Estimation and Spatiotemporal Variation Analysis of Net Primary Productivity in the Upper Luanhe River Basin in China From 2001 to 2017 Combining With a Downscaling Method

The upper Luanhe River Basin is a significant ecological barrier guarding the Beijing-Tianjin-Hebei region in China. Quantitative measures of vegetation productivity can be used to assess ecosystem carbon sequestration capacity and monitor regional ecological environmental health. Although several vegetation productivity products have been generated, poor spatiotemporal resolution limits their application in ecosystem service assessment. In this article, vegetation net primary productivity (NPP) from 2000 to 2017 with a resolution of 30 m in the upper Luanhe River Basin was generated based on a data fusion model and the multisource data synergized quantitative (MuSyQ) NPP model. Then, the variation trend of NPP and its climate controls were analyzed. Compared with forest NPP observation data, we derived an R-2 of 0.68 and the root-mean-square error of 81.70 gC(.)m(-2.)yr(-1). Annual NPP had a fluctuating increasing trend from 2001 to 2017, with values ranging between 3.43 and 5.00 TgC(.)yr(-1), with an annual increase trend of 0.04 TgC(.)yr(-1). Precipitation was significantly correlated with NPP in the upper part of the Luanhe River basin, which is an important reason for the interannual variation of NPP. Grassland had a stronger correlation to precipitation than forest because it is more sensitive to precipitation. The area where the temperature is significantly correlated with annual NPP only accounts for 2% of the study area, indicating that temperature has a weak influence on NPP. Furthermore, human activities, such as forest management, fertilization, and irrigation, can change the trend of annual NPP.

Automated summary

In this study, vegetation net primary productivity (NPP) in the upper Luanhe River Basin from 2000 to 2017 was generated using a data fusion model and the MuSyQ NPP model. The results showed a fluctuating increasing trend in annual NPP, with precipitation being a significant factor for the interannual variation. Temperature had a weak influence on NPP. Additionally, human activities could change the trend of annual NPP.