Predictability of surface water pollution loading in Pennsylvania using watershed-based landscape measurements

Journal of the American Water Resources Association

Volumn 37, Issue 4, 2001, Pages 821-835

  Johnson, Glen D ^a,b   Myers, Wayne L ^a,b   Patil, Ganapati P ^a,b  

^a NEW YORK STATE DEPARTMENT OF HEALTH   (United States)

^b PENNSYLVANIA STATE UNIVERSITY   (United States)

Author keywords

Landscape patterns; Multi scale relationships; Nutrient loading; Pollution potential; Water quality; Watersheds

Indexed keywords

GEOGRAPHIC INFORMATION SYSTEMS; MATHEMATICAL MODELS; REGRESSION ANALYSIS; REMOTE SENSING; SURFACE WATERS; WATER QUALITY; WATERSHEDS;

REGRESSION MODELS;

WATER POLLUTION;

GIS; LANDSCAPE; PREDICTION; SURFACE WATER; WATER POLLUTION;

PENNSYLVANIA; UNITED STATES;

EID: 0034792312     PISSN: 1093474X     EISSN: None     Source Type: Journal    
DOI: 10.1111/j.1752-1688.2001.tb05515.x     Document Type: Article

References (25)

1. A new look at statistical model identification
2. Integrated geographical assessment of environmental condition in water catchments: Linking landscape ecology, environmental modelling and GIS
3. Ecological risk assessment at the regional scale
4. Statewide GIS-based ranking of watersheds for agricultural pollution prevention
5. Hierarchical approaches to the study of water quality in rivers
6. Quantitative characterization of hierarchically scaled landscape patterns
7. Multiresolution fragmentation profiles for assessing hierarchically structured landscape patterns
8. Categorizing and monitoring watershed-delineated landscapes in Pennsylvania using conditional entropy profiles
9. Quantitative multiresolution characterization of landscape patterns for assessing the status of ecosystem health in watershed management areas
10. Fractal based methods in ecology: A review for analysis at multiple spatial scales
11. Some comments on Cp
12. Monitoring environmental quality at the landscape scale; using landscape indicators to assess biotic diversity, watershed integrity and landscape stability
13. A hierarchical framework for the analysis of scale
14. Landscape influences on stream biotic integrity assessed at multiple spatial scales
15. Multivariate statistics with applications in ecology
16. Landscape ecology; a hierarchical perspective can help scientists understand spatial patterns