Article(id=1311351167569986460, tenantId=1146029695717560320, journalId=1205116964453384197, issueId=1311351152067830064, articleNumber=null, orderNo=null, doi=10.20040/j.cnki.1000-7709.2026.20250440, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1741622400000, receivedDateStr=2025-03-11, revisedDate=1744387200000, revisedDateStr=2025-04-12, acceptedDate=1744819200000, acceptedDateStr=2025-04-17, onlineDate=1790580082075, onlineDateStr=2026-09-28, pubDate=1769270400000, pubDateStr=2026-01-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1790580082075, onlineIssueDateStr=2026-09-28, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1790580082075, creator=13701087609, updateTime=1790580082075, updator=13701087609, issue=Issue{id=1311351152067830064, tenantId=1146029695717560320, journalId=1205116964453384197, year='2026', volume='44', issue='1', pageStart='1', pageEnd='246', issueExtLink='null', onlineDate='null', pubDate='1769270400000', pubDateStr='2026-01-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1790580078378, creator='13701087609', updateTime=1790588459421, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1311386304772927717, tenantId=1146029695717560320, journalId=1205116964453384197, issueId=1311351152067830064, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1311386304772927718, tenantId=1146029695717560320, journalId=1205116964453384197, issueId=1311351152067830064, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=29, endPage=32, ext={EN=ArticleExt(id=1311351167758730141, articleId=1311351167569986460, tenantId=1146029695717560320, journalId=1205116964453384197, language=EN, title=Multi-factors Risk Assessment of Agricultural Drought at the County Level Across China Based on Regional Disaster System Theory, columnId=null, journalTitle=Water Resources and Power, columnName=null, runingTitle=null, highlight=null, articleAbstract=

Agricultural drought risk assessment is the prerequisite for agricultural drought risk management. Crop growth is highly vulnerable to threats from natural disasters such as droughts, floods, and typhoons, with drought-induced losses accounting for over 50% of the total agricultural natural disaster losses. Based on the regional natural disaster system theory, this study constructs an agricultural drought disaster risk assessment indicator system comprising three components of hazard, vulnerability, and exposure. A total of 22 indicators including annual precipitation were selected. The study adopts county-level administrative regions across China as research units and integrates the fuzzy comprehensive evaluation method to establish the agricultural drought disaster risk assessment framework. The results indicate that the spatial distribution of drought hazard is significantly correlated with annual precipitation, showing a trend of higher hazard in the northwest and lower in the southeast. Provinces with the highest vulnerability include Heilongjiang, Guizhou, and Ningxia, while Guangdong and Zhejiang exhibit the lowest vulnerability due to their strong economic resilience and low disaster impact indices. Henan, Hebei, Heilongjiang, and Ningxia demonstrate higher comprehensive drought risk ratings owing to high agricultural exposure levels. In contrast, regions such as Qinghai, Tibet, Fujian, and Zhejiang exhibit the lowest risk levels due to smaller agricultural scales or abundant water resources. This research can provide a basis for targeted agricultural disaster prevention and mitigation strategies.

, authors=Yuan LI, authorsList=Yuan LI, authorCompany=null, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1311351168052331422, articleId=1311351167569986460, tenantId=1146029695717560320, journalId=1205116964453384197, language=CN, title=基于区域灾害系统论的全国县级农业旱灾多要素风险评估, columnId=1207627659488632924, journalTitle=水电能源科学, columnName=水文水资源与环境, runingTitle=null, highlight=null, articleAbstract=

农业旱灾风险评估是农业旱灾风险管理的前提，农作物生长易受干旱、洪涝、台风等自然灾害威胁，其中旱灾导致的损失占农业自然灾害总损失的50%以上。基于区域自然灾害系统理论，构建了包含危险性、脆弱性和暴露性三要素的农业旱灾风险评估指标体系，共选取年降水量等22个指标因子，在全国范围内以县级行政区为研究单元，结合模糊综合评判法构建了农业旱灾风险指标评估体系。结果表明，旱灾危险性空间分布与年均降水量显著相关，呈现西北高、东南低的趋势；脆弱性最高的省份为黑龙江、贵州和宁夏，而广东、浙江因经济水平高且受灾指数低，脆弱性最低；河南、河北、黑龙江及宁夏因农业暴露度高，旱灾风险综合评级较高；青海、西藏、福建和浙江等地因农业规模较小或水资源充沛，风险等级最低。研究成果可为有针对性地制定农业防灾减灾政策提供依据。

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李远（1991-），男，工程师，研究方向为水利工程，E-mail: liyuan_hydro@163.com

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李远（1991-），男，工程师，研究方向为水利工程，E-mail: liyuan_hydro@163.com

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