Spatio-temporal variations of water vapor optical depth in the lower troposphere (450-3850 m) over Pune (18°32′N, 73°51′E, 559 m Above Mean Sea Level), India have been studied over a period of five years. ...Spatio-temporal variations of water vapor optical depth in the lower troposphere (450-3850 m) over Pune (18°32′N, 73°51′E, 559 m Above Mean Sea Level), India have been studied over a period of five years. The mean vertical structure showed that the moisture content is greatest at the lowest level and decreases with increasing altitude, except in the south-west monsoon season (June to September) where an increase upto 950 m has been found. Optical depths are maximum in the monsoon season. The increase from pre-monsoon (March-May) to monsoon season in moisture content on an average is by about 58% in the above altitude range. The temporal variations in surface Relative Humidity and optical depth at 450 m show positive correlation. The amplitude of seasonal oscillation is the largest at 1465 m altitude. The time-height cross-sections of water vapor optical depths in the lower troposphere showed a contrast between years of good and bad monsoon.展开更多
Aimed at high turbid coastal waters, an improved algorithm for retrieval ofaerosol optical properties from Geostationary Ocean Color Imager （GOCI） is proposed.The algorithm adopts support vector machine （SVM） to s...Aimed at high turbid coastal waters, an improved algorithm for retrieval ofaerosol optical properties from Geostationary Ocean Color Imager （GOCI） is proposed.The algorithm adopts support vector machine （SVM） to separate the interfering signalof phytoplankton pigments, suspended matter and chromophoric dissolved organicmatter （CDOM）. Radioactive Transfer Model （RTM） Rstar5b is utilized to simulate thetransmitting process. The algorithm can retrieve aerosol optical depth （AOD） andaerosol types simultaneously. In the study, the aerosol optical depth was retrieved overthe turbid waters in the summer of 2014 and 2015. The results of inversion werecompared with the corresponding AERONET data and GOCI service product toestimate the accuracy of the advanced method. The study shows that this algorithmhas better performance compared with GOCI service algorithm for turbid water in theYellow Sea.展开更多
To better understand soil moisture dynamics in the Yangtze River Estuary （YRE） and predict its variation in a simple way, a field monitoring experiment was carried out along the north branch of the Yangtze River, wh...To better understand soil moisture dynamics in the Yangtze River Estuary （YRE） and predict its variation in a simple way, a field monitoring experiment was carried out along the north branch of the Yangtze River, where seawater intrusion was strong and salt-water variation is one of the limiting factors of local agriculture. In present paper, relation between antecedent precipitation index （API） and soil water content is studied, and effects of groundwater depth on soil water content was analyzed. A relatively accurate prediction result of soil water content was reached using a neural network model. The impact analysis result showed that the variation of the API was consistent with soil water content and it displayed significant correlations with soil water content in both 20 and 50 cm soil layer, and higher correlation was observed in the layer of 20 cm. Groundwater impact analysis suggested that soil moisture was affected by the depth of groundwater, and was affected more greatly by groundwater at depth of 50 cm than that at 20 cm layer. By introducing API, groundwater depth and temperature together, a BP artificial network model was established to predict soil water content and an acceptable agreement was achieved. The model can be used for supplementing monitoring data of soil water content and predicting soil water content in shallow groundwater areas, and can provide favorable support for the research of water and salt transport in estuary area.展开更多
Quantitative assessment of the impact of groundwater depletion on phreatophytes in(hyper-)arid regions is key to sustainable groundwater management.However,a parsimonious model for predicting the response of phreatoph...Quantitative assessment of the impact of groundwater depletion on phreatophytes in(hyper-)arid regions is key to sustainable groundwater management.However,a parsimonious model for predicting the response of phreatophytes to a decrease of the water table is lacking.A variable saturated flow model,HYDRUS-1D,was used to numerically assess the influences of depth to the water table(DWT)and mean annual precipitation(MAP)on transpiration of groundwater-dependent vegetation in(hyper-)arid regions of northwest China.An exponential relationship is found for the normalized transpiration(a ratio of transpiration at a certain DWT to transpiration at 1 m depth,T_(a)^(*))with increasing DWT,while a positive linear relationship is identified between T_(a)^(*)and annual precipitation.Sensitivity analysis shows that the model is insensitive to parameters,such as saturated soil hydraulic conductivity and water stress parameters,indicated by an insignificant variation(less than 20%in most cases)under±50%changes of these parameters.Based on these two relationships,a universal model has been developed to predict the response of phreatophyte transpiration to groundwater drawdown for(hyper-)arid regions using MAP only.The estimated T_(a)^(*)from the model is reasonable by comparing with published measured values.展开更多
卫星导航定位连续运行参考站(continuously operating reference stations,CORS)系统作为GNSS与网络通信技术结合发展出的新兴导航定位CORS系统,具有快速高效、高精度、网络化等优点,不仅可以测量地表位置及运动,还可以借助GNSS信号的...卫星导航定位连续运行参考站(continuously operating reference stations,CORS)系统作为GNSS与网络通信技术结合发展出的新兴导航定位CORS系统,具有快速高效、高精度、网络化等优点,不仅可以测量地表位置及运动,还可以借助GNSS信号的折射与反射特征监测地表环境参数变化情况.本文提出一种将CORS站用于“积雪深度、土壤湿度、大气水汽、地表形变”的地表环境多参数综合监测体系,用以拓展CORS站在生态环境中的广泛应用.以齐齐哈尔市CORS站BFQE为实验案例,首先获取实验时段中CORS站接收的GNSS观测数据(含信噪比(signal to noise ratio,SNR)数据)、星历数据及气象数据对其进行预处理;其次对重采样的SNR数据采用非线性最小二乘及Lomb-Scargle谱分析方法解译特定时间段的浅层土壤湿度及地表积雪深度;然后通过联测远距离国际地球动力学服务机构站(International GPS Service for Geodynamics,IGS)采用相对定位技术获取测站的地表形变序列与大气水汽序列;最后,结合上述多种地表环境参数结果进行相关性分析,获得参数间的响应关系.实验结果表明:CORS站用于地表环境综合监测能够有效地监测多参数时间变化,反演得到的环境参数之间具有一定的响应关系.大气水汽含量会影响降雨的时空分布和强度,大气水汽反演值与降雨在趋势上呈现高度相关;在积雪时段,大气水汽的增加伴随着积雪深度的增加;大气水汽增加形成的降雨是土壤湿度的主要来源,解译土壤湿度总是在强降雨后呈现上升趋势,基于单星的土壤湿度与实测数据平均相关性为0.75,多星融合解译结果的相关性达到0.89,土壤含水率的均方根误差(root mean squared error,RMSE)为0.87%;地表形变时间序列在北(north,N)、东(east,E)方向形变较为稳定,天顶(up,U)方向的形变与大气水汽、积雪深度和土壤湿度存在一定的响应性波动.展开更多
文摘Spatio-temporal variations of water vapor optical depth in the lower troposphere (450-3850 m) over Pune (18°32′N, 73°51′E, 559 m Above Mean Sea Level), India have been studied over a period of five years. The mean vertical structure showed that the moisture content is greatest at the lowest level and decreases with increasing altitude, except in the south-west monsoon season (June to September) where an increase upto 950 m has been found. Optical depths are maximum in the monsoon season. The increase from pre-monsoon (March-May) to monsoon season in moisture content on an average is by about 58% in the above altitude range. The temporal variations in surface Relative Humidity and optical depth at 450 m show positive correlation. The amplitude of seasonal oscillation is the largest at 1465 m altitude. The time-height cross-sections of water vapor optical depths in the lower troposphere showed a contrast between years of good and bad monsoon.
基金supported by Tianjin Natural Science Foundation Project(14JCYBJC22500)
文摘Aimed at high turbid coastal waters, an improved algorithm for retrieval ofaerosol optical properties from Geostationary Ocean Color Imager （GOCI） is proposed.The algorithm adopts support vector machine （SVM） to separate the interfering signalof phytoplankton pigments, suspended matter and chromophoric dissolved organicmatter （CDOM）. Radioactive Transfer Model （RTM） Rstar5b is utilized to simulate thetransmitting process. The algorithm can retrieve aerosol optical depth （AOD） andaerosol types simultaneously. In the study, the aerosol optical depth was retrieved overthe turbid waters in the summer of 2014 and 2015. The results of inversion werecompared with the corresponding AERONET data and GOCI service product toestimate the accuracy of the advanced method. The study shows that this algorithmhas better performance compared with GOCI service algorithm for turbid water in theYellow Sea.
基金financially supported by the Ecological and Environmental Monitoring Project (JJ[2011]-017)funded by the Executive Office of the Three Gorges Project Construction Committee of the State Council of China+1 种基金the National Non-Profit Research Program of China (200903001)the National Basic Research Program of China(2010CB429001)
文摘To better understand soil moisture dynamics in the Yangtze River Estuary （YRE） and predict its variation in a simple way, a field monitoring experiment was carried out along the north branch of the Yangtze River, where seawater intrusion was strong and salt-water variation is one of the limiting factors of local agriculture. In present paper, relation between antecedent precipitation index （API） and soil water content is studied, and effects of groundwater depth on soil water content was analyzed. A relatively accurate prediction result of soil water content was reached using a neural network model. The impact analysis result showed that the variation of the API was consistent with soil water content and it displayed significant correlations with soil water content in both 20 and 50 cm soil layer, and higher correlation was observed in the layer of 20 cm. Groundwater impact analysis suggested that soil moisture was affected by the depth of groundwater, and was affected more greatly by groundwater at depth of 50 cm than that at 20 cm layer. By introducing API, groundwater depth and temperature together, a BP artificial network model was established to predict soil water content and an acceptable agreement was achieved. The model can be used for supplementing monitoring data of soil water content and predicting soil water content in shallow groundwater areas, and can provide favorable support for the research of water and salt transport in estuary area.
基金This research was funded by projects of the China Geological Survey(12120113104100 and DD20190351)National Natural Science Foundation of China(41877199)Shaanxi Science and Technology Department(2019TD-040,2021ZDLSF05-01).
文摘Quantitative assessment of the impact of groundwater depletion on phreatophytes in(hyper-)arid regions is key to sustainable groundwater management.However,a parsimonious model for predicting the response of phreatophytes to a decrease of the water table is lacking.A variable saturated flow model,HYDRUS-1D,was used to numerically assess the influences of depth to the water table(DWT)and mean annual precipitation(MAP)on transpiration of groundwater-dependent vegetation in(hyper-)arid regions of northwest China.An exponential relationship is found for the normalized transpiration(a ratio of transpiration at a certain DWT to transpiration at 1 m depth,T_(a)^(*))with increasing DWT,while a positive linear relationship is identified between T_(a)^(*)and annual precipitation.Sensitivity analysis shows that the model is insensitive to parameters,such as saturated soil hydraulic conductivity and water stress parameters,indicated by an insignificant variation(less than 20%in most cases)under±50%changes of these parameters.Based on these two relationships,a universal model has been developed to predict the response of phreatophyte transpiration to groundwater drawdown for(hyper-)arid regions using MAP only.The estimated T_(a)^(*)from the model is reasonable by comparing with published measured values.
文摘卫星导航定位连续运行参考站(continuously operating reference stations,CORS)系统作为GNSS与网络通信技术结合发展出的新兴导航定位CORS系统,具有快速高效、高精度、网络化等优点,不仅可以测量地表位置及运动,还可以借助GNSS信号的折射与反射特征监测地表环境参数变化情况.本文提出一种将CORS站用于“积雪深度、土壤湿度、大气水汽、地表形变”的地表环境多参数综合监测体系,用以拓展CORS站在生态环境中的广泛应用.以齐齐哈尔市CORS站BFQE为实验案例,首先获取实验时段中CORS站接收的GNSS观测数据(含信噪比(signal to noise ratio,SNR)数据)、星历数据及气象数据对其进行预处理;其次对重采样的SNR数据采用非线性最小二乘及Lomb-Scargle谱分析方法解译特定时间段的浅层土壤湿度及地表积雪深度;然后通过联测远距离国际地球动力学服务机构站(International GPS Service for Geodynamics,IGS)采用相对定位技术获取测站的地表形变序列与大气水汽序列;最后,结合上述多种地表环境参数结果进行相关性分析,获得参数间的响应关系.实验结果表明:CORS站用于地表环境综合监测能够有效地监测多参数时间变化,反演得到的环境参数之间具有一定的响应关系.大气水汽含量会影响降雨的时空分布和强度,大气水汽反演值与降雨在趋势上呈现高度相关;在积雪时段,大气水汽的增加伴随着积雪深度的增加;大气水汽增加形成的降雨是土壤湿度的主要来源,解译土壤湿度总是在强降雨后呈现上升趋势,基于单星的土壤湿度与实测数据平均相关性为0.75,多星融合解译结果的相关性达到0.89,土壤含水率的均方根误差(root mean squared error,RMSE)为0.87%;地表形变时间序列在北(north,N)、东(east,E)方向形变较为稳定,天顶(up,U)方向的形变与大气水汽、积雪深度和土壤湿度存在一定的响应性波动.
