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A simple framework for selection of water quality models

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Abstract

Water quality modeling is no longer just the preserve of specialists who seek to describe water quality processes but also for use by non specialists in everyday water quality management issues. With so many models already developed, it becomes prudent to adapt them to a situation than to develop a completely new model that would probably do the same simulations. The question is: which is the most appropriate model to apply to a situation? The specialist can always draw on past experiences to make a decision. However, this is not the case for the non specialist. A lot of different criteria can be used to decide which model to use for a particular situation based on some important factors. The objectives of modeling exercises differ and each water body is unique so there cannot be hard and fast rules on which is the best criteria for selecting the appropriate model. Furthermore, there is usually hardly any time on the project work plan allocated for model selection. Therefore there is need for a simple procedure to select the appropriate model. The objective of this paper was to develop a simple framework for selecting water quality models to aid the non specialist. The framework was then applied to a case study in order to evaluate its usefulness. The results from the case study show that after a thorough literature review, models can be evaluated against chosen criteria and the most appropriate model singled out. It was concluded that the framework is only effective if the research objective is adequately defined and the models are reviewed thoroughly, but it saves time for the actual modeling exercise.

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Acknowledgments

This paper is part of a doctoral fellowship research and the authors would like to acknowledge Tshwane University of Technology for funding the fellowship.

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Correspondence to A. Chinyama.

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Chinyama, A., Ochieng, G.M., Nhapi, I. et al. A simple framework for selection of water quality models. Rev Environ Sci Biotechnol 13, 109–119 (2014). https://doi.org/10.1007/s11157-013-9321-3

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