scholarly journals Monitoring Terrestrial Water Storage Changes with the Tongji-Grace2018 Model in the Nine Major River Basins of the Chinese Mainland

2021 ◽  
Vol 13 (9) ◽  
pp. 1851
Author(s):  
Zhiwei Chen ◽  
Xingfu Zhang ◽  
Jianhua Chen

Data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission can be used to monitor changes in terrestrial water storage (TWS). In this study, we exploit the TWS observations from a new temporal gravity field model, Tongji-Grace2018, which was developed using an optimized short-arc approach at Tongji University. We analyzed the changes in the TWS and groundwater storage (GWS) in each of the nine major river basins of the Chinese mainland from April 2002 to August 2016, using Tongji-Grace2018, the Global Land Data Assimilation System (GLDAS) hydrological model, in situ observations, and additional auxiliary data (such as precipitation and temperature). Our results indicate that the TWS of the Songliao, Yangtze, Pearl, and Southeastern River Basins are all increasing, with the most drastic TWS growth occurring in the Southeastern River Basin. The TWS of the Yellow, Haihe, Huaihe, and Southwestern River Basins are all decreasing, with the most drastic TWS loss occurring in the Haihe River Basin. The Continental River Basin TWS has remained largely unchanged over time. With the exception of the Songliao and Pearl River Basins, the GWS results produced by the Tongji-Grace2018 model are consistent with the in situ observations of these basins. The correlation coefficients for the Tongji-Grace2018 model results and the in situ observations for the Yellow, Huaihe, Yangtze, Southwestern, and Continental River Basins are higher than 0.710. Overall, the GWS results for the Songliao, Yellow, Haihe, Huaihe, Southwestern, and Continental River Basins all exhibit a downward trend, with the most severe groundwater loss occurring in the Haihe and Huaihe River Basins. However, the Yangtze and Southeastern River Basins both have upward-trending modeled and measured GWS values. This study demonstrates the effectiveness of the Tongji-Grace2018 model for the reliable estimation of TWS and GWS changes on the Chinese mainland, and may contribute to the management of available water resources.

2020 ◽  
Author(s):  
Juan F. Salazar ◽  
Silvana Bolaños ◽  
Estiven Rodríguez ◽  
Teresita Betancur ◽  
Juan Camilo Villegas ◽  
...  

<p>Many natural and social phenomena depend on the regulation of river flow regimes. Regulation is defined here as the capacity of river basins to attenuate extreme flows, which includes the capacity to enhance low flows during dry periods of time. This capacity depends on how basins store and release water through time, which in turn depends on manifold processes that can be highly dynamic and sensitive to global change. Here we focus on the Magdalena river basin in northwestern South America, which is critical for water and energy security in Colombia, and has experienced water scarcity problems in the past, including the collapse of the national hydropower system due to El Niño 1991-1992. In this basin we study the evolution of regulation and related processes from two perspectives. First, we present a widely applicable conceptual framework that is based on the scaling theory and allows assessing the evolution of regulation in river basins, and use this framework to show how the Magdalena basin’s regulation capacity has been changing in recent decades. Second, we use data from the GRACE mission to investigate variations in water storage in the basin, and identify recent decreasing trends in both terrestrial water storage and groundwater storage. Further we show that temporal and spatial patterns of water storage depletion are likely related to the occurrence of ENSO extremes and pronounced differences between the lower and higher parts of the basin, including the presence of major wetland systems in the low lands and Andean mountains in the high lands. Our results provide insights on how to assess and monitor regulation in river basins, as well as on how this regulation relates to the dynamics of low flows and water storage, and therefore to potential water scarcity problems.</p>


2006 ◽  
Vol 7 (1) ◽  
pp. 39-60 ◽  
Author(s):  
Martin Hirschi ◽  
Sonia I. Seneviratne ◽  
Christoph Schär

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.


2021 ◽  
Vol 3 (5) ◽  
Author(s):  
Dostdar Hussain ◽  
Aftab Ahmed Khan ◽  
Syed Najam Ul Hassan ◽  
Syed Ali Asad Naqvi ◽  
Akhtar Jamil

AbstractMountains regions like Gilgit-Baltistan (GB) province of Pakistan are solely dependent on seasonal snow and glacier melt. In Indus basin which forms in GB, there is a need to manage water in a sustainable way for the livelihood and economic activities of the downstream population. It is important to monitor water resources that include glaciers, snow-covered area, lakes, etc., besides traditional hydrological (point-based measurements by using the gauging station) and remote sensing-based studies (traditional satellite-based observations provide terrestrial water storage (TWS) change within few centimeters from the earth’s surface); the TWS anomalies (TWSA) for the GB region are not investigated. In this study, the TWSA in GB region is considered for the period of 13 years (from January 2003 to December 2016). Gravity Recovery and Climate Experiment (GRACE) level 2 monthly data from three processing centers, namely Centre for Space Research (CSR), German Research Center for Geosciences (GFZ), and Jet Propulsion Laboratory (JPL), System Global Land Data Assimilation System (GLDAS)-driven Noah model, and in situ precipitation data from weather stations, were used for the study investigation. GRACE can help to forecast the possible trends of increasing or decreasing TWS with high accuracy as compared to the past studies, which do not use satellite gravity data. Our results indicate that TWS shows a decreasing trend estimated by GRACE (CSR, GFZ, and JPL) and GLDAS-Noah model, but the trend is not significant statistically. The annual amplitude of GLDAS-Noah is greater than GRACE signal. Mean monthly analysis of TWSA indicates that TWS reaches its maximum in April, while it reaches its minimum in October. Furthermore, Spearman’s rank correlation is determined between GRACE estimated TWS with precipitation, soil moisture (SM) and snow water equivalent (SWE). We also assess the factors, SM and SWE which are the most efficient parameters producing GRACE TWS signal in the study area. In future, our results with the support of more in situ data can be helpful for conservation of natural resources and to manage flood hazards, droughts, and water distribution for the mountain regions.


2013 ◽  
Vol 17 (5) ◽  
pp. 1985-2000 ◽  
Author(s):  
Y. Huang ◽  
M. S. Salama ◽  
M. S. Krol ◽  
R. van der Velde ◽  
A. Y. Hoekstra ◽  
...  

Abstract. In this study, we analyze 32 yr of terrestrial water storage (TWS) data obtained from the Interim Reanalysis Data (ERA-Interim) and Noah model from the Global Land Data Assimilation System (GLDAS-Noah) for the period 1979 to 2010. The accuracy of these datasets is validated using 26 yr (1979–2004) of runoff data from the Yichang gauging station and comparing them with 32 yr of independent precipitation data obtained from the Global Precipitation Climatology Centre Full Data Reanalysis Version 6 (GPCC) and NOAA's PRECipitation REConstruction over Land (PREC/L). Spatial and temporal analysis of the TWS data shows that TWS in the Yangtze River basin has decreased significantly since the year 1998. The driest period in the basin occurred between 2005 and 2010, and particularly in the middle and lower Yangtze reaches. The TWS figures changed abruptly to persistently high negative anomalies in the middle and lower Yangtze reaches in 2004. The year 2006 is identified as major inflection point, at which the system starts exhibiting a persistent decrease in TWS. Comparing these TWS trends with independent precipitation datasets shows that the recent decrease in TWS can be attributed mainly to a decrease in the amount of precipitation. Our findings are based on observations and modeling datasets and confirm previous results based on gauging station datasets.


2017 ◽  
Vol 21 (9) ◽  
pp. 4533-4549 ◽  
Author(s):  
Mohammad Shamsudduha ◽  
Richard G. Taylor ◽  
Darren Jones ◽  
Laurent Longuevergne ◽  
Michael Owor ◽  
...  

Abstract. GRACE (Gravity Recovery and Climate Experiment) satellite data monitor large-scale changes in total terrestrial water storage (ΔTWS), providing an invaluable tool where in situ observations are limited. Substantial uncertainty remains, however, in the amplitude of GRACE gravity signals and the disaggregation of TWS into individual terrestrial water stores (e.g. groundwater storage). Here, we test the phase and amplitude of three GRACE ΔTWS signals from five commonly used gridded products (i.e. NASA's GRCTellus: CSR, JPL, GFZ; JPL-Mascons; GRGS GRACE) using in situ data and modelled soil moisture from the Global Land Data Assimilation System (GLDAS) in two sub-basins (LVB: Lake Victoria Basin; LKB: Lake Kyoga Basin) of the Upper Nile Basin. The analysis extends from January 2003 to December 2012, but focuses on a large and accurately observed reduction in ΔTWS of 83 km3 from 2003 to 2006 in the Lake Victoria Basin. We reveal substantial variability in current GRACE products to quantify the reduction of ΔTWS in Lake Victoria that ranges from 80 km3 (JPL-Mascons) to 69 and 31 km3 for GRGS and GRCTellus respectively. Representation of the phase in TWS in the Upper Nile Basin by GRACE products varies but is generally robust with GRGS, JPL-Mascons, and GRCTellus (ensemble mean of CSR, JPL, and GFZ time-series data), explaining 90, 84, and 75 % of the variance respectively in "in situ" or "bottom-up" ΔTWS in the LVB. Resolution of changes in groundwater storage (ΔGWS) from GRACE ΔTWS is greatly constrained by both uncertainty in changes in soil-moisture storage (ΔSMS) modelled by GLDAS LSMs (CLM, NOAH, VIC) and the low annual amplitudes in ΔGWS (e.g. 1.8–4.9 cm) observed in deeply weathered crystalline rocks underlying the Upper Nile Basin. Our study highlights the substantial uncertainty in the amplitude of ΔTWS that can result from different data-processing strategies in commonly used, gridded GRACE products; this uncertainty is disregarded in analyses of ΔTWS and individual stores applying a single GRACE product.


Author(s):  
Emad Hasan ◽  
Aondover Tarhule

GRACE-derived Terrestrial Water Storage Anomalies (TWSA) continue to be used in an expanding array of studies to analyze numerous processes and phenomena related to terrestrial water storage dynamics, including groundwater depletions, lake storage variations, snow, and glacial mass changes, as well as floods, droughts, among others. So far, however, few studies have investigated how the factors that affect total water storage (e.g., precipitation, runoff, soil moisture, evapotranspiration) interact and combine over space and time to produce the mass variations that GRACE detects. This paper is an attempt to fill that gap and stimulate needed research in this area. Using the Nile River Basin as case study, it explicitly analyzes nine hydroclimatic and anthropogenic processes, as well as their relationship to TWS in different climatic zones in the Nile River Basin. The analytic method employed the trends in both the dependent and independent variables applying two geographically multiple regression (GMR) approaches: (i) an unweighted or ordinary least square regression (OLS) model in which the contributions of all variables to TWS variability are deemed equal at all locations; and (ii) a geographically weighted regression (GWR) which assigns a weight to each variable at different locations based on the occurrence of trend clusters, determined by Moran’s cluster index. In both cases, model efficacy was investigated using standard goodness of fit diagnostics. The OLS showed that trends in five variables (i.e., precipitation, runoff, surface water soil moisture, and population density) significantly (p<0.0001) explain the trends in TWSA for the basin at large. However, the models R2 value is only 0.14. In contrast, the GWR produced R2 values ranging between 0.40 and 0.89, with an average of 0.86 and normally distributed standard residuals. The models retained in the GWR differ by climatic zone. The results showed that all nine variables contribute significantly to the trend in TWS in the Tropical region; population density is an important contributor to TWSA variability in all zones; ET and Population density are the only significant variables in the semiarid zone. This type of information is critical for developing robust statistical models for reconstructing time series of proxy GRACE anomalies that predate the launch of the GRACE mission and for gap-filling between GRACE and GRACE-FO.


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