scholarly journals GROUNDWATER STORAGE CHANGE ESTIMATION USING GRACE SATELLITE DATA IN INDUS BASIN

2020 ◽  
Vol 1 (1) ◽  
pp. 10-15
Author(s):  
Muhammad Salam ◽  
Muhammad Jehanzeb Masud Cheema ◽  
Wanchang Zhang ◽  
Saddam Hussain ◽  
Azeem Khan ◽  
...  
Keyword(s):  
Water Table ◽  
Land Surface ◽  
Large Scale ◽  
Water Storage ◽  
Indus Basin ◽  
Groundwater Storage ◽  
Grace Satellite ◽  
Over Exploitation ◽  
Flooding Events ◽  
Storage Change

Over exploitation of Ground Water (GW) has resulted in lowering of water table in the Indus Basin. While waterlogging, salinity and seawater intrusion has resulted in rising of water table in Indus Basin. The sparse piezometer network cannot provide sufficient data to map groundwater changes spatially. To estimate groundwater change in this region, data from Gravity Recovery and Climate Experiment (GRACE) satellite was used. GRACE measures (Total Water Storage) TWS and used to estimate groundwater storage change. Net change in storage of groundwater was estimated from the change in TWS by including the additional components such as Soil Moisture (SM), Surface water storage (Qs) and snowpack equivalent water (SWE). For the estimation of these components Global Land Data Assimilation system (GLDAS) Land Surface Models (LSMs) was used. Both GRACE and GLDAS produce results for the Indus Basin for the period of April 2010 to January 2017. The monitoring well water-level records from the Scarp Monitoring Organization (SMO) and the Punjab Irrigation and Drainage Authority (PIDA) from April 2009 to December 2016 were used. The groundwater results from different combinations of GRACE products GFZ (GeoforschungsZentrum Potsdam) CSR (Center for Space Research at University of Texas, Austin) JPL (Jet Propulsion Laboratory) and GLDAS LSMs (CLM, NOAH and VIC) are calibrated (April 2009-2014) and validated (April 2015-April 2016) with in-situ measurements. For yearly scale, their correlation coefficient reaches 0.71 with Nash-Sutcliffe Efficiency (NSE) 0.82. It was estimated that net loss in groundwater storage is at mean rate of 85.01 mm per year and 118,668.16 Km3 in the 7 year of study period (April 2010-Jan 2017). GRACE TWS data were also able to pick up the signals from the large-scale flooding events observed in 2010 and 2014. These flooding events played a significant role in the replenishment of the groundwater system in the Indus Basin. Our study indicates that the GRACE based estimation of groundwater storage changes is skillful enough to provide monthly updates on the trend of the groundwater storage changes for resource managers and policy makers of Indus Basin.

scholarly journals GROUNDWATER STORAGE CHANGE ESTIMATION USING GRACE SATELLITE DATA IN INDUS BASIN

2020 ◽  
Vol 1 (1) ◽  
pp. 13-18 ◽  
Author(s):  
Muhammad Salam ◽  
Muhammad Jehanzeb Masud Cheema ◽  
Wanchang Zhang ◽  
Saddam Hussain ◽  
Azeem Khan ◽  
...  
Keyword(s):  
Satellite Data ◽  
Indus Basin ◽  
Groundwater Storage ◽  
Grace Satellite ◽  
Storage Change

Estimating the water balance and uncertainty bounds in a highly groundwater-dependent and data-scarce areas: An example for the upper Citarum basin

2021 ◽  
Author(s):  
Steven Reinaldo Rusli ◽  
Albrecht Weerts ◽  
Victor Bense
Keyword(s):  
Water Balance ◽  
Water Storage ◽  
Total Water ◽  
Groundwater Abstraction ◽  
Water Balance Components ◽  
Groundwater Storage ◽  
Actual Evaporation ◽  
Basin Scale ◽  
Basin Water ◽  
Storage Change

<p>In this study, we estimate the water balance components of a highly groundwater-dependent and hydrological data-scarce basin of the upper reaches of the Citarum river in West Java, Indonesia. Firstly, we estimate the groundwater abstraction volumes based on population size and a review of literature (0.57mm/day). Estimates of other components like rainfall, actual evaporation, discharge, and total water storage changes are derived from global datasets and are simulated using a distributed hydrological wflow_sbm model which yields additional estimates of discharge, actual evaporation, and total water storage change. We compare each basin water balance estimate as well as quantify the uncertainty of some of the components using the Extended Triple Collocation (ETC) method.</p><p>The ETC application on four different rainfall estimates suggests a preference of using the CHIRPS product as the input to the water balance components estimates as it delivers the highest r<sup>2</sup>  and the lowest RMSE compared to three other sources. From the different data sources and results of the distributed hydrological modeling using CHIRPS as rainfall forcing, we estimate a positive groundwater storage change between 0.12 mm/day - 0.60 mm/day. These results are in agreement with groundwater storage change estimates based upon GRACE gravimetric satellite data, averaged at 0.25 mm/day. The positive groundwater storage change suggests sufficient groundwater recharge occurs compensating for groundwater abstraction. This conclusion seems in agreement with the observation since 2005, although measured in different magnitudes. To validate and narrow the estimated ranges of the basin water storage changes, a devoted groundwater model is necessary to be developed. The result shall also aid in assessing the current and future basin-scale groundwater level changes to support operational water management and policy in the Upper Citarum basin.</p>

scholarly journals Evaluation of Groundwater Storage Variations in Northern China Using GRACE Data

Geofluids ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Wenjie Yin ◽  
Litang Hu ◽  
Jiu Jimmy Jiao
Keyword(s):  
Land Surface ◽  
Snow Water Equivalent ◽  
Groundwater Resources ◽  
Dynamic Change ◽  
Northern China ◽  
Groundwater Storage ◽  
Grace Data ◽  
Depletion Rate ◽  
Terrestrial Water ◽  
Storage Change

Dynamic change of groundwater storage is one of the most important topics in the sustainable management of groundwater resources. Groundwater storage variations are firstly isolated from the terrestrial water storage change using the Global Land Data Assimilation System (GLDAS). Two datasets are used: (1) annual groundwater resources and (2) groundwater storage changes estimated from point-based groundwater level data in observation wells. Results show that the match between the GRACE-derived groundwater storage variations and annual water resources variation is not good in six river basins of Northern China. However, it is relatively good between yearly GRACE-derived groundwater storage data and groundwater storage change dataset in Huang-Huai-Hai Plain and the Song-Liao Plain. The mean annual depletion rate of groundwater storage in the Northern China was approximately 1.70 billion m3 yr−1 from 2003 to 2012. In terms of provinces, the yearly depletion rate is higher in Jing-Jin-Ji (Beijing, Tianjin, and Hebei province) and lowest in Henan province from 2003 to 2012, with the rate of 0.70 and 0.21 cm yr−1 Equivalent Water Height (EWH), respectively. Different land surface models suggest that the patterns from different models almost remain the same, and soil moisture variations are generally bigger than snow water equivalent variations.

scholarly journals Evaluation of Water Storage Change of Inland Cryosphere in Northwestern China

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Min Xu ◽  
Shichang Kang ◽  
Jiazhen Li
Keyword(s):  
Water Storage ◽  
Northwestern China ◽  
Satellite Mission ◽  
Pronounced Increase ◽  
The North ◽  
Gravity Fields ◽  
Grace Satellite ◽  
Gravity Recovery ◽  
Storage Change ◽  
Assimilation Model

The Gravity Recovery and Climate Experiment (GRACE) satellite mission provides measurements of Earth’s static and time-variable gravity fields with monthly resolution. In this study, changes of water storage in northwestern China were determined by GRACE monthly gravity field data obtained from 2003 to 2010. Comparisons of water storage change (WSC) simulated by a four-dimensional assimilation model (Noah) and observed by GRACE revealed similar patterns of change and a correlation coefficient of 0.71(P<0.05). Trend analysis indicated significant changes in the spatiotemporal variation of WSC in northwestern China during the 8-year study period, which were stronger in the east than in the west and more pronounced in the south than in the north. The most pronounced increase in water storage occurred in Gansu and Qinghai provinces, but, overall, water storage increased by 0.61 mm/a over northwestern China during the study period. Clear seasonal variations of WSC and precipitation were found, because glacial meltwater and precipitation are the main sources of water in the hydrosphere; meanwhile, the distributions of glaciers and permafrost also affect the spatial distribution of WSC.

scholarly journals Downscaling of GRACE-Derived Groundwater Storage Based on the Random Forest Model

2019 ◽  
Vol 11 (24) ◽  
pp. 2979 ◽  
Author(s):  
Li Chen ◽  
Qisheng He ◽  
Kun Liu ◽  
Jinyang Li ◽  
Chenlin Jing
Keyword(s):  
Random Forest ◽  
Spatial Resolution ◽  
Large Scale ◽  
Snow Water Equivalent ◽  
Water Storage ◽  
Research Area ◽  
Groundwater Storage ◽  
Coarse Spatial Resolution ◽  
Long Time ◽  
Local Water

Groundwater is an important part of water storage and one of the important sources of agricultural irrigation, urban living, and industrial water use. The recent launch of Gravity Recovery and Climate Experiment (GRACE) Satellite has provided a new way for studying large-scale water storage. The application of GRACE in local water resources has been greatly limited because of the coarse spatial resolution, and low temporal resolution. Therefore, it is of great significance to improve the spatial resolution of groundwater storage for regional water management. Based on the method of random forest (RF), this study combined six hydrological variables, including precipitation, evapotranspiration, runoff, soil moisture, snow water equivalent, and canopy water to conduct downscaling study, aiming at downscaling the resolution of the total water storage and groundwater storage from 1° (110 km) and to 0.25° (approximately 25 km). The results showed that, from the perspective of long time series, the prediction results of the RF model are ideal in the whole research area and the observations wells area. From the perspective of space, the detailed changes of water storage could be captured in greater detail after downscaling. The verification results show that, on the monthly scale and annual scale, the correlation between the downscaling results and the observation wells is 0.78 and 0.94, respectively, and they both reach the confidence level of 0.01. Therefore, the RF downscaling model has great potential for predicting groundwater storage.

Capturing watershed water balance with a physically-based two-hydrological-variable model: Application to the Little Washita basin

2021 ◽  
Author(s):  
Fanny Picourlat ◽  
Emmanuel Mouche ◽  
Claude Mugler
Keyword(s):  
Water Balance ◽  
Water Table ◽  
Land Surface ◽  
Large Scale ◽  
Three Dimensional ◽  
Hydrological Processes ◽  
Small Scale ◽  
Variable Model ◽  
Continental Hydrology ◽  
Hydrological Variable

&lt;p&gt;Hydrological processes import across scales is known to constitute a key challenge to improve their representation in large-scale land surface models. Since these models describe continental hydrology with vertical one dimensional infiltration and evapotranspiration, the challenge mainly resides in the dimensionality reduction of the processes. Departing from the catchment three-dimensional scale, previous work has shown that an equivalent two-dimensional hillslope model is able to simulate long term watershed water balance with good accuracy. This work has been done on the Little Washita basin (Ok, USA) using the integrated code HydroGeoSphere. Following this framework, we show that hillslope hydrology can be described by using realistic simplifying assumptions, such as linear water table profile. These assumptions allow the writing of an analytical model relying on two hydrological variables: the seepage face extension, which describe the intersection length between the water table and the land surface, and the water table slope. The last step of the work will be to use these key variables and this simplified description of the driving processes for importing small-scale hydrological processes into large-scale models.&lt;/p&gt;

Estimating Large-Scale Precipitation Minus Evapotranspiration from GRACE Satellite Gravity Measurements

2006 ◽  
Vol 7 (2) ◽  
pp. 252-270 ◽  
Author(s):  
Sean Swenson ◽  
John Wahr
Keyword(s):  
Land Surface ◽  
Seasonal Cycle ◽  
Large Scale ◽  
Gravity Data ◽  
Water Storage ◽  
Department Of Energy ◽  
Surface Model ◽  
Satellite Gravity ◽  
Discharge Data ◽  
Temporal Sampling

Abstract Currently, observations of key components of the earth's large-scale water and energy budgets are sparse or even nonexistent. One key component, precipitation minus evapotranspiration (P − ET), remains largely unmeasured due to the absence of observations of ET. Precipitation minus evapotranspiration describes the flux of water between the atmosphere and the earth's surface, and therefore provides important information regarding the interaction of the atmosphere with the land surface. In this paper, large-scale changes in continental water storage derived from satellite gravity data from the Gravity Recovery and Climate Experiment (GRACE) project are combined with river discharge data to obtain estimates of areally averaged P − ET. After constructing an equation describing the large-scale terrestrial water balance reflecting the temporal sampling of GRACE water storage estimates, GRACE-derived P − ET estimates are compared to those obtained from a reanalysis dataset [NCEP/Department of Energy (DOE) reanalysis-2] and a land surface model driven with observation-based forcing [Global Land Data Assimilation System (GLDAS)/Noah] for two large U.S. river basins. GRACE-derived P − ET compares quite favorably with the reanalysis-2 output, while P − ET from the Noah model shows significant differences. Because the uncertainties in the GRACE results can be computed rigorously, this comparison may be considered as a validation of the models. In addition to showing how GRACE P − ET estimates may be used to validate model output, the accuracy of GRACE estimates of both the seasonal cycle and the monthly averaged rate of P − ET is examined. Finally, the potential for estimating seasonal evapotranspiration is demonstrated by combining GRACE seasonal P − ET estimates with independent estimates of the seasonal cycle of precipitation.

scholarly journals Validation of terrestrial water storage variations as simulated by different global numerical models with GRACE satellite observations

2017 ◽  
Vol 21 (2) ◽  
pp. 821-837 ◽  
Author(s):  
Liangjing Zhang ◽  
Henryk Dobslaw ◽  
Tobias Stacke ◽  
Andreas Güntner ◽  
Robert Dill ◽  
...  
Keyword(s):  
Large Scale ◽  
Water Cycle ◽  
Numerical Models ◽  
Water Storage ◽  
Terrestrial Water Storage ◽  
Satellite Mission ◽  
Validation Data ◽  
Data Set ◽  
Terrestrial Water ◽  
Grace Satellite

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.

scholarly journals Representation of Water Table Dynamics in a Land Surface Scheme. Part II: Subgrid Variability

2005 ◽  
Vol 18 (12) ◽  
pp. 1881-1901 ◽  
Author(s):  
Pat J-F. Yeh ◽  
Elfatih A. B. Eltahir
Keyword(s):  
Groundwater Recharge ◽  
Water Table ◽  
Land Surface ◽  
Large Scale ◽  
Climate Models ◽  
Land Surface Scheme ◽  
Groundwater Runoff ◽  
Aquifer Storage ◽  
Mosaic Approach ◽  
Surface Scheme

Abstract A lumped unconfined aquifer model has been developed and interactively coupled to a land surface scheme in a companion paper. Here, the issue of the representation of subgrid variability of water table depths (WTDs) is addressed. A statistical–dynamical (SD) approach is used to account for the effects of the unresolved subgrid variability of WTD in the grid-scale groundwater runoff. The dynamic probability distribution function (PDF) of WTD is specified as a two-parameter gamma distribution based on observations. The grid-scale groundwater rating curve (i.e., aquifer storage–discharge relationship) is derived statistically by integrating a point groundwater runoff model with respect to the PDF of WTD. Next, a mosaic approach is utilized to account for the effects of subgrid variability of WTD in the grid-scale groundwater recharge. A grid cell is categorized into different subgrids based on the PDF of WTD. The grid-scale hydrologic fluxes are computed by averaging all of the subgrid fluxes weighted by their fractions. This new methodology combines the strengths of the SD approach and the mosaic approach. The results of model testing in Illinois from 1984 to 1994 indicate that the simulated hydrologic variables (soil saturation and WTD) and fluxes (evaporation, runoff, and groundwater recharge) agree well with the observations. Because of the paucity of the large-scale observations on WTD, the development of a practical parameter estimation procedure is indispensable before the global implementation of the developed scheme of water table dynamics in climate models.

scholarly journals The Review of GRACE Data Applications in Terrestrial Hydrology Monitoring

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Dong Jiang ◽  
Jianhua Wang ◽  
Yaohuan Huang ◽  
Kang Zhou ◽  
Xiangyi Ding ◽  
...  
Keyword(s):  
Large Scale ◽  
Water Cycle ◽  
Grace Data ◽  
Monitoring Result ◽  
Terrestrial Water ◽  
Terrestrial Hydrology ◽  
Grace Satellite ◽  
Gravity Recovery ◽  
Storage Change ◽  
Hydrological Monitoring

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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