水是生物体所必需的组成部分，是自然界最重要的资源，是地球最不可少的物质之一。对区域水资源进行有效地监测，在科学研究和实际生活中都具有十分重要的意义。目前，监测陆地水储量的手段主要包括水文观测、GRACE/GFO和GNSS，尽管水文观测的精度较高，但难以获取所有水成分（如深层地下水等）的数据。GRACE/GFO虽然能够监测大范围的水储量信息，但是，受空间、时间分辨率的限制，其难以获取高频或局部区域的水储量信息。GNSS能有效地监测局部区域由地表质量变化导致的位移变化，被广泛应用于监测区域陆地水储量变化。然而，GNSS 测站分布的密集程度以及其观测数据中包含的复杂非水文信息等，会直接影响其反演陆地水储量变化的可靠性和分辨率。鉴于GNSS和GRACE/GFO在反演区域陆地储水量变化方面具有互补优势，本文借鉴“分解-重构”法（Decomposition and Reconstruction Method，DRM）的思想，基于负荷格林函数理论，提出了一种融合GNSS和GRACE/GFO数据反演陆地储水量变化的方法。利用中国西南地区的90个GNSS测站位移时间序列数据和GRACE/GFO数据反演了该地区的陆地水储量变化，并与基于广义三角帽（Generalized Three-cornered Hat，GTCH）的融合方法进行了对比，以验证DRM融合方法的性能。主要工作和结论如下：

       (1)利用GRACE/GFO和水文模型数据，反演了2003-2011年中国西南地区陆地水储量变化，以验证GRACE/GFO反演陆地水储量变化的性能。2003-2011年间，西南地区陆地水储量整体上呈先上升再下降的趋势，峰值位于2008年。利用经验模态分解对GRACE/GFO和GLDAS计算的西南地区水储量变化时间序列进行了分解，发现其具有约4年的年际水循环周期。GRACE/GFO可以很好地反映区域陆地水储量的长期变化趋势，但反演结果过于平滑，无法体现局部高频的水储量变化。

       (2)利用最小二乘法对2012-2022年西南地区GNSS水文负荷位移进行拟合，计算了其周期振幅和相位，结果表明西南地区水文负荷位移的年振幅和相位均呈现出明显的空间差异，整体上由北向南逐渐增大，在云南南部地区达到峰值。此外，本文利用独立分量分析对GNSS水文负荷位移信号进行了分解，表明西南地区的陆地水储量变化具有多尺度水文周期的特征。由第三、四个独立分量可以看出，GNSS水文负荷位移中还包含了大量复杂的非水文信息，对反演结果可能产生一定的影响。

       (3)使用GNSS和GRACE/GFO数据通过DRM融合方法反演了中国西南地区2012-2022年的陆地水储量变化。在空间分布上，基于DRM融合方法反演的陆地水储量变化综合了GNSS和 GRACE/GFO各自的优点，提高了反演结果的可靠性。在时序变化上，仅使用GNSS、GRACE/GFO和基于DRM融合方法的反演结果具有较为一致的季节性变化。仅使用GNSS、GRACE/GFO反演结果与降水的最佳相关性出现在滞后降水2个月时，相关系数分别为0.84和0.82，而基于DRM融合方法的反演结果仅滞后于降水1个月，相关系数为0.89，高于仅利用GNSS、GRACE/GFO的相关系数。这表明，基于DRM融合方法的反演结果对降水引起的陆地水储量变化的响应比仅使用GNSS和GRACE/GFO更为敏捷和准确。

        Water is an essential component of living organisms, the most important resource of nature and one of the most indispensable substances of the Earth. The effective monitoring of regional water resources is of great significance in both scientific research and practical life. At present, the means of monitoring terrestrial water storage mainly include hydrological observation, GRACE/GFO and GNSS. Although hydrological observation has higher accuracy, it is difficult to obtain data of all water components (e.g., deep groundwater, etc.); GRACE/GFO is able to monitor the information on water storage on a large scale, but it is difficult to obtain the information on water storage in the high-frequency or local area due to the limitation of spatial and temporal resolution. GNSS can effectively monitor displacement changes caused by changes in surface quality in local areas, and has been widely used to monitor changes in regional terrestrial water storage. However, the density of GNSS stations and the complexity of non-hydrological information contained in the observation results directly affect the reliability and resolution of the inversion of terrestrial water storage changes. In view of the complementary advantages of GNSS and GRACE/GFO in reflecting regional terrestrial water storage changes, this paper draws on the idea of the Decomposition and Reconstruction Method (DRM), and based on the theory of the load Green's function, proposes a method that integrates GNSS and GRACE/GFO. In this paper, a method is proposed to integrate GNSS and GRACE/GFO data to invert the change of terrestrial water storage. The terrestrial water storage changes in Southwest China were inverted using 90 GNSS station displacement time series data and GRACE/GFO data, and compared with the fusion method based on Generalised Three-cornered Hat (GTCH) to verify the performance of the DRM fusion method. The main work and conclusions are as follows:

          (1) Using GRACE/GFO and hydrological model data, we inverted the terrestrial water storage changes in Southwest China from 2003 to 2011 to verify the performance of GRACE/GFO in inverting the terrestrial water storage changes. During the period of 2003-2011, the terrestrial water storage in Southwest China showed an overall trend of increasing and then decreasing, and the peak was located in 2008. The time series of water storage changes in the southwest region calculated by GRACE/GFO and GLDAS were decomposed using empirical mode decomposition, and found to have an interannual water cycle of about 4 yr. GRACE/GFO can well reflect the long-term trend of regional terrestrial water storage, but the inversion results are too smooth to reflect the local high-frequency water storage changes.

          (2) The least squares method is used to fit the GNSS hydrological load displacements in the Southwest region from 2012 to 2022, and the cycle amplitude and phase are calculated. The results show that the annual amplitude and phase of the hydrological load displacements in the Southwest region show obvious spatial differences, and the overall gradual increase from the north to the south, which reaches the peak in the southern region of Yunnan. In addition, this paper decomposes the GNSS hydrological load displacement signals using independent component analysis, indicating that the terrestrial water storage changes in Southwest China are characterised by a multi-scale hydrological cycle. From the third and fourth independent components, it can be seen that the GNSS hydrological load displacement also contains a large amount of complex non-hydrological information, which may have a certain impact on the inversion results.

           (3) The terrestrial water storage changes in Southwest China from 2012 to 2022 were inverted using the DRM fusion method and GNSS and GRACE/GFO data. In terms of spatial distribution, the DRM fusion inversion of terrestrial water storage changes combines the respective advantages of GNSS and GRACE/GFO, which improves the reliability of the inversion results. In terms of temporal changes, the fusion inversion results using only GNSS, GRACE/GFO and DRM have more consistent seasonal changes. The best correlation between the inversion results using only GNSS and GRACE/GFO and precipitation occurs at a lag of 2 months, with correlation coefficients of 0.84 and 0.82, respectively, whereas the DRM fusion inversion results are only lagged by 1 month, with a correlation coefficient of 0.89, which is higher than that of the correlation coefficients of using only GNSS and GRACE/GFO. This indicates that the DRM fusion inversion method is more agile and accurate in responding to precipitation-induced changes in terrestrial water storage than using only GNSS and only GRACE/GFO.

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