This advisory committee charter, developed for a National Estuarine Research Reserve project to evaluate a thin-layer placement as a strategy for marsh resilience, offers an example for engaging diverse end users in collaborative research.

This dam sediment estimation tool, developed through the Dams and Sediment in the Hudson (DaSH) project, supports dam removal planning for the Lower Hudson River valley.

This open-access article, published Geophysical Research Letters in 2020, uses turbidity observations to characterize estuary response following extreme discharge such as from storm-related flooding, which can be a proxy for sediment release from dam removals.

This article, submitted for publication to Earth Surface Processes and Landforms in 2020, describes findings from the Dams and Sediment in the Hudson (DaSH) project related to tidal wetland growth in the Hudson River estuary as a result of human activities. It presents sediment accumulation rates in marshes along the Hudson and reveals the rapid growth of marshes associated with anthropogenic structures.

These coastal hazard risk communication training process agendas can be used to as a model help facilitators develop trainings for coastal decision makers in other communities.

These facilitation guides and job aids, part of a Resilience Metrics toolkit, provide tools and activities for each step of the process to develop and track metrics of adaptation success.

This document provides guidance on the use of thin-layer sediment placement (TLP) as a tool for tidal marsh resilience in the face of sea-level rise.

These coastal hazard risk communication workshop materials can be used to help facilitate trainings for coastal decision makers.

The joint probability method (JPM) is the traditional way to determine the base flood elevation due to storm surge, and it usually requires simulation of st

The ocean is inextricably linked to human societies. Climate change and its associated impacts to the aquatic environment pose problems for human communities as well.