Each seminar highlights a different speaker who will discuss their latest research projects, cutting-edge technology or what is happening within certain technological industries. These industries include biomedical technologies or microsystems, assistive technologies, automation and intelligent systems, unmanned systems, advanced manufacturing and composite materials.
Abstract:
Climate change, extreme weather events, and water scarcity have severely impacted the agricultural sector. Under scarce conventional water supplies, a farm faces a decision between reducing production through deficit irrigation and leveraging alternative water and energy resources to continue producing large quantities of crops and these investments would have to be balanced against an unknown climate. Therefore, we develop a framework for farm investment decisions structured as a two-stage stochastic quadratically constrained linear program that maximizes farm profit over a 25-year period while considering an uncertain future climate and the costs of investing and operating various electricity and water technologies. We create four representative climate futures and two climate probability distributions that represent different beliefs that the decision maker might have about the likelihood of each climate scenario occurring. Then, we compare four solutions where decisions are made on information ranging from perfectly knowing the climate and weather to only the average precipitation. Our results show that expected profit and crop yield heavily depend on a decision maker’s given climate probability distributions. Aggressively preparing for an extreme climate can cause significant losses if a more moderate climate is realized. Furthermore, given a future climate, year-to-year weather variability can also corrode the potential cost savings from investing in alternative resources. The insights from this framework can help agricultural decision makers determine how to address climate uncertainty, water scarcity, and to a limited degree weather variability via investments in alternative water and electricity resources that can help improve resilience and fortify profits.
Bio:
Erick C. Jones Jr. is an Assistant Professor in the Department of Industrial, Manufacturing and Systems Engineering at the University of Texas at Arlington. He obtained a PhD from the Operations Research and Industrial Engineering program at the University of Texas at Austin and a B.S. in Chemical Engineering from Texas A&M University. He is a fellow of GEM, NSF INFEWS, and DOE MLEF and pursues research that can enhance quality of life by improving access to sustainable resources and economic opportunities, particularly where a lack of physical infrastructure or resources presents a major obstacle. He has worked with the Texas Energy Poverty Research Institute, Los Alamos National Labs, and the Houston Health Department to address energy poverty, CCS infrastructure, and equitable COVID-19 supply chains, respectively. In general, he specializes in using smart sensors and AI-enabled data to inform simulation and multi-system optimization models that optimize both investment and operational decisions. These models can be used to help decision makers plan and prepare for a future with an increasing frequency of extreme weather events, climate risk, and resource scarcity by investigating how resilience, efficiency, and self-generation strategies can mitigate these risks and present new opportunities.
Date:
May 3, 2022
Time:
12:00pm
Location:
UTARI Auditorium