摘要
探讨了干旱分区及农业旱灾风险区划的方法,并在云南省开展了应用研究。选取流域地貌特征指数、多年平均干旱指数和75%保证率年降雨量负距平百分率指标,采用主成分分析法对云南省进行干旱自然分区进行了研究;将干旱分区成果作为旱灾风险区划指标之一,综合考虑旱灾风险危险性、脆弱性及易损性因素建立了旱灾风险区划指标体系,并根据多层次模糊综合评估结果进行了云南农业旱灾风险区划研究。结果表明,滇东北是干旱易发区,滇西南是干旱轻发区或少发区;滇东北属于旱灾高风险区,滇西北属于旱灾低风险区。分区成果与云南省的历史干旱情况基本符合,表明基于主成分的干旱自然分区和基于构成要素的旱灾风险区划方法是可行的。
The method of drought partition and agricultural drought risk zoning were investigated, and Yunnan province was selected as a pilot to apply the presented methods. Firstly, three indicators, including topographical features index, average years of drought indices and negative anomaly percentage of 75% guarantee rate at annu- al level, were selected as the drought partition index, then the principal component analysis method was applied to describe drought natural partition of Yunnan province. While, drought partition consequent was used as the one of drought risk zoning index, synthetically considering drought risk hazard, fragility and vulnerability factors as the common constitutions of agricultural drought risk zoning index system. Moreover, multi-level fuzzy compre- hensive evaluation results were employed to synthetic agricultural drought risk zoning of Yunnan province. The results showed that the northeast of Yunnan province was the drought prone areas, which was more prone to drought than that of the southwest and belonged to the drought light-prone areas or less-prone areas. The north- east of Yunnan province was the high drought risk area, however, the northwest was the low drought risk area. The above consequences were basically consistent with the actual drought situation of Yunnan province. These showed that drought natural partition based on principal component method and drought risk zoning by the ele- ments in the practical application had certain feasibility and practicability.
出处
《灌溉排水学报》
CSCD
北大核心
2017年第2期44-51,共8页
Journal of Irrigation and Drainage
基金
湖北省教育厅科学技术研究项目(B2015255)
国家科技支撑计划项目(2013BAB06B01)
国家重点研发计划项目(2016YFC0402208)
三峡大学科学基金项目(KJ2013B072)
关键词
干旱分区
主成分分析法
旱灾风险区划
模糊综合评判
ARCGIS
drought partition
Principal Component Analysis
agricultural drought risk zoning
fuzzy comprehen-sive evaluation
ArcGIS