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

=== 4.6.9 Adaptation of the Cultural Water Uses of Indigenous Peoples, Local Communities and Traditional Peoples ===

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AR5 reported that religious and sacred values inform actions taken to adapt to climate change ( [[#Noble--2014|Noble et al., 2014]] ). Neither AR5 nor SR1.5 reviewed adaptation of indigenous, local and traditional uses of water. SROCC highlighted the context-specific adaptation strategies of vulnerable communities in coastal, polar and high-mountain areas, reporting that adaptive capacity and adaptation limits are not only physical, technical, institutional and financial, but also culturally informed ( [[#Hock--2019b|Hock et al., 2019b]] ; [[#Meredith--2019|Meredith et al., 2019]] ; [[#Oppenheimer--2019|Oppenheimer et al., 2019]] ).

There is ''high confidence'' that some Indigenous Peoples, local communities and traditional peoples could adapt, and are adapting to climate-driven hydrological changes and their impacts on culturally significant sites, species, ecosystems and practices in polar, high-mountain and coastal areas, where sufficient funding, decision-making power and resourcing exist (e.g., [[#Golden--2015|Golden et al., 2015]] ; [[#Bunce--2016|Bunce et al., 2016]] ; [[#Anderson--2018|Anderson et al., 2018]] ). However, there is also ''high confidence'' that there are significant structural barriers and limits to their adaptation, and that the outcomes of some adaptation strategies can be uneven and maladaptive ( ''medium evidence, high agreement'' ) (Sections 4.7.4; 4.8.3). These barriers include the lack of recognition of Indigenous Peoples’ sovereignty and exclusion of Indigenous Peoples from decision-making institutions ( [[#Ford--2017|Ford et al., 2017]] ; [[#Labbé--2017|Labbé et al., 2017]] ; [[#Eira--2018|Eira et al., 2018]] ; [[#McLeod--2018|McLeod et al., 2018]] ; [[#MacDonald--2020|MacDonald and Birchall, 2020]] ) (14.4.4.2.2; 13.8.1.2). At the same time, the rate and scale of climate change can impede the ability of vulnerable communities to turn their adaptive capacity into effective adaptation responses ( [[#Ford--2015|Ford et al., 2015]] ; [[#Herman-Mercer--2019|Herman-Mercer et al., 2019]] ).

There is ''high confidence'' that local people are adapting to the cultural impacts of climate-driven glacier retreat and decline in snow cover and ice in polar and high-mountain areas. However, there is also ''high confidence'' that such adaptation can be detrimental and disrupt local cultures. For example, in the Peruvian Andes, concerns about water availability for ritual purposes has led to restrictions on pilgrims’ removal of ice and limiting the size of ritual candles to preserve the glacier ( [[#Paerregaard--2013|Paerregaard, 2013]] ; [[#Allison--2015|Allison, 2015]] ). Relatedly, some local people have questioned the cosmological order and have reoriented their spiritual relationships accordingly ( [[#Paerregaard--2013|Paerregaard, 2013]] ; [[#Carey--2017|Carey et al., 2017]] ). In Siberia ( [[#Mustonen--2015|Mustonen, 2015]] ) and northern Finland ( [[#Turunen--2016|Turunen et al., 2016]] ), community-led decisions among herders favour alternative routing, pasture areas and shifts in nomadic cycles in response to changing flood events and permafrost conditions (Box 13.2). However, loss of grazing land and pasture fragmentation pose adaptation limits, and some strategies such as supplementary feeding and new technologies may further affect cultural traditions of herding communities ( [[#Risvoll--2016|Risvoll and Hovelsrud, 2016]] ; [[#Jaakkola--2018|Jaakkola et al., 2018]] ).

There is ''high confidence'' that relocation (managed retreat) is an adaptation response for communities in areas impacted by, or at risk of, inundation and other hydrological changes (15.3.4.7; 15.5.3). However, relocation can be culturally, socially, financially, politically and geographically constrained due to the importance of cultural relationships with traditional, customary or ancestral lands ( ''high confidence'' ) ( [[#Albert--2018|Albert et al., 2018]] ; [[#Narayan--2020|Narayan et al., 2020]] ; [[#Yates--2021|Yates et al., 2021]] ). Among Pacific islands, for example, the prospect of migration raises concerns about the loss of cultural identity and IK and practices, which can impact emotional well-being ( [[#Yates--2021|Yates et al., 2021]] ).

As cultural beliefs influence risk perception, there is ''medium confidence'' that some cultural understandings can foster a false sense of security among Indigenous Peoples, local communities and traditional peoples regarding climate-driven hydrological changes. For example, some members of the Rolwaling Sherpa community in Nepal believe that mountain deities protect them from GLOFs ( [[#Sherry--2017|Sherry and Curtis, 2017]] )( [[#4.2.2|Section 4.2.2]] ). Elsewhere, such as in the islands of Fiji and St. Vincent, cultural beliefs can diminish human agency because change is viewed as inevitable and beyond human intervention ( [[#Smith--2016|Smith and Rhiney, 2016]] ; [[#Currenti--2019|Currenti et al., 2019]] ). Yet such cultural beliefs are not necessarily maladaptive, as they potentially support other resilience factors, such as IKLK ( [[#4.8.5|Section 4.8.5]] ; [[#Ford--2020|Ford et al., 2020]] ), as well as cultural connections and social ties ( [[#Yates--2021|Yates et al., 2021]] ).

In sum, although some Indigenous Peoples, local communities and traditional peoples can adapt, and are adapting to climate-driven hydrological changes, and their impacts on and risks to culturally significant practices and beliefs ( ''medium confidence'' ), these strategies are constrained by structural barriers and adaptation limits ( ''high confidence'' ).

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'''Box 4.7 | Flood-Related Adaptation Responses'''
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Floods, due to their rapid onset and destructive force, require specific adaptation measures. Historically, to address flood damages and risk protection, retreat and accommodation were most common, emphasizing protecting and retreating ( [[#Wong--2014|Wong et al., 2014]] ; [[#Bott--2019|Bott and Braun, 2019]] ). Figure 4.22 identifies five major adaptation strategies from a meta-review of water-related adaptation responses that helps in protecting, retreating and accommodating ( [[#4.7.1|Section 4.7.1]] ).

Globally, structural measures for flood protection through hard infrastructure are the most common measures as they directly manage flood hazards by controlling flow through streams and prevent water overflow ( [[#Andrew--2017|Andrew and Sauquet, 2017]] ; [[#Duží--2017|Duží et al., 2017]] ). These measures include dikes, flood control gates, weirs, dams, storage and proper waste management ( [[#Barua--2017|Barua et al., 2017]] ; [[#Egbinola--2017|Egbinola et al., 2017]] ). Infrastructure measures require high maintenance, such as dredging and clearing channels and overpasses ( [[#Egbinola--2017|Egbinola et al., 2017]] ). A negative aspect of protective infrastructural measures is that, while they eliminate the hazard up to a certain magnitude ( [[#Di%20Baldassarre--2013|Di Baldassarre et al., 2013]] ), they also generate an illusion of no risk by diminishing frequent floods ( [[#Duží--2017|Duží et al., 2017]] ; [[#Logan--2018|Logan et al., 2018]] ). In addition, specific engineering solutions that might be introduced from other localities without proper contextual adjustments may lead to maladaptation ( [[#Mycoo--2014|Mycoo, 2014]] ; [[#Pritchard--2014|Pritchard and Thielemans, 2014]] ). NbS (Box 4.6) have shifted infrastructure measures from purely grey onto mixed engineering and environmental measures. Examples include SUDS, which aid in decreasing flow peaks and are affordable, aesthetically pleasing and socially acceptable while also reducing heat and hence the production of storms ( [[#Chan--2019|Chan et al., 2019]] ) ( [[#4.6.5|Section 4.6.5]] ).

Non-structural or soft measures for flood adaptation include human actions that generate capacities, information and, therefore, awareness of floods ( [[#Du--2020|Du et al., 2020]] ). Soft measures aim to integrate flood resilience within city management and planning ( [[#Wijaya--2015|Wijaya, 2015]] ; [[#Andrew--2017|Andrew and Sauquet, 2017]] ; [[#Abbas--2018|Abbas et al., 2018]] ). Social support between members of a community and economic mechanisms such as loans or remittances are soft measures that promote recovery or resilience to floods ( [[#Barua--2017|Barua et al., 2017]] ; [[#Musah-Surugu--2018|Musah-Surugu et al., 2018]] ; [[#Bott--2019|Bott and Braun, 2019]] ). Communities with heightened awareness and knowledge of floods are probably going to elect political leaders that will affect flood protection and policies that include adaptation ( [[#Abbas--2018|Abbas et al., 2018]] ). Soft measures can be an anchoring factor for policies that promote early warning systems, infrastructure, flood-resilient housing and environmental restoration ( [[#Andrew--2017|Andrew and Sauquet, 2017]] ; [[#Abbas--2018|Abbas et al., 2018]] ). However, soft measures, especially at large scale, may also lead to maladaptation, such as lack of synchronisation between international, national and local levels ( [[#Hedelin--2016|Hedelin, 2016]] ; [[#Lu--2016|Lu, 2016]] ; [[#Jamero--2017|Jamero et al., 2017]] ), and can further be hampered by bureaucracy ( [[#Pinto--2018|Pinto et al., 2018]] ).

Early warning systems (EWS) are defined as integrated systems of hazard monitoring, forecasting and prediction, disaster risk assessment, communication and preparedness activities systems to enable individuals, communities, governments and businesses to take timely action to reduce disaster risks in advance of hazardous events ( [[#UNISDR--2021|UNISDR, 2021]] ). By this definition, EWS are directly dependent on soft and hard infrastructure measures that increase capacity and reduce hazard ( [[#Abbas--2018|Abbas et al., 2018]] ). Aside from the capacity dependent on soft measures and the monitoring infrastructure, communication at all scales, from national weather services to local leaders, needs to be effective for prompt action ( [[#Devkota--2014|Devkota et al., 2014]] ). In many cases, EWS might be the only option to reduce flood casualties ( [[#Kontar--2015|Kontar et al., 2015]] ).

Accommodating floods has gained popularity as the effects of climate change become more apparent and as notable hydroclimatic events exceed the limitations of protective measures ( [[#Pritchard--2014|Pritchard and Thielemans, 2014]] ). NbS measures like wetland restoration can act as modern infrastructure protection with clear mitigation co-benefit and provide opportunities for accommodating floods. For example, initiatives such as ‘Room for the River’ consider flood safety combined with other values such as landscape, environment and cultural values ( [[#Zevenbergen--2015|Zevenbergen et al., 2015]] ). A popular EbA measure has been wetland restoration, which can control flood peaks, serve as storage ponds in addition to restoring the environment ( [[#Pinto--2018|Pinto et al., 2018]] ; [[#Saroar--2018|Saroar, 2018]] ). However, its effectiveness under different conditions is yet to be assessed ( [[#Wamsler--2016|Wamsler et al., 2016]] ). Flood resilient housing is another form of accommodating and living with floods. These comprise mostly of elevated homes or different flood protection measures considering vegetation around the house to make those flood resilient ( [[#Ling--2015|Ling et al., 2015]] ; [[#Abbas--2018|Abbas et al., 2018]] ; [[#Ferdous--2019|Ferdous et al., 2019]] ).

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Box 4.7

Despite different degrees of effectiveness, no flood adaptation measure is uniquely effective to eliminate flood risk. Adaptation to floods needs to be considered at a local level, considering the types of floods, community’s capacities and available livelihoods ( [[#Fenton--2017a|Fenton et al., 2017a]] ). Ideally, flood adaptation strategies need to include short-term actions linked to long-term goals, be flexible, consider multiple strategies and interlink investment agendas of stakeholders ( [[#Zevenbergen--2015|Zevenbergen et al., 2015]] ). Most importantly, flood adaptation and management options have been proven effective to reduce loss of human lives, but not entirely at sustaining livelihoods and reducing infrastructure damages ( [[#Rahman--2016|Rahman and Alam, 2016]] ; [[#Bower--2019|Bower et al., 2019]] ; [[#Ferdous--2019|Ferdous et al., 2019]] ).

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