GRACE估算陆地水储量季节和年际变化

利用最新公布的GRACE GFZ RL04数据,分析了2003年1月～2007年12月全球27条流域和陆地水储量的季节性和年际变化.结果表明,相近流域季节性变化相位接近.2003年1月～2007年12月陆地水储量季节性变化为1572.4 km3,其中变化最大流域为亚马逊河,其次分别为鄂毕河、尼罗河和尼日尔河等流域.5年来 GRACE陆地水储量的年际变化为-75.4±40.3 km3/a,其中亚马逊河、勒拿河和马更些河等流域的年际变化呈现正增长,而刚果河、密西西比河、恒河、育空河和雅鲁藏布江等流域则相反.GRACE与GLDAS数据均表明2006年后陆地水储量年际变化存在明显增加.     

利用GRACE卫星重力数据监测关中地区地下水储量变化

关中地区作为一带一路重要的工农业发达地区之一,开展针对该地区地下水储量变化的监测和分析工作对揭示地下水储量变化特征与经济社会发展具有重要现实意义.本文基于2003—2014年GRACE卫星重力场模型数据,采用组合滤波及单一尺度因子方法反演了关中地区陆地水储量变化,扣除GLDAS地表水平均结果,对关中地区地下水储量变化进行了监测分析.将陆地水储量变化与GLDAS进行相关性分析,将地下水储量变化与WGHM地下水模型及实测地下水位结果进行对比分析.研究结果表明：①关中地区陆地水变化与GLDAS模型结果具有较强的相关性,相关系数多数大于0.7,其中与模型平均结果的相关系数可达0.8.② 2003—2008年关中地区地下水呈正增长趋势,增加速率为0.25 cm·a^-1,与同期实测数据变化趋势一致;但2003—2013年地下水存在长期亏损,亏损速率为-0.37 cm·a^-1等效水高,这与同时期WGHM估算结果-0.35 cm·a^-1十分吻合.③关中地区地下水存在明显的年变化特征,在2003—2014年期间地下水减少速率为-0.44 cm·a^-1,与该地区降雨量有较好的一致性,在降雨偏少的2008、2012和2013年,地下水也显著减少.

     

全球水储量变化的GRACE卫星检测

利用GRACE月尺度变化的地球重力场反演了全球水储量变化,并与陆地水文资料、卫星测高资料及海洋模式得到的结果进行了比对.通过对SOURE台站重力变化的陆地水储量变化计算结果和GRACE重力场系数截断为15阶得到的结果比较,发现两者比较接近,且年周期变化特征明显.对于亚马逊流域,当重力场系数截断为15阶且平滑半径使用106 m时,GRACE反演的区域平均水储量厚度的周年变化振幅为15.6×10-2m,小于使用平滑半径为4×105m的23.7×10-2m.在研究长江流域时,本文对水文资料做球谐系数展开,并与GRACE数据做同样的截断和平滑处理,结果发现GRACE反演的水厚度变化与水文资料结果基本上符合.对于纬度±66°之间的海洋区域,GRACE反演的海水质量变化接近于结合卫星测高和海洋模式得到的结果,但对于2°×2°网格,则在一些区域差异明显,最大超过了0.2 m,中误差为3.8×10-2m.可见,当前GRACE卫星时变重力场只能确定出上千公里及以上尺度区域的水储量变化.     

基于GRACE的空间约束方法监测华北平原地下水储量变化

华北平原作为我国重要的工农业基地和政治经济中心,面临着严重的水资源危机.因此,开展对华北平原地下水储量变化的监测工作具有重要现实意义与科学价值.本文基于GRACE重力卫星的空间约束方法,研究了华北平原地下水储量变化的时空分布规律,并与地面水井实测与地下水模型结果进行了综合比较和分析.结果表明：2002—2014年,华北平原地下水存在明显的长期亏损,GRACE估计的亏损速率为-7.4±0.9 km³·a^-1,而地面水井资料估计的浅层地下水亏损速率为-1.2 km³·a^-1.对比两者之间的差异可以发现,华北平原的地下水亏损以深层地下水为主.2002—2008年,GRACE估计的华北平原地下水亏损速率为-5.3±2.2 km³·a^-1,这与华北平原两个地下水模型得到的平均亏损速率-5.4 km³·a^-1十分吻合.通过华北平原区域地下水模型的独立验证,说明GRACE可以有效评估华北平原的地下水储量变化趋势.除了长期亏损的趋势项之外,华北平原地下水还存在明显的年际变化特征,并与该地区年降雨量变化特征一致.在降雨偏少的2002年、2005—2009年和2014年,华北平原地下水储量显著减少.在空间分布上,GRACE结果表明,华北平原的地下水储量减少主要发生在山前平原和中部平原区,这也与水井实测资料和区域地下水模型结果较为吻合.与GRACE和区域地下水模型相比,目前的全球水文模型仍无法准确估计华北平原地下水变化的空间分布和亏损速率.上述研究表明,GRACE提供了评估华北平原地下水储量变化的重要监测手段.

     

利用广义三角帽方法评估GRACE反演中国大陆地区水储量变化的不确定性

在无真实观测值的情况下,本文利用广义三角帽方法评估了五种GRACE时变重力场模型（CSR、GFZ、GRGS、HUST发布的球谐系数解和JPL发布的Mascon解）反演中国大陆地区2003-2013年水储量变化的不确定性.研究结果表明,CSR、GFZ、JPL、HUST和GRGS反演月水储量变化不确定性的区域平均RMS分别为14.4 mm、26.3 mm、25.3 mm、26.6 mm和56.1 mm,其中GRGS的结果未恢复泄漏信号;在季和年尺度上,模型的不确定性均小于月尺度;扣除周期和趋势信号后,各模型反演结果更为一致.除长江流域外,CSR在13个流域的不确定性均小于其他模型,GRGS反演各流域水储量变化的不确定性通常较大,且可能高估了温带大陆性气候地区水储量的波动;CSR和JPL的不确定性受流域周边水文特征、气候类型、流域面积和形状的影响相对较小,不确定性变化范围分别为2.3~17.1 mm和5.6~22.5 mm,GFZ和HUST受影响较大,不确定性变化范围分别为5.5~35.1 mm和4.0~40.6 mm.本文的研究结果为GRACE产品不确定性评估提供了新的途径,为GRACE时变重力场模型的选取提供参考.

     

联合GRACE和GPS解译加州地下水储量变化

本文基于2002年04月—2016年08月共156月的GRACE时变重力场模型与地表水文模型,采用组合滤波与尺度因子法获取加州地下水储量变化,并联合EMD分解后的GPS测站垂向时间序列进行分析.结果显示:基于Swenson去相关与250 km高斯平滑半径组合滤波的GRACE地下水反演结果和GPS垂向时间序列季节性变化结果较好,与降水资料季节性变化特征明显,2002-2016年年均等效水高变化-9.4±2.1 mm/a.GPS测站垂向时间序列与附近水井相关性较好.通过深入分析发现地下水亏损是造成地表沉降的主要原因,且降水能够有效缓解以农业灌溉为主的地下水抽取.     

利用GRACE时变重力场探测2010年中国西南干旱陆地水储量变化

GRACE(Gravity Recovery And Climate Experiment)卫星计划为监测陆地水储量变化提供了有效技术手段.本文采用2003至2010年共计8年的GRACE月重力场模型反演中国西南区域陆地水储量变化,与GLDAS(Global Land Data Assimilation System)全球水文模型进行对比分析,其结果在时空分布上均符合较好,同时在2009年秋至2010年春该区域陆地水储量均呈现明显减少,与该时段云贵川三省的干旱事件相一致;比较分析了2009年秋至2010年春GRACE反演陆地水储量变化与TRMM(Tropical Rainfall Measuring Mission)合成数据计算的月降雨量的时空分布,两组结果均与西南干旱事件对应时段与区域十分吻合;对近8年的陆地水储量变化与月降雨量数据进行相关性分析,其结果表明陆地水储量变化与降雨量强相关,即降雨量是导致陆地水储量变化的主要因素;分析该区域地表温度变化,结果显示2009年9月至2010年3月地表温度均比历史同期高,地表温度的升高加剧了陆地水储量的减少.     

基于GRACE时变重力场的三峡水库补给水系水储量变化

利用22个月的GRACE时变重力场,反演了三峡水库补给水系的水储量变化,并按月给出了数值结果.与水文学同化模型（CPC）的两组比较说明基于GRACE重力的反演结果是合理的.当高斯平均半径为1000 km时,该区总水储量变化的峰谷差为14 cm,其年变化振幅为5.8 cm,相位为-40.8天,与CPC模型合成重力数据的反演结果进行比较,其总水储量变化均方差为1.3 cm,年变化振幅相差0.1 cm,相位相差1.0天.为进一步检验GRACE能否监测该区真实水储量变化,还将其反演结果与CPC模型的真实平均结果进行比较,结果发现总体均方差为2.1 cm,年变化振幅相差1.7 cm,相位相差9.3天.因此,第一种比较过高地估计了GRACE监测该区水储量变化的能力,第二种比较则较真实地反映了实际情况,尽管反演结果与水文学的结果差别较大,但仍然显示GRACE能监测该区每月的水储量变化.     

利用GRACE空间重力测量监测长江流域水储量的季节性变化

2002年3月成功发射的美德合作重力卫星计划GRACE(Gravity Recovery And Climate Experiment)已经开始提供阶次数达到120、时间分辨率为约1个月的地球重力场模型时变序列. GRACE的星座由两颗相距约220 km, 高度保持300~500 km, 而倾角保持约90°的近极轨卫星组成. 由于采用星载GPS和非保守力加速度计等高精度定轨技术以及高精度的星-星跟踪数据反演地球重力场, 在几百公里和更大空间尺度上, GRACE重力场的精度大大超过此前的卫星重力观测. 根据GRACE时变重力场反演的地球系统质量重新分布对固体地球物理、海洋物理、气候学以及大地测量等应用有重要的意义. 在长期时间尺度上, GRACE的结果可用于研究北极冰的变化, 并进而研究极冰融化对全球气候变化, 特别是对海平面长期变化的影响. 在季节性时间尺度上, 利用GRACE重力场的精度足以揭示平均小于1 cm的地表水变化或小于1 mbar的海底压强变化. 除了巨大的社会和经济效益外, 这些变化对了解地球系统的物质循环(主要是水循环)和能量循环有非常重要的意义. 利用2002年4月至2003年12月之间共15个月的GRACE时变重力场揭示了全球水储量的明显季节性变化, 并重点分析了中国长江流域水储量的变化. 结果表明长江流域水储量周年变化幅度可达到3.4 cm等效水高, 其最大值出现在春季和初秋. 根据GRACE时变重力场反演的水储量变化与两个目前最好的全球水文模型的符合相当好, 其差别小于1 cm等效水高. 研究表明现代空间重力测量技术在监测一些大流域的水储量变化(如长江流域)、全球水循环和气候变化上有巨大的应用潜力.     

GRACE/GRACE-FO重力卫星揭示近20年河西走廊陆地水储量时空变化

河西走廊由疏勒河流域、黑河流域和石羊河流域组成,水资源保护对河西走廊生态平衡和经济发展有着重要意义.本文利用JPL GRACE/GRACE-FO Mascon模型反演该区域陆地水储量的时空变化,结合GLDAS模型、实测地下水位和冰川水模型等数据对陆地水储量进行水平衡分析及时空特征变化分析,结果表明：(1)2002-04—2020-01间由于降水和冰川融水的补充,疏勒河流域南部和黑河大部分区域陆地水储量空间变化呈上升趋势,而蒸散消耗与农业扩张则导致疏勒河流域北部和石羊河流域陆地水储量下降;(2)通过水平衡研究发现人类耗水是疏勒河流域、黑河流域和石羊河流域陆地水储量变化的重要因素,平均贡献率分别为-24.49%、-47.20%和-43.29%;(3)河西走廊水资源治理政策的实施减少了农业灌溉耗水量、控制了耕地面积的扩张、抑制了地下水储量的消耗.     

Groundwater Monitoring Using GRACE and GLDAS Data after Downscaling Within Basaltic Aquifer System

Gravity Recovery and Climate Experiment (GRACE) satellite mission is ground-breaking information hotspot for the evaluation of groundwater storage. The present study aims at validating the sensitivity of GRACE data to groundwater storage variation within a basaltic aquifer system after its statistical downscaling on a regional scale. The basaltic aquifer system which covers 82.06% area of Maharashtra state in India, is selected as the study area. Five types of basaltic aquifer systems with varying groundwater storage capacities, based on hydrologic characteristics, have been identified within the study area. The spatial and seasonal trend analysis of observed in situ groundwater storage anomalies (ΔGWSano) computed from groundwater level data of 983 wells from the year 2002 to 2016, has been performed to analyze the variation in groundwater storages in the different basaltic aquifer system. The groundwater storage anomalies (ΔGWSDano) have been derived from GRACE Release 05 (RL05) after removing the soil moisture anomaly (ΔSMano) and canopy water storage anomaly (ΔCNOano) obtained from Global Land Data Assimilation System (GLDAS) land surface models (NOAH, MOSAIC, CLM and VIC). The artificial neural network technique has been used to downscale the GRACE and GLDAS data at a finer spatial resolution of 0.125°. The study shows that downscaled GRACE and GLDAS data at a finer spatial resolution is sensitive to seasonal groundwater storage variability in different basaltic aquifer systems and the regression coefficient R has been found satisfactory in the range of 0.696 to 0.818.     

Integration of GRACE mass variations into a global hydrological model

Time-variable gravity data of the GRACE (Gravity Recovery And Climate Experiment) satellite mission provide global information on temporal variations of continental water storage. In this study, we incorporate GRACE data for the first time directly into the tuning process of a global hydrological model to improve simulations of the continental water cycle. For the WaterGAP Global Hydrology Model (WGHM), we adopt a multi-objective calibration framework to constrain model predictions by both measured river discharge and water storage variations from GRACE and illustrate it on the example of three large river basins: Amazon, Mississippi and Congo. The approach leads to improved simulation results with regard to both objectives. In case of monthly total water storage variations we obtained a RMSE reduction of about 25 mm for the Amazon, 6 mm for the Mississippi and 1 mm for the Congo river basin. The results highlight the valuable nature of GRACE data when merged into large-scale hydrological modeling. Furthermore, they reveal the utility of the multi-objective calibration framework for the integration of remote sensing data into hydrological models.     

融合GOCE和GRACE卫星数据的无约束重力场模型Tongji-GOGR2019S

本文在法方程层面融合GOCE卫星的V_xx、V_yy、V_zz和V_xz重力梯度分量观测数据和GRACE卫星观测数据,采用直接法解算了220阶次的重力场模型Tongji-GOGR2019S.首先利用ⅡR带通滤波器在5~41 mHz的重力梯度带宽范围内对约24个月的GOCE重力梯度观测方程进行无相移滤波处理,并组成解算220阶次重力场模型的法方程,各梯度分量根据相对于参考模型统计精度进行定权;然后与13.5 a GRACE数据建立的180阶次Tongji-Grace02s重力场模型的法方程进行叠加,解算了220阶次的无约束纯卫星重力场模型Tongji-GOGR2019S.利用EIGEN-6C4重力场模型、GNSS/水准数据、DTU15重力异常数据以及欧洲区域似大地水准面模型EGG2015等数据对Tongji-GOGR2019S模型精度进行全面的检核评定,结果表明：引入GOCE卫星梯度数据后,高于72阶的位系数精度优于Tongji-Grace02s模型,Tongji-GOGR2019S模型的整体精度接近同阶次的DIR-R6等GOCE卫星第6代模型.

     

融合GOCE和GRACE卫星数据的无约束重力场模型Tongji-GOGR2019S

本文在法方程层面融合GOCE卫星的V_xx、V_yy、V_zz和V_xz重力梯度分量观测数据和GRACE卫星观测数据,采用直接法解算了220阶次的重力场模型Tongji-GOGR2019S.首先利用ⅡR带通滤波器在5~41 mHz的重力梯度带宽范围内对约24个月的GOCE重力梯度观测方程进行无相移滤波处理,并组成解算220阶次重力场模型的法方程,各梯度分量根据相对于参考模型统计精度进行定权;然后与13.5 a GRACE数据建立的180阶次Tongji-Grace02s重力场模型的法方程进行叠加,解算了220阶次的无约束纯卫星重力场模型Tongji-GOGR2019S.利用EIGEN-6C4重力场模型、GNSS/水准数据、DTU15重力异常数据以及欧洲区域似大地水准面模型EGG2015等数据对Tongji-GOGR2019S模型精度进行全面的检核评定,结果表明：引入GOCE卫星梯度数据后,高于72阶的位系数精度优于Tongji-Grace02s模型,Tongji-GOGR2019S模型的整体精度接近同阶次的DIR-R6等GOCE卫星第6代模型.     

Characterization of Ethiopian mega hydrogeological regimes using GRACE,TRMM and GLDAS datasets

Understanding the spatio-temporal characteristics of water storage changes is crucial for Ethiopia, a country that is facing a range of challenges in water management caused by anthropogenic impacts as well as climate variability. In addition to this, the scarcity of in situ measurements of soil moisture and groundwater, combined with intrinsic “scale limitations” of traditional methods used in hydrological characterization are further limiting the ability to assess water resource distribution in the region. The primary objective of this study is therefore to apply remotely sensed and model data over Ethiopia in order to (i) test the performance of models and remotely sensed data in modeling water resources distribution in un-gauged arid regions of Ethiopia, (ii) analyze the inter-annual and seasonal variability as well as changes in total water storage (TWS) over Ethiopia, (iii) understand the relationship between TWS changes, rainfall, and soil moisture anomalies over the study region, and (iv) identify the relationship between the characteristics of aquifers and TWS changes. The data used in this study includes; monthly gravity field data from the Gravity Recovery And Climate Experiment (GRACE) mission, rainfall data from the Tropical Rainfall Measuring Mission (TRMM), and soil moisture from the Global Land Data Assimilation System (GLDAS) model. Our investigation covers a period of 8 years from 2003 to 2011. The results of the study show that the western part and the north-eastern lowlands of Ethiopia experienced decrease in TWS water between 2003–2011, whereas all the other regions gained water during the study period. The impact of rainfall seasonality was also seen in the TWS changes. Applying the statistical method of Principal Component Analysis (PCA) to TWS, soil moisture and rainfall variations indentified the dominant annual water variability in the western, north-western, northern, and central regions, and the dominant seasonal variability in the western, north-western, and the eastern regions. A correlation analysis between TWS and rainfall indicated a minimum time lag of zero to a maximum of six months, whereas no lag is noticeable between soil moisture anomalies and TWS changes. The delay response and correlation coefficient between rainfall and TWS appears to be related to recharge mechanisms, revealing that most regions of Ethiopia receive indirect recharge. Our results also show that the magnitude of TWS changes is higher in the western region and lower in the north-eastern region, and that the elevation influences soil moisture as well as TWS.     

Assessment of the WATCLASS hydrological model result of the Mackenzie River basin using the GRACE satellite total water storage measurement

Earlier efforts have been geared towards modelling the hydrological water balance of the Mackenzie River basin and its sub‐basins using a coupled land surface–hydrological model for the Canadian cold region known as WATCLASS. The goal of this current study is to effectively inter‐compare the resulting total water storage anomalies estimated from the gravity recovery and climate experiment (GRACE) satellite analysis with those estimated from the atmospheric‐based water balance approach as well as the model output from WATCLASS over the 1 · 8 × 10⁶ km² Mackenzie River basin in Canada. Since the success of the parameter estimation stage of the coupled land surface–hydrological model, WATCLASS over this large catchment, was entirely based on a goodness of fit between the simulated and observed flows, it is often desirable to assess the reliability of the generated state variables prior to concluding on the overall efficiency of this model in reproducing the relevant hydrological processes over this region. A major challenge here lies in finding suitable dataset with which this comparison can be made to further assess the ability of the model in accurately reproducing other mass fluxes. The outcome of this inter‐comparison reveals the potential application of the GRACE‐based approach as a veritable tool required for the closure of the hydrological water balance of the Mackenzie River basin as well as serving as a dependable source of data for the calibration of traditional hydrological models. Copyright © 2009 John Wiley & Sons, Ltd.     

Groundwater Storage Changes: Present Status from GRACE Observations

Satellite gravity measurements from the Gravity Recovery and Climate Experiment (GRACE) provide quantitative measurement of terrestrial water storage (TWS) changes with unprecedented accuracy. Combining GRACE-observed TWS changes and independent estimates of water change in soil and snow and surface reservoirs offers a means for estimating groundwater storage change. Since its launch in March 2002, GRACE time-variable gravity data have been successfully used to quantify long-term groundwater storage changes in different regions over the world, including northwest India, the High Plains Aquifer and the Central Valley in the USA, the North China Plain, Middle East, and southern Murray–Darling Basin in Australia, where groundwater storage has been significantly depleted in recent years (or decades). It is difficult to rely on in situ groundwater measurements for accurate quantification of large, regional-scale groundwater storage changes, especially at long timescales due to inadequate spatial and temporal coverage of in situ data and uncertainties in storage coefficients. The now nearly 13 years of GRACE gravity data provide a successful and unique complementary tool for monitoring and measuring groundwater changes on a global and regional basis. Despite the successful applications of GRACE in studying global groundwater storage change, there are still some major challenges limiting the application and interpretation of GRACE data. In this paper, we present an overview of GRACE applications in groundwater studies and discuss if and how the main challenges to using GRACE data can be addressed.