An overwhelming majority of anthropogenic climate change studies have placed emphasis on biogeochemical agents, chiefly carbon dioxide emissions, which operate on a global scale. Fewer studies focus on biophysical factors such as land use/ land cover which operate on a regional or local scale. The impact from biophysical factors will continue to be reinforced with a growing human population and expanding resource demands. Of these factors, agricultural land use represents one of the largest, most extensive, and vital land use allocations.

The U.S. Midwest, dominated by rain-fed corn and soybean agriculture, is a key agricultural region which is lacking in studies exploring climate impacts. Potential increases in soil moisture availability combined with modern agricultural practices has resulted in the anthropogenic elevation of surface humidity and dew point temperature within this region. Commensurate with this change is a modification of surface energy balances resulting in decreased daily temperature ranges from diurnal cooling and elevated nocturnal minimums. Increased atmospheric moisture also has a direct effect on human comfort through a decrease in evaporative cooling capacity.

An updated 61 year regional growing season climatology from 59 NWS first order stations of dew point temperature, minimum/maximum temperature, and vapor pressure deficit provides evidence of land use impacts on regional and local climate factors. Significant increases in dew point (1-2°F), focusing on the Midwest, have been identified. Further, these increases have not been found in the U.S. South which is the typical source region for advected atmospheric moisture into the Midwest, thus indicative of a localized moisture source. Examination of historic USDA agricultural statistics aids in the understanding of potential contributions from land use on surface humidity. Further, 2017 field work provides a current multi-level canopy model of transpiration rates for regionally grown corn and soybeans with considerations for several controlling environmental variables. This has allowed accurate up-scaling to field levels for prediction of overall atmospheric moisture contributions at determined mid-day transpiration maximums over the course of the 2017 growing season.


Martin Mitchell

Committee Member

Fei Yuan

Committee Member

Christopher Ruhland

Date of Degree




Document Type



Master of Science (MS)


Social and Behavioral Sciences

Creative Commons License

Creative Commons Attribution-NonCommercial 4.0 International License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License



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