Learning consciousness in managing water for the environment, exemplified using Macquarie River and Marshes, Australia
Craig A. McLoughlin
A * , Richard T. Kingsford A and William Johnson B
A
B
Abstract
Ongoing learning is essential for freshwater ecosystem management, but there is limited documentation of successful integration into management.
We aimed to increase learning-related understanding required for effective adaptive management of water for the environment, in water-stressed and contested river systems.
We developed a learning approach (requisite learning) for managing water for the environment, demonstrated with real-world examples from the Macquarie River and Marshes, Australia.
Four co-existing, interdependent learning types enable effective management of water for the environment: (1) ‘adjusting routines’, (2) ‘adaptive assessment’, (3) ‘changing practice’, and (4) ‘transforming governance’, exemplified by using management of water for the environment for the Macquarie River and Marshes. To enable and improve requisite learning, stakeholder social learning, and flexibility in governance arrangements, must develop.
Ongoing learning is essential for effective adaptive management. Understanding what requisite learning is and how capacity can be improved, will help achieve outcomes required of managing water for the environment.
Effective management of water for the environment is essential, transparently delivering environmental outcomes and accounting for decision-making. To do this, we need to improve explicit learning understanding by nurturing learning mandates and champions, fostering social learning, increasing flexibility in governance arrangements, and institutionalising learning.
Keywords: adaptive management, environmental flows, freshwater ecology, governance, Murray–Darling Basin, river regulation, social learning, social-ecological systems.
Introduction
The highly biodiverse freshwater realm (freshwater living planet index, in Almond et al. 2022), with the highest species diversity per unit area of any realm (Finlayson et al. 2005; Dudgeon et al. 2006), provides vital ecosystem services, including provisions (e.g. food), non-material benefits (e.g. recreation) and regulating services (e.g. habitat creation or maintenance) (Díaz et al. 2019). The Anthropocene has witnessed severe biodiversity declines of freshwater ecosystems (Vörösmarty et al. 2010) at unprecedented rates and scales (Kingsford et al. 2017a; Albert et al. 2021). Approximately one-third of the world’s river basins were deemed severely water depleted, owing to water-resource development over the past half century (Harwood et al. 2017). Land-use change, water over-abstraction and building of dams have altered natural water quantity and quality in rivers and wetlands, contributing toward more than 80% decline in freshwater species’ (mammal, bird, amphibian, reptile and fish) populations, globally (freshwater living planet index, in Almond et al. 2022). This decline is projected to be increasingly exacerbated by climate-change impacts (Xi et al. 2021). The ongoing delivery of ecosystem services, for human benefit, is dependent on maintenance or restoration of ecosystem integrity within sustainable management and use of freshwater resources (United Nations World Water Assessment Programme and UN-Water 2018).
Responding to freshwater ecosystem degradation, many countries have legislated to provide water for the environment, monitored and evaluated to deliver ecosystem service-related outcomes (Harwood et al. 2017; Nel and Roux 2018; Tickner et al. 2020). These are often managed with natural flows or even water for other uses to maximise environmental outcomes. Such management of water for the environment is critical for many freshwater ecosystems. However, managing water for the environment is complex, given uncertainties in interacting social (including cultural) and biophysical system components, and inherent cost and benefit trade-offs of implementation (Webb et al. 2018; Chen et al. 2020; Thoms et al. 2020). Knowledge and understanding are always imperfect (Biggs and Rogers 2003; Rogers 2003; Gunderson 2015), inevitably making management uncertain (Stankey et al. 2005; R Biggs et al. 2015). Collating, documenting, and recognising links and dependencies makes it difficult to learn from actions and outcomes. Adaptive management provides an approach for explicitly organising these elements for management of water for the environment. Managers retain flexibility, but there is rigour for operations and learnings to achieve desired outcomes (Nel and Roux 2018; Anderson et al. 2019; McLoughlin et al. 2020). There is an increasing awareness of learning in adaptive management more generally, and as an integral component to effective management of water for the environment. In this context, learning is a reflexive process, identifying and critically examining the assumptions, values, and actions that frame knowledge (Cunliffe 2004; Pollard and du Toit 2007). It prompts adaptive feedback among stakeholders, facilitating single-loop (adjusting, improving existing routines, often ecological), double-loop (changing practice, often social), and triple-loop (reviewing values, governance arrangements, social) learning (Pahl-Wostl 2009).
Learning: adaptive resource management
Learning is essential for effective and successful adaptive management of natural resources (Roux et al. 2017; Allan and Watts 2018; Schoeman et al. 2019), to iteratively modify, improve and reframe policies, approaches and actions, while also transforming governance (Pahl-Wostl et al. 2013; McLoughlin and Thoms 2015; Pollard et al. 2023). Generically, adaptive resource management embodies a series of actions with deliberate intent to achieve goals, through the modification and refinement of hypotheses, objectives, outputs, or outcomes of management actions (Stankey et al. 2005; McLoughlin and Thoms 2015; Kingsford et al. 2017a). This approach is iterative, using monitoring with feedback loops (cf. Pollard et al. 2023) to enable learning for change (Pahl-Wostl 2009; McLoughlin et al. 2021). Learning helps drive the convergence of goals, understanding and expectations, the co-creation of knowledge and a shared understanding of complexity for adapting and enhancing management (Rogers et al. 2013; Nel and Roux 2018; Schoeman et al. 2019). The conditions that create learning opportunities in adaptive resource management are complex but are increasingly gaining attention (Rogers et al. 2013; Roux et al. 2017), largely because of the perceived failure of adaptive management in practice (Pahl-Wostl 2009; Rist et al. 2013; McLoughlin et al. 2020). Adaptive management relies heavily on effectual learning among all relevant stakeholders (Rogers et al. 2000; Pahl-Wostl 2009; Roux et al. 2017). Individuals with their perceptions, experiences, social relations and networks function as the web binding the adaptive system together (Pahl-Wostl 2009; Nel and Roux 2018). Within these networks, meaningful stakeholder participation drives learning within emergent social learning processes (see Reed et al. 2010; Ernst 2019).
There is limited documented evidence of effective application of learning or its challenges in adaptive resource management (cf. Pahl-Wostl et al. 2011a; Rist et al. 2013; Nel and Roux 2018). There is often a deficit in trust and cooperation across institutions and organisations, and ingrained norms of action without reflection obstruct pathways for learning (Pahl-Wostl et al. 2011a; Kingsford et al. 2017a; Nel and Roux 2018). These factors are exacerbated where there are different objectives for the same resource. A context of trust, network building, shared understanding and conflict resolution (Ernst 2019) need to enable (emergent) social learning outcomes for ongoing adaptive and transformative learning in adaptive resource management (Pahl-Wostl 2009; McLoughlin et al. 2021).
The three modes of learning, namely, single-, double- and triple-loop, have stimulated critical thinking in adaptive resource management (cf. Fabricius and Cundill 2014; McLoughlin et al. 2021; van Leeuwen et al. 2024). These learning modes reflect respective increases in time scales for change, including for different management and governance levels, providing direction and stability in social contexts (Pahl-Wostl 2009; Fabricius and Cundill 2014). Single-loop learning incrementally advances action strategies, without questioning underlying assumptions, with ‘technical’ processes continually improving established practices and routines to achieve goals (Pahl-Wostl 2009; McLoughlin et al. 2021). Double-loop learning challenges initial underlying assumptions and requires social learning (Pahl-Wostl 2009; Pahl-Wostl et al. 2011b) including shared cooperation, trust and understanding among stakeholders (Reed et al. 2010; Cundill et al. 2011; McLoughlin et al. 2021). New information goes beyond individuals, providing relational (e.g. improved sense of community), cognitive (e.g. change of perspectives) and technical (e.g. communication skills) dimensions (Muro and Jeffrey 2012). Double-loop learning is normally limited by structural governance and context constraints, for example, regulatory frameworks (Pahl-Wostl 2009; McLoughlin et al. 2021). Triple-loop learning changes such structural constraints (including norms and values), and sometimes the entire governance regime (Pahl-Wostl 2009). This transformation is required because management seeks solutions within the context of structural constraints that influence re-framing potentials.
Learning: managing water for the environment
Managing freshwater resources is complex, with interacting social (including cultural) and biophysical systems (Herrfahrdt-Pahle 2013; R Biggs et al. 2015; Anderson et al. 2019) that challenge traditional centralised, command-and-control water resource strategies (Cilliers 2008; R Biggs et al. 2015; Pahl-Wostl 2015). Command-and-control management assumes that interventions can be optimised and their impact predictable (Pahl-Wostl 2015). Freshwater management also operates at large spatial and temporal scales. Management of water for the environment is a separate but connected component, including legal allocations for the environment. Water for the environment should be monitored and assessed, with evaluation of biophysical and social outcomes (Horne et al. 2017; Anderson et al. 2019; McLoughlin et al. 2020). There are always complex trade-offs between the costs and benefits of releasing different volumes of environmental water, often with limited data on social and biophysical interactions (Webb et al. 2018). Such complex trade-offs are often not well articulated or presented. This makes transparency in management of water for the environment even more important. Adaptive management is well suited to managing water for the environment because it integrates complexity and uncertainty across linked social and ecological systems (Allen and Garmestani 2015; R Biggs et al. 2015). With climate-change impacts, mostly related to changes to frequency and intensity of droughts and floods, there is urgent need for collaboration, learning and ability to adapt and change while managing water for the environment (Pahl-Wostl 2009; McLoughlin et al. 2021).
Adaptive management of water for the environment is implemented in South Africa (e.g. McLoughlin et al. 2011; Pollard et al. 2011; Roux and Foxcroft 2011), Australia (e.g. Kingsford et al. 2011, 2017a; Conallin et al. 2018), Europe (e.g. Pahl-Wostl et al. 2007) and North America (e.g. Cosens and Williams 2012; Susskind et al. 2012). Yet, learning in management of water for the environment, and specifically environmental flows, is novel, typically focused on single-loop learning (Pahl-Wostl et al. 2011b; Schoeman et al. 2019; McLoughlin et al. 2020). Indeed, sustaining the practice of adaptive management, with effectual learning, is challenging, and many obstacles must be overcome, including deficits in trust relations among organisations (Pahl-Wostl et al. 2011b; Nel and Roux 2018). Active involvement of stakeholders and building ownership during decision-making must be pursued to strengthen commitment and promote consensus for achieving agreed outcomes (Pahl-Wostl 2009; Rogers et al. 2013; Nel and Roux 2018). For some wicked problems with diverse stakeholders, sometimes with competing objectives, consensus may not be possible, requiring mechanisms to drive decisions reflected in legislation and policy.
Single-, double- and triple-loop learning are considered explicitly in management of water for the environment in South Africa (e.g. Crocodile River; McLoughlin et al. 2021), Europe (e.g. Hungarian Tisza and the German and Dutch Rhine; Pahl-Wostl et al. 2013) and Australia (e.g. Murray–Darling Basin; Kingsford et al. 2017a; McLoughlin et al. 2020). Feedback for single-loop learning is mandatory during the actual doing (Fabricius and Cundill 2014), over days, weeks, months, annually and sometimes up to 5 years. Feedback for the double-loop mode of learning is usually over longer periods, averaging 5–10 years. The triple-loop mode of learning usually averages every 10–20 years. The latter two learning modes usually involve social and cultural dimensions. Such feedback of information and use of knowledge aids communication among stakeholders, managers, scientists, planners and policymakers, as well as improving trust (Anderson et al. 2019; Ford et al. 2023; Pollard et al. 2023).
There is an increasing need to understand how such learning concepts are realised in practice, within complex social-ecological systems such as river catchments. We constructed a learning approach (hereafter, ‘requisite learning’) for managing water for the environment, tying into classic single-, double- and triple-loop learning theory but waiving the ‘looping’ convention, that is, set time-intervals for the three learning modes (as above), because this is vague, averaged over time. The notation of ‘loops’ remains helpful in theory (cf. van Leeuwen et al. 2024), but difficult in contemplating learning for practice. We base requisite learning on four explicit, co-existing and interdependent learning types (cf. McLoughlin et al. 2021): (1) ‘adjusting routines’, that is, allowing for rapid information feedback to check more immediate operational outputs during management intervention(s). (2) ‘adaptive assessment’, that is, regular auditing against predicted outcomes by using explicit and measurable targets, after management intervention(s). (3) ‘changing practice’, that is, reframing of problems and solutions facilitated by reflection, helps to test achievement of agreed objectives (considering any surprises). Notably, we propose that this learning should be realised whenever the need and opportunity arises, not only every 5–10 years. (4) ‘transforming governance’, that is, responding to shifts in societal values and norms, and objectives, in conjunction with governance arrangements (Folke et al. 2005; Pollard et al. 2023; Roux et al. 2023). There should be ongoing and deliberate progression of this type of learning with time (not every 10–20 years).
Below, we outline this requisite learning for management of water for the environment (Fig. 1), encompassing ‘adjusting routines’, ‘adaptive assessment’ and ‘changing practice’, under an umbrella of ‘transforming governance’. Emergent enabling capacities (social learning, flexible governance arrangements) are emphasised for the latter two learning types, including key indicators for gauging progress. We define flexible (or adaptive) governance after Schultz et al. (2015), where both state and non-state actors are involved in flexible, learning-based collaborations and decision-making processes often at multiple levels. In managing social–ecological systems there is adaptive or flexible co-operation and coordination. In the subsequent section, we focus on a case-study presenting examples of real-world requisite learning, taken from the Macquarie River and Marshes management of water for the environment in Australia’s Murray–Darling Basin.
Requisite learning for effective and successful management of water for the environment. Practice or the ‘doing’ (black line) operates from left-to-right over time. The four windows (A to D) represent a continuum of learning capacity, increasing from left-to-right over time. ‘Adjusting-routines’ learning (white circles) and ‘adaptive-assessment’ learning (hashed circles) are mostly predictable, with regular outcomes over time. ‘Transforming-governance’ learning increases from left-to-right over time, coupled with a progressive and growing flexibility in governance arrangements (darkening shading). Social-learning capacity (green shading) also increases with time, from left-to-right. Therefore, and concurrently, the capacity for ‘changing-practice’ learning builds from left-to-right (thickening line), with rising probability that outcomes (green diamonds) from this learning can occur more frequently (as needed).
This learning process involves on-ground practice (the ‘doing’) where delivery of environmental flows is happening. Learning outcomes are relatively immediate and regular in managing water for the environment (Fig. 1), compared to the other three learning types, recognisable over predictable time intervals (open circles, Fig. 1). Management adjustments usually occur rapidly within a water year during watering events, on the basis of speedy monitoring data providing water operations-related information feedback, to achieve operational objectives. Within ‘adjusting-routines’ learning, information flow and use of knowledge typically occur at the local (e.g. Macquarie Marshes) to regional (e.g. northern Murray–Darling Basin) scale. At this level, key conditions driving this learning include the presence and actions of resourceful and dedicated actors with on-ground technical knowledge, expertise and communication necessary for implementing management of water for the environment. Processes of ‘the doing’ afford focus for ‘adaptive-assessment’ learning (checkered circles, Fig. 1).
This learning process is relatively predictable, compared to ‘changing-practice’ learning and ‘transforming-governance’ learning (below), with regular learning outcomes over time (Fig. 1), usually after collection of monitoring data and the auditing of ecological responses (against targets) to implemented environmental flows (checkered circles Fig. 1). There is an evaluation or estimation of the nature, quality, ability, extent, or significance of events or processes (H Biggs et al. 2011), backed up by rigorous science, building on best available knowledge, including tacit (experiential) and Aboriginal peoples knowledge. ‘Adaptive-assessment’ learning is intrinsic to classic models of adaptive resource management, namely, characteristic cyclic process of ‘plan–act–monitor–evaluate–adapt’ (e.g. Stankey et al. 2005; Allan and Stankey 2009; Williams and Brown 2014). Information flow and use of knowledge typically occur at the local (e.g. Macquarie Marshes) to regional (e.g. northern Murray–Darling Basin) scale. Key actors driving this learning include competent integrators of knowledge, namely, people with sound ecological understanding and analytic skills of the environmental flow–ecosystem-outcomes interface. There must be timely feedback of suitable information to water managers, supporting decisions made about implementing water for the environment. ‘Adaptive-assessment’ learning affords focus for ‘changing-practice’ learning (diamonds, Fig. 1).
This learning process is about reframing complex management problems (Fig. 1), with a change of existing routines in management of water for the environment (diamonds, Fig. 1). It involves a calm, lengthy and intent-driven reflection on problems (H Biggs et al. 2011). Flexible governance arrangements (see below) enable outcomes of this learning type, with stakeholder social learning ideally emerging and increasing with time (Fig. 1). Social learning is an all-encompassing enabler for management of water for the environment, interwoven across flexible governance arrangements (cf. Pollard et al. 2023; Roux et al. 2023), stimulating ‘changing practice’ (Pahl-Wostl 2015). It is a process of negotiation embedded in a specific context, with iterative feedback driving ongoing change (Ison and Watson 2007; Ernst 2019; Pollard et al. 2023). Both ‘technical’ (e.g. improved water operations or ecosystem integrity, see above) and ‘relational’ (e.g. stakeholders achieve consensus by cooperation) qualities must be recognised in management of water for the environment (Pahl-Wostl et al. 2007, 2008). Social learning is fostered across multiple cooperative agencies sharing knowledge (i.e. avoiding silos).
Three key categories of criteria advance stakeholder social learning (McLoughlin et al. 2021). First, preconditions are needed for social learning to emerge, for example, ability to reframe problems, stakeholder representativeness and availability of resources (Mostert et al. 2007). Second, there is an evolving community-of-practice (sensuWenger 1998) to drive social learning, for example, stakeholder networking and interactions, recognition of coordinator, and management support (Pahl-Wostl et al. 2008; Iaquinto et al. 2011). Third, capacities are sustained over time by emergent social learning, for example, trust, collective actions and exchange of ideas (Pahl-Wostl and Hare 2004; Pahl-Wostl et al. 2007; Cundill et al. 2011), often from within a community-of-practice. As capacity for social learning builds (e.g. stakeholder awareness of their interdependence, information sharing, joint problem solving), there is growing ability to exploit key ‘catalysts for change’, namely, real-world happenings (cf. HC Biggs et al. 2017). Catalysts may include the unique mix of resources, skills, personnel, timing of research or monitoring feedback, events (e.g. drought, high flows), and funding at hand. Timing is variable for when the required ‘catalysts for change’ converge for learning and change; thus, this learning type is unpredictable compared with ‘adjusting routines’ and adaptive assessment’. Nonetheless, the capacity to exploit ‘catalysts for change’ must always exist (improving over time), practitioners being prepared for such convergence when it occurs, therefore enabling more frequent change in practice as needed (Fig. 1). ‘Changing-practice’ learning is often essential when current long-term objectives are not achieved as expected, or shifting societal values demand a re-evaluation of existing objectives, or surprises may occur (e.g. large infrequent flood). Further, new technology, expertise or knowledge may become available (e.g. satellite applications), fuelling new rigorous monitoring approaches for improved assessment of newly agreed objectives. With time, these underlying learning processes find new innovative and agreeable ways of doing things when or as needed, changing practice. Such understanding contrasts with usual descriptions of classic ‘double-loop’ learning theory (every 5–10-years).
Conversely, with no significant stakeholder social learning emerging, and minimal flexibility in governance arrangements (see below), existing practices may continue indefinitely (trapped in window A in Fig. 1) albeit adjustments and adaptations are being made with time (open and checked circles respectively in window A in Fig. 1). An unfamiliarity with learning (types, complexity, roles) means lower probability that key ‘catalysts for change’ are recognised and then exploited for change when needed. Outcomes from ‘changing practice’ (diamonds, thickening line across windows B–D in Fig. 1) depend on enlightened, motivated and informed individuals (champions) within and across agencies. Champions grasp learning and its complexity and are adaptable and skilled in integrating information and knowledge while disseminating it in a timely fashion within and across agencies and scales in suitable formats (Roux et al. 2010; Stirzaker et al. 2011). They are alert and ready to exploit any available and pertinent ‘catalyst for change’. The ‘changing-practice’ learning type is often given effect at the regional (e.g. northern Murray–Darling Basin) to state (e.g. New South Wales) scale. It is limited by structural constraints of governance (e.g. Murray–Darling Basin rules and regulations), including societal norms and values. Notably, ‘changing-practice’ learning underscores the critical need for ‘transforming-governance’ learning (darkening shading in Fig. 1).
This learning process bestows an overarching context for application of the three other learning types in management of water for the environment, namely, ‘adjusting routines’, ‘adaptive assessment’ and ‘changing practice’. ‘Transforming governance’ enables governance regimes to absorb any shifts in societal norms or values, and to alter or loosen impeding structural constraints, as governance arrangements become increasingly flexible with time (darkening shading left-to-right Fig. 1). Roux et al. (2023) highlighted four universal principles for realising flexibility in governance arrangements while managing water for the environment; we include them as a process of ‘transforming-governance’ learning, including the pertinent indicators, as follows: polycentric institutions, measured by clarity about roles of diverse actors and joint decision-making with ability to settle conflict; collaboration, measured by a shared understanding of challenges and resolve for working together, and adequate leadership to organise collaborative activities; social learning, measured by existence of explicit learning spaces that support co-learning, and diverse knowledge types that promote co-learning and decisions; and complexity thinking, measured by shared stakeholder mental models, with suitable monitoring and research to advise management. The ‘transforming-governance’ learning type is typical at the state (e.g. New South Wales) to national (e.g. Murray–Darling Basin) and international scale. Actors involved must promote flexible governance arrangements by using their skills and qualities (e.g. political savoir-faire) to influence legislation and policy making (e.g. rationalising irrigation and water for the environment). Importantly, flexible governance arrangements underpin the reframing of management problems thus for applying ‘changing-practice’ learning.
Learning case study: managing water for the environment in the Macquarie River and Marshes
With requisite learning, we aimed to promote learning consciousness in management of water for the environment to contribute toward more effective and successful adaptive management within water-stressed and contested river systems, legislated to deliver environmental flows. We used a case study of the Macquarie River and Macquarie Marshes in Australia’s Murray–Darling Basin (Fig. 2) to illustrate this learning approach. These real-world examples (including future potential learning opportunities) focused on our requisite-learning approach, with global implications for managing water for the environment. We suggest ways for progressively building learning capacities with time. Ultimately, requisite learning accentuates a conscious and more explicit information feedback, improving learning capacity in adaptive management to deliver on water for the environment-related objectives, supporting ecosystem services.
(a) Location of the Macquarie Marshes floodplain (grey), showing variations in inundation frequency over a 10-year period (July 2011–June 2021), the Macquarie River (dark blue line) and Marebone flow gauge (MB, red triangle), Nature Reserve (green) and Ramsar site (hatched). (b) The Macquarie–Castlereagh River Catchment in New South Wales (NSW), with major dams of Burrendong Dam (BD) and Windamere Dam (WD), within (c) the northern portion of the Murray–Darling Basin of south-eastern Australia.
The Macquarie Marshes (hereafter, ‘the Marshes’) (~2200 km2; Thomas et al. 2015) is supplied by the Macquarie River. Flows are regulated by the large Burrendong and Windamere dams (Fig. 2), with small weirs, dams and diversion works on the floodplain upstream of the Marshes being used to divert and store flows and develop floodplains for irrigation (Fig. 2). The Macquarie River also supports regional centres (e.g. Dubbo). The long-term average extraction limit was modelled to be 356.9 GL year−1, shared as water utilities (towns, 19 GL), high-security licences (18 GL), general security licences (632 GL) and supplementary-access licences (50 GL), with modelled floodplain harvesting extraction (41.5 GL). In January 2022, there were estimated to be 174 GL of private storage (on farm dams), used for irrigation extraction (NSW Department of Planning Industry and Environment 2022a).
The New South Wales (NSW) and Commonwealth governments hold and manage 334 GL of general-security environmental water shares in the regulated Macquarie River. General-security water assets in this context receive additional balance related to dam inflows. Governments also hold ’supplementary’ and ‘unregulated’ licences. Additionally, there is planned environmental water in the regulated upper tributary of the Cudgegong River and Macquarie River, which is used to ‘run the river’. Further, various water-access rules for extraction, set by Water Sharing Plans or licence conditions, can contribute to water for the environment.
Ecological values
Approximately 10% of the Marshes are a protected area. The Macquarie Marshes Nature Reserve, with the addition of small private portions of land, is listed as a Wetland of International Importance under the Ramsar Convention (Fig. 2). The area supports a mosaic of diverse flood-dependent vegetation communities characterised by grasslands of reedbeds (Phragmites australis) and water couch (Paspalum distichum), mixed marshes of sedges and rushes, river red gum (Eucalyptus camaldulensis) forests and woodlands, lignum (Duma florulenta) shrublands, and woodlands of coolibah (Eucalyptus coolabah) and black box (Eucalyptus largiflorens) (Thomas and Ocock 2018; Mason et al. 2022). Threatened and iconic animal species include native fish (e.g. Murray cod, Maccullochella peelii; silver perch, Bidyanus bidyanus; and eel-tailed catfish, Tandanus tandanus) and waterbirds (e.g. straw-necked ibis, Threskiornis spinicollis; plumed egret, Ardea plumifera; eastern great egret, Ardea modesta; Australian painted-snipe, Rostratula australis; magpie goose, Anseranas semipalmata; glossy ibis, Plegadis falcinellus) (Department of Planning Industry and Environment 2020). The system is valued for its considerable abundances and diversity of waterbirds (Kingsford and Thomas 1995), including large breeding aggregations of large wading birds (e.g. straw-necked ibis, intermediate egret, Ardea intermedia; eastern great egret, glossy ibis) (Kingsford and Johnson 1998; Kingsford and Auld 2005; Bino et al. 2014).
Governance arrangements
Water in the Macquarie River, including water for the environment, is managed through legislation, strategies, and plans, at state and federal levels. The NSW Water Management Act (2000) is the primary legislative instrument, whereas the Commonwealth Government’s Commonwealth Water Act (2007) provides the framework for managing water resources in the Murray–Darling Basin. The NSW legislation uses Water Sharing Plans to determine water shares and rules of delivery.
For the Macquarie River and Marshes, these legislative instruments provide guiding mechanisms (policies and procedures) for the management of water for the environment. The Water Act 2007 established the Murray–Darling Basin Authority and the Commonwealth Environmental Water Holder (CEWH). The Murray–Darling Basin Authority was charged with developing the Basin Plan (2012) and the Basin-wide Environmental Watering Strategy (Murray–Darling Basin Authority 2014, 2019). The CEWH manages the Australian Government’s environmental water portfolio to protect and restore the environmental values of the Murray–Darling Basin, including a requirement to monitor and evaluate watering outcomes. The Macquarie–Castlereagh Long Term Water Plan (Department of Planning Industry and Environment 2020) gives effect to NSW implementation of the Basin Plan and its Basin-wide Watering Strategy, managing water for environment (Basin and catchment scales) to meet long-term environmental needs. Developed by the NSW Department of Climate Change, Energy, the Environment and Water (DCCEEW) the Long Term Water Plan sets objectives, targets and watering requirements for key plants, waterbirds, fish, frogs and system functions over timeframes of 5, 10 and 20 years (Department of Planning Industry and Environment 2020). The targets are for managing water for the environment by NSW environmental water managers. Short-term (1–3 year) decisions and strategies about environmental water use are prepared locally by environmental water managers in consultation with the community-government committee, Environmental Water Advisory Group (EWAG). Annual environmental water priorities are published for the Macquarie River and Marshes, reflecting legislative and policy commitments. Delivery of water for the environment is monitored and evaluated by NSW and Commonwealth agencies, partnering with research institutions.
Requisite learning
We identified experiences within the Macquarie River and Marshes management of water for the environment, categorised into the four learning types (‘adjusting routines’, ‘adaptive assessment’, ‘changing practice’ and ‘transforming governance’; Fig. 1). Information examples were sourced from journal articles, research or technical reports, internal government agency documents, and personal participation. Importantly, gaps or future (potential) ‘adjusting-routines’, ‘adaptive-assessment’, ‘changing-practice’ and ‘transforming-governance’ opportunities were included, as adaptive resource management is ongoing and evolving (Allan and Stankey 2009). We did not focus on effectiveness of adaptive management of water for the environment in the Macquarie River and Marshes, and excluded in-depth examination of the mechanisms, enablers (e.g. social learning, governance arrangements) or obstacles (e.g. organisational capacity). Any program managing water for the environment will have its idiosyncratic characteristics influencing learning application, requiring more focused examination.
The basis for this predictable learning process is the Annual Environmental Water Plan (AEWP), derived each year using all potential environmental water sources, anticipating a range of weather and future water-availability scenarios and watering targets for specific ecological aims (Fig. 3). The AEWPs provide critical context for environmental water activities (1 July to 30 June, in the ‘water year’). Implemented watering events may be adjusted during watering operations on the basis of real-time monitoring and feedback of information (e.g. inundation extent not being achieved; dotted arrow, Fig. 3). Furthermore, additional water may become available in the current year (e.g. tributary flows), sometimes triggering a rapid analysis with monitoring and information feedback to the EWAG, with potential for revising watering objectives (dashed arrow, Fig. 3). Water management operations may be adjusted (conditionally on current AEWP priorities being met) to meet revised objectives in the current water year, including stimulating and maintaining waterbird breeding.
Process of planning and delivery of water for the environment for the Macquarie River and Marshes. This begins with decisions on an annual environmental water plan, presented to the Environmental Water Advisory Group (EWAG) for endorsement. Delivery of water for the environment considers environmental conditions, availability of water in water accounts, including predictions of future availability (double-lined arrow). Environmental outcomes are monitored, evaluated and reported on to inform water delivery and annual environmental water plan. Adjustments to implemented flows may be made during watering events if required (dotted arrow), whereas subsequent environmental water-availability determinations may be updated, informed by information feedback on water availability (dashed arrow). Information from operational monitoring and evaluation of each year’s watering events is also used to inform investigation into longer-term ecological responses to environmental-flow implementation (thick solid arrow; see below).
The process of adjusting routines was exemplified by the challenges of managing water for the environment during the record 3-year drought of 2017–2019. The regulated flow in the Macquarie River, below Warren, was cut for the first period since the commencement of Burrendong Dam regulated flows in 1969, owing to critical water shortages. All remaining general-security water balances, including managed environmental water, were quarantined as of 1 July 2019. The significant impacts to the regulated river demanded a focus on drought recovery, described within a 3-year 2020–2023 strategy (NSW Department of Planning Industry and Environment 2021). The following two targeted objectives were co-designed and supported by the EWAG for August 2020: recruitment of native fish, flow generalist (e.g. Australian smelt, Retropinna semoni) and flow-pulse specialist (e.g. golden perch, Macquaria ambigua) species, and retaining environmental water in the dam where it could be carried over to subsequent years to support core wetland vegetation of the Marshes. This resulted in 150 GL of water for the environment (licensed) and 50 GL of environmental flow (licensed) carried over. By supporting the vegetation of the Marshes, the system ‘event-readiness’ would be improved for the large-scale breeding of waterbirds (ibis and egret species) and recruitment of native fish (NSW Department of Planning Industry and Environment 2021).
The scenario of record drought (also record floods) is not explicitly reflected in normal planning scenarios, requiring water managers to rapidly recalibrate objectives and actions on the basis of real-time monitoring feedback (dashed arrow, Fig. 3). Unanticipated catchment rainfall throughout 2020 returned river flows to the Macquarie River, and Burrendong Dam inflows restored access to quarantined balances, including the water for the environment licences. Subsequent adjustment to environmental flow delivery led to successful waterbird breeding, observed over the summers of 2021–2022 and 2022–2023, with sufficient water available for nest building, incubation and fledging of young (Brandis et al. 2022, 2023). Significant rainfall persisted until February 2023, with further spilling of Burrendong Dam. Further actions to provide waterbird habitat in subsequent years may assist with recruitment of the young birds into the breeding population (Kingsford et al. 2017b).
Objectives under the Long Term Water Plan (LTWP) set out what is to be achieved to maintain or restore priority components of water-dependent ecosystems, including flows and connectivity, vegetation, fish, waterbirds, flow-dependent frogs, and ecosystem functions (Fig. 4). The targets are quantitative measures of the desired outcomes expected every 5 years since plan implementation. Targets are developed from baseline assessments of indicators (metrics, long-term data) under a long-term ecological monitoring program (Department of Planning and Environment 2023).
Cycle of ecological assessments at annual and 5-yearly time steps for the Macquarie River and Marshes. Annual assessment of regularly monitored ecological indicators aims to determine progress towards meeting the Long Term Water Plan (LTWP) targets, and to inform the following year’s annual water-planning cycle (dotted arrow). Five-yearly evaluations use the monitored ecological indicator data to evaluate expected outcomes every 5 years (Matter 8), reporting to the Murray–Darling Basin Authority. Monitored data are used to develop or improve flow–ecology relationships for potentially adapting the generated environmental water requirements (EWR, long dashed arrow). The 5-yearly assessments contribute to re-assessment and updating of the LTWP (short dashed arrow).
Indicators have been identified for long-term monitoring, to assess ecosystem flux and progress in achieving targets and related objectives (Fig. 4). Monitoring data collection (frequency, timing) is based on indicator responsiveness to flow regime over time. For example, metrics include environmental water requirements, using flow gauges across the catchment; inundation extent and frequency, using 5–10 day satellite observations in conjunction with historical trends (1988 onwards, see Fig. 2); waterbird species richness or abundance and breeding activity, monitored annually (aerial waterbird survey) led by University of New South Wales, Sydney (Kingsford et al. 2020a), and complemented by the DCCEEW waterbird ground surveys (J. Spencer, unpubl. data). Each LTWP objective will undergo assessment, annually and every 5 years, with evaluation of target achievement informing annual and long-term water strategy and planning (Fig. 4), while reporting across required government frameworks.
Annual assessment determines the status of each indicator in relation to predictions of targets under conditions of the reporting year. For example, flows measured from stream gauges are assessed against the set flow component parameters (e.g. threshold, duration, season, frequency) that define the environmental water requirements, to be routinely analysed using an internal DCCEEW data-based dashboard. This dashboard will be used to inform the following year of annual water planning (dotted arrow, Fig. 4). Inundation-regime indicators include assessments of inundation extent within vegetation communities each year and will be compared with annual predictions and 10-year inundation requirements for vegetation communities (dotted arrow, Fig. 4). For waterbirds, indicators of species richness and abundance will be assessed against predictions for the year (dotted arrow, Fig. 4).
Assessment every 5 years evaluates achievement of ecological outcomes to determine whether LTWP objectives are met (jurisdictional reporting to Murray–Darling Basin Authority every 5 years, ‘Matter 8’) (NSW Department of Planning, Industry and Environment, Department of Regional NSW 2020, Fig. 4). Indicator status can be determined by comparing set targets against historical timeseries data, accounting for variability. Assessment of long-term data trends promotes understanding about likely indicator trajectories, increasing learning about how to achieve targets. Questions can be asked if there is non-delivery of environmental water requirements, informing any adaptions to water delivery for the environment or re-assessing the environmental water requirements (long dashed arrow, Fig. 4), or options to adapt indicators themselves (short dashed arrow, Fig. 4), largely owing to climate change-related uncertainty. Over time, new understanding of patterns of ecological response to flow drivers should emerge, improving delivery of water for the environment, requiring updates to the LTWP (short dashed arrow, Fig. 4). Critically, learning should improve water-management operations over time, to successfully maintain or restore water-dependent ecosystems.
At the Murray–Darling Basin level, there is impetus for Basin governments, communities and change makers to work together, to protect or restore ecological values of the Murray–Darling Basin Plan while ensuring sustainable sharing of the water resource among users (Murray–Darling Basin Authority 2020). A process of reflection resulted in identification of several priority areas, including climate challenges, and adaptation and resilience, enabling social or economic outcomes (including that of Aboriginal peoples), integrating water management with other activities for environmental restoration, and enhancing science or monitoring (Murray–Darling Basin Authority 2020). Furthermore, CEWH monitoring and evaluation processes under the Long Term Intervention Monitoring Project and the Environmental Water Knowledge and Research Project (2014–2019) were reframed into a single program (July 2019–June 2022) becoming the Flow-MER program (to June 2024, and beyond). Importantly, for the first time, the Macquarie River and Marshes were identified as a selected area for a 5-year monitoring program. The new program committed to increased flexibility for responsive monitoring, more emphasis on communication and engagement, and research (area-scale) guiding operational management decision-making on water use (Department of Climate Change, Energy, the Environment and Water 2023). Such change will promote processes of adaptive-assessment learning.
At the state-program level, the current NSW Government’s Environmental Water Management Program evolved over time. It was reflected on as a discrete program for the 2006–2013 period in terms of the program’s key activities, its progress towards meeting program objectives, and community involvement through EWAGs (NSW Office of Environment and Heritage 2015). Recommendations were made to improve the program, with implementation of these recommendations a focus of the 2014–2019 program evaluation (Artd Consultants 2021). This reflection process included document reviews, field visits, stakeholder surveys, and staff or stakeholder interviews (Artd Consultants 2021). There was progression from simple purchasing and water entitlement delivery to a complex system of robust monitoring, evaluation, and reporting, with improved agency partnerships, relationships, and administrative structures. Additionally, EWAGs were highly regarded by most communities. Strong effective relationships with water managers and operators allow the EWAG to effectively advise on planning and implementation of watering events. With the newly implemented Macquarie–Castlereagh LTWP (Basin Plan policy framework) (Department of Planning Industry and Environment 2020), which includes the Macquarie River and Marshes, recommendations include providing evidence for ecosystem responses to delivery of water for the environment, using robust systems. A situation that is likely to enable adaptive-assessment learning.
Another reflection and learning by the NSW Government relates to the method for assessing water-resource availability in catchments. Since 2003, the Burrendong Dam has nearly emptied several times, including during the 2018–2020 drought when there was no water available for the third year of the Macquarie River and Marshes 3-year water plan (affecting water managers and irrigators). A major driver of such water scarcity relates to the ‘allocation’ or estimate of water availability in the Macquarie catchment, entering Burrendong Dam, based on predictions from past climate (before 2004), described as the ‘credit’ model (Steinfeld et al. 2020). Clearly, this is problematic if climate change results in a drier period than predicted from past data. The following three changes to practice were considered: (1) water-resource assessments to include all rainfall and river-flow conditions (i.e. not just prior to 2004); (2) excluding ‘anticipated future inflows’ in allocations; and (3) reducing water planning to 2 years, thus decreasing risk of no water availability in Year 3. The first two options would result in lower water allocations for irrigated agriculture and environmental use, at least until the allocation system adjusted to the changed practice. The third option was implemented (NSW Department of Planning Industry and Environment 2022b), although this may not be optimal for the delivery of water for the environment, thus requiring future reflection.
Changing societal values in Australia (since 1990s) acknowledges ecologically sustainable management of Murray–Darling Basin’s freshwater resources, with greater economic efficiency and stakeholder involvement. This change coincides with major paradigm shifts in freshwater management worldwide (Holling and Meffe 1996; Pahl-Wostl et al. 2007; Herrfahrdt-Pahle 2013). Traditional technocratic (command-and-control) strategies focusing on water-resource development (economic or engineered rivers) are being replaced by sustainable management, incorporating complex coupled human and ecological systems (Holling 2001; R Biggs et al. 2015). Early water reforms in Australia introduced the National Principles for the Provision of Water for Ecosystems, including water rights and requirements for the environment. Taking a more central role, the Commonwealth government introduced the National Water Initiative (Fisher 2007), an intergovernmental agreement for developing integrated water-resource management plans (Marshall et al. 2013). The Commonwealth Water Act 2007 provided increased oversight and returning environmental flows to the Murray–Darling Basin rivers, within a sustainable management framework (Basin Plan). There was also a commitment to have flexible governance arrangements, with an emphasis on managing water for the environment. Environmental water is managed within and across three governance levels (local agencies, states, Commonwealth government). Active delivery of environmental water (real time) is planned and prioritised at the Basin, state, and Water Resource Plan Area (e.g. Macquarie–Castlereagh) levels (Murray–Darling Basin Authority 2014). Adaptive management allows for various triggers to be responded to, including any water adjustment that might be made to the sustainable diversion limits (McLoughlin et al. 2020).
Preparation of a Water Management Plan (1986) for the Marshes was a significant governance transformation associated with NSW management of water for the environment. It occurred after an environmental water-entitlement increase (18,500–50,000 ML after 1980) construed by local and regional actors and influential political figures (NSW Environment Minister and Water Minister). Research investigating relationships between flows and waterbird breeding (1986–1996; Kingsford and Thomas 1995) played a central role in the Macquarie Marshes Water Management Plan of 1996, with increased environmental water entitlement (50,000–125,000 ML) and establishment of the EWAG (statutory requirement in Water Sharing Plans). This change was enabled by important local and regional actors, plus political figures (NSW Premier, Water Minister and Environment Minister), and Chief Executive Officers of key organisations.
In the early 2010s, a novel strategic adaptive management (SAM) approach for managing the Macquarie Marshes Nature Reserve was proposed (Kingsford et al. 2011). This included key aspects of stakeholder engagement and institutional responsibilities to augment the existing Macquarie Marshes Nature Reserve Plan of Management (NSW National Parks and Wildlife Service 1993) (National Parks and Wildlife Act 1974). During the 1980s, the Department of Water Resources had explored adaptive environmental assessment and management for managing the Marshes (Gilmour and Geering 1991; D. Geering, A. Brady and H. Cross, unpubl. data), although with limited success largely owing to institutional and social factors dominating management at the time (Johnson 2005). Subsequent reflection and review processes underscored increasing concern about the Marshes’ ecological state, with formal water plans (1986 and 1996) progressively recognising degradation by river regulation and water diversions upstream of the Marshes (Kingsford and Thomas 1995; Fazey et al. 2006). With decreasing quality and quantity of wetland values owing to drought or long-term impacts altering system hydrology (diminished flood frequency, duration, extent; Kingsford and Thomas 1995; Ren et al. 2010; Ren and Kingsford 2011), these plans were instrumental in arresting mounting water-resource development (Kingsford et al. 2011). As a clear transparent process, SAM is envisaged to guide management by improving linkages among values, objectives, management actions, research, monitoring, evaluation, learning and change.
Strategic adaptive management can be applied using a step-by-step process (see Kingsford et al. 2011; Roux and Foxcroft 2011), reviewed and updated regularly to reflect changes in wetland system, understanding and shifting priorities (Kingsford et al. 2011, 2017a). The key management agency for managing water for the environment is the NSW environment agency, which is responsible for the Marshes and its environmental flows. Complexity remains high, with involvement of many government agencies and stakeholders, whereas the adaptive management-planning framework of the Macquarie Marshes Nature Reserve Plan of Management is outdated (Kingsford et al. 2017a). In response to the Millennium drought, an interagency initiative of the wetland recovery program compiled all available material to identify assets and water requirements. This became the Macquarie Marshes Adaptive Management Plan (NSW Department of Environment, Climate Change and Water 2010), but without requisite detailed objectives and learning processes. In 2015, the agency made a commitment to adaptive management in a position statement released in that year, but full development of SAM did not occur. Although communication remains strong, linkages between scientific effort and active management could be improved, with rigorous monitoring to inform objectives (e.g. inundation extent as a surrogate of wetland persistence, Thomas et al. 2015; frog breeding responses to wetland inundation extent and duration, Ocock et al. 2024). There is also a need to identify and link other related management responsibilities, such as floodplain management (e.g. floodplain earthworks; Steinfeld and Kingsford 2013). As with all ecosystems, there remains a need to increase transparency and accountability in management of the Marshes, supported by scientific evidence (Lindenmayer et al. 2011). This needs concerted commitment to adaptive resource management, within environmental water policy, planning, governance and implementation (Kingsford et al. 2017a).
Application of the SAM approach in different landscapes began in the early 2020s, for the Lake Eyre Basin rivers (Kingsford et al. 2021), native mammal restoration (Kingsford et al. 2020b), and the Lachlan Valley management of water for the environment, and potential persists for SAM application in the Marshes. For the Marshes, many of the key elements remain in relation to explicit specification of the Macquarie–Castlereagh Long Term Water Plan (Department of Planning Industry and Environment 2020). Further, environmental Monitoring, Evaluation and Reporting Strategy/Implementation for the NSW environment agency requires increased commitment to adaptive resource management (Department of Planning Industry and Environment – Biodiversity and Conservation 2019). Critically, ‘transforming governance’ is needed, for assimilating adaptive management frameworks for complex socio-ecological systems, such as rivers and wetlands including for environmental flows (Kingsford et al. 2017a). Blockages to effective management can be resolved by integrating across institutions, fostering co-learning, supporting explicit decision-making and effective integration of science, learning-by-doing, and enhancing morale (Kingsford et al. 2011). This requires ongoing learning incorporating ‘adjusting routines’, ‘adaptive assessment’, ‘changing practice’ and ‘transforming governance’.
Discussion
Managing water for the environment is complex, and this needs to be better understood and incorporated in management processes (McLoughlin et al. 2020). Managers and stakeholders frequently navigate this complexity, with limited resources, including readily available data (Schoeman et al. 2019). Globally, decisions in management of water for the environment should be informed by iterative learning (Pahl-Wostl 2009; Pahl-Wostl et al. 2013), through ‘adjusting routines’, ‘adaptive assessment’, ‘changing practice’ and ‘transforming governance’. There is also increasing uncertainty in relation to the effects of climate change (Pittock and Finlayson 2011; Xi et al. 2021). Effective and successful adaptive management of water for the environment requires freshwater managers and stakeholders to position themselves within this complex system of information flow, allowing learning to drive improved processes to achieve objectives and outcomes (McLoughlin et al. 2020). It is important to avoid potentially perverse consequences in management of water for the environment, where command and control processes, inadequately informed, are without necessary transparency, learning and flexible governance. Complexity cannot be simplified by entrenched linear and reductionist thinking, because this limits and traps management in the learning types of ‘adjusting routines’ and ‘adaptive assessment’ (McLoughlin et al. 2020). In the Murray–Darling Basin, published accounts of adaptive management generally favour ‘adjusting routines’ and ‘adaptive assessment’, reflected in planning, reporting and monitoring of environmental flows (Allan and Watts 2018; Schoeman et al. 2019). ‘Changing practice’ and ‘transforming governance’ (across governance levels cf. McLoughlin et al. 2020) are often inexplicit and less deliberate (sometimes sacrificed), thwarting meaningful evolution of adaptive management of water for the environment (McLoughlin et al. 2020). This appears true for the Macquarie River and Marshes over multiple decades, although all types of learning are present. Some learning is driving positive change in the management of water for the environment in the Macquarie River and Marshes.
The evolving Macquarie River and Marshes adaptive management system has major strength in its actual practice (the ‘doing’) and assessment, progress with regular adjustments and adaptations made to existing management routines. Importantly, more stakeholders understand the complexities and the importance of decisions about water for the environment. For example, within a water year, adjusting watering operations occurs, when there is increasing catchment rainfall, targeting unanticipated ecological components (‘adjusting routines’, Fig. 3). Furthermore, environmental water requirements can be assessed and adapted, as new knowledge emerges about flow-ecological responses (‘adaptive assessment’, Fig. 4). Key obstacles to this learning remain (requiring further investigation), including limited organisational capacity, physical constraints and inadequate monitoring with insufficient data for feedback of information.
Reflection, resulting in ‘changing-practice’ learning outcomes, is typical every 5–10 years, after appraising formal planning documents. This includes reframing of LTWP-related strategies for maintaining and improving riverine and floodplain long-term health, for effective delivery of water for the environment to the Macquarie River and Marshes. Questions have been raised about feasible changes to water-allocation processes after the regulated Macquarie River dried up in 2019, possibly made worse when calculated predictions of run-off into the dams were not realised, exacerbated by climate change (Steinfeld et al. 2020). This resulted in the quarantining of all general-security account balances in the 2019–2020 water year, including 103 GL of environmental licenced water. Importantly, ‘changing-practice’ learning needs to occur as opportunity and need arise, exploiting ‘catalysts for change’, rather than only rigidly every 5–10 years with plan appraisals. Certainly, there are major obstacles to this type of learning, including inflexible governance arrangements (e.g. learning processes might occur, but required change outcomes are impossible because of power relations and ingrained rules and regulations), inadequate collection of response data to inform reflection processes, and unacknowledged conflicts of interest. Thus, the Macquarie River and Marshes adaptive management system requires more capacity for social learning, for example, exploring diverse knowledge types (cf. Fazey et al. 2006) to support co-learning and decisions, and further, in the building of flexible governance arrangements, while making use of mental-model analyses to foster stakeholder complexity thinking (Roux et al. 2023).
Indeed, ‘transforming governance’ shapes the overarching context (past, present and future), including legislation, governance arrangements and planning, allowing for adaptive management of water for the environment (Gunderson 2015). This is exemplified by policies for broader stakeholder collaboration and deliberation, with consensus being reached for reforming approaches, identified under the Murray–Darling Basin Plan (conceding many challenges with implementation). Water management-related crises are the main stimulus for ‘transforming governance’ (values, norms and governance arrangements), exacerbated in the past by increasing over-allocation of licensed water (1990s) and severity of the Millenium Drought (2000s). Importantly, increasing flexibility in governance arrangements, coupled with ‘transforming-governance’ learning, needs to be an ongoing progressive endeavour, rather than just reacting to crises. There are obstacles to this type of learning, including lack of political will, vested interests (e.g. actors not articulating competing objectives), challenges in implementing legislation (e.g. excluding key flow records in water accounting), and institutional inertia. Further, top-down and bottom-up cascading of information and knowledge across hierarchical governance levels (e.g. in Murray–Darling Basin local agencies, states and Commonwealth government) adds additional complexity, influencing learning (see McLoughlin et al. 2020). Investigation into, and building additional capacity for, flexible governance arrangements and social learning are essential for overcoming many of the obstacles.
Implementation of water-related legislation, policy and management is imperfect, requiring ongoing and evolving learning during management of water for the environment for the Macquarie River and Marshes. There is a need to increase the capacity for decision-making by providing quantitative ecological outcomes from scenarios of managing water for the environment (‘adaptive assessment’). This demands decisions that are not just within the context of the current water year, but also subsequent years, because licensed environmental water can be carried over or held in the dam, where it could also be lost. This paper has highlighted two critical capacities that require ongoing improvement, namely, stakeholder social learning and flexible-governance arrangements, without which overcoming constraints and obstacles to learning and actual change remains difficult. Increasing flexibility in governance arrangements for SAM (‘transforming governance’) is important for potentially grappling with such challenges. There is an obligation to continue to examine capacities and obstacles to this learning in management of water for the environment in the Macquarie River and Marshes.
Implications: managing water for the environment
Ideally, over time, we should strive towards highly flexible governance arrangements coupled with ‘transforming governance’; including substantial stakeholder social-learning capacity for ‘changing practice’ when needed; and adequate motivation, and scientific, tacit or traditional knowledge and technical skills for ‘adaptive assessment’ and running and ‘adjusting routines’ (the ‘doing’) most efficiently (window D, Fig. 1). Practically, many challenges stand in the way of this ‘ideal’. Ultimately, there is considerable complexity of information flow and use of knowledge across often rigid governance institutions (cf. Pahl-Wostl et al. 2013; Pollard et al. 2023; Roux et al. 2023), across scales (cf. McLoughlin et al. 2020), and, concurrently, among many different people, program components and processes (cf. McLoughlin and Thoms 2015; Ford et al. 2023). Climate-change impacts on freshwater systems are contributing considerable complexity and uncertainty, including diminishing available resources (Pittock and Finlayson 2011). These factors contribute to perceived failures and lack of reported evidence for effective applications of learning in adaptive resource management.
Management of water for the environment programs, anywhere in the world, are on the continuum of learning capacity (within windows A, B, C or D, Fig. 1), dependent on flexibility of different governance arrangements and stakeholder social learning. We advocate for learning as an ongoing endeavour, with improved understanding and applying requisite learning to foster enabling conditions (social-learning and flexible-governance arrangements) deliberately but progressively with time, maturing along the learning continuum (Fig. 1). Such learning optimises ‘catalysts for change’ which can effectively transform governance, promoting change in management to deliver improved outcomes. Further with climate change-related uncertainty, there is an urgency to improve learning processes and outcomes in managing water for the environment. We recommend four (practical) actions related to learning to improve management of water for the environment (i.e. progressing left-to-right in Fig. 1).
There is a need to test and implement effective adaptive management of water for the environment, which promotes learning. For example, SAM (see above) has explicit, conscious learning processes with feedback of information. Importantly, it can also provide commitment and resources required for learning and adaptive management, to improve transparency and accountability by the agencies involved. Further, review existing governance arrangements, and strive to make governance arrangements more flexible, to promote actual change with learning (cf. van Leeuwen et al. 2024). Identify and measure suitable indicators, such as stakeholders’ shared understanding and explicit learning spaces, leadership, and connectedness of decision-makers (Roux et al. 2023), which can guide the process of increasing governance flexibility.
New information is essential for learning. This can come from targeted monitoring, informing on progress of indicators towards targets, and therefore efficacy of management. Further, research may focus on understanding cause and effect relationships that inform management of water for the environment. Requisite learning can also guide future research. For example, this could target different management scenarios, but also focus on social enablers and obstacles for applying the range of four learning types.
Increase understanding and use of ongoing learning across policy, planning and evaluation of programs managing water for the environment. This can be undertaken by explicitly referencing learning in documentation and processes. Recognise that ‘changing-practice’ learning, linked to ‘transforming-governance’ learning, is difficult to achieve without social learning (Pahl-Wostl et al. 2011b; Fabricius and Cundill 2014), because effective social learning subjugates many of the obstacles and challenges. Success results from ongoing learning and negotiation through communication within trusted networks, perspective sharing and building of adaptive group strategies (Huxham and Vangen 2000; Pahl-Wostl and Hare 2004). Conduct action research to build social-learning capacities (see above). Action research is a flexible methodology, permitting action (change, improvement) and research (understanding, knowledge) to be achieved concurrently, while involving people affected by the change (Pollard and du Toit 2011). Further, develop communities-of-practice, and elicit stakeholder mental models (see H Biggs et al. 2008; Lynam et al. 2012; Moon and Adams 2016). Mental model analyses make explicit the implicit assumptions individuals hold and how they understand a managed system (Adams et al. 2018) and may offer insights into how learning transpires and proceeds over time (cf. D Biggs et al. 2011). Overall, feedback and learning must be resourced and implemented as part of a monitoring process that integrates and promotes social relations in management of water for the environment (cf. Anderson et al. 2019). Hence, include social researchers in traditionally scientific monitoring and evaluation programs (Rogers et al. 2013; McLoughlin et al. 2020).
Recruit enthusiastic people with expertise and skills to foster and encourage learning across different governance levels. These champions promote a situational awareness of practitioners’ learning spheres and learning practice (McLoughlin et al. 2020), relative to the complexity that is present in adaptive management of water for the environment. For example, they motivate and guide networked stakeholders, while coordinating, integrating and sharing information with sensible use of knowledge (cf. Stirzaker et al. 2011). Champions help stakeholders become better at dealing with complex management problems, open to experimentation while considering different approaches (Pahl-Wostl 2009). They act as the glue binding the adaptive system together, without which it can stumble (McLoughlin and Thoms 2015; Nel and Roux 2018). Learning roles and responsibilities across governance levels must be explicitly clarified in management of water for the environment.
Conclusions
We have focused on the learning dimension of managing water for the environment and its importance for delivering environmental outcomes. We encourage ongoing and conscious improvement in the learning capacity (social learning and flexibility in governance arrangements) of environmental water managers, stakeholder advisory groups and policy makers, likely delivering major benefits. This means management not just responding immediately, as in seasonal time steps, or reacting to crises or conventional plan appraisals, but also considering long-term consequences of flexible governance and adaptive management of water for the environment. ‘Conscious’ learning can improve management by explicitly questioning effectiveness of current (and predicted) processes and their delivery of desired outcomes.
Requisite learning recognises the importance of having flexible governance arrangements in adaptive resource management (Folke et al. 2005; Pollard et al. 2023; Roux et al. 2023). It integrates timeframes and governance seamlessly into learning processes for more explicit and intentional practice, ‘adjusting routines’, ‘adaptive assessment’ and ‘changing practice’ (purposefully enabled by social learning) linked to ‘transforming governance’ (ongoing progression of flexibility in governance arrangements). In turn, social learning and flexible governance arrangements are expedited by feedback of information and use of knowledge, iteratively across stakeholder communities-of-practice (Pollard et al. 2023), in networks applying the four learning types. Requisite learning is important for managing freshwater in complex social ecological systems, where there is a need for decision-makers to learn and act along with their advisory groups. Employing our practical recommendations for incorporating these four interdependent types of learning, recognising short, medium and long-term outcomes, can improve management of water for the environment, through deliberate shaping of governance and management approaches to achieve agreed objectives.
Data availability
Data sharing is not applicable as no new data were generated or analysed during this study.
Declaration of funding
This work was financially supported through the NSW Water for the Environment Program of the NSW Department of Climate Change, Energy, the Environment and Water; and Australian Research Council (ARC) Linkage number LP180100159.
Acknowledgements
The authors thank the UNSW Centre for Ecosystem Science and the ARC for supporting this study.
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