Risk evaluation of natural disasters based on connection function

There are many uncertain factors,such as stochastic,fuzzy and gray information in the risk analysis on natural hazard.The set pair analysis(SPA)deals effectively with the various uncertain factors contributing to evaluation of the risk level of natural disasters.The evaluation indicators and standards of natural disasters risk are analyzed by identity-discrepancycontrary(IDC).The result,the connection numbers,still has uncertainty information.Thus,yielding the risk evaluation model of natural disasters based on connection function,which construct a set pair relation between the indicators of connection numbers and comprehensive evaluation standards,and describe uncertainty of the connection numbers by using connection function.The study showed that the proposed model takes into account only the uncertainty of risk evaluation indicator identification on natural disasters,also the uncertainty of result connection numbers.This approach gives full consideration to the uncertainty of systematic evaluation process along with the actual meaning of comprehensive evaluation functions.Therefore,this means it is able to reduce the uncertainty of final evaluation results and improve the accuracy and reasonability of evaluation results.This model is capable of reflecting actual situation of the risk evaluation on natural disaster affected by various uncertain factors and has a promotional value in the natural disaster risk assessment.

Assessment of Agricultural Drought Vulnerability Based on Crop Growth Stages:A Case Study of Huaibei Plain,China

Climate change can lead to and intensify drought disasters.Quantifying the vulnerability of disaster-affected elements is significant for understanding the mechanisms that transform drought intensity into eventual loss.This study proposed a growth-stage-based drought vulnerability index(GDVI)of soybean using meteorological,groundwater,land use,and field experiment data and crop growth model simulation.The CROPGRO-Soybean model was used to simulate crop growth and water deficit.Four growth stages were considered since the sensitivity of soybean to drought is strictly related to the growth stage.The GDVI was applied to the Huaibei Plain,Anhui Province,China,with the goal of quantifying the spatiotemporal characteristics of soybean drought vulnerability in typical years and growth stages.The results show that:(1)The sensitivity of leaf-related parameters exceeded that of other parameters during the vegetative growth stage,whereas the top weight and grain yield showed a higher sensitivity in the reproductive growth stage;(2)A semi-logarithmic law can describe the relationship between the drought sensitivity indicators and the GDVI during the four growth stages.The pod-filling phase is the most vulnerable stage for water deficit and with the highest loss upper limit(over 70%);(3)The 2001 and 2002 seasons were the driest time during 1997-2006.Fuyang and Huainan Cities were more vulnerable to drought than other regions on the Huaibei Plain in 2001,while Huaibei and Suzhou Cities were the most susceptible areas in 2002.The results could provide effective decision support for the categorization of areas vulnerable to droughts.