A Simulation Study On Carbon Use Efficiency Of Vegetation In Qinghai Lake Basin Based On The VPRM Model

The terrestrial ecosystem is an important system to mitigate the greenhouse effect and regulate climate change.Carbon Use Efficiency?CUE?is an important ecological parameter of the carbon cycle,reflecting the conversion of atmospheric CO₂ into biomass and Carbon sequestration Efficiency of the vegetation.Therefore,clarifying and quantifying the spatial and temporal variation characteristics of vegetation CUE is of great significance for assessing and predicting the carbon budget.Net Ecosystem Productivity?NEP?and Gross Primary Productivity?GPP?are indispensability ways to measure Ecosystem vegetation Productivity/and are basic conditions for calculating Ecosystem CUE.In Qinghai Lake Basin as The study area,this study is based on remote sensing data and meteorological data,using Vegetation photosynthetic breathing Model?The Vegetation Photosynthesis and Respiration Model,VPRM?to calculate The small lake wetland and tile yan was source wetland site NEP,and by using The observed two site NEP data VPRM Model parameter optimization and precision test.On this basis,GPP and NEP of Qinghai Lake Basin vegetation were calculated,and finally,CUE of Qinghai Lake Basin vegetation was calculated.The purpose of this study is to provide a reference for future studies on the simulation of vegetation productivity and carbon utilization efficiency in large-scale regions.The results are as follows:?1?on the 8-day scale,The coefficient of determination the linear fitting between the simulated and observed values of vegetation NEP in Wanyan Mount and Xiaobo Lake are 0.73?p<0.01?and 0.89?p<0.01?,respectively,indicating that the VPRM model is in Qinghai Lake Simulated vegetation NEP can better reflect the seasonal change trend of vegetation NEP and has a good fitting effect.However,in terms of relative error?RE?,the NEP simulation values of vegetation in Xiaobo Lake growing season and the beginning and end of Wayan Mountain growth period are underestimated,while the vegetation NEP simulation values in Wayan Mountain growing period are high Estimated phenomenon.?2?The vegetation GPP and NEP of the Qinghai Lake Basin under the 8-day scale of 2017-2018 increased from the growing season,reached the maximum during the vigorous growth season,then began to decline,and reached the minimum at the end of the growing season.In the growing season at the 8-day scale in 2017,the highest vegetation GPP value of the Qinghai Lake Basin was 48.26 g C/m²,and in2018 it was 40.53 g C/m².The vegetation GPP in both years increased from May and reached the maximum in July,And then began to decline,the lowest in October,the monthly average of vegetation GPP growth season in 2017 was 78.46 g C/m²,and in2018 was 71.79 g C/m²,the average annual total accumulation of vegetation GPP in the watershed in 2017 was 520.42 g C/m²,467.83 g C/m² in 2018,and the cumulative amount of vegetation GPP in 2017 is also greater than that in 2018.In 2017 and 2018,the vegetation NEP of the Qinghai Lake Basin changed in a single-peak trend,which increased from the 121st day?May 1st?,reached the maximum around the 200th day?July 19th?,and then began to decline.In 2017,the average annual accumulation of vegetation NPP in the basin was 170.60 g C/m²,and in 2018 it was 118.56 g C/m².The accumulation of vegetation NEP in the Qinghai Lake Basin in 2017 was greater than that in 2018,consistent with GPP,and vegetation growth in 2017,the situation is better than in 2018.The distribution of vegetation GPP and NEP in the watershed is the same,with Qinghai Lake as the center,forming a"low-high-low"ring-shaped belt,and the distribution law is decreasing from southeast to northwest.?3?The vegetation NEP observed at the Wayan Mountain site had a very significant positive correlation with the parameters LSWI,EVI,and T_a input by the model?p<0.001?,and the correlation with the PAR was not significant?p>0.05?.With sufficient light,vegetation NEP is less inhibited by light.The VPRM model of the simulation of vegetation productivity in the Qinghai Lake Basin,although the overall simulation has a good consistency,also has certain errors.The main reason for the error is that there is an error in the remote sensing image of the input parameters,there are errors in the acquisition methods of some parameter factors required by the model,in the ideal state the model simulation itself has an error with the actual situation,and the ecosystem vegetation productivity obtained by the vortex-related system also exists error.?4?The vegetation CUE of the Qinghai Lake Basin increased from the 145th day?May 25?,reached the highest value in about 200 days?July 19?,and then began to decrease.The CUE of the vegetation in the Qinghai Lake Basin showed a"single peak"trend in 273 days?September 30?.At the beginning and the end of the growing season,the vegetation CUE in 2017 was higher than that in 2018,the vegetation CUE was higher than 2017 in the period of vigorous growth,the average value of the vegetation CUE at the 8-day scale was 0.31 in 2018,and 0.34 in 2017.In 2017,the vegetation carbon sequestration potential of the Qinghai Lake basin was better.The distribution of vegetation CUE in the Qinghai Lake basin is mainly centered on Qinghai Lake,forming a"low-high-low"circular strip-like distribution characteristic,and the distribution law decreases from southeast to northwest.The high-value areas of vegetation CUE in the Qinghai Lake Basin are mainly distributed in the central part of the north bank of Qinghai Lake,most parts of the south bank and parts of the west bank.The vegetation GPP,NEP,and CUE in Qinghai Lake Basin increased first and then decreased with the increase of altitude,and their peaks all appeared in the range of 3500-3600 m above sea level.