Evaluating cross-sectoral impacts of climate change and adaptations on the energy-water nexus: a framework and California case study

Water and energy ⁵ systems worldwide are, by design and necessity, interdependent: water is an input for hydropower generation and thermal power plant cooling, and electricity powers the conveyance, treatment, usage, and disposal of water. These connections have commonly been referred to as the 'energy-water nexus' [1–5]. Climate change and the resulting shifts in the global hydrologic cycle [6, 7] may strengthen or strain these nexus connections in new and uncertain ways [8]. For example, temperature and precipitation changes could simultaneously increase irrigation water demand and energy requirements for groundwater pumping, while reducing surface water and hydropower availability [9, 10]. Further, water sector adaptation measures commonly sought during long-term declines in surface water, such as water recycling, desalination, or groundwater recharge and withdrawal, are energy-intensive [4, 11–14]. Ignoring such interactive climate impacts in planning reduces the reliability of both systems and increases the risk of cascading failures [15–19].

Climate change impacts on the energy and water sectors have been studied extensively, yet several gaps remain in the literature. On the one hand, many climate vulnerability studies evaluate risks to individual sectors but have not holistically assessed compounding climate risks, such as those inherent in the dynamic relationship between closely coupled electricity and water systems [15, 19–21]. Typically these analyses evaluate electricity [9, 22, 23] or water systems [24] in isolation assuming the other remains fixed, or assess climate-related changes to supplies or demands separately [9, 25–27], making it difficult to account for interdependent impacts within and across sectors. On the other hand, many energy-water 'nexus' studies—focused on demonstrating how integrated systems' management improves efficiency, increases equitable resource access, and maximizes synergies [2]—characterize historical conditions without climate change [28–30]. The cross-sectoral tradeoffs of climate adaptation strategies, such as the energy footprint of alternative water supplies, are particularly understudied despite recognition that ignoring such externalities could lead to maladaptation, whereby one sector's adaptation strategies increase climate vulnerabilities in another [29, 31, 32].

Given such complexity, a conceptual framework describing key system linkages and dynamics is essential to guide analysis [33]. In the first half of this paper, we integrate findings from the fragmented literature into a generalized framework that catalogues how the relationship between electricity and water systems around the world may evolve under, and adapt to, climate change. This framework identifies the most critical cross-system climate impacts, adaptations, and feedbacks, to guide long-term planners on what to evaluate to comprehensively understand the scale and uncertainties of climate risks and adaptations of their resources. Because of regional variations in climate and infrastructure, in the second half of this paper we use a case study approach to apply the framework, focusing on the state of California.

As a semi-arid, populous, and agriculturally-intensive state, California's electricity and water systems are inextricably linked. On average 9% of California's electricity consumption is from water conveyance, treatment of drinking and wastewater, and agricultural pumping [30], and about 10% of electricity consumption is from water end-uses [34]. The water sector is especially energy-intensive because of inter-basin transfers between the wet Northern and dry Southern regions [35]. Additionally, about 15% of in-state electricity generation comes from hydropower [36,37]. California, considered one of the most 'climate-challenged regions in North America,' [38] is projected to face temperature increases, more frequent droughts, and significant loss of snowpack (a major source of water storage) [39–41]. Recent droughts foreshadow how the state's energy-water nexus may fare under these impacts of climate change [19]. California's water sector's drought responses transferred and compounded vulnerability to its electricity sector—increased groundwater pumping spiked electricity consumption, while hydropower deficits were replaced by greenhouse gas (GHG)-emitting fossil generation [37, 42]. In addition, the state has already seen several unprecedented climate-related impacts to the electricity grid, such as the August 2020 West-wide heat wave that triggered California's rolling blackouts [43].

In our case study, we quantify climate impacts by first synthesizing the range of individual water and electricity supply and demand changes projected by California-specific studies. Aggregating these projections, we estimate the overall change to the state's water and electricity annual resource balances due directly to climate impacts and indirectly to various potential climate adaptations by the end-century. We find that in the electricity sector, increased electricity demand for air-conditioning is the primary contributor to demand-supply imbalances. In the water sector, California's future water balance could span a wide range of shortage or surplus under climate change, driven mainly by large supply uncertainties. In the event of the worst-case water shortage, our results show that water-conserving adaptation measures provide large energy savings co-benefits, while other energy-intensive water adaptations may double the electricity resource imbalance caused by direct climate impacts alone. Through this analysis, we both quantify the compounding climate risks and demonstrate mutually beneficial adaptation opportunities that could arise with increased energy-water cross-sectoral coordination. We summarize the framework in section 2, the California case study methodology in section 3, and the case study results in sections 4 and 5.

One of the core objectives of water and energy resource planners is to ensure adequate supplies to balance forecasted demands (subject to environmental, economic, and other constraints) [44–46]. Our framework (figure 1) thus distills findings from across the literature on how climate change may affect these key metrics of annual supply and demand quantities, and subsequent resource balances, of regional energy and water systems (linkages ${{{\boldsymbol{L}}}_1}$ through ${{{\boldsymbol{L}}}_{15}}$). This framework provides a first-order, system-level assessment tool to help resource planners and researchers identify the largest potential climate stressors, the range and order of magnitude of climate adaptation measures that may be needed, the possible compounding vulnerabilities due to cross-sectoral feedback effects, and the key uncertainties and knowledge gaps for further analysis.

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The framework centers (grey box) on the most relevant ⁶ projected climate change impacts—increased temperatures, reduced snowpack, earlier snowmelt, changed precipitation patterns, and more frequent extremes. Across future GHG emission scenarios, global circulation models (GCMs) project climate change will increase surface temperatures worldwide [6]. Although there is uncertainty about future precipitation [26, 47], wetter regions, such as the northern high latitudes, are expected to become wetter, while some drier regions, such as in the mid-latitudes, may become drier [47–49]. Higher temperatures will also shift precipitation towards rain, while reducing accumulation and speeding melt of snowpack, a natural slow-release reservoir that meets warm-season water demands [27, 50–54]. In many regions, the frequency and intensity of storms and droughts will also increase [6, 55, 56]. These climate impacts directly affect water supply (raw water availability, ${{{\boldsymbol{L}}}_1}$) and demand (irrigation water, ${{{\boldsymbol{L}}}_2}$), and electricity supply (transmission and generation efficiency, ${{{\boldsymbol{L}}}_3}$) and demand (air-conditioning, ${{{\boldsymbol{L}}}_4}$). There are subsequent feedbacks, e.g. water supply shifts (${{{\boldsymbol{L}}}_1}$) affect electricity supply (hydropower generation, ${{{\boldsymbol{L}}}_5}$ and thermoelectric cooling, ${{{\boldsymbol{L}}}_6}$). In response to a resource imbalance, adaptation measures can reduce water demands (${{{\boldsymbol{L}}}_7}$) or augment water supplies (${{{\boldsymbol{L}}}_9}$), but may inadvertently affect electricity demand (${{{\boldsymbol{L}}}_8}$, ${{{\boldsymbol{L}}}_{10}}$) and adaptations (${{{\boldsymbol{L}}}_{13}}$). Electricity adaptation strategies can expand supply-side capacity (${{{\boldsymbol{L}}}_{11}}$) and either reduce consumption through energy efficiency or increase consumption through electrification on the demand-side (${{{\boldsymbol{L}}}_{12}}$). Decarbonization of centralized electricity supply can reduce thermal power plant cooling water demands (${{{\boldsymbol{L}}}_{14}}$), and decentralized solar generation can power irrigation pumps and small-scale desalination to expand access to water supplies (${{{\boldsymbol{L}}}_{15}}$). Population growth, urbanization, and policy changes also affect energy and water systems.

In the framework diagram, changes in electricity supply and demand quantities due to climate impacts are denoted with solid orange linkages and water quantity changes are denoted with solid blue linkages. Dotted lines indicate supply and demand must balance in each system. Linkages that increase (decrease) quantities have + (−) and are green (red) if they decrease (increase) a system's demand-supply imbalance, i.e. difference or gap between demand and supply. Linkages with both + and − indicate disagreement in literature or multiple strategies with different effects (e.g. electrification increases while energy efficiency decreases demand; both are electricity demand-side adaptations). These linkages are reviewed below, with more details in the Supplemental Information (SI) (available online at https://stacks.iop.org/ERL/15/124065/mmedia).

2.1. Linkages ${{{{L}}}_1}$—${{{{L}}}_{6}}$: climate impacts on water and electricity supply and demand

2.2. Linkages ${{{{L}}}_7}$—${{{{L}}}_{15}}$: climate adaptations for water and electricity and their feedbacks

2.3. External factors: population growth, urbanization, policy changes

We apply our framework to California by: (1) synthesizing the range of climate impacts on linkages ${{{\boldsymbol{L}}}_1}$through ${{{\boldsymbol{L}}}_5}$ from existing studies (2) estimating the subsequent aggregate effect of climate change directly on both systems' annual resource balances, and (3) calculating energy consumption (${{{\boldsymbol{L}}}_8}$, ${{{\boldsymbol{L}}}_{10}}$) tradeoffs of different water adaptation strategies (${{{\boldsymbol{L}}}_7},{{\boldsymbol{\,}}}{{{\boldsymbol{L}}}_9}$) in the event of a worst-case water shortage.

We exclude changes to cooling water (${{{\boldsymbol{L}}}_6}$ or ${{{\boldsymbol{L}}}_{14}}$) because California already uses minimal freshwater, ⁷ and must further reduce thermal generation (excepting small shares of biomass and solar thermal) to meet its 2045, 100% carbon-free energy goal [121, 122]. We also omit solar PV and wind generation losses in ${{{\boldsymbol{L}}}_3}$ because of uncertain end-century resources and nominal expected impacts (solar capacity declines <2%) [72]. Subsequent analysis is planned for ${{{\boldsymbol{L}}}_{11}}$ through ${{{\boldsymbol{L}}}_{13}},{{\boldsymbol{\,}}}{{{\boldsymbol{L}}}_{15}}$, and external factors ⁸ .

3.1. Synthesis of climate impacts on water and electricity resource balances

We review literature quantifying climate change impacts on California's energy and water supplies and demands, excluding analyses with limited geographic coverage (apart from irrigation and hydropower which are typically analyzed regionally), and collect results from 18 studies for ${{\boldsymbol{{L}}}_{1}}$through ${{\boldsymbol{{L}}}_{5}}$. For each linkage, we cull the maximum and minimum of annual percentage changes to resources projected for end-century (2070–2100) ⁹ , characterizing the combined uncertainty from different methodologies, GCMs, and emissions scenarios across studies (more details on studies in table S2).

We standardize these ranges as absolute changes in water and energy volumes, applying the climate perturbation percentages to historical electricity and water stocks ¹⁰ (table 1 and S3). Finally, to calculate the overall bounding 'worst-case' and 'best-case' range of climate impacts on annual state water and energy balances, for each system the maximum of demand changes are subtracted from the minimum of supply changes, and the minimum of demand changes are subtracted from the maximum of supply changes, respectively. A resulting balance change that is negative indicates shortage (demand exceeds supply), and a positive balance change indicates surplus (supply exceeds demand). These sign conventions and method of calculation are appropriate to bound the systemwide worst-case and best-case because the climate impacts on demand and supply are coincident i.e. supply will decrease at the same time as demand will increase and vice versa.

Table 1. Calculations for climate change impacts on California annual water and electricity resource balances. $L_{1}$ and $L_{2}$ are calculated with 2002–2015 average urban and agricultural water balance data from the California Department of Water Resources [123] in Billion cubic meters, Bm³. Electricity linkages are calculated with residential and commercial building ($L_{4}$) and total ($L_{3}$) 2001–2018 average electricity consumption data from the California Energy Commission [124], and hydropower generation data ($L_{5}$) averaged 2002–2018 from the Energy Information Administration [125] in terawatt-hours, TWh. Irrigation demand changes ($L_{2}$) are calculated for the main agricultural regions (Sacramento Valley (Sac), San Joaquin Valley (SJV), Tulare Lake (Tul)) and hydropower changes are calculated for high- (>300 m) and low-elevation generators ($L_{5}$).

Annual water supply changes	Annual water demand changes
${{{\boldsymbol{L}}}_{1}}$, Raw water availability $\Delta \left[ Bm^{3} \right] =$ $\left( Total\,urban\,and\,ag.\,water,\,53\,Bm^{3}\right)*\left(\% \Delta \right)$	${{{\boldsymbol{L}}}_{2}}$, Irrigation water demand $\Delta \left[ Bm^{3} \right] =$ $\begin{array}{l} \left( Irrigation\,demand_{Sac}, \,10\,Bm^{3} \right)*\,\left( \% \, \Delta _{Sac} \, \right) \,+ \\\left( Irrigation\,demand_{SJV}, \,9\,Bm^{3} \right)*\,\left( \% \, \Delta _{SJV} \, \right) \,+ \\ \left( Irrigation\,demand_{Tul.}, \,14\,Bm^{3} \right)*\,\left( \% \, \Delta _{Tul.} \, \right)\end{array}$ $\,$ $\,$ $\,$
Total change in annual water balance
Annual water balance $\Delta \left [ Bm^{3} \right] = L_{1} - L_{2} \,:$ Worst-case water balance $\Delta \left [ Bm^{3} \right] = min \left( L_{1} \right) - max \left( L_{2} \right)$ Best-case water balance $\Delta \left[ Bm^{3} \right] = max \left ( L_{1} \right) - min \left ( L_{2} \right )$
Annual electricity supply changes	Annual electricity demand changes
${{{\boldsymbol{L}}}_{3}}$, Supply impact of transmission losses $\Delta \left[ TWh \right] =$ $\left( Total\,elec.\,consumption, \, 278\, TWh \right) *\, \left( \% \Delta \right)$ ${{{\boldsymbol{L}}}_{5}}$, Hydropower generation $\Delta \left[ TWh \right] =$ $\begin{array}{l} \left(Hydro\,generation_{low-elev.}, \, 11 \,TWh \right) *\, \left(\% \, \Delta _{low-elev.}\right)\, + \\ \left( Hydro\,generation_{high-elev.},\, 20\,TWh\right)*\, \left( \% \, \Delta _{high-elev.} \right)\end{array}$	${{{\boldsymbol{L}}}_4}$, Air-conditioning demand $\Delta \, \left[ TWh \right] =$ $\left(Res.\, and \,com.\, elec.\, consumption,\, 190\,TWh \right) *\,\left( \% \,\Delta \, \right)$
Total change in annual electricity balance
Annual electricity balance $\Delta \left[ TWh \right] = \left( L_{3} + L_{5} \right) - L_{4} :$
Worst-case electricity balance $\Delta \left[ TWh \right] = \left( min \left( L_{3} \right) + min \left( L_{5} \right) \right) - max \left( L_{4} \right)$
Best-case electricity balance $\Delta \left[ TWh \right] =$ $\left( max \left( L_{3} \right) + max \left( L_{5} \right) \right) - min \left( L_{4} \right)$

3.2. Climate adaptations for water shortages and their energy tradeoffs

If the worst-case, upper end of the water shortage calculated in section 3.1 is realized, significant application of adaptation measures that either augment water supplies or reduce water demands may be needed. We estimate the energy balance feedback (${{\boldsymbol{{L}}}_8}$, ${{\boldsymbol{{L}}}_{10}}$) from residential water conservation, agricultural water conservation, groundwater banking, water recycling for indirect potable reuse, and desalination adaptation measures (${{\boldsymbol{{L}}}_7},{{{\,}}}{{{\boldsymbol{L}}}_9}$) that could fill the maximum water shortage volume.

As shown in table 2, we first calculate the net energy intensity $\left( {NE{I_{i,j}}} \right)$ of each adaptation measure, by summing the average energy intensities of all processes required to implement the measure (i.e. treatment, pumping, etc.) [126] as $E{I_i}$, and subtracting $E{I_j},\,$the energy intensity of the water source it may replace because of climate impacts [105]. These energy intensity values are averages across studies as described in S3 [10, 11, 13, 30, 34, 108, 127–130,133–137].

$$\begin{equation*}NE{I_{i,j}} = E{I_i} - \,E{I_j}\end{equation*}$$

Table 2. Net energy intensity of water adaptations in California. Net energy intensity of a water adaptation measure $NEI_{{i,j}}$ is the difference in energy intensity of the substituted water source $EI_{{j}}$ and adaptation measure $EI_{{i}}$. $EI_{{i}}$ is the sum of energy spent in implementing the measure, using statewide averages of associated processes listed in the table. Negative $EI_{i}$ and $NEI_{i,j}$ values indicate energy savings, and positive values indicate energy consumption. $EI_{i}$ of residential water conservation includes energy savings from avoided water treatment, urban distribution, water heating, and wastewater treatment. $EI_{i}$ of agricultural water conservation includes energy savings from avoided agricultural distribution and irrigation. $EI_{i}$ of groundwater banking includes energy for groundwater pumping. $EI_{i}$ of water recycling includes energy for incremental treatment above wastewater treatment for indirect potable reuse, and for distribution from the treatment plant to storage. $EI_{i}$ of desalination includes energy for reverse osmosis treatment, averaged across values for seawater and brackish water, and for distribution from the treatment plant. Three $EI_{j}$ are included: local surface water (0.09 kWh m⁻³), California supply-weighted average (0.32 kWh m⁻³), and the average across delivery points of the State Water Project conveyance system (1.55 kWh m⁻³). $EI_{i}$ references: [10, 11, 13, 30, 34, 108, 127–130,133–137].

Water adaptation measures $i$	Calculation of $EI_{i}$ of adaptation measure [kWh m−3]	$EI_{i}$ of adaptation measure [kWh m−3]	$NEI_{i,j}$ swith $EI_{j}$ of local surface water [kWh m−3]	$NEI_{i,j}$ with $EI_{j}$ of CA avg. water source [kWh m−3]	$NEI_{i,j}$ with $EI_{j}$ of State Water Project water [kWh m−3]
$L_{7}$, Residential water conservation	$\begin{array}{l} - \left( treatment\,energy,\,0.17,\right.\\ + urban\,distribution\,energy,\,0.27\\ + res.\,water\,heating\,energy,3.16\\ \left. + wastewater\,treat.\,energy,0.69 \right)\end{array}$	−4.29	−4.39	−4.62	−5.84
${{{L}}}_{7}$, Agricultural water conservation	$\begin{array}{l} - \left( ag.\,distribution\,energy,\,0.21\right. \\ \left.+ irrigation\,energy,\,0.09 \right)\end{array}$	−0.30	−0.39	−0.62	−1.84
${{{L}}}_{9}$, Groundwater banking	$groundwater\,pumping\,energy,\, 0.38$	0.38	0.28	0.05	−1.17
${{{L}}}_{9}$, Water recycling for potable reuse	$\begin{array}{l} incremental\,treat.\,energy,\, 0.95 \\+ recycled\,dist.\,energy,\, 0.27\end{array}$	1.22	1.13	0.90	−0.32
${{{{L}}}_9}$, Desalination	$\begin{array}{l} desal\,treatment\,energy,\,2.55 \\+ desal\,dist.\,energy,\,0.29\end{array}$	2.84	2.75	2.52	1.30

where,

$E{I_i} =$ Energy intensity of adaptation $i$, summing energy intensities of all associated processes in $kWh \, m^{-3}$, {Residential water conservation, agricultural water conservation, groundwater banking, water recycling, desalination}.

$E{I_j} =$ Energy intensity of substituted water source $j\,$in $kWh \, m^{-3}$, $j\, \in$ {local surface water, California volume-weighted average water source, State Water Project deliveries}.

For example, if climate change effectively reduces deliveries via the energy-intensive State Water Project (SWP) inter-basin transfer, the $NEI_{i,j}$ of an adaptation measure is net of avoided SWP conveyance energy. Because of uncertainties in where and how much of each water source may be substituted, for each adaptation we test three $E{I_j}$ sensitivities that each assume a single source of substituted water $j$—local surface water (0.09 kWh m⁻³), a weighted average of all California water supplies (0.32 kWh m⁻³), and SWP deliveries (1.55 kWh m⁻³) (details in S3).

We then construct five corner case scenarios of each individual adaptation measure addressing 100% of the worst-case maximum water shortage volume, and four portfolio scenarios, ranging from most to least diversified, combining multiple measures capped at their feasible volume limits (table 3). Portfolio 1 caps residential (indoor plus outdoor) water conservation at 1.8 Bm³/year [96] and water recycling at 6.7 Bm³/year [12, 13] with the remaining shortage equally satisfied by groundwater banking, agricultural conservation, and desalination. Portfolios 2 through 4 cap residential conservation and recycling, and desalination meets the remaining volume.

Table 3. Scenarios of water sector climate adaptations. In corner case scenarios, the water shortage volume $WSV_{i}$ is equal to 100% of the worst-case water shortage volume (18 Bm³) calculated in section 3.1. In portfolio scenarios, $WSV_{i}$ contributions of several measures sum to address the worst-case water shortage. Water conservation and water recycling are capped at their limits,1.8 Bm³/year [96] and 6.7 Bm³/year [12, 13], respectively.

Corner case scenarios	${{{WS}}}{{{{V}}}_i}$ filled by adaptation measures	Portfolio scenarios	${{{WS}}}{{{{V}}}_i}$ filled by adaptation measures
Corner case 1:		Portfolio 1:
100% Residential water conservation	18 Bm3	10% Residential water conservation	1.8 Bm3
		18% Agricultural water conservation	3.2 Bm3
		18% Groundwater banking	3.2 Bm3
		37% Water recycling for potable reuse	6.7 Bm3
		18% Desalination	3.2 Bm3
Corner case 2:		Portfolio 2:
100% Agricultural water conservation	18 Bm3	10% Residential water conservation	1.8 Bm3
		37% Water recycling for potable reuse	6.7 Bm3
		53% Desalination	9.5 Bm3
Corner case 3:		Portfolio 3:
100% Groundwater banking	18 Bm3	10% Residential water conservation	1.8 Bm3
		90% Desalination	16.2 Bm3
Corner case 4:		Portfolio 4:
100% Water recycling for potable reuse	18 Bm3	37% Water recycling for potable reuse	6.7 Bm3
		63% Desalination	11.3 Bm3
Corner case 5:
100% Desalination	18 Bm3

Finally, for each combination of adaptation scenario $s$ and substituted water source $j$, we calculate the overall energy balance impact, $E{B_{s,j}}$, as the sum-product of the $NE{I_{i,j}}\,$ of included adaptation measures from table 2 and associated water volumes $WS{V_i}$ from table 3.

$$\begin{equation*}E{B_{s,j}} = \,\mathop \sum \limits_{i = 1}^n \left( {NE{I_{i,j}}\,} \right)\, \times \,\left( {WS{V_i}} \right)\end{equation*}$$

where,

$NE{I_{i,j}} =$ Net energy intensity for adaptation measure $i$ for substituted water source $j$ in $kWh \, m^{-3}$

$WS{V_i} =$ Water shortage volume filled by adaptation measure $i$ in ${m^3},\,i \in \{$Residential water conservation, agricultural water conservation, groundwater banking, water recycling, desalination$\}$ and $j \in \{$local surface water, California volume-weighted average water source, SWP deliveries$\}.$

For California's water system, we find that by end-century, climate change may cause an annual average imbalance ranging from an 18 Bm³ shortage in the worst-case to a 24 Bm³ surplus in the best-case (table 4, figure 2(a)). This large range is dominated by widely differing estimates (25% decrease to 46% increase) of raw water availability (${{{\boldsymbol{L}}}_1}$) [57, 131, 132]. Despite rich literature on California hydroclimatic phenomena and on subsets of its water system [12, 24, 39, 138] we find relatively little research estimating changes in California's total managed water supply. Further, studies differ on the degree to which any increased November through March runoff under climate change could be captured for water supplies, due to concurrent reservoir flood control requirements [39, 57]. Increased irrigation water demand (${{{\boldsymbol{L}}}_2}$) contributes the remaining imbalance; demands could decrease 2% or increase up to 31% within California's individual agricultural regions [61, 62, 104, 139, 140]. The variation reflects assumptions for ET and plant physiology [139], and regional differences in the share of water-intensive crops [61, 62].

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Table 4.  Range of end-century annual climate change impacts on California electricity and water systems. Details on all studies referenced for each linkage are in SI table 6.

Linkage	End-century annual % Δ from literature (−decrease/+increase)	Ref.	Calculated end-century annual absolute Δ
Supply-side ${{{{L}}}_1}$, Raw water availability	−25% to +46%	[57, 132, 133]	−13 to +24 Billion m3
Demand-side ${{{{L}}}_2}$, Irrigation water demand	Sacramento Valley: −2% to +31% San Joaquin Valley: 0% to +7% Tulare Lake:+3% to +7%	[60, 61, 102, 135, 136]	+0.2 to +5 Billion m3
Worst-case to best-case change in water balance (−shortage/+surplus)			−18 to +24 Billion m3
Supply-side ${{{{L}}}_3}$, Transmission energy losses	−0.14% to 0%	[69, 137]	−0.4–0 TWh
${{{{L}}}_5}$, Hydropower generation	Low elevation:−27% High elevation:−20% to +14%	[83–85, 138–140]	−7 to −0.2 TWh
Demand-side ${{{\boldsymbol{L}}}_4}$, Air-conditioning demand	+3% to +18%	[74, 141]	+6 to +34 TWh
Worst-case to best-case change in electricity balance (−shortage/+surplus)			−42 to −6 TWh

In California's electricity system, climate change may create an annual imbalance ranging from a shortage of 6 TWh in the best-case up to a shortage of 42 TWh in the worst-case (table 4, figure 2(b)). We find that higher electricity demand for air-conditioning (${{{\boldsymbol{L}}}_4}$) is the largest contributor (3% increase to 18% increase) [75, 145], concurring with prior work [71]. During summer months, peak demand may increase more sharply (4% to 20% increase) than total annual demand [70, 145, 146]. The ranges reflect differences across studies in GCMs, spatial resolution, and inclusion of both extensive and intensive growth [75]. On the supply-side, California's annual average hydropower generation (${{{\boldsymbol{L}}}_5}$) could decrease 27% or increase up to 14% by end-century, within individual high- and low-elevation regions [84–86, 142–144]. Absolute declines are greatest for high-elevation hydropower (which contributes two-thirds of total average hydropower generation) and hot/dry GCM projections, worsening with droughts ¹¹ . Despite disparities in annual estimates, studies agree seasonally—average hydropower generation (and spill) is projected to increase over winter and spring, and decrease up to 55% over summer, which may exacerbate grid reliability planning challenges. Lastly, studies project a nominal 0.1% increase in transmission resistive losses (${{{\boldsymbol{L}}}_3}$) [70, 141].

If climate change leads to water imbalances, our analysis finds that a wide range of energy impacts is possible from adaptations that meet the 18 Bm³ worst-case shortage. Figure 3 shows that the energy balance $(E{B_{s,j}})$ impacts of several adaptation scenarios (including corner cases and portfolios), are on the same order of magnitude or even surpass direct climate impacts on the energy system.

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Among the adaptation corner case scenarios, consistent with prior studies [96, 126, 147–149], we find that strategies that rely strongly on conservation measures, particularly in urban areas, could substantially reduce energy requirements for water sector adaptation. Residential conservation saves the most energy (about 80–110 TWh saved) by avoiding energy-intensive end-uses, conveyance, and treatment. Conversely, if the water shortage is met entirely with desalinated water, the energy impact (20–50 TWh of additional demand) could exceed that of direct climate change induced shortages in the electricity sector, from hydropower generation, transmission losses, and air-conditioning combined.

Diversified portfolios of both demand-side and supply-side adaptations reduce overall energy impacts, while also overcoming some of the physical limits [4, 12, 13], infrastructure costs [92], public opinion [97, 105], and water pricing [97] implementation barriers that make relying on corner cases unrealistic. For example, with a mix of residential and agricultural conservation, groundwater recharge, water recycling, and desalination, we find that Portfolio 1's energy impact (ranging from 18 TWh saved to 8 TWh of additional demand) could completely or near completely offset direct climate impacts on the energy imbalance. Conversely, energy impacts increase with less diversified strategies relying primarily on supply-side measures [108]. Portfolios 2, 3, and 4 nearly double the energy imbalance, like the most energy-intensive corner cases, because of their high shares of desalination and water recycling.

We find that the source of water substituted by an adaptation is nearly as important to the overall energy impact as the energy demand to implement the adaptation itself. All adaptation corner cases except for desalination save energy when substituting energy-intensive SWP water (using the average energy intensity across delivery points), whereas if a local or an 'average' water source is replaced, groundwater banking, recycled water, and desalination would still create energy shortages. The most diverse Portfolio 1 saves energy if replacing SWP deliveries, while the replacement of average and local surface water supplies still adds to the energy shortage.

Previous analyses have characterized either current electricity and water system connections, or future climate change vulnerabilities of individual system components in isolation. This study unites these two threads of literature and presents a generalized framework which can guide resource managers on evaluating climate impacts on the energy-water nexus for long-term planning. While this paper applies the framework to the California context, the overall concept can be broadly used by planners and researchers to conduct a first-order, aggregate assessment of cross-sectoral climate vulnerabilities and the tradeoffs among available adaptation technologies in regions with closely coupled electricity and water systems. The importance of particular linkages will differ by region based on hydroclimatic conditions and infrastructure. For example, generation losses depend on the share of thermoelectric plants that rely on cooling water, and water supply changes depend on region-specific snowpack storage, groundwater dependency, and reservoir operations. Further, the ability to realize co-benefits and minimize unintended energy impacts of water adaptations will also depend on a number of physical, institutional, environmental, and economic constraints[31] that are important criteria for future study and decision-making.

When applying this framework to California, we find that the range of potential climate-driven gaps between supply and demand are much larger for the water system (spanning both shortage and surplus) than the electricity system, reflecting large water supply uncertainties by end-century. To better support water and electricity planning efforts, subsequent research can explore in more detail how projected hydroclimatic variability and change interacts with the operations of constrained water infrastructure[22,24], especially in the nearer term, at more refined geographic and temporal scales, and during extreme events [68, 150]. For example, given available data, our estimates of annual average climate change impacts on energy and water resources in California potentially underestimate the severity of demand-supply imbalances during the summer months when several factors coincide (e.g. irrigation demand increases, raw water decreases, hydropower decreases, and air-conditioning increases).

Overall our findings imply that water sector adaptations could significantly compound the direct effect of climate change on the electricity system, suggesting the need for grid planning to incorporate not only direct impacts (such as future air-conditioning growth and hydropower reductions), but to also coordinate with water resource planners to prioritize energy considerations in decision-making and to anticipate water sector adaptations in electricity demand forecasts. Closer cross-sectoral adaptation planning could enable jointly funded R&D, customer incentives, and programs for water conservation, which would have the greatest mutual water and energy saving benefits and help ensure reliable services in both sectors. Climate change will bring new and uncertain challenges to strongly interdependent electricity and water systems. This analysis demonstrates the substantial benefits of coordinated climate adaptation planning between the electricity and water sectors to increase system resilience worldwide.

This material is based upon work supported by (1) the National Science Foundation under Grant No. DGE-1633740, 'Innovations in Food, Energy, Water Systems' (InFEWS) and (2) by the Office of Science, Office of Biological and Environmental Research, Climate and Environmental Science Division, of the U S Department of Energy under contract No. DE-AC02-05CH11231 as part of the HyperFACETS Project, 'A framework for improving analysis and modeling of Earth system and intersectoral dynamics at regional scales' (award No. DE-SC0016605).

The data that support the findings of this study are available upon reasonable request from the authors.