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
The Gravity Recovery and Climate Experiment（GRACE） satellite mission provides a unique opportunity to quantitatively study terrestrial water storage（TWS） variations. In this paper,the terrestrial water storage var...The Gravity Recovery and Climate Experiment（GRACE） satellite mission provides a unique opportunity to quantitatively study terrestrial water storage（TWS） variations. In this paper,the terrestrial water storage variations in the Poyang Lake Basin are recovered from the GRACE gravity data from January 2003 to March 2014 and compared with the Global Land Data Assimilation System（GLDAS） hydrological models and satellite altimetry. Furthermore, the impact of soil moisture content from GLDAS and rainfall from the Tropical Rainfall Measuring Mission（TRMM） on TWS variations are investigated. Our results indicate that the TWS variations from GRACE, GLDAS and satellite altimetry have a general consistency. The TWS trends in the Poyang Lake Basin determined from GRACE, GLDAS and satellite altimetry are increasing at 0.0141 km^3/a, 0.0328 km^3/a and 0.0238 km^3/a,respectively during the investigated time period. The TWS is governed mainly by the soil moisture content and dominated primarily by the precipitation but also modulated by the flood season of the Yangtze River as well as the lake and river exchange water.展开更多
There are only limited surface water resources available in the Heihe River Basin （HRB）, a typical inland river basin in the arid region of northwestern China, where groundwater overexploitation is a serious problem...There are only limited surface water resources available in the Heihe River Basin （HRB）, a typical inland river basin in the arid region of northwestern China, where groundwater overexploitation is a serious problem. Groundwater has become one of main resources of fresh water in the HRB. In this paper, temporal and spatial variations of groundwater in the HRB are estimated by the Gravity Recovery and Climate Experiment （GRACE） satellites. Our analysis shows that groundwater storage in the HRB reaches its highest in the summer of 2005, and then begins to decline in the following years and reaches steady status in 2008. Spatially, groundwater shows a decline in the upper HRB in the first two years and a slight increase in the following years, while this phenomenon is reversed in the middle HRB where groundwater slightly increases in 2005 and then declines in the following three years. In the lower HRB, GRACE detects a continual increase in the full six-year period. This approach is proven successful when employed in the HRB and thus offers a new insight into monitoring groundwater variations in a river basin with limited or even without any observed data.展开更多
The basic principle of spectral combination method is discussed,and the general expressions of the spectral weight and spectral combination of the united-processing of various types of gravimetric data are shown.What...The basic principle of spectral combination method is discussed,and the general expressions of the spectral weight and spectral combination of the united-processing of various types of gravimetric data are shown.What＇s more,based on degree error RMS of potential coefficients,the detailed expressions of spectral combination formulae and the corresponding spectral weights in the Earth＇s gravitational field model（EGM） determination using GOCE ＋ GRACE and CHAMP ＋ GRACE ＋ GOCE are derived.The fundamental situation that ulux-champ2013 s,tongji-GRACE01,go-cons-gcf-2-tim-r5 constructed respectively by CHAMP,GRACE,GOCE data and go-cons-gcf-2-dir-r5 constructed by syncretic processing of GRACE,GOCE and LAGEOS data are explained briefly,the degree error RMS,cumulative geoid height error and cumulative gravity anomaly error of these models are calculated.A syncretic model constructed from CHAMP,GRACE and GOCE data,which is expressed by champ ＋ grace ＋ goce,is obtained based on spectral combination method.Experimentation results show that the precision of CHAMP data model is the lowest in satellite-only models,so it is not needed in the determination of syncretic models.The GRACE data model can improve the GOCE data model in medium-long wavelength,so the overall precision of syncretic model can be improved.Consequently,as many types of gravimetric data as possible should be combined together in the data processing in order to strengthen the quality and reliability with widening scope and improve the precision and spatial resolution of the computational results.展开更多
In this paper we present a series of monthly gravity field solutions from Gravity Recovery and Climate Experiment（GRACE） range measurements using modified short arc approach,in which the ambiguity of range measureme...In this paper we present a series of monthly gravity field solutions from Gravity Recovery and Climate Experiment（GRACE） range measurements using modified short arc approach,in which the ambiguity of range measurements is eliminated via differentiating two adjacent range measurements.The data used for developing our monthly gravity field model are same as Tongji-GRACEOl model except that the range measurements are used to replace the range rate measurements,and our model is truncated to degree and order 60,spanning Jan.2004 to Dec.2010 also same as Tongji-GRACE01 model.Based on the comparison results of the C_（2,0）,C_（2,1）,S_（2,1）,and C_（15,15）,S_（15,15）,time series and the global mass change signals as well as the mass change time series in Amazon area of our model with those of Tongji-GRACE01 model,we can conclude that our monthly gravity field model is comparable with Tongji-GRACE01 monthly model.展开更多
With the Gravity Recovery and Climate Experiment {GRACE） mission as the prime example, an overview is given on the management and processing of Level IA data of a low-low satellite to satellite tracking mission. To i...With the Gravity Recovery and Climate Experiment {GRACE） mission as the prime example, an overview is given on the management and processing of Level IA data of a low-low satellite to satellite tracking mission. To illustrate the underlying principle and algorithm, a detailed study is made on the K-band ranging （KBR） assembly, which includes the measurement principles, modeling of noises, the generation of Level 1A data from that of Level 0 as well as Level IA to Level IB data processing.展开更多
A new temporal gravity field model called WHU-Grace01s solely recovered from Gravity Recovery and Climate Experiment （GRACE） K-Band Range Rate （KBRR） data based on dynamic integral approach is presented in this pa...A new temporal gravity field model called WHU-Grace01s solely recovered from Gravity Recovery and Climate Experiment （GRACE） K-Band Range Rate （KBRR） data based on dynamic integral approach is presented in this paper. After meticulously preprocessing of the GRACE KBRR data, the root mean square of its post residuals is about 0.2 micrometers per second, and seventy-two monthly temporal solutions truncated to degree and order 60 are computed for the period from January 2003 to December 2008. After applying the combi- nation filter in WHU-Grace01s, the global temporal signals show obvious periodical change rules in the large-scale fiver basins. In terms of the degree variance, our solution is smaller at high degrees, and shows a good consistency at the rest of degrees with the Release 05 models from Center for Space Research （CSR）, GeoForschungsZentrum Potsdam （GFZ） and Jet Pro- pulsion Laboratory 0PL）. Compared with other published models in terms of equivalent water height distribution, our solution is consistent with those published by CSR, GFZ, JPL, Delft institute of Earth Observation and Space system （DEOS）, Tongji University （Tongji）, Institute of Theoretical Geodesy （ITG）, Astronomical Institute in University of Bern （AIUB） and Groupe de Recherche de Geodesie Spatiale （GRGS}, which indicates that the accuracy of WHU-Grace01s has a good consistency with the previously published GRACE solutions.展开更多
Gravity Recovery and Climate Experiment(GRACE)satellite data monitors changes in terrestrial water storage,including groundwater,at a regional scale.However,the coarse spatial resolution limits its applicability to sm...Gravity Recovery and Climate Experiment(GRACE)satellite data monitors changes in terrestrial water storage,including groundwater,at a regional scale.However,the coarse spatial resolution limits its applicability to small watershed areas.This study introduces a novel ensemble learning-based model using meteorological and topographical data to enhance spatial resolution.The effectiveness was evaluated using groundwater-level observation data from the Henan rainstorm-affected area in July 2021.The factors influencing Groundwater Storage Anomalies(GWSA)were explored using Permutation Importance(Pi)and other methods.The results demonstrate that feature engineering and Blender ensemble learning improve downscaling accuracy;the Root Mean Square Error(RMSE)can be reduced by up to 18.95%.Furthermore,Blender ensemble learning decreased the RMSE by 3.58%,achieving an R-Square(R3)value of 0.7924.Restricting the downscaling inversion to June-August data greatly enhanced the accuracy,as evidenced by a holdout dataset test with an R2 value of 0.8247.The overall GWSA variation from January to August exhibited'slow rise,slow fall,sharp fall,and sharp rise.Additionally,heavy rain exhibits a lag effect on the groundwater supply.Meteorological and topographical factors drive fluctuations in GwSA values and changes in spatial distribution.Human activities also have a significant impact.展开更多
The GRACE satellite mission provides a new approach for monitoring,tracking,and assessing drought conditions by detecting changes in Earth's gravitational fields and inversing signals of terrestrial water storage ...The GRACE satellite mission provides a new approach for monitoring,tracking,and assessing drought conditions by detecting changes in Earth's gravitational fields and inversing signals of terrestrial water storage anomalies.Existing studies of terrestrial water storage anomalies related droughts paid rare attention to the behind atmospheric physical mechanisms,nor quantified the risk propagation patterns between terrestrial water storage deficits and hydrological or agricultural droughts.In this study,we first extract terrestrial water storage(TWS) droughts,hydrological droughts,and agricultural droughts by using multiple variables including TWS from the GRACE/GRACE-FO satellites,runoff and soil moisture from the ERA5-Land reanalysis dataset.We then identify key atmospheric and oceanic oscillation indices affecting water deficits by employing machine learning technologies.We characterize the joint distributions between drought duration and severity by using the Copula function and quantify the risk propagation of hydrological and agricultural droughts to TWS droughts.The results show that:(1) From 2002 to 2021,there is a significant decrasing trend of TWS in China;the WPIO group atmospheric circulation indices(sea surface temperature index within the Western Pacific and Indian Ocean) contributes the most to TWS.Specifically,the sea surface temperature anomalies within the NINO 3.4 region as well as the Western Pacific Warm Pool area index show significantly positive correlation relationships with TWS in southern China;(2) The northwestern China,the Yangtze River basin,and the downstream of the Pearl River basin are the hotspots of TWS droughts.Besides,the hotspots of hydrological droughts locate in northwestern China and the hotspots of agricultural droughts locate in South China and eastern Tibetan Plateau;(3) The elastic coefficients of hydrological droughts propagating to TWS droughts are higher than those of agricultural droughts,indicating that the TWS droughts are more sensitive to hydrological droughts than to agricultural droughts.展开更多
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 the National Natural Science Foundation of China(NSFC)Projects(11173050 and 11373059)
文摘The Gravity Recovery and Climate Experiment（GRACE） satellite mission provides a unique opportunity to quantitatively study terrestrial water storage（TWS） variations. In this paper,the terrestrial water storage variations in the Poyang Lake Basin are recovered from the GRACE gravity data from January 2003 to March 2014 and compared with the Global Land Data Assimilation System（GLDAS） hydrological models and satellite altimetry. Furthermore, the impact of soil moisture content from GLDAS and rainfall from the Tropical Rainfall Measuring Mission（TRMM） on TWS variations are investigated. Our results indicate that the TWS variations from GRACE, GLDAS and satellite altimetry have a general consistency. The TWS trends in the Poyang Lake Basin determined from GRACE, GLDAS and satellite altimetry are increasing at 0.0141 km^3/a, 0.0328 km^3/a and 0.0238 km^3/a,respectively during the investigated time period. The TWS is governed mainly by the soil moisture content and dominated primarily by the precipitation but also modulated by the flood season of the Yangtze River as well as the lake and river exchange water.
基金supported by NSFC/China (No. 91125006)IAM grant (No. IAM201215)partially by State Key Laboratory funding (No. SKLFSE201009)
文摘There are only limited surface water resources available in the Heihe River Basin （HRB）, a typical inland river basin in the arid region of northwestern China, where groundwater overexploitation is a serious problem. Groundwater has become one of main resources of fresh water in the HRB. In this paper, temporal and spatial variations of groundwater in the HRB are estimated by the Gravity Recovery and Climate Experiment （GRACE） satellites. Our analysis shows that groundwater storage in the HRB reaches its highest in the summer of 2005, and then begins to decline in the following years and reaches steady status in 2008. Spatially, groundwater shows a decline in the upper HRB in the first two years and a slight increase in the following years, while this phenomenon is reversed in the middle HRB where groundwater slightly increases in 2005 and then declines in the following three years. In the lower HRB, GRACE detects a continual increase in the full six-year period. This approach is proven successful when employed in the HRB and thus offers a new insight into monitoring groundwater variations in a river basin with limited or even without any observed data.
基金supported by the National Natural Science Foundation of China(41304022)the National 973 Foundation(61322201,2013CB733303)the Youth Innovation Foundation of High Resolution Earth Observation(GFZX04060103-5-12)
文摘The basic principle of spectral combination method is discussed,and the general expressions of the spectral weight and spectral combination of the united-processing of various types of gravimetric data are shown.What＇s more,based on degree error RMS of potential coefficients,the detailed expressions of spectral combination formulae and the corresponding spectral weights in the Earth＇s gravitational field model（EGM） determination using GOCE ＋ GRACE and CHAMP ＋ GRACE ＋ GOCE are derived.The fundamental situation that ulux-champ2013 s,tongji-GRACE01,go-cons-gcf-2-tim-r5 constructed respectively by CHAMP,GRACE,GOCE data and go-cons-gcf-2-dir-r5 constructed by syncretic processing of GRACE,GOCE and LAGEOS data are explained briefly,the degree error RMS,cumulative geoid height error and cumulative gravity anomaly error of these models are calculated.A syncretic model constructed from CHAMP,GRACE and GOCE data,which is expressed by champ ＋ grace ＋ goce,is obtained based on spectral combination method.Experimentation results show that the precision of CHAMP data model is the lowest in satellite-only models,so it is not needed in the determination of syncretic models.The GRACE data model can improve the GOCE data model in medium-long wavelength,so the overall precision of syncretic model can be improved.Consequently,as many types of gravimetric data as possible should be combined together in the data processing in order to strengthen the quality and reliability with widening scope and improve the precision and spatial resolution of the computational results.
基金sponsored by National Natural Science Foundation of China(41474017)National Key Basic Research Program of China(973 Program+3 种基金2012CB957703)sponsored by National Natural Science Foundation of China(41274035)State Key Laboratory of Geodesy and Earth's Dynamics(SKLGED2013-3-2-Z,SKLGED2014-1-3-E)State Key Laboratory of Geo-Information Engineering(SKLGIE2014-M-1-2)
文摘In this paper we present a series of monthly gravity field solutions from Gravity Recovery and Climate Experiment（GRACE） range measurements using modified short arc approach,in which the ambiguity of range measurements is eliminated via differentiating two adjacent range measurements.The data used for developing our monthly gravity field model are same as Tongji-GRACEOl model except that the range measurements are used to replace the range rate measurements,and our model is truncated to degree and order 60,spanning Jan.2004 to Dec.2010 also same as Tongji-GRACE01 model.Based on the comparison results of the C_（2,0）,C_（2,1）,S_（2,1）,and C_（15,15）,S_（15,15）,time series and the global mass change signals as well as the mass change time series in Amazon area of our model with those of Tongji-GRACE01 model,we can conclude that our monthly gravity field model is comparable with Tongji-GRACE01 monthly model.
基金the project entitled"Advanced Gravity Measurement in Space"supported by the National Space Science Center,Chinese Academy of Sciences Profs.Wenrui Hu and Houze Xu's effort to promote satellite gravity research in China motivated the feasibility study in the first placeSupport from National Natural Science Foundation of China(11305255,11171329 and 41404019)funding from State Key Laboratory of Geodesy and Earth's Dynamics,Institute of Geodesy and Geophysics,Chinese Academy of Sciences(SKLGED2013-3-8-E)are acknowledged
文摘With the Gravity Recovery and Climate Experiment {GRACE） mission as the prime example, an overview is given on the management and processing of Level IA data of a low-low satellite to satellite tracking mission. To illustrate the underlying principle and algorithm, a detailed study is made on the K-band ranging （KBR） assembly, which includes the measurement principles, modeling of noises, the generation of Level 1A data from that of Level 0 as well as Level IA to Level IB data processing.
基金supported by the National 973Program of China(2013CB733302)the National Natural Science Foundation of China(41131067,41174020,41374023,41474019)+2 种基金the Open Research Fund Program of the State Key Laboratory of Geodesy and Earth's Dynamics(SKLGED2015-1-3-E)the open fund of State Key Laboratory of Geographic Information Engineering(SKLGIE2013-M-1-3)the open fund of Key Laboratory of Geospace Environment and Geodesy,Ministry of Education(13-02-05)
文摘A new temporal gravity field model called WHU-Grace01s solely recovered from Gravity Recovery and Climate Experiment （GRACE） K-Band Range Rate （KBRR） data based on dynamic integral approach is presented in this paper. After meticulously preprocessing of the GRACE KBRR data, the root mean square of its post residuals is about 0.2 micrometers per second, and seventy-two monthly temporal solutions truncated to degree and order 60 are computed for the period from January 2003 to December 2008. After applying the combi- nation filter in WHU-Grace01s, the global temporal signals show obvious periodical change rules in the large-scale fiver basins. In terms of the degree variance, our solution is smaller at high degrees, and shows a good consistency at the rest of degrees with the Release 05 models from Center for Space Research （CSR）, GeoForschungsZentrum Potsdam （GFZ） and Jet Pro- pulsion Laboratory 0PL）. Compared with other published models in terms of equivalent water height distribution, our solution is consistent with those published by CSR, GFZ, JPL, Delft institute of Earth Observation and Space system （DEOS）, Tongji University （Tongji）, Institute of Theoretical Geodesy （ITG）, Astronomical Institute in University of Bern （AIUB） and Groupe de Recherche de Geodesie Spatiale （GRGS}, which indicates that the accuracy of WHU-Grace01s has a good consistency with the previously published GRACE solutions.
基金supported by National Natural Science Foundation of China:[grant no U1304402,41977284]Natural science and technology project of Department of Natural Resources of Henan Province:[grant no 2019-378-16].
文摘Gravity Recovery and Climate Experiment(GRACE)satellite data monitors changes in terrestrial water storage,including groundwater,at a regional scale.However,the coarse spatial resolution limits its applicability to small watershed areas.This study introduces a novel ensemble learning-based model using meteorological and topographical data to enhance spatial resolution.The effectiveness was evaluated using groundwater-level observation data from the Henan rainstorm-affected area in July 2021.The factors influencing Groundwater Storage Anomalies(GWSA)were explored using Permutation Importance(Pi)and other methods.The results demonstrate that feature engineering and Blender ensemble learning improve downscaling accuracy;the Root Mean Square Error(RMSE)can be reduced by up to 18.95%.Furthermore,Blender ensemble learning decreased the RMSE by 3.58%,achieving an R-Square(R3)value of 0.7924.Restricting the downscaling inversion to June-August data greatly enhanced the accuracy,as evidenced by a holdout dataset test with an R2 value of 0.8247.The overall GWSA variation from January to August exhibited'slow rise,slow fall,sharp fall,and sharp rise.Additionally,heavy rain exhibits a lag effect on the groundwater supply.Meteorological and topographical factors drive fluctuations in GwSA values and changes in spatial distribution.Human activities also have a significant impact.
基金supported by the National Natural Science Foundation of China (Grant No.52209020)the Natural Science Foundation of Hubei Province (Grant No.2023AFB722)。
文摘The GRACE satellite mission provides a new approach for monitoring,tracking,and assessing drought conditions by detecting changes in Earth's gravitational fields and inversing signals of terrestrial water storage anomalies.Existing studies of terrestrial water storage anomalies related droughts paid rare attention to the behind atmospheric physical mechanisms,nor quantified the risk propagation patterns between terrestrial water storage deficits and hydrological or agricultural droughts.In this study,we first extract terrestrial water storage(TWS) droughts,hydrological droughts,and agricultural droughts by using multiple variables including TWS from the GRACE/GRACE-FO satellites,runoff and soil moisture from the ERA5-Land reanalysis dataset.We then identify key atmospheric and oceanic oscillation indices affecting water deficits by employing machine learning technologies.We characterize the joint distributions between drought duration and severity by using the Copula function and quantify the risk propagation of hydrological and agricultural droughts to TWS droughts.The results show that:(1) From 2002 to 2021,there is a significant decrasing trend of TWS in China;the WPIO group atmospheric circulation indices(sea surface temperature index within the Western Pacific and Indian Ocean) contributes the most to TWS.Specifically,the sea surface temperature anomalies within the NINO 3.4 region as well as the Western Pacific Warm Pool area index show significantly positive correlation relationships with TWS in southern China;(2) The northwestern China,the Yangtze River basin,and the downstream of the Pearl River basin are the hotspots of TWS droughts.Besides,the hotspots of hydrological droughts locate in northwestern China and the hotspots of agricultural droughts locate in South China and eastern Tibetan Plateau;(3) The elastic coefficients of hydrological droughts propagating to TWS droughts are higher than those of agricultural droughts,indicating that the TWS droughts are more sensitive to hydrological droughts than to agricultural droughts.
