Risk Assessment of Agricultural Drought Disaster on the Huaibei Plain of China Based on the Improved Connection Number and Entropy Information Diffusion Method
2. Study Area
3.1. Development of an Evaluation Indicator System
- The disaster breeding environment, including precipitation, evaporation, and amount of water resources. It is the average value from the year in question to 10 years prior.
- The disaster factors, including annual average temperature and shallow groundwater depth. The 12-month Standardized Precipitation Index (SPI) was calculated using monthly rainfall data from 1983 to 2017 provided by the six national weather stations located in the six cities.
- The disaster affected body, including the area of grain planting, cultivated land, dry land, and drought-affected land, along with the value of agricultural production, agricultural water consumption, and total grain output.
- Disaster prevention and mitigation measures, including the area of effective irrigated land, per capita disposable income of rural households, and water supply capacity for drought-resistant water sources.
3.2. Evaluation Method
3.2.1. Determination of the Weight of the Agricultural Drought Evaluation Indicators
3.2.2. Assessment of Agricultural Drought Disaster
3.2.3. Risk Assessment of Agricultural Drought Disaster
4.1. Weight Analysis of Evaluation Indicators of ADD of the Huaibei Plain in Anhui Province
4.2. Assessment of Agricultural Drought Disaster of the Huaibei Plain
4.3. Risk Assessment of Agricultural Drought Disaster for the Huaibei Plain
- Using weight analysis, the disaster factors and the disaster affected body were found to be key elements of the agricultural drought disaster system in small units such as the Huaibei Plain. It was also found that the average annual precipitation from the year in question to 10 years prior (X1), 12-month SPI (X4), the annual average temperature (X5), water consumption per kilogram of grain production (X10), percentage of drought-affected area (X11), and rate of effective irrigation area (X12) are more important than other indicators in their corresponding subsystems.
- Based on a comprehensive analysis of the connection numbers CN (r, i) for the Huaibei Plain from 2008 to 2017, five cities (except Huaibei) had a mild to moderate degree of ADD in the period assessed. The conditions during 2011–2013 were relatively serious, especially in 2013. The chance of ADD in the southern area, represented by Fuyang, Huainan, and Bengbu, was greater than in the northern area, represented by Bozhou and Huaibei. Furthermore, ADD in the southern region was more serious than in the north.
- The frequency of ADD for each city is mainly once every 1–3 years, and, with an increased agricultural drought disaster index value, the frequency is significantly reduced. The frequency of severe and above-grade ADD is once every 10–30 years. The risk of ADD for the Huaibei Plain is characterized by frequent, mainly mild to moderate risk, making prevention and control measures key for effective risk management of natural disasters in the future.
- The southern region of the study area was found to be nearly twice as likely to be struck by ADD as the northern region. Meanwhile, the eastern region has a higher frequency of severe and above-grade events than the western region. The frequency of ADD is once every 2.8 years for Huaibei, which is lower than the average value of the southern four cities. Huainan, in contrast, has a frequency of severe and above-grade ADD of once every 11 years. Based on the risk assessment results above, the cities of the Huaibei Plain were ranked from high to low risk as: Huainan > Bengbu > Suzhou > Fuyang > Bozhou > Huaibei.
- In this study, some suggestions were proposed for ADD prevention and mitigation based on the analysis of risk assessment results and the background of disaster formation. It is necessary for high-risk cities in the study area, such as Huainan and Bengbu, to improve the resilience of their agricultural systems in the future by optimizing planting structures and enhancing irrigation water efficiency. These results confirm overall that the proposed method is feasible and effective and that the results are reasonable.
Conflicts of Interest
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|Evaluation Indicator||Connection Numbers||Agricultural Drought Disaster Index||Agricultural Drought Disaster|
|g||CN (r, i)||si|
|1||[0, 2.5]||[0, 0.5]||No drought|
|2||(2.5, 3]||(0.5, 0.6]||Grade I (mild drought)|
|3||(3, 3.5]||(0.6, 0.7]||Grade II (moderate drought)|
|4||(3.5, 4]||(0.7, 0.8]||Grade III (severe drought)|
|5||[4, 5]||[0.8, 1]||Grade IV (extremely severe drought)|
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Chen, M.; Ning, S.; Jin, J.; Cui, Y.; Wu, C.; Zhou, Y. Risk Assessment of Agricultural Drought Disaster on the Huaibei Plain of China Based on the Improved Connection Number and Entropy Information Diffusion Method. Water 2020, 12, 1089. https://doi.org/10.3390/w12041089
Chen M, Ning S, Jin J, Cui Y, Wu C, Zhou Y. Risk Assessment of Agricultural Drought Disaster on the Huaibei Plain of China Based on the Improved Connection Number and Entropy Information Diffusion Method. Water. 2020; 12(4):1089. https://doi.org/10.3390/w12041089Chicago/Turabian Style
Chen, Menglu, Shaowei Ning, Juliang Jin, Yi Cui, Chengguo Wu, and Yuliang Zhou. 2020. "Risk Assessment of Agricultural Drought Disaster on the Huaibei Plain of China Based on the Improved Connection Number and Entropy Information Diffusion Method" Water 12, no. 4: 1089. https://doi.org/10.3390/w12041089