Decision Support Framework for Water Quality Management in Reservoirs Integrating Artificial Intelligence and Statistical Approaches

Article

Farzana, Syeda Zehan, Paudyal, Dev Raj, Chadalavada, Sreeni and Alam, Md Jahangir. 2024. "Decision Support Framework for Water Quality Management in Reservoirs Integrating Artificial Intelligence and Statistical Approaches." Water. 16 (20). https://doi.org/10.3390/w16202944
Article Title

Decision Support Framework for Water Quality Management in Reservoirs Integrating Artificial Intelligence and Statistical Approaches

Article CategoryArticle
AuthorsFarzana, Syeda Zehan, Paudyal, Dev Raj, Chadalavada, Sreeni and Alam, Md Jahangir
Journal TitleWater
Journal Citation16 (20)
Article Number2944
Number of Pages25
Year2024
PublisherMDPI AG
Place of PublicationSwitzerland
ISSN2073-4441
Digital Object Identifier (DOI)https://doi.org/10.3390/w16202944
Web Address (URL)https://www.mdpi.com/2073-4441/16/20/2944
Abstract

Planning, managing and optimising surface water quality is a complex and multifaceted process, influenced by the effects of both climate uncertainties and anthropogenic activities. Developing an innovative and robust decision support framework (DSF) is essential for effective and efficient water quality management, so it can provide essential information on water quality and assist policy makers and water resource managers to identify potential causes of water quality deterioration. This framework is crucial for implementing actions such as infrastructure development, legislative compliance and environmental initiatives. Recent advancements in computational domains have created opportunities for employing artificial intelligence (AI), advanced statistics and mathematical methods for use in improved water quality management. This study proposed a comprehensive conceptual DSF to minimise the adverse effects of extreme weather events and climate change on water quality. The framework utilises machine learning (ML), deep learning (DL), geographical information system (GIS) and advanced statistical and mathematical techniques for water quality management. The foundation of this framework is the outcomes from our three studies, where we examined the application of ML and DL models for predicting water quality index (WQI) in reservoirs, utilising statistical and mathematical methods to find the seasonal trend of rainfall and water quality, exploring the potential connection between streamflow, rainfall and water quality, and employing GIS to show the spatial and temporal variability of hydrological parameters and WQI. Three potable water supply reservoirs in the Toowoomba region of Australia were taken as the study area for practical implementation of the proposed DSF. This framework can serve as a comprehensive mechanism to identify distinct seasonal characteristics and understand correlations between rainfall, streamflow and water quality. This will enable policy makers and water resource managers to enhance their decision making processes by selecting the management priorities to safeguard water quality in the face of future climate variability, including prolonged droughts and flooding.

Keywordsdecision support framework (DSF); extreme rainfall; streamflow; water quality management; machine learning (ML); geographical information system (GIS); deep learning (DL)
Contains Sensitive ContentDoes not contain sensitive content
ANZSRC Field of Research 2020460999. Information systems not elsewhere classified
Byline AffiliationsSchool of Surveying and Built Environment
School of Engineering
Murray-Darling Basin Authority, Australia
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Paudyal, Dev Raj, McDougall, Kevin and Apan, Armando. 2012. "Spatially enablement of NRM communities through spatial knowledge and information network development." Rajabifard, Abbas and Coleman, David (ed.) Spatially enabling government, industry and citizens: research and development perspectives. Needham, MA, United States. GSDI Association Press. pp. 81-102
Assessing spatial information access, use and sharing for catchment management in Australia
Paudyal, Dev Raj, McDougall, Kevin and Apan, Armando. 2011. "Assessing spatial information access, use and sharing for catchment management in Australia." Hock, Barbara (ed.) 2011 Surveying and Spatial Sciences Conference: Innovation in Action: Working Smarter (SSSC 2011). Wellington, New Zealand 21 - 25 Nov 2011 Rotorua, New Zealand.
Spatial information sharing for catchment management in Australia
Paudyal, Dev Raj. 2012. Spatial information sharing for catchment management in Australia. PhD Thesis Doctor of Philosophy. University of Southern Queensland.
Pro-poor land management in developing countries: a case study in Nepal and India
Paudyal, Dev Raj. 2011. Pro-poor land management in developing countries: a case study in Nepal and India. Saarbrüchen, Germany. VDM Verlag Dr. Muller.
Spatial data infrastructure convergence: building spatial data infrastructure bridges to address climate change
Paudyal, Dev Raj, McDougall, Kevin and Apan, Armando. 2011. "Spatial data infrastructure convergence: building spatial data infrastructure bridges to address climate change." Joshi, P. K. and Singh, T. P. (ed.) Geoinformatics for climate change studies. New Delhi, India. TERI Press. pp. 377-392
Pro-poor land management in developing countries: a case study in Nepal and India
Paudyal, Dev Raj. 2008. Pro-poor land management in developing countries: a case study in Nepal and India. Copenhagen, Denmark. International Federation of Surveyors (FIG).
A regional collaborative network to improve spatial information sharing in Australia
Paudyal, Dev Raj, McDougall, Kevin and Apan, Armando. 2010. "A regional collaborative network to improve spatial information sharing in Australia." 12th Global Spatial Data Infrastructure Association World Conference (GSDI 12). Singapore 19 - 22 Oct 2010 Melbourne, Australia.
Spatial data infrastructure for pro-poor land management
Paudyal, Dev Raj and McDougall, Kevin. 2010. "Spatial data infrastructure for pro-poor land management." Staiger, Rudolf (ed.) 24th International Federation of Surveyors International Congress (FIG 2010): Facing the Challenges - Building the Capacity. Sydney, Australia 11 - 16 Apr 2010 Sydney, Australia.
Spatial data infrastructure for catchment management: a case study of Condamine Catchment, Australia
Paudyal, Dev Raj, McDougall, Kevin and Apan, Armando. 2009. "Spatial data infrastructure for catchment management: a case study of Condamine Catchment, Australia." Indian Cartographer. 28, pp. 439-444.
Building SDI bridges for catchment management
Paudyal, Dev Raj, McDougall, Kevin and Apan, Armando. 2009. "Building SDI bridges for catchment management." van Loenen, B., Besemer, J. W. J. and Zevenbergen, J. A. (ed.) SDI convergence: research, emerging trends, and critical assessment. Delft, Netherlands. Netherlands Geodetic Commission. pp. 265-279
Building spatial data infrastructure to support sustainable catchment management
Paudyal, Dev Raj and McDougall, Kevin. 2008. "Building spatial data infrastructure to support sustainable catchment management." McDougall, Kevin (ed.) Queensland Spatial Conference 2008. Surfers Paradise, Australia 17 - 19 Jul 2008 Brisbane, Australia.