TY - JOUR
T1 - A water quality monitoring network design methodology for the selection of critical sampling points
T2 - Part II
AU - Strobl, R. O.
AU - Robillard, P. D.
AU - Day, R. L.
AU - Shannon, R. D.
AU - McDonnell, A. J.
PY - 2006/11
Y1 - 2006/11
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=33750618363&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33750618363&partnerID=8YFLogxK
U2 - 10.1007/s10661-006-0358-4
DO - 10.1007/s10661-006-0358-4
M3 - Article
C2 - 16502278
AN - SCOPUS:33750618363
SN - 0167-6369
VL - 122
SP - 319
EP - 334
JO - Environmental Monitoring and Assessment
JF - Environmental Monitoring and Assessment
IS - 1-3
ER -