In our case study, we operationalized and connected different methods in the QST process (Fig. 1) as follows. Two study areas were selected in different islands of the Canary Archipelago. The first area is the region of the Southeast of Gran Canaria, an agricultural area with a long trajectory in the use of AWR. Here, we analyzed narratives about the experiences managing these resources and the challenges ahead. The second study area focused on a new project of reclaimed water for agricultural use in the Valle Guerra region, Northeast Tenerife. When initiating this study, a tertiary treatment plant was launched, but the distribution network was still under construction. Therefore, farmers were relying exclusively on freshwater resources. Contrary to the Gran Canaria case, this study provided insights into the expectations and conflicts raised when an innovation is initially implemented. Both agricultural areas produce a variety of irrigated crops mostly for exportation (65–80% of annual production) but also for local markets and self-consumption.
This section covers the different stages and methods of our QST process as presented in Fig. 1. We only include mentions to relevant results to reflect on the quality of the process with regards to our methodological objectives.
Socio-institutional analysis and stakeholders map
Our QST process kicked off with a socio-institutional analysis that enabled a shared framing of the issue among researchers with different backgrounds and a general contextualization within the social, technical, and regulatory context of AWR in the Canaries. Building upon Corral-Quintana et al. (2016), the methodology at this stage combined the analysis of normative documents, websites of institutions and organisations, local gray, and scientific literature regarding water, energy, and agricultural governance in the region. In addition, this process assisted in mapping the relevant categories of actors to engage.
Table 1 presents the actors by categories. In the first stage, a broad categorization of actors was made according to their social–institutional roles, responsibilities and decision capacity within the Canarian context (general category in Table 1). As the analysis advanced, the different institutions and organisations identified were placed into the respective categories. Third, to identify representatives of each of these groups, we searched online social networks and main regional newspapers from 2017 to 2019. Individuals actively speaking or involved in the topics of agriculture, water, and energy were identified, obtaining an initial list of 50 actors. This list was filtered to a balanced sample of 30 actors actively speaking about AWR in relation with water and agriculture, and to a lesser extent with energy (the energy dimension was less frequently discussed in the media).
Identification of narratives
The interviews served the purpose of initiating the engagement process through a one-to-one conversation while eliciting narratives with regards to the past, present, and future of AWR in the study areas. An interview guide was collaboratively prepared by all members of the research team (see Online Appendix). We tried to widen the scope of analysis from the specific technical challenges AWR are facing to the roles they play in the islands’ environmental, socioeconomic, and institutional contexts. For this reason, the interviews commenced by asking about their views on the situation of water resources and the agricultural sector and about the purpose of AWR within this context. To improve our understanding of the network of actors and to identify actors to engage in the final workshop, we included questions on the interviewee relation with AWR and on the actors involved in both their development and governance. We further inquired about the current challenges and the future expectations. Finally, we introduced the nexus concept and asked about its potential usefulness for their daily actives and more in general for AWR governance.
Actors were contacted by phone and email and interview sessions were scheduled throughout January and February 2019. The interviews were semi-structured and conducted in Spanish by two researchers of the team, both Canarian and with different backgrounds in sociology and agronomy. Out of the 30 contacted actors, a total of 27 were finally interviewed (Table 1). In Gran Canaria, 7 interviewees represented expert knowledge from either public authorities or research organisations, with agricultural backgrounds more represented than water knowledge. On the other hand, in Tenerife, there was a stronger focus on water backgrounds and a larger representation of water and agricultural management organisations.
Civil society and individual farmers were under-represented in the sample of actors interviewed on both islands. This underrepresentation can be considered a limitation of our methodological procedure, because those groups have lower presence in the mainstream regional media. Thus, a more exhaustive search is needed using other sources, such as alternative, non-official, or very local media. Finally, it is noteworthy that only 3 of our interviewees were women, neither of them from governmental bodies, suggesting that this group is under-represented both in the media and in the institutional context.
In terms of the analysis, our first step was to distil the narratives from interviewed actors through an iterative coding of interview transcripts. A coding framework was developed connecting different categorizations of narratives (see Table A.1 in the Online Appendix). The first and most important analytical criterion was the way interviewees storied causality relations around AWR. For this purpose, we built upon Felt and Kommission (2007) to distinguish between justification narratives (why were/are AWR pertinent innovations in the study areas? What challenges do they face?), normative narratives (what should be done?), and explanation narratives (how should challenges be addressed?). These main questions linked to each type of narrative were answered following the pre-designed coding framework, associating specific actors’ quotes to each code. For instance, key codes for justification narratives are ‘social-ecological perception’, ‘causes’, 'benefits', and ‘problems’; for normative narratives: ‘solution’, ‘role’; and for explanation: ‘action’ and ‘target’. In the next step, we built the narratives analyzing the narrated causes–effects; how causes and benefits are related; what are the concerns at the moment; and what is the role of particular measures, targets, and policy instruments. Following this analysis, we arrive at a set of narratives, which do not represent specifically the vision of the interviewed person, but the standpoint of several actors as exposed in the typology of Table 1. It is worth noting that actors might not align across all narratives, but rather follow different causal avenues from the problems they perceive to particular solutions.
As a second analytical dimension, we focus on uncertainties surrounding the stories about causality. For this, we built upon Brugnach’s et al. (2008) relational uncertainty framework. We systematically coded as ambiguities the claims that sustained divergent positions in the identified narratives. We also analyzed epistemological uncertainties as claims referring to insufficient information or uncertainties about a particular issue and used as input for decision making.
Finally, we selected the most representative narratives to be considered in subsequent steps of the QST process (see list in the Online Appendix). By representative, we mean narratives claimed from more than one actor. In fact, those narratives defended by only two actors were coded as ‘underrepresented’ as compared to ‘mainstream’ narratives were more interviewees aligned. We only selected one narrative upholded by a single actor in Tenerife. The reason behind this exception is that this actor contested the main justification provided by AWR promoters from an important power position in the network of actors. Therefore, its influence as a contested narrative was high.
In general terms, the analysis revealed a strong convergence among most interviewees on the defense of AWR as a means to guarantee water availability and security in the Canaries. In the case of Gran Canaria, most actors highlighted the multiple benefits of AWR whereas the farmer and agronomic experts discussed new problems and risks associated with their quality. We observed strong concerns about the situation of the agricultural sector connected to proposals for making AWR accessible to small and rural farming systems producing for local markets. On the other hand, in Tenerife, we found critical perspectives of the role of AWR within the economic model of the island, contesting mainstream justifications. We also observed divergent positions with regards to farmers’ acceptance of the new resources. Considering these results, we decided to focus the final workshops on exploring those aspects with divergent opinions on one hand, and the uncertainties surrounding the expectations on future uses of AWR on the other hand. Before that, the identified narratives were contrasted with a quantitative analysis of nexus interconnections.
Quantitative analysis of nexus networks
Quantitative analysis within QST serves the purpose of generating pertinent feedback to previously identified narratives in terms of: (i) a system analysis that contextualizes the problem, (ii) exploration of ambiguities and divergent positions with available quantitative data; (iii) identification of key constraints to expected solutions or pathways derived from trade-offs across WEF nexus dimensions, and (iv) identification of key epistemological uncertainties with regards to existing data and evidence. The quantitative engine of QST is the Multi-Scale Integrated Analysis of Societal and Ecosystem Metabolism—MuSIASEM (Giampietro and Bukkens 2014) and its recent developments to nexus networks (Cabello et al. 2019; Serrano-Tovar et al. 2019). In a nutshell, MuSIASEM applies systems thinking to analyze relations between patterns of production and consumption of water, food, energy, and other resources. In addition, it explores relations between societal and environmental variables across scales.
In our research, MuSIASEM was applied to diagnose how AWR were used within the common pool of water resources, by what type of farming systems and at what energy and monetary cost in the study areas. To analyze such patterns of water use—food production—energy use, data were gathered through field surveys to a stratified sample of farms in each study area (31 in Gran Canaria and 37 in Tenerife) and complemented with secondary data sources. Among other agronomic variables, farmers were asked about their production systems (crops, technology, inputs, production, and markets) and water management practices (sources, suppliers, prices). The survey in Tenerife included explicit questions about the acceptance of the new reclaimed water resources. Secondary data sources were used to complete gaps in the surveys, to analyze the status of groundwater bodies and the energy costs of the different water resources.
Since the focus of this paper is on the analysis of narratives, a summary of the design of the nexus network and of the data management process is provided in the Appendix. Further information can be found in the MAGIC project deliverable (Cabello et al. 2020). In the next section, we explain how we analyzed quantitative data to provide feedback onto the narratives.
Connecting qualitative and quantitative analysis
The second analytical step was explicitly framed within the final deliberative workshops. That is, the contents and formats of the analysis were designed as a means to set the scene for an exercise of collective reflexivity on the identified narratives. As shown in Table 1, engaged actors in the workshops were mostly experts, academics, or public servants from different administrations and governmental bodies. However, there were also farmers, water management, and civil society organisations. Therefore, the challenge was how to design and present our analysis to such a diverse plenary in a way that could challenge assumptions about the expected roles of AWR while raising interest to spark discussions.
The process was highly interdisciplinary with quantitative and qualitative researchers working in close interaction. The most representative narratives found during the previous analysis were used to create a story about the innovation and its deployment in each study area. In Gran Canaria, the script connected justification (why?), normative (what?), and explanation narratives (how?) adding a temporal flow from past/present roles or challenges of AWR to future expectations. In Tenerife, the story emphasised the existence of different justifications for the need of AWR and explored divergences with regards to the use of reclaimed water.
Each narrative was illustrated with several anonymized claims from the interviews, plus, if data pertinent to the narrative was available, one or more graphs. The selection of the graphs’ format and content followed criteria of relevance and inclusiveness. That is, we chose the least amount of quantitative information in the simplest visualization format (mostly pie and bar graphs) to support the messages we wanted to convey. On some occasions, the data simply supported the narrative claims reinforcing an existing consensus (like ‘the use of AWR in Southeast Gran Canaria is now larger than freshwater resources’). On other occasions, it contradicted them by pointing to the presence of ambiguities and contested perspectives (like ‘farmers are in favour of AWR’, the survey data showed 40% of farmers rejecting the use of AWR in the Tenerife study area). Many times, it was about clarifying issues for which no information was signaled or for which different figures were used to support divergent positions (like the monetary and energy costs of different water sources), therefore addressing uncertainties. In addition, we found one narrative prescribing a future scenario for which potential constraints could be quantified (we estimated the cost of pumping AWR from the coastline to rural areas situated between 700 and 1000 m above the sea level). Finally, there were also relevant narratives referring to issues for which we had no data available (like claims about the impacts of AWR quality on soils and crops) or depicting futures which could not be estimated with existing data (for instance the expected role of renewable energy sources to lower the price of AWR). In those cases, we included the qualitative information about the narrative, signaling the lack of data, and the associated uncertainties. Figure 2 presents a summary of these different QST strategies. In the Online Appendix, we expand on the mentioned examples for each strategy.
Participatory assessment of narratives
The last stage of our QST process (Fig. 1) was to create spaces for social interaction where narratives could be assessed and desired futures imagined. A participatory workshop was organised in each study area engaging a total of 31 actors in Gran Canaria and 34 in Tenerife (Table 1). The workshops followed a similar structure. After presenting the mixed-methods analysis of narratives and contextualizing it within the MAGIC project and QST experimental research, participants were divided into 3 working groups. A participatory narrative inquiry method adapted from Kurtz (2014)Footnote 2 was used to appraise identified narratives within the groups: one Business as usual scenario (BAU) and two Alternative scenarios (Table 2).
The alternative scenarios were designed considering the results of our previous analysis. Considering the notable consensus of AWR observed in Gran Canaria, the scenarios were framed according to identified ‘what for’ narratives. They mostly referred to making AWR accessible for small and rural farmer. On the other hand, alternative scenarios in Tenerife were designed to explore contestation on the justification for the development and use of reclaimed water, providing a space for under-represented narratives to be expressed. For this purpose, we used imaginary news depicting ‘negative’ near-future contextual changes, namely the food trade and climate-energy crisis, that could potentially influence the use of reclaimed water in the study area. Additionally, this workshop kicked off with a field trip. We visited three actors holding different perspectives and information about the reclamation project: the reclamation plant and two farmers. Thereby, narratives as ‘knowing in action’ were added to the pool of information to explore divergences.
Within the groups, each participant was provided with a printed booklet including the mixed qualitative and quantitative analysis of 4–5 narratives to assess. The narratives for each group were selected to prompt a discussion about the context, constraints and uncertainties of the use of AWR within each scenario. For instance for the BAU scenarios, we selected narratives referring to the contribution of AWR to groundwater conservation and to foster agricultural production to explore uncertainties in these connections. On the other hand, assessed narratives in alternative scenarios referred to accessibility factors like price, quality, and energy costs. Narratives on actual problems and impacts generated by the use of AWR were appraised by all groups.
To assess the narratives, the same iterative process was followed: first, the narrative was read and time was given to go over the data and think of their opinions; second, deliberation over the narratives was structured with a two-axes panel in which the vertical axis depicted a dimension of viability from ‘Sure’ to ‘Impossible’ and the horizontal axis depicted a dimensions of desirability from ‘Great’ to ‘Terrible’. The resulting four-quadrant space provided a way to structure the views from participants on the different narratives according to the combination of the two plausibility criteria. The discussion was organised in rounds, so all actors could voice their opinion and locate their contributions in the panel. The aggregation of individual opinions generated a pattern that spoke for the collective positioning of the group with regards to each narrative. The process was repeated, so that, by the end of the exercise, collective patterns showing the assessment of the scenario were obtained.
Building upon this reflection, participants were asked to define a future out of the ideas within the viable-desirable quadrant using a headline format. In a final backcasting exercise, participants were asked to identify external and internal drivers for this future, to propose actions and to assign accountability by naming the actors and institutions that should be involved in those actions.