Abstract
Applying disaster system theory and with reference to the mechanisms that underlie agricultural drought risk, in this study, crop yield loss levels were determined on the basis of hazards and environmental and hazard-affected entities (crops). Thus, by applying agricultural drought risk assessment methodologies, the spatiotemporal distribution of maize drought risk was assessed at the national scale. The results of this analysis revealed that the overall maize drought risk decreases gradually along a northwest-to-southeast transect within maize planting areas, a function of the climatic change from arid to humid, and that the highest yield loss levels are located at values between 0.35 and 0.45. This translates to drought risks of once in every 10 and 20 years within 47.17% and 43.31% of the total maize-producing areas of China, respectively. Irrespective of the risk level, however, the highest maize yield loss rates are seen in northwestern China. The outcomes of this study provide the scientific basis for the future prevention and mitigation of agricultural droughts as well as the rationalization of related insurance.
Highlights
In disasters, risk is de ned as the probability of loss and depends on three factors: hazards, vulnerability, and exposure. is means that if the magnitude of any one of these factors changes, the risk will correspondingly increase or decrease [1,2,3]
standardized precipitation index (SPI) values for maize crop growth periods are used as the drought hazard index. is index of SPI has been commonly utilized for characterizing droughts [46], mainly because it is spatially invariant and is a reliable indicator for comparing one location with another. us, following reference [45], drought intensity was classified into four categories: “normal,” “moderately dry,” “severely dry,” and “extremely dry.”
Values of the SPI were calculated in this study by fitting a gamma probability distribution to interpolated rainfall fields; the corresponding cumulative rainfall probabilities were transformed to a standardized normal distribution using a mean of zero and a variance of one, with monthly and three-monthly time periods considered sufficient to preserve intra-annual variability. e results of the three-month SPI analysis are presented for simplicity
Summary
Risk is de ned as the probability of loss and depends on three factors: hazards, vulnerability, and exposure. is means that if the magnitude of any one of these factors changes, the risk will correspondingly increase or decrease [1,2,3]. More researchers agree on the risk expression of the United Nations ISDR (International Strategy of Disaster Reduction) [6, 7]. With the increase in frequency of extreme events, the management of extreme climate events based on risk assessment becomes an academic research hot spot [8]. Disaster risk assessment and management in China has been the focus of considerable research attention since the country’s participation in the International Decade for Natural Disaster Reduction. E results of studies carried out to date have both enriched the overall scope of natural disaster research and played a role in disaster management [16,17,18,19,20,21,22,23]. Natural disaster risk assessment tends to be integrated from the perspective of disaster
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