Digital Signal Processing Reference
In-Depth Information
The following section illustrates a selection of research progress in water quality and ecological
modelling in lakes. These studies shows the application of existing water quality modelling tools and
the development of specific tailored models depending on the objectives of water quality modelling
and the type of lake and associated ecological system.
Collins (1988) performed a study on lake water quality evaluation for management. A set of lake-
evaluation techniques that can be used as early indicators of anthropogenic stress on the aquatic
ecosystem were designed. These approaches were used to predict the response of the ecosystem to
changes in land- and water-use practices in an effort to protect or restore water quality. In this study
the mathematical model CE-QUAL-R1 was used with lake water-quality monitoring, and algae
nutrient bioassay experiments to assess the trophic status of Lake George, New York and to test
suitable management strategies.
Another study was conducted by Stefan et al. (1993) on model simulations of dissolved oxygen
characteristics of Minnesota Lakes
.
A deterministic, one-dimensional, unsteady numerical model has
been developed, tested, and applied to simulate mean daily dissolved oxygen (DO) characteristics in
27 lake classes in the state of Minnesota, USA. Results of the study showed changes of DO due to
climate change effects. Such changes would alter water quality dynamics in lakes and have a profound
effect on lake ecoystems including indigenous fishes. The results presented are useful for evaluating
environmental management options.
A lake ecological model was developed by Sagehanshi
et al.,
2001. In this study, an ecological model
describing the ecosystem of the Keszthely Basin, Lake Balaton, Hungary, one of the typical shallow
and eutrophic lakes, was proposed. This model includes three types of zooplankton and two types of
fish as well as two types of algae and nutrients. Parameters concerning the algae and fish were
estimated based on observations in the basin between 1991 and 1995. The other parameters and the
structure of the model were determined in an earlier study. The parameters of the model were
calibrated with the Monte Carlo technique, and its predictability was confirmed. The effects on the
basin's ecosystem of three restorative manipulations, namely a biomanipulation, reduction of loading
phosphorus, and dredging the sediment, were assessed by simulation studies using the proposed
model.
Del Buttcher (2003) conducted a study on approaches for nutrient management in the lake
Okeechobee Watershed, USA. Phosphorus has been identified as the limiting nutrient for algae
growth, and therefore has been the focus of in-lake and watershed restoration programmes. Watershed
modeling is playing a critical role in assisting water resource planners and regulators in spatially and
temporally quantifying the existing conditions throughout the Okeechobee watershed, as well as
providing cost-effective information for various Best Management Practices scenarios. The Watershed
Assessment Model (WAM) was selected because of its GIS-based structure that provides water and
nutrient flows throughout the entire stream network. This study indicates the importance of integrating
new tools with mathematical models such as GIS for better understanding, visualization and analysis
of the modeled system.
The difference in catchments and hydrology between lakes leads to a difference in nutrient loading and
water residence time. Management options to reduce the trophic state have to be analysed. (Van
Puijenbroek
et al.,
2004), presented the LakeLoad model which calculates the load of nutrients for 41
polder lakes in The Netherlands. Detailed hydrological information on the complex water system of
the polders is used to determine the lake catchment. A lake may loaded as a result of run-off and
leaching in the catchment, atmospheric deposition, point-source emissions and the inlet of water from
outside the polder. These input fluxes are modelled separately and the input is retrieved from other
models and databases. The output of this model is input to the ecological model, PCLake, which
calculates the growth of algae, fish and plants in the lake. Using these models it is possible to calculate
the effects of differences in agricultural practice or the reduction in point sources on the ecological
state of the lake. The effect of water management options, such as phosphorus removal from inlet
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