Editing IPCC:AR6/WGII/Chapter-4 (section)

=== 4.7.5 Costs of Adaptation and Losses due to Non-Adaptation ===

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Estimating adaptation costs for climate change impacts on the various water use sectors is vital for decision-making, budgeting, and resource allocation ( [[#Chambwera--2014|Chambwera et al., 2014]] ). However, in AR5, studies on adaptation costs for water were deemed to have ‘limited coverage’ and mainly focused on ‘isolated case studies’; costs in agriculture were ‘extremely limited’ ( [[#Chambwera--2014|Chambwera et al., 2014]] ).

One estimate on observed losses due to climate change from the UK notes that almost 50% of freshwater thermal capacity is lost on extreme high-temperature days, causing losses in the range of average GBP 29–66 million/year ( [[#Byers--2020|Byers et al., 2020]] ). However, global estimates of current losses because of climate change impacts on water resources remain few. Most of the evidence is focused on projected damages rather than actual ones ( [[#World%20Bank--2016|World Bank, 2016]] ; [[#Rozenberg--2019|Rozenberg and Fay, 2019]] ).

Without adaptation, water-related impacts of climate change are projected to reduce global GDP by 0.49% in 2050 under SSP3, with significant regional variations for the Middle East (14%); Sahel (11.7%); Central Asia (10.7%), and East Asia (7%) ( [[#World%20Bank--2016|World Bank, 2016]] ). In Asia, water-related impacts of climate change on all sectors of the economy are projected to reduce GDP by 0.9% (in high-income Asia) to 2.7% (in low-income Asia) by 2050 without adaptation or mitigation. Under the A1B scenario, real GDP is projected to fall by 0.78% by 2030 in South Asia ( [[#Ahmed--2014|Ahmed and Suphachalasai, 2014]] ). In Sub-Saharan Africa, damages from floods in 2100 are projected at 0.5% of GDP under a 2°C temperature rise without adaptation; and will be non-uniformly spread across countries ( [[#Markandya--2017|Markandya, 2017]] ; [[#Dottori--2018|Dottori et al., 2018]] ). In Europe, annual damages due to coastal flooding are projected at €93 billion by 2100 under RCP8.5-SSP3 ( [[#Ciscar--2018|Ciscar et al., 2018]] ). Global direct damages from fluvial floods are projected to rise to €1250 billion yr –1 under a 3°C global warming level and SSP5 socioeconomic scenario ( [[#Dottori--2018|Dottori et al., 2018]] ). A model-based study of selected water-related sectors like fluvial and coastal flooding, agricultural productivity of major crops, hydroelectric power generation, and thermal power generation provides much conservative estimates of GDP loss ( [[#Takakura--2019|Takakura et al., 2019]] ). The study shows that without adaptation, loss of global GDP could be 0.094% under RCP8.5 and SSP5 and 0.013% under RCP2.6 and SSP1 scenarios in 2090 (2080–2099), with regional values for Africa (0.017 to 0.286%), Asia (0.015 to 0.104%), Australasia (-0.012 to 0.003%), North America (-0.002 to 0.005%) and South and Central America (0.011 to 0.055%) ( [[#Takakura--2019|Takakura et al., 2019]] ). So, while there is general agreement about negative impacts on GDP due to water-related risks in the future, the magnitude of GDP loss estimates varies substantially and depends on various model assumptions ( ''high confidence'' ). Updating costs while improving the modelling of uncertainties is essential for evidence-based decision-making ( [[#Ginbo--2020|Ginbo et al., 2020]] ).

Costs of water-related infrastructure in adaptation have received attention at the global and regional level to bridge the ‘adaptation gap’ ( [[#Hallegatte--2018|Hallegatte et al., 2018]] ; [[#UNEP--2018|UNEP, 2018]] ; [[#Dellink--2019|Dellink et al., 2019]] ; [[#GCA--2019|GCA, 2019]] ). For example, ( [[#Rozenberg--2019|Rozenberg and Fay, 2019]] ) estimated that subsidising capital costs to extend irrigation to its full potential would cost 0.13% of the GDP per year of low-and middle-income countries between 2015 and 2030. The coastal and riverine protection cost was between 0.06% and 1% of these countries’ GDP per year over the same period. Projected economic damage due to coastal inundation was USD 169–482 billion in 2100 under RCP8.5-SSP3 without adaptation, but USD 43–203 billion cost to raise dike height will reduce 40% of the total damage ( [[#Tamura--2019|Tamura et al., 2019]] ). Hard infrastructure for river floods, costing $4–9 billion yr –1 , can reduce damage by USD 22–74 billion yr –1 ( [[#Tanoue--2021|Tanoue et al., 2021]] ). Damages are estimated to be up to six-time larger than the cost of implementing efficient adaptation measures (H2020., 2014). ( [[#GCA--2019|GCA, 2019]] ) reported that investing USD 1.8 trillion globally, for example, in early warning systems, climate-resilient infrastructure; dryland crop production; mangrove protection; and improving the resilience of water resources between 2020 and 2030 could generate USD 7.1 trillion in benefits.

Comparatively, less attention has been paid to low-regret options, especially at the national and local levels. Conservation agriculture and integrated production systems, early-warning systems, restoration of wetlands, and zoning are postulated to have lower investment and lock-in costs than engineering-based options ( [[#Mechler--2016|Mechler, 2016]] ; [[#Cronin--2018|Cronin et al., 2018]] ; [[#Johnson--2020|Johnson et al., 2020]] ). However, they require regular maintenance and high technical and human capacity, which are likely to vary by scale, location, and context ( [[#Chandra--2018|Chandra et al., 2018]] ; [[#Khanal--2019|Khanal et al., 2019]] ; [[#Mutenje--2019|Mutenje et al., 2019]] ; [[#Rahman--2019|Rahman and Hickey, 2019]] ). Global studies suggest improvements in returns on adaptation investments by delivering better services and reducing water wastage through appropriate water pricing and regulations ( [[#Damania--2017|Damania et al., 2017]] ; [[#Bhave--2018|Bhave et al., 2018]] ). For example, under scenarios SSP1 and SSP3, water pricing and regulation are projected to reverse losses in expected 2050 global GDP of 0.49% to gains of 0.09%. GDP losses are projected to drastically reduce in the Middle East, eliminated in the Sahel and Central Africa, and reversed into gains in Central Asia and East Africa, with benefits concentrated in worst-affected regions ( [[#World%20Bank--2016|World Bank, 2016]] ). More local and national studies are needed to identify low regret options and their benefits and actual costs ( [[#Blackburn--2018|Blackburn and Pelling, 2018]] ; [[#Abedin--2019|Abedin et al., 2019]] ; [[#Brown--2019|Brown et al., 2019]] ; [[#Momblanch--2019|Momblanch et al., 2019]] ; [[#Page--2020|Page and Dilling, 2020]] ) ( ''limited evidence, high agreement'' ).

In summary, climate change impacts on water resources are projected to lower GDP in many low-and middle-income countries without adequate adaptation measures ( ''high confidence'' ). However, estimating the exact quantum of future GDP loss due to water-related impacts of climate change is fraught with several methodological challenges. Adaptation measures that focus on reducing water-related impacts of climate change will help stem losses further. Still, more work needs to be done on actual benefits and costs of adaptation strategies and residual impacts and risks of delaying adaptation action ( ''medium confidence'' ). In addition, better evidence on the costs and benefits of low-regret solutions, such as water pricing, increasing water use efficiency through technology and service improvements, and enhanced support for autonomous adaptation, is also needed for informed decision-making ( ''high confidence'' ).

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'''Box 4.8 | Water-Energy-Food (WEF) Nexus Approaches for Managing Synergies and Trade-Offs'''
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The WEF nexus is an approach that recognises that water, energy and food are linked in a complex web of relationships in the hydrological, biological, social, and technological realms ( [[#D’Odorico--2018|D’Odorico et al., 2018]] ; [[#Liu--2018b|Liu et al., 2018b]] ; [[#Märker--2018|Märker et al., 2018]] ). For instance, agricultural production requires significant energy inputs due to intensive groundwater pumping ( [[#Siddiqi--2013|Siddiqi and Wescoat, 2013]] ; [[#Gurdak--2018|Gurdak, 2018]] ; [[#Putra--2020|Putra et al., 2020]] ). Similarly, hydropower production often has trade-offs with irrigation, affecting food production, carbon emission and forest protection ( [[#Meng--2020|Meng et al., 2020]] ). New technologies, such as desalination plants for urban water supply against future climate change and drought, are also very energy-intensive ( [[#Caldera--2018|Caldera et al., 2018]] ) (Box 4.5). Quantifying the complex interdependencies among food, energy and water is critical to achieving the SDGs and reducing trade-offs ( [[#Liu--2018a|Liu et al., 2018a]] ; [[#Liu--2018b|Liu et al., 2018b]] ; [[#UN--2019|UN, 2019]] ). A key benefit of the nexus approach is to leverage the interconnection of WEF and achieve the most efficiency in the overall systems. Hence, this approach allows for widening the set of salient stakeholders and, therefore, solution possibilities that may otherwise not be possible in single-domain efforts and helps connect these stakeholders to achieve synergistic goals ( [[#Ernst--2017|Ernst and Preston, 2017]] ; [[#Mercure--2019|Mercure et al., 2019]] ).

The WEF nexus approach thus opens up possibilities for strategic interventions across sectors through a better understanding of trade-offs ( [[#Albrecht--2018|Albrecht et al., 2018]] ). Policies and strategies aiming to cope with climate change may amplify rather than reduce negative externalities and trade-offs within the nexus: low carbon transition, the shift to non-conventional water resources, and agricultural intensification, all implemented to mitigate and adapt to climate change, are not always nexus-smart. Hence, a nexus approach that integrates management and governance across these three sectors can enhance WEF security by minimising trade-offs and maximising synergies between sectors. At the same time, renewable energy offers the opportunity to decouple water and food production from fossil fuel supply, leading to several advantages from both a socioeconomic and environmental point of view ( [[#Cipollina--2015|Cipollina et al., 2015]] ; [[#Pistocchi--2020|Pistocchi et al., 2020]] ). WEF nexus approaches can achieve overall system efficiency when maximising the use and recovery of water, energy, nutrients and materials ( [[#Pistocchi--2020|Pistocchi et al., 2020]] ; [[#Tian--2021|Tian et al., 2021]] ). These types of holistic system thinking of WEF show promising strategies to catalyse transformative changes. Suppose that the specific types and extent of WEF linkages in a region are well understood. In that case, it becomes possible to intervene through one element to cause an effect on another connected component that may have proven difficult for direct intervention ( [[#Mukherji--2020|Mukherji, 2020]] ).

Several challenges remain for sound operationalisation of the nexus, notably insufficient data, information and knowledge in understanding the WEF inter-linkages and lack of systematic tools to address trade-offs involved in the nexus and to generate future projections ( [[#Liu--2017a|Liu et al., 2017a]] ; [[#Liu--2018b|Liu et al., 2018b]] ). There are recent signs of progress in developing models and tools for addressing the nexus trade-offs, for example, the bioenergy–water nexus ( [[#Ai--2020|Ai et al., 2020]] ). There is a need to move beyond viewing the WEF nexus as a way of problem identification to seek integrated solutions to interconnected problems.

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