To collect data required for development, estimation, calibration, validation, and simulation of the landscape model
To Develop and estimate a land use change model for the Sandusky study area
To develop and apply an ecological unit module and habitat switching algorithm for the Sandusky watershed
To analyze collected data to determine feasibility of complete watershed model
To demonstrate the utility of past landscape models to local officials, extension agents (Sea Grant and OARDC), and community groups to illustrate benefits of developing similar models for Great Lakes watersheds. This project supports the initial stages in the development of a spatial watershed model to quantify habitat and water quality dynamics in coastal areas of Lake Erie that result from changes in government policy that influence land use. An essential portion of the watershed model, the hydrodynamic module, will be incorporated in a following research project. This stage of the research will focus on modeling a particular watershed and estuary within the Lake Erie basin – the Sandusky watershed and bay. After demonstrating the benefits of the predictive, spatial model for this watershed, similar models will be developed for other drainage basins and coastal zones within the Great Lakes.

Spatially explicit models that link policies to land use changes and land use changes to environmental changes are necessary for evaluating the impacts of existing and proposed policies. By establishing and quantifying these linkages, the model will elucidate the environmental and economic trade-offs of governmental policies that impact coastal water quality and habitats. When the interaction of multiple factors must be considered and temporal and spatial scales are extended, new tools, which account for these phenomena are needed. Watershed spatial models are tools that explicitly incorporate system processes and relationships across spatial and temporal boundaries, allowing the identification of short and long-term impacts of proposed land use policies. By developing and applying watershed models evaluations that span relevant spatial and temporal boundaries will allow short-term economic gains of development to be compared with eroded soils and the eutrophication of downstream water bodies. Consequently, the watershed models will be capable of analyzing the effects of government policies that may require ten or twenty years to fully impact the landscape and have far-removed consequences. Because the costs to develop a complete model are large, an initial study is warranted to collect and analyze data and develop and apply the land use/change and ecological modules. This is a challenging and technical project that can be carried out only with an integrated research team with a successful record of using spatial models in coastal environments. Specializations of the team include policy-landscape interactions, evaluation of management plans with spatial models, hydrodynamics, and wetland ecology.

Landscape models integrate ecosystem processes and human decisions across spatial and temporal scales and test assumptions by activating the mechanisms of each process and relationship at each time step, throughout the entire watershed. This is accomplished with a grid of landscape cells, each containing an ecological unit model, that are connected via fluxes of water, nutrients, sediments, and other materials transported across a landscape. The causality in this watershed model will begin with the land use change module. This component will predict human land use change based on a spatially explicit economic model that estimates land use change as a function of economic, demographic, political, and ecological variables. Changes in land use types in conjunction with climate variables will alter inputs to rivers within the watershed. A hydrodynamic module will later be incorporated to simulate the transport of water and materials from the watershed, through rivers, to the coastal zone. The hydrodynamic module will also transport sediment, nutrients and water across the coastal zone. The ecological unit module will respond to hydrologic and climate inputs and predict the effects of altered river inputs upon coastal ecosystems. This module will simulate edaphic and vegetative processes in each cell with coefficients specific to each habitat type. A habitat-switching algorithm will then be used to determine changes in habitats by monitoring fluctuations in state variables, such as vegetative biomass and water level. The first objective will be to collect and process the timeseries data required for this project. This includes historical records of climate (i.e. rain, wind, and temperature) and hydrology (i.e. lake level, river flow, and water quality) to serve as forcing functions and boundary conditions. Objective two will gather historic and present spatial data sets including habitat and land use maps. Calibration and validation of the completed model rely on habitat maps. The land use change model will be developed by generating GIS maps of demographic, economic, and environmental data within the watershed. Once these data are in place, a land use change model, similar to the model currently under development for Medina County in the Rocky River watershed, will be developed and estimated. This model will estimate the probability of conversion to an urban use as a function of accessibility to urban centers and towns; quality of public infrastructure and services, including schools, roads, and public sewer service; and physical and environmental features of the landscape, including existing land cover, slope, and soil type. An ecological unit module (task 3) will simulate the effects of climate, hydrology, and water quality on vegetative and soil process in each cell. Variations of this module specific to each land use and habitat type will be parameterized and calibrated using data from past projects of the investigators and data from a review of relevant literature. Feasibility of a complete watershed model (task 4) will be based on the extent of historical and present spatial and timeseries data. At a minimum, three sets of habitat and land use maps with associated timeseries data are required for calibration and validation. Meetings will be held with stakeholders throughout this project (task 5) to explain the functioning and justify the development of watershed models for Great Lake tributaries and associated coastal zones

Ecological unit model: Ecological unit models have been developed for several land use habitats, including forestry, wetlands, and cropland. Data have been collected from the literature to parameterize these models. Computer simulation results to-date show that the forestry model performs very well, predicting biomass growth with 94% accuracy. The remaining ecological unit models have not yet been simulated. This portion of the research will result in a Masters thesis in the Department of Food, Agricultural, and Biological Engineering.

Data: A variety of data have been gathered to support the development of both the ecological unit models and the land use change models. A student with expertise in remote sensing was employed for Winter and Spring 03 quarters to classify remotely sensed LandSat satellite images of land cover/land use for the seven county study region for 1984 and 2000. Zoning data are in the process of being collected on paper maps and transformed into electronic data using GIS digitizing techniques. Other data include a variety of GIS layers, including 1992 land cover/land use data, hydrology, floodplains, roads network, and a variety of Census data that describes population and socioeconomic and demographic characteristics at the block group level.

Land use change model: A theoretical model that explains sprawl in terms of leapfrog development as the result of congestion externalities has been developed. Results from this theoretical model describe the conditions under which leapfrog development occurs as the result of congestion from existing development in a local area and examine the role of rising incomes in generating sprawl. The model has generated several testable hypotheses regarding the evolution of sprawl patterns of development, including:

• Scattered development can arise from "interactions" among peoples' decisions regarding where to locate.
• Increases in income lead to temporary increases in scattered development.

In addition, an empirical model of residential land use change was estimated using parcel-level data from Erie County, Ohio from 1990-2003. The major findings from this model are:

• Proximity to the Lake, proximity to rivers increase likelihood of rural land conversion to residential land use. Specifically, a marginal increase in proximity to lake increases a parcel's likelihood of conversion by 8%.
• Proximity to highways and roads decrease likelihood of conversion to a residential land use.
• Proximity to Cleveland, Toledo and Norwalk increase likelihood of conversion whereas proximity to Sandusky decreases likelihood.
• Residential zoning restrictiveness (specifically, minimum lot size) deters rural land conversion. Specifically, a marginal increase in min lot size decreases probability of conversion by 4%.
• The amount of development in a local neighborhood around a land parcel has a significant effect on its zoning. Specifically, more development lessens the zoning restrictiveness. This result indicates that zoning "follows the market" rather than providing a strict constraint on development.

The land use modeling portion of the project supported two graduate students who completed Masters theses in the Department of Agricultural, Environmental and Development Economics.