Evaluating water quantity and quality of Canadian Great Lakes Watershed using LTHIA GIS Model

The Great Lakes, also known as the Great Lakes of North America, are a series of interconnected freshwater lakes located in the upper mid-east region of North America located at the border of Canada and the United States of America (USA). The Great Lakes are a source of drinking water for 10% of Ame...

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Veröffentlicht in:Canadian biosystems engineering 2023-12, Vol.65 (1), p.1-1.16
Hauptverfasser: Paul, Pranesh Kumar, Brar, Taranjot Singh, Daggupati, Prasad, Rudra, Ramesh, Goyal, Pradeep
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Sprache:eng ; fre
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Zusammenfassung:The Great Lakes, also known as the Great Lakes of North America, are a series of interconnected freshwater lakes located in the upper mid-east region of North America located at the border of Canada and the United States of America (USA). The Great Lakes are a source of drinking water for 10% of Americans and 25% of Canadians. Human activities have significantly degraded the Great Lakes in the past few decades. Against this backdrop, conducting a detailed study to assess the water quality and its quantification in the Canadian Great Lakes Watershed (CGLW) seems imperative. This study used the LTHIA model to analyze the surface runoff and two Non-Point Source pollution – total suspended solids (TSS) and total phosphorus (TP) of the Canadian Great Lakes watershed. The temporal analysis showed the highest runoff, TSS and TP in the Northern Lake Erie sub-watershed in 1954. In contrast, the lowest was observed in the Northwestern Lake Superior sub-watershed in 1952. The spatial analysis showed higher runoff, TSS and TP in the Eastern Lake Huron and Northern Lake Erie sub-watersheds. The decadal analysis revealed higher runoff, TSS and TP in 1980-90, 1990-99 and 2000-09. The climate change analysis revealed more variation in the runoff, TSS, and TP were projected in mid-century (2035-64) compared to end-century (2070-99). Finally, it has been shown that the LTHIA model can successfully simulate both water quantity and quality-related processes and climate change effects.
ISSN:1492-9058
1492-9066
DOI:10.7451/CBE.2023.65.1.1