Soil moisture(SM), which plays a crucial role in studies of the climate, ecology, agriculture and the environment, can be estimated and mapped by remote sensing technology over a wide region. However, remotely sensed ...Soil moisture(SM), which plays a crucial role in studies of the climate, ecology, agriculture and the environment, can be estimated and mapped by remote sensing technology over a wide region. However, remotely sensed SM is constrained by its estimation accuracy, which mainly stems from the influence of vegetation cover on soil spectra information in mixed pixels. To overcome the low-accuracy defects of existing surface albedo method for estimating SM, in this paper, Qinghai Lake Basin, an important animal husbandry production area in Qinghai Province, China, was chosen as an empirical research area. Using the surface albedo computed from moderate resolution imaging spectroradiometer(MODIS) reflectance products and the actual measured SM data, an albedo/vegetation coverage trapezoid feature space was constructed. Bare soil albedo was extracted from the surface albedo mainly containing information of soil, vegetation, and both albedo models for estimating SM were constructed separately. The accuracy of the bare soil albedo model(root mean square error=4.20, mean absolute percent error=22.75%, and theil inequality coefficient=0.67) was higher than that of the existing surface albedo model(root mean square error=4.66, mean absolute percent error=25.46% and theil inequality coefficient=0.74). This result indicated that the bare soil albedo greatly improved the accuracy of SM estimation and mapping. As this method eliminated the effect of vegetation cover and restored the inherent soil spectra, it not only quantitatively estimates and maps SM at regional scales with high accuracy, but also provides a new way of improving the accuracy of soil organic matter estimation and mapping.展开更多
Accurately measuring precipitation is integral for understanding water cycle processes and assessing climate change in the Qinghai–Tibet Plateau(QTP).The Geonor T-200B weighing precipitation gauge with a single Alter...Accurately measuring precipitation is integral for understanding water cycle processes and assessing climate change in the Qinghai–Tibet Plateau(QTP).The Geonor T-200B weighing precipitation gauge with a single Alter shield(Geonor)and the Chinese standard precipitation gauge(CSPG)are widely used for measuring precipitation in the QTP.However,their measurements need to be adjusted for wetting loss,evaporation loss and windinduced undercatch.Four existing transfer functions for adjusting the Geonor-recorded and three transfer functions for adjusting the CSPG-recorded precipitation at hourly,daily or event scale has been proposed based on the precipitation intercomparison experiments conducted at a single site in different regions.Two latest transfer functions for the Geonor(which are referred to as K2017a and K2017b)at the half-hour time scale based on the precipitation intercomparison experiments at multiple stations in the northern hemisphere were provided in the World Meteorological Organization Solid Precipitation Intercomparison Experiment.However,the applicability of these transfer functions in the QTP has not been evaluated.Therefore,the current study carried out a precipitation measurement intercomparison experiment between August 2018 and September 2020 at a site in Beiluhe in central QTP.The performance of these transfer functions at this site was also evaluated on the basis of mean bias(MB),root mean squared error(RMSE)and relative total catch(RTC).The results are as follows:First,the unadjusted RTC values of the Geonor for rain,mixed(snow mixed with rain),snow and hail are 92.06%,85.35%,64.11% and 91.82%,respectively,and the unadjusted RTC values of the CSPG for the same precipitation types are 92.59%,81.32%,46.43% and 95.56%,respectively.Second,K2017a has the most accurate adjustment results for the Geonor-recorded snow and mixed precipitation at the half-hour time scale,and the post-adjustment RTC values increased to 98.25% and 98.23%,respectively.M2007e,an event-based transfer function,was found to have the most accurate adjustment results for the Geonorrecorded snow precipitation at the event scale,and the post-adjustment RTC value increased to 96.36%.Third,the existing transfer functions for CSPG underestimate snowfall,while overestimating rainfall.Fourth,hail is a significant precipitation type in central QTP.The catch efficiency of hail precipitation and the temperature when hail precipitation occurs are close to those of rain;moreover,the transfer functions for rain are suitable for hail as well.展开更多
基金supported by the National Philosophy and Social Science Foundation of China (14XMZ072)the Natural Science Foundation of Qinghai Province, China (2017-ZJ-901 and 2014-ZJ-723)+1 种基金the National Natural Science Foundation of China (40861022 and 41661023)the Cooperative Scientific Research Project of "Chunhui Plan", Ministry of Education of China (Z2012092 and S2016026)
文摘Soil moisture(SM), which plays a crucial role in studies of the climate, ecology, agriculture and the environment, can be estimated and mapped by remote sensing technology over a wide region. However, remotely sensed SM is constrained by its estimation accuracy, which mainly stems from the influence of vegetation cover on soil spectra information in mixed pixels. To overcome the low-accuracy defects of existing surface albedo method for estimating SM, in this paper, Qinghai Lake Basin, an important animal husbandry production area in Qinghai Province, China, was chosen as an empirical research area. Using the surface albedo computed from moderate resolution imaging spectroradiometer(MODIS) reflectance products and the actual measured SM data, an albedo/vegetation coverage trapezoid feature space was constructed. Bare soil albedo was extracted from the surface albedo mainly containing information of soil, vegetation, and both albedo models for estimating SM were constructed separately. The accuracy of the bare soil albedo model(root mean square error=4.20, mean absolute percent error=22.75%, and theil inequality coefficient=0.67) was higher than that of the existing surface albedo model(root mean square error=4.66, mean absolute percent error=25.46% and theil inequality coefficient=0.74). This result indicated that the bare soil albedo greatly improved the accuracy of SM estimation and mapping. As this method eliminated the effect of vegetation cover and restored the inherent soil spectra, it not only quantitatively estimates and maps SM at regional scales with high accuracy, but also provides a new way of improving the accuracy of soil organic matter estimation and mapping.
基金supported primarily by the National Natural Sciences Foundation of China(42171467,42001060 and 41705139)Natural Science Foundation of Qinghai Province(2021-ZJ947Q)。
文摘Accurately measuring precipitation is integral for understanding water cycle processes and assessing climate change in the Qinghai–Tibet Plateau(QTP).The Geonor T-200B weighing precipitation gauge with a single Alter shield(Geonor)and the Chinese standard precipitation gauge(CSPG)are widely used for measuring precipitation in the QTP.However,their measurements need to be adjusted for wetting loss,evaporation loss and windinduced undercatch.Four existing transfer functions for adjusting the Geonor-recorded and three transfer functions for adjusting the CSPG-recorded precipitation at hourly,daily or event scale has been proposed based on the precipitation intercomparison experiments conducted at a single site in different regions.Two latest transfer functions for the Geonor(which are referred to as K2017a and K2017b)at the half-hour time scale based on the precipitation intercomparison experiments at multiple stations in the northern hemisphere were provided in the World Meteorological Organization Solid Precipitation Intercomparison Experiment.However,the applicability of these transfer functions in the QTP has not been evaluated.Therefore,the current study carried out a precipitation measurement intercomparison experiment between August 2018 and September 2020 at a site in Beiluhe in central QTP.The performance of these transfer functions at this site was also evaluated on the basis of mean bias(MB),root mean squared error(RMSE)and relative total catch(RTC).The results are as follows:First,the unadjusted RTC values of the Geonor for rain,mixed(snow mixed with rain),snow and hail are 92.06%,85.35%,64.11% and 91.82%,respectively,and the unadjusted RTC values of the CSPG for the same precipitation types are 92.59%,81.32%,46.43% and 95.56%,respectively.Second,K2017a has the most accurate adjustment results for the Geonor-recorded snow and mixed precipitation at the half-hour time scale,and the post-adjustment RTC values increased to 98.25% and 98.23%,respectively.M2007e,an event-based transfer function,was found to have the most accurate adjustment results for the Geonorrecorded snow precipitation at the event scale,and the post-adjustment RTC value increased to 96.36%.Third,the existing transfer functions for CSPG underestimate snowfall,while overestimating rainfall.Fourth,hail is a significant precipitation type in central QTP.The catch efficiency of hail precipitation and the temperature when hail precipitation occurs are close to those of rain;moreover,the transfer functions for rain are suitable for hail as well.
