Lake Water Clarity: Introduction

Water clarity, an indicator of water quality, is a loosely defined term generally related to how far one can see in a water body. The most common way to measure water clarity in lakes is by Secchi disk. This simple device is a weighted 20-cm dia. white disk (or a similar disk with black and white quadrants) that is lowered into the water column until it just disappears from an observer’s view. This depth is called the Secchi depth (SD). SD measurements should be made from the shaded side of a boat preferably around midday (10 am to 2 pm), and in practice, SD is determined as the average of the depths of disappearance and reappearance from a slightly greater depth. Results are reported in meters (m) or in feet (ft).

secchi

Photographs of Secchi disks showing decreasing water clarity from left to right. (Photographs courtesy Minnesota Pollution Control Agency).

SD is related primarily to the concentration of suspended particles in the water column, but CDOM, especially at high levels, also affects SD. SD varies widely among lakes and also varies considerably during the ice-free season in northern lakes; minima occur in late summer in association with algal blooms. SD values < 1 m usually indicate impaired waters that do not fully support their intended uses. Typical values for recreational lakes in Minnesota range from ~1 to 4 m, but values as high as 10-20 m can be found in large, deep lakes. In 2014, our group measured an SD of 64 ft (19.5 m) in a deep mine pit lake near Babbitt, MN.

Although the Secchi disk is a very simple device, an extensive theory has been developed to explain its results. For example, SD-1 is proportional to the sum of two fundamental optical prop­erties: α + Kd; α is the “beam attenuation coefficient” measured by an underwater trans­missometer, and Kd is the “diffuse attenuation coefficient” measured as the incident light remaining versus depth using an underwater light meter.

SD has two important features that make it a useful indicator of water quality. First, it is closely related to other important water quality indicators. Many past studies have found linear correlations between the reciprocal of SD (SD-1) and total phosphorus and chlorophyll concentrations. Second, SD values also are correlated with user perceptions of lake suitability for swimming and related recreational activities. A study on human perceptions of lake suitability in Minnesota found that SD values indicative of user-perceived impairment vary by eco­region (Heiskary and Wilson 1989). These authors found that lake users in the Northern Lakes and Forest (NLF) ecoregion region of northeastern Minnesota consider lakes to be impaired at larger SD values than lake users in agricultural southwestern Minnesota.  Water clarity (SD) tends naturally to be high in the NLF and typically is much lower in the southwestern ecoregions.

Three primary optical variables control SD values: chlorophyll (or algae and related suspended particles that chlorophyll represents), mineral suspended solids (SSmin), and organic color (CDOM). Chlorophyll and algal particles control SD in most lakes. SSmin and non-algal organic particles can be important in rivers and reservoirs affected by urban or agri­cultural activities. CDOM is the dominant control in highly colored lakes and some rivers draining forested wetlands. Satellite-inferred SD typically is calculated using empirical equations that respond primarily to algal and mineral turbidity, and reported relationships typically explain ~ 75-85% of the variance in SD. Current empirical equations do not work well in lakes with very high CDOM (a440 > ~ 10 m-1), but these are relatively uncommon.

A large database of SD derived from satellite imagery has been developed over the past 15 years in the lake-rich Upper Great Lakes states. In Minnesota, seven assessments have been completed of satellite-inferred SD across the state, each including >10,000 lakes (Olmanson et al. 2008). The results have been analyzed for temporal trends and geographic, land-cover, and hydrologic patterns (Olmanson et al. 2014). SD results for Minnesota lakes are available through the Lake Browser; other links on the Water Clarity tab show our SD studies at city to regional scales. Wisconsin and Michigan  also provide such web-based information.

References

Heiskary, S. A. and C. B. Wilson. 1989. The regional nature of lake water quality across Minnesota: An analysis for improving resource management. J. Minnesota Acad. Sci. 55: 71-77.

Olmanson, L. G., P. L. Brezonik and M. E. Bauer. 2014. Geospatial and temporal analysis of a 20-year record of Landsat-based water clarity in Minnesota’s 10,000 lakes. J. Amer. Water Resour. Assoc. 50(3): 748-761. DOI: 10.1111/jawr.12138.

Olmanson, L. G., M. E. Bauer, and P. L. Brezonik. 2008. A 20-year Landsat record of water clarity in Minnesota’s 10,000 lakes. Remote Sens. Environ. 112: 4086-97.