|Paper title||Satellite retrieval and validation of bio-optical water quality products in Ramganga river, India|
|Form of presentation||Poster|
Satellite retrieval and validation of bio-optical water quality products in Ramganga river, India
Veloisa Mascarenhas1*, Peter Hunter1, Matthew Blake1, Dipro Sarkar2, Rajiv Sinha2, Claire Miller3, Marion Scott3, Craig Wilkie3, Surajit Ray3, Andrew Tyler1
1University of Stirling, UK
2Indian Institute of Technology Kanpur, India
3University of Glasgow, UK
In addition to water resources, inland waters provide diverse habitats and ecosystem services. They are threatened however, by unregulated anthropogenic activities and so effective management and monitoring of these vital systems has gained increasing attention over the recent years. Being optically complex waters, inland water remote sensing continues to face challenges underpinning the retrieval of physical and biogeochemical properties. We present here the retrieval and assessment of satellite derived L2 bio-optical water quality products from Sentinel2 and Planet satellites for a highly turbid river system. Bio-optical water quality products including remote sensing reflectance, total suspended matter and chlorophyll-a (Chl-a) concentrations are validated using in situ observations along the river Ramganga, in India. The Ramganga has a large (22,644 km2) diverse catchment, with intensive agriculture, extensive industrial development and a rapidly growing population. The over-abstraction of both surface and groundwater, and pollution due to industrial and domestic waste, mean the Ramganga presents an ideal case study to demonstrate the value of satellite data for monitoring water quality in a highly impacted river system. For the case study, five different atmospheric correction methods are tested in processing the Level 1 Sentinel 2 imagery and a set of biogeochemical algorithms to estimate bio-optical products. Additional bio-optical products such as turbidity are estimated from satellite derived remote sensing reflectance to be matched with in situ turbidity observations. The Sentinel dataset is supplemented using high resolution (3-5 m) imagery from commercial satellite, Planet, processed using ACOLITE atmospheric correction method. The river transect is characterised by high variability in optically active constituents and remote sensing reflectance. Around the Moradabad area, in situ measured turbidity values peak during the month of July while Chl-a concentrations are observed to be highest in early May.