Hindcasting water quality in an optically complex system

• DOI: 10.2495/wp160041
• Publication Date: 2016-07-11T09:54:43Z
• Authors: C. Hyatt Hansen; P. Dennison; S. Burian; M. Barber; G. Williams
• Keywords: Hindcast; Turbidity

As is the case with many large lakes, field sampling records (and understanding of historical water quality) in Great Salt Lake natural surface system are heavily limited due to time and cost constraints, as well a number independent organizations collecting managing data.To address these deficiencies, remote sensing quality used hind-cast conditions algal blooms GSL (GSLSWS).This unique because its lakes closely connected, yet have widely varying characteristics conditions.An approach for development lake-specific models demonstrated, using Landsat field-sampled data.This study builds on previous studies which broad-spectral data near-coincident samples by evaluating ability accurately estimate under optically complex (such high turbidity shallow conditions).We also examine spatiotemporal variability issue near-coincidence between historic dataset fieldsamples images.Existing campaigns this area do not provide sufficient information about adverse or long-term patterns.Results model application however may useful metrics bloom dynamics, including timing blooms, duration spatial extent how dynamics vary over within system.Products broaden foundation conditions, can be move forward better monitoring management practices.