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Study On Multiple Underlying Surface Elements Water And Heat Fluxes In Horqin Sand Dune-Meadow Cascade Ecosystem

Posted on:2020-08-29Degree:MasterType:Thesis
Country:ChinaCandidate:T Y HuangFull Text:PDF
GTID:2393330578457009Subject:Hydrology and water resources
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Large aperture scintillometer(LAS)and eddy covariance(EC)are commonly used to measure water and heat fluxes between land and atmosphere near the surface.In this study,a cascade eco-belt between dunes and meadows in Horqin sandy land was taken as the research object.Based on the data of soil-vegetation-meteorological observation stations and vegetation survey on the cascade,the water and heat fluxes dynamic characteristics at different time scales under the complex underlying surface conditions and the response relationship between environmental factors and water and heat fluxes were studied by using large aperture scintillometer and eddy covariance system.A climatological footprint model is used to study and analyze the source areas of underlying surface of patch scale measured by eddy covariance and kilometer scale measured by large aperture scintillometer at different time scales.The applicability of large aperture scintillator in this area is also verified by scale conversion and fusion of the flux source areas observed by the two instruments.The main conclusions are as follows:(1)The diurnal variation of water and heat fluxes in the cascade ecosystem is significant.The fluxes fluctuate obviously in daytime and almost no fluctuate at night in the growing season.On sunny days,the curve of sensible heat flux and soil heat flux in daytime showed a significant single peak,while the curve of latent heat flux showed a double peak in the growing season and a single peak in the non-growing season.On cloudy conditions,the flux curves fluctuate irregularly.The sensible heat flux and latent heat flux curves reached the maximum value of one day around noon,while the peak value of soil heat flux curve had a time lag,in which the growing season lagged 1-2 hours and the non-growing season lagged 2-3 hours.The latent heat flux is the main form of near-surface energy consumption in the growing season.The monthly average latent heat flux accounts for 52% to 76% of net radiation in the growing season,while the proportion of non-growing season decreases.On the monthly scale,the trend of flux variation curve is obvious.The sensible heat flux has a single peak in each month,and the peak time moves backwards first and forwards then.The peak value of latent heat flux reaches the maximum in August.In terms of seasonal variation,the sensible heat flux in summer(June-August)is lower than that in spring(March-May),autumn(September-November)and winter(December),with an average peak value near 50W·m-2;the peak value of sensible heat flux in spring and autumn is slightly higher than that in winter,and the average peak value in three seasons is around 100W·m-2.Soil heat flux is positive in growing season,which shows energy storage,sensible heat is greater than latent heat in non-growing season,and negative in soil heat flux,which releases energy outward.(2)The responses of meteorological,soil factors and water and heat fluxes in the vegetation growing season were good.The correlation of monthly mean solar net radiation with monthly sensible heat flux and latent heat flux is above 0.96.The correlation of monthly mean air temperature,air humidity,relative vapor pressure and other meteorological factors with sensible heat flux and latent heat flux is also significant.The response of soil factors to sensible heat flux and latent heat flux is lower than that of meteorological factors due to complex topography and underlying surface conditions.The correlation between surface soil temperature(10cm),soil moisture(10cm)and water and heat flux is significant,while the correlation between soil conductivity and water and heat flux is not obvious.(3)Based on the climatological footprint model,the flux source region on the complex underlying surface of the cascade ecosystem zone is obtained by weighting method.Source location and area are different in different time scales.The location and area of the source area on the hour scale,the day scale and the ten-day scale vary greatly,while the change of the source area on the monthly scale is relatively stable.The change of the source area is related to environmental factors such as wind direction and stability.The monthly source areas in the growing season of the study area are mainly distributed on both sides of the light diameter of the large aperture scintillometer,and the source area is stable at 0.51 km2-0.55 km2.In terms of seasonal variation,the area of climatological footprint in the study area is autumn(September-October)>spring(May)>summer(June-August).According to the type map of underlying surface in the study area,the maize farmland in the middle part of LAS light path contributed the most in the growing season,followed by sand dune underlying surface and grassland underlying surface.The small lakes in the study area contributed little in the whole growing season.(4)The source region of a single eddy correlation system can not represent the source region under the condition of inhomogeneous underlying surface,but the EC source region located in the middle of the LAS optical path has a higher correlation with the LAS climatological footprint.Whichever wind direction,the eddy observation source area of the LAS transmitter and receiver is outside the LAS climatological footprint.In the three wind directions of westerly,northerly and southerly,the area of eddy climatological footprint and footprint weight proportion were meadow station>farmland station>lake station.The weighted EC of each station is fused into HEC.HLAS and HEC fit well and the multiple coefficient is 1.1798.The value of the HLAS is slightly larger than HEC.There is a good scale conversion relationship between them.It shows that the large aperture scintillometer has good applicability in this area.
Keywords/Search Tags:Desertification area, Horqin Sandy Land, Large aperture scintillometer(LAS), Eddy covariance(EC), Water and heat flux, Climatological footprint
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