Editing IPCC:AR6/WGII/Chapter-12 (section)

==== 12.5.3.4 Successful Adaptation and Limitations ====

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Although a growing body of adaptation initiatives exists for CSA, evidence on their effectiveness is scarce. In many parts of CSA the level of success of adaptation measures depends largely on the governance of projects and stakeholder-based processes and is closely related to their effectiveness, efficiency, social equity and sociopolitical legitimacy ( ''high confidence'' ) ( [[#Adger--2005|Adger et al., 2005]] ; [[#Rasmussen--2016b|Rasmussen, 2016b]] ; [[#Moulton--2021|Moulton et al., 2021]] ). Several PES experiences across CSA have been described as successful measures for watershed conservation and adaptation ( ''high confidence'' ). An example of success is the Quito water fund in Ecuador, which aims to improve the city’s water quality by integrating public and private stakeholder interests with ecosystem conservation and local community development since the 2000s ( [[#Bremer--2016|Bremer et al., 2016]] ; [[#Grima--2016|Grima et al., 2016]] ) (Case Study 12.6.1). At the same time, in Moyobamba in Peru, the development of a watershed protection programme was leveraged by a multi-stakeholder platform process that enabled deep social learning ( [[#Lindsay--2018|Lindsay, 2018]] ). In turn, initiatives that do not consider the entire set of social-ecological dimensions and dynamics of adaptation or unintentionally increase vulnerabilities of human or natural systems are at risk of leading to reduced outcomes ( [[#McDowell--2021|McDowell et al., 2021]] ) or maladaptation ( [[#Reid--2018|Reid et al., 2018]] ; [[#McDowell--2019|McDowell et al., 2019]] ; [[#Eriksen--2021|Eriksen et al., 2021]] ). However, systematic assessments of maladaptation in the water sector have barely been provided for CSA.

In CSA, only limited information on the limits of adaptation in relation to water is available, for instance on the possible path dependency of institutions and associated resistance to change ( [[#Barnett--2015|Barnett et al., 2015]] ). Examples of soft adaptation limits (i.e., options to avoid intolerable risks currently not available) include lack of trust and stakeholder flexibility, associated with unequal power relations that lead to reduced social learning and poor outcomes for improved water management, as reported in, for example, NWS ( [[#Lindsay--2018|Lindsay, 2018]] ). An example of hard adaptation limits (i.e., intolerable risks cannot be avoided) in the region is the loss of livelihoods and cultural values associated with glacier shrinkage in NWS ( [[#Jurt--2015|Jurt et al., 2015]] ).

Most barriers to advance adaptation in CSA correspond to soft limits associated with missing links of science–society–policy processes, institutional fragilities, pronounced hierarchies, unequal power relations and top-down water governance regimes ( ''high confidence'' ). One example is the abandonment of long-term hydrological monitoring sites within tropical Andean ecosystems (paramo) in Venezuela ( [[#Rodríguez-Morales--2019|Rodríguez-Morales et al., 2019]] ) due to the lack of governmental support during the political crisis. In that regard, the collection and availability of consistent hydroclimatic and socioeconomic data at adequate scales represent an important challenge in CSA. Major adaptation barriers are furthermore reported from central Chile in the context of a mega-drought since 2010, related to socioeconomic factors and a deficient bottom-up approach to informing and developing public policy ( [[#Aldunce--2017|Aldunce et al., 2017]] ). These gaps could be bridged by strengthening transdisciplinary approaches at the science–policy interface ( [[#Lillo-Ortega--2019|Lillo-Ortega et al., 2019]] ) with blended bottom-up and top-down adaptation to include scientific knowledge with impact and scenario assessments in local adaptation agendas ( [[#Huggel--2015b|Huggel et al., 2015b]] ). For instance, a new allocation rule for the Laja reservoir in southern Chile (SWS), based on consistent water balance modelling results, could inform policy and water management and potentially improve local water management and reduce water conflicts over the long term ( [[#Muñoz--2019b|Muñoz et al., 2019b]] ).

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