A survey of analytical methods for inclusion in a new energy-water nexus knowledge discovery framework

Figures & data

Figure 1. Modeling at the energy-water nexus (adapted from Vallario (2017)).

Figure 2. Notional Summary of Spatial and Temporal Scales for Various Analyses of Energy-Water Nexus Issues. Orange boxes represent the energy sector; blue boxes represent the water sector.

Figure 3. Circos diagram showing categories related by analytical method. Thickness of connecting lines is based on the number of common analytical methods used by each category pair.

Figure 4. Solar power regression ensemble workflow (adapted from Hossain, Oo, and Ali (2012)).

Figure 5. Example Energy-Water Nexus Knowledge Discovery Framework Workflow. Source: Bhaduri et al. (2018).

Vallario, R. (2017). Climate-energy modeling and model interdependencies. Rockville, MD: Presentation at Rockville Hilton.

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Hossain, M. R., Oo, A. M. T., & Ali, A. S. (2012). Hybrid prediction method of solar power using different computational intelligence algorithms. In Power Engineering Conference (AUPEC), 2012 22nd Australasian Universities, 1–6. IEEE.

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Bhaduri, B. L., Simon, A., Allen, M. R., Sanyal, J., Stewart, R. N., & McManamay, R. A. (2018). Energy-water nexus knowledge discovery framework, experts meeting report. Technical report, Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States).

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