Programme  OS4d Remote sensing, DSS and GIS applications  abstract 649

Monitoring of surface water quality in large rivers with satellite imagery

Author(s): Application to the Amazon basin
Author(s): Jean Michel Martinez, Jean-Loup Guyot, Gérard Cochonneau
Institut de Recherche pour le Développement

Keyword(s): Monitoring, water quality, remote sensing, sediment

Article: abs649_article.pdf
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Session: OS4d Remote sensing, DSS and GIS applications
AbstractThe use of satellite images to

monitor inland water quality has been commonly reduced to one shot studies because of the lack of appropriated

remote sensing sensors offering suitable spatial resolution and adequate revisit frequency. Satellite sensors measure

water colour that can be related to the presence of three parameters of interest : inorganic particular material

(sediment), organic particular material (alga) and organic dissolved matter. The monitoring of these elements

encompasses a wide range of application from contaminant transport (trace elements, nutrients, hydrophobic organic

compounds), water quality trends, reservoir sedimentation, lake eutrophication or soil erosion. Over inland waters

the challenge is to retrieve the parameters of interest when the water optical properties are affected at the same time

by the presence of mineral and organic matter at high concentrations.

The present decade has seen the launch

of sensors that propose new tradeoff between spatial resolution and time revisit. In this study we show that recent

sensors such as MODIS and MERIS, by joining fine spectral resolution, high temporal resolution (up to 2 images a

day) and medium spatial resolution (250 to 500 meters) may be used for the monitoring of the water quality of the

largest rivers of the world. In particular we will present and analyze the use of MODIS sensor for the monitoring of

suspended sediment concentration in rivers.

In this presentation we will briefly present the main steps of the

methodology (datamining tools, image feature extraction and generalised inversion techniques) allowing to process

remote sensing images and to produce time series of water quality parameters at different locations in the watershed.

Very high resolution images from SPOT 5 are also investigated in order to assess the potential of the next generation

sensor that will combine such fine resolution with high revisit frequency. The images are analysed over the Amazon

basin that presents a wide variety of hydrologic and geomorphologic conditions and where a large database of

measurements is available from the HYBAM measurement network maintained by the french research Institute IRD

and the local national water agencies.

We will show results on the monitoring of surface suspended sediment

fluxes of the Amazon river over the whole MODIS archive : 2000-2008. Comparisons with in situ data show an

absolute accuracy between 33 and 90 mg/l (about 45 % of relative accuracy). This accuracy is satisfying considering

the tremendous spatial scale difference between in situ measurements (250-millimeter samples) and the satellite data

(assessed from buffers containing hundreds of pixels) and the different time sampling. Impact of some geophysical

and hydrological factors of interest are analysed such as river width, water cycle variability, sediment properties.

Also, the impact of the remote sensing sensor configuration is tested as a function of spatial resolution, radiometric

accuracy and time sampling. These results show that current medium resolution sensors can be used operationnaly

for the monitoring of sediment fluxes in large rivers and that next generation sensors will expand this potential to

medium size rivers and other parameters of interest such as alga concentration.

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