基于涡度数据的东北草地光能利用率模型构建与验证

草地作为地球上分布最广的植被类型，在陆地碳循环中发挥着重要作用。草地生产力是估算产草量的基础，准确模拟生产力对草原资源合理利用及生态保护具有重要意义。以东北草地生产力为研究核心，利用涡度相关通量观测数据、遥感数据和气象数据，构建和检验东北草地光能利用率模型。东北草地光能利用率模型以归一化物候植被指数(NDPI)代表光合有效辐射吸收比例，以地表水分指数(LSWI)+0.5表示水分胁迫因子。基于44个草原站的通量数据对东北草地光能利用率模型进行验证，东北草地光能利用率模型的R²为0.855，高于MODIS GPP产品(R²=0.719)，略高于VPM GPP产品(R²=0.848)，东北草地光能利用率模型的MAE和RMSE分别为0.374 g Cm^-2和0.735 g Cm^-2，低于MODIS GPP产品(MAE=0.562 g Cm^-2,RMSE=1.026 g Cm^-2)和VPM GPP产品(MAE=0.667 g Cm^-2...

Constructing and Validating Light Use Efficiency Model of the Grassland in Northeastern China based on Flux Data

As the most widely distributed vegetation type on earth， grassland plays an important role in the terrestrial carbon cycle. Grassland productivity is the basis for estimating grassland yield. Grasping the temporal and spatial variation of grassland productivity is of great significance for rational utilization of grassland resources and protection of grassland ecological environment. This thesis taking the productivity of grassland in northeastern China as core， constructing and validating light use efficiency model based on eddy covariance flux data， remote sensing， and climate data， explored the spatiotemporal patterns on this basis. The research results are as follows： in the northeastern China steppe LUE model， FPAR was represented by NDPI， water stress factor was represented by LSWI + 0.5. Based on the flux data of four grassland stations， the R² of the northeastern China steppe LUE model was 0.855， which was higher than that of MODIS GPP （R² = 0.719）， and slightly higher than VPM GPP （R² = 0.848）. MAE and RMSE of the northeastern China steppe LUE model were 0.374 gCm^-2 and 0.735 gCm^-2，respectively，which were lower than that of MODIS GPP（MAE=0.562 gCm^-2， RMSE = 1.026 gCm^-2） and VPM GPP products （MAE = 0.667 gCm^-2， RMSE = 1.339 gCm^-2）. VPM GPP product generally overestimated the flux GPP； MODIS GPP product significantly overestimated typical steppe GPP in dry years， and significantly underestimated meadow steppe GPP. Although the northeastern China steppe LUE model was higher than the typical steppe flux GPP in the dry years， its overestimation degree is less than that of MODIS GPP and VPM GPP products. The northeastern China steppe LUE model is superior to MODIS GPP and VPM GPP products in terms of model accuracy and dynamic consistency， and the fitting accuracy of the annual scale is much higher than MODIS GPP and VPM GPP. The modified of water stress and FPAR was the reason for the improvement of LUE model accuracy， and the relative contribution of water stress is greater. This study demonstrates that it is necessary to use the improved light energy utilization model to simulate grassland productivity in northeastern China.