Skip to main content

Advertisement

SpringerLink
Log in

Managing the water–electricity demand nexus in a warming climate

  • Published:
Climatic Change Aims and scope Submit manuscript

Abstract

Models that consider the interconnectivity between urban systems, including water and electricity, are becoming more common, both in research and in practice. However, there are still too few that consider the impact of climate change, and fewer still that look beyond the baseline climate data (i.e., precipitation and temperature). Here, a data-driven, regional model that considers a wider array of climate variables is built and tested to evaluate the impact of climate change on the coupled water and electricity demand nexus in the Midwestern USA. The model, which is based on a state-of-the-art statistical learning algorithm, is first used to compare model runs comprised of different climatic variables. The model runs included a baseline model that considers only precipitation and temperature, as well as a selected feature model that considered a wider array of climatic variables, including relative humidity and wind speed. Following this comparison, the model is used to make future projections of the coupled water and electricity demand as a function of future climate change scenarios. The results indicate that (1) the inclusion of additional climate variables beyond the baseline provides a significant improvement in predictive accuracy, and (2) the climate-sensitive portions of summer electricity and water use are expected to increase in the region by 19% and 7%, respectively. Finally, the regional-scale model is leveraged to make city-level projections, indicating a 10–20% (2–5%) increase in electricity (water) use across the analyzed cities due to a warming climate.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  • Ashoori N, Dzombak DA, Small MJ (2016) Modeling the effects of conservation, demographics, price, and climate on urban water demand in Los Angeles, California. Water Resour Manag 30(14):5247–5262. https://doi.org/10.1007/s11269-016-1483-7

    Article  Google Scholar 

  • Auffhammer M, Baylis P, Hausman CH (2017) Climate change is projected to have severe impacts on the frequency and intensity of peak electricity demand across the United States. Proc Natl Acad Sci 114(8):1886–1891. https://doi.org/10.1073/pnas.1613193114

    Article  Google Scholar 

  • Balling RC, Gober P, Jones N (2008) Sensitivity of residential water consumption to variations in climate: an intraurban analysis of Phoenix, Arizona. Water Resour Res 44(10):1–11. https://doi.org/10.1029/2007WR006722

    Article  Google Scholar 

  • Bartos MD, Chester MV (2014) The conservation nexus: valuing interdependent water and energy savings in Arizona. Environ Sci Technol 48(4):2139–2149. https://doi.org/10.1021/es4033343

    Article  Google Scholar 

  • Bruss CB, Nateghi R, Zaitchik BF (2019) Explaining national trends in terrestrial water storage. Front Environ Sci 7:85

    Article  Google Scholar 

  • Caruana R, Niculescu-Mizil A (2006) An empirical comparison of supervised learning algorithms. In: Proceedings of the 23rd International Conference on Machine Learning. https://doi.org/10.1145/1143844.1143865

  • Cronin J, Anandarajah G, Dessens O (2018) Climate change impacts on the energy system: a review of trends and gaps. Clim Chang 151(2):79–93. https://doi.org/10.1007/s10584-018-2265-4

    Article  Google Scholar 

  • Dai A (2011) Drought under global warming: a review. Wiley Interdiscip Rev Clim Chang 2(1):45–65. https://doi.org/10.1002/wcc.81

    Article  Google Scholar 

  • Dale LL, Karali N, Millstein D, Carnall M, Vicuña S, Borchers N, Bustos E, O’Hagan J, Purkey D, Heaps C, Sieber J, Collins WD, Sohn MD (2015) An integrated assessment of water-energy and climate change in Sacramento, California: how strong is the nexus? Clim Chang 132(2):223–235. https://doi.org/10.1007/s10584-015-1370-x

    Article  Google Scholar 

  • Derrible S (2017) Urban infrastructure is not a tree: integrating and decentralizing urban infrastructure systems. Environment and Planning B: Urban Analytics and City Science 44(3):553–569. https://doi.org/10.1177/0265813516647063

    Article  Google Scholar 

  • Escriva-Bou A, Lund JR, Pulido-Velazquez M (2018) Saving energy from urban water demand management. Water Resour Res 54(7):4265–4276. https://doi.org/10.1029/2017WR021448

    Article  Google Scholar 

  • Friedman JH (2001) Greedy function approximation: a gradient boosting machine. Ann Stat 29(5):1189–1232. https://doi.org/10.1214/aos/1013203451, arXiv:1011.1669v3

    Article  Google Scholar 

  • Gjorgiev B, Sansavini G (2017) Electrical power generation under policy constrained water-energy nexus. Appl Energy 210:568–579. https://doi.org/10.1016/j.apenergy.2017.09.011

    Article  Google Scholar 

  • Hastie T, Tibshirani R, Friedman J (2009) The elements of statistical learning, 2nd edn. Springer, New York. arXiv:1011.1669v3

    Book  Google Scholar 

  • Hauer ME (2019) Population projections for U.S. counties by age, sex, and race controlled to shared socioeconomic pathway. Sci Data 6:1–15. https://doi.org/10.1038/sdata.2019.5

    Article  Google Scholar 

  • Hempel S, Frieler K, Warszawski L, Schewe J, Piontek F (2013) A trend-preserving bias correction—the ISI-MIP approach. Earth Syst Dyn 4(2):219–236. https://doi.org/10.5194/esd-4-219-2013

    Article  Google Scholar 

  • Hussey K, Pittock J (2012) The energy-water nexus: managing the links between energy and water for a sustainable future. Ecol Soc 17(1):31. https://doi.org/10.5751/ES-04641-170131

    Article  Google Scholar 

  • IPCC (2013) Climate change 2013: the physical science basis. Tech. rep

  • IPCC (2018) Global warming of 1.5 ∘C. An IPCC Special Report on the impacts of global warming of 1.5 ∘C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change,. Tech. rep

  • Jacob D, Kotova L, Teichmann C, Sobolowski SP, Vautard R, Donnelly C, Koutroulis AG, Grillakis MG, Tsanis IK, Damm A, Sakalli A, Vliet MTHV, Centre B, Ipsl L, Uvsq CEAC (2018) Earth’s future climate impacts in Europe under + 1.5 ∘c global warming Earth’s future. Earth’s Future 6:264–285. https://doi.org/10.1002/eft2.286

    Article  Google Scholar 

  • James R, Washington R, Schleussner CF, Rogelj J, Conway D (2017) Characterizing half-a-degree difference: a review of methods for identifying regional climate responses to global warming targets. Wiley Interdiscip Rev Clim Chang 8(2). https://doi.org/10.1002/wcc.457

    Google Scholar 

  • Lokhandwala M, Nateghi R (2018) Leveraging advanced predictive analytics to assess commercial cooling load in the U.S. Sustainable Production and Consumption 14:66–81. https://doi.org/10.1016/j.spc.2018.01.001

    Article  Google Scholar 

  • Loulou R, Goldstein G, Noble K (2004) Documentation for the MARKAL family of models (October), http://www.etsap.org/tools.htm

  • Maas A, Goemans C, Manning DT, Burkhardt J, Arabi M (2019) Complements of the house: estimating demand-side linkages between residential water and electricity. Water Resources and Economics. https://doi.org/10.1016/j.wre.2019.02.001

    Article  Google Scholar 

  • Marx A, Kumar R, Thober S, Rakovec O, Wanders N, Zink M, Wood EF, Pan M, Sheffield J, Samaniego L (2018) Climate change alters low flows in Europe under global warming of 1.5, 2, and 3 ∘C. Hydrol Earth Syst Sci 22(2):1017–1032. https://doi.org/10.5194/hess-22-1017-2018

    Article  Google Scholar 

  • Miller PJ, Lubke GH, McArtor DB, Bergeman CS (2016) Finding structure in data using multivariate tree boosting. Psychol Methods 21(4):583–602. https://doi.org/10.1037/met0000087

    Article  Google Scholar 

  • Mostafavi N, Gándara F, Hoque S (2018) Predicting water consumption from energy data: modeling the residential energy and water nexus in the integrated urban metabolism analysis tool (IUMAT). Energy and Buildings 158:1683–1693. https://doi.org/10.1016/j.enbuild.2017.12.005

    Article  Google Scholar 

  • Mukherjee S, Nateghi R (2017) Climate sensitivity of end-use electricity consumption in the built environment: an application to the state of Florida, United States. Energy 128:688–700

    Article  Google Scholar 

  • Mukherjee S, Nateghi R (2019) A data-driven approach to assessing supply inadequacy risks due to climate-induced shifts in electricity demand. Risk Anal 39 (3):673–694. https://doi.org/10.1111/risa.13192

    Article  Google Scholar 

  • Mukherjee S, Nateghi R, Hastak M (2018) A multi-hazard approach to assess severe weather-induced major power outage risks in the us. Reliab Eng Syst Safe 175:283–305

    Article  Google Scholar 

  • Mukherjee S, Vineeth CR, Nateghi R (2019) Evaluating regional climate-electricity demand nexus: a composite Bayesian predictive framework. Appl Energy 235(2018):1561–1582. https://doi.org/10.1016/j.apenergy.2018.10.119

    Article  Google Scholar 

  • Mukhopadhyay S, Nateghi R (2017) Estimating climate—demand nexus to support longterm adequacy planning in the energy sector. In: 2017 IEEE Power & Energy Society General Meeting, IEEE, pp 1–5

  • Nateghi R (2012) Modeling hurricane activity in the Atlantic Basin and reliability of power distribution systems impacted by hurricanes in the US. The Johns Hopkins University

  • Nateghi R (2018) Multi-dimensional infrastructure resilience modeling: an application to hurricane-prone electric power distribution systems. IEEE Access 6:13478–13489. https://doi.org/10.1109/ACCESS.2018.2792680

    Article  Google Scholar 

  • Nateghi R, Mukherjee S (2017) A multi-paradigm framework to assess the impacts of climate change on end-use energy demand. PloS One 12(11):e0188033

    Article  Google Scholar 

  • Nateghi R, Guikema SD, Quiring SM (2011) Comparison and validation of statistical methods for predicting power outage durations in the event of hurricanes. Risk Analysis: An International Journal 31(12):1897–1906

    Article  Google Scholar 

  • Nateghi R, Guikema SD, Wu Y, Bruss CB (2016) Critical assessment of the foundations of power transmission and distribution reliability metrics and standards. Risk Anal 36(1):4–15

    Article  Google Scholar 

  • Newell JP, Goldstein B, Foster A (2019) A 40-year review of the food-energy-water nexus literature with a focus on the urban. Environmental Research Letters

  • NOAA National Centers for Environmental Information (2010) Local climatological data (LCD)

  • Obringer R, Nateghi R (2019) Multivariate modeling for sustainable and resilient infrastructure systems and communities. In: Romeijn H, Schaefer A, Thomas R (eds) Proceedings of the 2019 IISE Annual Conference, 1905.05803

  • Obringer R, Kumar R, Nateghi R (2019) Analyzing the climate sensitivity of the coupled water-electricity demand nexus in the Midwestern United States. Appl Energy 252. https://doi.org/10.1016/j.apenergy.2019.113466

    Article  Google Scholar 

  • Pereira-Cardenal SJ, Madsen H, Arnbjerg-Nielsen K, Riegels N, Jensen R, Mo B, Wangensteen I, Bauer-Gottwein P (2014) Assessing climate change impacts on the iberian power system using a coupled water-power model. Clim Chang 126(3):351–364. https://doi.org/10.1007/s10584-014-1221-1

    Article  Google Scholar 

  • Rachunok B, Nateghi R (2019) Interdependent infrastructure system risk and resilience to natural hazards. arXiv:190405763

  • Rachunok BA, Bennett JB, Nateghi R (2019) Twitter and disasters: a social resilience fingerprint. IEEE Access 7:58495–58506

    Article  Google Scholar 

  • Raymond L, Gotham D, McClain W, Mukherjee S, Nateghi R, Preckel PV, Schubert P, Singh S, Wachs E (2018) Projected climate change impacts on indiana’s energy demand and supply. Clim Chang pp 1–15

  • Ruddell DM, Dixon PG (2014) The energy-water nexus: are there tradeoffs between residential energy and water consumption in arid cities? Int J Biometeorol 58 (7):1421–1431. https://doi.org/10.1007/s00484-013-0743-y

    Article  Google Scholar 

  • Sailor DJ, Muñoz J (1997) Sensitivity of electricity and natural gas consumption to climate in the U.S.A.—Methodology and results for eight states. Energy 22(10):987–998. https://econpapers.repec.org/RePEc:eee:energy:v:22:y:1997:i:10:p:987-998

    Article  Google Scholar 

  • Samaniego L, Thober S, Kumar R, Wanders N, Rakovec O, Pan M, Zink M, Sheffield J, Wood EF, Marx A (2018) Anthropogenic warming exacerbates European soil moisture droughts. Nat Clim Chang 8(5):421–426. https://doi.org/10.1038/s41558-018-0138-5

    Article  Google Scholar 

  • Scanlon BR, Duncan I, Reedy RC (2013) Drought and the water-energy nexus in Texas. Environ Res Lett 8(4). https://doi.org/10.1088/1748-9326/8/4/045033

    Article  Google Scholar 

  • Singh R, Kumar R (2019) Climate versus demographic controls on water availability across India at 1.5 ∘c, 2.0 ∘c and 3.0 ∘c global warming levels. Glob Planet Chang 177(2018):1–9. https://doi.org/10.1016/j.gloplacha.2019.03.006

    Article  Google Scholar 

  • The World Bank (2010) Cities and climate change: an urgent agenda. Tech. rep., The World Bank

  • UNFCC (2015) Adoption of the Paris agreement, Proposal by the President. Tech. rep. United Nations, Geneva, Switzerland

  • US Energy Information Administration (2019) Form EIA-861M Sales and Revenue Data

  • Vautard R, Gobiet A, Sobolowski S, Kjellström E, Stegehuis A, Watkiss P, Mendlik T, Landgren O, Nikulin G, Teichmann C, Jacob D (2014) The European climate under a 2 ∘c global warming. Environ Res Lett 9(3). https://doi.org/10.1088/1748-9326/9/3/034006

    Article  Google Scholar 

  • Venkatesh G, Chan A (2014) Understanding the water-energy-carbon nexus in urban water utilities: comparison of four city case studies and the relevant influencing factors. Energy 75:153–166. https://doi.org/10.1016/j.energy.2014.06.111

    Article  Google Scholar 

  • Warszawski L, Frieler K, Huber V, Piontek F, Serdeczny O, Schewe J (2014) The inter-sectoral impact model intercomparison project (ISI–MIP): project framework. Proc Natl Acad Sci 111(9):3228–3232. https://doi.org/10.1073/pnas.1312330110

    Article  Google Scholar 

  • Wolter K, Timlin MS (1998) Measuring the strength of ENSO events: How does 1997/98 rank? Weather 53(9):315–324

    Article  Google Scholar 

Download references

Acknowledgments

The authors are grateful to the ISI-MIP project for providing the GCM-based climate projection data used in this study. The authors would also like to acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling for the CMIP5 simulations.

Funding

The ISI-MIP project was funded by the German Federal Ministry of Education and Research (BMBF) with project funding reference number 01LS1201A. Additionally, the authors would like to acknowledge the Purdue University Center for the Environment as well as NSF grant nos. 1826161 and 1832688.

Author information

Authors and Affiliations

  1. Environmental and Ecological Engineering, Purdue University, West Lafayette, IN, 47907, USA

    Renee Obringer & Roshanak Nateghi

  2. Department Computational Hydrosystems, Helmholtz Centre for Environmental Research - UFZ, 04318, Leipzig, Germany

    Rohini Kumar

  3. School of Industrial Engineering, Purdue University, West Lafayette, IN, 47907, USA

    Roshanak Nateghi

Authors
  1. Renee Obringer
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Rohini Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Roshanak Nateghi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Renee Obringer.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

(TEX 4.04 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Obringer, R., Kumar, R. & Nateghi, R. Managing the water–electricity demand nexus in a warming climate. Climatic Change 159, 233–252 (2020). https://doi.org/10.1007/s10584-020-02669-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10584-020-02669-7

Keywords

Search

Navigation