Monitoring and modeling shelterbelt microclimates and impacts on wheat production - The University of Tulsa
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Monitoring and modeling shelterbelt microclimates and impacts on wheat production

Graduate student Foysal Hasan poses in front of an microclimate monitoring stationFoysal Hasan, a graduate student in Department of Geosciences, is studying the decline of shelterbelts in southwest Oklahoma and the impact that this decline has on microclimates and wheat production. The project involves learning how to collect, process and analyze geospatial field data and remote sensing data (UAV imagery and satellite imagery). The microclimate monitoring station built by Hasan will collect field data (air temperature, soil moisture, rainfall and wind speed/direction).

Oklahoma planted more than 20 million trees as shelterbelts or windbreaks following the Dust Bowl of the 1930s. The shelterbelts reduced the loss of topsoil from fields due to wind erosion and increased the soil moisture content, which increased agricultural production of Oklahoma’s No. 1 cash crop: wheat. In recent years, climate change and advanced agricultural practices have resulted in the deterioration, die-off and removal of shelterbelts. The aim of this project is to quantify the effects on local microclimates protected by shelterbelts and the impact the loss of shelterbelts has on wheat production. Microclimates will be modeled using the Environmental Policy Integrated Climate model. UAV/satellite imagery will be used to characterize existing shelterbelts and determine how the quantity and quality of shelterbelts have changed over time.

Field data collected with the microclimate monitoring station will quantify the physical and physiological characteristics of selected shelterbelts with a group of sensors conducting high-frequency, multi-season monitoring of the primary microclimatic variables (air temperature, soil moisture, rainfall and wind speed/direction) that are critical to the growth and production of wheat. After assembling the first microclimate monitoring station, Hasan setup and tested the station at The University of Tulsa for 18 days in October 2022 and used this data to run some statistical analysis. All sensors have wireless communication with the solar-powered datalogger. The datalogger is also equipped with a cellular modem, which will allow data to be downloaded remotely, lowering labor costs and enabling near real-time data quality checks.

UAV 3D image looking down on a complex of buildings with a grass courtyard in the centerIn addition to the data from the microclimate monitoring station, an unmanned aerial vehicle (UAV) with a camera will be used to produce images of study areas, a high-resolution topographic model and a digital elevation model (DEM) to generate 3D images of the study areas. Hasan practiced using the drone to create a 3D image of the park west of Keplinger Hall using the DEM from the UAV and image processing software. These images were produced using commercial software, Agisoft Metashape to perform photogrammetric processing of digital images to generate the 3D spatial data. The imagery will be used to characterize different objects in the field, trees, grasses, crops, fallow fields, etc.

Hasan is grateful to his project’s principal investigators, Adjunct Professor Junran Li and Professor Kenneth Roberts (chair for the Department of Chemistry and Biochemistry), for their support and supervision. Hasan also thanked Assistant Professor John Volesky for his guidance throughout the project’s trial setup and guidance and Professor Jingyi Chen (chair of the Department of Geosciences) for his motivation for writing for the website.

This project is funded by the Oklahoma Center for Advancement of Science and Technology.