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Groundwater Protection Model at Niagara Using GIS Tools

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posted on 08.06.2021, 12:20 by Mafruha Ahmed
Groundwater is the safest and most reliable source of available freshwater. Although traditionally groundwater has been assumed to be free from contamination, numerous discoveries, in recent years of toxic chemicals in well water have proven this assumption to be false. Groundwater contamination from chemical dump sites tends to attract the greatest public attention, but contamination from other sources such as septic systems, pesticides, and underground storage tanks also can be significant. Intensive agriculture in areas of high soil permeability and high water tables also causes groundwater contamination from the percolation of chemicals and nutrients through the soil profile. Protecting groundwater resources from pollution is therefore essential for its proper management and preventing probable hazards. Groundwater vulnerablility assessment is an issue of spatial distribution and therefore typically carried out using geographic information systems (GIS). Even when using a simple qualitative method, the complex processing of spatial information is completed faster using GIS Models are tools to simulate the behavior of physical systems. They can predict the future evolution of the systems, they can be used as interpretative tools in order to study system dynamics and they can give hints for data collection and design of experiments. Models are sometimes used to examine the evolution of generic natural systems, without a specific application to a definite site or population. ArcGis 9 provides new tolls to build protection model to study grounwater contamination isues of various watersheds that performs multiple geoprocessing operations. The study articulates the most vulnerable locations of Niagara for groundwater contamination, what geospatial data are needed to support these resource assessment activities, and how GIS tools are required to facilitate the generation of a best optimized model.





Civil Engineering

Thesis Advisor

Songnian Li