scholarly journals Simulating the influence of water storage changes on the superconducting gravimeter of the Geodetic Observatory Wettzell, Germany

Geophysics ◽  
2008 ◽  
Vol 73 (6) ◽  
pp. WA95-WA104 ◽  
Author(s):  
Benjamin Creutzfeldt ◽  
Andreas Güntner ◽  
Thomas Klügel ◽  
Hartmut Wziontek
Keyword(s):  
Soil Moisture ◽  
Water Storage ◽  
Superconducting Gravimeter ◽  
Spatiotemporal Variability ◽  
Gravity Effect ◽  
Snow Storage ◽  
Superconducting Gravimeters ◽  
Influence Of Water ◽  
Gravity Signal ◽  
Local Water

Superconducting gravimeters (SG) measure temporal changes of the Earth’s gravity field with high accuracy and long-term stability. Variations in local water storage components (snow, soil moisture, groundwater, surface water, and water stored by vegetation) can have a significant influence on SG measurements and — from a geodetic perspective — add noise to the SG records. At the same time, this hydrological gravity signal can provide substantial information about the quantification of water balances. A 4D forward model with a spatially nested discretization domain was developed to investigate the local hydrological gravity effect on the SG records of the Geodetic Observatory Wettzell, Germany. The possible maximum gravity effect was investigated using hypothetical water storage changes based on physical boundary conditions. Generally, on flat terrain, a water mass change of[Formula: see text] in the model domain causes a gravity change of [Formula: see text]. Simulation results show that topography increases this value to [Formula: see text]. Errors in the Digital Elevation Model can influence the results significantly. The radius of influence of local water storage variations is limited to [Formula: see text]. Detailed hydrological measurements should be carried out in a radius of [Formula: see text] around the SG station. Groundwater, soil moisture, and snow storage changes dominate the hydrological gravity effect at the SG Wettzell. Using observed time series for these variables in the 4D model and comparing the results to the measured gravity residuals show similarities in both seasonal and shorter-term dynamics. However, differences exist, e.g., the range comparison of the mean modeled [Formula: see text] gravity signal and the measured [Formula: see text] gravity signal, making additional hydrological measurements necessary to describe the full spatiotemporal variability of local water masses.

Reducing gravity data for the influence of water storage variations beneath observatory buildings

Geophysics ◽  
2019 ◽  
Vol 84 (1) ◽  
pp. EN15-EN31 ◽  
Author(s):  
Marvin Reich ◽  
Michal Mikolaj ◽  
Theresa Blume ◽  
Andreas Güntner
Keyword(s):  
Soil Moisture ◽  
Gravity Data ◽  
Near Field ◽  
Water Storage ◽  
Natural Soil ◽  
Mass Distributions ◽  
Site Characteristics ◽  
Influence Of Water ◽  
Building Effects ◽  
Local Water

Ground-based gravimetry is increasingly used to study mass distributions and mass transport below the earth surface. The gravity effect of local water storage variations can be large and should be accounted for in the interpretation of these data. However, the effect of hydrologic mass changes in the immediate vicinity of the gravimeter is not considered in standard routines for separating unwanted signal components. This applies in particular to the effect of the buildings in which gravimeters are installed. The building shields the underlying soil from precipitation and evapotranspiration and thus directly affects the water storage dynamics in the near-field of the gravimeter. A combined approach of in situ soil moisture observations and hydrologic modeling was used to quantify the altered water storage variations below observatory buildings. Subsequently, the errors caused by different estimation approaches for this umbrella effect in hydrogravitational computations were assessed. Depending on the site characteristics, the errors range from 4.1 to [Formula: see text] for the intra-annual amplitude when natural soil moisture data are considered for modeling the umbrella effect, and they range from 4.1 to [Formula: see text] when assuming no gravity change within 5 m below the building. These results were condensed to general recommendations, leading to a new simple and broadly applicable method to reduce observed gravity data for building effects, given basic information about the gravimeter location, building dimensions, climatic regime, and soil type of the observation site. This new reduction approach indicates errors of the intra-annual amplitude from 1.9 to [Formula: see text].

scholarly journals A study of the monsoonal hydrology contribution using a 8-yr record (2010–2018) from superconducting gravimeter OSG-060 at Djougou (Benin, West Africa)

2020 ◽  
Vol 221 (1) ◽  
pp. 431-439 ◽  
Author(s):  
J Hinderer ◽  
B Hector ◽  
U Riccardi ◽  
S Rosat ◽  
J-P Boy ◽  
...  
Keyword(s):  
Soil Moisture ◽  
West Africa ◽  
Water Table ◽  
Energy Budget ◽  
Water Storage ◽  
Superconducting Gravimeter ◽  
Absolute Gravity ◽  
Surface Model ◽  
Residual Signal ◽  
Gravity Observation

SUMMARY We analyse a nearly 8-yr record (2010–2018) of the superconducting gravimeter OSG-060 located at Djougou (Benin, West Africa). After tidal analysis removing all solid Earth and ocean loading tidal contributions and correcting for the long-term instrumental drift and atmospheric loading, we obtain a gravity residual signal which is essentially a hydrological signal due to the monsoon. This signal is first compared to several global hydrology models (ERA, GLDAS and MERRA). Our superconducting gravimeter residual signal is also superimposed onto episodic absolute gravity measurements and to space gravimetry GRACE data. A further comparison is done using local hydrological data like soil moisture in the very superficial layer (0–1.2 m), water table depth and rainfall. The temporal evolution of the correlation coefficient between the gravity observation and both the soil moisture and the water table is well explained by the direct infiltration process of rain water together with the lateral transfer discharging the water table. Finally, we compute the water storage changes (WSC) using a simulation based on the physically based Parflow-CLM numerical model of the catchment, which solves the water and energy budget from the impermeable bedrock to the top of the canopy layer using the 3-D Richards equation for the water transfers in the ground, the kinematic wave equation for the surface runoff and a land surface model (CLM) for the energy budget and evapotranspiration calculation. This model forced by rain is in agreement with evapotranspiration and stream flow data and leads to simulated water storage changes that nicely fit to the observed gravity signal. This study points out the important role played by surface gravity changes in terms of a reliable proxy for water storage changes occurring in small catchments.

scholarly journals Testing an optimality-based model of rooting zone water storage capacity in temperate forests

2017 ◽  
Author(s):  
Matthias J. R. Speich ◽  
Heike Lischke ◽  
Massimiliano Zappa
Keyword(s):  
Soil Moisture ◽  
Storage Capacity ◽  
Water Storage ◽  
Balance Model ◽  
Rooting Depth ◽  
Water Storage Capacity ◽  
Rooting Zone ◽  
Local Water ◽  
Zone Water ◽  
Good Agreement

Abstract. Rooting zone water storage capacity Sr is a crucial parameter in models of hydrology, ecosystem gas exchange and vegetation dynamics. Despite its importance, this parameter is still poorly constrained and subject to high uncertainty. We tested the analytical, optimality-based model of effective rooting depth proposed by Guswa (2010) with regard to its applicability for parameterizing Sr in temperate forests. The model assumes that plants dimension their rooting systems in order to maximize net carbon gain. Results from this model were compared against values obtained by calibrating a local water balance model against latent heat flux and soil moisture observations from 15 eddy covariance sites. To increase the applicability of the rooting depth model, we provide a numerical approximation of its underlying probabilistic soil moisture model. The calibration and validation of the local water balance model show that the concept of a single rooting zone storage capacity was appropriate at most temperate and cold sites, but not at Mediterranean sites and for very coarse soils. At a majority of sites, the estimates of Sr are generally in good agreement. However, mismatches were found in stands dominated by Norway spruce, especially at high elevations. These mismatches were attributed to the fact that the model does not consider rooting depth limitations due to oxygen stress and low soil temperature. Also, it is not clear whether the rooting behavior of pines on coarse soils is captured properly. Nevertheless, the overall good agreement suggests that this model may be useful for generating estimates of rooting zone storage capacity for both hydrological and ecological applications. Another potential use is the dynamic parameterization of the rooting zone in process-based models, which greatly increases the reliability of transient climate-impact assessment studies.

scholarly journals Regression Models for Soil Water Storage Estimation Using the ESA CCI Satellite Soil Moisture Product: A Case Study in Northeast Portugal

Water ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 37
Author(s):  
Tomás de Figueiredo ◽  
Ana Caroline Royer ◽  
Felícia Fonseca ◽  
Fabiana Costa de Araújo Schütz ◽  
Zulimar Hernández
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Regression Models ◽  
Meteorological Data ◽  
Water Storage ◽  
Model Performance ◽  
Soil Water Balance ◽  
Soil Water Storage ◽  
The Relationship

The European Space Agency Climate Change Initiative Soil Moisture (ESA CCI SM) product provides soil moisture estimates from radar satellite data with a daily temporal resolution. Despite validation exercises with ground data that have been performed since the product’s launch, SM has not yet been consistently related to soil water storage, which is a key step for its application for prediction purposes. This study aimed to analyse the relationship between soil water storage (S), which was obtained from soil water balance computations with ground meteorological data, and soil moisture, which was obtained from radar data, as affected by soil water storage capacity (Smax). As a case study, a 14-year monthly series of soil water storage, produced via soil water balance computations using ground meteorological data from northeast Portugal and Smax from 25 mm to 150 mm, were matched with the corresponding monthly averaged SM product. Linear (I) and logistic (II) regression models relating S with SM were compared. Model performance (r2 in the 0.8–0.9 range) varied non-monotonically with Smax, with it being the highest at an Smax of 50 mm. The logistic model (II) performed better than the linear model (I) in the lower range of Smax. Improvements in model performance obtained with segregation of the data series in two subsets, representing soil water recharge and depletion phases throughout the year, outlined the hysteresis in the relationship between S and SM.

Stepwise improvement of hydrological models using satellite-based evaporation and total water storage estimations

2021 ◽  
Author(s):  
Markus Hrachowitz ◽  
Petra Hulsman ◽  
Hubert Savenije
Keyword(s):  
Model Calibration ◽  
Hydrological Model ◽  
Model Development ◽  
Water Storage ◽  
Spatiotemporal Variability ◽  
Model Structure ◽  
Hydrological Models ◽  
Total Water ◽  
Spatiotemporal Model ◽  
Multiple Variables

<p>Hydrological models are often calibrated with respect to flow observations at the basin outlet. As a result, flow predictions may seem reliable but this is not necessarily the case for the spatiotemporal variability of system-internal processes, especially in large river basins. Satellite observations contain valuable information not only for poorly gauged basins with limited ground observations and spatiotemporal model calibration, but also for stepwise model development. This study explored the value of satellite observations to improve our understanding of hydrological processes through stepwise model structure adaption and to calibrate models both temporally and spatially. More specifically, satellite-based evaporation and total water storage anomaly observations were used to diagnose model deficiencies and to subsequently improve the hydrological model structure and the selection of feasible parameter sets. A distributed, process based hydrological model was developed for the Luangwa river basin in Zambia and calibrated with respect to discharge as benchmark. This model was modified stepwise by testing five alternative hypotheses related to the process of upwelling groundwater in wetlands, which was assumed to be negligible in the benchmark model, and the spatial discretization of the groundwater reservoir. Each model hypothesis was calibrated with respect to 1) discharge and 2) multiple variables simultaneously including discharge and the spatiotemporal variability in the evaporation and total water storage anomalies. The benchmark model calibrated with respect to discharge reproduced this variable well, as also the basin-averaged evaporation and total water storage anomalies. However, the evaporation in wetland dominated areas and the spatial variability in the evaporation and total water storage anomalies were poorly modelled. The model improved the most when introducing upwelling groundwater flow from a distributed groundwater reservoir and calibrating it with respect to multiple variables simultaneously. This study showed satellite-based evaporation and total water storage anomaly observations provide valuable information for improved understanding of hydrological processes through stepwise model development and spatiotemporal model calibration.</p>

scholarly journals Recent changes in terrestrial water storage in the Upper Nile Basin: an evaluation of commonly used gridded GRACE products

2017 ◽  
Vol 21 (9) ◽  
pp. 4533-4549 ◽  
Author(s):  
Mohammad Shamsudduha ◽  
Richard G. Taylor ◽  
Darren Jones ◽  
Laurent Longuevergne ◽  
Michael Owor ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Lake Victoria ◽  
Water Storage ◽  
Terrestrial Water Storage ◽  
Nile Basin ◽  
Lake Victoria Basin ◽  
Groundwater Storage ◽  
Terrestrial Water ◽  
Substantial Uncertainty

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.

scholarly journals Estimating annual water storage variations in medium-scale (2000–10 000 km<sup>2</sup>) basins using microwave-based soil moisture retrievals

2017 ◽  
Vol 21 (3) ◽  
pp. 1849-1862 ◽  
Author(s):  
Wade T. Crow ◽  
Eunjin Han ◽  
Dongryeol Ryu ◽  
Christopher R. Hain ◽  
Martha C. Anderson
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Water Budget ◽  
Surface Soil ◽  
Water Storage ◽  
Microwave Remote Sensing ◽  
The United States ◽  
Surface Soil Moisture ◽  
Medium Scale ◽  
Annual Water

Abstract. Due to their shallow vertical support, remotely sensed surface soil moisture retrievals are commonly regarded as being of limited value for water budget applications requiring the characterization of temporal variations in total terrestrial water storage (dS ∕ dt). However, advances in our ability to estimate evapotranspiration remotely now allow for the direct evaluation of approaches for quantifying dS ∕ dt via water budget closure considerations. By applying an annual water budget analysis within a series of medium-scale (2000–10 000 km2) basins within the United States, we demonstrate that, despite their clear theoretical limitations, surface soil moisture retrievals derived from passive microwave remote sensing contain statistically significant information concerning dS ∕ dt. This suggests the possibility of using (relatively) higher-resolution microwave remote sensing products to enhance the spatial resolution of dS ∕ dt estimates acquired from gravity remote sensing.

scholarly journals Effects of Climate Variability on Water Storage in the Colorado River Basin

2009 ◽  
Vol 10 (5) ◽  
pp. 1257-1270 ◽  
Author(s):  
Ruud Hurkmans ◽  
Peter A. Troch ◽  
Remko Uijlenhoet ◽  
Paul Torfs ◽  
Matej Durcik
Keyword(s):  
Soil Moisture ◽  
River Basin ◽  
Colorado River ◽  
Decadal Variability ◽  
Southern Oscillation ◽  
Water Storage ◽  
Low Frequency ◽  
Colorado River Basin ◽  
Climate Indices ◽  
Deep Soil

Abstract Understanding the long-term (interannual–decadal) variability of water availability in river basins is paramount for water resources management. Here, the authors analyze time series of simulated terrestrial water storage components, observed precipitation, and discharge spanning 74 yr in the Colorado River basin and relate them to climate indices that describe variability of sea surface temperature and sea level pressure in the tropical and extratropical Pacific. El Niño–Southern Oscillation (ENSO) indices in winter [January–March (JFM)] are related to winter precipitation as well as to soil moisture and discharge in the lower Colorado River basin. The low-frequency mode of the Pacific decadal oscillation (PDO) appears to be strongly correlated with deep soil moisture. During the negative PDO phase, saturated storage anomalies tend to be negative and the “amplitudes” (mean absolute anomalies) of shallow soil moisture, snow, and discharge are slightly lower compared to periods of positive PDO phases. Predicting interannual variability, therefore, strongly depends on the capability of predicting PDO regime shifts. If indeed a shift to a cool PDO phase occurred in the mid-1990s, as data suggest, the current dry conditions in the Colorado River basin may persist.

scholarly journals Trend Dynamics of GRACE Terrestrial Water Storage in the Nile River Basin

2019 ◽  
Author(s):  
Emad Hasan ◽  
Aondover Tarhule
Keyword(s):  
Soil Moisture ◽  
Population Density ◽  
River Basin ◽  
Goodness Of Fit ◽  
Water Storage ◽  
Least Square ◽  
Nile River ◽  
Terrestrial Water Storage ◽  
Terrestrial Water ◽  
Nile River Basin

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&rsquo;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&lt;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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