Quantifying water storage change and land subsidence induced by reservoir impoundment using GRACE, Landsat, and GPS data

Tangdamrongsub, Natthachet; Han, Shin‐Chan; Jasinski, Michael F.; Šprlák, Michal

doi:10.1016/j.rse.2019.111385

Cited by 30 publications

(22 citation statements)

References 81 publications

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“…The GRACE monthly geopotential spherical harmonic coefficients (SHC), together with the load Love numbers [7], are used to compute the ΔTWS and Δr as follows [54]:…”

Section: Computation Of Terrestrial Water Storage and Vertical Displamentioning

confidence: 99%

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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“…The GRACE monthly geopotential spherical harmonic coefficients (SHC), together with the load Love numbers [7], are used to compute the ΔTWS and Δr as follows [54]:…”

Section: Computation Of Terrestrial Water Storage and Vertical Displamentioning

confidence: 99%

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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“…Human activity is observed to affect the Earth's crust. Mass concentrations associated with water reservoir impoundment are found to cause subsidence (e.g., Tangdamrongsubab et al, 2019), affect earthquake rates (Gahalaut & Gahalaut, 2010; Talwani, 1997), and even change the shape and rotation of the Earth (Boy & Chao, 2002). Direct settlement is expected after buildings are constructed (e.g., Day, 2010), and further unplanned subsidence may also happen (e.g., Polcari et al, 2019; Post, 2019).…”

Section: Introductionmentioning

confidence: 99%

The Weight of Cities: Urbanization Effects on Earth's Subsurface

Parsons

2021

AGU Advances

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Across the world, people increasingly choose to live in cities. By 2050, 70% of Earth's population will live in large urban areas. Upon considering a large city, questions arise such as, how much does that weigh? What are its effects on the landscape? Does it cause measurable subsidence? Here I calculate the weight of San Francisco Bay region urbanization, where 7.75 million people live at, or near the coast. It is difficult to account for everything that is in a city. I assume that most of the weight is buildings and their contents, which allows the use of base outline and height data to approximate their mass, which is cumulatively 1.6•10 12 kg. I build a series of finite element models to study effects of pressure exerted by the weight distribution. Within the elastic realm, I look at compression, flexure, isostatic compensation, stress change, dilatation, and fluid flow changes. Within the nonlinear realm I show example calculations of primary and secondary settlement of soils under load. The combined modeled subsidence from building loads is at least 5-80 mm, with the largest contributions coming from nonlinear settlement and creep in soils. A general result is closing of pore space and redirection of pore fluids. While the calculated subsidence of the Bay Area is relatively small compared with other sources of elevation change such as pumping and recharge of aquifers, all sources of subsidence are concerning given an expected 200-300 mm sea level rise at San Francisco by the year 2050. Plain Language Summary By the year 2050, 70% of Earth's population will live in cities. The belongings and needs of these growing populations concentrate mass over relatively small areas. In this paper, I calculate the weight of a metropolitan region and study the changes to the solid earth beneath it using numerical modeling techniques. I find that the subsidence under this weight is not insignificant and that it adds to other causes of urban subsidence, such as ground water pumping. As global populations move disproportionately toward the coasts, this additional subsidence in combination with expected sea level rise may exacerbate risk associated with inundation. Human activity is observed to affect the Earth's crust. Mass concentrations associated with water reservoir impoundment are found to cause subsidence (e.g.,

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“…The demonstrated simulation period is 1981-2012, coincident with the availability of meteorological forcing data. Recent studies have shown success in assimilating GRACE data into a coarse-scale CABLE version to improve TWS and groundwater storage (GWS) estimates in the Goulburn River catchment and in the North China Plain (Tangdamrongsub et al, 2020;Yin et al, 2020). In this study, GRACE observations (Luthcke et al, 2013) are also assimilated into CABLE 0.05 • (and CABLE 0.5 • ) to improve the accuracy of TWS components between 2003 and 2012.…”

Section: Introductionmentioning

confidence: 99%

Development and evaluation of 0.05° terrestrial water storage estimates using CABLE land surface model and GRACE data assimilation

Tangdamrongsub¹,

Jasinski²,

Shellito³

2021

Preprint

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Abstract. Accurate estimation of terrestrial water storage (TWS) at a meaningful spatiotemporal resolution is important for reliable assessments of regional water resources and climate variability. Individual components of TWS include soil moisture, snow, groundwater, and canopy storage and can be estimated from the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model. The spatial resolution of CABLE is currently limited to 0.5° by the resolution of soil and vegetation datasets that underlie model parameterizations, posing a challenge to using CABLE for hydrological applications at a local scale. This study aims to improve the spatial detail (from 0.5° to 0.05°) and timespan (1981–2012) of CABLE TWS estimates using rederived model parameters and high-resolution meteorological forcing. In addition, TWS observations derived from the Gravity Recovery and Climate Experiment (GRACE) satellite mission are assimilated into CABLE to improve TWS accuracy. The success of the approach is demonstrated in Australia, where multiple ground observation networks are available for validation. The evaluation process is conducted using four different case studies that employ different model spatial resolutions and include or omit GRACE data assimilation (DA). We find that the CABLE 0.05° developed here improves TWS estimates in terms of accuracy, spatial resolution, and long-term water resource assessment reliability. The inclusion of GRACE DA increases the accuracy of groundwater storage (GWS) estimates and has little impact on surface soil moisture or evapotranspiration. The use of improved model parameters and improved state estimations (via GRACE DA) together is recommended to achieve the best GWS accuracy. The workflow elaborated in this paper relies only on publicly accessible global datasets, allowing reproduction of the 0.05° TWS estimates in any study region.

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Quantifying water storage change and land subsidence induced by reservoir impoundment using GRACE, Landsat, and GPS data

Cited by 30 publications

References 81 publications

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

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

The Weight of Cities: Urbanization Effects on Earth's Subsurface

Development and evaluation of 0.05° terrestrial water storage estimates using CABLE land surface model and GRACE data assimilation

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