<![CDATA[EAS Seminar Series - Dr. Matthew Bilskie]]> 36678 Coastal hazards result from interacting physical processes that span a wide range of spatial and temporal scales. Accurately representing these processes remains a fundamental challenge for predicting coastal flooding and landscape response, particularly as the coastal environment and the hazards affecting it continue to change.

This seminar will present research that integrates numerical modeling, field observations, and remote sensing to improve understanding and prediction of coastal hazards and to inform resilience strategies. Examples from the southeastern United States will illustrate how process-based hydrodynamic models are being advanced toward high-resolution, probabilistic, and real-time predictions of coastal flooding. Field observations and UAV-based methods provide complementary measurements of coastal systems at scales that are difficult to resolve, helping investigate processes within marshes, barrier islands, and other dynamic coastal environments.

The seminar will also explore how these capabilities can be translated from hazard characterization into resilience design. Ongoing research integrates observations and models across scales to quantify the protective function of natural coastal systems and evaluate nature-based and hybrid solutions for flood and shoreline protection, including applications at coastal military installations. Taken together, this work illustrates opportunities to connect understanding of coastal processes, hazard prediction, and engineering implementation to support more resilient coastal systems.

*Refreshments: 12-12:30 PM, ES&T Atrium

]]> tbuchanan9 1 1786448806 2026-08-11 11:46:46 1786449092 2026-08-11 11:51:32 0 0 event Coastal hazards result from interacting physical processes that span a wide range of spatial and temporal scales. Accurately representing these processes remains a fundamental challenge for predicting coastal flooding and landscape response, particularly as the coastal environment and the hazards affecting it continue to change.

This seminar will present research that integrates numerical modeling, field observations, and remote sensing to improve understanding and prediction of coastal hazards and to inform resilience strategies. Examples from the southeastern United States will illustrate how process-based hydrodynamic models are being advanced toward high-resolution, probabilistic, and real-time predictions of coastal flooding. Field observations and UAV-based methods provide complementary measurements of coastal systems at scales that are difficult to resolve, helping investigate processes within marshes, barrier islands, and other dynamic coastal environments.

The seminar will also explore how these capabilities can be translated from hazard characterization into resilience design. Ongoing research integrates observations and models across scales to quantify the protective function of natural coastal systems and evaluate nature-based and hybrid solutions for flood and shoreline protection, including applications at coastal military installations. Taken together, this work illustrates opportunities to connect understanding of coastal processes, hazard prediction, and engineering implementation to support more resilient coastal systems.

*Refreshments: 12-12:30 PM, ES&T Atrium

]]> 2026-09-10T11:00:00-04:00 2026-09-10T12:00:00-04:00 2026-09-10T12:00:00-04:00 2026-09-10 15:00:00 2026-09-10 16:00:00 2026-09-10 16:00:00 2026-09-10T11:00:00-04:00 2026-09-10T12:00:00-04:00 America/New_York America/New_York datetime 2026-09-10 11:00:00 2026-09-10 12:00:00 America/New_York America/New_York datetime <![CDATA[]]> 680835 680835 image <![CDATA[Headshot Bilskie]]> image/jpeg 1786448944 2026-08-11 11:49:04 1786448944 2026-08-11 11:49:04 <![CDATA[]]> <![CDATA[EAS Seminar Series - Dr. Jacob Cohen]]> 36678 Marine heatwaves (MHWs) are oceanic extreme events characterized by prolonged periods of unusually high sea surface temperatures. MHWs cause devastating effects on biological communities and marine ecosystems. MHW events can last from days to years and move across ocean basins. While MHWs have traditionally been studied across grid cells, recent work has explored the spatiotemporal representation of MHWs. Here, we use Ocetrac, a python package for identifying and tracking spatially connected MHWs, to study the spatiotemporal evolution of MHWs and to understand their drivers, impacts, and prediction. First, we evaluate drivers of large North Pacific MHWs in a large ensemble of climate simulations using the Community Earth System Model (CESM). We demonstrate that regional MHWs are controlled by different atmospheric drivers and are related to climate modes like the Pacific Decadal Oscillation and El Niño. Next, we investigate the biogeochemical impacts of the Blob 2.0, a consequential MHW that occurred in the Northeast Pacific in summer 2019. We use CESM and a set of observational datasets to show that warm temperature anomalies associated with the Blob 2.0 negatively correlate with dissolved inorganic carbon and dissolved oxygen. Finally, we evaluate global spatiotemporal forecasts of MHWs and develop intuitive metrics that demonstrate long-term forecast skill of MHW area, location, and intensity. Together, these studies improve our understanding of MHWs and advance our capabilities to plan for and respond to extreme ocean temperatures.

*Refreshments: 12-12:30 PM, ES&T Atrium

]]> tbuchanan9 1 1786020726 2026-08-06 12:52:06 1786020968 2026-08-06 12:56:08 0 0 event Marine heatwaves (MHWs) are oceanic extreme events characterized by prolonged periods of unusually high sea surface temperatures. MHWs cause devastating effects on biological communities and marine ecosystems. MHW events can last from days to years and move across ocean basins. While MHWs have traditionally been studied across grid cells, recent work has explored the spatiotemporal representation of MHWs. Here, we use Ocetrac, a python package for identifying and tracking spatially connected MHWs, to study the spatiotemporal evolution of MHWs and to understand their drivers, impacts, and prediction. First, we evaluate drivers of large North Pacific MHWs in a large ensemble of climate simulations using the Community Earth System Model (CESM). We demonstrate that regional MHWs are controlled by different atmospheric drivers and are related to climate modes like the Pacific Decadal Oscillation and El Niño. Next, we investigate the biogeochemical impacts of the Blob 2.0, a consequential MHW that occurred in the Northeast Pacific in summer 2019. We use CESM and a set of observational datasets to show that warm temperature anomalies associated with the Blob 2.0 negatively correlate with dissolved inorganic carbon and dissolved oxygen. Finally, we evaluate global spatiotemporal forecasts of MHWs and develop intuitive metrics that demonstrate long-term forecast skill of MHW area, location, and intensity. Together, these studies improve our understanding of MHWs and advance our capabilities to plan for and respond to extreme ocean temperatures.

*Refreshments: 12-12:30 PM, ES&T Atrium

]]> 2026-10-01T11:00:00-04:00 2026-10-01T12:00:00-04:00 2026-10-01T12:00:00-04:00 2026-10-01 15:00:00 2026-10-01 16:00:00 2026-10-01 16:00:00 2026-10-01T11:00:00-04:00 2026-10-01T12:00:00-04:00 America/New_York America/New_York datetime 2026-10-01 11:00:00 2026-10-01 12:00:00 America/New_York America/New_York datetime <![CDATA[]]> 680799 680799 image <![CDATA[Cohen Headshot]]> image/jpeg 1786020919 2026-08-06 12:55:19 1786020919 2026-08-06 12:55:19 <![CDATA[]]> <![CDATA[EAS Seminar Series - Dr. Donghui Xu]]> 36678 Earth System Models (ESMs) are essential tools for simulating global water and energy cycles and supporting water resource assessments. However, the accuracy of their hydrologic simulations is often limited by parametric uncertainties and process simplifications. In this presentation, I will present my research efforts to enhance the representation of hydrologic and hydrodynamic processes in a fully coupled ESM. However, its coarse resolution (e.g., 50 km – 100 km) further limits their ability to simulate urban flooding dynamics at the scale relevant to human activities and infrastructure. To address this challenge, I contributed to the development of a new river dynamics core that solves two-dimensional shallow water equations, enabling efficient high-fidelity hydrodynamic simulations (e.g., 30m) at large scales. I will demonstrate this new capability using a case study of compound flooding driven by Hurricane Irene. By coupling with a regionally refined atmospheric model, a two-dimensional barotropic ocean model, and a high-resolution land surface model within an ESM, the multi-scale modeling framework captures unprecedented details of flooding processes in complex urban environments. Despite these advances, such actionable-scale flooding simulations remain computationally infeasible for real-time forecasting. To further improve the model efficiency, I proposed a real-time flooding forecast framework based on a machine learning based surrogate model trained on outputs from the physical flooding model prior to flood events. During an event, the surrogate model can rapidly predict flooding extent using forecasted precipitation within seconds on a low-end computer, while also quantifying uncertainties associated with precipitation forecasts.

*Refreshments: 12-12:30 PM, ES&T Atrium

]]> tbuchanan9 1 1785506928 2026-07-31 14:08:48 1785507875 2026-07-31 14:24:35 0 0 event Earth System Models (ESMs) are essential tools for simulating global water and energy cycles and supporting water resource assessments. However, the accuracy of their hydrologic simulations is often limited by parametric uncertainties and process simplifications. In this presentation, I will present my research efforts to enhance the representation of hydrologic and hydrodynamic processes in a fully coupled ESM. However, its coarse resolution (e.g., 50 km – 100 km) further limits their ability to simulate urban flooding dynamics at the scale relevant to human activities and infrastructure. To address this challenge, I contributed to the development of a new river dynamics core that solves two-dimensional shallow water equations, enabling efficient high-fidelity hydrodynamic simulations (e.g., 30m) at large scales. I will demonstrate this new capability using a case study of compound flooding driven by Hurricane Irene. By coupling with a regionally refined atmospheric model, a two-dimensional barotropic ocean model, and a high-resolution land surface model within an ESM, the multi-scale modeling framework captures unprecedented details of flooding processes in complex urban environments. Despite these advances, such actionable-scale flooding simulations remain computationally infeasible for real-time forecasting. To further improve the model efficiency, I proposed a real-time flooding forecast framework based on a machine learning based surrogate model trained on outputs from the physical flooding model prior to flood events. During an event, the surrogate model can rapidly predict flooding extent using forecasted precipitation within seconds on a low-end computer, while also quantifying uncertainties associated with precipitation forecasts.

*Refreshments: 12-12:30 PM, ES&T Atrium

]]> 2026-09-17T11:00:00-04:00 2026-09-17T12:00:00-04:00 2026-09-17T12:00:00-04:00 2026-09-17 15:00:00 2026-09-17 16:00:00 2026-09-17 16:00:00 2026-09-17T11:00:00-04:00 2026-09-17T12:00:00-04:00 America/New_York America/New_York datetime 2026-09-17 11:00:00 2026-09-17 12:00:00 America/New_York America/New_York datetime <![CDATA[]]> 680737 680737 image <![CDATA[Xu Headshot]]> image/jpeg 1785507154 2026-07-31 14:12:34 1785507154 2026-07-31 14:12:34 <![CDATA[]]> <![CDATA[EAS Seminar Series - Dr. Ignacio Sepulveda]]> 36678 The seminar will highlight three research efforts developed in Chile during my stay in 2025. First, through collaborations with private organizations, we measured the Kamchatka tsunami as it entered the Valdivia River Estuary in Chile. These unique ADCP measurements included currents and water levels, providing rare observations of tsunami-river-tide interactions. Building on the success of this deployment, we installed two permanent monitoring stations in the Valdivia River to continuously measure water levels, waves, temperature, salinity, and dissolved oxygen.

Second, I introduce the TRIDENT model (Tides and Rivers Influencing the Dynamic Evolution of Nearshore Tsunamis), a modeling framework designed to simulate the coupling between tsunamis, tides, and river flows. The coupled model is designed for estuaries, tidal channels, and fjords, and it addresses key challenges when simulating these interactions.

Finally, I will present results from a study that links dispersive tsunami wave trains visible in satellite imagery to near-trench earthquake rupture. By analyzing tsunami dispersion in the near-source wave field, this approach provides a new observational footprint for constraining source processes that improves resolving power near the trench compared with traditional seismic, geodetic, and tsunami sensing technologies.

Collectively, these studies demonstrate complementary advances, from field deployment to coupled modeling for hazard prediction to remote-sensing-based discovery, that expand the toolkit for understanding and assessing tsunami hazards and risks.

*Refreshments: 12-12:30 PM, ES&T Atrium

]]> tbuchanan9 1 1785506429 2026-07-31 14:00:29 1785506882 2026-07-31 14:08:02 0 0 event The seminar will highlight three research efforts developed in Chile during my stay in 2025. First, through collaborations with private organizations, we measured the Kamchatka tsunami as it entered the Valdivia River Estuary in Chile. These unique ADCP measurements included currents and water levels, providing rare observations of tsunami-river-tide interactions. Building on the success of this deployment, we installed two permanent monitoring stations in the Valdivia River to continuously measure water levels, waves, temperature, salinity, and dissolved oxygen.

Second, I introduce the TRIDENT model (Tides and Rivers Influencing the Dynamic Evolution of Nearshore Tsunamis), a modeling framework designed to simulate the coupling between tsunamis, tides, and river flows. The coupled model is designed for estuaries, tidal channels, and fjords, and it addresses key challenges when simulating these interactions.

Finally, I will present results from a study that links dispersive tsunami wave trains visible in satellite imagery to near-trench earthquake rupture. By analyzing tsunami dispersion in the near-source wave field, this approach provides a new observational footprint for constraining source processes that improves resolving power near the trench compared with traditional seismic, geodetic, and tsunami sensing technologies.

Collectively, these studies demonstrate complementary advances, from field deployment to coupled modeling for hazard prediction to remote-sensing-based discovery, that expand the toolkit for understanding and assessing tsunami hazards and risks.

*Refreshments: 12-12:30 PM, ES&T Atrium

]]> 2026-09-24T11:00:00-04:00 2026-09-24T12:00:00-04:00 2026-09-24T12:00:00-04:00 2026-09-24 15:00:00 2026-09-24 16:00:00 2026-09-24 16:00:00 2026-09-24T11:00:00-04:00 2026-09-24T12:00:00-04:00 America/New_York America/New_York datetime 2026-09-24 11:00:00 2026-09-24 12:00:00 America/New_York America/New_York datetime <![CDATA[]]> 680736 680736 image <![CDATA[Sepulveda Headshot]]> image/png 1785506800 2026-07-31 14:06:40 1785506800 2026-07-31 14:06:40 <![CDATA[]]>