2024 Abstracts

Integrated Coastal Modeling: ESS Modeling of Natural Watersheds and Engineered Systems in the Coastal Zone


David Moulton1* (moulton@lanl.gov), Daniil Svyatsky1, Yu Zhang1, Giacomo Capodaglio1, Naren Vohra1, Maria Contreras-Vargas1, Ian Kraucunas2


1Los Alamos National Laboratory, Los Alamos, NM; 2Pacific Northwest National Laboratory, Richland, WA



The Integrated Coastal Modeling project brings together four programs within BER, namely Regional and Global Model Analysis, Earth System Model Development, MultiSector Dynamics, and ESS. This unique collaboration offers the opportunity to explore various facets of coastal science in an interdisciplinary setting. The project’s ESS contributions consider coastal regions as comprised of a range of natural and engineered features that play a critical role in determining their resilience to various climate-influenced drivers, including drought, sea level rise, storm surge, and shifting precipitation patterns. In this setting, the full coupling of surface and subsurface processes is critical to developing a predictive understanding of how these systems function. To demonstrate this benefit of fully coupled process-based models, the team used the Advanced Terrestrial Simulator (ATS) to study the impact of antecedent conditions on flooding through the response of the Harbeson watershed to a series of storms. Next, to continue exploring the natural system response, researchers used the saltwater intrusion capabilities in the ATS to study the formation of ghost forests in the Delaware Bay. This capability also supports studies related to salt marsh migration and the loss of agricultural land to saltwater intrusion. Finally, to study the engineered environment and its response to these drivers, the team highlights a prototype of a storm drain network process kernel in the ATS that is coupled to its integrated hydrology model. This fully coupled system has the unique capability to not only capture the impact of the drainage network on flooding, but also the impact of green spaces or riparian zones. The project demonstrates this new urban modeling capability in a synthetic setting. In future work, the team will consider specific sites with data supporting green space performance assessments under flooding and storm drain networks inferred from publicly available data.