How Does Human Activity in Watersheds Affect the Water Quality of Lakes?
How does human activity in watersheds affect the water quality of lakes?
Water is a vital resource that sustains all living things. In Michigan, people value this abundant resource and are attractive to the thousands of inland lakes which provide aesthetic, as well as recreational opportunities throughout the year. The health of our lakes is directly impacted by the amount of recreational use they receive, shoreline development, and water quality. Water quality covers many aspects of lake chemistry and biology. Both natural and man- made features of watersheds impact the quality of aquatic habitats. Examining the relationship between land use and water clarity in lakes can help us to understand what negatively impacts the health of our lakes. This in turn will lead us to finding solutions to improve and maintain the quality of our lakes and waterways. I expect aquatic habitats in watersheds with more man-made features to have lower water quality and clarity. I expect this because runoff from man-made features will contain chemicals and particles that reduce clarity through biological and physical processes. Begin the lab by saving the 12 maps of the six lakes (six color coded by land use and the same six in grayscale) along with a Legend file on the website. The Legend file explains the color coding of land uses in the map files. Open up each map and Legend in the ImageJ program and move the mouse cursor over the different areas of the grayscale image and looking in the Menu window, a numerical value (between 0 and 255) for each level of gray can be determined. A list of numerical values was obtained for each color image by comparing the numerical value in the grayscale image with the corresponding color image. By using the Legend. it was possible to match the numerical values to each land use type and then determine the area of each land use type in the grayscale image. Take the maps that are in black and
Water is a vital resource that sustains all living things. In Michigan, people value this abundant resource and are attractive to the thousands of inland lakes which provide aesthetic, as well as recreational opportunities throughout the year. The health of our lakes is directly impacted by the amount of recreational use they receive, shoreline development, and water quality. Water quality covers many aspects of lake chemistry and biology. Both natural and man- made features of watersheds impact the quality of aquatic habitats. Examining the relationship between land use and water clarity in lakes can help us to understand what negatively impacts the health of our lakes. This in turn will lead us to finding solutions to improve and maintain the quality of our lakes and waterways. I expect aquatic habitats in watersheds with more man-made features to have lower water quality and clarity. I expect this because runoff from man-made features will contain chemicals and particles that reduce clarity through biological and physical processes. Begin the lab by saving the 12 maps of the six lakes (six color coded by land use and the same six in grayscale) along with a Legend file on the website. The Legend file explains the color coding of land uses in the map files. Open up each map and Legend in the ImageJ program and move the mouse cursor over the different areas of the grayscale image and looking in the Menu window, a numerical value (between 0 and 255) for each level of gray can be determined. A list of numerical values was obtained for each color image by comparing the numerical value in the grayscale image with the corresponding color image. By using the Legend. it was possible to match the numerical values to each land use type and then determine the area of each land use type in the grayscale image. Take the maps that are in black and
Bibliography: Water quality data for these lakes can be obtained from the Michigan Department of Environmental Quality website. For this analysis of water clarity, parameters of Secchi disk, total Phosphorous (Spring data), and Chlorophyll (mean) were used.