Hui Wang
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Hui Wang has a total of 5 co-authors. Here are the top co-authors by number of shared publications:
- Ding Zhou
College of Water Resources and Civil Engineering, Hunan Agricultural University, Changsha 410128, China
1 shared publication - Donghao Ma
State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science Chinese Academy of Sciences Nanjing China
1 shared publication - Fangfang Wang
State Experimental Station of Agro-Ecosystem in Fengqiu, State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210018, China
1 shared publication - Jiabao Zhang
State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, China
1 shared publication - Xiangxiang Wang
Anhui Institute of Strategic Study on Carbon Dioxide Emissions Peak and Carbon Neutrality in Urban-Rural Development, College of Environment and Energy Engineering, Anhui Jianzhu University, Hefei 230601, China
1 shared publication
Latest Publications
- Open Access
Evaluation of AquaCrop’s Ability to Simulate Water Stress Based on 2-Year Case Study of Maize Crop
To apply AquaCrop to the study of agricultural soil moisture in the North China Plain, a water-treatment experiment on summer maize was carried out at the Fengqiu experimental station of the Chinese Academy of Sciences from 2017 to 2018. A water treatment was used to achieve field water capacities of 20 (W1), 40 (W2), and 60 (W3) cm soil layers under irrigation, and a rain-fed treatment (W0) was added. The model parameters were calibrated using the measured data in 2017. Then, they were applied to 2018 to verify the ability of the model to simulate water stress. The results showed that the variation trends for crop yield, canopy coverage, total soil water content, and the curve in the growth cycle simulated via AquaCrop were consistent with the actual observations; the results of a discrete analysis showed that the values of b (regression coefficient), R2 (determination coefficient), and EF (efficiency) were close to 1, and the values of the RMSE (root mean square error) were close to 0, which proved that the model could simulate dynamic changes in summer maize yield, canopy coverage, and total soil water content well. AquaCrop had good applicability in the North China Plain and could be applied to the study of agricultural water consumption and water-use efficiency in this area. The simulated values obtained can serve as an easily obtainable source of long-term experimental data in areas with frequent non-extreme weather events.
Open AccessEvaluation of AquaCrop’s Ability to Simulate Water Stress Based on 2-Year Case Study of Maize Crop
To apply AquaCrop to the study of agricultural soil moisture in the North China Plain, a water-treatment experiment on summer maize was carried out at the Fengqiu experimental station of the Chinese Academy of Sciences from 2017 to 2018. A water treatment was used to achieve field water capacities of 20 (W1), 40 (W2), and 60 (W3) cm soil layers under irrigation, and a rain-fed treatment (W0) was added. The model parameters were calibrated using the measured data in 2017. Then, they were applied to 2018 to verify the ability of the model to simulate water stress. The results showed that the variation trends for crop yield, canopy coverage, total soil water content, and the curve in the growth cycle simulated via AquaCrop were consistent with the actual observations; the results of a discrete analysis showed that the values of b (regression coefficient), R2 (determination coefficient), and EF (efficiency) were close to 1, and the values of the RMSE (root mean square error) were close to 0, which proved that the model could simulate dynamic changes in summer maize yield, canopy coverage, and total soil water content well. AquaCrop had good applicability in the North China Plain and could be applied to the study of agricultural water consumption and water-use efficiency in this area. The simulated values obtained can serve as an easily obtainable source of long-term experimental data in areas with frequent non-extreme weather events.