Surface Deformation and Influence of Hydrological Mass Over Himalaya and North India Revealed From a Decade of Continuous GPS and GRACE Observations

Saji, Ajish P.; Sunil, P. S.; Sreejith, K. M.; Gautam, Param K.; Kumar, K.G.; Ponraj, Mohanadoss; Amirtharaj, S.; Shaju, Rose Mary; Begum, S. Kareemunnisa; Reddy, C. D.; Ramesh, D. S.

doi:10.1029/2018jf004943

Cited by 22 publications

(19 citation statements)

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“…One of the most commonly used external models comes from the Gravity Recovery And Climate Experiment (GRACE) mission, which produces spatiotemporal descriptions of the Earth's gravity field and inferred redistribution of near-surface mass. A large body of research supports the general agreement between GRACE-based models of deformation and the hydrological loads observed in GNSS data (Chanard et al, 2018;Fu et al, 2013;Fu & Freymueller, 2012;Hao et al, 2016;Tregoning et al, 2009;Yan et al, 2019;Saji et al, 2020). However, GRACE data products are relatively coarsely sampled in both space and time, having a spatial wavelength of 350-500 km and monthly sampling, and an inherent tradeoff between temporal and spatial resolution in the processing.…”

Section: Introductionmentioning

confidence: 82%

GNSS characterization of hydrological loading in South and Southeast Asia

Materna

Feng

Lindsey

et al. 2020

Geophysical Journal International

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Summary The elastic response of the lithosphere to surface mass redistributions produces geodetically measurable deformation of the Earth. This deformation is especially pronounced in South and Southeast Asia, where the annual monsoon produces large-amplitude hydrological loads. The Myanmar-India-Bangladesh-Bhutan (MIBB) network of about 20 continuously operating Global Navigation Satellite Systems (GNSS) stations, established in 2011, provides an opportunity to study the Earth's response to these loads. In this study, we use GRACE temporal gravity products as an estimate of long-wavelength surface water distribution and use this estimate in an elastic loading calculation. We compare the predicted vertical deformation from GRACE with that observed with GNSS. We find that elastic loading inferred from the GRACE gravity model is able to explain the phase and much of the peak-to-peak amplitude (typically 2–3 cm) of the vertical GNSS oscillations, especially in northeast India and central Myanmar. GRACE-based corrections reduce the RMS scatter of the GNSS data by 30–45 per cent in these regions. However, this approach does not capture all of the seasonal deformation in central Bangladesh and southern Myanmar. We show by a synthetic test that local hydrological effects may explain discrepancies between the GNSS and GRACE signals in these places. Two independent hydrological loading models of water stored in soil, vegetation, snow, lakes, and streams display phase lags compared to the GRACE and GNSS observations, perhaps indicating that groundwater contributes to the observed loading in addition to near-surface hydrology. The results of our calculations have implications for survey-mode GNSS measurements, which make up the majority of geodetic measurements in this region. By using the GNSS data together with estimates of hydrological loading from independent observations and models, we may be able to more accurately determine crustal motions caused by tectonic processes in South and Southeast Asia, while also improving our ability to monitor the annual monsoon and resulting water storage changes in the region.

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Section: Introductionmentioning

confidence: 82%

GNSS characterization of hydrological loading in South and Southeast Asia

Materna

Feng

Lindsey

et al. 2020

Geophysical Journal International

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“…In the western sector (Lon: 75°; Lat: 30°) GRACE predicts a wider anomaly zone compared to our simulations. This is probably due to a long-term water mass variation associated to intense anthropogenic water extraction (Saji et al, 2020) which is not modelled in GLDAS products. The crustal tectonic uplift seems to be able to explain part of the positive trend in the Central-Eastern Tibet, the mismatch in amplitude could be caused by other components not modelled such as water volume variations associated to the endorheic lakes, as suggested by Zhang et al (2017).…”

Section: Forward Modeling Of the Gravity Fieldsmentioning

confidence: 99%

Geophysical Challenges for Future Satellite Gravity Missions: Assessing the Impact of MOCASS Mission

Pivetta

Braitenberg

Barbolla

2021

Pure Appl. Geophys.

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The GRACE/GRACE-FO satellites have observed large scale mass changes, contributing to the mass budget calculation of the hydro-and cryosphere. The scale of the observable mass changes must be in the order of 300 km or bigger to be resolved. Smaller scale glaciers and hydrologic basins significantly contribute to the closure of the water mass balance, but are not detected with the present spatial resolution of the satellite. The challenge of future satellite gravity missions is to fill this gap, providing higher temporal and spatial resolution. We assess the impact of a geodetic satellite mission carrying on board a cold atom interferometric gradiometer (MOCASS: Mass Observation with Cold Atom Sensors in Space) on the resolution of simulated geophysical phenomena, considering mass changes in the hydrosphere and cryosphere. Moreover, we consider mass redistributions due to seamounts and tectonic movements, belonging to the solid earth processes. The MOCASS type satellite is able to recover 50% smaller deglaciation rates over a mountain range as the High Mountains of Asia compared to GRACE, and to detect the mass of 60% of the cumulative number of glaciers, an improvement respect to GRACE which detects less than 20% in the same area. For seamounts a significantly smaller mass eruption could be detected with respect to GRACE, reaching a level of mass detection of a submarine basalt eruption of 1.6 109 m3. This mass corresponds to the eruption of Mount Saint Helens. The simulations demonstrate that a MOCASS type mission would significantly improve the resolution of mass changes respect to existing geodetic satellite missions.

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“…Measuring land deformation using Global Positioning System (GPS) networks has been used to achieve <1-cm measurement's accuracy [6,[15][16][17]. However, this technique requires moderately dense GPS sites to operate continuously.…”

Section: Introductionmentioning

confidence: 99%

“…In data-sparse regions, satellite gravity data have been considered a primary measurement regarding multiple advantages such as continuous time series, extended ground coverage, and no operational cost required from users. The Gravity Recovery and Climate Experiment (GRACE [18]) and its successor, GRACE-Follow On (GRACE-FO [19]), satellite missions have provided accurate monthly earth gravity field measurements in various applications, including water resource, land deformation, and climate [17,[20][21][22][23]. For convenience, the term GRACE is used for both GRACE and GRACE-FO throughout this paper.…”

Section: Introductionmentioning

confidence: 99%

“…For convenience, the term GRACE is used for both GRACE and GRACE-FO throughout this paper. The successful measuring of large-scale land deformation by GRACE has been reported in various geographic and climate conditions, e.g., the Himalayas and India [17], Africa [11], and Australia [24]. The downside of GRACE data is the relatively coarse spatial resolution (i.e.,~300 × 300 km 2 ) that may degrade the derived local deformation's accuracy [6].…”

Section: Introductionmentioning

confidence: 99%

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The Assessment of Hydrologic- and Flood-Induced Land Deformation in Data-Sparse Regions Using GRACE/GRACE-FO Data Assimilation

Tangdamrongsub

Šprlák

2021

Remote Sensing

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The vertical motion of the Earth’s surface is dominated by the hydrologic cycle on a seasonal scale. Accurate land deformation measurements can provide constructive insight into the regional geophysical process. Although the Global Positioning System (GPS) delivers relatively accurate measurements, GPS networks are not uniformly distributed across the globe, posing a challenge to obtaining accurate deformation information in data-sparse regions, e.g., Central South-East Asia (CSEA). Model simulations and gravity data (from the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO)) have been successfully used to improve the spatial coverage. While combining model estimates and GRACE/GRACE-FO data via the GRACE/GRACE-FO data assimilation (DA) framework can potentially improve the accuracy and resolution of deformation estimates, the approach has rarely been considered or investigated thus far. This study assesses the performance of vertical displacement estimates from GRACE/GRACE-FO, the PCRaster Global Water Balance (PCR-GLOBWB) hydrology model, and the GRACE/GRACE-FO DA approach (assimilating GRACE/GRACE-FO into PCR-GLOBWB) in CSEA, where measurements from six GPS sites are available for validation. The results show that GRACE/GRACE-FO, PCR-GLOBWB, and GRACE/GRACE-FO DA accurately capture regional-scale hydrologic- and flood-induced vertical displacements, with the correlation value and RMS reduction relative to GPS measurements up to 0.89 and 53%, respectively. The analyses also confirm the GRACE/GRACE-FO DA’s effectiveness in providing vertical displacement estimates consistent with GRACE/GRACE-FO data while maintaining high-spatial details of the PCR-GLOBWB model, highlighting the benefits of GRACE/GRACE-FO DA in data-sparse regions.

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Surface Deformation and Influence of Hydrological Mass Over Himalaya and North India Revealed From a Decade of Continuous GPS and GRACE Observations

Cited by 22 publications

References 57 publications

GNSS characterization of hydrological loading in South and Southeast Asia

GNSS characterization of hydrological loading in South and Southeast Asia

Geophysical Challenges for Future Satellite Gravity Missions: Assessing the Impact of MOCASS Mission

The Assessment of Hydrologic- and Flood-Induced Land Deformation in Data-Sparse Regions Using GRACE/GRACE-FO Data Assimilation

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