[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-3711":3,"related-3711":38},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":8,"published_at":11,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":24,"tags":26,"search_phrases":32,"slug":35,"view_count":36,"doi":8,"paper":8,"created_at":37},3711,"黄淮海气候韧性农业关键技术在山东泰安集成示范","https:\u002F\u002Fnews.sciencenet.cn\u002Fhtmlnews\u002F2026\u002F9\u002F572040.shtm","9月19日中国农业科学院重大科技任务黄淮海气候韧性农业关键技术研发与示范现场观摩会在山东泰安召开。围绕精准预警、韧性品种、韧性农田、防控减损、快速重建五维联动技术体系，开展气象灾害监测预警决策平台与无人机、农业机器人、智能灌排协同集成应用。",null,"9月19日，中国农业科学院重大科技任务“黄淮海气候韧性农业关键技术研发与示范”现场观摩及任务推进研讨会在山东省泰安市召开。会上集中展示了夏玉米抗逆品种、韧性农田、抗逆产品、智能装备及技术集成应用，交流研究进展，为黄淮海粮食主产区防灾减损、稳产增效提供科技支撑。会议由中国农业科学院农业环境与可持续发展研究所组织。\n\n科技赋能抗逆增产——黄淮海气候韧性农业抗逆产品制剂与品种展示。中国农科院供图\n\n黄淮海是我国小麦、玉米重要产区，高温热害、旱涝急转、连阴雨渍涝等灾害给粮食稳产带来挑战。任务团队围绕“精准预警—韧性品种—韧性农田—防控减损—快速重建”五维联动技术体系，将灾害预警与品种选用、农田改良、栽培管理和应急措施相结合，着力提升农业生产灾前预防、灾中减损和灾后恢复能力。\n\n在洼里村示范区，与会代表实地观摩生态基础设施、技术验证试验和集成示范田，听取示范区建设及关键技术应用情况介绍。示范区依托已有高标准农田，将生态沟渠、灌排一体、水肥一体化等设施与抗逆品种、农艺调控、应急防控等技术配套应用，探索工程设施与农艺措施相结合的韧性农田建设路径。在技术验证和集成示范田，任务团队通过单项技术与集成技术的对比试验，评价不同技术组合的抗逆减损效果，为优化夏玉米全生育期防灾措施提供依据。\n\n围绕打造“天空地”一体化农业防灾减灾智慧体系，任务团队将气象灾害监测预警决策平台与田间监测、无人机、农业机器人、智能灌排等技术装备协同集成，探索形成“灾害感知—智能研判—精准决策—快速响应”的智慧防灾链条。平台可开展高温、干旱等气象灾害风险识别和防控措施推送，无人机及农业机器人可开展灾情勘查、精准施肥、抗逆喷施和应急作业，智能灌排装备根据田间水分状况开展快速调控，推动农业防灾减灾由经验判断、被动应对向智能感知、主动防控转变。\n\n智慧引领精准防控——“天空地”一体化农业智能机器人装备演示。中国农科院供图\n\n此次观摩集中呈现了重大任务4个子任务协同攻关的阶段性进展。任务团队将灾害智能监测评估、韧性新种质与耕作栽培、韧性农田与抗逆产品等研究成果集成应用于田间，推动“天上看、地上测、平台算、装备干”相互衔接，逐步形成从灾前预警、灾中防控到灾后恢复的全链条技术体系，促进单项技术向系统化、智能化综合防控方案转变。\n\n会议期间，任务团队汇报了总体实施进展和各子任务研究情况，与会专家围绕技术集成效果、区域适配和示范推广等进行交流，并就后续任务实施提出意见建议。下一步，任务团队将继续开展黄淮海不同区域的技术验证与模式优化，推进标准化技术规程编制，推动成熟适用技术推广应用。\n\n有关管理部门、任务咨询专家、涉农高校和科研院所，以及当地农业农村部门、气象部门、科技部门、示范基地、新型农业经营主体和任务团队代表共50余人参加会议。\n\n版权声明：凡本网注明“来源：中国科学报、科学网、科学新闻杂志”的所有作品，网站转载，请在正文上方注明来源和作者，且不得对内容作实质性改动；微信公众号、头条号等新媒体平台，转载请联系授权。邮箱：shouquan@stimes.cn。","科学网","2026-09-24T01:29:00Z","报道",10,false,75,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},22,18,15,14,6,1,"国家级科研机构在黄淮海主产区集成示范气候韧性农业技术，含五维技术体系与天空地一体化智慧防灾链条，信息增量与专业深度较好，但属阶段性进展通报，时效性一般。",[25],{"name":10,"url":6},[27,28,29,30,31],"智慧农业","智能装备","防灾减灾","黄淮海","气候韧性农业",[33,34],"中国农科院 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Al-Mamun","openalex","2026-09-27T23:30:05.905976Z",{"id":82,"title":83,"url":84,"summary":85,"summary_zh":8,"content":86,"source_name":87,"source_url":8,"published_at":88,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":89,"score_detail":90,"sources":92,"tags":94,"search_phrases":98,"slug":101,"view_count":36,"doi":8,"paper":8,"created_at":102},3298,"给黄淮海粮仓穿上韧性铠甲——气候韧性农业关键技术在泰安集成示范 天空地一体化防灾减灾智慧体系","https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7687548454628934183\u002F","9月19日，中国农业科学院重大科技任务黄淮海气候韧性农业关键技术研发与示范现场观摩及任务推进研讨会在山东省泰安市召开。会议由中国农业科学院农业环境与可持续发展研究所组织，集中展示夏玉米抗逆品种、韧性农田、抗逆产品、智能装备及技术集成应用。任务团队围绕精准预警-韧性品种-韧性农田-防控减损-快速重建五维联动技术体系；将气象灾害监测预警决策平台与田间监测、无人机、农业机器人、智能灌排等技术装备协同集成，探索形成灾害感知-智能研判-精准决策-快速响应的智慧防灾链条。","## 给黄淮海粮仓穿上“韧性铠甲”，气候韧性农业关键技术在泰安集成示范\n\n2026-09-20 17:34·[环球网](https:\u002F\u002Fwww.toutiao.com\u002Fc\u002Fuser\u002Ftoken\u002FMS4wLjABAAAAvazHMceCo3MeM9IJbll231AC8GkJDcrd__iZFw2hi4o\u002F?source=tuwen_detail)\n\n来源：光明网\n\n9月19日，中国农业科学院重大科技任务“黄淮海气候韧性农业关键技术研发与示范”现场观摩及任务推进研讨会在山东省泰安市召开。会议由中国农业科学院农业环境与可持续发展研究所组织，集中展示夏玉米抗逆品种、韧性农田、抗逆产品、智能装备及技术集成应用，交流研究进展，为黄淮海粮食主产区防灾减损、稳产增效提供科技支撑。\n\n![Image 1](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-axegupay5k\u002F773d1e55ea7b4e80a25316e3d4f211dd~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1790813084&x-signature=%2FwW2BjSLM%2Bxd3IuWn4nYgT2shBg%3D)\n黄淮海是我国小麦、玉米重要产区，高温热害、旱涝急转、连阴雨渍涝等灾害给粮食稳产带来挑战。任务团队围绕“精准预警—韧性品种—韧性农田—防控减损—快速重建”五维联动技术体系，将灾害预警与品种选用、农田改良、栽培管理和应急措施相结合，着力提升农业生产灾前预防、灾中减损和灾后恢复能力。\n\n![Image 2](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-tjoges91tu\u002Fbbc85b32abae7b6d222913ed10ae7445~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1790813084&x-signature=QpqQYDixKmzRAC0uFz%2FufwlrTcg%3D)\n在洼里村示范区，与会代表实地观摩生态基础设施、技术验证试验和集成示范田，听取示范区建设及关键技术应用情况介绍。示范区依托已有高标准农田，将生态沟渠、灌排一体、水肥一体化等设施与抗逆品种、农艺调控、应急防控等技术配套应用，探索工程设施与农艺措施相结合的韧性农田建设路径。在技术验证和集成示范田，任务团队通过单项技术与集成技术的对比试验，评价不同技术组合的抗逆减损效果，为优化夏玉米全生育期防灾措施提供依据。\n\n围绕打造“天空地”一体化农业防灾减灾智慧体系，任务团队将气象灾害监测预警决策平台与田间监测、无人机、农业机器人、智能灌排等技术装备协同集成，探索形成“灾害感知—智能研判—精准决策—快速响应”的智慧防灾链条。平台可开展高温、干旱等气象灾害风险识别和防控措施推送，无人机及农业机器人可开展灾情勘查、精准施肥、抗逆喷施和应急作业，智能灌排装备根据田间水分状况开展快速调控，推动农业防灾减灾由经验判断、被动应对向智能感知、主动防控转变。\n\n![Image 3](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-tjoges91tu\u002Ff5f20f31849251e940e92ed03f700553~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1790813084&x-signature=Ve3OHh9%2F3vnEQtj%2BUvRxRpxSiwU%3D)\n此次观摩集中呈现了重大任务4个子任务协同攻关的阶段性进展。任务团队将灾害智能监测评估、韧性新种质与耕作栽培、韧性农田与抗逆产品等研究成果集成应用于田间，推动“天上看、地上测、平台算、装备干”相互衔接，逐步形成从灾前预警、灾中防控到灾后恢复的全链条技术体系，促进单项技术向系统化、智能化综合防控方案转变。\n\n![Image 4](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-tjoges91tu\u002F5e260517533470ce1d78d4b76482a704~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1790813084&x-signature=OPXutMF2cywkqxZD3uf92C249yM%3D)\n会议期间，任务团队汇报了总体实施进展和各子任务研究情况，与会专家围绕技术集成效果、区域适配和示范推广等进行交流，并就后续任务实施提出意见建议。下一步，任务团队将继续开展黄淮海不同区域的技术验证与模式优化，推进标准化技术规程编制，推动成熟适用技术推广应用。\n\n有关管理部门、任务咨询专家、涉农高校和科研院所，以及当地农业农村部门、气象部门、科技部门、示范基地、新型农业经营主体和任务团队代表共50余人参加会议。（宋雅娟）","光明网（今日头条转载） 2026年09月20日","2026-09-20T09:34:00Z",74,{"impact":17,"substance":18,"depth":19,"authority":51,"freshness":21,"relevant":22,"comment":91},"国家级科研任务在黄淮海主产区的集成示范，五维联动与天空地智慧防灾体系有实质技术增量，值得进入每日精选。",[93],{"name":87,"url":84},[30,31,95,96,97],"天空地一体化","智慧防灾","韧性农田",[99,100],"中国农业科学院 黄淮海 气候韧性农业","泰安 天空地一体化 防灾减灾","中国农业科学院黄淮海气候韧性农业-3298","2026-09-24T00:03:59.088634Z",{"id":104,"title":105,"url":106,"summary":107,"summary_zh":8,"content":108,"source_name":109,"source_url":8,"published_at":110,"category":12,"cover_url":8,"hotness":111,"is_selected":14,"score":89,"score_detail":112,"sources":114,"tags":119,"search_phrases":122,"slug":125,"view_count":36,"doi":8,"paper":8,"created_at":126},3111,"江苏省农科院院长朱艳出席 2026 世界农业科技创新大会作\"建设气候韧性农业：中国江苏的经验与策略\"主旨演讲","https:\u002F\u002Fhome.jaas.ac.cn\u002Fznbmxwlsml\u002Fgjhzc\u002Fart\u002F2026\u002Fart_a07fcd60380d494c9ac02c215708d7ea.html","9-15 至 19 2026 年世界农业科技创新大会（WAFI）在北京举行，江苏农科院院长朱艳应邀出席世界农业科学家论坛作主旨演讲。朱艳以\"建设气候韧性农业：中国江苏的经验与策略\"为题分享\"前沿育种—良法配套—智慧赋能\"路径：精准培育气候适应型品种重点创制耐高温耐盐碱节水型优质耐逆种质；精细化开展农艺管理集成示范\"麦—稻周年大面积丰产增效技术体系\"；AI 融入全环节智能管控，构建作物系统模拟模型研发粮食作物逆境灾害动态预警与定量评估技术；分享与 CGIAR、AgMIP 等海外科教机构和国际组织联合开展应对气候变化国际合作进展。","9月15日至19日，2026年世界农业科技创新大会（WAFI）在北京举行。大会以“农食系统绿色健康转型”为主题，由中国农业大学、平谷区人民政府、北京市农业农村局和国际农业研究磋商组织（CGIAR）共同主办。会议期间，院长、党委副书记朱艳应邀出席世界农业科学家论坛并作主旨演讲。\n\n[![Image 1: A3017F2F331F7F14DEFC59D29D081BB5.jpg](https:\u002F\u002Fhome.jaas.ac.cn\u002Fcms_files\u002Ffilemanager\u002F191335345\u002Fpicture\u002F20268\u002FSa52f10e390324c7b9184546c22090621-800.jpg)](https:\u002F\u002Fhome.jaas.ac.cn\u002Fcms_files\u002Ffilemanager\u002F191335345\u002Fpicture\u002F20268\u002Fa52f10e390324c7b9184546c22090621.jpg)\n\n朱艳以“建设气候韧性农业：中国江苏的经验与策略”为题重点分享了我省在应对气候变化挑战探索出的“前沿育种—良法配套—智慧赋能”路径。一是精准培育气候适应型品种，重点创制耐高温、耐盐碱、节水型优质耐逆种质，育成了一批高产抗逆的水稻、小麦及大豆等新品种，并加快建设江苏省农业种质资源综合基因库，筑牢应对气候变化的“种质”防线。二是精细化开展农艺管理，集成示范“麦—稻周年大面积丰产增效技术体系”，推广水稻集中育秧、小麦适期晚播等避灾技术，同时落实轮作休耕等绿色制度，打好可持续的气候适应“组合拳”。三是AI融入全环节智能管控，构建作物系统模拟模型，研发粮食作物逆境灾害动态预警与定量评估技术，覆盖稻麦全链条生产管理，形成应对气候变化的智慧体系。她还分享了我院与国际农业研究磋商组织（CGIAR）、国际农业模型比较与改进项目（AgMIP）等海外科教机构和国际组织联合开展应对气候变化的国际合作进展。\n\n朱艳表示，江苏省农业科学院愿与全球农业科学家一道，推动建立应对气候变化的全球知识共享平台，贡献更多可复制、可推广的“江苏方案”。\n\n[![Image 2: 朱院-世界农业科技创新大会2.jpg](https:\u002F\u002Fhome.jaas.ac.cn\u002Fcms_files\u002Ffilemanager\u002F191335345\u002Fpicture\u002F20268\u002FS4a20548ff6c34efe97426fb6933e1a41-800.jpg)](https:\u002F\u002Fhome.jaas.ac.cn\u002Fcms_files\u002Ffilemanager\u002F191335345\u002Fpicture\u002F20268\u002F4a20548ff6c34efe97426fb6933e1a41.jpg)\n\n世界农业科技创新大会（WAFI）由北京市委市政府发起，以“创新农业 共享未来”为宗旨，聚焦促进全球农食系统转型的前沿创新，深入推动产学研互动和国际交流合作。自2023年启动以来，大会已成功举办4届，联合国粮农组织、世界粮食计划署等国际机构深度参与，赢得国内外同仁的高度认可，已成为全球农业科技领域具有实质影响力的高端对话平台之一。","江苏省农业科学院","2026-09-18T06:56:00Z",25,{"impact":17,"substance":18,"depth":19,"authority":51,"freshness":21,"relevant":22,"comment":113},"省级农科院院长在国际大会分享气候韧性农业的江苏路径，内容具体、有国际合作信息，但属会议报道，时效略过，可作主题聚合素材而非头条精选。",[115,116],{"name":109,"url":106},{"name":117,"url":118},"江苏省农业科学院 2026年09月","https:\u002F\u002Fjaas.ac.cn\u002Fznbmxwlsml\u002Fgjhzc\u002Fart\u002F2026\u002Fart_a07fcd60380d494c9ac02c215708d7ea.html",[27,57,120,121,31],"种业振兴","国际合作",[123,124],"江苏省农科院 气候韧性农业","朱艳 WAFI 主旨演讲","江苏省农科院气候韧性农业-3111","2026-09-22T00:05:36.089846Z",{"id":128,"title":129,"url":130,"summary":131,"summary_zh":8,"content":132,"source_name":133,"source_url":8,"published_at":134,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":48,"score_detail":135,"sources":139,"tags":141,"search_phrases":145,"slug":148,"view_count":36,"doi":8,"paper":8,"created_at":149},1839,"秋粮主产区打好田间管理组合拳 分类施策全力以赴确保粮食丰产归仓","https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7681217168805052943\u002F","山东德州天衢新区赵虎镇1300亩玉米田铺设毛细血管般密集滴灌带，应用水肥一体化节水节肥均30%，预计亩均增产300斤；河南中部农田在9190万元救灾资金支撑下运用多光谱无人机进行智能体检和飞防；财政部和农业农村部已下达农业生产防灾救灾资金20.37亿元支持一喷多促。","## 秋粮主产区打好田间管理“组合拳” 分类施策全力以赴确保粮食丰产归仓\n\n2026-09-03 16:05·[北青网](https:\u002F\u002Fwww.toutiao.com\u002Fc\u002Fuser\u002Ftoken\u002FMS4wLjABAAAAkBInTefEXGPcS0avMIcyzcyDIb8T8hL6gUlrrWDJxIw\u002F?source=tuwen_detail)\n\n央视网消息：眼下，全国大部分秋粮正值灌浆期，主产区分类施策，加强田间管理，全力夺取丰收。\n\n![Image 1](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-axegupay5k\u002F65a56d2a6a6b4e34b08e7aea1684de39~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1789430857&x-signature=zP8NhPM%2B5KRq0Fsi%2BUZYNgzfw6A%3D)\n农业农村部最新农情调度显示，2026年，全国秋粮播种面积预计稳中略增。目前，除局部地区受灾外，大部分秋粮长势良好。 在山东德州天衢新区赵虎镇的高标准农田里，这片1300亩的玉米田里铺设着如毛细血管般密集的黑色滴灌带，在手机App上点开开关，滴灌带可以精准地将水肥送到玉米根系。 2026年，山东大力推广水肥一体化技术，面积达到930万亩，增产趋势明显。 山东省德州市天衢新区赵虎镇种植户刘杰超介绍，他们应用水肥一体化，节水节肥都在30%，预计产量每亩会增加300斤，整体收益大概会多收入39万元。 作为粮油作物大面积单产提升的关键举措，全国水肥一体化应用面积，在2025年达到8800万亩的基础上，2026年持续增加。\n\n![Image 2](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-tjoges91tu\u002Fbed4b5aa6d903868be667ba1c533bd7e~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1789430857&x-signature=AkUhh%2Ffb4JUI87EPkj7z2nxvgns%3D)\n在黑龙江宝清县，65厘米的小垄拓宽成了110厘米的大垄，不仅种得更多，分布也更均匀，光、热、水、肥利用率同步提升，作物长势明显优于周边地块。 黑龙江省双鸭山市宝清县五九七农场有限公司农业发展部副部长李龙介绍，这块地每亩播量是6000株，保苗率在97%以上。 受前期降雨影响，河南中部部分农田受灾。当地在用好9190万元中央农业生产救灾资金的基础上，派出6个专家组指导农田恢复生产。在漯河，搭载高清成像的多光谱无 人机，对受灾地块进行了智能“体检”，随后开展无 人机飞防预防病虫害滋生扩散。\n\n![Image 3](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-tjoges91tu\u002Fed7be700bf580f06660201a6cec4ae8c~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1789430857&x-signature=2Z5OzHZB9y%2FbccgnAd0pFkL6ufU%3D)\n目前，距离全国秋粮大面积收获还有不到一个月的时间。受台风多发以及高温高湿天气的影响，南方水稻主产区、黄淮海主产区病虫害发生风险增加，农业农村部指导各地做好病虫害防治，并采取叶面喷施等防灾减灾稳产增产技术，全力以赴确保秋粮安全成熟。","央视网\u002F北青网 2026-09-03","2026-09-03T08:05:00Z",{"impact":111,"substance":50,"depth":19,"authority":136,"freshness":137,"relevant":22,"comment":138},12,5,"全国秋粮主产区田间管理综合报道，涵盖水肥一体化、大垄密植等增产技术，数据详实，来源权威，时效性稍差。",[140],{"name":133,"url":130},[27,29,142,143,144],"秋粮生产","水肥一体化","田间管理",[146,147],"水肥一体化 智慧农业 田间管理 秋粮生产","水肥一体化 智慧农业","水肥一体化智慧农业田间管理秋粮生产-1839","2026-09-08T00:07:11.044134Z",{"id":151,"title":152,"url":153,"summary":154,"summary_zh":8,"content":8,"source_name":155,"source_url":8,"published_at":156,"category":12,"cover_url":8,"hotness":13,"is_selected":157,"score":158,"score_detail":159,"sources":164,"tags":166,"search_phrases":168,"slug":171,"view_count":172,"doi":8,"paper":8,"created_at":173},1542,"国务院副总理刘国中赴内蒙古调研：紧盯秋粮田管、推动智慧农业发展、抓好防灾减灾","https:\u002F\u002Fszb.farmer.com.cn\u002Fnmrb\u002Fhtml\u002F2026\u002F20260904\u002F20260904_1\u002Fnmrb_20260904_13396_1_2095622475098460171.html","据新华社呼和浩特 9 月 3 日电，中共中央政治局委员、国务院副总理刘国中 9 月 1 日至 3 日赴内蒙古通辽科左中旗等地调研。他强调，秋粮占全年粮食产量 3\u002F4，要分区分类科学开展田管、抓紧落实\"一喷多促\"、推进良田良种良机良法集成增效；立足抗灾夺丰收，加强监测预警与应急农机具储备调度；发挥农民合作社等新型经营主体作用，发展社会化服务；要加快人工智能运用和智慧农业发展，积极选育突破性品种、推广密植精准调控等先进适用技术、加力研发高端智能与丘陵山区适用农机装备；要稳慎推进第二轮土地承包到期后再延长 30 年试点；强化农业节水增效，深化农业水价综合改革、推广水肥一体化、浅埋滴灌。","农民日报头版头条","2026-09-03T22:00:00Z",true,90,{"impact":160,"substance":17,"depth":161,"authority":19,"freshness":162,"relevant":22,"comment":163},28,16,9,"副总理调研强调智慧农业与防灾减灾，政策导向明确，信息权威且时效性强。",[165],{"name":155,"url":153},[27,57,167,29,142],"高标准农田",[169,170],"农业人工智能 高标准农田 智慧农业 秋粮生产","农业人工智能 高标准农田","农业人工智能高标准农田智慧农业秋粮生产-1542",2,"2026-09-04T00:05:29.693313Z",{"id":175,"title":176,"url":177,"summary":178,"summary_zh":179,"content":8,"source_name":180,"source_url":177,"published_at":181,"category":47,"cover_url":8,"hotness":13,"is_selected":14,"score":48,"score_detail":182,"sources":185,"tags":187,"search_phrases":190,"slug":193,"view_count":36,"doi":194,"paper":195,"created_at":214},1437,"SFNL-Former: A Novel Spatial-Frequency Non-local Network for Precipitation Forecast","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.rcradv.2026.200381","ABSTRACT Accurate, high-resolution precipitation forecast is vital for urban disaster mitigation and agriculture, underpinning fine-grained social management. Furthermore, as the primary input to the terrestrial hydrological cycle, its accurate quantification is essential for sustainable water resource management and efficient circulation. However, this task remains highly challenging due to the complex spatiotemporal and non-linear dynamical evolution inherent in atmospheric processes. Deep learning has been extensively applied to weather forecast through CNN-RNN or Transformer architectures, yet these methods often struggle to capture global meteorological motions while simultaneously preserving the fine-grained details of localized strong convection. Furthermore, they are prone to producing blurred predictions or exhibiting high false alarm rates when encountering extreme precipitation events characterized by long-tailed distributions. To address these issues, we propose the Spatial-Frequency and Non-Local Former Network (SFNL-Former), which accurately predicts complex precipitation evolution via explicit spatial-frequency domain feature separation and efficient long-range spatiotemporal modeling. A Spatial-Frequency Domain Attention (SFDA) encoder is designed to separately extract low-frequency global backgrounds and high-frequency local textures of precipitation fields. Furthermore, the Locality-Sensitive Hashing (LSH) based Non-Local Sparse-Aware Transformer (NLSAT) is introduced to capture long-range spatiotemporal dependencies with linear complexity. Experiments on real-world datasets demonstrate that SFNL-Former outperforms existing baseline methods across multiple metrics and spatial scales. Specifically, under challenging high-intensity precipitation thresholds, the model improves the Critical Success Index and substantially reduces the False Alarm Rate, while maintaining optimal prediction coherence. Consequently, the framework enables critical decision support for proactive disaster response, fostering more resilient social management systems under future extreme weather scenarios.","准确、高分辨率的降水预报对于城市灾害缓解和农业至关重要，是精细化管理的基础。此外，作为陆地水文循环的主要输入，其精确量化对于可持续水资源管理和高效循环至关重要。然而，由于大气过程固有的复杂时空和非线性动力学演变，这一任务仍极具挑战性。深度学习已通过CNN-RNN或Transformer架构广泛应用于天气预报，但这些方法往往难以在捕捉全球气象运动的同时保留局部强对流的细粒度细节。此外，在面对以长尾分布为特征的极端降水事件时，它们容易产生模糊预测或表现出高误报率。为解决这些问题，我们提出了空间频率与非局部Former网络（SFNL-Former），通过显式的空间频率域特征分离和高效的长距离时空建模，准确预测复杂的降水演变。设计了一种空间频率域注意力（SFDA）编码器，分别提取降水场的低频全局背景和高频局部纹理。此外，引入了基于局部敏感哈希（LSH）的非局部稀疏感知Transformer（NLSAT），以线性复杂度捕捉长距离时空依赖性。在真实数据集上的实验表明，SFNL-Former在多个指标和空间尺度上均优于现有基线方法。具体而言，在具有挑战性的高强度降水阈值下，该模型提高了关键成功指数并大幅降低了误报率，同时保持了最优的预测一致性。因此，该框架能够为主动灾害响应提供关键决策支持，在未来极端天气情景下促进更具韧性的社会管理系统。","Resources Conservation & Recycling Advances","2026-09-01T00:00:00Z",{"impact":18,"substance":17,"depth":18,"authority":136,"freshness":183,"relevant":22,"comment":184},7,"论文提出SFNL-Former模型提升降水预报精度，对农业防灾有应用价值，方法新颖，数据可靠。",[186],{"name":180,"url":177},[27,57,29,188,189],"深度学习","降水预报",[191,192],"农业人工智能 智慧农业 深度学习 防灾减灾","农业人工智能 智慧农业","农业人工智能智慧农业深度学习防灾减灾-1437","10.1016\u002Fj.rcradv.2026.200381",{"doi":194,"openalex_id":196,"authors":197,"venue":180,"cited_by_count":36,"oa_url":206,"card":207,"direction":213,"ingested_from":79},"W7204864017",[198,200,203],{"name":199,"orcid":8},"Hanjie Wang",{"name":201,"orcid":202},"Xinyue Mo","https:\u002F\u002Forcid.org\u002F0000-0002-4685-3645",{"name":204,"orcid":205},"Huan Li","https:\u002F\u002Forcid.org\u002F0000-0002-7683-2589","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS2667378926000702\u002Fpdf",{"tldr":208,"method":209,"finding":210,"direction":211,"opportunity":212},"提出SFNL-Former网络，通过空间-频率分离和长程建模提升降水预报精度。","空间-频率域注意力编码器与基于LSH的非局部稀疏感知Transformer。","在高强度降水阈值下，CSI提升且误报率显著降低，预测一致性最优。","农业人工智能与决策模型","可探索将SFNL-Former应用于农业区域精细化降水预报，结合多源数据提升极端天气下的农业灾害预警能力。","农业遥感与作物表型","2026-09-02T23:30:51.395339Z"]