Learning from concurrent adaptive management in multiple catchments within a large environmental flows program in Australia

Abstract

Adaptive management is central to improving outcomes of environmental water delivery. The Australian Government's Murray−Darling Basin (MDB) Plan 2012 explicitly states that adaptive management should be applied in the planning, prioritisation and use of environmental water. A Long Term Intervention Monitoring (LTIM) program was established in 2014 to evaluate responses to environmental water delivery for seven Areas within the MDB, with evaluation also undertaken at the Basin scale. Adaptive management at the Area scale was assessed using two approaches: (a) through a reflective exercise undertaken by researchers, water managers and community members and (b) through an independent review and evaluation of the program, where relevant reports were reviewed and managers and researchers involved in the LTIM program were interviewed. Both assessment approaches revealed that the scale of management actions influenced the extent to which learnings were incorporated into subsequent actions. Although there were many examples where learnings within an Area had been used to adaptively manage subsequent environmental water deliveries within that Area, there was inconsistent documentation of the processes for incorporating learnings into decision making. Although this likely limited the sharing of learnings, there were also examples where learnings from one Area had influenced environmental water management inanother, suggesting that sharing between concurrent projects can increase learning.The two assessments identified ways to improve and systematically document the adaptive management learnings. With improved processes to increase reflection, documentation and sharing of learnings across projects, there is an opportunity to improve management of environmental water and ecosystem outcomes. K E Y W O R D S adaptive management, decision-making, environmental water, monitoring and evaluation, Murray−Darling Basin, social learning, uncertainty

Riverine landscapes, water resource development and management: A view from downunder

“…The final two manuscripts of this special issue consider adaptive management from different perspectives. Watts et al, (2020) use the Long‐Term Intervention Monitoring program of the Murray Darling Basin (cf. Gawne et al, 2020) as an example to highlight learnings from environmental water delivery and show how to manage environmental water deliveries, adaptively, within the Basin at a number of scales.…”

A trickle, not a flood: environmental watering in the Murray–Darling Basin, Australia

“…The Plan has regularly been claimed as an example of adaptive management in practice (Murray-Darling Basin Authority 2017; Watts et al 2020;Gawne et al 2020). However, the current Basin-scale monitoring and evaluation program is limited in extent and lacks an ecologically defensible methodology for upscaling to whole-of-Basin reporting.…”

“…The plethora of environmental watering arrangements has led to a complex, rules-based culture of decision making, monitoring and reporting. The Plan has been presented as an exercise in adaptive management (Murray-Darling Basin Authority 2017; Watts et al 2020;Gawne et al 2020). But it remains unclear how lessons learned can be integrated into the Plan outside its rigid rules and timelines: the Plan is subject to 5yearly review and is due to be fully operational in 2024.…”

Ten principles for achieving scientific impact with integrity in policy and management

“…Many researchers work with water managers in planning, delivering, and monitoring the effects of individual flow events, and provide management recommendations to inform future flow actions; however, they usually remain relatively distant from policy issues. Scientists in this role function to some extent as 'pure scientists' (Table 1) collecting and reporting data to support adaptive management (Allan and Watts 2017;Watts et al 2020). Because of the uncertainty and the need for timely advice, these scientists also provide advice based on previous experience, and therefore occupy the roles of 'trusted advisor' and 'knowledge broker' in a management context.…”

“…opinions and falsehoods will have a greater influence than verifiable facts or the 'best available science"' (Grafton et al 2020). This was due in part to a failure of commentators to engage with the monitoring data, even though the results were available publicly and summarised for both scientific and more general audiences (Webb et al 2018;Watts et al 2020). The ensuing public discussion was critical of the Basin Plan, but largely overlooked the available monitoring data and conclusions.…”