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WATER QUALITY MODELING OF THE OLD WOMAN CREEK WATERSHED, OHIO, UNDER THE INFLUENCE OF CLIMATE CHANGE TO YEAR 2100

OLAOYE, ISRAEL A
http://rave.ohiolink.edu/etdc/view?acc_num=kent1605955492844115

Abstract Details

2020, PHD, Kent State University, College of Arts and Sciences / Department of Earth Sciences.
A comprehensive analysis was carried out on the Old Woman Creek (OWC) watershed to determine the impact of the projected land use and climate change on the flow and water quality variables of the OWC watershed. The analysis was done in different stages using remote sensing, machine learning, and hydrological modeling. The hydrological model was set up in Soil and Water Assessment Tool (SWAT), using PRISM climate data and 20 Coupled Model Intercomparison Project Phase 5 (CMIP5) data. The model was calibrated using a Multi-Objective Evolutionary Algorithm and Pareto Optimization and was validated using the streamflow data from the USGS gage station, at Berlin Road in the OWC watershed, and water quality data from the water quality laboratory, Heidelberg University, Tiffin, Ohio. Machine learning (ML), Cellular automata (CA) Markov modeling, and overlay analysis were used to analyze the historical land use/land cover (LULC) of OWC watershed for 2001, 2011, and 2016, to predict the same at intervals across the 21st century, and to locate the zones that are susceptible to flood and drought. Simulations were made for the years 2030, 2060, 2088, and 2100. A significant increase in flood risk was observed to be associated with the projected urban growth, while an insignificant increase was observed for the drought risk zones by the end of the century. The impact of agricultural practices in the watershed on flow and nine water quality variables in the watershed was evaluated using the calibrated model, by conducting land use Scenarios simulations with varying percentages of agricultural land from 20% to 40%, 53.5%, 65%, and 80%. Analysis consisting of 105 simulations with both PRISM and 20 CMIP5 models was run for the period 2015-2017. The average of the 20 CMIP5 simulation results shows good agreement with the PRISM simulation results. A weak negative correlation was observed between each of streamflow and sediment, and agriculture land, while a strong positive correlation was observed between agricultural land and other water quality variables. The separate and synergistic effect of the projected LULC and climate change in the 21st century on flow and nine water quality variables was evaluated using the calibrated model, by conducting annual simulations in two land-use Scenarios: Scenario 1 for constant land use, and Scenario 2 where land use was varied. The simulations for the two Scenarios were run in four time periods to account for climate change: historical (1985-2014), current to near future (2018-2045), mid-century (2046-2075), and late-century (2076-2100) climate windows. The relationship between the results obtained for Scenarios 1 and 2 shows that the effect of the projected land-use change is of a little impact compared to the effect of the projected climate change on the water quality variables. The effect of the projected 21st-century seasonal variation in climate change on flow and the same water quality variables was evaluated using the calibrated hydrological model, by conducting monthly simulations with both PRISM data, and the best three CMIP5 models for the four stated climate windows. For the historical period, the average of the best three CMIP5 results shows similar trends with PRISM simulation results for all variables. For the other climate windows, a progressive increase across the climate windows was observed for all the water quality variables in the Fall, Winter, and Spring. In the Summer, a decrease was observed within each climate window, while a small increase was observed across all the climate windows, for all the water quality variables. The projected increase in flow and other variables have implications for water quality, and the general health of the OWC estuary. The projected climate change would worsen the water quality in both the OWC watershed and Lake Erie. The knowledge obtained from this analysis can be applied to similar agricultural watersheds with point source pollutants across the world.
Joseph Ortiz (Advisor)
217 p.
Agriculture; Area Planning and Development; Artificial Intelligence; Environmental Geology; Environmental Studies; Geology; Hydrologic Sciences; Hydrology; Land Use Planning
PRISM; CMIP5; Multi-Objective Evolutionary Algorithm and Pareto Optimization; Machine learning; Cellular automata

Recommended Citations

Citations

  • OLAOYE, I. A. (2020). WATER QUALITY MODELING OF THE OLD WOMAN CREEK WATERSHED, OHIO, UNDER THE INFLUENCE OF CLIMATE CHANGE TO YEAR 2100 [Doctoral dissertation, Kent State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=kent1605955492844115

    APA Style (7th edition)

  • OLAOYE, ISRAEL. WATER QUALITY MODELING OF THE OLD WOMAN CREEK WATERSHED, OHIO, UNDER THE INFLUENCE OF CLIMATE CHANGE TO YEAR 2100 . 2020. Kent State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=kent1605955492844115.

    MLA Style (8th edition)

  • OLAOYE, ISRAEL. "WATER QUALITY MODELING OF THE OLD WOMAN CREEK WATERSHED, OHIO, UNDER THE INFLUENCE OF CLIMATE CHANGE TO YEAR 2100 ." Doctoral dissertation, Kent State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=kent1605955492844115

    Chicago Manual of Style (17th edition)

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This open access ETD is published by Kent State University and OhioLINK.