scholarly journals Improving the Resolution of GRACE Data for Spatio-Temporal Groundwater Storage Assessment

2021 ◽  
Vol 13 (17) ◽  
pp. 3513
Author(s):  
Shoaib Ali ◽  
Dong Liu ◽  
Qiang Fu ◽  
Muhammad Jehanzeb Masud Cheema ◽  
Quoc Bao Pham ◽  
...  
Keyword(s):  
Spatial Scale ◽  
Regional Scale ◽  
Water Storage ◽  
Slope Aspect ◽  
Small Scale ◽  
Ann Model ◽  
Groundwater Storage ◽  
Large Spatial Scale ◽  
Grace Data ◽  
Hydrological Variables

Groundwater has a significant contribution to water storage and is considered to be one of the sources for agricultural irrigation; industrial; and domestic water use. The Gravity Recovery and Climate Experiment (GRACE) satellite provides a unique opportunity to evaluate terrestrial water storage (TWS) and groundwater storage (GWS) at a large spatial scale. However; the coarse resolution of GRACE limits its ability to investigate the water storage change at a small scale. It is; therefore; needed to improve the resolution of GRACE data at a spatial scale applicable for regional-level studies. In this study; a machine-learning-based downscaling random forest model (RFM) and artificial neural network (ANN) model were developed to downscale GRACE data (TWS and GWS) from 1° to a higher resolution (0.25°). The spatial maps of downscaled TWS and GWS were generated over the Indus basin irrigation system (IBIS). Variations in TWS of GRACE in combination with geospatial variables; including digital elevation model (DEM), slope; aspect; and hydrological variables; including soil moisture; evapotranspiration; rainfall; surface runoff; canopy water; and temperature; were used. The geospatial and hydrological variables could potentially contribute to; or correlate with; GRACE TWS. The RFM outperformed the ANN model and results show Pearson correlation coefficient (R) (0.97), root mean square error (RMSE) (11.83 mm), mean absolute error (MAE) (7.71 mm), and Nash–Sutcliffe efficiency (NSE) (0.94) while comparing with the training dataset from 2003 to 2016. These results indicate the suitability of RFM to downscale GRACE data at a regional scale. The downscaled GWS data were analyzed; and we observed that the region has lost GWS of about −9.54 ± 1.27 km3 at the rate of −0.68 ± 0.09 km3/year from 2003 to 2016. The validation results showed that R between downscaled GWS and observational wells GWS are 0.67 and 0.77 at seasonal and annual scales with a confidence level of 95%, respectively. It can; therefore; be concluded that the RFM has the potential to downscale GRACE data at a spatial scale suitable to predict GWS at regional scales.

scholarly journals Improved Understanding of Groundwater Storage Changes under the Influence of River Basin Governance in Northwestern China Using GRACE Data

2021 ◽  
Vol 13 (14) ◽  
pp. 2672
Author(s):  
Xin Liu ◽  
Litang Hu ◽  
Kangning Sun ◽  
Zhengqiu Yang ◽  
Jianchong Sun ◽  
...  
Keyword(s):  
River Basin ◽  
Groundwater Level ◽  
Regional Scale ◽  
Water Storage ◽  
Northwestern China ◽  
In Situ Observation ◽  
Observation Data ◽  
Groundwater Storage ◽  
Grace Data

Groundwater is crucial for economic development in arid and semiarid areas. The Shiyang River Basin (SRB) has the most prominent water use issues in northwestern China, and overexploited groundwater resources have led to continuous groundwater-level decline. The key governance planning project of the SRB was issued in 2007. This paper synthetically combines remote-sensing data from Gravity Recovery and Climate Experiment (GRACE) data and precipitation, actual evapotranspiration, land use, and in situ groundwater-level data to evaluate groundwater storage variations on a regional scale. Terrestrial water storage anomalies (TWSA) and groundwater storage anomalies (GWSA), in addition to their influencing factors in the SRB since the implementation of the key governance project, are analyzed in order to evaluate the effect of governance. The results show that GRACE-derived GWS variations are consistent with in situ observation data in the basin, with a correlation coefficient of 0.68. The GWS in the SRB had a slow downward trend from 2003 to 2016, and this increased by 0.38 billion m³/year after 2018. As the meteorological data did not change significantly, the changes in water storage are mainly caused by human activities, which are estimated by using the principle of water balance. The decline in GWS in the middle and lower reaches of the SRB has been curbed since 2009 and has gradually rebounded since 2014. GWS decreased by 2.2 mm EWH (equivalent water height) from 2011 to 2016, which was 91% lower than that from 2007 to 2010. The cropland area in the middle and lower reaches of the SRB also stopped increasing after 2011 and gradually decreased after 2014, while the area of natural vegetation gradually increased, indicating that the groundwater level and associated ecology significantly recovered after the implementation of the project.

scholarly journals Interpretation of GRACE data of the Nile Basin using a groundwater recharge model

2010 ◽  
Vol 7 (4) ◽  
pp. 4501-4533 ◽  
Author(s):  
H. C. Bonsor ◽  
M. M. Mansour ◽  
A. M. MacDonald ◽  
A. G. Hughes ◽  
R. G. Hipkin ◽  
...  
Keyword(s):  
Groundwater Recharge ◽  
Water Mass ◽  
Regional Scale ◽  
Water Storage ◽  
Terrestrial Water Storage ◽  
Nile Basin ◽  
Groundwater Storage ◽  
Grace Data ◽  
Terrestrial Water ◽  
Annual Water

Abstract. Assessing and quantifying natural water storage is becoming increasingly important as nations develop strategies for economic growth and adaptations measures for climate change. The Gravity Recovery and Climate Experiment (GRACE) data provide a new opportunity to gain a direct and independent measure of water mass variations on a regional scale. Hydrological models are required to interpret these mass variations and partition them between different parts of the hydrological cycle, but groundwater storage has generally been poorly constrained by such models. This study focused on the Nile basin, and used a groundwater recharge model ZOODRM (Zoomable Object Oriented Distributed Recharge Model) to help interpret the seasonal variation in terrestrial water storage indicated by GRACE. The recharge model was constructed using almost entirely remotely sensed input data and calibrated to observed hydrological data from the Nile. GRACE data for the Nile Basin indicates an annual terrestrial water storage of approximately 200 km3: water input is from rainfall, and much of this water is evaporated within the basin since average annual outflow of the Nile is less than 30 km3. Total annual recharge simulated by ZOODRM is 400 km3/yr; 0–50 mm/yr within the semi arid lower catchments, and a mean of 250 mm/yr in the sub-tropical upper catchments. These results are comparable to the few site specific studies of recharge in the basin. Accounting for year-round discharge of groundwater, the seasonal groundwater storage is 100–150 km3/yr and seasonal change in soil moisture, 30 km3/yr. Together, they account for between 50 and 90% of the annual water storage in the catchment. The annual water mass variation (200 km3/yr) is an order of magnitude smaller than the rainfall input into the catchment (2000 km3/yr), which could be consistent with a high degree of moisture recycling within the basin. Future work is required to advance the calibration of the ZOODRM model, particularly improving the timing of runoff routing.

scholarly journals Calibration and evaluation of a semi-distributed watershed model of Sub-Saharan Africa using GRACE data

2012 ◽  
Vol 16 (9) ◽  
pp. 3083-3099 ◽  
Author(s):  
H. Xie ◽  
L. Longuevergne ◽  
C. Ringler ◽  
B. R. Scanlon
Keyword(s):  
Regional Scale ◽  
Water Storage ◽  
Hydrologic Model ◽  
Sub Saharan Africa ◽  
Model Parameters ◽  
Total Water ◽  
Discharge Data ◽  
Model Based ◽  
Grace Data ◽  
Sub Saharan

Abstract. Irrigation development is rapidly expanding in mostly rainfed Sub-Saharan Africa. This expansion underscores the need for a more comprehensive understanding of water resources beyond surface water. Gravity Recovery and Climate Experiment (GRACE) satellites provide valuable information on spatio-temporal variability in water storage. The objective of this study was to calibrate and evaluate a semi-distributed regional-scale hydrologic model based on the Soil and Water Assessment Tool (SWAT) code for basins in Sub-Saharan Africa using seven-year (July 2002–April 2009) 10-day GRACE data and multi-site river discharge data. The analysis was conducted in a multi-criteria framework. In spite of the uncertainty arising from the tradeoff in optimising model parameters with respect to two non-commensurable criteria defined for two fluxes, SWAT was found to perform well in simulating total water storage variability in most areas of Sub-Saharan Africa, which have semi-arid and sub-humid climates, and that among various water storages represented in SWAT, water storage variations in soil, vadose zone and groundwater are dominant. The study also showed that the simulated total water storage variations tend to have less agreement with GRACE data in arid and equatorial humid regions, and model-based partitioning of total water storage variations into different water storage compartments may be highly uncertain. Thus, future work will be needed for model enhancement in these areas with inferior model fit and for uncertainty reduction in component-wise estimation of water storage variations.

Small spatial scale effects of wave action exposure on morphological traits of the limpet Lottia subrugosa

2019 ◽  
Vol 99 (06) ◽  
pp. 1309-1315
Author(s):  
Edson A. Vieira ◽  
Marília Bueno
Keyword(s):  
Spatial Scale ◽  
Scale Effects ◽  
Spatial Scales ◽  
Wave Exposure ◽  
Wave Action ◽  
Shell Shape ◽  
Small Scale ◽  
Small Spatial Scale ◽  
Large Spatial Scale ◽  
Exposed Shore

AbstractMany studies have already assessed how wave action may affect morphology of intertidal species among sites that vary in wave exposure, but few attempted to look to this issue in smaller scales. Using the most common limpet of the Brazilian coast, Lottia subrugosa, and assuming position on rocky boulders as a proxy for wave action at small scale, we tested the hypothesis that waves may also influence limpet morphology at a smaller spatial scale by investigating how individual size, foot area and shell shape vary between sheltered and exposed boulder sides on three shores in the coast of Ubatuba, Brazil. Limpets consistently showed a proportionally larger foot on exposed boulder sides for all shores, indicating that stronger attachment is an important mechanism to deal with wave action dislodgement at a smaller scale. Shell shape also varied in the scale investigated here, with more conical (dissipative) shells occurring in exposed boulder sides in one exposed shore across time and in the other exposed shore in one year. Shell shape did not vary regarding boulder sides across time in the most sheltered shore. Although we did not assess large spatial scale effects of wave action in this study, variations of the effect of waves at small spatial scale observed for shell shape suggest that it may be modulated by the local wave exposure regime. Our work highlights the importance of wave action at small spatial scales, and may help to understand the ecological variability of limpets inhabiting rocky shores.

Assessing Impacts of Climate Extremes and Human Water Use on GRACE Total Water Storage Trends in Major U.S. Aquifers

2020 ◽  
Author(s):  
Bridget Scanlon ◽  
Ashraf Rateb ◽  
Alexander Sun ◽  
Himanshu Save
Keyword(s):  
Surface Water ◽  
Water Use ◽  
Groundwater Level ◽  
Water Storage ◽  
Climate Extremes ◽  
High Plains ◽  
Total Water ◽  
Groundwater Storage ◽  
Grace Data ◽  
The U.S

<p>There is considerable concern about water depletion caused by climate extremes (e.g., drought) and human water use in the U.S. and globally. Major U.S. aquifers provide an ideal laboratory to assess water storage changes from GRACE satellites because the aquifers are intensively monitored and modeled. The objective of this study was to assess the relative importance of climate extremes and human water use on GRACE Total Water Storage Anomalies in 14 major U.S. aquifers and to evaluate the reliability of the GRACE data by comparing with groundwater level monitoring (~-23,000 wells) and regional and global models. We quantified total water and groundwater storage anomalies over 2002 – 2017 from GRACE satellites and compared GRACE data with groundwater level monitoring and regional and global modeling results.  </p> <p>The results show that water storage changes were controlled primarily by climate extremes and amplified or dampened by human water use, primarily irrigation. The results were somewhat surprising, with stable or rising long-term trends in the majority of aquifers with large scale depletion limited to agricultural areas in the semi-arid southwest and southcentral U.S. GRACE total water storage in the California Central Valley and Central/Southern High Plains aquifers was depleted by drought and amplified by groundwater irrigation, totaling ~70 km<sup>3</sup> (2002–2017), about 2× the capacity of Lake Mead, the largest surface reservoir in the U.S. In the Pacific Northwest and Northern High Plains aquifers, lower drought intensities were partially dampened by conjunctive use of surface water and groundwater for irrigation and managed aquifer recharge, increasing water storage by up to 22 km<sup>3</sup> in the Northern High Plains over the 15 yr period. GRACE-derived total water storage changes in the remaining aquifers were stable or slightly rising throughout the rest of the U.S.</p> <p>GRACE data compared favorably with composite groundwater level hydrographs for most aquifers except for those with very low signals, indicating that GRACE tracks groundwater storage dynamics. Comparison with regional models was restricted to the limited overlap periods but showed good correspondence for modeled aquifers with the exception of the Mississippi Embayment, where the modeled trend is 4x the GRACE trend. The discrepancy is attributed to uncertainties in model storage parameters and groundwater/surface water interactions. Global hydrologic models (WGHM-2d and PCR-GLOBWB-5.0 overestimated trends in groundwater storage in heavily exploited aquifers in the southwestern and southcentral U.S. Land surface models (CLSM-F2.5 and NOAH-MP) seem to track GRACE TWSAs better than global hydrologic models but underestimated TWS trends in aquifers dominated by irrigation.</p> <p>Intercomparing GRACE, traditional hydrologic monitoring, and modeling data underscore the importance of considering all data sources to constrain water storage changes.  GRACE satellite data have critical implications for many nationally important aquifers, highlighting the importance of conjunctively using surface-water and groundwater and managed aquifer recharge to enhance sustainable development.</p>

scholarly journals Towards a Wave Theory Interpretation of Time-Distance Helioseismology Data

2001 ◽  
Vol 203 ◽  
pp. 180-182
Author(s):  
A. C. Birch ◽  
A. G. Kosovichev
Keyword(s):  
Spatial Scale ◽  
Born Approximation ◽  
Acoustic Waves ◽  
Sound Speed ◽  
Large Scale ◽  
Small Scale ◽  
Ray Theory ◽  
Travel Times ◽  
Large Spatial Scale ◽  
Time Distance

Time-distance helioseismology, which measures the time for acoustic waves to travel between points on the solar surface, has been used to study small-scale three-dimensional features in the sun, for example active regions, as well as large-scale features, such as meridional flow, that are not accessible by standard global helioseismology. Traditionally, travel times have been interpreted using geometrical ray theory, which is not always a good approximation. In order to develop a wave interpretation of time-distance data we employ the first Born approximation, which takes into account finite-wavelength effects and is expected to provide more accurate inversion results. In the Born approximation, in contrast with ray theory, travel times are sensitive to perturbations to sound speed which are located off the ray path. In an example calculation of travel time perturbations due to sound speed perturbations that are functions only of depth, we see that that the Born and ray approximations agree when applied to perturbations with large spatial scale and that the ray approximation fails when applied to perturbations with small spatial scale.

Exploring meso-scale soil water and groundwater storage changes within the USA through a Bayesian combination of GRACE data with monthly 12.5 km model simulations

2020 ◽  
Author(s):  
Nooshin Mehrnegar ◽  
Owen Jones ◽  
Michael B. Singer ◽  
Maike Schumacher ◽  
Thomas Jagdhuber ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Soil Water ◽  
Water Storage ◽  
Balance Model ◽  
Soil Water Storage ◽  
Groundwater Storage ◽  
In Situ Data ◽  
Grace Data ◽  
The Usa

<p>Climatic changes in precipitation intensity across the United States (USA) may also affect the frequency and magnitude of drought and flooding events, with potentially serious consequences for water supply across this country. Reliable estimation of water storage changes in the soil root zone and groundwater aquifers is important for predicting future water availability, drought and flood monitoring and weather prediction. In this study, we assimilate Terrestrial Water Storage (TWS) derived from Gravity Recovery and Climate Experiment (GRACE) satellite observations into a water balance model with 12.5-km spatial resolution. Our goal is to explore meso-scale surface and deep-level soil water storage, as well as groundwater changes within the USA covering the period 2003-2017. A new Bayesian approach is formulated and implemented in this study, which provides a dynamic solution for a state-space equation between hydrological model outputs and TWS observations, while considering their error structures. The unknown state parameters and temporal dependency between them are estimated through a combination of forward/backward Kalman Filtering and Markov Chain Monto Carlo (MCMC) methods.</p><p>The outputs of this methodological approach are evaluated using in situ data from historical USGS groundwater data (over 6600 wells) and the ESA CCI surface soil moisture data. The results indicate that our GRACE data assimilation generally improves the simulation of groundwater and soil moisture across the USA. For example, the long-term linear trend fitted to the Bayesian-derived groundwater and soil water storage are in a same direction as those of in situ data in 63% and 58% of regions studied across the USA, respectively. However, this vale is estimated less than 51% for both water storage estimates derived from the original water balance model, which suggesting that the data assimilation modulates the hydrological models to perform more realistically. The biggest improvements are observed in the southeast USA with considerably large inter-annual variability in precipitation, where modelled groundwater apparently responded too strongly to the changes in atmospheric forcing. The Bayesian data assimilation method also improves the temporal correlation coefficients between the in situ USGS and ESA CCI data and model outputs after merging with GRACE TWS estimates. For instance, the correlation coefficient between groundwater storage and USGS observation increased from -0.52 to 0.48 and from -0.28 to 0.25 in southeast and southwest of USA, respectively. Finally, we will explore changes in Bayesian-derived groundwater and soil water storage within the Florida, California and South of Mississippi regions and interpret their relations with climate-induced factors such as precipitation and ENSO index.</p><p><strong>Keywords:</strong> USA; Data Assimilation; Bayesian Method; Kalman Filtering; MCMC; GRACE; W3RA; groundwater storage; soil water storage; USGS; ESA CCI.</p><p> </p>

Detect groundwater storage in an island watershed by GRACE gravimetry

2020 ◽  
Author(s):  
Chung-Chieh Huang ◽  
Hong-Ru Lin ◽  
Jyun-Lin Chen ◽  
Shao-Yang Huang ◽  
Jet-Chau Wen ◽  
...  
Keyword(s):  
High Precision ◽  
Large Scale ◽  
Field Measurements ◽  
Alluvial Fan ◽  
Small Scale ◽  
Groundwater Storage ◽  
Satellite Gravimetry ◽  
Grace Data ◽  
Terrestrial Water ◽  
Central Taiwan

<p>         Since the successful launch of the Gravity Recovery and Climate Experiment (GRACE) on March 17<sup>th</sup>, 2002, a number of scientists have adopted satellite gravimetry for the detection of variations on terrestrial water storage (TWS). Use of high-precision GRACE gravimetry presents advantages in hydrogeologic studies, such as providing accurate estimates of currents and gravity fields. Many studies have proven that the high-precision GRACE gravimetry can observe large-scale (over 50,000 km<sup>2</sup>) variations in groundwater storage (GWS). However, relatively few studies conducted using satellite gravimetry have focused on scales smaller than 5,000 km<sup>2</sup>.</p><p>        The purpose of this study is to investigate the potential for using GRACE gravimetry to observe small-scale variations in GWS specifically, this paper presents a case study of the Zhoushui River alluvial fan (~2,560 km<sup>2</sup>) in central Taiwan as an example of how well GRACE data compare to field-based data for ascertaining small-scale variations in GWS. Field measurements of groundwater level in 52 observation wells (2002-2017) were used to analyze variations in GWS. Results of this field-based analysis were compared to results obtained using the GWS data (2002-2017) obtained by GRACE gravimetry. This comparison allowed us to evaluate the similarities and differences in both methods as well as to prove the feasibility of using GRACE gravimetry in small-scale regions. Results of our comparative analysis indicate that water resources in small watershed can be successfully managed using gravimetric data collected by GRACE satellite.</p><p> </p><p>Keywords: Groundwater storage, GRACE, Watershed</p>

Regional patterns in periphyton accrual and diatom assemblage structure in a heterogeneous nutrient landscape

2002 ◽  
Vol 59 (3) ◽  
pp. 564-577 ◽  
Author(s):  
Eric B Snyder ◽  
Christopher T Robinson ◽  
G Wayne Minshall ◽  
Samuel R Rushforth
Keyword(s):  
Spatial Scale ◽  
Total Phosphorus ◽  
Drainage Basin ◽  
Inorganic Nitrogen ◽  
Diatom Assemblage ◽  
Small Scale ◽  
Regional Patterns ◽  
Large Spatial Scale ◽  
Total Inorganic Nitrogen ◽  
Nutrient Diffusing Substrata

The effect of nutrient regime on periphyton community development in large rivers was examined (sites ranged from oligotrophic to eutrophic). Patterns in diatom community structure were examined at a large spatial scale (ultimate), whereas at the microhabitat scale (proximate), artificial nutrient-diffusing substrata were used to examine periphyton response to amendment with nitrogen, phosphorus, and N + P. Ratios of ambient dissolved inorganic nitrogen to total phosphorus were used to make predictions of nutrient limitation (molar total inorganic nitrogen (TIN) : total phosphorus (TP)), which matched experimental results in 8 of 12 sites. Two sites with highest ambient nutrient levels (mean NO3 + NO2 and TP, 1.49 and 0.081 mg·L–1, respectively) possessed the highest diatom richness and diversity (mean richness = 42). Lowest diatom taxa richness (19) occurred in an impounded system with low TP (0.008 mg·L–1). Principal components analysis (PCA) of diatom taxa structure among sites (control treatments only) and small-scale patterns among nutrient treatments using all sites and treatments combined indicated that sites were grouped according to drainage basin (r2 = 0.79) and that there was no unified response to enrichment (r2 = 0.43). Results suggest that large spatial scale factors are more important in determining the potential benthic diatom assemblage than small-scale, proximate variables provided by the diffusers.

Dynamics of Terrestrial Water Storage Change from Satellite and Surface Observations and Modeling

2010 ◽  
Vol 11 (1) ◽  
pp. 156-170 ◽  
Author(s):  
Qiuhong Tang ◽  
Huilin Gao ◽  
Pat Yeh ◽  
Taikan Oki ◽  
Fengge Su ◽  
...  
Keyword(s):  
Water Cycle ◽  
Regional Scale ◽  
Water Storage ◽  
Terrestrial Water Storage ◽  
Surface Observation ◽  
Grace Data ◽  
Terrestrial Water ◽  
Gravity Recovery ◽  
Storage Change ◽  
Surface Observations

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.

Sign in / Sign up

Export Citation Format

Share Document