Keywords
GIS and Environmental Science; World Wide Telescope; Microsoft Streamlnsight and Windows Azure; Water Quality Monitoring
Location
Session D1: GIS and Environmental Modeling for Decision Support
Start Date
16-6-2014 10:40 AM
End Date
16-6-2014 12:00 PM
Abstract
Managing the water quality in an urban environment is extremely challenging. While it flows, the water picks up pollutants such as lawn care chemicals, oil, and pet waste bacteria. In fact, topography plays a factor in where water runoff goes. However, there are many other factors, such as urban density, impermeable surface coverage, weather events and tidal patterns which all have the potential to impact not only the final destination of a particular pollutant but also the rate of travel along the route. In this paper, we propose a system, named AMADEUS (Azure Marketplace of Applications for Diverse Environmental Use as a Service), which is an interactive, self-service framework that allows end users to explore, analyse, and visualize the environmental data within the context of their applications.
As a case study, we present a sample application on AMADEUS which aims to identify contaminant sources in the Puget Sound region. AMADEUS integrates chemical spill data, meteorological data, Puget Sound buoy data, and water runoff models to perform pollutant path tracking and prediction. More specifically, given a water fall location, AMADEUS is able to identify the runoff path, compute the impact of environmental factors. For example, it can trace back the pollutant to its source, and predict the final destination of the pollutant. In addition, AMADEUS provides user friendly visualization to demonstrate the tracking and prediction of pollutants' routes.
Included in
Civil Engineering Commons, Data Storage Systems Commons, Environmental Engineering Commons, Hydraulic Engineering Commons, Other Civil and Environmental Engineering Commons
AMADEUS: A System for Monitoring Water Quality Parameters and Predicting Contaminant Paths
Session D1: GIS and Environmental Modeling for Decision Support
Managing the water quality in an urban environment is extremely challenging. While it flows, the water picks up pollutants such as lawn care chemicals, oil, and pet waste bacteria. In fact, topography plays a factor in where water runoff goes. However, there are many other factors, such as urban density, impermeable surface coverage, weather events and tidal patterns which all have the potential to impact not only the final destination of a particular pollutant but also the rate of travel along the route. In this paper, we propose a system, named AMADEUS (Azure Marketplace of Applications for Diverse Environmental Use as a Service), which is an interactive, self-service framework that allows end users to explore, analyse, and visualize the environmental data within the context of their applications.
As a case study, we present a sample application on AMADEUS which aims to identify contaminant sources in the Puget Sound region. AMADEUS integrates chemical spill data, meteorological data, Puget Sound buoy data, and water runoff models to perform pollutant path tracking and prediction. More specifically, given a water fall location, AMADEUS is able to identify the runoff path, compute the impact of environmental factors. For example, it can trace back the pollutant to its source, and predict the final destination of the pollutant. In addition, AMADEUS provides user friendly visualization to demonstrate the tracking and prediction of pollutants' routes.
