To facilitate watershed management, watershed models are often developed and used to assess the expected impact of scenarios of past and future management policies and practices and the impact of watershed conditions. However, the level of load reductions estimated using monitoring data often does not match with model predictions, leading to questions around the level of effort and investment being made in restoration activities and the reliability of the model.

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The main objective of this project is to leverage machine learning approaches -- more specifically, the combined use of hierarchical clustering and random forest (RF) classification -- to reveal regional patterns and drivers of nitrogenand phosphorus trends across the Chesapeake Bay watershed. This work involves three objectives:

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UMCES received accreditation from the Middle States Commission on Higher Education. As part of the accreditation process, UMCES needs to assess and communicate its goals better. The Institutional Assessment evaluates how successful UMCES is at meeting its goals of scientific research, public service, and education. We will do this by working through the 5-step report card process and producing a report card-like assessment for public consumption.

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IAN has teamed up with oceanographers at our home campus of Horn Point Laboratory and at the Department of Natural Resources in order to revisit a growing concern of algal blooms off Assateague Island National Seashore on the Southern Eastern Shore. IAN's role in this project involves synthesizing data collected offshore and helping to establish relevant thresholds for offshore nutrient data, as well as aiding in communication of the studies data and findings.

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The Chesapeake Bay Program and the U.S. Geologic Survey are compiling tributary basin summaries for 12 major tributaries or tributary groups in the Chesapeake Bay Watershed. These summaries summarize the following information: (1) How tidal water quality changes over time; (2) How factors that drive those changes change over time; and (3) Current state of the science on connecting change in aquatic conditions to its drivers.

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This report card was produced in December 2015 by The University of Maryland Center for Environmental Science and represents a joint effort of graduate students and faculty in the Marine Estuarine Environmental Sciences program at the Appalachian Laboratory in Frostburg and the Integration and Application Network. The report card provides an assessment of stream health in the Upper Potomac Headwaters region upstream of Harpers Ferry, West Virginia.

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The Chesapeake Bay Program, MD Department of Natural Resources, and VA Department of Environmental Quality collaborate annually to produce bay-wide summaries of water quality trends in the tidal waters. These annual estimates at more than 150 stations for nutrients, dissolved oxygen, Secchi depth, chlorophyll a and other parameters help gauge the health of the bay and identify changes due to management actions and climate.

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Oysters are a keystone of sustainable fisheries and aquaculture, healthy coastal ecosystems, and resilient communities in the Chesapeake Bay region. Bringing new knowledge of different types of fishery management and aquaculture techniques to fishing communities in this region is a vital part of developing thriving coastal communities, yet communicating these techniques and strategies is not straightforward and may not be effective without prior stakeholder engagement.

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WWF and the University of Maryland Center for Environmental Sciences seek to empower stakeholders around the world to develop and effectively use credible, locally owned report cards in their basins, fostering sustainable water management across basins around the world.

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The main goal of this project is to develop a web-based tool that allows users to explore time series of important bay health indicators, resources and influences. Users would be able to drag a slider across a series of years to see how status changes over time. A carousel of images, conceptual diagram, and videos could scroll through, regardless of where the slider is. Data would also be presented for inputs and overall bay status. An indicator would show what year was being shown.

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