scholarly journals Regional Agricultural Drought Risk Assessment Method Based on Risk Transforming Process

2021 ◽  
Author(s):  
Yanqi WEI ◽  
Yi CUI ◽  
Juliang JIN ◽  
Hiroshi ISHIDAIRA ◽  
Haichao LI ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Risk Management ◽  
Yield Loss ◽  
Agricultural Drought ◽  
Drought Risk ◽  
Risk Area ◽  
Potential Yield ◽  
Agricultural Drought Risk ◽  
Risk Curves ◽  
Drought Risk Management

Abstract Drought risk management can effectively reduce drought losses and improve drought resistance capability, of which drought risk assessment is the core issue. This study evaluated the agricultural drought risk in Huaibei Plain of Anhui Province in China by the approach of constructing drought loss risk curves and risk distribution maps. The results showed that: 1) The drought events that occurred in northern regions (Huaibei and Suzhou) were with the characteristics of high-frequency and low-intensity, while in southern regions (Huainan and Bengbu), the occurring characteristics were low-frequency, high-intensity, and long-duration. 2) Without irrigation, Fuyang was the high-risk region with more than 80% potential yield loss rate, while Huainan was the relatively low-risk area with a potential yield loss of 50%. 3) Irrigation had a significant effect on reducing drought risk loss, while the efficiency was influenced by the spatio-temporal distribution of precipitation. The irrigation scheme in study area still remains to be optimized based on the characteristics of precipitation and crop growth. This study established and practiced a quantitative framework for regional drought risk assessment by creating drought risk curves and risk maps, which have significant value in improving the regional agricultural drought risk management level.

Research on Agricultural Drought Risk Measurement Based on Bayes Hybrid Model

2021 ◽  
Vol 7 (5) ◽  
pp. 3983-3987
Author(s):  
Jianping Wu ◽  
Xiaowen Liu ◽  
Yaoping Tang ◽  
Hongfei Xu
Keyword(s):  
Risk Management ◽  
Hybrid Model ◽  
Loss Rate ◽  
Risk Measurement ◽  
Agricultural Drought ◽  
Distribution Model ◽  
Drought Risk ◽  
Agricultural Economy ◽  
Agricultural Drought Risk ◽  
Drought Risk Management

The development of agricultural economy depends to a large extent on the drought. It is necessary to accurately analyze the current drought risk in order to formulate a more reliable drought risk management strategy and reduce the impact of disasters on the development of the agricultural economy. In order to improve the level of drought risk measurement, this paper selects VaR as the measurement tool, and proposes a mixed distribution model research. Use this model to fit the distribution of drought loss rate, and measure the drought risk by estimating VaR. Among them, the mixed distribution model is mainly composed of two parts, namely GPD and conventional distribution. The former is used to characterize the risk tail. Considering the difficulty of selecting the GPD distribution threshold, this paper introduces the Bayes calculation method to optimize, forming a Bayes hybrid model, including Norm-GDP model and Gamma-GPD model. The application results show that the fitting results generated by the Norm-GDP model application have a better distribution of drought loss rates, and the VaR estimation results are more reliable. Taking 10-year, 20-year, and 100-year disasters as examples, the estimated drought loss rate is 9.46%, 11.05%, and 30.22%. The generation of these metric values can provide a reference for my country’s agricultural drought risk management.

scholarly journals Risk Assessment of Maize Drought in China Based on Physical Vulnerability

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Fang Chen ◽  
Huicong Jia ◽  
Donghua Pan
Keyword(s):  
Risk Assessment ◽  
Yield Loss ◽  
Maize Yield ◽  
Scientific Basis ◽  
Agricultural Drought ◽  
Risk Level ◽  
Drought Risk ◽  
National Scale ◽  
Agricultural Drought Risk ◽  
Disaster System

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.

scholarly journals Risk identification of agricultural drought for sustainable Agroecosystems

2014 ◽  
Vol 14 (9) ◽  
pp. 2435-2448 ◽  
Author(s):  
N. R. Dalezios ◽  
A. Blanta ◽  
N. V. Spyropoulos ◽  
A. M. Tarquis
Keyword(s):  
Risk Assessment ◽  
Risk Management ◽  
Satellite Data ◽  
Warm Season ◽  
Risk Identification ◽  
Agricultural Drought ◽  
Drought Risk ◽  
Areal Extent ◽  
Spatiotemporal Features ◽  
Noaa Avhrr

Abstract. Drought is considered as one of the major natural hazards with a significant impact on agriculture, environment, society and economy. Droughts affect sustainability of agriculture and may result in environmental degradation of a region, which is one of the factors contributing to the vulnerability of agriculture. This paper addresses agrometeorological or agricultural drought within the risk management framework. Risk management consists of risk assessment, as well as a feedback on the adopted risk reduction measures. And risk assessment comprises three distinct steps, namely risk identification, risk estimation and risk evaluation. This paper deals with risk identification of agricultural drought, which involves drought quantification and monitoring, as well as statistical inference. For the quantitative assessment of agricultural drought, as well as the computation of spatiotemporal features, one of the most reliable and widely used indices is applied, namely the vegetation health index (VHI). The computation of VHI is based on satellite data of temperature and the normalized difference vegetation index (NDVI). The spatiotemporal features of drought, which are extracted from VHI, are areal extent, onset and end time, duration and severity. In this paper, a 20-year (1981–2001) time series of the National Oceanic and Atmospheric Administration/advanced very high resolution radiometer (NOAA/AVHRR) satellite data is used, where monthly images of VHI are extracted. Application is implemented in Thessaly, which is the major agricultural drought-prone region of Greece, characterized by vulnerable agriculture. The results show that agricultural drought appears every year during the warm season in the region. The severity of drought is increasing from mild to extreme throughout the warm season, with peaks appearing in the summer. Similarly, the areal extent of drought is also increasing during the warm season, whereas the number of extreme drought pixels is much less than those of mild to moderate drought throughout the warm season. Finally, the areas with diachronic drought persistence can be located. Drought early warning is developed using empirical functional relationships of severity and areal extent. In particular, two second-order polynomials are fitted, one for low and the other for high severity drought classes, respectively. The two fitted curves offer a forecasting tool on a monthly basis from May to October. The results of this drought risk identification effort are considered quite satisfactory offering a prognostic potential. The adopted remote-sensing data and methods have proven very effective in delineating spatial variability and features in drought quantification and monitoring.

scholarly journals Study on the drought risk of maize in the farming-pastoral ecotone in Northern China based on physical vulnerability assessment

2016 ◽  
Author(s):  
Zhiqiang Wang ◽  
Jingyi Jiang ◽  
Qing Ma
Keyword(s):  
Climate Change ◽  
Risk Assessment ◽  
Yield Loss ◽  
Northern China ◽  
Agricultural Drought ◽  
Drought Risk ◽  
Physical Vulnerability ◽  
Vulnerability Curve ◽  
Intensity Index ◽  
Drought Hazard

Abstract. Climate change is affecting every aspect of human activities, especially the agriculture. In China, extreme drought events caused by climate change have posed great threaten to food safety. In this work we aimed to study the drought risk of maize in the farming-pastoral ecotone in Northern China based on physical vulnerability assessment. The physical vulnerability curve was constructed from the relationship between drought hazard intensity index and yield loss rate. The risk assessment of agricultural drought was conducted from the drought hazard intensity index and physical vulnerability curve. Results of the drought hazard intensity index showed that the risk of agricultural drought displayed a negative correlation with the precipitation and kept rising from 1966 to 2011. Risk assessments of yield loss ratio shows that physical vulnerability curve has magnify and reduce function to drought hazard. So improving the capacity of maize to resist drought can help them adapt to drought hazard. In conclusion, the farming-pastoral ecotone in Northern China had great sensitivity to climate change and high probability for severe drought hazard. Risk assessment of physical vulnerability can help better understanding the physical vulnerability to agricultural drought and can also promote measurements to adapt to the climate change.

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