Research On The Mechanism Of Coupling Water And Carbon Of Vegetation In The Mountainous Area Of North China

With the intensification of human activities and the deterioration of water quality,the shortage of water resources in the mountainous area of north China is becoming more and more serious.In the context of global climate change and water crisis,the mountainous area of north China is taken as the study area in this study,taking the characteristics of water-carbon cycle as the starting point,the water use efficiency(WUE),which can best reflect the coupling relationship between water and carbon,is taken as the research object.Based on CASA model and meteorological,land cover and remote sensing data,the net primary productivity of vegetation(NPP)in the study area was estimated from 2000 to 2018,the estimated NPP combined with evapotranspiration(ET)calculates the regional vegetation WUE,the spatial and temporal distribution and trend change characteristics of ET,NPP and WUE in the study area were analyzed.Based on the relationship between water-carbon cycle,meteorological factors and vegetation factors,the response of regional WUE to climate and vegetation changes was discussed to quantitatively evaluate the threshold value of meteorological factors and vegetation factors on regional water-carbon coupling.The research results are as follows:(1)The average precipitation was 503.5mm from 1957 to 2018,showing an insignificant downward trend,with an average decrease of 0.13-6.57mm/10yr;the average temperature is 8.6?,which shows an obvious upward trend,and the average temperature increase is about 0.025-0.46?/10yr.From 2000 to 2018,the coverage of forest and grassland increased,and the coverage of cropland decreased by 1.96%.(2)The inter-annual variation range of ET from 2000 to 2018 is 289.9-462.5mm,the overall trend is upward and fluctuates at a rate of 3.72mm/yr.During the year,the distribution of ET is not uniform,showing a single-peak distribution which increased first and then decreased,with obvious seasonal differences.The order from the largest to the smallest was summer>spring>autumn>winter.The annual average ET has obvious spatial heterogeneity,which decreases gradually from southeast to northwest,and the spatial annual change rate is between-25.8?62.97mm/yr.The spatial variation trend of ET in different seasons is quite different,with the increase rate of 2.01 mm/yr in spring and 2.45mm/yr in autumn,5.87mm/yr in summer and 0.073mm/yr in winter.The order of ET of different vegetation types was broad-leaved forest(464.02mm/yr)>mixed forest(419.20mm/yr)>coniferous forest(380.35mm/yr)>shrubland(365.72mm/yr)>grassland(341.22mm/yr)>cropland(311.97mm/yr).The sensitivity of ET to meteorological factors is significantly different.When precipitation,solar radiation and temperature increase by 10%,ET will increase by 3.26%,2.25%and 1.05%,respectively,while when drought severity index increases by 10%,ET will decrease by 2.73%.Precipitation is the most prominent meteorological factor affecting ET.There was a significant positive correlation between ET and NDVI and LAI.For every 10%increase in NDVI and LAI,ET will increase by 2.07%and 1.84%,respectively.(3)The simulation results of other models and the MODIS NPP data were used to compare and verify the NPP values estimated by the CASA model.It is found that the CASA model has good simulation results for the NPP in the study area and has certain reliability,which was applicable to study the spatial and temporal distribution and trend change characteristics of NPP in the mountainous area of north China.(4)The inter-annual variation range of NPP from 2000 to 2018 is 230.57-498.81gC/m2-yr,the overall trend is upward and fluctuates at a rate of 7.18 gC/m2·yr.During the year,the distribution of NPP is not uniform,with obvious seasonal differences.The order from the largest to the smallest is summer>spring>autumn>winter.The annual average NPP has obvious spatial heterogeneity,which decreases gradually from southeast to northwest,and the spatial annual change rate is between-32.38?45.87 gC/m2-yr.The NPP of different vegetation types in the region showed an increasing trend,and the average increase of NPP in cropland was 9.27 gC/m2·yr,the average increase of NPP in grassland was 6.83 gC/m2·yr,the NPP of coniferous forest,broad-leaved forest and mixed forest was already very high before the implementation of the ecological restoration project,the growth rate is less than that of cropland and grassland,with the average increase of 4.09,5.86 and 5.99gC/m2·yr,respectively;the average increase of NPP in shrubland was 2.86 gC/m2.yr.The synergistic effect of precipitation,temperature,solar radiation and drought severity index from 2000 to 2018 can explain the change of 68%in NPP.Vegetation cover change is an important factor affecting the change of vegetation NPP.As the area of cropland with low NPP is converted to forest,shrubland and grassland with high NPP,it will lead to an increase in regional NPP.(5)the simulation results of other models were used to compare and verify the estimation results of WUE,and it is found that the simulation results of WUE in this study are reasonable and credible,which was applicable to analyze the spatial and temporal distribution and trend change characteristics of WUE in the mountainous area of north China.The average value of WUE from 2000 to 2018 is 0.985 gC/mm·m2,indicating that for every millimeter of water loss via evapotranspiration,about 0.985 g of CO2 is fixed by vegetation growth.During the year,WUE presents a single-peak distribution with obvious seasonal difference,and the order from the largest to the smallest is summer>spring>autumn>winter.The annual average WUE has obvious spatial heterogeneity,and the spatial annual change rate is between-0.265?0.389gC/mm·m2.The variation trend of WUE in different vegetation types is obviously different,and the order is forest(1.148 gC/mm·m2)>grassland(0.928 gC/mm·m2)>shrubland(0.832 gC/mm·m2)>cropland(0.747 gC/mm-m2).(6)The change of vegetation WUE is closely related to LAI,temperature,precipitation,solar radiation and drought severity index.Through principal component analysis,it is found that LAI,temperature and precipitation are the main factors leading to vegetation WUE changes,and the cumulative contribution rate is 79.43%.From 2000 to 2018,vegetation WUE has a quadratic curve relationship with annual average precipitation and annual average temperature.When the annual average precipitation is 490-510mm and the annual average temperature is 13?,the vegetation WUE reaches the threshold value,that is to say,the vegetation water utilization is the highest in the study area;the relationship between vegetation WUE and LAI is nonlinear,when the LAI is 1.27m2m-2,the vegetation WUE reaches the threshold of 2.866 gC/mm·m2.