With marine pollution issues becoming serious and widespread, a series of coastal environmental managemental policies are being carried out worldwide, the effectiveness of which requires comprehensive evaluation.

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Many coastal ecosystems suffer from eutrophication, algal blooms, and dead zones due to excessive anthropogenic inputs of nitrogen (N) and phosphorus (P). This has led to regional restoration efforts that focus on managing watershed loads of N and P. In Chesapeake Bay, the largest estuary in the United States, dual nutrient reductions of N and P have been pursued since the 1980s.

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This paper develops a barometer that indexes water quality in the Chesapeake Bay and summarizes quality over spatial regions and temporal periods. The barometer has a basis in risk assessment and hydrology, and is a function of three different metrics of water quality relative to numerical criteria: relative frequency of criterion attainment; magnitude of deviation from a numerical criterion; and duration of criterion attainment.

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Understanding drivers of water quality in local watersheds is the first step for implementing targeted restoration practices. Nutrient inventories can inform water quality management decisions by identifying shifts in nitrogen (N) and phosphorus (P) balances over space and time while also keeping track of the likely urban and agricultural point and nonpoint sources of pollution.

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Anthropogenic nutrient inputs have led to nutrient enrichment in many waterbodies worldwide, including Chesapeake Bay (USA). River water quality integrates the spatial and temporal changes of watersheds and forms the foundation for disentangling the effects of anthropogenic inputs.

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In Chesapeake Bay in the United States, decades of management efforts have resulted in modest reductions of nutrient loads from the watershed, but the corresponding improvements in estuarine water quality have not consistently followed. Generalize additive models were used to directly link river flows and nutrient loads from the watershed to nutrient trends in the estuary on a station-by-station basis, which allowed for identification of exactly when and where responses are happening.

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Nitrogen, a critical element in all forms of life, is continuously being passed from nonliving to living matter and then back again, but an excess of this nutrient can have adverse effects on aquatic environments. An understanding of the past, present, and future sources, movement, and fate of nitrogen in the Chesapeake Bay watershed can help inform efforts to bring this cycle back into balance (fig. OV.1).

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Environmental monitoring programs generate multivariate time series for the assessment of ecosystem health. Recent developments in causal inference offer ways to translate these observational data into networks able to explain gains and losses in the trajectories of indicator variables. Here, we present a case study of this approach using surface water dissolved oxygen (DO) criteria attainment across the Chesapeake Bay.

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In the Chesapeake Bay, excess nitrogen (N) from both landscape and atmospheric sources has for decades fueled algal growth, disrupted aquatic ecosystems, and negatively impacted coastal economies. Since the 1980s, Chesapeake Bay Program partners have worked to implement a wide range of measures across the region—from the upgrading of wastewater treatment plants to implementation of farm-level best management practices—to reduce N fluxes to the Bay.

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A number of statistical approaches have been developed to quantify the overall trend in river water quality, but most approaches are not intended for reporting separate trends for different flow conditions. We propose an approach called FN2Q, which is an extension of the flow-normalization (FN) procedure of the well-established WRTDS (“Weighted Regressions on Time, Discharge, and Season”) method.

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