The section includes the enumeration and categorization of stresses that a water resource system is typically subjected to. If, at the simplest level, resilience is a response to stress, it is worthwhile to canvass the stresses faced by a water system in order to understand what a comprehensive approach to resilience requires. The authors then review several dominant resilience paradigms, distill out the properties reflected in the characterization of these paradigms, and then explicitly address the unavoidable normativity of resilience. This last aspect is important to emphasize for decision makers, especially engineers, who might cast their work as being wholly objective/scientific in nature and therefore overlook the tacit value assumptions of their work.
Before moving forward, however, a brief defense of the approach adopted here is in order. In surveying resilience paradigms, the intent is not to recreate extant literature; see for example [7
]. Rather, the authors contend that, when combined, the emphases of individual paradigms support an inclusive, operationalized approach to water system resilience. That is, instead of treating these as mutually exclusive competitors, the authors suggest that each paradigm contains useful insights that can be combined towards a comprehensive approach to resilience in water resource systems. Key isomorphic similarities exist between the general paradigms discussed below and WRM specifically. The literature supports this. Quinlan et al. state “While multiple conceptions of resilience can be problematic in terms of common indicators and comparable metrics, they can also extend the concept to a broader spectrum of contexts and drive exploration for better approaches to implementation.” [13
] (p. 679). Furthermore, Martin-Breen and Anderies argue “…although each framework has historical roots in particular disciplines, the frameworks themselves can be applied to any domain” [14
] (p. 5). Finally, cross sectoral isomorphology has yielded interesting predictive insights in other domains; see Cantu and Beruvides analysis of similarities between cotton and lumber market behavior [15
Some might argue that this bottom-up approach (i.e., beginning with conceptual foundations and building up from there) is needlessly classical, excessively academic, and without practical import. It is better, the argument continues, to begin with water resource systems as they are and work from there. While initially attractive in its immediacy and apparent practicality, such an approach risks the uncoordinated combination of multiple systems ideas or strategies. For instance, within the domain of engineering, several approaches to resilience prevail. Infrastructure resilience, for example, is sometimes defined as the rapid restoration of the pre-disturbance state of affairs [16
]. Whereas some in water resource management have embraced SES resilience which does not privilege the original state of affairs so heavily [17
]. Instead, SES allows that desirable equilibrium can take more than one form. Even within the domain of WRM, however, SES resilience is not universally or, at a minimum, explicitly recognized. The strategic water plan used to develop the operationalized approach outlined in this paper contains no mention of “social-ecological systems” or “social-ecological resilience” [18
]. Even when it is recognized, water resource managers sometimes (arguably by necessity in many cases) focus on short term time horizons (several months to a year or two) versus longer term horizons (e.g., decades); see transformability discussion in [17
]. This is meaningful insofar as the latter, longer horizons are significant in SES resilience. The variability exemplified here, then, can lead to less than effective outcomes or, worse still, counterproductive ones. The goal, in other words, is to move from a mosaic approach to a more systematic one; one that is ultimately systemic in its orientation. An early step towards this goal is to outline a theoretically informed, general operational approach that facilitates measuring and modeling resilience as a dynamic system characteristic.
To unpack the notion of resilience, it is useful to begin with a review of stress in a WRM context. The authors group these stressors into several categories with the understanding that some of the distinctions within the categories exist along a spectrum versus being fully discrete. First, water system stress can be either periodic or continuous. Storm events are an example of the former. A rapid increase of water in a system can lead to an increase of harmful bacteria in surface water and add strain to infrastructure (e.g., treatment systems); even given the boon of an increase in supply [4
]. Periodic pressures can be subclassified by frequency (e.g., high versus low frequency). By contrast, the constant water draw-down from miscellaneous sectoral stakeholders including citizens, farmers, and businesses (energy companies, manufacturers, etc.) represents a continuous strain on the system. Population and economic dynamics determine whether this continuous pressure is constant or increasing; even the former can lead to a lack of resilience over the medium to long term. This distinction between constant and increasing pressures can be treated as a subclassification of continuous stress. Depending how one defines the temporal boundaries of the system, droughts can either be classified as a continuous or periodic stress.
Second, stresses can be both internal and external to the system. In addition to being periodic in nature, aforementioned storm events are external to the system itself. External stressors are, almost by definition, beyond the control of WRM decision makers and ought to be treated as exogenous parameters in corresponding models. Internal stresses include, again, stakeholder draw down as well as other instances such as a leaky (inefficient) infrastructure [20
]. Not all internal stressors are necessarily within the control of water resource managers. For instance, if groundwater supplies are defined as part of a WRM system, the recharge rate (which is impacted by both natural hydrology and anthropogenic pressures) of an aquifer can be considered, with some exceptions, as being beyond the direct control of water decision makers specifically [21
]. There is not, in other words, symmetry in the relation between periodic/external stressors and continuous/internal stressors.
The magnitude of the stress must also be considered. Not surprisingly, magnitude can be reckoned along qualitative lines (i.e., high, medium, and low) or on a continuous quantitative scale. For the sake of simplicity, the authors focus on the former in this paper. Though more coarse grained than a continuously defined magnitude, the high-medium-low approach lends itself to ease of implementation for water resource managers and other professionals; provided such markers (high-medium-low) can be scientifically established. Magnitude, arguably, can defined both objectively and relative to the resilience of the system. It is an important facet to understand when enumerating resilience properties; especially elasticity and stability.
Water resource managers have the unenviable task of trying to anticipate and design for stresses across these categories. The challenge is even more daunting given that combinations across categories create even more threats to system resilience. As highlighted by the storm example, a stress can be both periodic and high magnitude. This is distinct from lower level storms (e.g., those associated with a wet season) that are periodic but low magnitude events. Being aware of what category of stress one is designing for is important not only in determining the most effective strategy to address this stressor but also to identify gaps in the system’s resilience. For instance, Easton and Beruvides developed a method for quantifying the resilience of power infrastructure based upon the modulus of resilience from materials engineering [22
]. This approach is specifically intended to establish the resilience of power systems to high impact but low frequency stressors such as hurricanes. The approach does not, per the authors admission, address high frequency low intensity events. This is due, in part, to the latter being covered by infrastructure reliability versus resilience. This work illustrates that stresses on a system can be multi-faceted in nature and dictate different responses regarding resilience strategies.
2.2. Resilience and Related Terms
CS Holling [23
] is credited with introducing the term resilience in ecology [12
]. However, the term is not limited to this domain. Martin-Breen and Anderies state [14
] (p. 5):
“Resilience has, in the past four decades, been a term increasingly employed throughout a number of sciences: psychology and ecology, most prominently. Increasingly one finds it in political science, business administration, sociology, history, disaster planning, urban planning, and international development.”
Despite this tenure and ubiquity, however, there are some persistent ambiguities in the use of the term. The quote from Martin-Breen and Anderies continues: “The shared use of the term does not, however, imply unified concepts of resilience nor the theories in which it is embedded. Different uses generate different methods, sometimes different methodologies” [14
] (p. 5). Gunderson notes, “Since most management actions are based upon some type of theory, these multiple meanings of resilience can lead to very different sets of policies and actions” [12
] (p. 425). This variation reflects more than context-driven differences. Rather, some of it is attributable an incomplete understanding of the notion of resilience, ideological differences, and unavoidable constraints such as economics.
Martin-Breen and Anderies profile three resilience paradigms—what they refer to as engineering resilience, systems resilience, and resilience in complex adaptive systems [14
]. Beginning with the first, engineering resilience as “bouncing back faster after stress, enduring greater stresses, and being disturbed less by a given amount of stress” [14
] (p. 5). Similarly, Quinlan et al. borrow from Holling [24
] to define engineering resilience as “a system’s speed of return to equilibrium following a shock, indicating that a system can only have a single stability regime” [13
] (p. 678). Angeler and Allen maintain that engineering resilience focuses on the rapid return to the structural and
functional aspects of the system [5
]. These characterizations appear to be largely informed by a structural-materials oriented approach in engineering; an interpretation reinforced by their choice of examples: Bridges, buildings, and infrastructure as a whole. Emphasis in engineering resilience is on the restoration of the state of affairs that preceded the perturbation. It is worth noting that this characterization of resilience is not a wholly static notion. Martin-Breen and Anderies do allow for the system to become progressively less sensitive to the original stress; as manifest by a decrease in distortion amount or, presumably, duration [14
]. While the authors argue that this characterization of engineering approaches is unduly narrow, it does yield several useful insights. It, for instance, helps to highlight a couple properties of resilient systems. They demonstrate both a certain amount of elasticity and stability; where both can increase over time even as the system retains its normal state [14
]. An additional property included here is the speed with which the system returns to its normal state. In this paper, this property is referred to as the retraction rate.
It is in systems resilience that the idea of the system itself changing over time is introduced [14
]. Resilience in these systems can be defined as “maintaining system function in the event of a disturbance” [14
] (p. 7). Here the emphasis is on preservation of system function
versus its original structure. This conception of resilience also demonstrates an appreciation for the multi-level (e.g., stakeholder, spatial, and/or temporal scales) dynamism captured in systems-oriented approaches to resilience [7
]. Accounting for multi-level interactions such as fast and slow feedbacks is critical viz. system resilience. This is especially true when decisions favoring short term, rapid feedback comes at the expense of overall system resilience [26
]. At a minimum, the emphasis on function over structure characteristic of systems resilience is important because, fundamentally, it sets the criterion of success. Stated differently, it helps establish a broader stability domain and, by extension, thresholds [12
]. These thresholds help identify critical points in the system that, when passed, can have deleterious, irreversible effects [7
]. Thresholds also, the authors propose, acts as an important constraint on desired retraction rate; preventing undue emphasis on speed alone. The authors expand on this point in the next section.
Though the move away from an emphasis on the original state of affairs to the preservation of system function constitutes an improvement, Martin-Breen and Anderies maintain that it is still incomplete. They pose the question “If a government collapses, or becomes ineffective, does that mean a community can’t be resilient?” [14
] (p. 7). They go on to argue that communities can evolve over time; even in the face of a catastrophic collapse of the institutions they were previously dependent upon. This objection introduces a property of resilience that is thematic across several definitions—adaptive capacity (AC); see [27
]. Adaptability (and transformability—more on this shortly) helps to define both ecological and social-ecological resilience [7
]. Both ecological and social-ecological resilience fall under what Martin-Breen and Anderies refer to as complex adaptive systems [14
]. Such systems are capable of adapting to stresses over time even fundamentally reorganizing. Folke et al. make a distinction between adaptation and transformation that helps capture the last point. Paraphrasing Berkes et al. [27
], they state “Adaptability captures the capacity of a SES to learn, combine experience and knowledge, adjust its responses to changing external drivers and internal processes, and continue developing within the current stability domain or basin of attraction” [7
] (p. 2). Transformation, on the other hand, involves the more radical change from one stability domain to a new one [7
]. While attractive for its flexibility, the authors focus on adaptability instead. The capacity for adaptation, then, is an additional property of resilience.
2.3. Properties of Resilience
The contention that the paradigms above are distinct but not mutually exclusive underlies the following observation—system resilience is a composite of several properties. These properties can be derived from the paradigms above and represent an early (viz. this project) attempt to move conceptual definitions into an operational domain. It is useful, then, to enumerate and describe these properties. Listing these properties explicitly can lead to a better understanding of the specific targets and outcomes of individual resilience interventions. That is, resilience interventions (aka “strategies”) can be framed by their impact on one or more of the properties listed in this section. This, in turn, allows for an assessment of goodness-of-fit between intervention and the leverage point(s) in the system. Equally important, this connection between intervention and property also has the potential to identify unintended negative feedback loops, both reinforcing and balancing, when more than one resilience intervention is deployed simultaneously. Finally, the approach adopted here facilitates customization to a variety of different systems across multiple domains; especially where resilience is a central, critical goal. In enumerating these properties and identifying their corresponding water resource system measures in Part 3, the authors extend the structural-materials approach characteristic of engineering resilience. While such an extension is helpful, there are limits. It is important to keep in mind that systems resilience retains some sui generis features. There is a limit to the isomorphic connection between the structural-materials and systems domain in other words.
The application of stress does not entail that the system will distort as a result. Martin-Breen and Anderies’ characterization of engineering resilience includes the possibility that a system may become less susceptible to a given stress over time [14
]. That is, the same magnitude of stress applied at tn
may not affect the system as much as it did at t1
. This insight implies that systems have an activation limit; the authors refer to this as the system’s “stability”. It must be noted that this represents a departure from how stability is used elsewhere. As discussed in Gunderson, some authors use the term to denote when a system is at or near an equilibrium point [12
]. Other conceptions couple stability and retraction rate. Some conceptions also take stability to imply the existence of only one valid stability domain. In this work, stability is used much more narrowly to denote the activation threshold a stressor must exceed to create a distortion in the system. If a stress falls below the limit represented by stability, then it does not cause distortion in the system. This lack of distortion may lead to the inclination to disregard stability in the context of resilience. That is, one might argue that resilience is concerned with what happens once the system begins to distort and not before. However, given that some resilience strategies are intended to increase this activation limit, it is worth including it in this typology. Moreover, strategies intended to promote stability may also impact other properties such as elasticity and thus warrant consideration.
Perhaps the most readily identifiable property corresponds to the magnitude of the disturbance the system can handle or absorb before failure. The corresponding system effect is distortion—so the concern more specifically here is with the amount of distortion a system can sustain before failure. Conjuring the image of rubber band, “elasticity” refers to the total distance the band can be stretched before breaking. This distortion can manifest in the system as a whole or with respect to one or more of its components. If a system is defined, in part, by the inclusion of certain necessary components, the failure of any one of these will then lead to overall system collapse. Goldberg refers to this property as “flexibility” and links it with what he refers to as “boundary-oriented” approaches to resilience [30
] (p. 22). He appears to treat an emphasis on flexibility as being mutually exclusive with one that focuses on the speed-of-return to the system’s pre-disturbance state. The authors do not go this far and so eschew the term ‘flexibility’ in favor of the intuitively appealing ‘elasticity’.
It should be noted that in structural-materials science when a distortion is observable, it falls within the domain of “plasticity” versus “elasticity” [31
]. Unobservable distortions fall within a material’s elasticity range. This understanding of elasticity holds that as soon as stress is applied, there is a corresponding distortion; denying the notion of stability introduced above. Instead, elasticity constitutes the first significant threshold of the stress-strain relationship. Distortions that occur in the elastic region are temporary in nature—the material returns to its original state (e.g., geometry). Once a stress exceeds this threshold, then plasticity occurs. The distortion (deformation) observed in the plasticity range is permanent. Insofar as the deformation observed in a material’s plasticity range is permanent, this term is inaccurate in the context of systems resilience where deformation as the result of stress is temporary [22
]. The authors, then, opt to continue to use the term ‘elasticity’ but depart from the characterization that distortions in the elasticity range are unobservable. The contention that systems have an activation limit below which stress causes no distortion (observable or otherwise) represents another departure from the structural-materials approach.
2.3.3. Retraction Rate
If elasticity refers to the amount (distance) a system can distort as the result of stress, then retraction rate refers to the speed with which it returns to a state of dynamic equilibrium. Considering the characterization of engineering resilience above, this property is most germane to those circumstances in which the system returns to its original, pre-disturbance state. This property, for instance, is not necessarily applicable to those situations in which a system permanently changes (e.g., evolves) to a new status quo. Borrowing from both Folke et al. and Martin-Breen and Anderies, this latter rate may be referred to as ‘transformation rate’ [7
]. It is worth pointing out that a faster retraction rate is not always favorable and may, in fact, come at the expense of overall system integrity. Goldberg, for example, observes that rapid, short term interventions intended to either maximize system output or, minimally, restore system equilibrium can lead to overall decline in system health [30
]. The application of pesticides to crops serve as one such cautionary tale. An escalating, destructive cycle of pesticide application, pest resistance, and environmental degradation is the result, he contends, of a short-term emphasis on rapid system balancing [30
]. In generalizing the lessons learned from this and other examples, he states [30
] (p. 19):
“the decision-making process led to large-scale and rapidly implemented decisions. The system upon which such decisions were imposed reacted with unexpected consequences. These unexpected and often undesirable consequences resulted largely from the simplification of the system that is caused by large, fast, simple and direct decision-making process.”
This is not to say that slower is always better. Rapid restoration to an original state may be desirable in some instances (e.g., the restoration of critical infrastructure); see [22
]. This indicates that a nuanced approach to water system resilience interventions requires some recognition of what type of situation one is in. An unreflective emphasis on a rapid versus slow retraction or vice versa is counterproductive. This helps to highlight that individual resilience properties can either work in concert with or against each other.
2.3.4. Adaptive Capacity
The discussion of adaptation above leads to a fourth resilience property—AC. Whereas elasticity, retraction rate, and stability are anchored by the system’s current equilibrium parameters, AC allows for the possibility of permanent system change over time; thereby enhancing its persistence. When actualized, this capacity allows for system evolution while preserving its identity. Note, the authors treat “adaptation” as the actual manifestation of AC. The distinction between adaptation and transformation discussed by Gunderson and Martin-Breen and Anderies turns on what is being preserved (e.g., structure or function) [12
]. If resilience is narrowly defined as preserving the original identity of the system, the distinction between adaptation (remaining within the original stability domain) and transformation (changing to another stability domain) is necessary. However, if the emphasis is placed on the continuity of a functionality that is equifinal in nature, the distinction between adaptation and transformation becomes much less important. The authors adopt the latter approach for the analysis in this paper.
The idea that a system can be stable in the face of stress up to a point implies that there is a threshold beyond which permanent changes take place. This threshold is part of the literature on ecological and SES resilience [5
]. “Thresholds are equivalent to tipping points and may be detected as discontinuities or bifurcation points in complex systems” [5
] (pp. 619–620). Identifying this inflection point can provide helpful insights regarding system leverage as well as provide a necessary constraint to a prescribed retraction rate. The authors return to the latter point in Section 3.1
Some comments on acute vs. chronic distortion are necessary. Thus far, the assumption has been that each of these properties contribute to the preservation of system function, if not structure, indefinitely. However, it is important to recognize that chronic stresses may lead to the permanent degradation of these system properties. Returning to the rubber band metaphor, repeatedly stretching the band eventually leads to a reduction in the tension it can exert or its retraction rate. System design and engineering should take such medium to long term capacity degradation into account.
Quinlan et al. summarize the types of resilience surveyed in their article and authors adapt this approach to resilience types featured in this article [13
]. Specifically, Table 1
orients around Martin-Breen and Anderies’ literature review and summarizes the types of resilience profiled so far, the definition and characteristics associated with each, and the resilience properties derived as a result [14
2.4. System Identity and Scope
The brief survey of definitions and characteristics above illustrates two key questions that should be addressed in aid of an informed, operationalized understanding of WRM resilience. First, it is crucial to understand what ought to be preserved in the face of stress. That is, what anchors the identity of the system intended to be resilient? Based on the simplified characterization of engineering resilience mentioned above, the answer appears to be that a system is equivalent to its structure and that the goal of this form of resilience is the rapid restoration of the original structure; the pre-stress condition [14
]. If so, then it is incumbent on decision makers to identify the essential structural components of the WRM system and ensure they are preserved and, where possible, made more robust to various stressors. Other definitions above (e.g., systems resilience) shift the emphasis to function continuity (instead of structure) over time [5
]. The additional assertion that complex adaptive systems, including SES, have multiple alternate equilibria, a clear expression of equifinality, would appear to reinforce the idea that it is the preservation of function specifically that ought to concern WRM managers [13
The second key question that needs to be addressed relates to system scope; both in terms of considered entities (“stakeholders” for lack of a more accurate term) and temporal horizon. Choice of scope matters at an operational level both with respect to the dynamics given attention and gravitas as well with respect to identifying what constitutes success; specifically, the attribution of resilience. From the perspective of local decision makers, the lowest common denominator of a WRM system is likely to be current human users. This group can be further subdivided according to sector (e.g., agricultural, municipal, industrial) though even the most narrowly focused interventions for resilience are likely to include these and any other relevant human sector. This is social resilience [14
]. Note, at the simplest level, this only captures current generations. More inclusive definitions of social resilience do demonstrate a concern for future generations but remain focused on human interests and outcomes exclusively. By extension, those approaches that focus exclusively on ecosystems can be referred to as ecosystem resilience. SES resilience incorporates both social and ecological dimensions. Though several of the authors discussed so far differentiate between social, ecological, and SES resilience primarily in terms of (1) the level of dynamism demonstrated, (2) presence or absence of multiple equilibria, and (3) emphasis on structure or function, it is natural to extend this to stakeholder identification [5
]. Given this and the emphasis on slower moving variables, ecological resilience is characterized by a wholistic focus and, arguably, diminished emphasis on the welfare of discrete entities or even population subsets within the system. To be clear, slow-moving variables are those that can take decades to play out. In discussing lake system resilience, Carpenter et al. classify sediment phosphorous as a slow-moving variable [26
]. In water resource systems, naturally occurring (vs. artificial aquifer storage/recharge) aquifer recharge can be a slow-moving variable [18
]. These variables impact overall system stability but can present as background noise (at best) in system models with a time horizon shorter than the effect manifestation horizon.
Thus far, the focus of stakeholder inclusion has focused at the level of the system itself. However, Quinlan et al. and Matthews rightly maintain that this focus should not be exclusive [13
]. Matthews frames it this way: “Do we fund projects that broadly build resilience for communities and ecosystems to reduce the impacts of climate change? Or do we ensure that all
projects are themselves resilient to ongoing impacts, whether or not they provide broader resilience?” [32
] (p. 15). Quinlan et al. observe that a shift to governance systems also involves a change from an analytical perspective to a “management or governance” perspective [13
] (p. 684). Of course, the resilience of a system and the resilience of its governance cannot be neatly pulled apart; nor should they be. In WRM, if these two aspects are not fully inextricable, they are certainly mutually causally efficacious. Quinlan et al. recognize as much insofar as they point out that identifying the relationship between resilience strategies, including those focused on the system itself and those on system governance, can lead to “theoretically grounded, composite resilience indices and potential ways of comparing broader concepts…” [13
] (p. 684). Whereas traditional water management approaches emphasized supply and engineering solutions alone, integrated WRM sees that demand must be managed as well and that governance and education both have critical roles to play here [4
]. This more comprehensive approach has been embraced by water resource managers with noteworthy outcomes [17
]. Speaking about resilience without addressing education and governance, then, is incomplete. The operational framework proposed in the next section would create a mechanism by which these interventions can be assessed; both on their own and in combination with others intended to promote system resilience.
An operationalized understanding of resilience also requires specification regarding the temporal scope of the system. That is, the period of time over which the system needs to persist. The answer to this question dictates not only the stressors designed for but the determination of success. Identifying which stakeholders count will go some distance towards informing the relevant time horizon. Returning to the narrow focus alluded to above, if one is concerned with social resilience only, the relevant time horizon will, minimally, be the lifespan of current human stakeholders (e.g., years to a couple of decades) or perhaps one to two future generations; 50–100 years for example. A pivot to either ecological or SES resilience requires the incorporation of slower moving variables that can take decades if not centuries to play out. While this introduces greater complexity and uncertainty, such an expansion is essential given the impact such variables can have on WRM systems; climate change being a perfect example of this.
A persuasive case can also be made for linking a system’s time horizon with what can be measured or modeled. This appears to be the implicit assumption when looking at both studies analyzing WRM dynamics and strategic water plans formulated at a municipal, county, and state level. Along these pragmatic lines, it is also worth considering the resilience implications of a temporal horizon set hitched to election frequency. Elections matter with respect to how water resources are managed. An official who promises lower taxes may meet this commitment by underfunding or canceling critical infrastructure improvements which can lead to a functional decrease in water supply and/or quality both of which, in turn, can stress a water system [20
]. Not surprisingly, what emerges is the importance of temporal dynamics at several scales. A composite strategy should take all of these into account and is reflected in cross-scale resilience approaches [5
The questions raised in this section have direct implications for the development of a systems dynamics model. For instance, the preliminary model in Section 3.3
below includes both human and non-human stakeholders. As the dynamics of consumption and supply availability are plugged into a future iteration of the model, a time horizon will need to be specified over which the resilience of the system is assessed.
2.5. Normativity in Resilience
There is an unavoidable normativity in the application of resilience thinking and interventions. This is so for a couple of reasons. Privileging the conceptions embraced by various stakeholders and decision makers assigns undue weight to approaches that are either incomplete or too narrow with regard to stakeholder inclusion and/or temporal horizon. In many instances, current practices are simply not up to the task. This, then, introduces the question: what should
the goal be? Naturally, related questions regarding who/what should count and for how long follow. Moreover, resilience is, itself, not always a desirable outcome. Some individual and system level pathologies demonstrate a harmful amount of intransigence [13
]. In the context of WRM, for example, a Tragedy of the Commons archetype can show deleterious persistence. This archetype is the result of overusing a shared, finite resource where the negative effects of such overuse are delayed. The feedback delay means that bad behavior can build inertia until the likelihood of resource depletion, if not exhaustion, increases substantially. Insofar as water is a commons, the conditions leading to the Tragedy are contraindicated if the goal is to have a sustainable water system. It is, thus, important to ask whether resilience is desirable to begin with. The authors contend that, prima facie, WRM resilience is fairly uncontroversial with respect to its desirability. Hence, this section will primarily focus on the following questions: who are the beneficiaries of the resilient system and for how long?
WRM are comprised of both human and natural systems. Interactions between these occur at multiple spatial and temporal scales. Moreover, the primary concern of both decision maker and consumer is the provision of supply (i.e., functionality) versus the particulars of how the supply is delivered. Indeed, as illustrated in the strategic water plan discussed in the next Part, the nature of this supply changes over time. It seems clear, then, that SES resilience is the most appropriate to apply within the domain of WRM. It captures the composite, dynamic, and adaptive aspects of water resource systems and recognizes the interaction between social and natural variables in a system. While the authors argue that the expedient return to an original system state (e.g., supply restoration after an outage) is appropriate to emphasize, this approach to resilience also concerns itself with meeting longer term, chronic issues as well. The authors contend that stakeholders in a water resource system are primarily concerned with the system’s ongoing function to continuously supply water versus a particular structural arrangement. In theory, this flexibility also implies the possibility of multiple equilibria so long as water continues to be made available though Baehler and Biddle’s study appears to indicate that decision makers involved in day-day resource management are more likely to favor adaptation within the current stability domain over the more radical transformations that lead to a new stability domain [17
]. This emphasis on functionality is not to discount the role of structure; especially insofar as structure makes a given function possible.
The dual emphasis on social and ecological variables is a double-edged sword. Slow moving variables such as groundwater recharge, climate change, and others have clear causal implications for ongoing water availability and, therefore, ought to be accounted for when assessing a systems resilience to stress. The dynamics of such slow-moving variables can be complex given that they might either exert continuous but low-level pressure on a system or build, like a capacitor, and then impact all at once. This reflects the potential, albeit unavoidable, downside to SES models; increased complexity. Complexity is a potential downside for two reasons. First, an increase in complexity can also increase the potential for error, unintended model artifacts, and other concerns. Second, the more complex a model is, the less attractive it may be to decision makers who need tools that are accessible, reliable, and well matched to the available data [34
]. Factoring in the welfare of non-human stakeholders both reflects an ethical mandate of SES resilience and further increases the complexity of this project.
Even the initial survey offered in this paper reveals an enormous amount of intricacy involved with conceptualizing and actualizing resilience. It may be tempting to sidestep the resulting difficulty altogether by arguing for a kind of prescriptive pluralism; to allow multiple definitions of resilience to be adopted and prescribed regarding a system and its governance. At an operational level this leads to an approach to measurement that is fractured and diminishes the benefit of the isomorphic application of insights from one domain to another. Thus, the authors reject this prescriptive pluralism in favor of a generalized approach that can be customized to different systems; not only in the domain of the commons resource management but beyond as well.