China Meteorological Administration Researchers Advance Knowledge in Risk Management (Identification and Risk Characteristics of Agricultural Drought Disaster Events Based on the Copula Function in Northeast China): Risk Management

Insurance Daily News

2022 SEP 12 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- Research findings on risk management are discussed in a new report. According to news reporting from Shenyang, People’s Republic of China, by NewsRx journalists, research stated, “Accurate feature identification of drought disaster events is required for proper risk management in agriculture. This study improved the crop water deficit index (CWDI) by including the daily meteorological, crop development stage, soil moisture content, and yield data for 1981-2020 in northeastern China.”

Financial supporters for this research include Fundamental Scientific Research Business Expenses of Central-level Public Welfare Scientific Research Institutes.

Our news reporters obtained a quote from the research from China Meteorological Administration: “Two drought characteristic variables (drought duration and intensity) were extracted using the theory of runs to produce the improved crop water deficit index (CWDIwp). Thresholds for the bivariate indicators were also determined for agricultural drought events of varying severity. A joint distribution model for drought variables was constructed based on five types of Archimedean copulas. The joint probability and the joint recurrence period for agricultural drought events were analyzed for drought events with varying intensities in northeast China. The results suggest that the CWDIwp can reliably identify the onset, duration, and intensity of drought events over the study area and can be used to monitor agricultural drought events. The conditional probability of drought intensity (duration) decreased as the drought duration (intensity) threshold increased, whereas the drought recurrence period increased as the threshold for drought duration and intensity rose. In the period (1981-2020), drought intensity in the three Northeastern provinces showed an increasing trend in the order Jilin Province > Liaoning Province > Heilongjiang Province. The spatial distribution of the joint probability and the joint recurrence period was obvious, and the joint probability showed a decreasing distribution trend from west to east. The distribution trend for the joint probability was opposite to that of the joint recurrence period. Furthermore, the areas with high drought probability values corresponded to the areas with low values for the recurrence period, indicating that the drought occurrence probability was higher, and the recurrence period value was lower in the drought-prone areas. The high-risk drought areas (60-87%) were in western Liaoning and western Jilin, with a recurrence period of 1-3 years, whereas the low-risk areas (<40%) were located in the mountainous areas of eastern Liaoning and eastern Jilin. The joint probability and joint recurrence period for agricultural drought events of varying severity were quite different, with the probability following the order light drought > moderate drought > severe drought > extreme drought.”

According to the news editors, the research concluded: “The order for the recurrence period was light drought < moderate drought < severe drought < extreme drought. The results provide technical support for disaster prevention and mitigation in drought risk management.”

For more information on this research see: Identification and Risk Characteristics of Agricultural Drought Disaster Events Based on the Copula Function in Northeast China. Atmosphere, 2022,13(1234):1234. (Atmosphere - http://www.mdpi.com/journal/atmosphere/). The publisher for Atmosphere is MDPI AG.

A free version of this journal article is available at https://doi.org/10.3390/atmos13081234.

Our news journalists report that more information may be obtained by contacting Shujie Zhang, Institute of Atmospheric Environment, China Meteorological Administration, Shenyang 110166, People’s Republic of China. Additional authors for this research include Ping Wang, Dongni Wang, Yushu Zhang, Ruipeng Ji, Fu Cai.