Empirical Relationships Between Watershed Attributes and Headwater Lake Chemistry in the Adirondack Region

摘要

This study focuses on the Adirondack region of New York and has two purposes: to (1) develop empirical models that can be used to assess the chemical status of lakes for which no chemistry data exist and (2) determine on a regional scale watershed attributes that account for variability in lake pH and acid-neutralizing capacity (ANC). Headwater lakes, rather than lakes linked to upstream lakes, were selected for initial analysis. Both bivariate (correlations and Wilcoxon and Kruskal-Wallis tests) and multivariate analyses were performed. Fifty-seven watershed attributes were selected as input variables to multiple linear regression and discriminant analysis. For model development approx.200 lakes for which pH and ANC data exist were randomly subdivided into a specification and a verification data set. Several indices were used to select models for predicting lake pH (31 variables) and ANC (27 variables). Twenty-five variables are common to the pH and ANC models: four lake morphology, nine soil/geology, eight land cover, three disturbance, and one watershed aspect. An atmospheric input variable (H sup + or NO sub 3- ) explains the greatest amount of variation in the dependent variable (pH and ANC) for both models. The percentage of watershed in conifers is the next strongest predictor variable. For all headwater lakes in the Adirondacks, approx.60% of the lakes are estimated to have an ANC less than or equal to50 mu eq/L, and 40% of the lakes have a pH less than or equal to5.5, levels believed to be detrimental to some fish species. (ERA citation 12:039614)