Understanding how municipal water systems and their managers are learning and adapting depends on sound and accessible data. Water systems represent a socio-technical system that includes “water, ecological and climatological interfaces, infrastructure, laws, consumer practices, and public and private-sector organizations” (Hornberger et al. 2015, p 4635). Therefore, data on water systems should contain a variety of factors, including climate predictions, organizational adaptability, water usage, population characteristics, education/training of water managers, economic data, and infrastructure details. Institutional actors could benefit from information systems that collect, analyze, and display sustainability and resilience characteristics of the water system management process, including elements of adaptive management, adaptive capacity, and dynamic capabilities.
Adaptive water governance
One approach that institutions and communities adopt for water governance is adaptive management—the systematic process in which management continually improves its strategies based on what has been learned from previous management outcomes (Benson et al. 2015; Engle et al. 2011; Pahl-Wostl 2007; Pahl-Wostl et al. 2007). Adaptive management can lead to system change, including socio-political change that alters water usage and demand, physical infrastructure retrofits that make water supply and delivery more sustainable, and ecological forethought that considers the sustainability of the Earth for posterity (Pahl-Wostl 2007). Adaptive management is place and system dependent because each faces dissimilar uncertainties, including land use, population, economic activity, cultural factors, political circumstances, climatic conditions, and demand for services (Smit and Wandel 2006; Ivey et al. 2004). Instead, it is more the recognition of and willingness to experiment with management tactics to address uncertainties that characterizes adaptive water governance.
Oftentimes, the mentality is to do the bare minimum to carry out the adaptive management, thereby depriving the management approach of teeth. Adaptive management involves:
exploring alternative ways to meet management objectives, predicting the outcomes of alternatives based on the current state of knowledge, implementing one or more of the alternatives, monitoring to learn about the impacts of management actions, and then using the results to update knowledge and adjust management actions. Adaptive management is rooted in the process of learning and adapting, through partnerships of managers, scientists, and other stakeholders who learn together how to create and maintain sustainable resource systems (according to Williams et al. 2009 p. 1).
Organizations and communities cannot afford to remain risk adverse due to path dependence. Engle et al. (2011) argued that any “management that treats different aspects of water, e.g., hydrological, ecological, and socio-economic, separately, ignores their inherent interdependency, possibly at the expense of long-term sustainability” (p. 1). Management routines and processes, then, must be dynamic and evolve alongside the regulatory, social, economic, and ecological changes (Gunderson and Light 2006; Dessai and Hulme 2007). Adaptive water management benefits from integrating scientific knowledge and local knowledge, and institutional mechanisms can help stakeholders to continually coproduce and interpret this knowledge (Simpson et al. 2015).
Building adaptive capacity
Adopting adaptive management principles in water governance can lead to a higher degree of adaptive capacity in a system, be it ecological, socio-political, or socio-ecological, to “adapt to change and respond to disturbances” (Armitage 2005, 706). As Armitage (2005) noted, several authors have refined the concept to fit their research needs (Olsson et al. 2004; Smit and Wandel 2006; Walker et al. 2002), but the general idea is to manage common resources, such as water, through experiments, learning processes, and acting on that knowledge to “foster innovative solutions in complex social and ecological circumstances” (Armitage 2005, 703). The end goal is to become more resilient and reduce vulnerabilities (Folke et al. 2002).
To manage a water system effectively and increase its adaptive capacity, institutional actors and water users must understand the issues that surround their current system and have the ability to predict how the system might be disturbed (DeOreo 2006; Lockwood et al. 2015). For instance, systems that are expected to experience increased growth should respond proactively to ensure adequate water supplies for residents and businesses. Raw water assets, whether it is purchased water, groundwater, or surface water, are vital to adaptive management and increasing capacity. The source of the water supply and demand forecast information may influence how local water managers interpret scientific information from higher governance bodies (Damanpour and Schneider 2009; Lemos 2008, 2015). While one study in Ontario, Canada, found that some watershed-level governance decision-makers perceived technical scientific knowledge to be more valid than local knowledge (Simpson et al. 2015), differences in the water decision-making context in Oklahoma (e.g., local distrust of government and state agencies) suggest a potentially different interpretation of the value of scientific versus local knowledge. This may also differ spatially and between urban and rural areas within Oklahoma, where different historical traditions characterize their connection to higher-level government agencies.
Many factors influence the ability of organizations to produce adaptive measures (Ivey et al. 2004). Organizational skills such as managerial competence, resources, infrastructure quality, risk aversion of employees, and formal institutions guide adaptive decision-making within organizations (Arnell and Delaney 2006; Lockwood et al. 2015). Boyle (2014) suggests that utilities should first address financial constraints by adjusting user rates that “reflect the incremental cost of producing another unit of water, taking into consideration long-term water resource capital costs and the rising costs associated with water shortages” (p. 4). Water infrastructure is also a crucial component affecting adaptive capacity, and a 2009 American Society of Civil Engineer study gave the USA a ‘D’ grade on water system infrastructure (Boyle 2014). Drinking water and waste water infrastructure once again received a ‘D’ in the 2013 report (American Society of Civil Engineers 2013). Solving this infrastructure deficit will require adaptive management and institutional innovativeness.
Another vital aspect of water utility adaptive capacity is the degree to which a utility can influence consumer behavior (Arnell and Delaney 2006; Lockwood et al. 2015). Maintaining good relationships with customers and government officials is especially important in systems that seek authorization for new innovations that do not have regulatory support (Bulkeley and Betsill 2005). Without broad support from the public, necessary funding from such options as water rate increases may not be possible because utilities are subject to the approval of city councils. Implementing successful adaptation strategies involves coordination spanning multiple jurisdictions and departments, which makes communication and the allocation of responsibilities more difficult (Berkhout et al. 2006). Governments may initiate adaptive measures through regulations and mandates (Adger et al. 2005). To be successful, these adaptive policies must be based on trust, reciprocity, and the value of social networks (Lockwood et al. 2015).
Adger et al. (2005) argued that adaptations can be organized in three categories: reducing sensitivity, altering exposure, and increasing resilience to cope with changes. Increasing potable water reservoir capacity or drilling new water wells that provide reserve supply for emergency cases are examples of measures that reduce sensitivities. Altering exposure entails the investment in new or upgraded infrastructure that is more climate resistant, and increased resiliency of a system can occur through actions that enhance the general public’s comfort and security while also strengthening the community’s ability to withstand and recuperate against various stressors and losses. Resilience is also enhanced by incorporating flexibility of information collection and exchange, as well as flexibility of water storage and movement within the water system—all of which would benefit from digitalization and the sharing of information.
Identifying and deploying capacity
The process of identifying and deploying various adaptations is complex and often constrained by institutional forces. Municipal adaptations are first spurred by assessing the nature and scale of system vulnerabilities (Bulkeley and Betsill 2005). Significant hurdles are apparent at this stage, the most notably being the lack of adequate data concerning local scale impacts as a result of climate change and current quality assessments of system infrastructure. Adaptation at the urban scale has largely been limited to knowledge accumulation and strategy development. Financial resources and the lack of power in decision-making processes by management are largely to blame for the inability to enact adaptations. Zimmerman and Faris (2011), for example, found that North American cities have largely remained stagnant in their pursuit of water governance that considers climate change adaptation and policy. Experiments that may prove beneficial to more widespread adoption of climate change adaptations occur merely as “interventions to try out new ideas and methods in the context of future uncertainties” (Broto and Bulkeley 2013, p 92). Adaptive capacity can be generated through effective management that places significant emphasis on learning (Pahl-Wostl 2007); at the same time, management processes and routines can become “more adaptive and flexible to make it operational under fast changing socio-economic boundary conditions and climate change” (Pahl-Wostl 2007, p 51).
Water governance can contribute to sustainability value creation for urban water systems (Marlow et al. 2013). This requires more significant changes than the current trend in water management of treating and delivering low cost water to consumers (Marlow et al. 2013). Faced with the uncertain impacts of climate change, past knowledge of urban water systems and water resources must coevolve with ongoing water system knowledge generation to become more dynamic (Kiparsky et al. 2012). Wiek and Larson (2012) maintain that sustainable water governance requires “coordinating all relevant actors in their water-related supply, delivery, use, and outflow activities in a way that ensures a sufficient and equitable level of social and economic welfare without compromising the viability and integrity of the supporting hydro-ecosystems in the long term” (p. 3156). Such an approach advocates for the use of sustainable yield as part of an adaptive capacity and learning-centered system.
Measuring adaptive capacity through dynamic capabilities
One way to measure the extent to which water utilities are building adaptive capacity is to view managerial actions through a dynamic capabilities lens. Teece et al. (1997) defined dynamic capabilities as the “ability to integrate, build, and reconfigure internal and external competences to address rapidly changing environments” (p. 516). Innovativeness can be measured as an output of dynamic capabilities learning processes, and thus as a measure of how organizations build adaptive capacity and execute adaptive water management (Lieberherr and Truffer 2015). This approach can help fill the “serious knowledge gaps and the lack of a sound conceptual base to understand learning and change in multi-level governance regimes” (Pahl-Wostl 2009, p 355).
Information systems, digitalization, and visualization of water governance
The digitalization of data opens new opportunities, particularly in the sustainability arena. Since the goal of adaptive water governance is system resilience, sharing what has been learned and what capabilities were beneficial can enhance other water utilities’ efforts of becoming more sustainable (Chen et al. 2008; Robinson et al. 2006). Digitalizing content makes things more transparent, and depending on the type of information system used, it can also lead to real-time education. Indeed, if water managing organizations established an information system for digitalizing material related to their adaptive capacity building techniques via their dynamic capabilities, they could improve their efficiency and ability to use the information to enhance system resilience, while establishing a potentially long lasting database for others to reference (Standing and Jackson 2007). A recent example is the creation of the New California Water Atlas (NCWA), which
tells the story of California water, makes data about water resources more open and transparent, and provides tools to activate effective citizen participants. NCWA…re-imagines the role of an Atlas in today’s real-time web and big data era. [NCWA will] provide users with an intuitive and smoothly functioning interface for understanding the state’s water system, which serves as a platform for sharing stories and data.
The builders of the atlas explain that “data about this complex [water] system is woefully unorganized, inconsistent, and difficult to navigate. Information is scattered across many sites, and users are confronted by multiple data formats with few options for automated retrieval” (The New California Water Atlas 2015). And herein lies the overarching problem: big data is of no use unless it is readily accessible and usable.
With advances in technology, researchers can now digitalize disparate forms of data. Digitalization as a process enables researchers to visualize, join, and represent disparate data to form new interpretations. Visualizing the qualitative data has enabled us to see how actors and infrastructures in Oklahoma compare to one other based on patterns of population, precipitation, and income, and local water governance factors such as training, partnerships, and knowledge of water infrastructure improvement grants.