Affiliation:
1. Department of Fisheries, Wildlife, and Conservation Biology University of Minnesota St. Paul Minnesota USA
Abstract
AbstractLake morphometry is a driver of limnological processes, yet digitized bathymetry is lacking for most lakes. Here, we describe a method for efficiently extracting hypsography from bathymetric maps using ImageJ. To validate our method, we compared results generated from two independent users to those obtained from digital elevation models for 100 lakes. The mean absolute difference between hypsographic curves extracted using ImageJ vs. digital elevation models (DEMs) was 0.049 (95% CI 0.041–0.056) proportion of lake area, suggesting that ImageJ provides accurate hypsography. We calculated the mean absolute difference between the two users (0.016; 95% CI: 0.011–0.021), which suggests high interobserver reliability. Finally, we compared DEMs to an interpolated hypsography using only the maximum lake depth and found large differences. We apply this method to extract data for 1012 lakes. Our data and approach will be useful where bathymetric maps exist but are not digitized.
Funder
Minnesota Department of Natural Resources