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Water Management

Research of the Organization for Economic Co-Operation and Development (OECD)

Soil & Water Conservation Society of Metro Halifax (SWCSMH)

Updated: August 12, 2015                                    Eutrophication of Waters (OECD)

(cf. Horner & Associates Ltd., 1995;  Mandaville, 2000;  Vollenweider, 1976; and  Vollenweider and Kerekes, 1982)


Lake Management- Quality objectives as a function of its intended use

Excessive supply of phosphorus in water is the cause of eutrophication, yet phosphorus in itself does not interfere with the normal use of water. The trophic responses caused by the nutrient enrichment such as high algal biomass, dense growth of macrophytes, reduced transparency, and reduced hypolimnetic or oxygen concentrations under ice cover are symptoms of eutrophication which do interfere with normal use of the water. Therefore, water management should consider water quality objectives in terms of trophic response objectives, with regard to the intended use of the water.

These objectives may vary considerably between different regions, depending on local conditions and on the expectation of the population concerning water quality. Depending on the intended use (e.g., drinking water, industrial water, power plant cooling water, recreation, multiple use, etc.), the stringency of objectives could be set at various levels, considering algal biomass (chlorophyll a) as a trophic response indicator, i.e.:

  1. Mean algal biomass (annual, ice-free season, summer) to be kept below a certain level;

  2. Mean annual peak algal biomass to be kept below a certain level;

  3. Exceptional (highest possible) annual peak biomass to be kept below a certain level.

Predictive Models

OECD Management Model (Vollenweider and Kerekes, 1982):

Table-4: Management Model- yearly averages

Management Model- yearly averages (Vollenweider and Kerekes, 1982)

In this system, the trophic categories are slightly more stringently defined (i.e., approximately at the class midpoints) than are the categories used for diagnostic purposes. This provides a certain safety margin for the design of the loading objectives. The OECD Management Model together with the long term correlation equations are depicted in Figure-7 below.

Figure-7: OECD Management Model together with the long term correlation equations

OECD Management Model (Vollenweider and Kerekes, 1982)

Vollenweider 1976 Model (Vollenweider, 1976):

The OECD (1982) regressions above need the water residence time, τw, which in turn would imply mean depth. In many cases, mean depths of lakes are not available. In such cases, this older model, which was also a part of the OECD programme, may be used with the appropriate trophic categories, preferably the OECD (1982) Management Model, plotted on the graphs. Though, one could in reality plot any other categories as well. (cf. Figure-8 below).

The model is: Lc (mg/m.y) = Pcsp (z/τw + 10), where

Lc is the critical loading of phosphorus,
Pcsp is the critical concentration of total phosphorus (mg/m) for simplicity taken at spring overturn,
z is the mean depth, and
τw the water residence time

In this model, z/τw = qs represents the hydraulic load which is independant of mean depth. It can be argued however that the model ignores, or at least underestimates, the effect of mean depth, i.e., the dilution function.

Figure-8: An example of the Vollenweider (1976) Model with the OECD (1982) Management Model trophic categories superimposed (Mandaville, 2000):

An example of the Vollenweider (1976) Model with the OECD (1982) Management Model trophic categories superimposed

Some sensitive areas and exceptions in modelling:

  1. The prediction of lake concentration should be given with statistical confidence limits to reflect more realistically the uncertainties in the model prediction.
    1. The models assume steady state conditions in a completely "mixed reactor".
    2. It is unlikely that individual loading estimates are more accurate than 35%.
    3. The nutrient loading models give an estimation of average conditions; local conditions may deviate considerably, temporally and/or spatially.
    4. The empirical phosphorus loading models should be used only for water bodies within the range of conditions (hydrologic, morphometric, trophic and climatic) represented by each of the model development data set.
    5. A steady state on an annual basis is assumed in the models. This is seldom the case, even in undisturbed natural systems, considerable year to year variations in nutrient load are detected due to fluctuations in annual runoff as well as in the nutrient loads.
    6. The models assume that the basin is open and that there is an annual water surplus or outflow from the lake (the models cannot be applied without modification to closed basins or arid and semi-arid regions).

  2. In large water bodies or those of complex morphometry, localized imbalances in nutrient concentration and trophic response may develop ("local reactors"). In extreme cases localized symptoms of eutrophication may develop near point sources of nutrients, in an otherwise oligotrophic water body.

  3. The relationship between phosphorus and algal chlorophyll (i.e. algal biomass) is a log-log plot of the data, and there is considerable scatter to the linear data, indicating effects from other factors in the pelagic environment, such as light, nitrogen, or zooplankton grazing, in limiting algal biomass. This also indicates that there can be wide variation in the expected chlorophyll from any given phosphorus concentration.

  4. The chlorophyll a - total phosphorus ratio, an index of the efficiency of algae to utilize phosphorus varies greatly among lakes (ca. 0.05 to 0.7 in the OECD programme). A shift in algal composition and the efficiency of phosphorus use can profoundly affect the trophic response in a given water body.

  5. Macrophytes and filamentous algae are ignored in the models, macrophytes may contain large amounts of phosphorus which is ignored in the determination of in-lake P concentration.

  6. Macrophytes often act as nutrient pumps and may cause appreciable internal loading.

  7. Biological activity such as by bottom feeding fish and emerging bottom dwelling invertebrate fauna often produces considerable internal loading of nutrients.

  8. The presence or absence of fish and types present in a lake can profoundly affect the apparent trophic response; in the absence of predation highly abundant zooplankton reduce phytoplankton by grazing which results in lower than expected chlorophyll a concentrations.

  9. The type of algal community can profoundly affect the sedimentation rate of phosphorus; lakes dominated by diatoms remove phosphorus by sedimentation at a much faster rate than lakes dominated by more buoyant green or blue-green algae.

  10. In shallow unstratified lakes, the recycling and utilization of nutrients is more efficient than in deep stratified lakes.

  11. In reservoirs, peculiar flow regimes and hypolimnetic water withdrawal (rich in nutrients) should be taken into account.

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