Abstract
In order to resolve the spatial component of the design of a water quality monitoring network, a methodology has been developed to identify the critical sampling locations within a watershed. This methodology, called Critical Sampling Points (CSP), focuses on the contaminant total phosphorus (TP), and is applicable to small, predominantly agricultural-forested watersheds. The CSP methodology was translated into a model, called Water Quality Monitoring Station Analysis (WQMSA). It incorporates a geographic information system (GIS) for spatial analysis and data manipulation purposes, a hydrologic/water quality simulation model for estimating TP loads, and an artificial intelligence technology for improved input data representation. The model input data include a number of hydrologic, topographic, soils, vegetative, and land use factors. The model also includes an economic and logistics component. The validity of the CSP methodology was tested on a small experimental Pennsylvanian watershed, for which TP data from a number of single storm events were available for various sampling points within the watershed. A comparison of the ratios of observed to predicted TP loads between sampling points revealed that the model's results were promising.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 319-334 |
| Number of pages | 16 |
| Journal | Environmental Monitoring and Assessment |
| Volume | 122 |
| Issue number | 1-3 |
| DOIs | |
| State | Published - Nov 2006 |
All Science Journal Classification (ASJC) codes
- General Environmental Science
- Pollution
- Management, Monitoring, Policy and Law