道和排水廊道输送。这些条件使得仅凭野外观测难以识别侵蚀易发区，尤其是在数据稀缺的极端干旱环境中。本研究提出了一种GeoAI增强的RUSLE框架，用于模拟研究流域内水力驱动的土壤流失和泥沙输移动态。修正通用土壤流失方程（RUSLE）与地理空间数据集、遥感产品、数字高程模型衍生的地形属性以及基于机器学习的空间分析相结合，以估算水力侵蚀风险的空间分布。降雨侵蚀力、土壤可蚀性、地形影响、土地覆盖条件和保护措施因子在GIS环境中被导出并制图。此外，引入泥沙输移比（SDR）以评估相对泥沙输移潜力，并改进对坡面土壤流失估算值如何转化为排水系统内产沙量的解释。结果表明，RUSLE衍生的潜在土壤流失估算值范围为0至319.5 t ha⁻¹ yr⁻¹，其中轻度侵蚀等级覆盖流域面积的43.2%，模拟的严重侵蚀热点区域覆盖10.9%。高风险区主要集中在陡坡、排水廊道、植被稀疏地表和易侵蚀砂质土壤沿线。SDR结果表明整体泥沙连通性较低，约85%–99%的侵蚀物质可能就地滞留于流域内，具体取决于空间变化的SDR值。随机森林内部一致性分析解释了RUSLE衍生土壤流失估算值中81.73%的方差，表明输入因子捕捉了大部分模拟的空间变异性；然而，该结果不应被解释为独立的野外验证。总体而言，RUSLE、SDR、遥感、GIS和GeoAI的整合为识别侵蚀易发区、区分土壤流失潜力与泥沙输移潜力、优先安排保护干预措施以及支持极端干旱环境中的可持续流域管理提供了一个有用的框架。","Frontiers in Earth Science","2026-09-09T00:00:00Z",66,{"impact":17,"substance":241,"depth":242,"authority":175,"freshness":17,"relevant":22,"comment":296},"GeoAI融合RUSLE与SDR模型量化超干旱流域侵蚀与泥沙输移，方法新颖、数据扎实，但属区域案例研究，对国内三农实践的直接价值有限。",[298],{"name":292,"url":289},[300,27,301,28,302],"农业人工智能","水土保持","流域治理",[],{"status":33,"locked":14,"version":34,"method":35,"evidence":305},{"candidates":306,"agricultural_evidence":14,"reason":67},[307,314,320,324,329,335],{"code":308,"score":19,"supported":41,"title":309,"abstract":311,"tags":313},"H2",[310],"soil",[312,310],"土壤",[],{"code":55,"score":112,"supported":41,"title":315,"abstract":316,"tags":319},[],[317,115,318],"空间分析","spatial analysis",[],{"code":48,"score":49,"supported":41,"title":321,"abstract":322,"tags":323},[],[27,52],[27],{"code":39,"score":325,"supported":41,"title":326,"abstract":327,"tags":328},4,[],[45],[28],{"code":330,"score":325,"supported":41,"title":331,"abstract":332,"tags":334},"I2",[],[333],"机器学习",[300],{"code":336,"score":22,"supported":14,"title":337,"abstract":338,"tags":339},"H6",[],[],[301],[341,342],"农业人工智能 干旱区农业 水土保持 流域治理","农业人工智能 干旱区农业","农业人工智能干旱区农业水土保持流域治理-2168","10.3389\u002Ffeart.2026.1893163",{"doi":344,"openalex_id":346,"authors":347,"venue":292,"cited_by_count":72,"oa_url":350,"card":351,"direction":161,"ingested_from":90},"W7212020416",[348],{"name":349,"orcid":9},"Ali R. Alruzuq","https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fearth-science\u002Farticles\u002F10.3389\u002Ffeart.2026.1893163\u002Fpdf",{"tldr":352,"method":353,"finding":354,"direction":161,"opportunity":355},"用GeoAI增强RUSLE与SDR模型，评估沙特超干旱流域土壤侵蚀与泥沙输移空间格局。","RUSLE结合遥感、DEM、GIS与随机森林空间分析，并引入泥沙输移比SDR。","侵蚀量0–319.5 t\u002Fha\u002Fyr，严重区占10.9%，约85%–99%侵蚀物就地滞留。","可将GeoAI-RUSLE-SDR框架迁移至数据稀缺区，结合实地监测验证并耦合泥沙连通性指数。","2026-09-11T23:30:31.280278Z",{"id":358,"title":359,"url":360,"summary":361,"summary_zh":362,"content":9,"source_name":363,"source_url":360,"published_at":364,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":171,"score_detail":365,"sources":367,"tags":369,"primary_topic":372,"secondary_topics":377,"classification":378,"search_phrases":405,"slug":408,"view_count":72,"doi":409,"paper":410,"created_at":421},5588,"Certified Temporal Fusion of Artificial Intelligence Climate Analytics for Crop Failure Early Warning Under Sparse Agricultural Sensors: Error Bounds and Famine Relief Targeting","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23545489","Sparse agricultural sensor networks across sub-Saharan Africa leave crop-failure early-warning systems with too little ground observation to support reliable famine relief targeting. The framework treats sensor sparsity as a missing-data problem with a known observation operator and propagates climate-analytics uncertainty through a temporal Kalman-Buys filter whose gain is constrained by a certified risk envelope. Using NASA POWER monthly reanalysis for Accra, Ghana (2000-2023, 312 observations), the analysis establishes a mean temperature of 26.521 C and a warming trend of 0.1622 C per decade, which calibrates the climate-analytics prior. The derived bounds show that relief-targeting error scales with the square root of sensor density and with the Lipschitz constant of the crop-response function, yielding an explicit sensor-placement rule for a target misclassification rate. The contribution is a certified, assumption-explicit bridge between climate analytics and famine relief targeting that states the conditions under which early warning is trustworthy.","撒哈拉以南非洲稀疏的农业传感器网络使得作物歉收预警系统缺乏足够的地面观测数据，难以支撑可靠的饥荒救援目标定位。该框架将传感器稀疏性视为具有已知观测算子的缺失数据问题，并通过时间Kalman-Buys滤波器传播气候分析不确定性，该滤波器的增益受经认证的风险包络约束。利用NASA POWER对加纳阿克拉的月度再分析数据（2000—2023年，312个观测值），分析确定了平均气温为26.521°C、每十年0.1622°C的增暖趋势，据此校准了气候分析先验。推导出的界限表明，救援目标定位误差随传感器密度的平方根以及作物响应函数的Lipschitz常数缩放，从而为目标误分类率给出了明确的传感器布设规则。该研究的贡献在于构建了一个经认证的、假设明确的气候分析与饥荒救援目标定位之间的桥梁，阐明了早期预警可信赖的条件。","Zenodo (CERN European Organization for Nuclear Research)","2026-10-21T00:00:00Z",{"impact":173,"substance":174,"depth":18,"authority":173,"freshness":13,"relevant":22,"comment":366},"该研究提出一种带误差界认证的时序融合方法，用于稀疏传感器条件下的作物歉收预警与饥荒救援瞄准，方法新颖、结论明确，但案例局限于加纳阿克拉，产业影响有限，适合作为技术前沿条目收录。",[368],{"name":363,"url":360},[370,300,203,27,371],"智慧农业","气候分析",{"code":330,"slug":373,"name":374,"path":375,"parent_code":376},"agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai","I",[],{"status":190,"locked":14,"version":34,"method":35,"evidence":379},{"candidates":380,"agricultural_evidence":41},[381,386,392,396,401],{"code":330,"score":112,"supported":41,"title":382,"abstract":384,"tags":385},[383],"artificial intelligence",[],[300],{"code":387,"score":21,"supported":41,"title":388,"abstract":389,"tags":391},"I5",[],[390],"农业传感",[],{"code":200,"score":22,"supported":14,"title":393,"abstract":394,"tags":395},[],[],[203],{"code":397,"score":22,"supported":14,"title":398,"abstract":399,"tags":400},"I1",[],[],[370],{"code":48,"score":22,"supported":14,"title":402,"abstract":403,"tags":404},[],[],[27],[406,407],"NASA POWER 加纳 气候分析","作物歉收 早期预警 传感器","NASAPOWER加纳气候分析-5588","10.5281\u002Fzenodo.23545489",{"doi":409,"openalex_id":411,"authors":412,"venue":363,"cited_by_count":72,"oa_url":360,"card":415,"direction":420,"ingested_from":90},"W7223111766",[413],{"name":414,"orcid":9},"Fatima-Zahra El Khattabi",{"tldr":416,"method":417,"finding":418,"direction":161,"opportunity":419},"提出带误差界的时间融合框架，在稀疏传感器下用气候分析预警作物歉收。","卡尔曼-布西滤波+NASA POWER再分析数据，风险包络约束增益。","救济瞄准误差随传感器密度平方根和作物响应Lipschitz常数缩放，给出布点规则。","可将该认证误差界框架扩展到多作物多区域，结合卫星遥感弥补地面传感器稀疏。","农业人工智能与决策模型","2026-10-22T11:21:02.682497Z",{"id":423,"title":424,"url":425,"summary":426,"summary_zh":9,"content":9,"source_name":427,"source_url":425,"published_at":364,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":428,"score_detail":429,"sources":431,"tags":433,"primary_topic":437,"secondary_topics":441,"classification":442,"search_phrases":454,"slug":457,"view_count":72,"doi":458,"paper":459,"created_at":475},5579,"A Composite Field-Evaluation Framework for Digital Agriculture Maps","https:\u002F\u002Fdoi.org\u002F10.21203\u002Frs.3.rs-11283264\u002Fv1","A Composite Field-Evaluation Framework for Digital Agriculture Maps。Research Square","Research Square",38,{"impact":17,"substance":20,"depth":17,"authority":20,"freshness":13,"relevant":22,"comment":430},"预印本提出数字农业地图的田间复合评估框架，方法有一定新意，但摘要信息极少、未经同行评审，公共影响有限，暂不宜进入每日精选。",[432],{"name":427,"url":425},[434,435,27,436],"数字农业","农业信息化","地图评估",{"code":397,"slug":438,"name":439,"path":440,"parent_code":376},"smart-agriculture","智慧农业总论","\u002Ftopic\u002Fdigital-agriculture\u002Fsmart-agriculture",[],{"status":190,"locked":14,"version":34,"method":35,"evidence":443},{"candidates":444,"agricultural_evidence":41},[445,450],{"code":397,"score":175,"supported":41,"title":446,"abstract":448,"tags":449},[447],"digital agriculture",[447],[435,434],{"code":48,"score":22,"supported":14,"title":451,"abstract":452,"tags":453},[],[],[27],[455,456],"Research Square 数字农业","农业信息化 地图评估 数字农业 遥感","ResearchSquare数字农业-5579","10.21203\u002Frs.3.rs-11283264\u002Fv1",{"doi":458,"openalex_id":460,"authors":461,"venue":427,"cited_by_count":72,"oa_url":425,"card":9,"direction":474,"ingested_from":90},"W7223099987",[462,465,468,471],{"name":463,"orcid":464},"Phillip Lanza","https:\u002F\u002Forcid.org\u002F0000-0002-5545-1744",{"name":466,"orcid":467},"David G. Rossiter","https:\u002F\u002Forcid.org\u002F0000-0003-4558-1286",{"name":469,"orcid":470},"Diana Stuart Sinton","https:\u002F\u002Forcid.org\u002F0000-0001-5828-9001",{"name":472,"orcid":473},"Louis Longchamps","https:\u002F\u002Forcid.org\u002F0000-0002-4761-6094","数字乡村与农业信息化","2026-10-22T11:20:47.463814Z"]