Dr. Zhao Zhang is an Associated Professor in the field of integrated risk. Her research areas include agriculture ecology, agricultural production, climate change, climate disasters, and geographic environment and human health. She is the supervisor of several graduate students. Dr. Zhang delivers lectures of ‘Agricultural Disasters and Food Security’, and ‘Environmental Risk and Human Society’. In the area of integrated risk, Dr. Zhang has published 69 articles in the related international academic journals, e.g. Agricultural and Forest Meteorology, European Journal of Agronomy, Science of the Total Environment, and Journal of Environmental Management. Total citations have amounted to 1225 times, with impact points of 179.88. She has taken part in or taken charge of several research programs funded by governments at different levels, enterprises and organization
Natural hazards usually occur randomly and occasionally. The information during these dynamic courses is obtained difficultly, which have caused the basic theory and methodology in the field of disaster risk science are only focused on a single hazard, rather than multi-hazards. However, crop will encounter multi-natural hazards during the long period of growth and development. Therefore, traditional statistical method is not able to identify scientifically yield loss. Such weakness does not only hinder the development of disaster risk science, but also limit the methods and achievements of disaster risk sciences to be applied extensively by the related departments (e.g., “the uniform premium rating in a province”, “yield loss identified unknowingly by a definite disaster” etc., such problems encountered by crop insurance companies). Therefore, it is highly necessary and significant to perform the risk assessment of agricultural meteorological disasters (AMD) on multi-scales, multi-hazards, and multi-processes to understand the mechanisms controlling the final losses. Firstly, the developed MCWLA-Wheat model will be improved to strengthen its ability to simulate the impact of extreme events (drought, high temperature, dry-hot wind). Then, the improved model will be parameterized at the grid (0.25°×0.25°) scale, and be validated at the two scales (county and province). Then, by inputting the different scenarios of AMDs, the MCWLA-Wheat will simulate the dynamic processes responding to these stress scenarios, and the respective yield losses will be calculated by MCWLA-Wheat. The study will finally construct the models to catch the relationship between “a single\multi-hazards – yield loss risk” and assess the integrated risk for winter wheat in North China Plain. We are sure that the achievements in the study will provide new theory and method for the disaster risk field, and will benefit the related departments to assess rapidly the yield loss from AMDs, and to set a reasonable premium rating.
- Start From: 2016 - 01
- End By: 2019 - 12
- Sponsored By: Beijing Normal University