Complex Systems Modeling II
By Daniel Delgado
Solar eclipse. PHOTO: MSNBC
I recently watched a video of a solar eclipse occurring in front of a cheering crowd and could only see how beautiful the event was. Shortly after I imagined that same event through my ancestor’s eyes and how scary or ominous it could have been to see the sun disappear in the middle of the day. My training as an environmental engineer has taught me to see the relationships around me through math and science and interpret the world by first focusing on a small scale to simplify the interactions, and then expanding from there. Most of my training has been in direct relationships, meaning if X occurs, the result will be Y. The problem with that is that there are often far more X’s that influence the resulting Y. To get a better understanding of what will happen, we must get a better understanding of what causes it, and how those causes interact with each other as they influence the outcome. In complex systems modeling, we focused on those influences. Not only the influences that the causes have on one another, but also the influences the outcomes have on the causes, or feedbacks.
For most people, including myself, it is difficult to keep track of this elaborate dance of forces. We used modeling programs like Python and Vensim to help us take small relationships, and treat them like a puzzle piece to complete an image of what is occurring, and what can occur based on what has occurred and how these trends are changing with time. While I found physical and chemical interactions like agricultural flow rates, nutrient loading, and their impacts on water bodies easier to model, I also learn to integrate social factors like economics and human behavior into the modeling process. Since humans do not always behave in a way that is readily captured in today’s models, archetypes of know behaviors were used to better predict what can occur.
I took this course as the pandemic of COVID-19 continued to change the world around me. The pandemic and the way people and nations responded gave me a deeper respect for epidemiologists and the people tracking this data to inform public policies. When people say how the scientists were wrong at predicting the number of deaths, I do not think they realize that the system is always changing based on our actions or in actions. Fortunately, the original predictions of death tolls over a given period were wrong because behaviors were changed. Hopefully, in the future we use complex modeling techniques to better inform the public and take educated actions on what we are willing to sacrifice to get what we hope to achieve. Fear of these natural phenomenon often come from not knowing why they occur and what is to come, and that “not knowing” can be greatly reduced through complex systems modeling.
About the Author After high school Daniel spent six years in the Navy as a nuclear plant operator onboard a submarine. Those experiences created an interest in engineering that lead to environmental engineering. After completing his contract with the Navy, Daniel enrolled in community college and later transferred to San Diego State University (SDSU). At SDSU he was accepted as a research assistant helping with algal biomass research. There he grew algae in wastewater to treat the water and use the algae as fuel stock . Upon completing his bachelors in environmental engineering, he was accepted to University of South Florida (USF), Tampa, for a Ph. D. program in civil engineering with a concentration in environmental engineering. There he researches biological onsite wastewater treatment for removal of nutrients. His research interests revolve around food, water, energy nexus specifically in wastewater treatment, resource recovery from waste, and bioremediation.
STRONG COASTS is supported by a National Science Foundation Collaborative Research Traineeship (NRT) award (#1735320) led by the University of South Florida (USF) and the University of the Virgin Islands (UVI) to develop a community-engaged training and research program in systems thinking to better manage complex and interconnected food, energy, and water systems in coastal locations. The views expressed here do not reflect the views of the National Science Foundation.