Participative water supply management and adaptive capacity in social ecological systems
1. Forschungsfragen
1.1. Welche Rolle spielt CBNRM für die Adaptive Capacity in SES?
1.1.1. Subfragen
1.1.1.1. Wie unterscheidet sich die Governance der Wasserversorgung in den Fallbeispielen?
1.1.1.2. Wie sind die Wasserversorgenden jeweils organisiert?
1.1.1.2.1. Wieso kann das ESPH eine so gute Wasserqualität und -aufbereitung garantieren?
1.1.1.3. Wie viel Fachwissen besteht jeweils in Bezug auf Wasserressourcenmanagement?
1.1.1.4. Unter welchen Umständen können Nutzende mit Wasserknappheit umgehen?
1.1.1.5. Was erhöht die Resilienz gegen Wasserknappheit auf lokaler Ebene?
1.1.1.6. Wie ist die Adaptive Capacity im Kontext von Wasserknappheit bei Gemeinden zu bewerten?
1.1.1.7. Was wird jeweils gegen Wasserknappheit getan?
1.1.1.8. Welche Rolle spielen Umweltbezogene Klimainformationen in diesem Zusammenhang?
1.1.1.8.1. Babcock et al. (2016)
1.1.1.9. Inwiefern sorgen welche Entitäten für einen transofrmativen Wandel hin zu einer Nexus-Perspektive?
1.1.1.10. Inwiefern Stellt zentrales Top-down-Management in armen, vernachlässigten Gemeinden eine bessere Alternative im Vergleich zum CBNRM dar?
1.1.1.10.1. ASADAS können unter Armut nicht operieren, wie angedacht
1.1.1.11. Unter welchen Bedingungen kann CBNRM für die Adaptive Capacity in SES förderlich sein?
1.1.1.12. Welche anderen Bedingungen sind für die Adaptive Capacity in SES förderlich?
1.1.1.13. Inwiefern üben die jeweiligen Wasserversorgenden Einfluss auf die Adaptive Capacity in ihren Systemen aus?
1.1.2. Hypothesen
1.1.2.1. Je größer der Anteil der ASADAS an der Wasserversorgung, desto höher die Adaptive Kapazität.
1.1.2.2. Beim ESPH bestehen die wenigsten Koordinationsdefizite
1.1.2.3. Gemeinschaften ohne ASADAS weisen die meisten trinkwasserbezogenen Defizite auf
1.2. How and why are communities under water scarcity uccessful in adapting to climate change?
2. Definitionen
2.1. CBNRM = Community Based Natural Resources Management
3. Methodik
3.1. Erhebung der Fuzzy Set-Variablen: qualitativ oder quantitativ?
3.1.1. Variablen
3.1.1.1. ADAP-Indicators from Twin2Go project
3.1.1.1.1. Strategy for adaptation to climate change in the water sector (81)
3.1.1.1.2. Availability of specific knowledge enabling adaptation (82)
3.1.1.1.3. Awareness of water managers regarding adaptation to climate change (83)
3.1.1.1.4. Coordinated implementation process regarding adaptation to climate change: Program/Plan of activities and measures (84)
3.1.1.1.5. Operational activities combining hard and soft approaches (85)
3.1.1.1.6. Ways to deal with climate variability (floods and droughts) (86)
3.1.1.2. Other indicators too? (DIS, COR)
3.1.1.3. Weitere Indikatoren, die das System beschreiben
3.1.1.3.1. Standortfaktoren
3.1.1.3.2. Klimadaten
3.1.1.3.3. Bevölkerungszahlen
3.1.1.3.4. Infrastrukturdaten
3.1.1.3.5. ICAA management region
3.1.1.3.6. Wasserqualitätsproben nach e.coli-Bakterien
3.1.1.3.7. Soziale Vulnerabilität
3.1.2. SES-Framework zur Strukturierung von Variablen
3.1.3. Quantitative Befragung der Bevölkerung
3.1.3.1. Ca. 30 per site
3.1.3.2. Zufriedenheit der Bevölkerung mit der Wasserversorgung
3.1.3.3. Bewertung der Bevölkerung von AC
3.1.3.4. Survey respondents who correctly identified community as the owner of the aqueduct (Dobbin/Sarathy)
3.1.3.5. Survey respondents that report they or someone from their house attends annual assemblies (Dobbin/Sarathy)
3.1.3.6. Number of users that attended that last community assembly (percent of users) (Dobbin/Sarathy)
3.1.3.7. Survey respondents who would prefer their ASADA over direct ICAA management (Dobbin7Sarathy)
3.1.4. Erhebungsmethode: Qualitative Interviews
3.1.4.1. 10 key informant interviews
3.1.4.2. In-depth, semistructured interviews were conducted with ASADA board members and employees, and with ICAA
3.1.4.3. Employment status of ASADA president
3.1.4.4. Work experience of board president
3.1.4.5. Number of full-time personnel
3.1.4.6. Board participates in government training programs?
3.2. Möglich: Systems framework (Wiek/Larson 2012)
3.2.1. Identifikation von Akteuren, Institutionen, Aktionen
3.2.2. Identifikation von Wasserflüssen und Intrastruktur
3.3. Möglich: Vergleichende Netzwerkanalyse in Gemeinden mit unterschiedlicher Wasserversorgungseinheit
3.3.1. Inwiefern unterscheiden sich die Netzwerke?
3.4. (fs)QCA
3.4.1. Central condition: ASADA
3.4.2. Outcome. ADAP
3.4.3. Welche Rolle spielt ASADA für ADAP? In wie vielen Fällen ist ASADA eine Bedingung für ADAP? Welche anderen Rezepte führen zu ADAP, wenn asada ist?
4. Sonstige Gedanken
4.1. Das Water Governance System in Costa Rica wird als Fragmentiert bezeichnet. Könnte man die Adaptive Capacity steigern, wenn man für ein höheres Maß an horizontaler Koordination sorgt?
4.2. How can horizontal integration be achieved?
4.2.1. Prä-Post-Studie
4.2.1.1. Erhebung von fsQCA-Indikatoren in mehreren Fallbeispielen
4.2.1.2. Intervention: Stakeholder-Kommunikationsworkshops oder Design einer Onlineplattform
4.2.1.3. Post-Erhebung von Indikatoren
4.3. 02.02.
4.3.1. Gibt es im Einzugsgebiet Orte mit größerer Wasserknappheit?
4.3.2. Koordinationsprobleme - Bestehen in Watersheds bessere Möglichkeiten der Koordination?
4.3.3. Welche Nutzung und Nutzungsformen bestehen in Watersheds?
4.3.4. ASADAS kontextualisieren
4.3.5. Möglich: Manche Fallbeispiele vertieft analysieren und manche oberflächlicher
4.3.6. Case Srudy Analysis (Yin) lesen
4.3.7. Exposé
4.3.7.1. Fallauswahl als Arbeitsschritt darlegen
4.3.7.2. Ideen entwickeln für Fragekomplexe für Paper --> Problemorientierung!
4.4. ASADA-Mitglieder arbeiten zum Großteil unentgeltlich --> Anteilig kann mehr Geld in die Aquädukte fließen, als z.B. beim AyA, wo viele Beschäftigte bezahlt werden müssen
5. Literatur
5.1. Ostrom
5.2. Moraya Montenegro und Bautista Solís (2020)
5.2.1. Rural communites (ASADAS) are very committed with their aqueducts
5.3. Cuadrado Quesada (2017)
5.3.1. Majority of communities in Santa Cruz are supplied by ASADAS
5.3.2. ASADAS as most participative mechanism in water governance in Costa Rica
5.3.3. Importance and history of ASADAS
5.3.4. Biggest problem of ASADAS: lack of institutional support
5.3.4.1. Nosotros le decimos al AyA que, si se supone que el AyA es la “madre” de las ASADAS, nosotros somos huérfanas... ellos no nos dan apoyo ni técnico ni administrativo ni legal... nunca nos capacitan en ningún tema... todo lo hacemos por nosotros mismos... peor aún, sentimos que ellos solo quieren hacernos desaparecer (ASADA N.º 213, 20 de junio, 2014).
5.3.5. Communal leadership helps organizing and solving problems
5.4. Kuzdas et al. (2015)
5.4.1. Analyze key governance actors, their activities and roles
5.4.1.1. Systems framework: analyze regional water systems across four domains: water supply, delivery, use, and outflows (Wiek and Larson 2012)
5.4.1.1.1. Layer 1: Actors, institutions, & actions: Identifies relevant social actors and their networks
5.4.1.1.2. Layer 2: Water flows & infrastructure: How water moves through the system, and how it is distributed, used, conserved, treated, etc. influences peoples actions and vice versa
5.4.2. Research questions & Results
5.4.2.1. What is the structure (or extent of polycentricity) of relevant institutions and the governance actor network (overall and for each water governance domain), and how do these structures influence water governance outcomes? (RQ1).
5.4.2.2. How do individual actors influence water governance and its outcomes in the region? (RQ2).
5.4.2.2.1. ASADA involvement in governance leads to higher cooperation
5.4.2.2.2. ASADA involvement depends on organizational capacity to meaningfully contribute, their will, and available assets that they can draw on to take action
5.4.2.2.3. rural groups are suspicious of government-produced information
5.4.2.2.4. ASADAs don't have capital to drill wells; City holds water right to Río Potrero, limits water supply options for ASADAs
5.4.2.3. How do collective knowledge gaps about the water system affect its governance? (RQ3).
5.4.2.3.1. Key information on water quantities being extracted is not conveyed to ASADAS
5.4.2.3.2. Lower activity levels and coordination of governance in water deliveries related to disconnected ASADAS
5.4.2.3.3. ASADAS who share water sources don't necessarily coordinate with each other
5.4.3. Discussion
5.4.3.1. In Mexico, centralized water governance struggled to make decisions appropriate to local needs (Eakin et al. 2011)
5.4.3.2. ASADAS mostly too disconnected from governance regime to provide meaningful input
5.4.3.3. high variations in ASADA organizational capacity
5.4.3.4. Smallholder farmers and smaller rural communities serviced by ASADAs stand to be impacted the greatest by extreme events
5.4.3.5. ASADAS often distrust government information and programmes
5.4.3.6. Hypothesis: Capacity and political savvy of local leadership is one factor driving differences in local water governance outcomes within the Province
5.5. Pahl Wostl/Knieper (2014)
5.5.1. 29 case studies for comparative analysis of water governance and management systems in national river basins
5.5.2. Performance increased with polycentricity of governance system
5.5.3. Governance systems
5.5.3.1. Polycentric governance systems
5.5.3.1.1. Balance bottom-up and top-down (multi-level) and lateral (inter-sectoral) pathways of influence
5.5.3.1.2. They are assumed to have high performance with respect to integration across issues and scales and regarding adaptive capacity
5.5.3.1.3. Require the combination of different governance modes − namely, markets, regulatory mechanisms, bureaucratic hierarchies and learning networks
5.5.3.1.4. Liebermann (2011): ‘‘the concurrent efforts of at least two governance authorities exercising their powers over a common group of people within a single sector or for a common problem’’
5.5.3.1.5. modular structure characterizing polycentric systems increases resilience and the capacity for dealing with shocks and disturbance
5.5.3.2. Centralized Coordinated
5.5.3.3. Centralized Rent-seeking
5.5.3.3.1. rent-seeking behavior impedes effective coordination
5.5.3.3.2. Lower adaptive capacity
5.5.3.4. Fragmented
5.5.3.4.1. Lack coordination
5.5.3.4.2. Leads to uncoordinated and contradicting actions
5.5.4. Methods
5.5.4.1. Qualitative Comparative Analysis (QCA)
5.5.4.1.1. identifies sets of conditions as potential paths that lead to an outcome
5.5.4.1.2. makes the distinction between sufficient and necessary conditions
5.5.4.2. fsQCA: Analyze different paths toward high and low performance
5.5.4.2.1. cases have in general partial membership in more than one ideal type, they also contribute to more than one configuration.
5.5.4.2.2. Measured by response to climate change challenge
5.5.4.3. Data from Twin2Go project
5.5.4.3.1. Questionnaire comprising 81 indicators regarding DIS, COR and ADAP
5.5.4.3.2. Performance measure for climate change: climate change awareness, adaptation plans, and operational implementation
5.5.4.4. Transform data to 0-1 scale
5.5.4.5. Calculate values for DIS, COR, VCOR, HCOR, ADAP my aggregating fuzzy-set membership values of underlying indicators
5.5.5. Results
5.5.5.1. Polycentric governance systems have high AC
5.5.5.2. Lack of horizontal integration seems to be the essential bottleneck in fragmented regimes
5.6. Barnes et al. (2020)
5.7. Cuadrado Quesada (2021)
5.7.1. ASADAs are key to overall water governance, sanitation, environmental protection and land use planning.
5.7.2. In many communities, ASADAS have controlled urban growth by negating water
5.7.3. Research questions
5.7.3.1. What have been the responsibilities and rights of the ASADAs in Costa Rica in the last 20 years;
5.7.3.2. how can the legal figure of the ASADAs be better understood/defined from a study of their practices;
5.7.3.3. what is the future and challenges of the ASADAs, particularly in their new role as regulators of land use planning; and what is the future of the ASADAs,
5.7.3.4. particularly in their new role as regulators of land use planning?
5.7.4. Tasks of ASADAS according to ASADA regulation
5.7.5. 60% of rural residents; 33% of total population (Monge, Paz y Ovares 2013)
5.7.6. between 1980 and 2012: Have enabled access to better water sources for 28% (Dobbin und Sarathy 2015)
5.7.7. ASADA members want to help their community
5.7.8. Money that ASADAS have can mainly go into aqueducts since most members are volunteers
5.7.9. Nowadays ASADAS are one of the main actors in Costa Rican water governance (FANCA, 2006; Monge, Paz y Ovares, 2013; Cuadrado-Quesada, 2017)
5.7.10. Some ASADAS receive PES because they regenerate forests in their communities where sources are
5.7.11. Responsabilities of ASADAs according to law are very extemsive
5.7.11.1. Only few legal entities in Costa Rica have as many responsabilities in the rural context as ASADAs
5.7.12. The communal is in danger, because public interests are represented by the state and private interets by companies, but who represents the communal?
5.7.13. Rooting of ASADAs and their members in communities is important
5.7.14. In the last years, AyA had several programs to strengthen ASADAs
5.7.14.1. ASADAs often don't have resources to realize big infrastructure projects
5.7.15. An ASADA in a coastal community has negated water rights to a potential resident because of possible saltwater intrusion
5.8. Dobbin/Sarathy (2015)
5.8.1. incomplete decentralization and inadequate institutional support as factors that contribute to failed co-management
5.8.2. AyA couldn't meet the needs of rural majority due to spending cuts, wage reductions, sector reform, and devaluation --> creation of ASADAS
5.8.3. Only 60% of ASADAS provide potable water (UN Human Rights Council 2009). In spite of pervasive rhetoric celebrating co-management’s benefits, almost half of all ASADAS are not succeeding.
5.8.4. Case studies: Uvita, Matapalo, Hatillo
5.8.5. Violations of ASADA regulations did not lead to sanctions
5.8.6. poverty-related ASADA disparities amplify themselves
5.8.6.1. Poor ASADAS can't eploy their members
5.8.6.2. Members of poor ASADAS can't really participate because of full-time jobs
5.8.6.3. No money for expensive systems or fixing old ones
5.8.6.4. concerns about personal expenses visibly affect management
5.8.6.5. ICAA assistance and oversight can only be given if Hatillo board members actually have the time and resources to ask for them
5.8.6.6. Hatillo: Vicious cycle of ASADA neglect
5.8.7. Hint: Varying levels of community involvement impact ASADA performance
5.8.7.1. Yes, measured by water quality
5.8.7.2. No, measured by percent of water users registered as ASADA associates
5.8.7.3. link higher water quality with community-initiated processes of ASADA formation, but not with other manifestations of community involvement in ASADA operations
5.8.7.4. Varying levels of human capital impact ASADA performance
5.8.8. Pagdee et al. identified leadership and community interest as two variables related to success regarding forestry
5.8.9. A similar study investigating the factors that affect the success of fisheries co-management also points to the critical roles of leadership, capacity building in marginalized communities, and adequate financial resources for successful collaboration (Pomeroy et al. 2001)
5.8.10. But rather than a panacea for Central America, co-management is a tool
5.9. Engle (2011)
5.9.1. Maladaptation
5.9.2. Anticipatory adaptation
5.9.3. Reactive adaptation
5.9.4. IPCC (2001): Determinants of AC: economic resources, technology, information and skills, infrastructure, institutions, equity
5.9.5. Connection adaption and collective action
5.9.6. Adaptive capacity is considered critical for reducing vulnerability
5.9.7. Gauging AC
5.9.7.1. is difficult because of latent nature
5.9.7.2. empirically investigate actions surrounding past stress events (e.g., droughts, floods, storm surges, fires, etc.)
5.9.7.3. use this knowledge as a proxy for how systems might build and mobilize (or not) their adaptive capacity to prepare for and respond to future climate changes
5.9.8. Moreover, it is possible that rather than focusing on which specific adaptations were most effective during these periods of gradual and rapid change, it might be more useful to understand what structures, relationships, processes, and other variables allowed for (or blocked) the facilitation of such adaptations (i.e., adaptive capacity).
5.9.8.1. Legitimization of my study
5.9.9. AC is context-specific
5.9.10. Indices and assumptions for measuring AC: (Ivey et al., 2004; Brooks et al., 2005; Smit and Wandel, 2006)
5.9.11. Difference between measuring and charactizing AC
5.9.12. Approaches for measuring/characterizing AC
5.9.12.1. First approach
5.9.12.1.1. analyze the impacts (e.g., loss oflives and property, damage to ecosystems goods and services, etc.) ofrecent stress events that a grouping of similar systems (e.g., SES with similar functions and attributes) has experienced to a relatively uniform extent
5.9.12.1.2. the lower the negative impacts, themoreadaptivecapacity within thesystems
5.9.12.2. Second approach
5.9.12.2.1. looking at multiple periods in time leading up to, during, and after a climatic event to evaluate whether systems actually prepared for and/or adapted to the stress (Adger et al., 2007; Bussey et al., 2010; Ford et al., 2010; Nielsen and Reenberg, 2010).
5.9.12.2.2. if the system adapted or adjusted, then the capacity to do so had to have existed
5.9.12.2.3. identify the factors that facilitated or inhibited these adaptations, where adaptations occurred or did not occur
5.10. Suárez Serrano et al. (2018)
5.10.1. Only 56,4 % of ASADAS offer potable water
5.10.2. Importance of ASADAS in Costa Rica
5.10.3. Of 317 ASADAS in Guanacaste, only 186 have delegation plans with AyA, 175 have less than 200 abbonnents
5.10.4. methods
5.10.4.1. Case study selection: ASADAS in areas that suffer from drought the most
5.10.4.2. Survey instrument: survey “Formulario unificado del Instituto Costarricense de Acueductos y Alcantarillados Subgerencia Gestión de Sistemas Comunales” evaluating
5.10.4.2.1. administrative and financial management
5.10.4.2.2. commercial management
5.10.4.2.3. community management
5.10.4.2.4. water resource management
5.10.4.2.5. water systems management
5.10.4.3. Scaling ASADA development 0-100
5.10.4.4. Water quality indicators
5.10.4.4.1. pH
5.10.4.4.2. electric cunductivity
5.10.4.4.3. turbicity
5.10.4.4.4. color
5.10.4.4.5. taste
5.10.4.4.6. odor
5.10.4.4.7. coliforms
5.10.4.5. testing water quality in rain seasons because rain increases contamination risk
5.10.5. Some ASADAS don't count their water reserves and don't have proper sewerage
5.10.6. Not enough communial participation in water use and protection topics
5.10.7. High vulnerability of ASADAS because of old systems
5.10.8. 3 universal components of sustainability: water demand of community, financing, cost recovery
5.10.9. Some ASADAS in Guanacastecan cantons have conformed
5.10.10. FLU platforms offer implementation of climate adaption measures
5.11. Madrigal Ballestero (2015)
5.11.1. Methods
5.11.1.1. Analysis of ASADAS by applying SES framework
5.11.1.2. Comparing six similar ASADAS
5.11.1.2.1. similar socio-economic and climatic indicators
5.11.1.2.2. ASADAS have less effect from tourism industry
5.11.1.2.3. Medium development areas according to IDS
5.11.1.2.4. 50% of population occupied in agriculture
5.11.1.3. Assessment and characterization of AC closely related to Engle (2011)
5.11.1.3.1. Implementation of adaptation measures and performance during ENSO events
5.11.1.4. conceptual framework for analyzing AC in CBDWO
5.11.1.5. Data collection
5.11.1.5.1. In-depth interviews with water committee members
5.11.1.5.2. Household surveys
5.11.1.5.3. Technical evaluation of infrastructure
5.11.2. Results
5.11.2.1. frequency of water shortages reported by households in the dry season as a proxy of CBDWO performance
5.11.2.2. Main factors explaining performance differencies
5.11.2.2.1. characteristics of the infrastructure to deliver water
5.11.2.2.2. demand-driven approach and social capital
5.11.2.2.3. the human capital of the water committee
5.11.2.2.4. financial and operational rules in use by the local organization (Governance structure)
5.11.2.2.5. accountability mechanisms
5.11.2.3. Adaptation measures
5.11.2.3.1. Hard
5.11.2.3.2. Soft
5.11.2.3.3. Ecosystem based
5.11.2.3.4. Sequential order of adaptation measures
5.11.2.4. Limited capacities of ASADAS
5.12. QCA
5.12.1. Legewie (2013)
5.12.1.1. Main principles of QCA
5.12.1.1.1. complex causality as an underlying assumption
5.12.1.1.2. combination of detailed withincase analyses with formalized crosscase comparisons as the modus operandi
5.12.1.2. Advantages of QCA
5.12.1.2.1. most systematic way to analyze complex causality and logical relations between causal factors and an outcome
5.12.1.2.2. Especially helpful for medium-N data sets (15-50 cases)
5.12.1.2.3. Causality and typology explorable
5.12.1.2.4. Increases transparity of analyses by making explicit number of choices
5.12.1.2.5. Allows identifying patterns in the data that help to guide the development of detailed explanations of social phenomena
5.12.1.2.6. Powerful tool for the development of cutting-edge mid-range theories
5.12.1.3. Concepts
5.12.1.3.1. (Fuzzy) sets, conditions/outcomes, Boolean algebra
5.12.1.3.2. Truth table analysis
5.12.1.3.3. Boolean minimization
5.12.1.3.4. Simplifying assumptions
5.12.1.3.5. Solution types
5.12.2. Rihoux (2006)
5.12.2.1. Several uses of QCA
5.12.2.1.1. to summarize data, i.e. to describe cases in a synthetic way by producing a truth table, as a tool for data exploration and typology-building
5.12.2.1.2. to check coherence within the data: the detection of contradictions allows one to learn more about the individual cases
5.12.2.1.3. to test existing theories or assumptions, to corroborate or refute these theories or assumptions
5.12.2.1.4. to test some new ideas or assumptions formulated by the researcher, and not embodied in an existing theory
5.12.2.1.5. to elaborate new assumptions or theories:
5.12.2.2. Particularly transparent technique
5.12.2.2.1. Researcher makes own choices
5.12.2.2.2. Researcher justifies choices
5.12.2.3. QCA allows consideration of qualitative and quantitative phenomena
5.12.2.4. Small N: Dichotomous QCA Medium N: MVQCA High N: Fuzzy sets
5.12.2.4.1. Not state of the art?
5.12.2.4.2. Disadvantage of small-N: Number of logically possible combinations of conditions quickly overwhelms the number of empirically observed combinations (Ragin, 1987).
5.12.2.4.3. Answer: allow the software to use non-observed cases (called ‘remainders’, ‘logical cases’ or ‘counterfactuals’).
5.12.2.5. Case selection
5.12.2.5.1. not broaden too much the variety of cases.
5.12.2.5.2. The quest for generalization should always be bounded, by comparing cases that share a sufficient number of features and that operate within sufficiently comparable contexts (Lijphart, 1971; Collier, 1993; Ragin et al., 1996).
5.12.2.5.3. It is of vital importance that these comparable cases display enough diversity with regard to the conditions which will be included in the model, and also with regard to the outcome variable.
5.12.2.6. QCA allows for three-way comparison
5.12.2.7. It is good to obtain contradictory configurations
5.12.2.7.1. researcher can learn from these contradictions, as it forces him or her to go back to the empirical cases and to theory
5.12.2.8. Easy and hard simplifying assumptions
5.12.2.9. contradictory simplifying assumptions
5.12.2.10. QCA focuses on combinations of conditions, not on net effect of single variables on the outcome --> Problem mit aktueller Fragestellung
5.12.3. Twin2Go
5.12.3.1. Useful indicators
5.12.3.1.1. 10 (QUAL)
5.12.3.1.2. 11 (QUAL)
5.12.3.1.3. 12 (QUAL)
5.12.3.1.4. 13 (QUANT)
5.12.3.1.5. 14 (QUANT)
5.12.3.1.6. 15 (QUANT/QUAL)
5.12.3.1.7. 16 (QUAL)
5.12.3.1.8. 17 (QUAL)
5.12.3.1.9. 18 (QUAL)
5.12.3.1.10. 19 (QUAL)
5.12.3.1.11. 23 (QUAL)
5.12.3.1.12. 43 (QUANT)
5.12.3.1.13. 59 (QUAL)
5.13. Yin (2018)
5.13.1. Each case must be carefully selected so that the individual case studies either
5.13.1.1. (a) predict similar results (a literal replication) or
5.13.1.2. (b) predict contrasting results but for anticipatable reasons (a theoretical replication).
5.13.2. More replications = higher degreee of certainty
5.13.2.1. Literal replications = ASADA communities
5.13.2.2. Theoretical replications to ASADA communities = AyA/municipalidades communities
5.13.3. Holistic and embedded CS
5.13.3.1. Mixed methods qual/quant = embedded design
5.13.4. Design adaptation always possible
5.13.5. CS candidate screening: <12 candidates
5.13.5.1. querying people knowledgeable about each candidate
5.13.5.2. collect limited documentation about each candidate.
5.13.5.3. AVOID extensive screening procedure that effectively leads to a “mini” case study of every candidate case.
5.13.6. CS candidate screening: >12 candidates
5.13.6.1. collecting relevant quantitative data about the entire pool, from some archival source (e.g., statistical databases about individual schools or firms).
5.13.6.2. define some relevant criteria for either stratifying or reducing the number of candidates
5.13.6.3. reduce the number of candidates to 12 or fewer and then to conduct the onephased procedure
5.13.7. Pilot CS
5.13.7.1. Identification
5.13.7.1.1. know that the informants at a fieldwork site are unusually congenial and accessible, or the site may be geographically convenient or may have an unusual amount of documentation and data.
5.13.7.1.2. complicated case, compared with the likely real cases, so that nearly all relevant data collection issues will be encountered in the pilot case.
5.13.7.2. can be so important that substantial resources may be devoted to this phase of the research
5.13.7.3. Selection
5.13.7.3.1. Convenience, access, geographic proximity as main criteria
5.13.7.3.2. assume the role of a “laboratory” in detailing your protocol, allowing you to observe different phenomena from many different angles or to try different approaches on a trial basis
5.13.7.4. Scope
5.13.7.4.1. can be much broader than the ultimate data collection plan
5.13.7.4.2. can cover both substantive and methodological issues
5.13.7.5. Reports
5.13.7.5.1. mainly of value to the research team itself and need to be written clearly, even if only in the form of memos
5.13.7.5.2. report from one pilot case also can indicate the modifications to be attempted in the next pilot case.
6. Hintergrund
6.1. Operators
6.1.1. AyA (also ICAA)
6.1.1.1. AyA lacks capacity to meet water management responsibilities in rural areas
6.1.1.2. 46,7 % of population
6.1.1.3. the technical governing body responsible for drinking water supply and wastewater sanitation services as well as their operator.
6.1.1.4. Responsible for the collection, evacuation, treatment and disposal of domestic liquid waste; defining the sanitary sewer system as collection networks, collectors, treatment plants and everything required to receive, transport and treat sewage produced in households or workplaces
6.1.1.5. Has sub-department for overseeing and supervising the management of ASADAS
6.1.1.6. AyA aqueducts have verious deficits
6.1.2. ASADAS
6.1.2.1. 24,3 % of population
6.1.2.2. Administrative Associations of Water Supply Systems and Communal Sewers
6.1.2.3. Also known as CAARS
6.1.2.4. Non-profit
6.1.2.5. Apply the rate established by ARESEP
6.1.2.6. Can be defined as multilevel governance regimes
6.1.2.7. Water provision efficiency above national average (Gumeta Gómez et al.)
6.1.2.8. Other responsibilites (Cuadrado Quesada 2021)
6.1.2.8.1. sanitary sewerage service
6.1.2.8.2. surface and groundwater governance (Ballestero, 2016)
6.1.2.8.3. protection of aquifer recharge areas and protection of springs.
6.1.3. ESPH
6.1.3.1. 4,7 % of population
6.1.3.2. Heredia Public Services Company
6.1.3.3. Größter Anteil trinkbaren Leitungswassers besteht in Heredia
6.1.4. Municipalities
6.1.4.1. 17,5 % of population
6.1.5. Others
6.1.6. linea800@aya.go.cr
6.2. Overall, one can conclude that drinking water suppliers are the ones most affected by coordination deficits. [...] Hence, at a local scale they act as innovators and agents of transformative change towards a WEF nexus perspective (e.g. payments for ecosystem services to farmers, development and implementation of integrated landscape management concepts). (Pahl-Wostl 2019)
7. Probleme/Fragen
7.1. Pilot-Fallstudie von hier aus nicht wirklich möglich. Reise Ende 2023 nur zur Durchführung der Pilotstudie und Fallbeispielauswahl?
7.1.1. Zu langsam?