Landscape indicators of stream water quality in central Appalachia (USA): Land use/land cover or land surface condition?

Abstract

Relationships between land use/cover (LUC) and stream water quality have been well-documented in many environments and at a range of spatial scales. From these analyses, reduced in-stream biological integrity and habitat quality are commonly associated with increasing amounts of anthropogenic LUC. However, very few studies have examined the influence of landscape condition, relative to studies using LUC, on water quality parameters. Landscape condition indices use remote sensing-based data to quantify biophysical land surface condition.

The primary objective of this study was to assess the relationships between LUC class proportions and indices of land surface condition (LSC) and macroinvertebrate-based water quality metrics. These relationships were examined at three spatial scales (reach, stream network, and catchment). Strong correlations were observed between both LUC class proportions and LSC indices with macroinvertebrate-based metrics, although there was almost twice the number of significant correlations for LUC as compared with LSC. Similar to previous research, relationships between landscape variables and macroinvertebrate metrics were not consistent across spatial scales. Overall, results suggest that LUC class proportions are better indicators of water quality conditions in the study area. Future work will expand this analysis and include additional water quality parameters and landscape variables with the goals of deepening the understanding of landscape impacts on stream water quality and providing resource managers with valuable information that will to help guide planning and assessment activities.

Keywords:

• Landsat
• macroinvertebrate
• scale
• remote sensing

Acknowledgements

Financial support was provided by the Institute for Regional Analysis and Public Policy at Morehead State University. Juli Taylor, Brittany Moody and Alan Grubb assisted with data collection and processing.