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粮食核心区建设是河南省建设中原经济区的核心战略之一,而气候变化背景下各种气象灾害的频繁发生对其提出了严峻的挑战,其中,旱灾是河南发生频率最高的自然灾害。采用基于信息扩散理论的风险评估模型对河南省自1971年以来的旱灾危害从致灾和承灾两个层面进行评估,从而给出不同程度旱灾发生的可能性,为河南省粮食核心区战略地位的提升及灾害防治提供理论依据。研究结果表明:从承灾层面来看,受灾风险等级远高于成灾风险等级;受(成)灾面积指数一般不超过50%和30%,该受(成)灾面积指数下的风险概率值分别达到0.001和0.0006;受(成)灾风险概率小于3年一遇的面积指数分别为25%和10%;5%、10%、15%、20%成灾面积指数下的风险估计值分别为0.76、0.39、0.16和0.10,即分别为1.3年、2.6年、6.1年和9.8年一遇;从致灾层面来看,偏旱的估计值为0.110,即约9年一遇,在此等级下,分别对应受(成)灾面积指数为35%和20%。评估结果与河南省农业气象旱灾发生的实际情况基本吻合,表明应用此模型对信息量不足的自然灾害进行风险性评估是科学可行的。
The construction of grain core area is one of the core strategies of Henan Province in building Central Plains Economic Zone. However, the frequent occurrence of various meteorological disasters under the background of climate change poses a serious challenge to them. Among them, drought is the most frequent natural disaster in Henan. Based on the risk assessment model based on information diffusion theory, this paper evaluates the hazard of flood disaster in Henan Province since 1971 from the aspects of disaster and disaster bearing, and gives the possibility of different degrees of drought disaster, which is the strategic position of Henan Grain Core District Provide a theoretical basis for the promotion and disaster prevention. The results show that: from the aspect of disaster prevention, the risk level of disaster risk is far higher than the disaster risk level; the risk index of affected area is less than 50% and 30% Respectively. The area indices with the probability of disaster risk less than 3 years are 25% and 10%, respectively. The estimated risk under the disaster area index of 5%, 10%, 15% and 20% Namely 0.76, 0.39, 0.16 and 0.10 respectively, that is 1.3 years, 2.6 years, 6.1 years and 9.8 years respectively. From the aspect of disaster-induced aspect, the estimation of drought-relief is 0.110, which is about once every 9 years. Under this rank, corresponding to (by) disaster area index of 35% and 20% respectively. The results are in good agreement with the actual situation of agrometeorological drought in Henan Province, which shows that it is scientifically feasible to apply this model to the risk assessment of natural disasters with insufficient information.