The USGS will provide leadership to develop, test, and apply community-based predictive models that are reliable, credible, timely, available to and used by the USGS, partners, and customers to promote the health and welfare of estuarine resources and aid resource managers in decision making. The ability to model and predict system processes accurately indicates that a fundamental understanding of a system has been achieved. The ability to develop predictive capabilities has been the ultimate goal of classical science and will remain the goal of the Gulf of Mexico Estuaries Integrated Science effort.

We recommend that USGS project managers identify which future modeling efforts USGS should lead and which should be led by others but supported by USGS through partnering and cost-sharing. Models should be flexible, generalized predictive tools developed in response to regional issues, and applicable in other estuarine systems with similar issues. Models should be relevant to current customer needs and regional issues, validated through testing and monitoring activities, easily accessible to internal and external users, and widely utilized. Results of model scenarios should be in a format compatible with GIS for spatial representation. Modeling products and results will contribute to a web-based decision support and query system.

An Information Transfer Model (ITM) similar to the one used for the USGS Southwest Washington Coastal Erosion Study is appropriate for this study. This model forms a framework for transferring scientific information to management communities. There are four stages of the scientific framework denoted along the left edge of Figure 2, beginning with the data phase.

A collective knowledge base is developed through an iterative process of data synthesis, science integration, and fully understanding the information. Models will be developed via the collective knowledge base wherein the experience of many disciplines will be brought together and scientifically linked. Scientific and management uncertainties will always be present. Therefore, the models developed must be flexible and allow adaptation to these uncertainties.

Models developed by this study may range from simple expanded conceptual models to interactive GIS products and complicated numerical models. Researchers operating through an integrated science study plan will work in cooperation with resource managers to ensure that model development addresses relevant issues and priority planning efforts. Resource managers attending the workshop expressed a need for several types of predictive models designed to examine the consequences of system alterations. Examples include, but are not limited to, the following:

a) interactive tools for estimation and evaluation of existing and potential nutrient and contaminant loads in estuarine systems with the ability to forecast the impacts of proposed projects on eutrophication and contaminant levels in the estuary;

b) sediment transport models utilizing a GIS data base to identify the location of known and probable sediment contamination and surficial grain size. May incorporate wave propagation models that calculate bottom shear stress and wave orbital velocities,

c) circulation and salinity models,

d) predictive models for habitat distribution, land use and land cover, and shoreline change.

An experience base is developed in the latter stages of the project that applies to current and future USGS estuary studies in the Gulf of Mexico. The experience base is an ongoing and evolving component consisting of USGS scientists and local managers. Products for decision-makers are produced at this stage.