Date of Award


Document Type


Degree Name

Doctor of Philosophy (PhD)


Atmospheric and Earth Science

Committee Chair

Udaysankar Nair

Committee Member

Leiqiu Hu

Committee Member

Kevin Knupp

Committee Member

Jay Land

Committee Member

Rezaul Mahmood


Irrigation--United States, Baroclinic models, Convection (Meteorology)


Agriculture is the most substantial change to the natural land surface made by humans, and irrigation plays a crucial role. Irrigation is utilized for 20% of croplands, and those regions produce 40% of the global food supply. The Great Plains Irrigation Experiment (GRAINEX) deployed to southeast Nebraska during the summer of 2018 to investigate the effects of irrigation on the atmosphere. This dissertation utilizes those observations in conjunction with numerical modeling to determine how irrigation modifies the Great Plains slope wind. Analysis of rawinsondes indicate that irrigation present in upslope regions of the domain weakens the slope wind circulation and eliminates it entirely on some days. Evaluation of virtual temperature profiles and surface energy fluxes shows that this is due to decreased baroclinicity across the GRAINEX domain compared to not-irrigated conditions. Numerical experiments with the Weather Research and Forecasting (WRF) model support this interpretation. Irrigation in the GRAINEX domain also enhances low-level nocturnal jets by stabilizing the boundary layer and decreasing momentum transport towards the surface. Additionally, experiments with the Regional Atmospheric Model (RAMS) indicates that irrigation weakens vertical motions within morning Horizontal Convective Rolls (HCRs) by up to 5% and increases roll spacing by 10%. HCRs are common boundary layer structures that interact with numerous other atmospheric phenomena, including drylines and mesoscale convective systems. In regions where both irrigation and HCRs are prevalent, persistent changes to HCR circulations by irrigation can have diverse impacts on the atmosphere. Understanding the impacts of irrigation on the atmosphere, however, is incomplete without knowing the quantity of water being applied to the region. This dissertation also develops a novel methodology for determining irrigation water application by combining satellite observations of land surface temperature and single-column WRF simulations using machine learning. Comparison of the new methodology to prior maps of irrigation extent show that the new maps are 66% accurate in terms of spatial distribution. Additionally, inputting the estimated irrigation water application into WRF improves simulation of surface energy fluxes and land surface temperature.



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