Progress 11/07/23 to 11/06/24
Outputs
Target Audience:The audience for our work includes agricultural officials involved in agricultural land planning, crop scheduling, and disaster prevention, along with transportation officials focused on designing transport infrastructure to prevent traffic accidents. They are especially concerned with extreme traffic incidents influenced by agricultural practices and the environment around the road Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?The dust storm investigation is a good case study for students to learn the multi-phase simulation in Computational Fluid Dynamics (CFD), improving their understanding of the multi-phase flow and the numerical method of Large Eddy Simulation (LES). We also hired an NSF Research Experiences for Undergraduates (REU) student from the University of Maryland to work on satellite remote sensing. How have the results been disseminated to communities of interest?All research results have been disseminated to the community through university websites and the farm doc platform at the University of Illinois Urbana-Champaign. These websites and seminars can be found in the links below. https://farmdocdaily.illinois.edu/2024/02/cover-crops-and-covered-cropland-2022-us-census-of-agriculture.html ?https://farmdocdaily.illinois.edu/2024/08/back-to-policy-design-the-inflation-reduction-acts-conservation-assistance.html What do you plan to do during the next reporting period to accomplish the goals?Our goal is to improve the dust storm simulation model configuration, tuning down the dust plume to more accurate scenarios. Based on the model simulations, we also aim to draw a quantitative relation between cover crop adoption and its impact on mitigation. We will also integrate all three research goals together to finalize this project.
Impacts
What was accomplished under these goals?
1. Characterizing dust storm processes via news, reports and remote sensing. We examine news and reports regarding the highway car crash caused by dust, which occurred around 11 A.M. on May 1, 2023. The incident took place at 39.505407 N, -89.645350 W, in the northbound lane of the highway, providing a precise location. Wind speed at the time was approximately 45 mph (20 m/s) from the northwest. The crops planted near the crash site were identified as soybean and corn. Reports from the National Agricultural Statistics Service indicate that April 2023 had significantly lower precipitation and higher temperatures than the historical average. Additionally, the planting season had started earlier than usual, so seedbed preparation was underway on May 1, 2023. This led to dust being rolled up, resulting in high dust concentration and reduced road visibility. Further investigation into the environmental conditions during seedbed preparation revealed a dust concentration of about 14 mg/m³, with an average particle size of approximately 10 μm. The relationship between dust concentration and visibility was also analyzed and will be applied in subsequent studies. To further characterize the dust storm, we will first define two experiment regions: the dust storm region and nearby non-dust storm. Then, we will randomly select sample fields for each region. For the sampled field, we will derive information including agricultural practice (e.g. planting dates, cover cropping or not, and tillage type) and environmental conditions (e.g. temperature, precipitation, soil moisture, and wind speed and direction). Finally, the statistical models (e.g. analysis of variance) and machine learning models (e.g. causal forests) will be adopted to determine the impacts of each variable on the dust storm event. 2. Understanding mechanisms through multi-scale simulations Based on the collected data, we established the boundary conditions and computational domain. Figure 1 illustrates the crash area landscape, and Figure 2 displays the domain's bottom setup for numerical simulation. Green, yellow, and light blue areas respectively represent trees, roads, and buildings. Tree height is set at 20 m, and building height at 10 m. A two-phase flow model using Large Eddy Simulation (LES) with Lagrangian particles is developed, including a tree model to simulate drag effects within the computational domain. We have conducted several simulations to investigate the impact of wind speed and threshold friction velocity on dust concentration. Specifically, we performed sensitivity analyses by simulating the same event with varying vegetation fractions to assess their influence on dust entrainment From the literature, we note that particles tend to accumulate at the area with a higher strain rate than the rotational rate, which can be influenced by drag forces from trees within the flow field. For further simulation cases, we focus on dust concentration levels at road sections adjacent to the trees, where higher strain rates lead to particle accumulation. 3. Social and policy analysis with stakeholders for dust storm mitigation We have conducted a social science analysis to summarize the news report from the public. Among these articles, there are 50% of articles published in Illinois, 33% of articles published nationally, and 17% of articles published in agricultural journals or out-of-Illinois regional publications. From the news articles, farmers near I-55 were blamed for planting during dry weather, using intensive tillage practices, or failing to adopt cover crops.?
Publications
- Type:
Peer Reviewed Journal Articles
Status:
Published
Year Published:
2024
Citation:
Zhou, Q., Guan, K., Wang, S., Hipple, J. and Chen, Z., 2024. From satellite-based phenological metrics to crop planting dates: Deriving field-level planting dates for corn and soybean in the US Midwest. ISPRS Journal of Photogrammetry and Remote Sensing, 216, pp.259-273.
|