ارزیابی ریسک خشکسالی بر ذرت
Abstract
۱٫ Introduction
۲٫ Materials and methods
۳٫ Results
۴٫ Discussion
۵٫ Conclusion
Declaration of competing interest
Acknowledgements
References
Abstract
Drought risk assessment is a vital part of drought risk management, which plays an important role in drought mitigation. Due to its complexity, drought risk is difficult to define and challenging to quantitatively assess, as the drought impacts associate with many social sectors. This contribution method the issue by quantitatively evaluating the yield loss due to drought as a function of the drought severity indicator in Liaoning province, China for spring maize using logarithmic regression. As crop water deficit is essence to identify agricultural drought, it developed a drought severity indicator using the crop water stress coefficient and duration. The Agricultural Production Systems sIMulator (APSIM) crop model was employed to simulate the spring maize growth to obtain daily water deficit during the growth period (May to September) and yield. The relationship between drought severity frequency and yield loss rate due to drought was established to assess the drought risk of spring maize when drought severity frequency is equal to 20%, 10%, 5% and 2%. The results show that Chaoyang and Fuxin have the highest drought risk in four levels of drought severity frequency whilst the lowest drought risk was identified in Tieling. The central Liaoning province has a moderate drought risk. For a specific drought severity frequency, drought risk increases from east to west in Liaoning province whilst it varies in each city at different drought severities. This method can predict yield loss due to drought for drought early warning. Drought risk maps presents spatial characteristics that can help to agricultural drought mitigation and the development of drought preparedness plan in Liaoning province.
Introduction
Drought is slow-onset and one of the most widespread natural hazards. Drought impacts are nonstructural and the occurrence of drought is associated with significant impacts in water resources, environment, energy, and human lives, especially in agricultural production (Wilhite, 2005;Wilhite and Pulwarty, 2018). These characteristics make it particularly challenging to quantify drought risk and capture drought impacts. In China, the average annual yield loss due to drought has increased from 4.35 million tons in the 1950s, to 34.9 million tons in the early twenty-first century (Lv, 2013). Drought affected approximately 60% of the maize sown area during 1990-2007, which resulted in a 20%-30% reduction in production (Jia et al., 2012). The widespread and costly nature of drought has naturally led to an interest in drought risk assessment. Methods to quantify drought risk help decision makers in drought risk management and drought mitigation. It also has a great significance in the theory and practice of quantitative drought risk assessment (Bachmair et al., 2017;Botterill and Hayes, 2012). To date, a number of previous studies have evaluated the drought risk of different regions and climates across the world at different spatial scales, most of which focus on agricultural drought risk (Xie et al., 2016). Agriculture is directly affected by the occurrence of drought as it reliable on precipitation, temperature and evapotranspiration, which can decrease the soil moisture (Sruthi and Aslam, 2015).