Journal articles: 'Terrestrial Water Storage'

1

Kuehne, John, and Clark R. Wilson. "Terrestrial water storage and polar motion." Journal of Geophysical Research: Solid Earth 96, B3 (March 10, 1991): 4337–45. http://dx.doi.org/10.1029/90jb02573.

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Savin, Igor Yu, and Bakhytnur S. Gabdullin. "Specifics of long-term dynamics of terrestrial water storage detected using GRACE satellite in Belgorod region." RUDN Journal of Agronomy and Animal Industries 15, no. 4 (December 15, 2020): 363–74. http://dx.doi.org/10.22363/2312-797x-2020-15-4-363-374.

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GRACE monthly satellite data for the period from 2002 to 2016 were used to analyze the longterm dynamics of the terrestrial water storage in the Belgorod region of Russia. The correlation of satellite data with climatic water balance with a lag varying on the territory from 2 to 4 months was revealed. There was found a stable tendency to decrease in terrestrial water storage, and predominance of negative values on the territory of the Belgorod region since 2008. The minimum attains the lowest values in comparison with the whole studied period. However, seasonality of the changes is maintained throughout the entire analyzed time series. The frequency of changes in the terrestrial water storage throughout the entire area is not very clear: only the long-term maximum of the terrestrial water storage of the territory in 2006 is well expressed. Another, less pronounced local maximum was observed in 2013. Local long-term minima of the terrestrial water storage of the territory were in 2002, 2009 and 2015. There is a positive trend in the amplitude of seasonal fluctuations in the terrestrial water storage of the territory: the amplitude has been constantly increasing in recent years. The territory of the Belgorod region has negative long-term trend of terrestrial water storage with their rather large spatial variation. The angle of inclination of the trend decreases from north-west to south-east in the region. GRACE satellite data can serve as a fairly reliable detection indicator of the trend of terrestrial water storage in large areas.

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Hirschi, Martin, and Sonia I. Seneviratne. "Basin-scale water-balance dataset (BSWB): an update." Earth System Science Data 9, no. 1 (March 30, 2017): 251–58. http://dx.doi.org/10.5194/essd-9-251-2017.

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Abstract. This paper presents an update of a basin-scale diagnostic dataset of monthly variations in terrestrial water storage for large river basins worldwide (BSWB v2016, doi:10.5905/ethz-1007-82). Terrestrial water storage comprises all forms of water storage on land surfaces, and its seasonal and inter-annual variations are mostly determined by soil moisture, groundwater, snow cover, and surface water. The dataset presented is derived using a combined atmospheric and terrestrial water-balance approach with conventional streamflow measurements and reanalysis data of atmospheric moisture flux convergence. It extends a previous, existing version of the dataset (Mueller et al., 2011) temporally and spatially.

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Trautmann, Tina, Sujan Koirala, Nuno Carvalhais, Annette Eicker, Manfred Fink, Christoph Niemann, and Martin Jung. "Understanding terrestrial water storage variations in northern latitudes across scales." Hydrology and Earth System Sciences 22, no. 7 (July 27, 2018): 4061–82. http://dx.doi.org/10.5194/hess-22-4061-2018.

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Abstract. The GRACE satellites provide signals of total terrestrial water storage (TWS) variations over large spatial domains at seasonal to inter-annual timescales. While the GRACE data have been extensively and successfully used to assess spatio-temporal changes in TWS, little effort has been made to quantify the relative contributions of snowpacks, soil moisture, and other components to the integrated TWS signal across northern latitudes, which is essential to gain a better insight into the underlying hydrological processes. Therefore, this study aims to assess which storage component dominates the spatio-temporal patterns of TWS variations in the humid regions of northern mid- to high latitudes. To do so, we constrained a rather parsimonious hydrological model with multiple state-of-the-art Earth observation products including GRACE TWS anomalies, estimates of snow water equivalent, evapotranspiration fluxes, and gridded runoff estimates. The optimized model demonstrates good agreement with observed hydrological spatio-temporal patterns and was used to assess the relative contributions of solid (snowpack) versus liquid (soil moisture, retained water) storage components to total TWS variations. In particular, we analysed whether the same storage component dominates TWS variations at seasonal and inter-annual temporal scales, and whether the dominating component is consistent across small to large spatial scales. Consistent with previous studies, we show that snow dynamics control seasonal TWS variations across all spatial scales in the northern mid- to high latitudes. In contrast, we find that inter-annual variations of TWS are dominated by liquid water storages at all spatial scales. The relative contribution of snow to inter-annual TWS variations, though, increases when the spatial domain over which the storages are averaged becomes larger. This is due to a stronger spatial coherence of snow dynamics that are mainly driven by temperature, as opposed to spatially more heterogeneous liquid water anomalies, that cancel out when averaged over a larger spatial domain. The findings first highlight the effectiveness of our model–data fusion approach that jointly interprets multiple Earth observation data streams with a simple model. Secondly, they reveal that the determinants of TWS variations in snow-affected northern latitudes are scale-dependent. In particular, they seem to be not merely driven by snow variability, but rather are determined by liquid water storages on inter-annual timescales. We conclude that inferred driving mechanisms of TWS cannot simply be transferred from one scale to another, which is of particular relevance for understanding the short- and long-term variability of water resources.

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Trautmann, Tina, Sujan Koirala, Nuno Carvalhais, Andreas Güntner, and Martin Jung. "The importance of vegetation in understanding terrestrial water storage variations." Hydrology and Earth System Sciences 26, no. 4 (February 24, 2022): 1089–109. http://dx.doi.org/10.5194/hess-26-1089-2022.

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Abstract. So far, various studies have aimed at decomposing the integrated terrestrial water storage variations observed by satellite gravimetry (GRACE, GRACE-FO) with the help of large-scale hydrological models. While the results of the storage decomposition depend on model structure, little attention has been given to the impact of the way that vegetation is represented in these models. Although vegetation structure and activity represent the crucial link between water, carbon, and energy cycles, their representation in large-scale hydrological models remains a major source of uncertainty. At the same time, the increasing availability and quality of Earth-observation-based vegetation data provide valuable information with good prospects for improving model simulations and gaining better insights into the role of vegetation within the global water cycle. In this study, we use observation-based vegetation information such as vegetation indices and rooting depths for spatializing the parameters of a simple global hydrological model to define infiltration, root water uptake, and transpiration processes. The parameters are further constrained by considering observations of terrestrial water storage anomalies (TWS), soil moisture, evapotranspiration (ET) and gridded runoff (Q) estimates in a multi-criteria calibration approach. We assess the implications of including varying vegetation characteristics on the simulation results, with a particular focus on the partitioning between water storage components. To isolate the effect of vegetation, we compare a model experiment in which vegetation parameters vary in space and time to a baseline experiment in which all parameters are calibrated as static, globally uniform values. Both experiments show good overall performance, but explicitly including varying vegetation data leads to even better performance and more physically plausible parameter values. The largest improvements regarding TWS and ET are seen in supply-limited (semi-arid) regions and in the tropics, whereas Q simulations improve mainly in northern latitudes. While the total fluxes and storages are similar, accounting for vegetation substantially changes the contributions of different soil water storage components to the TWS variations. This suggests an important role of the representation of vegetation in hydrological models for interpreting TWS variations. Our simulations further indicate a major effect of deeper moisture storages and groundwater–soil moisture–vegetation interactions as a key to understanding TWS variations. We highlight the need for further observations to identify the adequate model structure rather than only model parameters for a reasonable representation and interpretation of vegetation–water interactions.

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6

Hatch, Mike. "Environmental geophysics/ Grace mapping of terrestrial water storage." Preview 2019, no. 202 (September 3, 2019): 38–39. http://dx.doi.org/10.1080/14432471.2019.1671159.

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7

Balcerak, Ernie. "Predicting fire activity using terrestrial water storage data." Eos, Transactions American Geophysical Union 94, no. 21 (May 21, 2013): 196. http://dx.doi.org/10.1002/2013eo210015.

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Chinnasamy, Pennan, and Revathi Ganapathy. "Long-term variations in water storage in Peninsular Malaysia." Journal of Hydroinformatics 20, no. 5 (November 7, 2017): 1180–90. http://dx.doi.org/10.2166/hydro.2017.043.

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Abstract Information on ongoing climate change impacts on water availability is limited for Asian regions, particularly for Peninsular Malaysia. Annual flash floods are common during peak monsoon seasons, while the dry seasons are hit by droughts, leading to socio-economic stress. This study, for the first time, analyzed the long-term trends (14 years, from 2002 to 2014) in terrestrial water storage and groundwater storage for Peninsular Malaysia, using Gravity Recovery And Climate Experiment data. Results indicate a decline in net terrestrial and groundwater storage over the last decade. Spatially, the northern regions are more affected by droughts, while the southern regions have more flash floods. Groundwater storage trends show strong correlations to the monsoon seasons, indicating that most of the shallow aquifer groundwater is used. Results also indicate that, with proper planning and management, excess monsoon/flash flood water can be stored in water storage structures up to the order of 87 billion liters per year. This can help in dry season water distribution and water transfer projects. Findings from this study can expand the understanding of ongoing climate change impacts on groundwater storage and terrestrial water storage, and can lead to better management of water resources in Peninsular Malaysia.

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9

Meng, Gaojia, Guofeng Zhu, Jiawei Liu, Kailiang Zhao, Siyu Lu, Rui Li, Dongdong Qiu, Yinying Jiao, Longhu Chen, and Niu Sun. "GRACE Data Quantify Water Storage Changes in the Shiyang River Basin, an Inland River in the Arid Zone." Remote Sensing 15, no. 13 (June 21, 2023): 3209. http://dx.doi.org/10.3390/rs15133209.

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Global changes and human activities have significantly altered water cycle processes and water resource patterns in inland river basins in arid zones. New tools are needed to conduct more comprehensive and scientific assessments of basin water cycle processes and water resource patterns. Based on GRACE satellite and Landsat data, this study investigated terrestrial water storage changes and surface water area in the Shiyang River Drainage Basin from 2002 to 2021. It explored the effects of climate change and water conservancy construction on terrestrial water storage changes in the basin. The results of the study show that, although the surface water quantity in the Shiyang River basin has increased in the past 20 years, the overall decreasing trend of terrestrial water storage in the basin of the Shiyang River has an interannual decreasing rate of 0.01 cm/a. The decreasing trend of water storage in the midstream and downstream areas is more prominent. The change in precipitation controls the change in water storage in the Shiyang River Drainage Basin. Artificial water transfer has changed the spatial distribution of water resources in the basin of the Shiyang River. However, it still has not completely reversed the trend of decreasing water storage in the middle and lower reaches of the Shiyang River.

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He, Yanfeng, Jinghua Xiong, Shenglian Guo, Sirui Zhong, Chuntao Yu, and Shungang Ma. "Using Multi-Source Data to Assess the Hydrologic Alteration and Extremes under a Changing Environment in the Yalong River Basin." Water 15, no. 7 (April 1, 2023): 1357. http://dx.doi.org/10.3390/w15071357.

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Climate change and human activities are two important factors in the changing environment that affect the variability of the hydrological cycle and river regime in the Yalong River basin. This paper analyzed the hydrological alteration and extremes in the Yalong River basin based on multi-source satellite data, and projected the hydrological response under different future climate change scenarios using the CwatM hydrological model. The results show that: (1) The overall change in hydrological alteration at Tongzilin station was moderate during the period of 1998–2011 and severe during the period of 2012–2020. (2) Precipitation (average 781 mm/a) is the dominant factor of water cycle on a monthly scale, which can explain the temporal variability of runoff, evaporation, and terrestrial water storage, while terrestrial water storage is also simultaneously regulated by runoff and evaporation. (3) The GRACE data are comparable with regional water resource bulletins. The terrestrial water storage is mainly regulated by surface water (average 1062 × 108 m3), while the contribution of groundwater (average 298 × 108 m3) is relatively small. (4) The evaporation and runoff processes will intensify in the future due to climate warming and increasing precipitation (~10%), and terrestrial water storage will be depleted. The magnitude of change will increase with the enhancement of emission scenarios.

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11

Hirschi, Martin, Sonia I. Seneviratne, and Christoph Schär. "Seasonal Variations in Terrestrial Water Storage for Major Midlatitude River Basins." Journal of Hydrometeorology 7, no. 1 (February 1, 2006): 39–60. http://dx.doi.org/10.1175/jhm480.1.

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Abstract This paper presents a new diagnostic dataset of monthly variations in terrestrial water storage for 37 midlatitude river basins in Europe, Asia, North America, and Australia. Terrestrial water storage is the sum of all forms of water storage on land surfaces, and its seasonal and interannual variations are in principle determined by soil moisture, groundwater, snow cover, and surface water. The dataset is derived with the combined atmospheric and terrestrial water-balance approach using conventional streamflow measurements and atmospheric moisture convergence data from the ECMWF 40-yr Re-Analysis (ERA-40). A recent study for the Mississippi River basin (Seneviratne et al. 2004) has demonstrated the validity of this diagnostic approach and found that it agreed well with in situ observations in Illinois. The present study extends this previous analysis to other regions of the midlatitudes. A systematic analysis is presented of the slow drift that occurs with the water-balance approach. It is shown that the drift not only depends on the size of the catchment under consideration, but also on the geographical region and the underlying topography. The drift is in general not constant in time, but artificial inhomogeneities may result from changes in the global observing system used in the 44 yr of the reanalysis. To remove this time-dependent drift, a simple high-pass filter is applied. Validation of the results is conducted for several catchments with an appreciable coverage of in situ soil moisture and snow cover depth observations in the former Soviet Union, Mongolia, and China. Although the groundwater component is not accounted for in these observations, encouraging correlations are found between diagnostic and in situ estimates of terrestrial water storage, both for seasonal and interannual variations. Comparisons conducted against simulated ERA-40 terrestrial water storage variations suggest that the reanalysis substantially underestimates the amplitude of the seasonal cycle. The basin-scale water-balance (BSWB) dataset is available for download over the Internet. It constitutes a useful tool for the validation of climate models, large-scale land surface data assimilation systems, and indirect observations of terrestrial water storage variations.

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12

Troch, Peter, Matej Durcik, Sonia Seneviratne, Martin Hirschi, Adriaan Teuling, Ruud Hurkmans, and Shaakeel Hasan. "New data sets to estimate terrestrial water storage change." Eos, Transactions American Geophysical Union 88, no. 45 (November 6, 2007): 469–70. http://dx.doi.org/10.1029/2007eo450001.

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13

Hamlington, B. D., J. T. Reager, H. Chandanpurkar, and K. ‐Y Kim. "Amplitude Modulation of Seasonal Variability in Terrestrial Water Storage." Geophysical Research Letters 46, no. 8 (April 23, 2019): 4404–12. http://dx.doi.org/10.1029/2019gl082272.

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14

Kenea, Tadesse Tujuba, Jürgen Kusche, Seifu Kebede, and Andreas Güntner. "Forecasting terrestrial water storage for drought management in Ethiopia." Hydrological Sciences Journal 65, no. 13 (July 29, 2020): 2210–23. http://dx.doi.org/10.1080/02626667.2020.1790564.

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15

Han, Shin-Chan, C. K. Shum, Christopher Jekeli, and Doug Alsdorf. "Improved estimation of terrestrial water storage changes from GRACE." Geophysical Research Letters 32, no. 7 (April 2005): n/a. http://dx.doi.org/10.1029/2005gl022382.

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Ndehedehe, Christopher E., Joseph L. Awange, Michael Kuhn, Nathan O. Agutu, and Yoichi Fukuda. "Climate teleconnections influence on West Africa's terrestrial water storage." Hydrological Processes 31, no. 18 (July 21, 2017): 3206–24. http://dx.doi.org/10.1002/hyp.11237.

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17

Fersch, Benjamin, Harald Kunstmann, András Bárdossy, Balaji Devaraju, and Nico Sneeuw. "Continental-Scale Basin Water Storage Variation from Global and Dynamically Downscaled Atmospheric Water Budgets in Comparison with GRACE-Derived Observations." Journal of Hydrometeorology 13, no. 5 (October 1, 2012): 1589–603. http://dx.doi.org/10.1175/jhm-d-11-0143.1.

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Abstract Since 2002, the Gravity Recovery and Climate Experiment (GRACE) has provided gravity-derived observations of variations in the terrestrial water storage. Because of the lack of suitable direct observations of large-scale water storage changes, a validation of the GRACE observations remains difficult. An approach that allows the evaluation of terrestrial water storage variations from GRACE by a comparison with those derived from aerologic water budgets using the atmospheric moisture flux divergence is presented. In addition to reanalysis products from the European Centre for Medium-Range Weather Forecasts and the National Centers for Environmental Prediction, high-resolution regional atmospheric simulations were produced with the Weather Research and Forecast modeling system (WRF) and validated against globally gridded observational data of precipitation and 2-m temperature. The study encompasses six different climatic and hydrographic regions: the Amazon basin, the catchments of Lena and Yenisei, central Australia, the Sahara, the Chad depression, and the Niger. Atmospheric-related uncertainty bounds based on the range of the ensemble of estimated terrestrial water storage variations were computed using different configurations of the regional climate model WRF and different global reanalyses. Atmospheric-related uncertainty ranges with those originating from the GRACE products of GeoForschungsZentrum Potsdam, the Center for Space Research, and the Jet Propulsion Laboratory were also compared. It is shown that dynamically downscaled atmospheric fields are able to add value to global reanalyses, depending on the geographical location of the considered catchments. Global and downscaled atmospheric water budgets are in reasonable agreement (r ≈ 0.7 − 0.9) with GRACE-derived terrestrial mass variations. However, atmospheric- and satellite-based approaches show shortcomings for regions with small storage change rates (<20–25 mm month−1).

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Fok, Hok Sum, and Yongxin Liu. "An Improved GPS-Inferred Seasonal Terrestrial Water Storage Using Terrain-Corrected Vertical Crustal Displacements Constrained by GRACE." Remote Sensing 11, no. 12 (June 17, 2019): 1433. http://dx.doi.org/10.3390/rs11121433.

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Based on a geophysical model for elastic loading, the application potential of Global Positioning System (GPS) vertical crustal displacements for inverting terrestrial water storage has been demonstrated using the Tikhonov regularization and the Helmert variance component estimation since 2014. However, the GPS-inferred terrestrial water storage has larger resulting amplitudes than those inferred from satellite gravimetry (i.e., Gravity Recovery and Climate Experiment (GRACE)) and those simulated from hydrological models (e.g., Global Land Data Assimilation System (GLDAS)). We speculate that the enlarged amplitudes should be partly due to irregularly distributed GPS stations and the neglect of the terrain effect. Within southwest China, covering part of southeastern Tibet as a study region, a novel GPS-inferred terrestrial water storage approach is proposed via terrain-corrected GPS and supplementary vertical crustal displacements inferred from GRACE, serving as "virtual GPS stations" for constraining the inversion. Compared to the Tikhonov regularization and Helmert variance component estimation, we employ Akaike’s Bayesian Information Criterion as an inverse method to prove the effectiveness of our solution. Our results indicate that the combined application of the terrain-corrected GPS vertical crustal displacements and supplementary GRACE spatial data constraints improves the inversion accuracy of the GPS-inferred terrestrial water storage from the Helmert variance component estimation, Tikhonov regularization, and Akaike’s Bayesian Information Criterion, by 55%, 33%, and 41%, respectively, when compared to that of the GLDAS-modeled terrestrial water storage. The solution inverted with Akaike’s Bayesian Information Criterion exhibits more stability regardless of the constraint conditions, when compared to those of other inferred solutions. The best Akaike’s Bayesian Information Criterion inverted solution agrees well with the GLDAS-modeled one, with a root-mean-square error (RMSE) of 3.75 cm, equivalent to a 15.6% relative error, when compared to 39.4% obtained in previous studies. The remaining discrepancy might be due to the difference between GPS and GRACE in sensing different surface water storage components, the remaining effect of the water storage changes in rivers and reservoirs, and the internal error in the geophysical model for elastic loading.

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Andrew, Robert L., Huade Guan, and Okke Batelaan. "Large-scale vegetation responses to terrestrial moisture storage changes." Hydrology and Earth System Sciences 21, no. 9 (September 8, 2017): 4469–78. http://dx.doi.org/10.5194/hess-21-4469-2017.

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Abstract. The normalised difference vegetation index (NDVI) is a useful tool for studying vegetation activity and ecosystem performance at a large spatial scale. In this study we use the Gravity Recovery and Climate Experiment (GRACE) total water storage (TWS) estimates to examine temporal variability of the NDVI across Australia. We aim to demonstrate a new method that reveals the moisture dependence of vegetation cover at different temporal resolutions. Time series of monthly GRACE TWS anomalies are decomposed into different temporal frequencies using a discrete wavelet transform and analysed against time series of the NDVI anomalies in a stepwise regression. The results show that combinations of different frequencies of decomposed GRACE TWS data explain NDVI temporal variations better than raw GRACE TWS alone. Generally, the NDVI appears to be more sensitive to interannual changes in water storage than shorter changes, though grassland-dominated areas are sensitive to higher-frequencies of water-storage changes. Different types of vegetation, defined by areas of land use type, show distinct differences in how they respond to the changes in water storage, which is generally consistent with our physical understanding. This unique method provides useful insight into how the NDVI is affected by changes in water storage at different temporal scales across land use types.

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Xu, Min, Bai Sheng Ye, and Qiu Dong Zhao. "Terrestrial Water Storge Changes in the Tangnaihai Basin Measured by GRACE during 2003-2008, China." Applied Mechanics and Materials 316-317 (April 2013): 520–26. http://dx.doi.org/10.4028/www.scientific.net/amm.316-317.520.

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Abstract.The amount of water storage change in Tangnaihai basin is obtained by using monthly gravity field data, which is derived from GRACE satellite between 2003 and 2008, with Gaussian filter. Combined with the same time period monthly precipitation data of the regional meteorological stations, we analysis spatial-temporal variation trend of water storge change in Tangnaihai basin for nearly 6 years. Results show that the spatial distribution of water storge change in Tangnaihai basin has obvious difference,water storge change is more in west than in east area.Water storge change has obviously seasonal variation change, and it has the same process with precipitation.The trend of water storge change increase in annual in study area. Water storge change increased from 2003 to 2008 in totally in Tangnaihai basin.The average rate is 0.5 mm/month,and water storge change reduced about 6.1*106 m3.

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Pokhrel, Yadu, Farshid Felfelani, Yusuke Satoh, Julien Boulange, Peter Burek, Anne Gädeke, Dieter Gerten, et al. "Global terrestrial water storage and drought severity under climate change." Nature Climate Change 11, no. 3 (January 11, 2021): 226–33. http://dx.doi.org/10.1038/s41558-020-00972-w.

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22

Huang, Qingzhong, Qiang Zhang, Chong-Yu Xu, Qin Li, and Peng Sun. "Terrestrial Water Storage in China: Spatiotemporal Pattern and Driving Factors." Sustainability 11, no. 23 (November 25, 2019): 6646. http://dx.doi.org/10.3390/su11236646.

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China is the largest agricultural country with the largest population and booming socio-economy, and hence, remarkably increasing water demand. In this sense, it is practically critical to obtain knowledge about spatiotemporal variations of the territorial water storage (TWS) and relevant driving factors. In this study, we attempted to investigate TWS changes in both space and time using the monthly GRACE (Gravity Recovery and Climate Experiment) data during 2003–2015. Impacts of four climate indices on TWS were explored, and these four climate indices are, respectively, El Niño Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), North Atlantic Oscillation (NAO), and Pacific decadal oscillation (PDO). In addition, we also considered the impacts of precipitation changes on TWS. We found significant correlations between climatic variations and TWS changes across China. Meanwhile, the impacts of climate indices on TWS changes were shifting from one region to another across China with different time lags ranging from 0 to 12 months. ENSO, IOD and PDO exerted significant impacts on TWS over 80% of the regions across China, while NAO affected TWS changes over around 40% of the regions across China. Moreover, we also detected significant relations between TWS and precipitation changes within 9 out of the 10 largest river basins across China. These results highlight the management of TWS across China in a changing environment and also provide a theoretical ground for TWS management in other regions of the globe.

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Lenk, Onur. "Satellite based estimates of terrestrial water storage variations in Turkey." Journal of Geodynamics 67 (July 2013): 106–10. http://dx.doi.org/10.1016/j.jog.2012.04.010.

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Ni, Shengnan, Jianli Chen, Clark R. Wilson, Jin Li, Xiaogong Hu, and Rong Fu. "Global Terrestrial Water Storage Changes and Connections to ENSO Events." Surveys in Geophysics 39, no. 1 (July 24, 2017): 1–22. http://dx.doi.org/10.1007/s10712-017-9421-7.

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Lee, Sang-Il. "Validation of Terrestrial Water Storage Change Estimates Using Hydrologic Simulation." Journal of Water Resources and Ocean Science 3, no. 1 (2014): 5. http://dx.doi.org/10.11648/j.wros.20140301.12.

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Śliwińska, Justyna, Małgorzata Wińska, and Jolanta Nastula. "Terrestrial water storage variations and their effect on polar motion." Acta Geophysica 67, no. 1 (December 6, 2018): 17–39. http://dx.doi.org/10.1007/s11600-018-0227-x.

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Lee, Hoontaek, Martin Jung, Nuno Carvalhais, Tina Trautmann, Basil Kraft, Markus Reichstein, Matthias Forkel, and Sujan Koirala. "Diagnosing modeling errors in global terrestrial water storage interannual variability." Hydrology and Earth System Sciences 27, no. 7 (April 14, 2023): 1531–63. http://dx.doi.org/10.5194/hess-27-1531-2023.

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Abstract. Terrestrial water storage (TWS) is an integrative hydrological state that is key for our understanding of the global water cycle. The TWS observation from the GRACE missions has, therefore, been instrumental in the calibration and validation of hydrological models and understanding the variations in the hydrological storage. The models, however, still show significant uncertainties in reproducing observed TWS variations, especially for the interannual variability (IAV) at the global scale. Here, we diagnose the regions dominating the variance in globally integrated TWS IAV and the sources of the errors in two data-driven hydrological models that were calibrated against global TWS, snow water equivalent, evapotranspiration, and runoff data. We used (1) a parsimonious process-based hydrological model, the Strategies to INtegrate Data and BiogeochemicAl moDels (SINDBAD) framework and (2) a machine learning, physically based hybrid hydrological model (H2M) that combines a dynamic neural network with a water balance concept. While both models agree with the Gravity Recovery and Climate Experiment (GRACE) that global TWS IAV is largely driven by the semi-arid regions of southern Africa, the Indian subcontinent and northern Australia, and the humid regions of northern South America and the Mekong River basin, the models still show errors such as the overestimation of the observed magnitude of TWS IAV at the global scale. Our analysis identifies modeling error hotspots of the global TWS IAV, mostly in the tropical regions including the Amazon, sub-Saharan regions, and Southeast Asia, indicating that the regions that dominate global TWS IAV are not necessarily the same as those that dominate the error in global TWS IAV. Excluding those error hotspot regions in the global integration yields large improvements in the simulated global TWS IAV, which implies that model improvements can focus on improving processes in these hotspot regions. Further analysis indicates that error hotspot regions are associated with lateral flow dynamics, including both sub-pixel moisture convergence and across-pixel lateral river flow, or with interactions between surface processes and groundwater. The association of model deficiencies with land processes that delay the TWS variation could, in part, explain why the models cannot represent the observed lagged response of TWS IAV to precipitation IAV in hotspot regions that manifest as errors in global TWS IAV. Our approach presents a general avenue to better diagnose model simulation errors for global data streams to guide efficient and focused model development for regions and processes that matter the most.

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Idowu and Zhou. "Performance Evaluation of a Potential Component of an Early Flood Warning System—A Case Study of the 2012 Flood, Lower Niger River Basin, Nigeria." Remote Sensing 11, no. 17 (August 21, 2019): 1970. http://dx.doi.org/10.3390/rs11171970.

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Floods frequently occur in Nigeria. The catastrophic 2012 flood in Nigeria claimed 363 lives and affected about seven million people. A total loss of about 2.29 trillion Naira (7.2 billion US Dollars) was estimated. The effect of flooding in the country has been devastating because of sparse to no flood monitoring, and a lack of an effective early flood warning system in the country. Here, we evaluated the efficacy of using the Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage anomaly (TWSA) to evaluate the hydrological conditions of the Lower Niger River Basin (LNRB) in Nigeria in terms of precipitation and antecedent terrestrial water storage prior to the 2012 flood event. Furthermore, we accessed the potential of the GRACE-based flood potential index (FPI) at correctly predicting previous floods, especially the devastating 2012 flood event. For validation, we compared the GRACE terrestrial water storage capacity (TWSC) quantitatively and qualitatively to the water budget of TWSC and Dartmouth Flood Observatory (DFO) respectively. Furthermore, we derived a water budget-based FPI using Reager’s methodology and compared it to the GRACE-derived FPI quantitatively. Generally, the GRACE TWSC estimates showed seasonal consistency with the water budget TWSC estimates with a correlation coefficient of 0.8. The comparison between the GRACE-derived FPI and water budget-derived FPI gave a correlation coefficient of 0.9 and also agreed well with the flood reported by the DFO. Also, the FPI showed a marked increase with precipitation which implies that rainfall is the main cause of flooding in the study area. Additionally, the computed GRACE-based storage deficit revealed that there was a decrease in water storage prior to the flooding month while the FPI increased. Hence, the GRACE-based FPI and storage deficit when supplemented with water budget-based FPI could suggest a potential for flood prediction and water storage monitoring respectively.

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Tang, Qiuhong, Huilin Gao, Pat Yeh, Taikan Oki, Fengge Su, and Dennis P. Lettenmaier. "Dynamics of Terrestrial Water Storage Change from Satellite and Surface Observations and Modeling." Journal of Hydrometeorology 11, no. 1 (February 1, 2010): 156–70. http://dx.doi.org/10.1175/2009jhm1152.1.

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Abstract Terrestrial water storage (TWS) is a fundamental component of the water cycle. On a regional scale, measurements of terrestrial water storage change (TWSC) are extremely scarce at any time scale. This study investigates the feasibility of estimating monthly-to-seasonal variations of regional TWSC from modeling and a combination of satellite and in situ surface observations based on water balance computations that use ground-based precipitation observations in both cases. The study area is the Klamath and Sacramento River drainage basins in the western United States (total area of about 110 000 km2). The TWSC from the satellite/surface observation–based estimates is compared with model results and land water storage from the Gravity Recovery and Climate Experiment (GRACE) data. The results show that long-term evapotranspiration estimates and runoff measurements generally balance with observed precipitation, suggesting that the evapotranspiration estimates have relatively small bias for long averaging times. Observations show that storage change in water management reservoirs is about 12% of the seasonal amplitude of the TWSC cycle, but it can be up to 30% at the subbasin scale. Comparing with predevelopment conditions, the satellite/surface observation–based estimates show larger evapotranspiration and smaller runoff than do modeling estimates, suggesting extensive anthropogenic alteration of TWSC in the study area. Comparison of satellite/surface observation–based and GRACE TWSC shows that the seasonal cycle of terrestrial water storage is substantially underestimated by GRACE.

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Qiao, Baojin, Bingkang Nie, Changmao Liang, Longwei Xiang, and Liping Zhu. "Spatial Difference of Terrestrial Water Storage Change and Lake Water Storage Change in the Inner Tibetan Plateau." Remote Sensing 13, no. 10 (May 19, 2021): 1984. http://dx.doi.org/10.3390/rs13101984.

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Water resources are rich on the Tibetan Plateau, with large amounts of glaciers, lakes, and permafrost. Terrestrial water storage (TWS) on the Tibetan Plateau has experienced a significant change in recent decades. However, there is a lack of research about the spatial difference between TWSC and lake water storage change (LWSC), which is helpful to understand the response of water storage to climate change. In this study, we estimate the change in TWS, lake water storage (LWS), soil moisture, and permafrost, respectively, according to satellite and model data during 2005−2013 in the inner Tibetan Plateau and glacial meltwater from previous literature. The results indicate a sizeable spatial difference between TWSC and LWSC. LWSC was mainly concentrated in the northeastern part (18.71 ± 1.35 Gt, 37.7% of the total) and southeastern part (22.68 ± 1.63 Gt, 45.6% of the total), but the increased TWS was mainly in the northeastern region (region B, 18.96 ± 1.26 Gt, 57%). Based on mass balance, LWSC was the primary cause of TWSC for the entire inner Tibetan Plateau. However, the TWS of the southeastern part increased by 3.97 ± 2.5 Gt, but LWS had increased by 22.68 ± 1.63 Gt, and groundwater had lost 16.91 ± 7.26 Gt. The increased TWS in the northeastern region was equivalent to the increased LWS, and groundwater had increased by 4.47 ± 4.87 Gt. Still, LWS only increased by 2.89 ± 0.21 Gt in the central part, and the increase in groundwater was the primary cause of TWSC. These results suggest that the primary cause of increased TWS shows a sizeable spatial difference. According to the water balance, an increase in precipitation was the primary cause of lake expansion for the entire inner Tibetan Plateau, which contributed 73% (36.28 Gt) to lake expansion (49.69 ± 3.58 Gt), and both glacial meltwater and permafrost degradation was 13.5%.

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Yin, Dongqin, and Michael L. Roderick. "Inter-annual variability of the global terrestrial water cycle." Hydrology and Earth System Sciences 24, no. 1 (January 24, 2020): 381–96. http://dx.doi.org/10.5194/hess-24-381-2020.

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Abstract. Variability of the terrestrial water cycle, i.e. precipitation (P), evapotranspiration (E), runoff (Q) and water storage change (ΔS) is the key to understanding hydro-climate extremes. However, a comprehensive global assessment for the partitioning of variability in P between E, Q and ΔS is still not available. In this study, we use the recently released global monthly hydrologic reanalysis product known as the Climate Data Record (CDR) to conduct an initial investigation of the inter-annual variability of the global terrestrial water cycle. We first examine global patterns in partitioning the long-term mean P‾ between the various sinks E‾, Q‾ and ΔS‾ and confirm the well-known patterns with P‾ partitioned between E‾ and Q‾ according to the aridity index. In a new analysis based on the concept of variability source and sinks we then examine how variability in the precipitation σP2 (the source) is partitioned between the three variability sinks σE2, σQ2 and σΔS2 along with the three relevant covariance terms, and how that partitioning varies with the aridity index. We find that the partitioning of inter-annual variability does not simply follow the mean state partitioning. Instead we find that σP2 is mostly partitioned between σQ2, σΔS2 and the associated covariances with limited partitioning to σE2. We also find that the magnitude of the covariance components can be large and often negative, indicating that variability in the sinks (e.g. σQ2, σΔS2) can, and regularly does, exceed variability in the source (σP2). Further investigations under extreme conditions revealed that in extremely dry environments the variance partitioning is closely related to the water storage capacity. With limited storage capacity the partitioning of σP2 is mostly to σE2, but as the storage capacity increases the partitioning of σP2 is increasingly shared between σE2, σΔS2 and the covariance between those variables. In other environments (i.e. extremely wet and semi-arid–semi-humid) the variance partitioning proved to be extremely complex and a synthesis has not been developed. We anticipate that a major scientific effort will be needed to develop a synthesis of hydrologic variability.

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Chen, Zheng, Wenjie Wang, Weiguo Jiang, Mingliang Gao, Beibei Zhao, and Yunwei Chen. "The Different Spatial and Temporal Variability of Terrestrial Water Storage in Major Grain-Producing Regions of China." Water 13, no. 8 (April 9, 2021): 1027. http://dx.doi.org/10.3390/w13081027.

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Irrigation is an important factor affecting the change of terrestrial water storage (TWS), especially in grain-producing areas. The Northeast China Plain (NECP), the Huang-Huai-Hai Plain (HHH) and the middle and lower reaches of the Yangtze River Basin Plain (YRB) are major grain-producing regions of China, with particular climate conditions, crops and irrigation schemes. However, there are few papers focusing on the different variation pattern of water storage between NECP, HHH and YRB. In this paper, the characteristics of terrestrial water storage anomaly (TWSA) and groundwater storage in the three regions mentioned above from 2003 to 2014 were analyzed, and the main reasons for water storage variations in the three regions were also discussed. The result shows that although effective irrigated areas increased in all three regions, TWSA only decreased in HHH and TWSA in the other two regions have shown an increasing trend. Spatially, the water storage deficit was more serious in middle and south NECP and HHH. In the three regions, water storage variations were impacted by meteorological condition and anthropogenic stress (e.g., irrigation). However, irrigation water consumption has a greater impact on water storage deficit in HHH than the other two regions, and water storage variation in YRB was mainly impacted by meteorological conditions. In this case, we suggest that the structure of agricultural planting in HHH should be adjusted to reduce the water consumption for irrigation.

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Wang, Xuanxuan, Liu Liu, Qiankun Niu, Hao Li, and Zongxue Xu. "Multiple Data Products Reveal Long-Term Variation Characteristics of Terrestrial Water Storage and Its Dominant Factors in Data-Scarce Alpine Regions." Remote Sensing 13, no. 12 (June 16, 2021): 2356. http://dx.doi.org/10.3390/rs13122356.

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As the “Water Tower of Asia” and “The Third Pole” of the world, the Qinghai–Tibet Plateau (QTP) shows great sensitivity to global climate change, and the change in its terrestrial water storage has become a focus of attention globally. Differences in multi-source data and different calculation methods have caused great uncertainty in the accurate estimation of terrestrial water storage. In this study, the Yarlung Zangbo River Basin (YZRB), located in the southeast of the QTP, was selected as the study area, with the aim of investigating the spatio-temporal variation characteristics of terrestrial water storage change (TWSC). Gravity Recovery and Climate Experiment (GRACE) data from 2003 to 2017, combined with the fifth-generation reanalysis product of the European Centre for Medium-Range Weather Forecasts (ERA5) data and Global Land Data Assimilation System (GLDAS) data, were adopted for the performance evaluation of TWSC estimation. Based on ERA5 and GLDAS, the terrestrial water balance method (PER) and the summation method (SS) were used to estimate terrestrial water storage, obtaining four sets of TWSC, which were compared with TWSC derived from GRACE. The results show that the TWSC estimated by the SS method based on GLDAS is most consistent with the results of GRACE. The time-lag effect was identified in the TWSC estimated by the PER method based on ERA5 and GLDAS, respectively, with 2-month and 3-month lags. Therefore, based on the GLDAS, the SS method was used to further explore the long-term temporal and spatial evolution of TWSC in the YZRB. During the period of 1948–2017, TWSC showed a significantly increasing trend; however, an abrupt change in TWSC was detected around 2002. That is, TWSC showed a significantly increasing trend before 2002 (slope = 0.0236 mm/month, p < 0.01) but a significantly decreasing trend (slope = −0.397 mm/month, p < 0.01) after 2002. Additional attribution analysis on the abrupt change in TWSC before and after 2002 was conducted, indicating that, compared with the snow water equivalent, the soil moisture dominated the long-term variation of TWSC. In terms of spatial distribution, TWSC showed a large spatial heterogeneity, mainly in the middle reaches with a high intensity of human activities and the Parlung Zangbo River Basin, distributed with great glaciers. The results obtained in this study can provide reliable data support and technical means for exploring the spatio-temporal evolution mechanism of terrestrial water storage in data-scarce alpine regions.

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Grigoriev, Vadim Yu, and Natalia L. Frolova. "TERRESTRIAL WATER STORAGE CHANGE OF EUROPEAN RUSSIA AND ITS IMPACT ON WATER BALANCE." GEOGRAPHY, ENVIRONMENT, SUSTAINABILITY 11, no. 1 (March 30, 2018): 38–50. http://dx.doi.org/10.24057/2071-9388-2018-11-1-38-50.

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Yılmaz, Yeliz, Kristoffer Aalstad, and Omer Sen. "Multiple Remotely Sensed Lines of Evidence for a Depleting Seasonal Snowpack in the Near East." Remote Sensing 11, no. 5 (February 26, 2019): 483. http://dx.doi.org/10.3390/rs11050483.

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The snow-fed river basins of the Near East region are facing an urgent threat in the form of declining water resources. In this study, we analyzed several remote sensing products (optical, passive microwave, and gravimetric) and outputs of a meteorological reanalysis data set to understand the relationship between the terrestrial water storage anomalies and the mountain snowpack. The results from different satellite retrievals show a clear signal of a depletion of both water storage and the seasonal snowpack in four basins in the region. We find a strong reduction in terrestrial water storage over the Gravity Recovery and Climate Experiment (GRACE) observational period, particularly over the higher elevations. Snow-cover duration estimates from Moderate Resolution Imaging Spectroradiometer (MODIS) products point towards negative and significant trends up to one month per decade in the current era. These numbers are a clear indicator of the partial disappearance of the seasonal snow-cover in the region which has been projected to occur by the end of the century. The spatial patterns of changes in the snow-cover duration are positively correlated with both GRACE terrestrial water storage decline and peak snow water equivalent (SWE) depletion from the ERA5 reanalysis. Possible drivers of the snowpack depletion are a significant reduction in the snowfall ratio and an earlier snowmelt. A continued depletion of the montane snowpack in the Near East paints a bleak picture for future water availability in this water-stressed region.

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Odinaev, Mirshakar, Zengyun Hu, Xi Chen, Min Mao, Zhuo Zhang, Hao Zhang, and Meijun Wang. "Dynamic Changes of Terrestrial Water Cycle Components over Central Asia in the Last Two Decades from 2003 to 2020." Remote Sensing 15, no. 13 (June 28, 2023): 3318. http://dx.doi.org/10.3390/rs15133318.

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The terrestrial water cycle is important for the arid regions of central Asia (CA). In this study, the spatiotemporal variations in the three climate variables [temperature (TMP), precipitation (PRE), and potential evapotranspiration (PET)] and terrestrial water cycle components [soil moisture (SM), snow water equivalent (SWE), runoff, terrestrial water storage (TWS), and groundwater storage (GWS)] of CA are comprehensively analyzed based on multiple datasets from 2003 to 2020. The major results are as follows: (1) Significant decreasing trends were observed for the TWS anomaly (TWSA) and GWS anomaly (GWSA) during 2003–2020, indicating serious water resource depletion. The annual linear trend values of TWSA and GWSA are −0.31 and −0.27 mm/a, respectively. The depletion centers are distributed over most areas of western and southern Kazakhstan (KAZ) and nearly all areas of Uzbekistan (UZB), Kyrgyzstan (KGZ), and Tajikistan (TJK). (2) TMP and PET have the largest significant negative impacts on SM and SWE. The PRE has a positive impact on terrestrial water variations. (3) During 1999–2019, water withdrawal did not significantly increase, whereas TWS showed a significant decreasing trend. Our results provide a comprehensive analysis of the basic TWS variation that plays a significant role in the water resource management of CA.

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Jiang, Dong, Jianhua Wang, Yaohuan Huang, Kang Zhou, Xiangyi Ding, and Jingying Fu. "The Review of GRACE Data Applications in Terrestrial Hydrology Monitoring." Advances in Meteorology 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/725131.

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The Gravity Recovery and Climate Experiment (GRACE) satellite provides a new method for terrestrial hydrology research, which can be used for improving the monitoring result of the spatial and temporal changes of water cycle at large scale quickly. The paper presents a review of recent applications of GRACE data in terrestrial hydrology monitoring. Firstly, the scientific GRACE dataset is briefly introduced. Recently main applications of GRACE data in terrestrial hydrological monitoring at large scale, including terrestrial water storage change evaluation, hydrological components of groundwater and evapotranspiration (ET) retrieving, droughts analysis, and glacier response of global change, are described. Both advantages and limitations of GRACE data applications are then discussed. Recommendations for further research of the terrestrial water monitoring based on GRACE data are also proposed.

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Zhang, Liangjing, Henryk Dobslaw, Tobias Stacke, Andreas Güntner, Robert Dill, and Maik Thomas. "Validation of terrestrial water storage variations as simulated by different global numerical models with GRACE satellite observations." Hydrology and Earth System Sciences 21, no. 2 (February 10, 2017): 821–37. http://dx.doi.org/10.5194/hess-21-821-2017.

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Abstract. Estimates of terrestrial water storage (TWS) variations from the Gravity Recovery and Climate Experiment (GRACE) satellite mission are used to assess the accuracy of four global numerical model realizations that simulate the continental branch of the global water cycle. Based on four different validation metrics, we demonstrate that for the 31 largest discharge basins worldwide all model runs agree with the observations to a very limited degree only, together with large spreads among the models themselves. Since we apply a common atmospheric forcing data set to all hydrological models considered, we conclude that those discrepancies are not entirely related to uncertainties in meteorologic input, but instead to the model structure and parametrization, and in particular to the representation of individual storage components with different spatial characteristics in each of the models. TWS as monitored by the GRACE mission is therefore a valuable validation data set for global numerical simulations of the terrestrial water storage since it is sensitive to very different model physics in individual basins, which offers helpful insight to modellers for the future improvement of large-scale numerical models of the global terrestrial water cycle.

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He, Panxing, Zongjiu Sun, Zhiming Han, Xiaoliang Ma, Pei Zhao, Yifei Liu, and Jun Ma. "Divergent Trends of Water Storage Observed via Gravity Satellite across Distinct Areas in China." Water 12, no. 10 (October 14, 2020): 2862. http://dx.doi.org/10.3390/w12102862.

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Knowledge of the spatiotemporal variations of terrestrial water storage (TWS) is critical for the sustainable management of water resources in China. However, this knowledge has not been quantified and compared for the different climate types and underlying surface characteristics. Here, we present observational evidence for the spatiotemporal dynamics of water storage based on the products from the Gravity Recovery and Climate Experiment (GRACE) and the Global Land Data Assimilation System (GLDAS) in China over 2003–2016. Our results were the following: (1) gravity satellite dataset showed divergent trends of TWS across distinct areas due to human factors and climate factors. The overall changing trend of water storage is that the north experiences a loss of water and the south gains in water, which aggravates the uneven spatial distribution of water resources in China. (2) In the eastern monsoon area, the depletion of water storage in North China (NC) was found to be mostly due to anthropogenic disturbance through groundwater pumping in plain areas. However, precipitation was shown to be a key driver for the increase of water storage in South China (SC). Increasing precipitation in SC was linked to atmospheric circulation enhancement and Pacific Ocean warming, meaning an unrecognized teleconnection between circulation anomalies and water storage. (3) At high altitudes in the west, the change of water storage was affected by the melting of ice and snow due to the rising temperatures, yet the topography determines the trend of water storage. We found that the mountainous terrain led to the loss of water storage in Tianshan Mountain (TSM), while the closed basin topography gathered the melted water in the interior of the Tibetan Plateau (ITP). This study highlights the impacts of the local climate and topography on terrestrial water storage, and has reference value for the government and the public to address the crisis of water resources in China.

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Li, Ya-wei, Yu-zhe Wang, Min Xu, and Shi-chang Kang. "Lake water storage change estimation and its linkage with terrestrial water storage change in the northeastern Tibetan Plateau." Journal of Mountain Science 18, no. 7 (July 2021): 1737–47. http://dx.doi.org/10.1007/s11629-020-6474-8.

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Nakaegawa, Tosiyuki, Keiko Yamamoto, Taichu Y. Tanaka, Takashi Hasegawa, and Yoichi Fukuda. "Investigation of temporal characteristics of terrestrial water storage changes and its comparison to terrestrial mass changes." Hydrological Processes 26, no. 16 (July 4, 2012): 2470–81. http://dx.doi.org/10.1002/hyp.9392.

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Muskett, Reginald R. "GRACE, the Chandler Wobble and Interpretations of Terrestrial Water Transient Storage." International Journal of Geosciences 12, no. 02 (2021): 102–20. http://dx.doi.org/10.4236/ijg.2021.122007.

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Chen, Ajiao, Huade Guan, and Okke Batelaan. "Non-linear interactions between vegetation and terrestrial water storage in Australia." Journal of Hydrology 613 (October 2022): 128336. http://dx.doi.org/10.1016/j.jhydrol.2022.128336.

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Sun, A. Y., J. Chen, and J. Donges. "Global terrestrial water storage connectivity revealed using complex climate network analyses." Nonlinear Processes in Geophysics 22, no. 4 (July 30, 2015): 433–46. http://dx.doi.org/10.5194/npg-22-433-2015.

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Abstract. Terrestrial water storage (TWS) exerts a key control in global water, energy, and biogeochemical cycles. Although certain causal relationship exists between precipitation and TWS, the latter quantity also reflects impacts of anthropogenic activities. Thus, quantification of the spatial patterns of TWS will not only help to understand feedbacks between climate dynamics and the hydrologic cycle, but also provide new insights and model calibration constraints for improving the current land surface models. This work is the first attempt to quantify the spatial connectivity of TWS using the complex network theory, which has received broad attention in the climate modeling community in recent years. Complex networks of TWS anomalies are built using two global TWS data sets, a remote sensing product that is obtained from the Gravity Recovery and Climate Experiment (GRACE) satellite mission, and a model-generated data set from the global land data assimilation system's NOAH model (GLDAS-NOAH). Both data sets have 1° × 1° grid resolutions and cover most global land areas except for permafrost regions. TWS networks are built by first quantifying pairwise correlation among all valid TWS anomaly time series, and then applying a cutoff threshold derived from the edge-density function to retain only the most important features in the network. Basinwise network connectivity maps are used to illuminate connectivity of individual river basins with other regions. The constructed network degree centrality maps show the TWS anomaly hotspots around the globe and the patterns are consistent with recent GRACE studies. Parallel analyses of networks constructed using the two data sets reveal that the GLDAS-NOAH model captures many of the spatial patterns shown by GRACE, although significant discrepancies exist in some regions. Thus, our results provide further measures for constraining the current land surface models, especially in data sparse regions.

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Sun, A. Y., J. Chen, and J. Donges. "Global terrestrial water storage connectivity revealed using complex climate network analyses." Nonlinear Processes in Geophysics Discussions 2, no. 2 (April 30, 2015): 781–809. http://dx.doi.org/10.5194/npgd-2-781-2015.

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Abstract. Terrestrial water storage (TWS) exerts a key control in global water, energy, and biogeochemical cycles. Although certain causal relationships exist between precipitation and TWS, the latter also reflects impacts of anthropogenic activities. Thus, quantification of the spatial patterns of TWS will not only help to understand feedbacks between climate dynamics and hydrologic cycle, but also provide new model calibration constraints for improving the current land surface models. In this work, the connectivity of TWS is quantified using the climate network theory, which has received broad attention in the climate modeling community in recent years. Complex networks of TWS anomalies are built using two global TWS datasets, a remote-sensing product that is obtained from the Gravity Recovery and Climate Experiment (GRACE) satellite mission, and a model-generated dataset from the global land data assimilation system's NOAH model (GLDAS-NOAH). Both datasets have 1 ° × 1 ° resolutions and cover most global land areas except for permafrost regions. TWS networks are built by first quantifying pairwise correlation among all valid TWS anomaly time series, and then applying a statistical cutoff threshold to retain only the most important features in the network. Basinwise network connectivity maps are used to illuminate connectivity of individual river basins with other regions. The constructed network degree centrality maps show TWS hotspots around the globe and the patterns are consistent with recent GRACE studies. Parallel analyses of networks constructed using the two datasets indicate that the GLDAS-NOAH model captures many of the spatial patterns shown by GRACE, although significant discrepancies exist in some regions. Thus, our results provide important insights for constraining land surface models, especially in data sparse regions.

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Zhang, Xu, Jinbao Li, Zifeng Wang, and Qianjin Dong. "Global hydroclimatic drivers of terrestrial water storage changes in different climates." CATENA 219 (December 2022): 106598. http://dx.doi.org/10.1016/j.catena.2022.106598.

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Phillips, T., R. S. Nerem, Baylor Fox-Kemper, J. S. Famiglietti, and B. Rajagopalan. "The influence of ENSO on global terrestrial water storage using GRACE." Geophysical Research Letters 39, no. 16 (August 25, 2012): n/a. http://dx.doi.org/10.1029/2012gl052495.

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Moiwo, Juana Paul, Fulu Tao, and Wenxi Lu. "Estimating soil moisture storage change using quasi-terrestrial water balance method." Agricultural Water Management 102, no. 1 (December 2011): 25–34. http://dx.doi.org/10.1016/j.agwat.2011.10.003.

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Xie, Yangyang, Shengzhi Huang, Saiyan Liu, Guoyong Leng, Jian Peng, Qiang Huang, and Pei Li. "GRACE-Based Terrestrial Water Storage in Northwest China: Changes and Causes." Remote Sensing 10, no. 7 (July 23, 2018): 1163. http://dx.doi.org/10.3390/rs10071163.

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Monitoring variations in terrestrial water storage (TWS) is of great significance for the management of water resources. However, it remains a challenge to continuously monitor TWS variations using in situ observations and hydrological models because of a limited number of gauge stations and the complicated spatial distribution characteristics of TWS. In contrast, the Gravity Recovery and Climate Experiment (GRACE) could overcome the aforementioned restrictions, providing a new reliable means of observing TWS variation. Thus, GRACE was employed to investigate TWS variations in Northwest China (NWC) between April 2002 and March 2016. Unlike previous studies, we focused on the interactions of multiple climatic and vegetational factors, and their combined effects on TWS variation. In addition, we also analyzed the relationship between TWS variations and socioeconomic water consumption. The results indicated that (i) TWS had obvious seasonal variations in NWC, and showed significant decreasing trends in most parts of NWC at the 95% confidence level; (ii) decreasing sunshine duration and wind speed resulted in an increase in TWS in Qinghai province, whereas the increasing air temperature, ameliorative vegetational coverage, and excessive groundwater withdrawal jointly led to a decrease in TWS in the other provinces of NWC; (iii) TWS variations in NWC had a good correlation with water storage variations in cascade reservoirs of the upper Yellow River; and (iv) the overall interactions between multiple climatic and vegetational factors were obvious, and the strong effects of some climatic and vegetational factors could mask the weak influences of other factors in TWS variations in NWC. Hence, it is necessary to focus on the interactions of multiple factors and their combined effects on TWS variations when exploring the causes of TWS variations.

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Jing, Wenlong, Ling Yao, Xiaodan Zhao, Pengyan Zhang, Yangxiaoyue Liu, Xiaolin Xia, Jia Song, Ji Yang, Yong Li, and Chenghu Zhou. "Understanding Terrestrial Water Storage Declining Trends in the Yellow River Basin." Journal of Geophysical Research: Atmospheres 124, no. 23 (December 15, 2019): 12963–84. http://dx.doi.org/10.1029/2019jd031432.

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Journal articles on the topic 'Terrestrial Water Storage'

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