| Dynamic drought risk assessment of spring maize in three provinces in Northeast China |
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| DOI：10.7606/j.issn.1000-7601.2022.03.27 |
| Key Words: BCC/RCC-WG weather generator APSIM crop model spring maize drought dynamic risk Northeast China |
| Author Name | Affiliation | | WANG Yaxu | Postdoctoral Workstation of China Reinsurance (Group) Corporation， Beijing 100033 China
China Institute of Water Resources and Hydropower Research, Beijing 100038 | | LU Juan | China Institute of Water Resources and Hydropower Research, Beijing 100038 | | ZUO Huiqiang | hina RE Catastrophe Risk Management Company Ltd., Beijing, 100052, China | | GAO Hui | China Institute of Water Resources and Hydropower Research, Beijing 100038 | | QU Yanping | China Institute of Water Resources and Hydropower Research, Beijing 100038 | | SU Zhicheng | China Institute of Water Resources and Hydropower Research, Beijing 100038 | | YIN Jianming | hina RE Catastrophe Risk Management Company Ltd., Beijing, 100052, China |
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| Abstract: |
| Uncertainty of drought evolution and trends determines the dynamic characteristics of drought risk. How to use effective methods to characterize the changes of risk is the key to evaluate the dynamic drought risk. Due to the slow occurrence and development of drought, the accuracy of long-term numerical forecasting products is low, which has certain limitations in drought prediction. In this study, weather generator was selected to randomly generate a large number of samples of future daily weather data to describe the drought evolution which was used to drive crop models to evaluate crop yield loss due to drought and dynamic drought risk. Three provinces located in Northeast China were selected as the study area. The BCC/RCG-WG weather generator developed by the National Climate Center was employed to generate future meteorological data randomly. Driven by the meteorological data, the APSIM crop model was used to simulate spring maize yield loss due to drought which was calibrated and validated based on field test data during 2012-2017. Expected yield loss rate due to drought was calculated to evaluate the dynamic drought risk during the spring maize growth period in the three provinces of Northeast China in a typical drought year 2000 in real time. The results showed that R2 between simulated and measured spring maize sowing to flowering days, growth period days, and yield were all greater than 0.5. The Normalized Root Mean Square Error (NRMSE) were all below 10%, indicating that APSIM model had a good effect in simulating spring maize growth in the three provinces of Northeast China. The R2 of annual average meteorological elements generated by the BCC/RCG-WG with observed meteorological elements were above 0.9 during 1961-2020, and the average relative errors of monthly average rainfall, maximum temperature, minimum temperature, sunshine hours, relative humidity, and average wind speed were 9.1%, 9.9%, 14.5%, 6.1%, 14.7% and 21.6%, respectively. In 2000, the dynamic drought risk during the spring maize growth period the three provinces of Northeast China showed a trend of first increasing and then decreasing. The drought dynamic risk during the spring maize jointing to tasseling stage was the highest. The average expected yield loss rate in the three provinces of Northeast China was 0.23 on 10th July. Spatially, there were high drought dynamic risk in northern Heilongjiang, western Liaoning, and midwest Jilin Province. There was a low drought risk in spring maize seedling stage and sufficient water in the later stage had a strong compensation effect. While there was a high drought risk when drought occurs at jointing stage and water compensation effect was weak when water was sufficient at later stage. |
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