As an important part of the regional environment, the wet-dry climate condition is determined by precipitation and potential evapotranspiration （expressed as ETo）. Based on weather station data, this study first cal...As an important part of the regional environment, the wet-dry climate condition is determined by precipitation and potential evapotranspiration （expressed as ETo）. Based on weather station data, this study first calculated ETo by using the FAO56 Penrnan-Monteith model. Then, the dryness index K （ratio of ETo to precipitation） was used to study the spatio-temporal variation of the wet-dry condition in China from 1961 to 2015; moreover, dominant climatic factors of the wet-dry condition change were discussed. The annual precipitation and ETo of the Qinling-Huaihe line were close to a balance （K≈1.0）. The annual precipitation in most areas exceeded the ETo in the south of this line and the east of Hengduan Mountains （K〈0.0）, where the climate is wet. Furthermore, the precipitation in the northwest inland areas of China, where the climate is dry, was markedly lower than ETo （K≥4.0）. The overall annual K of China fluctuated around the 55-year mean and its linear trend was not significant. However, a relatively wet period of about 10 yr （1987-1996） was recorded. The overall annual K of China showed strong cyclicality on the time scale of 3, 7-8, 11 and 26-28 yr, and regional differences of the annual K trends and cyclicality were large. The degrees of wetness in the Northwest China and western Qinghai-Tibet Plateau were substantially increased, whereas the degrees of dryness in the Yunnan-Guizhou Plateau, Sichuan Basin, and Loess Plateau were markedly increased. The linear trend of the annual K in most regions of China was not significant, and the annual K of most areas in China showed strong cyclicality on the 8-14 yr time scale. Precipitation was the dominant factor of wet-dry condition change in most areas, especially in North China, where the annual K change was highly correlated with precipitation.展开更多
Supra-permafrost groundwater(SPG)is a key factor that causes damage to highways and railways in the Qinghai-Tibet Engineering Corridor(QTEC).It is difficult to monitor SPG in the field due to their complex formation m...Supra-permafrost groundwater(SPG)is a key factor that causes damage to highways and railways in the Qinghai-Tibet Engineering Corridor(QTEC).It is difficult to monitor SPG in the field due to their complex formation mechanisms and movement characteristics.Traditional single-site field monitoring studies limit the spatial and temporal precision of SPG spatial distribution.To determine the moisture content of shallow soils and the SPG distribution along the QTEC,this work employed the temperature vegetation dryness index and remote sensing models for groundwater table distribution models.The accuracies of the models were validated using mea-surements obtained from different sites in the corridor.In the permafrost zones of the QTEC,72%,22%and 6%of the SPG were located at depths of 0.5-1,<0.5 and>1 m,respectively.Meanwhile,79.4%of the area along the Qinghai-Tibet Highway(QTH)(Xidatan-Tanggula)section contained SPG.In these sections with SPG,37.9%have an SPG table at depths of 0.5-0.8 m.This study preliminarily explored the SPG distribution in the QTEC with a 30 m resolution.The findings can help improve the spatial scale of SPG research,provide a basis for the analysis of the hydrothermal mechanisms,and serve as a guide in the assessment of operational risks and road structure designs.展开更多
The Mongolian Plateau is one of the regions most sensitive to climate change,the more obvious increase of temperature in 21 st century here has been considered as one of the important causes of drought and desertifica...The Mongolian Plateau is one of the regions most sensitive to climate change,the more obvious increase of temperature in 21 st century here has been considered as one of the important causes of drought and desertification.It is very important to understand the multi-year variation and occurrence characteristics of drought in the Mongolian Plateau to explore the ecological environment and the response mechanism of surface materials to climate change.This study examines the spatio-temporal variations in drought and its frequency of occurrence in the Mongolian Plateau based on the Advanced Very High Resolution Radiometer(AVHRR)Normalized Difference Vegetation Index(NDVI)(1982–1999)and the Moderate-resolution Imaging Spectroradiometer(MODIS)(2000–2018)datasets;the Temperature Vegetation Dryness Index(TVDI)was used as a drought evaluation index.The results indicate that drought was widespread across the Mongolian Plateau between1982 and 2018,and aridification incremented in the 21 st century.Between 1982 and 2018,an area of 164.38×10^4 km^2/yr suffered from drought,accounting for approximately 55.28%of the total study area.An area of approximately 150.06×10^4 km^2(51.43%)was subject to more than 160 droughts during 259 months of the growing seasons between 1982 and 2018.We observed variable frequencies of drought occurrence depending on land cover/land use types.Drought predominantly occurred in bare land and grassland,both of which accounting for approximately 79.47%of the total study area.These terrains were characterized by low vegetation and scarce precipitation,which led to frequent and extreme drought events.We also noted significant differences between the areal distribution of drought,drought frequency,and degree of drought depending on the seasons.In spring,droughts were widespread,occurred with a high frequency,and were severe;in autumn,they were localized,frequent,and severe;whereas,in summer,droughts were the most widespread and frequent,but less severe.The increase in temperature,decrease in precipi展开更多
Spatio-temporal dynamic monitoring of soil moisture is highly important to management of agricultural and vegetation eco-systems.The temperature-vegetation dryness index based on the triangle or trapezoid method has b...Spatio-temporal dynamic monitoring of soil moisture is highly important to management of agricultural and vegetation eco-systems.The temperature-vegetation dryness index based on the triangle or trapezoid method has been used widely in previous studies.However,most existing studies simply used linear regression to construct empirical models to fit the edges of the feature space.This requires extensive data from a vast study area,and may lead to subjective results.In this study,a Modified Temperature-Vegetation Dryness Index(MTVDI)was used to monitor surface soil moisture status using MODIS(Moderate-resolution Imaging Spectroradiometer)remote sensing data,in which the dry edge conditions were determined at the pixel scale based on surface energy balance.The MTVDI was validated by field measurements at 30 sites for 10 d and compared with the Temperature-Vegetation Dryness Index(TVDI).The results showed that the R^(2) for MTVDI and soil moisture obviously improved(0.45 for TVDI,0.69 for MTVDI).As for spatial changes,MTVDI can also better reflect the actual soil moisture condition than TVDI.As a result,MTVDI can be considered an effective method to monitor the spatio-temporal changes in surface soil moisture on a regional scale.展开更多
Temperature vegetation dryness index(TVDI)in a triangular or trapezoidal feature space can be calculated from the land surface temperature(LST)and normalized difference vegetation index(NDVI),and has been widely appli...Temperature vegetation dryness index(TVDI)in a triangular or trapezoidal feature space can be calculated from the land surface temperature(LST)and normalized difference vegetation index(NDVI),and has been widely applied to regional drought monitoring.However,thermal infrared sensors cannot penetrate clouds to detect surface information of sub-cloud pixels.In cloudy areas,LST data include a large number of cloudy pixels,seriously degrading the spatial and temporal continuity of drought monitoring.In this paper,the Remotely Sensed Daily Land Surface Temperature Reconstruction model(RSDAST)is combined with the LST reconstructed(RLST)by the RSDAST and applied to drought monitoring in a cloudy area.The drought monitoring capability of the reconstructed temperature vegetation drought index(RTVDI)under cloudy conditions is evaluated by comparing the correlation between land surface observations for soil moisture and the TVDI before and after surface temperature reconstruction.Results show that the effective duration and area of the RTVDI in the study area were larger than those of the original TVDI(OTVDI)in 2011.In addition,RLST/NDVI scatter plots cover a wide range of values,with the fitted dry–wet boundaries more representative of real soil moisture conditions.Under continuously cloudy conditions,the OTVDI inverted from the original LST(OLST)loses its drought monitoring capability,whereas RTVDI can completely and accurately reconstruct surface moisture conditions across the entire study area.The correlation between TVDI and soil moisture is stronger for RTVDI(R=-0.45)than that for OTVDI(R=-0.33).In terms of the spatial and temporal distributions,the R value for correlation between RTVDI and soil moisture was higher than that for OTVDI.Hence,in continuously cloudy areas,RTVDI not only expands drought monitoring capability in time and space,but also improves the accuracy of surface soil moisture monitoring and enhances the applicability and reliability of thermal infrared data under extreme conditions.展开更多
Development of drought monitoring techniques is important for understanding and mitigating droughts and for rational agricultural management. This study used data from multiple sources, including MOD13 A3, TRMM 3 B43,...Development of drought monitoring techniques is important for understanding and mitigating droughts and for rational agricultural management. This study used data from multiple sources, including MOD13 A3, TRMM 3 B43, and SRTMDEM, for Yunnan Province, China from 2009 to 2018 to calculate the tropical rainfall condition index(TRCI), vegetation condition index(VCI), temperature condition index(TCI), and elevation factors. Principal component analysis(PCA) and analytic hierarchy process(AHP) were used to construct comprehensive drought monitoring models for Yunnan Province. The reliability of the models was verified, following which the drought situation in Yunnan Province for the past ten years was analysed. The results showed that:(1) The comprehensive drought index(CDI) had a high correlation with the standardized precipitation index, standardized precipitation evapotranspiration index, temperature vegetation dryness index, and CLDAS(China Meteorological Administration land data assimilation system), indicating that the CDI was a strong indicator of drought through meteorological, remote sensing and soil moisture monitoring.(2) The droughts from 2009 to 2018 showed generally consistent spatiotemporal changes. Droughts occurred in most parts of the province, with an average drought frequency of 29% and four droughtprone centres.(3) Monthly drought coverage during 2009 to 2014 exceeded that over 2015 to 2018. January had the largest average drought coverage over the study period(61.92%). Droughts at most stations during the remaining months except for October exhibited a weakening trend(slope > 0). The CDI provides a novel approach for drought monitoring in areas with complex terrain such as Yunnan Province.展开更多
基金supported by the Key Projects of National Natural Science Foundation of China(Grant No.41530749)the Youth Projects of National Natural Science Foundation of China(Grant Nos.41501202&41701100)the Science and Technology Project of Sichuan Provincial Department of Education(Grant No.15ZB0023)
文摘As an important part of the regional environment, the wet-dry climate condition is determined by precipitation and potential evapotranspiration （expressed as ETo）. Based on weather station data, this study first calculated ETo by using the FAO56 Penrnan-Monteith model. Then, the dryness index K （ratio of ETo to precipitation） was used to study the spatio-temporal variation of the wet-dry condition in China from 1961 to 2015; moreover, dominant climatic factors of the wet-dry condition change were discussed. The annual precipitation and ETo of the Qinling-Huaihe line were close to a balance （K≈1.0）. The annual precipitation in most areas exceeded the ETo in the south of this line and the east of Hengduan Mountains （K〈0.0）, where the climate is wet. Furthermore, the precipitation in the northwest inland areas of China, where the climate is dry, was markedly lower than ETo （K≥4.0）. The overall annual K of China fluctuated around the 55-year mean and its linear trend was not significant. However, a relatively wet period of about 10 yr （1987-1996） was recorded. The overall annual K of China showed strong cyclicality on the time scale of 3, 7-8, 11 and 26-28 yr, and regional differences of the annual K trends and cyclicality were large. The degrees of wetness in the Northwest China and western Qinghai-Tibet Plateau were substantially increased, whereas the degrees of dryness in the Yunnan-Guizhou Plateau, Sichuan Basin, and Loess Plateau were markedly increased. The linear trend of the annual K in most regions of China was not significant, and the annual K of most areas in China showed strong cyclicality on the 8-14 yr time scale. Precipitation was the dominant factor of wet-dry condition change in most areas, especially in North China, where the annual K change was highly correlated with precipitation.
基金supported by the National Natural Science Foundation of China (42001065 and 41630636)the Open Project of State Key Laboratory of Frozen Soil Engineering (SKLFSE202106)the University First-Class Discipline Construction Project of Ningxia,China (NXYLXK2021A03).
文摘Supra-permafrost groundwater(SPG)is a key factor that causes damage to highways and railways in the Qinghai-Tibet Engineering Corridor(QTEC).It is difficult to monitor SPG in the field due to their complex formation mechanisms and movement characteristics.Traditional single-site field monitoring studies limit the spatial and temporal precision of SPG spatial distribution.To determine the moisture content of shallow soils and the SPG distribution along the QTEC,this work employed the temperature vegetation dryness index and remote sensing models for groundwater table distribution models.The accuracies of the models were validated using mea-surements obtained from different sites in the corridor.In the permafrost zones of the QTEC,72%,22%and 6%of the SPG were located at depths of 0.5-1,<0.5 and>1 m,respectively.Meanwhile,79.4%of the area along the Qinghai-Tibet Highway(QTH)(Xidatan-Tanggula)section contained SPG.In these sections with SPG,37.9%have an SPG table at depths of 0.5-0.8 m.This study preliminarily explored the SPG distribution in the QTEC with a 30 m resolution.The findings can help improve the spatial scale of SPG research,provide a basis for the analysis of the hydrothermal mechanisms,and serve as a guide in the assessment of operational risks and road structure designs.
基金Under the auspices of Special Project on Basic Resources of Science and Technology(No.2017FY101301)National Natural Science Foundation of China(No.41971398,31770764)Natural Science Foundation Balance Project(No.IDS2019JY-2)。
文摘The Mongolian Plateau is one of the regions most sensitive to climate change,the more obvious increase of temperature in 21 st century here has been considered as one of the important causes of drought and desertification.It is very important to understand the multi-year variation and occurrence characteristics of drought in the Mongolian Plateau to explore the ecological environment and the response mechanism of surface materials to climate change.This study examines the spatio-temporal variations in drought and its frequency of occurrence in the Mongolian Plateau based on the Advanced Very High Resolution Radiometer(AVHRR)Normalized Difference Vegetation Index(NDVI)(1982–1999)and the Moderate-resolution Imaging Spectroradiometer(MODIS)(2000–2018)datasets;the Temperature Vegetation Dryness Index(TVDI)was used as a drought evaluation index.The results indicate that drought was widespread across the Mongolian Plateau between1982 and 2018,and aridification incremented in the 21 st century.Between 1982 and 2018,an area of 164.38×10^4 km^2/yr suffered from drought,accounting for approximately 55.28%of the total study area.An area of approximately 150.06×10^4 km^2(51.43%)was subject to more than 160 droughts during 259 months of the growing seasons between 1982 and 2018.We observed variable frequencies of drought occurrence depending on land cover/land use types.Drought predominantly occurred in bare land and grassland,both of which accounting for approximately 79.47%of the total study area.These terrains were characterized by low vegetation and scarce precipitation,which led to frequent and extreme drought events.We also noted significant differences between the areal distribution of drought,drought frequency,and degree of drought depending on the seasons.In spring,droughts were widespread,occurred with a high frequency,and were severe;in autumn,they were localized,frequent,and severe;whereas,in summer,droughts were the most widespread and frequent,but less severe.The increase in temperature,decrease in precipi
基金Under the auspices of the National Natural Science Foundation of China(No.41801180)the Natural Science Basic Research Plan in Shaanxi Province of China(No.2020JQ415,2019JQ-767)。
文摘Spatio-temporal dynamic monitoring of soil moisture is highly important to management of agricultural and vegetation eco-systems.The temperature-vegetation dryness index based on the triangle or trapezoid method has been used widely in previous studies.However,most existing studies simply used linear regression to construct empirical models to fit the edges of the feature space.This requires extensive data from a vast study area,and may lead to subjective results.In this study,a Modified Temperature-Vegetation Dryness Index(MTVDI)was used to monitor surface soil moisture status using MODIS(Moderate-resolution Imaging Spectroradiometer)remote sensing data,in which the dry edge conditions were determined at the pixel scale based on surface energy balance.The MTVDI was validated by field measurements at 30 sites for 10 d and compared with the Temperature-Vegetation Dryness Index(TVDI).The results showed that the R^(2) for MTVDI and soil moisture obviously improved(0.45 for TVDI,0.69 for MTVDI).As for spatial changes,MTVDI can also better reflect the actual soil moisture condition than TVDI.As a result,MTVDI can be considered an effective method to monitor the spatio-temporal changes in surface soil moisture on a regional scale.
基金Supported by the National Natural Science Foundation of China(41631180 and 41801315)Science and Technology Department of Chongqing Municipality(cstc2019jcyj-msxm X0649)Innovation Project of Chinese Academy of Agricultural Sciences(960-3)。
文摘Temperature vegetation dryness index(TVDI)in a triangular or trapezoidal feature space can be calculated from the land surface temperature(LST)and normalized difference vegetation index(NDVI),and has been widely applied to regional drought monitoring.However,thermal infrared sensors cannot penetrate clouds to detect surface information of sub-cloud pixels.In cloudy areas,LST data include a large number of cloudy pixels,seriously degrading the spatial and temporal continuity of drought monitoring.In this paper,the Remotely Sensed Daily Land Surface Temperature Reconstruction model(RSDAST)is combined with the LST reconstructed(RLST)by the RSDAST and applied to drought monitoring in a cloudy area.The drought monitoring capability of the reconstructed temperature vegetation drought index(RTVDI)under cloudy conditions is evaluated by comparing the correlation between land surface observations for soil moisture and the TVDI before and after surface temperature reconstruction.Results show that the effective duration and area of the RTVDI in the study area were larger than those of the original TVDI(OTVDI)in 2011.In addition,RLST/NDVI scatter plots cover a wide range of values,with the fitted dry–wet boundaries more representative of real soil moisture conditions.Under continuously cloudy conditions,the OTVDI inverted from the original LST(OLST)loses its drought monitoring capability,whereas RTVDI can completely and accurately reconstruct surface moisture conditions across the entire study area.The correlation between TVDI and soil moisture is stronger for RTVDI(R=-0.45)than that for OTVDI(R=-0.33).In terms of the spatial and temporal distributions,the R value for correlation between RTVDI and soil moisture was higher than that for OTVDI.Hence,in continuously cloudy areas,RTVDI not only expands drought monitoring capability in time and space,but also improves the accuracy of surface soil moisture monitoring and enhances the applicability and reliability of thermal infrared data under extreme conditions.
基金This research was funded by the Multigovernment International Science and Technology Innovation Cooperation Key Project of the National Key Research and Development Program of China(Grant No.2018YFE0184300)Erasmus+Capacity Building in Higher Education of the Education,Audiovisual and Culture Executive Agency(EACEA)(Grant No.586037-EPP-1-2017-1-HU-EPPKA2CBHE-JP)+3 种基金the National Natural Science Foundation of China(Grant No.41561048)the Technical Methods and Empirical Study on Ecological Assets Measurement in County Level of Yunnan Province(Grant No.ZDZZD201506)the Young and Middleaged Academic and Technical Leaders Reserve Talents Training Program of Yunnan Province(Grant No.2008PY056)the Program for Innovative Research Team(in Science and Technology)at the University of Yunnan Province,IRTSTYN。
文摘Development of drought monitoring techniques is important for understanding and mitigating droughts and for rational agricultural management. This study used data from multiple sources, including MOD13 A3, TRMM 3 B43, and SRTMDEM, for Yunnan Province, China from 2009 to 2018 to calculate the tropical rainfall condition index(TRCI), vegetation condition index(VCI), temperature condition index(TCI), and elevation factors. Principal component analysis(PCA) and analytic hierarchy process(AHP) were used to construct comprehensive drought monitoring models for Yunnan Province. The reliability of the models was verified, following which the drought situation in Yunnan Province for the past ten years was analysed. The results showed that:(1) The comprehensive drought index(CDI) had a high correlation with the standardized precipitation index, standardized precipitation evapotranspiration index, temperature vegetation dryness index, and CLDAS(China Meteorological Administration land data assimilation system), indicating that the CDI was a strong indicator of drought through meteorological, remote sensing and soil moisture monitoring.(2) The droughts from 2009 to 2018 showed generally consistent spatiotemporal changes. Droughts occurred in most parts of the province, with an average drought frequency of 29% and four droughtprone centres.(3) Monthly drought coverage during 2009 to 2014 exceeded that over 2015 to 2018. January had the largest average drought coverage over the study period(61.92%). Droughts at most stations during the remaining months except for October exhibited a weakening trend(slope > 0). The CDI provides a novel approach for drought monitoring in areas with complex terrain such as Yunnan Province.
