2005—2017年两次强ENSO事件对中国区域陆地水储量变化影响的卫星重力观测

近年来极端气候事件的频发对全球和区域性水循环产生了重大影响,特别是2005—2017年间两次强ENSO(El Nino-Southern Oscillation)事件使得全球陆地水储量出现了较大的年际波动.GRACE(Gravity Recovery and Climate Experiment)重力卫星随着数据质量的提高、后处理方法的完善和超过十年的连续观测,捕捉陆地水储量异常的能力明显提高,这为研究2005—2017年间两次强ENSO事件对中国区域陆地水储量变化的影响提供了观测基础.本文综合利用GRACE卫星重力数据、GLDAS水文模型和实测降水资料分析了中国区域陆地水储量年际变化和与ENSO的关系.研究发现:长江流域中、下游地区和东南诸河流域与ENSO存在较高的相关性,与ENSO的相关系数最大值分别为0.55、0.78、0.70,较ENSO分别滞后约7个月、5个月和5个月.其中长江流域下游地区与ENSO的相关性最强,2010/11 La Nina和2015/16 El Nino两次强ENSO事件使得陆地水储量分别发生了约-24.1亿吨和27.9亿吨的波动.在2010/11 La Nina期间,长江流域下游地区和东南诸河流域陆地水储量异常约在2011年4—5月达到谷值,而长江流域中游地区晚1~2月达到谷值.在2015/16 El Nino期间,长江流域中、下游地区和东南诸河流域陆地水储量从2015年9月到2016年7月持续出现正异常信号.其中,2015年秋冬季(2015年9月至2016年1月)陆地水储量异常明显是受此次El Nino同期影响的结果;2016年春季(4—5月)陆地水异常是受到此次厄尔尼诺峰值的滞后影响所致;2016年7月的陆地水储量异常则与西北太平洋存在的异常反气旋环流有关.     

应用GPS数据和Slepian基函数反演川云渝地区陆地水储量变化

局部Slepian函数是将局部区域内的地球物理信号转化为空间谱的一种方法,其可以保证在球面上局部范围内获得最优谱平滑解,非常适用于局部范围地球物理信号的研究.本文利用中国陆态网西南地区72个测站的连续GPS观测资料分析川云渝地区陆地水负荷形变特征,并基于Slepian函数方法解算60阶的空间谱基函数,结合弹性质量负荷理论研究了川云渝地区2011年至2015年陆地水储量变化的时空分布模式.针对Slepian函数的边界效应问题,本文使用GLDAS格网数据计算得到站点处垂直负荷位移时间序列,然后利用该位移数据来进行水储量变化恢复实验,结果表明当边界扩充为3°时能较好地恢复GLDAS模型输出的陆地水储量变化.通过对比区域内GPS、GRACE、GLDAS得到的等效水高以及降雨数据,发现季节性降水是陆地水变化的一个重要驱动因子,GPS反演结果与GRACE和GLDAS数据具有较强的空间一致性.云南地区周年变化要强于川渝地区,其中云南西部的山区陆地水变化最大,约为30 cm,最小为川北以及重庆地区仅为7 cm.相较于GPS反演结果,GRACE与GLDAS明显低估了陆地水储量的季节性变化,分别达到24%和47%.比较分析地区内平均等效水高时间序列的相位发现,GPS得到的陆地水变化与降雨数据一致性较好,而GRACE与GLDAS存在一到两个月左右的时延.同时GPS能较好的探测出2015年1月左右南方地区大范围的强降水,而GRACE与GLDAS并没有体现出该现象,说明GPS能更为灵敏地探测到局部地区陆地水的变化.在站点等效水高时间序列上,GPS与GRACE的相关性总体上要优于GPS与GLDAS,陆地水周年变化较大的云南和四川西部地区站点三种数据间相关性较好,而其他季节性信号不明显的地区则相关性较差.本文的研究表明运用GPS-Slepian方法能够独立地监测高时空分辨率的陆地水储量变化,是作为当前补充GRACE观测资料空缺期的有益尝试.     

基于Forward-Modeling方法的黑河流域水储量变化特征研究

黑河流域陆地水储量变化对流域下游等周边区域水资源的合理利用以及经济和社会发展等有着重要的意义.本文利用2003年1月至2013年12月的GRACE RL05数据反演了黑河流域陆地水储量长时间序列的变化,并针对重力场模型和数据处理中产生的信号泄漏问题,采用Forward-Modeling方法进行了改正并恢复泄漏信号;将GRACE获得的泄漏信号恢复前后的黑河流域水储量变化结果与全球水文模型GLDAS和CPC进行比较分析,结果表明泄漏信号改正后的结果与水文模型结果的时间序列相关性均有明显提高,从其空间分布结果可以看出Forward-Modeling方法有效地恢复初始信号、增强被湮没的信号,泄漏信号误差减小;通过分析黑河流域水储量变化的长时间序列结果,发现其具有明显的阶段性变化特征,即2003—2006年呈明显下降趋势,约为-0.86cm·a-1,在2007—2010年趋于平衡状态,而2011—2013年则呈现缓慢上升趋势约为0.14cm·a-1;联合GRACE数据和GLDAS数据反演了黑河流域地下水储量变化,并与全球降雨数据GPCC进行了比较分析,两者相关性可达到0.88以上.     

应用GRACE卫星重力数据计算陆地水变化的相关进展评述

GRACE重力卫星自2002年3月发射至今,已进行了十多年的连续观测,由此获得的重力场变化数据被广泛地应用于研究地表河流及地下水储量变化、南极和格林兰岛冰盖厚度以及全球海平面变化等.本文从GRACE重力卫星数据的处理方法入手,对其数据特点、限制条件和水文模型计算方法等问题进行了系统总结,并针对近年来利用GRACE卫星数据开展的相关研究,从估算全球水储量的变化、区域水储量变化、地下水变化以及陆地河流流域的水储量变化等方面对相关研究和应用进行了简要评述.最后,对使用GRACE卫星数据反演陆地水储量的验证方法和存在的问题进行讨论.本文对于全面了解近年来应用GRACE卫星数据研究陆地水储量变化方面的相关进展具有参考意义.     

利用重力卫星GRACE监测亚马逊流域2002-2010年的陆地水变化

本文利用GRACE (Gravity Recovery and Climate Experiment) 卫星重力资料研究了亚马逊流域2002-2010年的陆地水变化,并与水文模式和降雨资料进行了比较分析.在年际尺度上,GRACE结果表明:2002-2003年和2005年,亚马逊流域发生明显的干旱现象;2007年至2009年,陆地水呈逐年增加的趋势,并在2009年6月变化值达到最大,为772±181 km³;自2009年6月至2010年12月,陆地水总量又急剧减少了1139±262 km³,这相当于全球海平面上升3.2±0.7 mm所需的水量.水文模式得到的亚马逊流域陆地水在2010年也表现出明显的减少.降雨资料与GRACE观测资料有很好的一致性.在2005年和2010年的干旱期,亚马逊流域的降雨显著减少,说明降雨是亚马逊流域陆地水变化的重要因素.此外,本文采用的尺度因子的方法有效地降低了GRACE后处理误差的影响.     

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.     

附加GPS时序约束的GRACE陆地水储量反演

利用GRACE重力卫星反演陆地地球物理变化信息时,通常需要对位系数进行截断和空间平均滤波等处理,这将导致监测信息较实际值"缩减"一定的比例,从而造成反演结果可信度降低.针对此,本文提出了一种附加GPS时序约束的GRACE反演陆地水文信息修正法.利用2003-2015年RL05_GRACE月重力场数据,选取前60阶采用扇形滤波与去相关滤波组合法,获得了加州区域由于陆地水储量及地表荷载变化引起的垂向形变时间序列,并利用同时间段多个GPS测站资料获得了同尺度U方向形变时间序列,采用时频分析技术对比分析了两类垂向形变时间序列的振幅与季节性特征,获取了GRACE位系数处理中存在的"缩减系数",基于此修正并精化了GRACE反演水文变化信息,该信息能有效反映出研究区域较真实的陆地水文变化信息.     

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和GLDAS水文模型反演安徽省地下水储量变化

地下水储量的有效监测是实现区域水资源管理的重要依据,传统监测方法存在各自的局限性导致其实现较为困难.本文提供一种使用GRACE卫星重力数据与GLDAS水文模型数据反演得到安徽省区域地下水储量变化的方法.利用2002年4月-2017年6月不同机构GRACE卫星重力数据的综合解,经过DDK去相关光滑滤波与退卷积法分别消除或削弱南北条带误差、改正信号泄露反演得到安徽省陆地水储量变化,扣除由GLDAS水文模型数据获取的地表水储量变化,得到安徽省地下水储量变化时间序列,并结合国家统计局官方发布的安徽省地下水资源量进行初步验证分析.研究结果表明:安徽省地下水储量变化长期表现为波动下降趋势,其年变化率约为-5.35 mm·a-1,且呈现出自东南方向至西北方向逐次递减的显著空间差异;地下水储量表现出明显的季节性变化,夏季和冬季地下水储量呈现回升趋势,春季和秋季呈现出下降趋势.除去反演过程存在较大干扰因素的情况,反演结果与国家统计局官方数据的相关系数达到89.62％,因此本文反演得到的地下水储量变化的结果是相对可靠的.     

利用GPS和GRACE分析四川地表垂向位移变化

陆地水储量的季节性变化是导致地表周期性负荷形变位移的主要因素,有效地剔除地表位移中的陆地水储量影响,是获取地壳构造垂向运动的必要过程.四川地处青藏高原东边缘,地形分区明显,境内以长江水系为主,水资源丰富,研究四川地区地表负荷形变位移,有助于分析陆地水储量的时空分布特性及地壳构造形变信息.本文利用研究区域内59个CORS站的GPS观测数据,计算了CORS站点的垂向位移,并将其与GRACE所得相应结果进行对比分析.结果显示,GPS和GRACE所得垂向位移时间序列的振幅大小整体相符,但存在明显的相位差.GPS站点振幅最大值为12.7 mm,对应HANY站,最小值为1.5 mm,对应SCMX站.GRACE所得的地表垂向位移振幅大小均为3~4 mm,且最大位移集中出现在7-9月份;而GPS站点出现最大位移的月份和地形相关,东部盆地、西北部高原和南部山地分别出现在7-8月份、10-11月份和10月份.GPS站点时间序列中的周年项与陆地水的季节性变化强相关,为了讨论陆地水储量对GPS站点位移的影响,本文利用改进的总体经验模态分解方法（MEEMD：Modified Ensemble Empirical Mode Decomposition）,从GPS垂向位移时间序列中提取出周年项及约2年的年际变化项.发现利用MEEMD获取的周年项改正原始GPS时间序列时可使其WRMS（Weight Root Mean Square）减少量减小约26%,结果优于最小二乘拟合方法提取的GPS周年项改正效果,验证了MEEMD方法在GPS坐标时间序列处理中的可行性及有效性.     

Terrestrial Water Storage Anomalies Associated with Drought in Southwestern USA from GPS Observations

The Earth’s surface fluid mass redistribution, e.g., groundwater depletion and severe drought, causes the elastic surface deformation, which can be measured by global positioning system (GPS). In this paper, the continuous GPS observations are used to estimate the terrestrial water storage (TWS) changes in southwestern USA, which have a good agreement with TWS changes derived from Gravity Recovery And Climate Experiment (GRACE) and hydrological models. The seasonal variation is mostly located in the Rocky mountain range and Mississippi river watershed. The largest amplitude of the seasonal variation is between 12 and 15 cm in equivalent water thickness. The timing and duration of TWS anomalies caused by the severe drought in 2012 are observed by the GPS-derived TWS, which are confirmed by the GRACE results. Different hydrological models are further used for comparison with GPS and GRACE results. The magnitude of TWS depletion from GRACE and GPS observations during the drought is larger than that from hydrological models, which indicates that the drought was caused by comparable groundwater and surface water depletion. The interannual TWS changes from GPS are also consistent with the precipitation pattern over the past 6 years, which further confirms the severe drought in 2012. This study demonstrates that continuous GPS observations have the potential as real-time drought indicator.     

Consistency of precipitation products over the Arabian Peninsula and interactions with soil moisture and water storage

The regional-scale consistency between four precipitation products from the GPCC, TRMM, WM, and CMORPH datasets over the Arabian Peninsula was assessed. Their macroscale relationships were inter-compared with soil moisture and total water storage (TWS) estimates from AMSR-E and GRACE. The consistency analysis was studied with multivariate statistical hypothesis testing and Pearson correlation metrics for the period from January 2000 to December 2010. The products and GRACE estimates were assessed over a representative sub-domain (United Arab Emirates) with available in situ well observations. Next, geographically temporally weighted regression (GTWR) was employed to examine the interdependencies among the peninsula’s hydrological components. The results showed GPCC-TRMM recording the highest correlation (0.85) with insignificant mean differences over more than 90% of the peninsula. The highest GTWR predictive performance of TWS (R² = 0.84) was achieved with TRMM forcing, which indicates its potential to monitor changes in TWS over the arid peninsular region.     

Global Terrestrial Water Storage Changes and Connections to ENSO Events

Improved data quality of extended record of the Gravity Recovery and Climate Experiment (GRACE) satellite gravity solutions enables better understanding of terrestrial water storage (TWS) variations. Connections of TWS and climate change are critical to investigate regional and global water cycles. In this study, we provide a comprehensive analysis of global connections between interannual TWS changes and El Niño Southern Oscillation (ENSO) events, using multiple sources of data, including GRACE measurements, land surface model (LSM) predictions and precipitation observations. We use cross-correlation and coherence spectrum analysis to examine global connections between interannual TWS changes and the Niño 3.4 index, and select four river basins (Amazon, Orinoco, Colorado, and Lena) for more detailed analysis. The results indicate that interannual TWS changes are strongly correlated with ENSO over much of the globe, with maximum cross-correlation coefficients up to ~0.70, well above the 95% significance level (~0.29) derived by the Monte Carlo experiments. The strongest correlations are found in tropical and subtropical regions, especially in the Amazon, Orinoco, and La Plata basins. While both GRACE and LSM TWS estimates show reasonably good correlations with ENSO and generally consistent spatial correlation patterns, notably higher correlations are found between GRACE TWS and ENSO. The existence of significant correlations in middle–high latitudes shows the large-scale impact of ENSO on the global water cycle.     

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.     

基于多源数据分析维多利亚湖流域水储量变化

本文利用CSR发布的GRACE RL06时变重力场模型,结合两种水文模式、卫星测高、降雨和蒸散等多源数据,从多个角度综合系统地分析维多利亚湖流域2003-01—2017-06的陆地水储量变化.比较了正向建模方法和单一尺度因子对泄漏误差的改正效果,经对比采用正向建模方法在此流域效果更好.基于多源数据得出以下三点与此前研究不同的结论:(1)GRACE RL06版本数据探测到流域内的水储量在2003-01—2017-06呈增加趋势,球谐位系数和Mascon产品得到的变化速率分别为14.9 mm·a^-1和16.7 mm·a^-1,观测误差小于RL05版本的结果,RL05版本低估了流域水储量的变化速率;(2)2013-01—2016-02期间GRACE和测高探测到湖泊水量增长,而水文模式探测到流域内水储量减少,推测这一现象由大坝蓄水造成;(3)受El Nino事件影响,2016-03—2017-06流域降雨减少,流域水储量减少,GRACE球谐位系数和Mascon探测到的变化速率分别为-100.3 mm·a^-1和-129.7 mm·a^-1.本文结果表明卫星观测数据可为在缺乏直接观测数据的情况下分析人类活动和自然变化对区域水储量的影响提供一种可行的途径,这也为研究我国湖泊流域水储量变化提供参考.     

The influence of groundwater representation on hydrological simulation and its assessment using satellite‐based water storage variation

The interaction between surface water and groundwater is an important aspect of hydrological processes. Despite its importance, groundwater is not well represented in many land surface models. In this study, a groundwater module with consideration of surface water and groundwater dynamic interactions is incorporated into the distributed biosphere hydrological (DBH) model in the upstream of the Yellow River basin, China. Two numerical experiments are conducted using the DBH model: one with groundwater module active, namely, DBH_GW and the other without, namely, DBH_NGW. Simulations by two experiments are compared with observed river discharge and terrestrial water storage (TWS) variation from the Gravity Recovery and Climate Experiment (GRACE). The results show that river discharge during the low flow season that is underestimated in the DBH_NGW has been improved by incorporating the groundwater scheme. As for the TWS, simulation in DBH_GW shows better agreement with GRACE data in terms of interannual and intraseasonal variations and annual changing trend. Furthermore, compared with DBH_GW, TWS simulated in DBH_NGW shows smaller decreases during autumn and smaller increases in spring. These results suggest that consideration of groundwater dynamics enables a more reasonable representation of TWS change by increasing TWS amplitudes and signals and as a consequence, improves river discharge simulation in the low flow seasons when groundwater is a major component in runoff. Additionally, incorporation of groundwater module also leads to wetter soil moisture and higher evapotranspiration, especially in the wet seasons.     

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.     

Seasonal Water Storage Variations as Impacted by Water Abstractions: Comparing the Output of a Global Hydrological Model with GRACE and GPS Observations

Better quantification of continental water storage variations is expected to improve our understanding of water flows, including evapotranspiration, runoff and river discharge as well as human water abstractions. For the first time, total water storage (TWS) on the land area of the globe as computed by the global water model WaterGAP (Water Global Assessment and Prognosis) was compared to both gravity recovery and climate experiment (GRACE) and global positioning system (GPS) observations. The GRACE satellites sense the effect of TWS on the dynamic gravity field of the Earth. GPS reference points are displaced due to crustal deformation caused by time-varying TWS. Unfortunately, the worldwide coverage of the GPS tracking network is irregular, while GRACE provides global coverage albeit with low spatial resolution. Detrended TWS time series were analyzed by determining scaling factors for mean annual amplitude (f _GRACE) and time series of monthly TWS (f _GPS). Both GRACE and GPS indicate that WaterGAP underestimates seasonal variations of TWS on most of the land area of the globe. In addition, seasonal maximum TWS occurs 1 month earlier according to WaterGAP than according to GRACE on most land areas. While WaterGAP TWS is sensitive to the applied climate input data, none of the two data sets result in a clearly better fit to the observations. Due to the low number of GPS sites, GPS observations are less useful for validating global hydrological models than GRACE observations, but they serve to support the validity of GRACE TWS as observational target for hydrological modeling. For unknown reasons, WaterGAP appears to fit better to GPS than to GRACE. Both GPS and GRACE data, however, are rather uncertain due to a number of reasons, in particular in dry regions. It is not possible to benefit from either GPS or GRACE observations to monitor and quantify human water abstractions if only detrended (seasonal) TWS variations are considered. Regarding GRACE, this is mainly caused by the attenuation of the TWS differences between water abstraction variants due to the filtering required for GRACE TWS. Regarding GPS, station density is too low. Only if water abstractions lead to long-term changes in TWS by depletion or restoration of water storage in groundwater or large surface water bodies, GRACE may be used to support the quantification of human water abstractions.