Performance of landscape composition metrics for predicting water quality in headwater catchments.

Land use is a predominant threat to the ecological integrity of streams and rivers. Understanding land use-water quality interactions is essential for the development and prioritization of management strategies and, thus, the improvement of water quality. Weighting schemes for land use have recently been employed as methods to advance the predictive power of empirical models, however, their performance has seldom been explored for various water quality parameters. In this work, multiple landscape composition metrics were applied within headwater catchments of Central Europe to investigate how weighting land use with certain combinations of spatial and topographic variables, while implementing alternate distance measures and functions, can influence predictions of water quality. The predictive ability of metrics was evaluated for eleven water quality parameters using linear regression. Results indicate that stream proximity, measured with Euclidean distance, in combination with slope or log-transformed flow accumulation were dominant factors affecting the concentrations of pH, total phosphorus, nitrite and orthophosphate phosphorus, whereas the unweighted land use composition was the most effective predictor of calcium, electrical conductivity, nitrates and total suspended solids. Therefore, both metrics are recommended when examining land use-water quality relationships in small, submontane catchments and should be applied according to individual water quality parameter.