Abstract
We discuss three directions for future research in sustainable natural resource management. These directions are drawn mainly from our research experience and expertise in the energy sector and other natural resource areas. First, we believe that future sustainability and resilience in natural resource management can be enhanced through better utilization of outcomes from process- or physical-based climate change models, such as Global Climate Models. Second, directly related to the electric power sectors is a better harnessing variability and unpredictability via flexibility, transmission, and storage. Third, future natural resource management should consider interdependence of multiple systems, such as power, natural gas, and water systems, through co-optimization of these interdependent systems. We elaborate each of these three future research directions in this chapter.
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Notes
- 1.
Much of the discussion in this section draws upon the first and third author’s experience of working on a project of the California’s Fourth Climate Assessment. However, the discussions here are sufficiently broad to generalize to other situations.
References
Averyt, K., Fisher, J., Huber-Lee, A., Lewis, A., Macknick, J., Madden, N., Rogers, J., & Tellinghuisen, S. (2011). Freshwater use by U.S. power plants: electricity’s thirst for a precious resource: A report of the energy and water in a warming world initiative. Cambridge, MA: Union of Concerned Scientists.
Averyt, K., Fisher, J., Huber-Lee, A., Lewis, A., Macknick, J., Madden, N., Rogers, J., & Tellinghuisen, S. (2013). Water-smart power: Strengthening the U.S. electricity system in a warming world. Cambridge, MA: Union of Concerned Scientists.
Boyd, S., Parikh, N., Chu, E., Peleato, B., Eckstein, J. F. K., Barber, N. L., Hutson, S. S., Linsey, K. S., Lovelace, J. K., & Maupin, M. A. (2011). Distributed optimization and statistical learning via the alternating direction method of multipliers. Foundations and Trends in Machine Learning, 3(1), 1–122.
California Natural Resource Agency. (2019). Introduction to California’s fourth climate change assessment. Retrieved from http://resources.ca.gov/climate/safeguarding/research/.
Cayan, D. R., Pierce, D., & Kalansky, J. (2018). Climate scenarios for the California 4th climate change assessment model selection, downscaling, drought scenario and sea level rise. Retrieved from http://www.climateassessment.ca.gov/techreports/docs/20180827-Projections_CCCA4-CEC-2018-006.pdf.
Chen, Y., Chen, N., Guldmann, J.-M., Liu, A. L., & Wang, C. H. (2020). Investigating climate-change-induced vulnerability of the northern California natural gas energy system and identifying resilience options. Unpublished report, University of California Santa Cruz.
Cook, B. I., Ault, T. R., & Smerdon, J. E. (2015). Unprecedented 21st century drought risk in the American Southwest and Central Plains. Science Advances, 1, 1–7.
Deng, W., Lai, M. J., Peng, Z., & Yin, W. (2017). Parallel multi-block ADMM with o(1=k) convergence. Journal of Scientic Computing, 71(2), 712–736.
Eckstein, J., & Yao, W. (2012). Augmented Lagrangian and alternating direction methods for convex optimization: A tutorial and some illustrative computational results. RUTCOR research reports 32-3.
Haimes, Y. Y., & Jiang, P. (2001). Leontief-based model of risk in complex interconnected infrastructures. Journal of Infrastructure Systems, 7(1), 1–12.
Hawkins, E., & Sutton, R. T. (2011). The potential to narrow uncertainty in projections of regional precipitation change. Climate Dynamics, 37, 407–418.
He, C., Wu, L., Liu, T., & Shahidehpour, M. (2018a). Robust co-optimization scheduling of electricity and natural gas systems via ADMM. IEEE Transactions on Sustainable Energy, 8(2), 658–670.
He, C., Wu, L., Liu, T., & Bie, Z. (2018b). Robust co-optimization planning of interdependent electricity and natural gas systems with a joint N-1 and probabilistic reliability criterion. IEEE Transactions on Power Systems, 33(2), 2140–2154.
Kenny, J. F., Barber, N. L., Hutson, S. S., Linsey, K. S., Lovelace, J. K., & Maupin, M. A. (2009). A 2009 estimated use of water in the United States in 2005. Reston, VA: The U.S. Geological Survey.
Macknick, J., Newmark, R., Heath, G., & Hallett, K. C. (2011). A review of operational water consumption and withdrawal factors for electricity generating technologies. National Renewable Energy Laboratory, technical report: NREL/TP-6A20–50900.
Macknick, J., Newmark, R., Heath, G., & Hallett, K. C. (2012). Operational water consumption and withdrawal factors for electricity generating technologies: A review of existing literature. Environmental Research Letters, 7(4), 1–109.
National Oceanic and Atmospheric Administration. (n.d.) Is sea level rising? Yes, sea level is rising at an increasing rate. Retrieved from https://oceanservice.noaa.gov/facts/sealevel.html.
Ouyang, M. (2014). Review on modeling and simulation of interdependent critical infrastructure systems. Reliability Engineering and System Safety, 121, 43–60.
Pederson, P., Dudenhoeer, D., Hartley, S., & Permann, M. (2006). Critical infrastructure interdependency modeling: A survey of the U.S. and international research. Idaho Falls, ID: Idaho National Laboratory.
Pierce, D. W., Cayan, D. R., Maurer, E. P., Abatzoglou, J. T., & Hegewisch, K. C. (2015). Improved bias correction techniques for hydrological simulations of climate change. Journal of Hydrometerology, 16, 2421–2422.
Pierce, D. W., Cayan, D. R., & Thrasher, B. L. (2014). Statistical downscaling using localized constructed analogs (LOCA). Journal of Hydrometerology, 15, 2558–2585.
Powell, M. J. (1973). On search directions for minimization algorithms. Mathematical Programming, 4(1), 193–201.
Rothausen, S. G. S. A., & Declan, C. (2011). Greenhouse-gas emissions from energy use in the water sector. Nature: Climate Change, 7(4), 210–219.
Spinoni, J., Naumann, G., Carrao, H., Barbosa, P., & Vogt, J. (2014). World drought frequency, duration, and severity for 1951-2010. International Journal of Climatology, 34(8), 2792–2804.
Turchi, C. S., Wagner, M. J., & Kutscher, C. F. (2010). Water use in parabolic trough power plants: Summary results from Worley Parsons’ analyses. National Renewable Energy Laboratory technical report NREL/TP-5500-49468.
U.S. Department of Homeland Security. (2019). Critical infrastructure sectors. Retrieved from https://www.cisa.gov/critical-infrastructure-sectors
U.S. Geological Survey. (2019). 1 meter digital elevation models (DEMs)—USGS National map 3DEP downloadable data collection. Retrieved from https://catalog.data.gov/dataset/usgs-national-elevation-dataset-ned-1-meter-downloadable-data-collection-from-the-national-map.
Wald, M. L. (2012). So, how hot was it? The New York Times. Retrieved from https://green.blogs.nytimes.com/2012/07/17/so-how-hot-was-it/?_r=0.
Wing, I. S., & Kolodziej, M. (2008). The regional greenhouse gas initiative: emissions leakage and the effectiveness of interstate border adjustments. John F. Kennedy School of Government, Harvard University, policy program working paper RPP-2008-03.
World Climate Research Programme. (2019). Overview CMIP6 experimental design and organization. Retrieved from https://www.wcrp-climate.org/wgcm-cmip/wgcm-cmip6.
Zuloaga, S., Khatavkar, P., Vittal, V., Vittal, V., & Mays, L. W. (2019). Interdependent electric and water infrastructure modelling, optimisation and control. IET Energy Systems Integration, 2(1), 9–21.
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Chen, Y., Conejo, A.J., Liu, A.L. (2021). Future Research Directions for Sustainable Natural Resource Management. In: Chen, C., Chen, Y., Jayaraman, V. (eds) Pursuing Sustainability. International Series in Operations Research & Management Science, vol 301. Springer, Cham. https://doi.org/10.1007/978-3-030-58023-0_16
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