TITLE:
Hydrological Variability from Gauging Stations and Simulated SWOT Data, for Major French Rivers
AUTHORS:
L. Chevalier, B. Laignel, I. Turki, F. Lyard, C. Lion
KEYWORDS:
Hydrological Variability, Discharge, SWOT, Watershed, Wavelet Analyses
JOURNAL NAME:
Journal of Geoscience and Environment Protection,
Vol.5 No.13,
December
29,
2017
ABSTRACT: This study was carried out under the aegis of the program Surface Water and Ocean Topography (SWOT) associated with the National Center of Space Studies (CNES). The future SWOT mission will offer new opportunities to survey the hydrodynamic in the rivers because it will provide data on the water level/ discharges with a high spatial resolution (oceans: 1 km, rivers: 100 m of width) and with a global cover. However, it is important to estimate the capacity of SWOT to reproduce the hydrodynamic phenomena in the estuaries and the temporal and the spatial variability of this dynamic. The aim of this paper is 1) to estimate the capacity of SWOT to reproduce the hydrological variability of watersheds, and 2) to validate the use of these data for other zone without hydrometric station. Based on discharge measurements and simulated Surface Water and Ocean Topography (SWOT) data, we have investigated the hydrological variability of the main French rivers (Seine, Loire, Garonne and Rh?ne) by applying a series of statistical analyses to the discharge time series. A frequency analysis has been also used using a technique of wavelet. Results have shown a similar hydrological variability of the four watersheds. Three different periods of hydrologic variability has been identified: before 1970, between 1970 and 1990, and after 1990. Using these analyses, simulated SWOT samples and discharges were compared during the three studied periods. Simulated SWOT data, obtained by a synthetic sampling of river discharges basing on the number of measurements per repeat orbit, reproduce the hydrological variability of rivers. Such reproduction seems to be independent in the number of SWOT passages (from two to four), except for the minimum and maximum annual discharges where number of overpass seems to have an influence. These results were validated by coherence wavelet which underlines coherence higher than 90% between simulated SWOT data and in-situ discharges. Nevertheless, good correlation was not observed for the minimum and the maximum annual discharge with an underestimation for SWOT maximum annual and an overestimation of the minimum annual SWOT ones. Moreover, best identification of minimum, mean and maximum annual discharge depends on SWOT overpasses.