利用GRACE反演陕甘晋高原地下水储量变化

采用GRACE时变重力场模型和GLDAS水文模型反演了陕甘晋高原地下水储量的时空变化,并与TRMM降雨资料及实测水井数据进行了对比分析。研究结果表明：在时间域上,整个区域的地下水在2005-2014年大约以3.6±0.7 mm/a的速率递减;在空间域上,整个区域自西向东10年内的递减速率依次增大,其中山西中部地区最大。与TRMM降雨资料的对比发现,降雨与地下水储量变化强相关,但不是引起地下水储量减少的原因。与水井实测数据对比发现,除特殊情况外,本文反演得到的结果与水井水位变化趋势基本一致。     

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Regional differences in the effects of El Niño and La Niña on low flows and floods

Abstract

The response of monthly 7-day low flow, monthly instantaneous peak flow, and monthly frequency of flood events to El Niño and La Niña episodes is investigated for 18 rivers that represent a diverse range of climatic types throughout New Zealand. A significant positive or negative deviation from the long-term average was observed in over half the possible combinations of river, streamflow index, and type of ENSO episode; significant deviations were most frequent in the case of low flow, especially during La Niña episodes. Patterns of streamflow response differ widely between rivers, and the response of a given river to individual ENSO episodes is very variable. The patterns of streamflow response to ENSO are consistent to some extent with the climatic effects of ENSO already identified by meteorologists. Two core regions can be defined in which streamflow tends to respond in the same way. These are in the northeast of the North Island, and in the axial ranges of the South Island, where there are significant effects of ENSO on the frequency and duration of rain-bearing northeasterly and westerly winds respectively. The patterns of response strongly reflect topography, and the exposure of catchments to predominant air masses.     

联合GRACE和GLDAS数据的河南省地下水储量反演与时空变化分析

针对利用传统监测手段难以高效获取地下水储量观测数据的问题,基于GRACE重力卫星的大尺度水资源储量反演已成为当前水资源调查的研究热点。本文利用2012-2016年CSR机构发布的GRACE RL06月解数据,通过等效水高反演得到河南省陆地水储量时序结果,扣除由同期GLDAS水文模型计算得到的地表水储量时序数据,从而得到河南省地下水储量时序变化数据结果。经与地下水位监测井实测数据进行对比验证,相关系数显著性水平达0.01,表明本文算法流程具有较高的可靠性。进一步的统计分析结果表明,河南省北部地区的地下水储量呈亏损态势,最大变化率超过26 mm/a;河南省中部和东部地区地下水储量有一定盈余,最大变化率超过16 mm/a,相关结果数据与河南省水利局公布的全省主要地下水超采区范围吻合。本文旨在利用GRACE重力卫星数据与GLDAS水文模型反演获取河南省地下水储量空间分布差异及演变趋势,相关算法流程可为广域地下水储量调查监测提供技术支撑;研究数据可为该区域地下水资源的合理利用与保护提供参考。     

基于GRACE数据的黄河流域地下水储量变化与人口暴露研究

近年来黄河流域人与水资源矛盾愈发突出,尤其是地下水储量的过度消耗已成为限制该区域人与自然和谐发展的主要矛盾之一。基于重力反演与气候实验卫星数据和全球陆面数据同化系数数据,根据流域水循环与水量平衡原理,测算2003—2016年黄河流域地下水储量的变化情况,在探究其时空变化特征的基础上,识别了地下水储量下降明显区域的人口暴露度。结果表明：（1） 空间分布上,黄河流域地下水储量西多东少,由西向东下降程度不断加剧,且下降区域呈现由下游向中上游扩散的态势。下降区域主要集中在中东部地区,变化等级以较剧烈减少和剧烈减少为主。（2） 时间变化上,2003—2016年黄河流域地下水储量整体呈下降趋势,年均降幅为5.93 mm·a^-1。其中,2004—2016年为连续下降,2015—2016年的下降幅度最大;另外,地下水储量时间变化存在季节效应,地下水储量下降幅度春季最大、冬季次之、秋季再次之、夏季最小。（3） 地下水暴露风险状态下的地级市人口密度在空间上呈东高西低、中部交错分布的状态,暴露风险人口密度最大地级市共16个;地下水储量下降人口累积百分比呈现明显上升的趋势,在2016年达到最大值。研究结果以期为黄河流域地下水资源可持续利用提供科学参考。     

基于GRACE卫星和地表流动重力的汶川MS 8.0地震前重力时空变化

利用GRACE卫星重力场模型和地表流动重力观测资料,计算2008年汶川M_S 8.0地震发生前6年的重力变化,对卫星和流动重力段差结果与卫星重力反映的重力场动态变化特征进行研究,结果表明：①GRACE卫星重力段差受滤波半径影响显著,与地表流动重力观测结果相比,在重力变化数值上差异较大,在变化率上较为一致;②在汶川地震孕育阶段,川滇地区重力等值线呈“增大—减速增大—减小”的特征,震前2年形成近似垂直于龙门山断裂带的重力变化梯度带。     

Hydrological variability of major French rivers over recent decades,assessed from gauging station and GRACE observations

Abstract

This study was carried out in the framework of the Surface Water and Ocean Topography (SWOT) programme of the French National Centre of Space Studies (CNES). Based on discharge measurements and Gravity Recovery and Climate Experiment (GRACE) determination of total water storage (TWS), we have investigated the hydrological variability of the main French drainage basins (Seine, Loire, Garonne and Rhône) using a wavelet approach (continuous wavelet analyses and wavelet coherence analyses). The results of this analysis have shown a coherence ranging between 82% and 90% for TWS and discharge, thus demonstrating the potential use of TWS for characterization of the hydrological variability of French rivers. Strong coherence between the four basin discharges (between 73% and 92%) and between their associated TWS data (from 82% to 98%) suggested a common external influence on hydrological variability. To determine this influence, we investigated the relationship between hydrological variability and the North Atlantic Oscillation (NAO), considered as an index of prevailing climate in Europe. Basin discharges show strong coherence with NAO, ranging between 64% and 72% over the period 1959–2010. The coherence between NAO and TWS was 62% to 67% for 2003–2009. This is similar to the coherence between NAO and basin discharges detected for the same period. According to these results, strong influence of the NAO was clearly observed on the TWS and discharges of the major French river basins.

Editor Z.W. Kundzewicz     

Relation between GRACE-derived surface mass variations and precipitation over Australia

Surface mass changes (SMCs) obtained from time-variable gravity observations of the Gravity Recovery and Climate Experiment (GRACE) satellite mission and precipitation data from the Australian Bureau of Metrology and the Tropical Rainfall Measurement Mission are analysed over the Australian continent to determine whether there is a statistically significant correlation between them. The multiple linear regression analysis and the principal-component analysis techniques are applied in order to reveal the spatial and temporal variability of each data set separately as well as their mutual relationships. The study provides results and their statistical significance for the whole of Australia including the Murray Darling Basin in the southeast. The results suggest a significant decrease in water storage in the southeast of Australia and a dominant annual cycle over the majority of the continent for the four year period considered (January 2003 to December 2006), both in the surface mass and rainfall time series. The study revealed a direct relation between the data sets over most parts of Australia as confirmed by visual comparison and correlation analysis. When compared with precipitation data GRACE-derived SMCs exhibit smoother spatial and temporal variations. The latter is better suited to detect long-term trends in the presence of strong annual signals, which can adversely affect long-term trend estimates. Results regarding the magnitude of the annual signal suggest that only about a fourth of the precipitation's water masses remain sufficiently long in an area to be detected as a gravity change. The respective phases of the annual signals show an average time lag of about 40 days between precipitation and SMCs, suggesting that it takes about one to two months until a temporal gravity observation can detect a precipitation event.     

GRACE detection of the medium- to far-field coseismic gravity changes caused by the 2004 MW9.3 Sumatra-Andaman earthquake

Large earthquakes cause observable changes in the Earth's gravity field, which have been detected by the Gravity Recovery and Climate Experiment (GRACE). Since most previous studies focus on the detection of near-field gravity effects, this study provides the results from the medium- to far-field gravity changes caused by the 2004 Sumatra-Andaman earthquake that are recorded within GRACE monthly solutions. Utilizing a spherical-earth dislocation model we documented that large-scale signals predominate in the global field of the coseismic gravity changes caused by the earthquake. After removing the near-field effects, the coseismic gravity changes show a negative anomaly feature with an average magnitude of -0.18×10^-8 m·s^-2 in the region ranging ~40° from the epicenter, which is considered as the "medium field" in this study. From the GRACE data released by Center for Space Research from August 2002 to December 2008, we retrieved the large-scale gravity changes smoothed with 3 000 km Gaussian filter. The results show that the coseismic gravity changes detected by GRACE in the medium field have an average of (-0.20€±0.06)×10^-8 m·s^-2, which agrees with the model prediction. The detection confirms that GRACE is sensitive to large-scale medium-field coseismic gravitational effects of mega earthquakes, and also validates the spherical-earth dislocation model in the medium field from the perspective of satellite gravimetry.     

An analysis of the steric sea level change by introducing sea surface temperature

In this paper, we use the optimum interpolation sea surface temperature (OISST) provided by the National Center for Environmental Prediction (NCEP) to replace the temperature in the top three layers in the ISHII data, and make use of the modified ISHII temperature data to calculate the thermosteric sea level (called modified steric sea level (SSL) hereafter). We subtract the modified SSL and the steric sea level (called ordinary SSL hereafter) derived from the ISHII temperature and salinity from the steric sea level (SSL) provided by the Gravity Recovery and Climate Experiment (GRACE), respectively, and find that the rms error of the difference of the former is obviously smaller than that of the latter. Therefore we reach the conclusion that under the assumption that the GRACE SSL is accurate, the modified SSL can reflect the true steric sea level more accurately. Making use of the modified SSL, we can find that the modified SSL in sea areas of different spatial scales shows an obvious rising trend in the upper 0-700 m layer for the period 1982-2006. The global mean SSL rises with a rate of 0.6 mm year-1 .The modified SSLs in sea areas of different spatial scales all show obvious oscillations with period of one year. There are oscillations with periods of 4-8 years in global oceans and with periods of 2-7 years in the Pacific. The Empirical Orthogonal Function method is applied to the sea areas of different spatial scales and we find that the first modes all have obvious 1-year period oscillations, the first mode of the global ocean has 4-8 year period oscillations, and that of the Pacific has 2-6 year period oscillations. The spatial distribution of the linear rising trend of the global modified SSL in the upper 0-700 m layer is inhomogeneous with intense regional characteristics. The modified SSL linear trend indicates a zonal dipole in the tropical Pacific, rising in the west and descending in the east. In the North Atlantic, the modified SSL indicates a meridional dipole, rising in the latitude band of 20°N-40°N and 45°N-65.5°N and descending obviously in the latitude band of 40°N-45°N.