The occurrence of earthquakes is closely related to the crustal geotectonic movement and the migration of mass,which consequently cause changes in gravity.The Gravity Recovery And Climate Experiment(GRACE)satellite da...The occurrence of earthquakes is closely related to the crustal geotectonic movement and the migration of mass,which consequently cause changes in gravity.The Gravity Recovery And Climate Experiment(GRACE)satellite data can be used to detect gravity changes associated with large earthquakes.However,previous GRACE satellite-based seismic gravity-change studies have focused more on coseismic gravity changes than on preseismic gravity changes.Moreover,the noise of the north–south stripe in GRACE data is difficult to eliminate,thereby resulting in the loss of some gravity information related to tectonic activities.To explore the preseismic gravity anomalies in a more refined way,we first propose a method of characterizing gravity variation based on the maximum shear strain of gravity,inspired by the concept of crustal strain.The offset index method is then adopted to describe the gravity anomalies,and the spatial and temporal characteristics of gravity anomalies before earthquakes are analyzed at the scales of the fault zone and plate,respectively.In this work,experiments are carried out on the Tibetan Plateau and its surrounding areas,and the following findings are obtained:First,from the observation scale of the fault zone,we detect the occurrence of large-area gravity anomalies near the epicenter,oftentimes about half a year before an earthquake,and these anomalies were distributed along the fault zone.Second,from the observation scale of the plate,we find that when an earthquake occurred on the Tibetan Plateau,a large number of gravity anomalies also occurred at the boundary of the Tibetan Plateau and the Indian Plate.Moreover,the aforementioned experiments confirm that the proposed method can successfully capture the preseismic gravity anomalies of large earthquakes with a magnitude of less than 8,which suggests a new idea for the application of gravity satellite data to earthquake research.展开更多
Water storage has important significance for understanding water cycles of global and local domains and for monitoring climate and environmental changes. As a key variable in hydrology, water storage change represents...Water storage has important significance for understanding water cycles of global and local domains and for monitoring climate and environmental changes. As a key variable in hydrology, water storage change represents the sum of precipitation, evaporation, surface runoff, soil water and groundwater exchanges. Water storage change data during the period of 2003-2008 for the source region of the Yellow River were collected from Gravity Recovery and Climate Experiment （GRACE） satellite data. The monthly actual evaporation was estimated according to the water balance equation. The simulated actual evaporation was significantly consistent and correlative with not only the observed pan （20 cm） data, but also the simulated results of the version 2 of Simple Biosphere model. The average annual evaporation of the Tangnaihai Basin was 506.4 mm, where evaporation in spring, summer, autumn and winter was 130.9 mm, 275.2 mm, 74.3 mm and 26.1 mm, and accounted for 25.8%, 54.3%, 14.7% and 5.2% of the average annual evaporation, respectively, The precipitation increased slightly and the actual evaporation showed an obvious decrease. The water storage change of the source region of the Yellow River displayed an increase of 0.51 mm per month from 2003 to 2008, which indicated that the storage capacity has significantly increased, probably caused by the degradation of permafrost and the increase of the thickness of active layers. The decline of actual evaporation and the increase of water storage capacity resulted in the increase of river runoff.展开更多
As global warming continues,the monitoring of changes in terrestrial water storage becomes increasingly important since it plays a critical role in understanding global change and water resource management.In North Am...As global warming continues,the monitoring of changes in terrestrial water storage becomes increasingly important since it plays a critical role in understanding global change and water resource management.In North America as elsewhere in the world,changes in water resources strongly impact agriculture and animal husbandry.From a combination of Gravity Recovery and Climate Experiment（GRACE） gravity and Global Positioning System（GPS） data,it is recently found that water storage from August,2002 to March,2011 recovered after the extreme Canadian Prairies drought between 1999 and 2005.In this paper,we use GRACE monthly gravity data of Release 5 to track the water storage change from August,2002 to June,2014.In Canadian Prairies and the Great Lakes areas,the total water storage is found to have increased during the last decade by a rate of 73.8 ± 14.5 Gt/a,which is larger than that found in the previous study due to the longer time span of GRACE observations used and the reduction of the leakage error.We also find a long term decrease of water storage at a rate of-12.0 ± 4.2 Gt/a in Ungava Peninsula,possibly due to permafrost degradation and less snow accumulation during the winter in the region.In addition,the effect of total mass gain in the surveyed area,on present-day sea level,amounts to-0.18 mm/a,and thus should be taken into account in studies of global sea level change.展开更多
文章利用重力恢复与气候实验卫星(Gravity Recovery and Climate Experiment,GRACE)时变重力场球谐系数文件,联合全球陆面数据同化系统(Global Land Data Assimilation System,GLDAS)水文模型反演安徽省2003—2016年地下水储量的时空变...文章利用重力恢复与气候实验卫星(Gravity Recovery and Climate Experiment,GRACE)时变重力场球谐系数文件,联合全球陆面数据同化系统(Global Land Data Assimilation System,GLDAS)水文模型反演安徽省2003—2016年地下水储量的时空变化。通过奇异谱分析(Singular Spectrum Analysis,SSA)地下水时间序列,结合热带降雨测量任务(Tropical Rainfall Measuring Mission,TRMM)降雨数据对地下水储量变化规律进行分析。结果表明,安徽省地下水储量在2011年和2014年前后发生较大变化,在2003—2011年的变化率为0.37 cm/a,2011—2014年的下降速率为-0.2 cm/a,2014—2016年的增长速率为1.9 cm/a;进一步与降雨数据关联,发现降雨量是影响安徽省地下水储量年际变化和季节性变化的主要因素。在空间上,安徽省呈现自东北向西南逐渐缓和的趋势,最大亏损出现在皖北地区,为-7.52 mm/a,在西南地区的最大盈余达到8.38 mm/a。展开更多
地下水干旱是影响半干旱沙区植被建设的重要因素,毛乌素沙地位于中国北方干旱半干旱区,地下水资源管理是实现该地区长期可持续发展的重要保障。由于缺乏对地下水在空间和时间维度上的直接观测,地下水干旱的定量评估面临挑战。旨在探索...地下水干旱是影响半干旱沙区植被建设的重要因素,毛乌素沙地位于中国北方干旱半干旱区,地下水资源管理是实现该地区长期可持续发展的重要保障。由于缺乏对地下水在空间和时间维度上的直接观测,地下水干旱的定量评估面临挑战。旨在探索地下水储量的变化规律,基于重力恢复及气候试验(Gravity Recovery and Climate Experiment,GRACE)卫星数据,并结合全球陆地数据同化系统(Global Land Data Assimilation System,GLDAS)观测数据,反演毛乌素沙地2002—2021年地下水储量动态变化。进而构建地下水水位估算指标,并重新定义为GRACE地下水储量变化指数(GRACE Groundwater Storage Index,GGSI),以量化分析该地区的地下水干旱状况。研究选择4种不同的分布函数,通过KS检验选取最优分布函数,其次在不同时间尺度上计算GGSI以定量分析地下水干旱。计算GGSI与降水之间的相关系数,揭示地下水干旱对降水的滞后效应,最后进行GGSI与SPI的时滞分析。结果表明:1)不同的拟合函数对数据拟合结果有不同的反应,该研究区域的最佳拟合函数为PearsonⅢ函数,PearsonⅢ函数能够更准确地反映该地区地下水储量的变化趋势;2)2002—2021年期间GGSI呈波动变化,随着时间尺度的增大,GGSI值变化趋势更为明显,呈先上升后下降整体变化比较稳定的趋势,不同时间尺度下,同一地区的干旱起始、结束及严重程度各异,但干旱期总体一致。毛乌素沙地的干旱年份为2007、2021年;3)干旱对降水的滞后时间集中在5个月和8个月,在这两段滞后期中都表现出了较高的相关性。展开更多
地球重力场的变化是导致陆地水储量变化的重要因素之一,利用GRACE(Gravity Recovery and Climate Experiment)重力场恢复与气候实验重力卫星数据,结合GLDAS(Global Land Data Assimilation Systems)全球陆面数据同化系统和实测地下水位...地球重力场的变化是导致陆地水储量变化的重要因素之一,利用GRACE(Gravity Recovery and Climate Experiment)重力场恢复与气候实验重力卫星数据,结合GLDAS(Global Land Data Assimilation Systems)全球陆面数据同化系统和实测地下水位数据,反演和田地区克里雅河流域11年间四季和田地区的陆地水储量动态变化,模拟计算地下水等效水高变化趋势,构建了地下水水位估算模型。研究结果表明:和田地区春、夏两季的陆地水储量呈现出增加趋势,而秋、冬两季出现亏损状态;GRACE地球重力卫星所反演的陆地水储量比GLDAS同化系统所模拟的水资源变化更为剧烈,但2类数据的动态变化拟合度很高;GLDAS水资源等效水高二阶微分、GLDAS水资源变化倒数一阶微分、GRACE陆地水储量变化倒数变化、地下水储量变化一阶微分的敏感程度最高,构建的多元逐步回归模型明显优于线性函数,且水位深度越浅,该估算模型的适用性越高。展开更多
基金supported by the National Key Research and Development Program of China(Grant No.2019YFC1509202)the National Natural Science Foundation of China(Grant Nos.41772350,61371189,and 41701513).
文摘The occurrence of earthquakes is closely related to the crustal geotectonic movement and the migration of mass,which consequently cause changes in gravity.The Gravity Recovery And Climate Experiment(GRACE)satellite data can be used to detect gravity changes associated with large earthquakes.However,previous GRACE satellite-based seismic gravity-change studies have focused more on coseismic gravity changes than on preseismic gravity changes.Moreover,the noise of the north–south stripe in GRACE data is difficult to eliminate,thereby resulting in the loss of some gravity information related to tectonic activities.To explore the preseismic gravity anomalies in a more refined way,we first propose a method of characterizing gravity variation based on the maximum shear strain of gravity,inspired by the concept of crustal strain.The offset index method is then adopted to describe the gravity anomalies,and the spatial and temporal characteristics of gravity anomalies before earthquakes are analyzed at the scales of the fault zone and plate,respectively.In this work,experiments are carried out on the Tibetan Plateau and its surrounding areas,and the following findings are obtained:First,from the observation scale of the fault zone,we detect the occurrence of large-area gravity anomalies near the epicenter,oftentimes about half a year before an earthquake,and these anomalies were distributed along the fault zone.Second,from the observation scale of the plate,we find that when an earthquake occurred on the Tibetan Plateau,a large number of gravity anomalies also occurred at the boundary of the Tibetan Plateau and the Indian Plate.Moreover,the aforementioned experiments confirm that the proposed method can successfully capture the preseismic gravity anomalies of large earthquakes with a magnitude of less than 8,which suggests a new idea for the application of gravity satellite data to earthquake research.
基金funded by the Global Change Research Program of China (2010CB951401)the National Natural Science Foundation of China (41030638, 41121001, 41030527,41130641,and 41201025)the One Hundred Talents Program of the Chinese Academy of Sciences
文摘Water storage has important significance for understanding water cycles of global and local domains and for monitoring climate and environmental changes. As a key variable in hydrology, water storage change represents the sum of precipitation, evaporation, surface runoff, soil water and groundwater exchanges. Water storage change data during the period of 2003-2008 for the source region of the Yellow River were collected from Gravity Recovery and Climate Experiment （GRACE） satellite data. The monthly actual evaporation was estimated according to the water balance equation. The simulated actual evaporation was significantly consistent and correlative with not only the observed pan （20 cm） data, but also the simulated results of the version 2 of Simple Biosphere model. The average annual evaporation of the Tangnaihai Basin was 506.4 mm, where evaporation in spring, summer, autumn and winter was 130.9 mm, 275.2 mm, 74.3 mm and 26.1 mm, and accounted for 25.8%, 54.3%, 14.7% and 5.2% of the average annual evaporation, respectively, The precipitation increased slightly and the actual evaporation showed an obvious decrease. The water storage change of the source region of the Yellow River displayed an increase of 0.51 mm per month from 2003 to 2008, which indicated that the storage capacity has significantly increased, probably caused by the degradation of permafrost and the increase of the thickness of active layers. The decline of actual evaporation and the increase of water storage capacity resulted in the increase of river runoff.
基金supported by National Natural Science Foundation of China(Grant Nos.41431070,41174016,41274026,41274024,41321063)National Key Basic Research Program of China(973 Program,2012CB957703)+1 种基金CAS/SAFEA International Partnership Program for Creative Research Teams(KZZD-EW-TZ-05)The Chinese Academy of Sciences
文摘As global warming continues,the monitoring of changes in terrestrial water storage becomes increasingly important since it plays a critical role in understanding global change and water resource management.In North America as elsewhere in the world,changes in water resources strongly impact agriculture and animal husbandry.From a combination of Gravity Recovery and Climate Experiment（GRACE） gravity and Global Positioning System（GPS） data,it is recently found that water storage from August,2002 to March,2011 recovered after the extreme Canadian Prairies drought between 1999 and 2005.In this paper,we use GRACE monthly gravity data of Release 5 to track the water storage change from August,2002 to June,2014.In Canadian Prairies and the Great Lakes areas,the total water storage is found to have increased during the last decade by a rate of 73.8 ± 14.5 Gt/a,which is larger than that found in the previous study due to the longer time span of GRACE observations used and the reduction of the leakage error.We also find a long term decrease of water storage at a rate of-12.0 ± 4.2 Gt/a in Ungava Peninsula,possibly due to permafrost degradation and less snow accumulation during the winter in the region.In addition,the effect of total mass gain in the surveyed area,on present-day sea level,amounts to-0.18 mm/a,and thus should be taken into account in studies of global sea level change.
文摘地下水干旱是影响半干旱沙区植被建设的重要因素,毛乌素沙地位于中国北方干旱半干旱区,地下水资源管理是实现该地区长期可持续发展的重要保障。由于缺乏对地下水在空间和时间维度上的直接观测,地下水干旱的定量评估面临挑战。旨在探索地下水储量的变化规律,基于重力恢复及气候试验(Gravity Recovery and Climate Experiment,GRACE)卫星数据,并结合全球陆地数据同化系统(Global Land Data Assimilation System,GLDAS)观测数据,反演毛乌素沙地2002—2021年地下水储量动态变化。进而构建地下水水位估算指标,并重新定义为GRACE地下水储量变化指数(GRACE Groundwater Storage Index,GGSI),以量化分析该地区的地下水干旱状况。研究选择4种不同的分布函数,通过KS检验选取最优分布函数,其次在不同时间尺度上计算GGSI以定量分析地下水干旱。计算GGSI与降水之间的相关系数,揭示地下水干旱对降水的滞后效应,最后进行GGSI与SPI的时滞分析。结果表明:1)不同的拟合函数对数据拟合结果有不同的反应,该研究区域的最佳拟合函数为PearsonⅢ函数,PearsonⅢ函数能够更准确地反映该地区地下水储量的变化趋势;2)2002—2021年期间GGSI呈波动变化,随着时间尺度的增大,GGSI值变化趋势更为明显,呈先上升后下降整体变化比较稳定的趋势,不同时间尺度下,同一地区的干旱起始、结束及严重程度各异,但干旱期总体一致。毛乌素沙地的干旱年份为2007、2021年;3)干旱对降水的滞后时间集中在5个月和8个月,在这两段滞后期中都表现出了较高的相关性。
文摘地球重力场的变化是导致陆地水储量变化的重要因素之一,利用GRACE(Gravity Recovery and Climate Experiment)重力场恢复与气候实验重力卫星数据,结合GLDAS(Global Land Data Assimilation Systems)全球陆面数据同化系统和实测地下水位数据,反演和田地区克里雅河流域11年间四季和田地区的陆地水储量动态变化,模拟计算地下水等效水高变化趋势,构建了地下水水位估算模型。研究结果表明:和田地区春、夏两季的陆地水储量呈现出增加趋势,而秋、冬两季出现亏损状态;GRACE地球重力卫星所反演的陆地水储量比GLDAS同化系统所模拟的水资源变化更为剧烈,但2类数据的动态变化拟合度很高;GLDAS水资源等效水高二阶微分、GLDAS水资源变化倒数一阶微分、GRACE陆地水储量变化倒数变化、地下水储量变化一阶微分的敏感程度最高,构建的多元逐步回归模型明显优于线性函数,且水位深度越浅,该估算模型的适用性越高。
