Bathymetry sediment thickness and crustal structure from satellite gravity data

2000 ◽  
Vol 31 (1-2) ◽  
pp. 89-93 ◽  
Author(s):  
Derek Woodward ◽  
Ray Wood
Keyword(s):  
Crustal Structure ◽  
Gravity Data ◽  
Sediment Thickness ◽  
Satellite Gravity

New insights into the Andean crustal structure between 32° and 34°S from GOCE satellite gravity data and EGM2008 model

2014 ◽  
Vol 399 (1) ◽  
pp. 183-202 ◽  
Author(s):  
O. Alvarez ◽  
M. E. Gimenez ◽  
M. P. Martinez ◽  
F. Lince Klinger ◽  
C. Braitenberg
Keyword(s):  
Crustal Structure ◽  
Gravity Data ◽  
Satellite Gravity ◽  
Goce Satellite

Insight on the western Mediterranean crustal structure from GOCE satellite gravity data

2019 ◽  
Vol 124 ◽  
pp. 67-78 ◽  
Author(s):  
G. Dufréchou ◽  
R. Martin ◽  
S. Bonvalot ◽  
S. Bruinsma
Keyword(s):  
Crustal Structure ◽  
Gravity Data ◽  
Western Mediterranean ◽  
Satellite Gravity ◽  
Goce Satellite

scholarly journals A time series assessment of terrestrial water storage and its relationship with hydro-meteorological factors in Gilgit-Baltistan region using GRACE observation and GLDAS-Noah model

2021 ◽  
Vol 3 (5) ◽  
Author(s):  
Dostdar Hussain ◽  
Aftab Ahmed Khan ◽  
Syed Najam Ul Hassan ◽  
Syed Ali Asad Naqvi ◽  
Akhtar Jamil
Keyword(s):  
Snow Water Equivalent ◽  
Gravity Data ◽  
Water Storage ◽  
Indus Basin ◽  
Flood Hazards ◽  
Terrestrial Water Storage ◽  
Satellite Gravity ◽  
Terrestrial Water ◽  
Gilgit Baltistan

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.

scholarly journals Comparing global tomography-derived and gravity-based upper mantle density models

2020 ◽  
Vol 221 (3) ◽  
pp. 1542-1554 ◽  
Author(s):  
B C Root
Keyword(s):  
Seismic Tomography ◽  
Upper Mantle ◽  
Seismic Data ◽  
Gravity Data ◽  
Heterogeneous Data ◽  
Clear Correlation ◽  
Data Sets ◽  
Satellite Gravity ◽  
Similar Density ◽  
Similar Peak

SUMMARY Current seismic tomography models show a complex environment underneath the crust, corroborated by high-precision satellite gravity observations. Both data sets are used to independently explore the density structure of the upper mantle. However, combining these two data sets proves to be challenging. The gravity-data has an inherent insensitivity in the radial direction and seismic tomography has a heterogeneous data acquisition, resulting in smoothed tomography models with de-correlation between different models for the mid-to-small wavelength features. Therefore, this study aims to assess and quantify the effect of regularization on a seismic tomography model by exploiting the high lateral sensitivity of gravity data. Seismic tomography models, SL2013sv, SAVANI, SMEAN2 and S40RTS are compared to a gravity-based density model of the upper mantle. In order to obtain similar density solutions compared to the seismic-derived models, the gravity-based model needs to be smoothed with a Gaussian filter. Different smoothening characteristics are observed for the variety of seismic tomography models, relating to the regularization approach in the inversions. Various S40RTS models with similar seismic data but different regularization settings show that the smoothening effect is stronger with increasing regularization. The type of regularization has a dominant effect on the final tomography solution. To reduce the effect of regularization on the tomography models, an enhancement procedure is proposed. This enhancement should be performed within the spectral domain of the actual resolution of the seismic tomography model. The enhanced seismic tomography models show improved spatial correlation with each other and with the gravity-based model. The variation of the density anomalies have similar peak-to-peak magnitudes and clear correlation to geological structures. The resolvement of the spectral misalignment between tomographic models and gravity-based solutions is the first step in the improvement of multidata inversion studies of the upper mantle and benefit from the advantages in both data sets.

scholarly journals Monitoring mass changes in the Volta River basin using GRACE satellite gravity and TRMM precipitation

2012 ◽  
Vol 18 (4) ◽  
pp. 549-563 ◽  
Author(s):  
Vagner G. Ferreira ◽  
Zheng Gong ◽  
Samuel A. Andam-Akorful
Keyword(s):  
River Basin ◽  
Gravity Data ◽  
West African ◽  
Rainfall Time Series ◽  
Tropical Rainfall Measurement Mission ◽  
Satellite Gravity ◽  
Rainfall Events ◽  
The North ◽  
Trmm Precipitation ◽  
Grace Satellite

GRACE satellite gravity data was used to estimate mass changes within the Volta River basin in West African for the period of January, 2005 to December, 2010. We also used the precipitation data from the Tropical Rainfall Measurement Mission (TRMM) to determine relative contributions source to the seasonal hydrological balance within the Volta River basin. We found out that the seasonal mass change tends to be detected by GRACE for periods from 1 month in the south to 4 months in the north of the basin after the rainfall events. The results suggested a significant gain in water storage in the basin at reference epoch 2007.5 and a dominant annual cycle for the period under consideration for both in the mass changes and rainfall time series. However, there was a low correlation between mass changes and rainfall implying that there must be other processes which cause mass changes without rainfall in the upstream of the Volta River basin.

scholarly journals Accuracy Analysis of Gravity Field Changes from Grace RL06 and RL05 Data Compared to in Situ Gravimetric Measurements in the Context of Choosing Optimal Filtering Type

2020 ◽  
Vol 55 (3) ◽  
pp. 100-117
Author(s):  
Viktor Szabó ◽  
Dorota Marjańska
Keyword(s):  
Gravity Field ◽  
Ocean Circulation ◽  
Gravity Data ◽  
The Other ◽  
Subsurface Water ◽  
Satellite Gravity ◽  
Absolute Gravimetry ◽  
The Earth ◽  
Gravity Measurements ◽  
Gravity Recovery

AbstractGlobal satellite gravity measurements provide unique information regarding gravity field distribution and its variability on the Earth. The main cause of gravity changes is the mass transportation within the Earth, appearing as, e.g. dynamic fluctuations in hydrology, glaciology, oceanology, meteorology and the lithosphere. This phenomenon has become more comprehensible thanks to the dedicated gravimetric missions such as Gravity Recovery and Climate Experiment (GRACE), Challenging Minisatellite Payload (CHAMP) and Gravity Field and Steady-State Ocean Circulation Explorer (GOCE). From among these missions, GRACE seems to be the most dominating source of gravity data, sharing a unique set of observations from over 15 years. The results of this experiment are often of interest to geodesists and geophysicists due to its high compatibility with the other methods of gravity measurements, especially absolute gravimetry. Direct validation of gravity field solutions is crucial as it can provide conclusions concerning forecasts of subsurface water changes. The aim of this work is to present the issue of selection of filtration parameters for monthly gravity field solutions in RL06 and RL05 releases and then to compare them to a time series of absolute gravimetric data conducted in quasi-monthly measurements in Astro-Geodetic Observatory in Józefosław (Poland). The other purpose of this study is to estimate the accuracy of GRACE temporal solutions in comparison with absolute terrestrial gravimetry data and making an attempt to indicate the significance of differences between solutions using various types of filtration (DDK, Gaussian) from selected research centres.

scholarly journals Lineament Extraction using Gravity Data in the Citarum Watershed

2021 ◽  
Vol 53 (1) ◽  
Author(s):  
Gumilar Utamas Nugraha ◽  
Karit Lumban Goal ◽  
Lina Handayani ◽  
Rachmat Fajar Lubis
Keyword(s):  
Gravity Data ◽  
Bouguer Anomaly ◽  
High Density ◽  
Low Density ◽  
Residual Value ◽  
Satellite Gravity ◽  
Structural Weakness ◽  
Major Trend ◽  
Lineament Extraction ◽  
Butterworth Filters

Lineament is one of the most important features showing subsurface elements or structural weakness such as faults. This study aims to identify subsurface lineament patterns using automatic lineament in Citarum watershed with gravity data. Satellite gravity data were used to generate a sub-surface lineament. Satellite gravity data corrected using Bouguer and terrain correction to obtain a complete Bouguer anomaly value. Butterworth filters were used to separate regional and residual anomaly from the complete Bouguer anomaly value. Residual anomaly gravity data used to analyze sub-surface lineament. Lineament generated using Line module in PCI Geomatica to obtain sub-surface lineament from gravity residual value. The orientations of lineaments and fault lines were created by using rose diagrams. The main trends observed in the lineament map could be recognized in these diagrams, showing a strongly major trend in NW-SE, and the subdominant directions were in N-S. Area with a high density of lineament located at the Southern part of the study area. High-density lineament might be correlated with fractured volcanic rock upstream of the Citarum watershed, meanwhile, low-density lineament is associated with low-density sediment. The high-density fracture might be associated with intensive tectonics and volcanism.

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