Stochastic reliability-based risk evaluation and mapping for watershed systems and sustainability (STREAMS)

Mitigating water contamination, improving water security, and increasing sustainability involve environmental awareness and conscientious decision-making by denizens and stakeholders. Achieving such awareness requires visually compelling geospatial decision-making tools that take into account the probabilistic and spatially distributed nature of water contamination. Inspired by the success of weather maps, this paper presents a novel STochastic Reliability-based Risk Evaluation And Mapping for watershed Systems and Sustainability (STREAMS) tool that produces and effectively communicates the risk of water contamination as maps. STREAMS is integrated with ArcGIS geoprocessing tools and uses physics-based reliability theory to compute the spatial distribution of risk, which is defined as the probability of exceeding a safety threshold of water contamination within a watershed. A quantitative analysis of the efficacy of mitigation strategies is conducted by estimating risk reduction from best management practices throughout the entire watershed. Two case studies at different spatial scales are presented, demonstrating STREAMS application to watersheds with varied properties.

A geographic data model for representing ground water systems

The Arc Hydro ground water data model is a geographic data model for representing spatial and temporal ground water information within a geographic information system (GIS). The data model is a standardized representation of ground water systems within a spatial database that provides a public domain template for GIS users to store, document, and analyze commonly used spatial and temporal ground water data sets. This paper describes the data model framework, a simplified version of the complete ground water data model that includes two-dimensional and three-dimensional (3D) object classes for representing aquifers, wells, and borehole data, and the 3D geospatial context in which these data exist. The framework data model also includes tabular objects for representing temporal information such as water levels and water quality samples that are related with spatial features.

Regional scale flood modeling using NEXRAD rainfall, GIS, and HEC-HMS/RAS: a case study for the San Antonio River Basin Summer 2002 storm event

This paper develops a framework for regional scale flood modeling that integrates NEXRAD Level III rainfall, GIS, and a hydrological model (HEC-HMS/RAS). The San Antonio River Basin (about 4000 square miles, 10,000 km2) in Central Texas, USA, is the domain of the study because it is a region subject to frequent occurrences of severe flash flooding. A major flood in the summer of 2002 is chosen as a case to examine the modeling framework. The model consists of a rainfall-runoff model (HEC-HMS) that converts precipitation excess to overland flow and channel runoff, as well as a hydraulic model (HEC-RAS) that models unsteady state flow through the river channel network based on the HEC-HMS-derived hydrographs. HEC-HMS is run on a 4 x 4 km grid in the domain, a resolution consistent with the resolution of NEXRAD rainfall taken from the local river authority. Watershed parameters are calibrated manually to produce a good simulation of discharge at 12 subbasins. With the calibrated discharge, HEC-RAS is capable of producing floodplain polygons that are comparable to the satellite imagery. The modeling framework presented in this study incorporates a portion of the recently developed GIS tool named Map to Map that has been created on a local scale and extends it to a regional scale. The results of this research will benefit future modeling efforts by providing a tool for hydrological forecasts of flooding on a regional scale. While designed for the San Antonio River Basin, this regional scale model may be used as a prototype for model applications in other areas of the country.