Abstract
Narrowing the decision space is crucial in water quality management at the meso-scale for developing countries, where a lack of data and financial budgets prevent the development of appropriate management plans and result in serious water quality degradation in many rivers. In this study, a framework for handling this task is proposed, comprising a lumped water quality model, with sensitivity and uncertainty analyses, and a management domain, including loss estimation and value of information analysis. Through a case study with linear alkylbenzene sulfonate (LAS) in the Yodo River, it is found that non-point sources and flow rate are factors that influence LAS concentration at the hot spot location. By considering the entire process of water quality management planning, we identify that the definition of the cost function of LAS treatment determines the appropriate estimation for the expected loss in reducing LAS under uncertain water quality conditions. The value of information analysis with “expected value of including uncertainty” and “expected value of perfect information” further helps estimate the benefit of including uncertainty in decision-making and the financial cost for obtaining more information regarding inputs that have been previously prioritized.
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Acknowledgments
We thank the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan, for providing a scholarship to study and conduct this research during the graduate course at Osaka University. The authors would like to express appreciation to Lumina Decision Systems for providing a license to use Analytica® software for educational and research purposes that enables us to finish this work.
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Le, A.H., Tokai, A. & Nakakubo, T. Applying value of information methods to prioritize elements for water quality management with an example of linear alkylbenzene sulfonate in the Yodo River, Japan. Environ Syst Decis 34, 110–123 (2014). https://doi.org/10.1007/s10669-014-9490-9
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DOI: https://doi.org/10.1007/s10669-014-9490-9