Risk assessment of drought disaster in the maize-growing region of Songliao Plain, China

Author(s):  
J Zhang
2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Menghua Deng ◽  
Junfei Chen ◽  
Guiyun Liu ◽  
Huimin Wang

A new model for risk assessment of drought based on projection pursuit optimized by immune evolutionary algorithm and information diffusion method (IEAPP-IDM) was proposed. Due to the fact that drought risk assessment is a complex multicriteria and multilevel problem, the IEAPP-IDM model can project the multidimensional indicators of samples into one-dimension projection scores; then, the information carried by the projection scores was diffused into drought risk levels; finally, the drought disaster risk estimate was obtained. In the present study, Qujing was employed to assess the drought risk with the proposed model. The results showed that Xuanwei possessed higher risk, while Luliang and Zhanyi possessed lower risk. At the same time, the probability risk of drought in Malong and Luoping was increasing, while the probability risk of drought in in Qilin and Shizong was decreasing. The results obtained by the assessment model are consistent with the actual situation of Qujing and verify the model’s effectiveness. The study can provide scientific reference in drought risk management for Qujing and other places of China.


2016 ◽  
Vol 128 (3-4) ◽  
pp. 533-540 ◽  
Author(s):  
Qi Zhang ◽  
Jiquan Zhang ◽  
Chunyi Wang

Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 1089
Author(s):  
Menglu Chen ◽  
Shaowei Ning ◽  
Juliang Jin ◽  
Yi Cui ◽  
Chengguo Wu ◽  
...  

In recent years, drought disaster has occurred frequently in China, causing significant agricultural losses. It is increasingly important to assess the risk of agricultural drought disaster (ADD) and to develop a targeted risk management approach. In this study, an ADD risk assessment model was established. First, an improved fuzzy analytic hierarchy process based on an accelerated genetic algorithm (AGA-FAHP) was used to build an evaluation indicator system. Then, based on the indicators, the ADD assessment connection numbers were established using the improved connection number method. Finally, the entropy information diffusion method was used to form an ADD risk assessment model. The model was applied to the Huaibei Plain in Anhui Province (China), with the assessment showing that, in the period from 2008 to 2017, the plain was threatened continuously by ADD, especially during 2011–2013. The risk assessment showed that southern cities of the study area were nearly twice as likely to be struck by ADD as northern cities. Meanwhile, the eastern region had a higher frequency of severe and above-grade ADD events (once every 21 years) than the western region (once every 25.3 years). Therefore, Huainan was identified as a high-risk city and Huaibei as a low-risk city, with Suzhou and Bengbu more vulnerable to ADD than Fuyang and Bozhou. Understanding the spatial dynamics of risk in the study area can improve agricultural system resilience by optimizing planting structures and by enhancing irrigation water efficiency. This model could be used to provide support for increasing agricultural drought disaster resilience and risk management efficiency.


2011 ◽  
Vol 61 (2) ◽  
pp. 785-801 ◽  
Author(s):  
Lu Hao ◽  
Xiaoyu Zhang ◽  
Shoudong Liu

2021 ◽  
Vol 193 (7) ◽  
Author(s):  
Zhenghua Hu ◽  
Zhurong Wu ◽  
Yixuan Zhang ◽  
Qi Li ◽  
A. R. M. Towfiqul Islam ◽  
...  

Author(s):  
Ping Ai ◽  
Binbin Chen ◽  
Dingbo Yuan ◽  
Min Hong ◽  
Hongwei Liu

Abstract The dynamic risk assessment of drought is crucial in the transition from the crisis management model to the risk management model, which can reveal the evolution mechanism of drought disasters. Due to a lack of data and research perspectives, most current studies are still based on static risk assessment. This study proposes a conceptual model for the dynamic risk assessment of droughts based on the probability of their occurrence and potential impacts. The developed dynamic risk index considers the hazard, exposure, vulnerability, and capacity for drought mitigation. The analytic hierarchy process (AHP) method was used to determine the weight coefficient of each indicator in the model. The novelty of the proposed model lies in the integration of four elements of drought disasters with spatiotemporal characteristics. Jiangxi Province, which is frequently affected by drought, was selected as the study area to validate the proposed model. Experimental results demonstrate that the proposed model rapidly reflects the degree of drought disaster risk caused by drought events and the influencing factors at monthly and annual scales. Moreover, the datasets based on the influencing factors of drought disasters in different regions have a good commonality in the proposed model.


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