Estimation of net primary productivity and correlation study with climate parameters in Jiangxi Province using the enhanced CASA model
LU Tie-ding1,2, ZHANG Yuan1, ZENG Si-ting1, TAO Rui3, TENG Yue4
1. School of Surveying and Geoinformation Engineering, East China University of Technology, Nanchang 330013, China; 2. Key Laboratory of Mine Environmental Monitoring and Improving around Poyang Lake of Ministry of Natural Resources, East China University of Technology, Nanchang 330013, China; 3. Jiangxi Communications Design and Research Instituteco., Ltd, Nanchang 330000, China; 4. Jiangxi Provincial Natural Resources Surveying and Monitoring Institute, Nanchang 330002, China
Abstract：This research increases the accuracy of Net Primary Productivity (NPP) estimation in the CASA (Carnegie-Ames-Stanford Approach) model by refining the calculation methods for solar radiation parameters and water stress coefficients. Based on the improvement, correlation and trend analysis of NPP and meteorological variables were carried out.Following model optimization, the correlation between NPP and field observation data improved to 0.62. From 2001 to 2022, the annual average NPP in Jiangxi Province increased steadily, with the average value exceeding 1000gC/(m2·a). The monthly NPP values were in the following seasonal order: autumn > summer > winter > spring, with July having the highest value. The highest and lowest annual NPP values were observed in 2018 and 2010, respectively. Trend analysis and correlation facts show that, despite a decline in solar radiation from 2001 to 2022, NPP changes were not considerably impacted. A least-squares regression model revealed that NPP increased with rising temperature and decreased with decreasing sun radiation. Despite recent increases in extreme events (2019~2022), there has been no notable decrease in NPP levels.
鲁铁定, 章园, 曾思婷, 陶蕊, 腾月. 江西省NPP估算及其与气候因子的关联分析-基于改进CASA模型[J]. 中国环境科学, 2025, 45(1): 369-378.
LU Tie-ding, ZHANG Yuan, ZENG Si-ting, TAO Rui, TENG Yue. Estimation of net primary productivity and correlation study with climate parameters in Jiangxi Province using the enhanced CASA model. CHINA ENVIRONMENTAL SCIENCECE, 2025, 45(1): 369-378.
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