Literature DB >> 35183627

Assessing the current water clarity status of ~100,000 lakes across southern Canada: A remote sensing approach.

Eliza S Deutsch1, Marie-Josée Fortin2, Jeffrey A Cardille3.   

Abstract

Canada has more lakes than any other country, making comprehensive monitoring a huge challenge. As more and more satellite data become readily available, and as faster data processing systems make massive satellite data operations possible, new opportunities exist to use remote sensing to develop comprehensive assessments of water quality at very large spatial scales. In this study, we use a published empirical algorithm to estimate Secchi depth from Landsat 8 reflectance data in order to estimate water clarity in lakes across southern Canada. Combined with ancillary information on lake morphological, hydrological, and watershed geological and landuse characteristics, we were able to assess broad spatial patterns in water clarity for the first time. Ecological zones, underlying geological substrate, and lake depth had particularly strong influences on clarity across the whole country. Lakes in western mountain ecozones had significantly clearer waters than those in the prairies and plains, while lakes in sedimentary rock formations tended to have lower clarity than lakes in intrusive rock. Deep lakes were significantly clearer than shallow lakes over most of the country. Water clarity was also significantly influenced by human impact (urbanization, agriculture, and industry) in the watershed, with most lakes in high impact areas having low clarity or very low clarity. Finally, we used in situ measured data to help interpret the underlying optical water column constituents influencing clarity across Canada, and found that chlorophyll-a, total suspended solids, and color dissolved organic matter all had strong but varying underlying effects on water clarity across different ecozones. This research provides an important step towards further research on the relationship between water column optical properties and the health and vulnerability status of lakes across the country.
Copyright © 2022 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Lakes; Landsat 8 OLI; Secchi depth; Spatial variability; Water clarity

Mesh:

Year:  2022        PMID: 35183627     DOI: 10.1016/j.scitotenv.2022.153971

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  1 in total

1.  Retrieving Inland Reservoir Water Quality Parameters Using Landsat 8-9 OLI and Sentinel-2 MSI Sensors with Empirical Multivariate Regression.

Authors:  Haobin Meng; Jing Zhang; Zhen Zheng
Journal:  Int J Environ Res Public Health       Date:  2022-06-23       Impact factor: 4.614

  1 in total

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