معیارهای عملکرد مبتنی بر انعطاف پذیری برای مدیریت منابع آب تحت عدم اطمینان Resilience-based performance metrics for water resources management under uncertainty

1 Introduction Multiple modern decision-making methodologies are currently being trialled for application to water resources management (WRM) adaptation planning under deep uncertainty; however, the output results from these ‘adaptation investigations’ can be highly dependent on the performance metrics employed. Terms such as ‘robustness’ or ‘flexibility’ are typically used to define the performance or ‘pliability’ of a water system or adaptation strategy across a broad range of future conditions or scenarios (Groves et al., 2008; Maier et al., 2016; Matrosov et al., 2013; Moody and Brown, 2013; Smit et al., 2000); however, it is the performance metrics (or criteria/indicators) that will define the performance of a water system to a single future scenario or set of conditions. Despite the widening range of decision-making approaches under development, the outputs from these methods are highly dependent on how the water resource system performance itself is evaluated. For example, how to define the assessment metrics applied to quantify the performance of a water system to a given future scenario and how this performance can vary over the range of potential futures/uncertainties. It’s within these more practical engineering features that a wider knowledge gap is often over looked. The more well-known performance metrics often cited within WRM literature are those of Hashimoto et al. (1982) who were among the first to propose the use of the terms; reliability, vulnerability and resilience for water resource system performance evaluation. These performance criteria, in general, refer to how likely a system is to fail (its reliability), how severe the consequences of failure might be (its vulnerability) and how quickly it can bounce back, which is the recovery from a failure (its resilience). The term resilience has gathered particular traction in recent studies, with the general agreement that ‘resilience’ as a concept for WRM, should go beyond its original ‘Hashimoto’ definition. Walker and Salt (2006) are advocates for the idea of ‘resilience thinking’, which ventures beyond the concepts of optimization to believed ‘knowns’ but instead fosters the capacity to look at social-ecological systems as a whole and incorporate diverse approaches to increase resilience to both expected and unexpected disturbances. This resilience thinking was applied in Seekell et al. (2017) as an indicator-based analysis to compare the sustainability of global food systems. It was found that very few countries performed high or low for all indicators, emphasizing the complexity of system dynamics and the varied information provided by different metrics.