JAWRA Journal of the American Water Resources Association · 2003 · 38 citations · 8 references
Natural ResourcesHydrologyWater Resources ManagementWater Quality ManagementWater Resources EngineeringWatershed HydrologyWater PollutionWater QualityWatershed AssessmentWatershed Condition MonitoringWatershed ModelingWatershed StructureCluster AnalysisMultivariate Hydrologic AnalysisPhysical Characteristics AssessmentStatistical Discriminant AnalysisWater Quality AnalysisWatershed Condition AssessmentWatershed Data AnalysisWatershed Monitoring
ABSTRACT: Multivariate analyses were used to develop equations that could predict certain water quality (WQ) conditions for unmonitored watersheds in Puerto Rico based on their physical characteristics. Long term WQ data were used to represent the WQ of 15 watersheds in Puerto Rico. A factor analysis (FA) was performed to reduce the number of chemical constituents. Cluster analysis (CA) was used to group watersheds with similar WQ characteristics. Finally, a discriminant analysis (DA) was performed to relate the WQ clusters to different physical parameters and generate predicting equations. The FA identified six factors (77 percent of variation explained): nutrients, dissolved ions, sodium and chloride, silicacious geology, red ox conditions, and discharge. From the FA, specific conductance, sodium, phosphorous, silica, and dissolved oxygen were selected to represent the WQ characteristics in the CA. The CA determined five groups of watersheds (forested, urban polluted, mixed urban/rural, forested plutonic, and limestone) with similar WQ properties. From the five WQ clusters, two categories can be observed: forested and urban watersheds. The DA found that changes in forest cover, percent of limestone, mean annual rainfall, and watershed shape factor were the most important physical features affecting the WQ of watersheds in Puerto Rico.
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