Citation:

Detenbeck, N., A. Morrison, R. Abele, T. Plessel, V. Zoltay, M. Tenbrink, AND S. Rego. Data access and decision tools for coastal water resources management. American Water Resources Association (AWRA) Summer Specialty Conference: GIS and Water Resources IX, Sacramento, CA, July 11 - 13, 2016.

Impact/Purpose:

This presentation will provide an overview of EPA's Estuary Data Mapper application, focusing on new functionality that supports model interoperability, technical transfer of model outputs for scenarios to support decision making, and data import to EPA's decision support tools such as WMOST.

Description:

US EPA has supported the development of numerous models and tools to support implementation of environmental regulations. However, transfer of knowledge and methods from detailed technical models to support practical problem solving by local communities and watershed or coastal management organizations remains a challenge. We have developed the Estuary Data Mapper (EDM) to facilitate data discovery, visualization and access to support environmental problem solving for coastal watersheds and estuaries. EDM is a stand-alone application based on open-source software which requires only internet access for operation. Initially, development of EDM focused on delivery of raw data streams from distributed web services, ranging from atmospheric deposition to hydrologic, tidal, and water quality time series, estuarine habitat characteristics, and remote sensing products. We have transitioned to include access to value-added products which provide end-users with results of future scenario analysis, facilitate extension of models across geographic regions, and/or promote model interoperability. Here we present three examples: 1) the delivery of input data for the development of seagrass models across estuaries, 2) scenarios illustrating the implications of riparian buffer management (loss or restoration) for stream thermal regimes and fish communities, and 3) access to hydrology model outputs to foster connections across models at different scales, ultimately feeding a decision-support tool for integrated water management (Watershed Management Optimization Support Tool, WMOST). In the first case, we developed an approach to predict habitat suitability for seagrass in riverine estuaries, demonstrated this approach using data for Narragansett Bay, RI and then facilitated the application of this approach to other systems. Through EDM, we provide other modelers access to raw data on seagrass distribution, benthic sediment characteristics, merged topo-bathymetry, and wind data to calculate wind-wave energy indices and optical properties from both water quality monitoring and remote sensing products.In the second case, we developed a predictive spatial stream network model for New England stream/river temperature regimes. Managers need access to the distribution of stream/river thermal regimes across New England to support criteria development and an understanding of the sensitivity and resilience of lotic systems. We provide managers with ready access to results of model predictions as well as scenarios which predict the sensitivity of lotic systems to riparian buffer loss and evaluate restoration potential.In the third case, we developed WMOST to support integrated water management. This Excel-based tool focuses on optimization of decisions based on user-specified targets for baseflows, water storage, or peak flows and the relative cost of water resource management options across stormwater, drinking water, wastewater, and land conservation programs. WMOST relies on outputs from hydrology models (e.g.,HSPF, SWAT) to perform water balance calculations: time series unit runoff and recharge; weather data time series; percent effective impervious area; and groundwater recession coefficients by Hydrologic Response Unit (HRU). To facilitate data access for WMOST users, we are developing preprocessors to extract and format data for use in WMOST, and distributing geospatial time series for historic and projected climate change scenarios together with HRU distribution maps for visualization and download via EDM.

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