Long-term lake water quality predictors

Midhat Hondzo, Heinz G. Stefan

Research output: Contribution to journalArticlepeer-review

23 Scopus citations

Abstract

Daily water temperature and dissolved oxygen profiles in 3002 Minnesota lakes have been simulated by deterministic process-based water quality models with daily meteorological conditions from 1955 to 1979 as input. From the simulated results, indicators of lake water quality and fish habitat characteristics have been extracted and correlated selectively with normal air temperature, lake mean depth, wind-related densimetric Froude number and Lake number. A seasonal maximum Lake number was found to be a good predictor for volume averaged water temperatures, maximum water temperatures near lake bottom, seasonal stratification characteristics, volume averaged dissolved oxygen concentrations, anoxia characteristics and fish good-growth habitat. Lakes with a maximum daily Lake number bigger than 1.0, are seasonally stratified, have low hypolimnetic dissolved oxygen concentration, and only a fraction of lake depth available for good-growth of fish. Lakes with maximum daily Lake number less than 1.0 are polymictic, with high dissolved oxygen concentration, and with maximum depth available for good fish growth. Empirical formulas for lake water quality and stratification indicators derived from the simulation results give good predictions of temperature and dissolved oxygen characteristics estimated from measurements in seven Minnesota lakes.

Original languageEnglish (US)
Pages (from-to)2835-2852
Number of pages18
JournalWater Research
Volume30
Issue number12
DOIs
StatePublished - Dec 1996

Keywords

  • Dissolved oxygen
  • Fish habitat
  • Long-term average
  • Numerical simulations
  • Predictor variables
  • Water temperature

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