Regional Agricultural Drought Risk Assessment Method Based on Risk Transforming Process

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

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.

Agricultural Drought Risk Assessment: A Spatial Analysis of Hazard, Exposure, and Vulnerability in Zacatecas, Mexico

Drought is one of the major threats to water and food security in many regions around the world. The present study focuses on the evaluation of agricultural drought risk from an integrated perspective, that is, emphasizing the combined role of hazard, exposure, and vulnerability to drought. For this purpose, we used the Mexican state of Zacatecas as a case study. This state is one of the most vulnerable to the adverse effects of agricultural drought in the country. The proposed method includes three stages: first, we analyzed the risk of agricultural drought at the municipal scale using the FAO Agricultural Stress Index System (ASIS) in its country version (Country-Level ASIS) and also determined a Drought Hazard Index (DHI). Subsequently, we conducted a municipal assessment of exposure and vulnerability to drought based on a set of socioeconomic and environmental indicators, which we combined using an analytical procedure to generate the Drought Exposure Index (DEI) and the Drought Vulnerability Index (DVI). Finally, we determined a Drought Risk Index (DRI) based on a weighted addition of the hazard, exposure, and vulnerability indices. Results showed that 32% of the state’s municipalities are at high and very high risk of agricultural drought; these municipalities are located mainly in the center and north of the state, where 75.8% of agriculture is rainfed, 63.6% of production units are located, and 67.4% of the state’s population depends on agricultural activity. These results are in general agreement with those obtained by other studies analyzing drought in the state of Zacatecas using different meteorological drought indices, and the results are also largely in line with official data on agricultural surfaces affected by drought in this state. The generated maps can help stakeholders and public policymakers to guide investments and actions aimed at reducing vulnerability to and risk of agricultural drought. The method described can also be applied to other Mexican states or adapted for use in other states or countries around the world.