The model performance in simulating soil water content(SWC) is crucial for successfully modeling earth’s system,especially in high mountainous areas.In this study,the performance of Community Land Model 5.0(CLM5.0) i...The model performance in simulating soil water content(SWC) is crucial for successfully modeling earth’s system,especially in high mountainous areas.In this study,the performance of Community Land Model 5.0(CLM5.0) in simulating liquid SWC was evaluated against observations from nine in-situ sites in the upper reach of the Heihe River Watershed(HRW),Northwest China.The CLM5.0 shows reliable performance in the study area with correlation coefficients(R) ranging between 0.79–0.93,root mean standard errors(RMSE)ranging between 0.044–0.097 m^(3)/m^(3),and the mean bias(BIAS) ranging between-0.084–0.061 m^(3)/m^(3).The slightly worse performance of CLM5.0 than CLM4.5 on alpine meadow and grassland is mainly caused by the revised canopy interception parameterization.The CLM5.0 overestimates interception and underestimates evapotranspiration(ET) on both alpine meadow and grassland during the growth period.The systematical overestimations at all the grassland sites indicate that the underestimation of ET is much larger than the overestimation of interception on grassland during growth period,while the errors of simulated interception and ET are partially canceled out on alpine meadow.Moreover,the underestimation of ET is more responsible for the overestimation of SWC than the overestimation of interception in the high mountainous area.It is necessary to estimate reasonable empirical parameter α(proportion of leaf water collection area) in interception parameterization scheme and further improve the dry surface layerbased soil evaporation resistance parameterization introduced in CLM5.0 in future researches.The performance of CLM5.0 is better under completely frozen stage than thawing stage and freezing stage,because of low variations of liquid SWC caused by extremely low hydraulic conductivity of soils.The underestimation of liquid SWC under frozen state is caused by underestimation of soil temperature,which leads to more ice mass and less liquid water in total water content.展开更多
The mid-southern section of the Hengduan Mountains is a typical region of mountainous landscape in western China and is the core region of "Shangri-La", a world-famous ecotourism destination. The landscape c...The mid-southern section of the Hengduan Mountains is a typical region of mountainous landscape in western China and is the core region of "Shangri-La", a world-famous ecotourism destination. The landscape classification system is an important scientific basis for landscape protection and tourism development in this region. By combining geology and geography and referring to the concepts of "system tract" and "tectonic system" in geology, this paper comes up with grading standards for the geoscience landscape system of this region. Based on the regional stratigraphic structure, tectonic fault marks and geomorphological differentiation, this paper comes up with 2 Grade Ⅰ geoscience landscape system tracts, 8 Grade Ⅱ geoscience landscape systems, 21 Grade Ⅲ geoscience landscape areas, and 165 representative Grade Ⅳ geoscience landscape attractions. According to the main classification methods for the geological heritage and tourism landscapes, the geoscience landscapes can be divided into 4 categories, 16 types and 19 subtypes. On this basis, 23 eco-tourism areas of the mid-southern section of the Hengduan Mountains can be delimited. The study provides a theoretical direction and method reference for the geoscience landscape division and tourism zonation, which has an importantsignificance on the mountain landscape protection and tourism development in the regions of complex geo-environments.展开更多
Accurate estimates of precipitation are fundamental for hydrometeorological and ecohydrological studies,but are more difficult in high mountainous areas because of the high elevation and complex terrain.This study com...Accurate estimates of precipitation are fundamental for hydrometeorological and ecohydrological studies,but are more difficult in high mountainous areas because of the high elevation and complex terrain.This study compares and evaluates two kinds of precipitation datasets,the reanalysis product downscaled by the Weather Research and Forecasting(WRF)output,and the satellite product,the Tropical Rainfall Measuring Mission(TRMM)Multisatellite Precipitation Analysis(TMPA)product,as well as their bias-corrected datasets in the Middle Qilian Mountain in Northwest China.Results show that the WRF output with finer resolution perfonns well in both estimating precipitation and hydrological simulation,while the TMPA product is unreliable in high mountainous areas.Moreover,bias-corrected WRF output also performs better than bias-corrected TMPA product.Combined with the previous studies,atmospheric reanalysis datasets are more suitable than the satellite products in high mountainous areas.Climate is more important than altitude for the\falseAlarms'events of the TRMM product.Designed to focus on the tropical areas,the TMPA product mistakes certain meteorological situations for precipitation in subhumid and semiarid areas,thus causing significant"falseAlarms"events and leading to significant overestimations and unreliable performance.Simple linear bias correction method,only removing systematical errors,can significantly improves the accuracy of both the WRF output and the TMPA product in arid high mountainous areas with data scarcity.Evaluated by hydrological simulations,the bias-corrected WRF output is more reliable than the gauge dataset.Thus,data merging of the WRF output and gauge observations would provide more reliable precipitation estimations in arid high mountainous areas.展开更多
基金partially funded by the National Natural Science Foundation of China (41877148 and 42030501)Key Laboratory of Ecohydrology of Inland River Basin,Chinese Academy of Sciences。
文摘The model performance in simulating soil water content(SWC) is crucial for successfully modeling earth’s system,especially in high mountainous areas.In this study,the performance of Community Land Model 5.0(CLM5.0) in simulating liquid SWC was evaluated against observations from nine in-situ sites in the upper reach of the Heihe River Watershed(HRW),Northwest China.The CLM5.0 shows reliable performance in the study area with correlation coefficients(R) ranging between 0.79–0.93,root mean standard errors(RMSE)ranging between 0.044–0.097 m^(3)/m^(3),and the mean bias(BIAS) ranging between-0.084–0.061 m^(3)/m^(3).The slightly worse performance of CLM5.0 than CLM4.5 on alpine meadow and grassland is mainly caused by the revised canopy interception parameterization.The CLM5.0 overestimates interception and underestimates evapotranspiration(ET) on both alpine meadow and grassland during the growth period.The systematical overestimations at all the grassland sites indicate that the underestimation of ET is much larger than the overestimation of interception on grassland during growth period,while the errors of simulated interception and ET are partially canceled out on alpine meadow.Moreover,the underestimation of ET is more responsible for the overestimation of SWC than the overestimation of interception in the high mountainous area.It is necessary to estimate reasonable empirical parameter α(proportion of leaf water collection area) in interception parameterization scheme and further improve the dry surface layerbased soil evaporation resistance parameterization introduced in CLM5.0 in future researches.The performance of CLM5.0 is better under completely frozen stage than thawing stage and freezing stage,because of low variations of liquid SWC caused by extremely low hydraulic conductivity of soils.The underestimation of liquid SWC under frozen state is caused by underestimation of soil temperature,which leads to more ice mass and less liquid water in total water content.
基金supported by the Sichuan Tourism Youth Expert Training Program in Sichuan Provincial Tourism Development Committee (Grant No. SCTYETP2017L05) the Young Scholars Training Program in Chengdu University of Technology (Grant No. KYGG201424)
文摘The mid-southern section of the Hengduan Mountains is a typical region of mountainous landscape in western China and is the core region of "Shangri-La", a world-famous ecotourism destination. The landscape classification system is an important scientific basis for landscape protection and tourism development in this region. By combining geology and geography and referring to the concepts of "system tract" and "tectonic system" in geology, this paper comes up with grading standards for the geoscience landscape system of this region. Based on the regional stratigraphic structure, tectonic fault marks and geomorphological differentiation, this paper comes up with 2 Grade Ⅰ geoscience landscape system tracts, 8 Grade Ⅱ geoscience landscape systems, 21 Grade Ⅲ geoscience landscape areas, and 165 representative Grade Ⅳ geoscience landscape attractions. According to the main classification methods for the geological heritage and tourism landscapes, the geoscience landscapes can be divided into 4 categories, 16 types and 19 subtypes. On this basis, 23 eco-tourism areas of the mid-southern section of the Hengduan Mountains can be delimited. The study provides a theoretical direction and method reference for the geoscience landscape division and tourism zonation, which has an importantsignificance on the mountain landscape protection and tourism development in the regions of complex geo-environments.
基金Under the auspices of National Natural Science Foundation of China(No.42030501,41877148,41501016,41530752)Scherer Endowment Fund of Department of Geography,Western Michigan University and the Fundamental Research Funds for the Central Universities(No.lzujbky-2019-98)。
文摘Accurate estimates of precipitation are fundamental for hydrometeorological and ecohydrological studies,but are more difficult in high mountainous areas because of the high elevation and complex terrain.This study compares and evaluates two kinds of precipitation datasets,the reanalysis product downscaled by the Weather Research and Forecasting(WRF)output,and the satellite product,the Tropical Rainfall Measuring Mission(TRMM)Multisatellite Precipitation Analysis(TMPA)product,as well as their bias-corrected datasets in the Middle Qilian Mountain in Northwest China.Results show that the WRF output with finer resolution perfonns well in both estimating precipitation and hydrological simulation,while the TMPA product is unreliable in high mountainous areas.Moreover,bias-corrected WRF output also performs better than bias-corrected TMPA product.Combined with the previous studies,atmospheric reanalysis datasets are more suitable than the satellite products in high mountainous areas.Climate is more important than altitude for the\falseAlarms'events of the TRMM product.Designed to focus on the tropical areas,the TMPA product mistakes certain meteorological situations for precipitation in subhumid and semiarid areas,thus causing significant"falseAlarms"events and leading to significant overestimations and unreliable performance.Simple linear bias correction method,only removing systematical errors,can significantly improves the accuracy of both the WRF output and the TMPA product in arid high mountainous areas with data scarcity.Evaluated by hydrological simulations,the bias-corrected WRF output is more reliable than the gauge dataset.Thus,data merging of the WRF output and gauge observations would provide more reliable precipitation estimations in arid high mountainous areas.