Satellite-based estimates of groundwater storage variations in large drainage basins with extensive floodplains

Frappart, Frédéric; Papa, Fabrice; Güntner, Andreas; Werth, Susanna; Silva, Joécila Santos da; Tomasella, Javier; Seyler, Frédérique; Prigent, Catherine; Rossow, William B.; Calmant, Stéphane; Bonnet, Marie‐Paule

doi:10.1016/j.rse.2011.02.003

Cited by 77 publications

(83 citation statements)

References 37 publications

(45 reference statements)

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“…, an error of ~30%. This is of the same order of magnitude as the maximum error (23%) found for the Rio Negro in the Amazon Basin [27,62].…”

Section: Time Variations Of Surface Water Storage In the Orinoco Floosupporting

confidence: 69%

“…We used both datasets during their period of common availability, from 2003 to 2007. Details of the two-step methodology have been published in [28,62] and are summarized below.…”

Section: Methods For Estimating Surface Water Storagementioning

confidence: 99%

“…Following Frappart et al [27,62], water levels for a given month were linearly interpolated over GIEMS inundation. Each monthly map of surface water levels had a spatial resolution of 0.25°, and the elevation of each pixel was provided with reference to a map of minimum water levels estimated for the entire observation period (2003-2007) using a hypsometric approach (see Frappart et al [28,29]).…”

Section: Monthly Maps Of Surface Water Levelsmentioning

confidence: 99%

“…φj.t) is the anomaly of TWS at time t for the pixel at coordinates (λj, φj). The error of the method was estimated following Frappart et al [27,62] (Equation (7)): min ( ) (( ( , , ) ( , , ( , , ))) ( , , ) ( , , ) ( , , ))…”

Section: Time Series Of Water Volume Variationsmentioning

confidence: 99%

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Surface Freshwater Storage Variations in the Orinoco Floodplains Using Multi-Satellite Observations

et al. 2014

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Variations in surface water extent and storage are poorly characterized from regional to global scales. In this study, a multi-satellite approach is proposed to estimate the water stored in the floodplains of the Orinoco Basin at a monthly time-scale using remotely-sensed observations of surface water from the Global Inundation Extent Multi-Satellite (GIEMS) and stages from Envisat radar altimetry. Surface water storage variations over [2003][2004][2005][2006][2007] exhibit large interannual variability and a strong seasonal signal, peaking during summer, OPEN ACCESSRemote Sens. 2015, 7 90 and associated with the flood pulse. The volume of surface water storage in the Orinoco Basin was highly correlated with the river discharge at Ciudad Bolivar (R = 0.95), the closest station to the mouth where discharge was estimated, although discharge lagged one month behind storage. The correlation remained high (R = 0.73) after removing seasonal effects. Mean annual variations in surface water volume represented ~170 km 3 , contributing to ~45% of the Gravity Recovery and Climate Experiment (GRACE)-derived total water storage variations and representing ~13% of the total volume of water that flowed out of the Orinoco Basin to the Atlantic Ocean.

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“…, an error of ~30%. This is of the same order of magnitude as the maximum error (23%) found for the Rio Negro in the Amazon Basin [27,62].…”

Section: Time Variations Of Surface Water Storage In the Orinoco Floosupporting

confidence: 69%

“…We used both datasets during their period of common availability, from 2003 to 2007. Details of the two-step methodology have been published in [28,62] and are summarized below.…”

Section: Methods For Estimating Surface Water Storagementioning

confidence: 99%

Section: Monthly Maps Of Surface Water Levelsmentioning

confidence: 99%

Section: Time Series Of Water Volume Variationsmentioning

confidence: 99%

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Surface Freshwater Storage Variations in the Orinoco Floodplains Using Multi-Satellite Observations

et al. 2014

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“…Several satellite altimetry missions were launched since the late 1980s: GEOSAT (1986)(1987)(1988), ERS-1 (1991ERS-1 ( -1996, Topex/Poseidon Recently, satellite radar altimetry was combined with satellite imagery to derive volume variations of surface water in large river basins such as the Negro River Basin [9] [10] [11], and the [12]. Few studies were carried out to derive variations of water volume in lakes using the combination of imagery and altimetry data.…”

Section: H M Ebaid M Aziz Journal Of Geographic Information Systemmentioning

confidence: 99%

Integrating Radar Altimeters and Optical Imagery Data for Estimating Water Volume Variations in Lakes and Reservoirs (Case Study: Lake Nasser)

Ebaid¹,

Aziz²

2017

JGIS

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Monitoring of variations in water for lakes and reservoirs is a requirement for meeting human needs and assessing ongoing climatic changes. However, regular gauging networks fail to provide the information needed for water volume data. The aim of this study is to evaluate an approach to estimate water volume variation for the southern part of Lake Nasser in Egypt without in-situ gauge measurements and bathymetry maps. Combination of both Hydroweb satellite altimetry and Landsat 8 satellite imagery data was used. As compared to in-situ water levels, satellite altimetry provided accurate water levels variations for Lake Nasser; the RMSE was 0.28 m, with excellent agreement (R 2 is 0.98). The lowest water level of altimetry database i.e. 174.57 m was used as a reference level for estimating water volumes variations for the study duration 8/2014-6/2015. All water altimetry levels were converted to differences of recorded water level above the lowest altimetry Level (∆WL). Series of Landsat 8 imagery data were selected to extract surface areas corresponding to radar altimetry water levels dates. Areas-∆WL relationship model was established as a polynomial function: A = f(∆WL), and therefore, the relationship of the water volume above the lowest water level for the study time (∆V) and ∆WL was obtained through the analytical integration of (Area-∆WL) model. Another approach (Heron method) was also applied for estimating water volume variations. Validation of these two approaches showed that estimated water volume variations above reference water level using both methods i.e. integration and Heron agreed well with in-situ measurements of volume variation deduced from recent bathymetry map and in-situ water levels (R 2 for both methods = . Another byproduct for these approaches was the modeling for a remote detecting water level. Once the F(L) relationship is set up for a given region, future Landsat images can be utilized to track water levels freely of radar altimetry. Finally it can be concluded that remote sensing resources (satellites radar altimeters and optical satellite images) that are openly accessible these days represent a great opportunity to remotely monitor reservoir water capacity and help in examining and observing hydrological and water driven procedures.

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Surface freshwater storage and variability in the Amazon basin from multi‐satellite observations, 1993–2007

et al. 2013

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show abstract

Satellite-based estimates of groundwater storage variations in large drainage basins with extensive floodplains

Cited by 77 publications

References 37 publications

Surface Freshwater Storage Variations in the Orinoco Floodplains Using Multi-Satellite Observations

Surface Freshwater Storage Variations in the Orinoco Floodplains Using Multi-Satellite Observations

Integrating Radar Altimeters and Optical Imagery Data for Estimating Water Volume Variations in Lakes and Reservoirs (Case Study: Lake Nasser)

Surface freshwater storage and variability in the Amazon basin from multi‐satellite observations, 1993–2007

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