The purpose for the establishment of the research and monitoring program. At OWC estuary was to provide additional knowledge to what we know about the Great Lakes estuarine system and particularly, the OWC estuary. The huge volume of research being carried out. Would provide information for different stake holders such as the resource management agencies and government bodies interested in coastal management. The knowledge and facts established will aid decision making in town planning, waste management, waterway management and land use and development.
This research is aimed at developing land use/land cover and climate change monitoring scheme for the OWC watershed and estuary. It involves the use of CA-Markov model and artificial intelligence to study the past. And project the land use/ land cover of OWC watershed into the future. The use of hydrological modeling in SWAT to simulate the response of 10 important hydrological variables. To different agricultural management practices, changes in the projected land use/ land cover. Changes in the projected climate using the GCM climate models and changes in the climate seasonal pattern. This aim is addressed in 4 different chapters.
In chapter 2, the land use/ land cover changes of OWC watershed was studied from the previous years (2000-2100). The CA-Markov model and Multilayer perceptron (MLP) neural networks approach was used for land use change projection into the future (2016 -2100). Overlay analysis in GIS was used for drought and flood zone prediction.
In Chapter 3, hydrological model was created for OWC watershed, the model was calibrated using multiobjective algorithm developed by Confessor and Whittaker 2007 and validated using measured daily data from the USGS gauge station at Berlin Road in OWC. The response of the 10 hydrological variables to different agricultural land use percentages between 2015- 2017 was simulated using PRISM and the 20 CMIP5 model and the average of the 20 CMIP5 results compared to PRISM results.
In chapter 4, the impact of the predicted land use and climate change for the OWC watershed on the estuary was evaluated using 10 hydrological variables under 2 Scenarios across 4 climate windows. 20 CMIP 5 model were used to simulate the PRISM result for the past climate window (1985 – 2014) and it was found that the average of the 20 CMIP5 results is a good predictor of PRISM result. 20 CMIP 5 model were used for the simulation of 10 hydrological variables for the current and future climate windows.
In chapter 5, the performance of each of the 20 CMIP5 model was tested using Euclidean distance relative to their average and the best 3 models for the OWC watershed selected for seasonal variation analysis. The average of 3 CMIP5 was compared to the PRISM result for the first climate window and the selected CMIP5 models used for the simulation of 10 hydrological variables for the current and the future climate windows.
The land use/ land cover of OWC watershed was predicted to change slightly throughout the 21st century except if there is an interruption of the current trend by an unexpected government policy. A reduction of about 3.6 % in agricultural and an increase of 2.38 % in urbanization were simulated for the last climate window relative to the first. The area prone to flooding is expected to increases from 3.4% to 10.4% and the area prone to drought is expected to increases from 3.5% to 5.7% by the last climate window.
The average of the 20 CMIP5 results is consistent with PRISM results for the OWC watershed. Changes in agricultural land use does not affect flow significantly. Flow is controlled mainly by precipitation and nutrient transport is mainly controlled by nutrients availability. Increase in agricultural land creates more space for infiltration thereby reducing flow and sediment transport and increases nutrient transport due to more quantity of fertilizer available. This indicates that a reduction in flow can be associated with high nutrient concentration.
The average of the 20 CMIP5 results is consistent with the PRISM result for the OWC watershed as established in the simulations for the past climate window. The variability in CMIP5 result is small being the average of 20 results compared to the PRISM which is one result.
The projected changes in land use / land cover in OWC watershed is expected to lead to increase in flow. The reduction in agricultural land would make less land available to infiltration thereby increasing flow and the increase in urbanization would increase runoff. The projected land use change was simulated to increase sediment and nutrient transport to the estuary. The effect of land use change increases across the climate windows.
The projected increase in precipitation and temperature is expected to increase flow across the climate windows, flow drives the sediment and nutrient transport but not mineral P. The additive effect of both land use change and climate change would result in higher flow and nutrient transport across the climate windows. The effect of land use represents little measurable impact compared to that of climate change.
The three best CMIP5 models (GFDL-ESM2M, MPI-ESM-MR, EC-EARTH) were used for seasonal analysis which was done in the past, current and future1 and future 2 climate windows (1985 -2014, 2018 -2045, 2046 -2075 and 2076 -2100). The results for the average of the best 3 CMIP5 model are consistent with the PRISM result.
The observed seasonal streamflow pattern is consistent across the four climate windows and peak flow, sediment transport and nutrient transport season predicted to shift from Winter to Spring.
From climate windows 1 to 4, hydrologic variables including Organic nitrogen, Organic P, Mineral P, Chlorophyl a, CBOD and total P have two peaks in winter ans Spring which collapses into one in climate window 4 with the dissapperance of winter peak. The projected seasonal and annual changes in the hydrologic variable over the 21 st century would impact algae growth and the health of the OWC estuary and Lake Erie.
The projected increase in temperature would increase the water vapor in the atmosphere thereby increasing the frequency of high precipitation. The projected increase in precipitation would drive high flow, nutrient and sediment transport. The projected increase in urbanization and decrease in agricultural land would increase flow. The additive effect of climate change and land use change would lead to high flow, high nutrient transport, high CBOD and high dissolved oxygen. More preparation and attention should be given to the predicted high flow.
The nutrient transport would drive more eutrophication which would further deteriorate the water quality. The organic waste in the estuary would increase and decompose by bacteria leading to the increase in CBOD and dissolved oxygen level predicted across the climate windows. High CBOD and dissolved oxygen would harm aquatic life and water quality. This implies a likely loss in aquatic resources and more tedious and resource driven water purification system for the community.
