SOLS: A lake database to monitor in the Near Real Time water level and storage variations from remote sensing data

Crétaux, J.; Jelinski, W.; Calmant, Stéphane; Kouraev, Alexei V.; Vuglinski, V.; Bergé-Nguyen, Muriel; Gennero, M. C.; Niño, Fernando; Río, R. Abarca del; Cazenave, Anny; Maisongrande, Philippe

doi:10.1016/j.asr.2011.01.004

Cited by 603 publications

(451 citation statements)

References 30 publications

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“…Regular and accurate monitor of variations in water for lakes and reservoirs would be necessary for equitable allocation of water and for a better understanding of the impact of climate change [1] [2] [3]. The traditional method of measuring water level is by gaging station installed near river mouths, bridges, weirs and sluices.…”

Section: Introductionmentioning

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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Section: Introductionmentioning

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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“…Birkinshaw et al [28] Table 2 We could not compare our results with data from the GLRM [11] or Hydroweb [9] databases, because no common virtual stations are available. In the ESA River and Lake database [5] …”

Section: Comparison With Other Altimetry Productsmentioning

confidence: 84%

Treating the Hooking Effect in Satellite Altimetry Data: A Case Study along the Mekong River and Its Tributaries

et al. 2016

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This study investigates the potential of satellite altimetry for water level time series estimation of smaller inland waters where only very few measurements above the water surface are available. A new method was developed using off-nadir measurements to estimate the parabola generated by the hooking effect. For this purpose, a new waveform retracker was used as well as an adopted version of the RANdom SAmple Consensus (RANSAC) algorithm. The method is applied to compute time series of the water levels height of the Mekong River and some of its tributaries from Envisat high-frequency data. Reliable time series can be obtained from river crossings with widths of less than 500 m and without direct nadir measurements over the water. The expected annual variations are clearly depicted and the time series well agree with available in situ gauging data. The mean RMS value is 1.22 m between the resulting time series and in situ data, the best result is 0.34 m, the worst 2.26 m, and 80% of the time series have an RMS below 1.5 m.

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“…Its beam footprint width is about 3.5 km. The radar altimetry dataset used in this study is the one available on Hydroweb (Crétaux et al, 2011). The Envisat radar altimetry dataset covers several large rivers, lakes and floodplains within the Amazon basin, being composed of over 1500 VS. After selection of VS located over rivers with sufficiently long and consistent time series, 475 VS remained (see Fig.…”

Section: Envisat Altimetry Datamentioning

confidence: 99%

“…A recent effort in acquiring altimetric data resulted in an unprecedented radar altimetry dataset at several hundreds of virtual stations over the main lakes, rivers and tributaries on the planet (http://www.legos.obs-mip.fr/soa/hydrologie/ hydroweb/), hereafter called the Hydroweb dataset (Crétaux et al, 2011). In addition, recent studies have focused on the development of more precise global modeling systems capable of simulating continental water fluxes (e.g.…”

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confidence: 99%

Estimating water discharge from large radar altimetry datasets

Getirana

Peters‐Lidard

2013

Hydrol. Earth Syst. Sci.

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Abstract. The objective of this study is to evaluate the potential of large altimetry datasets as a complementary gauging network capable of providing water discharge in ungauged regions. A rating curve-based methodology is adopted to derive water discharge from altimetric data provided by the Envisat satellite at 475 virtual stations (VS) within the Amazon basin. From a global-scale perspective, the stage-discharge relations at VS are built based on radar altimetry and outputs from a modeling system composed of a land surface model and a global river routing scheme. In order to quantify the impact of model uncertainties on rating-curve based discharges, a second experiment is performed using outputs from a simulation where daily observed discharges at 135 gauging stations are introduced in the modeling system. Discharge estimates at 90 VS are evaluated against observations during the curve fitting calibration (2002)(2003)(2004)(2005) and evaluation (2006)(2007)(2008) periods, resulting in mean normalized RMS errors as high as 39 and 15 % for experiments without and with direct insertion of data, respectively. Without direct insertion, uncertainty of discharge estimates can be mostly attributed to forcing errors at smaller scales, generating a positive correlation between performance and drainage area. Mean relative streamflow volume errors (RE) of altimetry-based discharges varied from 15 to 84 % for large and small drainage areas, respectively. Rating curves produced a mean RE of 51 % versus 68 % from model outputs. Inserting discharge data into the modeling system decreases the mean RE from 51 to 18 %, and mean NRMSE from 24 to 9 %. These results demonstrate the feasibility of applying the proposed methodology to the continental or global scales.

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SOLS: A lake database to monitor in the Near Real Time water level and storage variations from remote sensing data

Cited by 603 publications

References 30 publications

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

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

Treating the Hooking Effect in Satellite Altimetry Data: A Case Study along the Mekong River and Its Tributaries

Estimating water discharge from large radar altimetry datasets

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