Periodic autoregressive moving average models for the analysis of streamflow [abstract]

EXTRACT (SEE PDF FOR FULL ABSTRACT): Streamflow values show definite seasonal patterns in their month-to-month correlation structure. The structure also seems to vary as a function of the type of stream (coastal versus mountain or humid versus arid region). The standard autoregressive moving average (ARMA) time series model is incapable of reproducing this correlation structure. ... A periodic ARMA time series model is one in which an ARMA model is fitted to each month or season but the parameters of the model are constrained to be periodic according to a Fourier series. This constraint greatly reduces the number of parameters but still leaves the flexibility for matching the seasonally varying correlograms.

Prioritizing county-level well-being: Moving toward assessment of Gulf Coast counties impacted by the Deepwater Horizon Industrial Disaster

To develop a portfolio of indicators and measures that could best measure changes in the social, economic, environmental and health dimensions of well-being in coastal counties we convened a group of experts March 8-9, 2011 in Charleston, SC, U.S.A. The region of interest was of the northern Gulf of Mexico, specifically, those coastal counties most impacted during the explosion and subsequent oil spill from the Macondo Prospect wellhead during the summer of 2010. Over the course of the two-day workshop participants moved through presentations and facilitated sessions to identify and prioritize potential indicators and measures deemed most valuable for capturing changes in well-being related to changes in or disruption of ecosystem services. The experts reached consensus on a list of indicators that are now being operationalized by NOAA researchers. The ultimate goal of this research project is to determine whether a meaningful set of social and economic indicators can be developed to document changes in well-being that occur as a result of changes in ecosystem services. The outcomes and outputs from the workshop that is the subject of this report helped us to identify high-quality indicators useful for measuring well-being.

Report of the special session of "Chesapeake Bay Ecological Forecasting: Moving Ecosystem Modeling from Research to Operation" of the 2010 Chesapeake Modeling Symposium

Moving ecosystem modeling from research to applications and operations has direct management relevance and will be integral to achieving the water quality and living resource goals of the 2010 Chesapeake Bay Executive Order. Yet despite decades of ecosystem modeling efforts of linking climate to water quality, plankton and fish, ecological models are rarely taken to the operational phase. In an effort to promote operational ecosystem modeling and ecological forecasting in Chesapeake Bay, a meeting was convened on this topic at the 2010 Chesapeake Modeling Symposium (May, 10-11). These presentations show that tremendous progress has been made over the last five years toward the development of operational ecological forecasting models, and that efforts in Chesapeake Bay are leading the way nationally. Ecological forecasts predict the impacts of chemical, biological, and physical changes on ecosystems, ecosystem components, and people. They have great potential to educate and inform not only ecosystem management, but also the outlook and opinion of the general public, for whom we manage coastal ecosystems. In the context of the Chesapeake Bay Executive Order, ecological forecasting can be used to identify favorable restoration sites, predict which sites and species will be viable under various climate scenarios, and predict the impact of a restoration project on water quality.