Humans drive future water scarcity changes across all Shared Socioeconomic Pathways

This analysis makes deterministic classifications of how, when water resources are limited and constrained, the human and climate systems interact. The relative effects of both systems on water scarcity are quantified at global and basin scales across 15 global futures that include five different socioeconomic conditions (the Shared Socioeconomic Pathways, SSPs) and four different climatic conditions (the Representative Concentration Pathways, RCPs). These 15 scenarios are used to first analyze a 'Human Alone' component by isolating the human impact on future scarcity. This is accomplished by holding all climate variables to their 2005 levels while altering socioeconomic growth and technological change. General circulation model (GCM) derived climate impacts for five models (supplementary material) are applied (section 2.4) to establish 75 'Human and Climate' scenarios which allows for the quantification of climate impacts (figure 1). Climatic impacts to water supply, agricultural productivity and change, hydropower availability, and building energy demands are applied from 5 different bias-corrected GCMs to make a suite of 75 climate runs. By subtracting the human derived impacts from the 'Human Alone' scenarios, from the 'Human and Climate' scenarios the climate impact is isolated (equation (2c)). First, the drivers of future water scarcity are evaluated by isolating the impacts that both humans and climate have while accounting for feedbacks between humans, energy, and land. Secondly, the simultaneous impacts that human and climate systems have on water scarcity are analyzed by determining whether each system is increasing or decreasing scarcity in all global water basins. Below we describe the GCAM model, the scenario components, climate derived impacts, and the calculations of scarcity changes and attribution.

Zoom In Zoom Out Reset image size

This study uses the global change assessment model (GCAM), with inclusions of water constraints to both renewable and nonrenewable sources of water, to investigate the relative contributions of climate and human systems on water scarcity regionally and globally under a wide range of scenarios. GCAM links socioeconomics, the energy system, land-use change, climate, and the water sector. GCAM is a market-equilibrium model that allows for prices to be adjusted within each time step to ensure that the supply and demand of goods and services remains equilibrated at each time step allowing for simultaneous market clearing across sectors. This study accounts for a limited supply of water by employing cost resource curves across all 235 basins that follow a logit formulation to determine the share of each water source (renewable surface water, nonrenewable groundwater, and desalinated water) needed to meet the water demands within all basins (Kim et al 2016, Turner et al 2019, supplementary material). As depletion of various water sources increases the extraction price increases, which leads to compounding price increases on the goods and services that require higher-priced water sources.

This study employs the use of temporally varying socioeconomics and climate systems. These systems are represented by the Shared Socioeconomic Pathways (SSP), for socioeconomic change, in combination with the Representative Concentration Pathways (RCPs), for climatic change. The SSPs are a set of five future scenarios with varying changes to global population, the economy (Riahi et al 2017), and land use (Popp et al 2017), which were designed to explore varying degrees of challenges to climate change adaptation and mitigation (O'Neill et al 2017). These scenarios have been defined, both qualitatively and quantitatively, using a set of global integrated human-Earth systems models, in which individual models have been used to produce a marker scenario (Riahi et al 2017) for singular SSPs (Calvin et al 2017, Fricko et al 2017, Fujimori et al 2017, Kriegler et al 2017, Van Vuuren et al 2017) and provide uncertainty ranges across all other SSPs. These results provide alternative projections of the evolution of the economy, energy systems, land systems, emissions, and climate. Within GCAM, quantitative assumptions of the SSPs have been made for the economy, energy sector, land use, agricultural sector (Calvin et al 2017), and for the water sector (Graham et al 2018). The RCPs are a set of four future greenhouse gas (GHG) emission pathways in which end-of-century radiative forcing approaches four-levels by altering future greenhouse gas emissions and by changing underlying socioeconomic projections (van Vuuren et al 2011).

The SSPs and RCPs are combined to form a set of future global change scenarios which allows comprehensive socioeconomic assumptions to be matched with future radiative forcing pathways to achieve future global warming targets; creating the next set of scenarios that will provide the basis for future Intergovernmental Panel on Climate Change (IPCC) assessments (Eyring et al 2016, O'Neill et al 2016). Each is then matched with their individual Shared Policy Assumptions (SPAs) in order to account for differences in adaptation and mitigation strategies across the SSPs (Kriegler et al 2014, Calvin et al 2017). These combinations create a set of 15 potential global futures which are varied six times, for five GCMs and one set in which climate impacts across all sectors are neglected to produce 90 total scenarios.

This study accounts for four different climatic impacts: water supply, agricultural productivity, hydropower capacity changes, and building energy demands derived from five general circulation models (GCMs). We calculate the impact on each aspect at four different radiative forcing levels and apply these to the appropriate scenarios within the SSP-RCP scenario matrix. Future water supply is calculated by using bias-corrected precipitation and temperature data derived for four RCPs from five CMIP5 generation GCMs as part of the Inter-Sectoral Impact Model Intercomparison Project [ISI-MIP; Warszawski et al 2014]. These values are entered into the global hydrologic model Xanthos (Li et al 2017, Liu et al 2018, Vernon et al 2019, supplementary material), which calculates accessible water, i.e. available surface runoff and groundwater recharge, at the GCAM 235-basin scale at five-year time steps. Climate derived impacts to crop yield changes (Rosenzweig et al 2014), hydropower capacity changes (Turner et al 2017), and building energy demands (Clarke et al 2018) are calculated from the same set of ISI-MIP models and the climate varying impacts are added to their respective RCP scenarios. By including scenarios that both include and exclude climate impacts we can account for the compounding effects of changing hydrologic conditions, hydropower availability, crop yields, and energy demands on water scarcity, while also separating the impact of human activities from that of the climate system, which include changing water demands for agriculture, power generation, industry, and public supply.

Water scarcity analyses can contain several different aspects of water use. For the purpose of this study, we will consider the water scarcity index (WSI), noted below as S, by comparing the amount of total water withdrawals, W_d from all sources (renewable surface runoff, nonrenewable groundwater extraction, and desalination) to the total GCM derived accessible surface runoff, Q, shown in equation (1), the scarcity is calculated in time period t, basin b, and SSP-RCP-GCM scenario s

$$\begin{eqnarray}&&{S}\left({t},{b},{s}\right)=\displaystyle \frac{{{W}}_{{d}}}{{Q}}.\end{eqnarray} \tag{ 1 }$$

The impacts from human and climate systems must be isolated in order to quantify the relative impact of each system on water scarcity changes. To calculate the impact from the human system, the change in scarcity from the baseline year of 2005 (supplementary figure S1 is available online at stacks.iop.org/ERL/15/014007/mmedia), is calculated for the 'Human Alone' scenario, S_H, equation (2a). The impact from the climate system must then be isolated from the 'Human and Climate' scenarios by subtracting the scarcity found in the 'Human Alone' from the scarcity found in the 'Human and Climate' scenarios, equation (2b), in equation (2c). The 'Human and Climate' scenarios likely contain changes to the human system, such as human responses to changing climate, that are not captured by subtracting the 'Human Alone', however these changes are assumed to be a result of the climate impacts and therefore are classified as such in this study

$$\begin{eqnarray}&&{\rm{\Delta }}{{S}}_{{H}}({t})={{S}}_{{{H}}_{{t}}}-{{S}}_{{{H}}_{2005}},\end{eqnarray} \tag{ 2a }$$

$$\begin{eqnarray}&&{\rm{\Delta }}{{S}}_{{X}}({t})={{S}}_{{{X}}_{{t}}}-{{S}}_{{{X}}_{2005}},\end{eqnarray} \tag{ 2b }$$

$$\begin{eqnarray}&&{\rm{\Delta }}{{S}}_{{C}}\left({t}\right)={{S}}_{{X}}\left({t}\right)-{{S}}_{{H}}({t}).\end{eqnarray} \tag{ 2c }$$

In order to calculate the impact that humans and climate have on water scarcity equations S1 and S2 from Veldkamp et al (2015) are modified and shown as equations (3a) and (3b) below

$$\begin{eqnarray}&&{{I}}_{{H}}({t})=\displaystyle \frac{{\rm{\Delta }}{{S}}_{{H}}({t})}{\left|{\rm{\Delta }}{{S}}_{{C}}({t})\right|+\left|{\rm{\Delta }}{{S}}_{{H}}({t})\right|},\end{eqnarray} \tag{ 3a }$$

$$\begin{eqnarray}&&{{I}}_{{C}}({t})=\displaystyle \frac{{\rm{\Delta }}{{S}}_{{C}}({t})}{\left|{\rm{\Delta }}{{S}}_{{C}}({t})\right|+\left|{\rm{\Delta }}{{S}}_{{H}}({t})\right|}\end{eqnarray} \tag{ 3b }$$

I_H, (human impact) and I_C, (climate impact) represent the relative impact on water scarcity due to human or climate influences brought upon by the change in water scarcity from 2005 values (supplementary figures S2–5). In order to find the main driver of water scarcity we compare the two impacts as in equations (4b) and (4c)

$$\begin{eqnarray}&&\left|{{I}}_{{H}}\right|+\left|{{I}}_{{C}}\right|=1,\end{eqnarray} \tag{ 4a }$$

$$\begin{eqnarray}&&{\rm{Human}}\,{\rm{Driven}}:\left|{I}_{C}\right|\lt \left|{I}_{H}\right|,\end{eqnarray} \tag{ 4b }$$

$$\begin{eqnarray}&&{\rm{Climate}}\,{\rm{Driven}}:\left|{I}_{C}\right|\gt \left|{I}_{H}\right|.\end{eqnarray} \tag{ 4c }$$

The sign of human and climate impacts allows for the classification of increasing or decreasing scarcity.

The water supply and demand calculations, including the implications of climate impacts, are performed for each SSP-RCP scenario to quantify how water scarcity changes. Each of these scenarios will have differences in their human and climate impacts as each SSP-RCP combination will address the climate future differently. In GCAM, the energy, water, and land system for each SSP scenario will evolve differently dependent upon the socioeconomic development and technical change (Calvin et al 2017). Absent any efforts to limit radiative forcing, each SSP will reach a different end of century radiative forcing. Additionally, each SSP-RCP combination will have different means of approaching the same RCP (e.g. a different combination of economic, energy, land, and, water system changes), all of which are included here as human impacts. The introduction of climate impacts (i.e. water supply changes, agricultural productivity changes, hydropower availability, and building energy demands) further alters the evolution of the energy, water, land system for SSP-RCP scenario. Thus, each of the 90 scenarios are inherently different and can respond to climate change differently.

Across all scenarios it is found that a majority of the basins that have negligible changes in water scarcity are located in the Northern Hemisphere high latitudes, Amazonian Rainforest, and parts of Australia, regardless of time period or scenario (figure 2(b), supplementary figures S7–8). In the areas which have a defined change in water scarcity, 80% of the land area experience water scarcity changes dominated by humans by 2100 (red shading and supplementary figure S2). This is true for SSP1, SSP2, and SSP4. Whereas in SSP3, extremely high population growth results in 92% of land area which has water scarcity changes driven by humans, and SSP5, where only 71% is driven by humans due to the contributions from reaching RCP8.5 conditions (supplementary figures S9–10).

Zoom In Zoom Out Reset image size

Throughout the century, the area experiencing human driven water scarcity changes typically increases up to the year 2100. Human-dominated, water scarcity increases (H+) occur in 60% of the globe while 22% experiences decreasing scarcity due to humans (H−). Significant differences arise across SSPs as socioeconomic differences drive efficiency improvements, demand changes, and altered water dependency (Calvin et al 2017, Graham et al 2018). SSP1 experiences a shift from H+ to H− in a large amount of land throughout the century, leading to just 36% of the globe classified as H+ in 2100, while humans act to decrease water scarcity in 44%. While not as extreme, similar shifts from H+ and H− occur in SSP4 and SSP5, whereas in SSP2 and SSP3 more than 75% of the globe is H+. Although differences exist across each SSP scenario, the three scenarios that shift from H+ to H− experience global or regional GDP growth that allows for the adoption of efficient water use technologies. Additional storyline features such as sustainability focus, fuel preference, and universal adoption rates also influence cross-SSP differences.

Figure 2(b) shows a spatial representation of water scarcity drivers across the average of all future scenarios. Although socioeconomic scenario assumptions diverge in the second half of the century, the main driver remains humans in most basins. The robustness of the results decreases, and uncertainty increases by 2100 (supplementary figure S9), consistent with figure 2(a). Basins in sub-Saharan Africa have significant agreement across scenarios of human driven scarcity changes in both 2050 and 2100 riven by population growth increases throughout the century.

Although the previous section focused on the dominant driver of water scarcity, the impacts brought upon by the secondary driver must be accounted for. These impacts provide either compounding, where both systems change scarcity by the same sign, or counteracting, where human and climate systems have opposing signs, effects on water scarcity enhancement. To account for this, figure 3 introduces four distinct water scarcity change categories to define how human (H) and climate (C) systems individually, yet simultaneously, increase (+) or decrease (−) water scarcity within a basin.

Zoom In Zoom Out Reset image size

Expanding on the notion of differing signs of change and considering the simultaneous impacts of human and climate systems on future water scarcity figure 3(a) shows the combination across all scenarios. When considering all scenarios (figure 3(a), left), 45% of nonnegligible land shows a compounding effect (green and red) by the end of the century, whereas 55% of the globe has counteracting effects (orange and blue). An increasing dependence on socioeconomic future arises throughout the century as SSP1 produces compounding effects in 52% of the globe. This comes about due to a significant increase in H–C– basins and a shift away from H+ C– conditions in parts of Africa and Eurasia (areas of decreasing robustness in figure 3(b), and supplementary figure S11). SSP2 on the other hand has only 39% of the globe with compounding impacts driven by 59% of global basins falling into the H+C– category (supplementary figure S12).

Figure 3(b) represents how water scarcity changes are dependent upon geographic location, as distinct areas of H− and H+ arise while much of the world experiences climate induced scarcity decreases (C–, green and orange). Areas of the Mediterranean and West Asia are shown to have water scarcity increases due to climate by 2050 (figure 3(b), supplementary figures S2–5), in line with previous studies (Haddeland et al 2014, Schewe et al 2014), however these results diverge by 2100. Meanwhile, much of the midwestern United States is shown to have human driven scarcity decreases in 2050 and 2100, unlike what has been shown in some previous studies (Haddeland et al 2014, Schlosser et al 2014). Prescribed SSP-specific improvements in water use technologies (Graham et al 2018), are likely to cause human-driven water scarcity decreases, particularly in regions where population is not expected to change dramatically in the future (Samir and Lutz 2017) while GDP growth is expected to allow for water use improvements across many SSPs (Calvin et al 2017). Nearly all of Africa experiences counteracting water scarcity effects as population driven increases in demand lead to increases in scarcity, while climate-driven increases in precipitation increase water supply and thus lower scarcity (supplementary figure S11). As in figure 2(b), the robustness of the classification is again shown to decrease by the end of the century (right). This is due to differences in efficiency and the sustainability focus of the socioeconomic scenarios driving the evolution of water scarcity categories, particularly in central Eurasia and Africa where population change projections and GDP vary by SSP (Calvin et al 2017, Graham et al 2018). Areas of negligible changes remain the same as in figure 2(b), by definition.

Results thus far have focused on differences across SSPs while aggregating all climate futures, but it is important to distinguish between impacts at multiple radiative forcing levels. The end of century distribution of human and climate impacts in a basin by scenario are displayed in figure 4(b) where the size of each point represents the WSI of its basin in 2100. Applying equations (3a) and (3b), the human and climate impacts will fall on the drawn diamond. However, as each SSP-RCP scenario is made up of five different GCM runs, the robustness of the relative contributions towards water scarcity changes of both human and climate for each basin can be captured. As points move towards the center of the diamond, impacts in individual basins become increasingly uncertain across GCMs.

Zoom In Zoom Out Reset image size

The distribution of human impacts is shown in figure 4(a) with clear bimodal patterns across all SSPs. The peaks of all distributions fall where (−0.5 > I_H > 0.5), where I_H is the human impact, justifying the notion that humans are having a larger impact than climate on water scarcity in most basins globally independent of socioeconomic scenario. However, the distribution of these impacts varies greatly by SSP (supplementary figure S10). Specifically, SSP1 is largely negatively favored (decreasing scarcity), whereas SSP2 and SSP3 lean significantly more positive. The spreads for SSP4 and SSP5 are much closer to a uniform bimodal distribution with close to equal numbers of basins with positive and negative human impacts.

The distribution of climate impacts is shown in figure 4(c) across each of the RCP radiative forcing levels. Independent of radiative forcing future, the relative impact of climate is slightly negative, shown as the peak frequency is below the zero line in each distribution. The magnitude of this impact provides additional evidence for the relatively low impact of climate compared to humans across all SSP-RCP scenarios. The spread of climate impacts decreases as the end of century radiative forcing target decreases, leading to the conclusion that at lower radiative forcing futures, climate systems are likely to have smaller impacts on scarcity than humans in an increasing number of basins. The opposite result occurs in the RCP8.5 scenario as the distribution is more uniform across climate impacts, which emphasizes the important notion that at higher radiative forcings, water scarcity will likely be more susceptible to climate impacts. As RCP8.5 is currently only attainable under the SSP5 scenario, additional research is needed to understand how different socioeconomic conditions alter future water scarcity at high radiative forcing levels.