Rapid increasing of renewable energies and the knowledge about their environmental effects are very limited. As a result, the renewable energies (e.g. solar or wind energies) will play a vital role in the future because it is well accepted by environmental friendly industries. This dissertation presents the modeling, data analysis and field experiment, developed for investigation of the interactions among microclimatological factors, land characteristics and solar/wind renewable energy production systems. The research covers multi scales from high resolution farm scales (six acres’ area), mid-size large wind farms and global scales. The main idea of this research is to study the environmental impacts of renewable energies which affect the water resources and therefore the water, food and energy nexus. This research studies how renewable energy can change the water use efficiency, biomass production, energy efficiency and ultimately relates it to sustainable development. Selecting the best location, crop and climate for renewable energy is an important key component in obtaining a sustainable development.
The first part of the dissertation includes an experimental observation study on the effects of solar panel on the adjacent microclimate and vegetation. The field study setup included installations of local weather stations and soil moisture neutron probes to monitor the microclimatological and moisture variations. The monitoring was performed both between solar arrays and outside the area (control area). The data showed that (1) the soil moisture under panels are significantly higher than the control area, (2) dry biomass of grass is higher under panels and (3) the area under panels were significantly more water efficient. The investigations on the grass species under agri-voltaic panels reveals a significant increase in late season biomass (90% more biomass) and areas under PV panels were significantly more water efficient. This is accomplished by harvesting solar excess and converting it to electricity.
Secondly, an algorithm developed using the first law of thermodynamics and solar panel efficiency solved for the energy balance equation. Solar panel efficiency found as a function of microclimatological factors include radiation, temperature, relative humidity and wind speed. The validated algorithm was then applied to the global scales. The computations of efficiencies shows the most efficient geographical locations for solar panel installations based on micro-environmental factors, but also a more generalized methodology to relate potential efficiency to land cover.
The third part of the thesis assess the crop yield and water use efficiency of major crops grown in Oregon, considering three shade levels 90%, 75% and 50%. AquaCrop model was used to evaluate the potential water use efficiency in Oregon. Our results show there is no difference in yield when shade is applied but the amount of water needed for irrigation is reduced. The biomass results showed no gain or loss occurs in different shade levels but there is a difference in the amount of irrigated water.
The forth part of the dissertation relates to the interactions of the wind turbines with farm lands. A numerical framework was developed to process the wind farm LANDSAT snap shots before and after the wind turbine installations. The numerical scheme was developed using Mapping Evapotranspiration at high Resolution with Internal Calibration (METRIC) and can calculate and analyze evapotranspiration on the agricultural field and analyze the resulted pixel-based data. From the data analyses on Fowler wind farm (located in Indiana, US) approximately 10% more evapotranspiration was seen in agricultural fields that are co-located near wind turbines (i.e. footprints) compared to places that have no wind turbine.