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The development and application of evolutionary algorithms (EAs) and other metaheuristics for the optimisation of water resources systems has been an active research field for over two decades. Research to date has emphasized algorithmic improvements and individual applications in specific areas (e.g. model calibration, water distribution systems, groundwater management, river-basin planning and management, etc.). However, there has been limited synthesis between shared problem traits, common EA challenges, and needed advances across major applications. This paper clarifies the current status and future research directions for better solving key water resources problems using EAs. Advances in understanding fitness landscape properties and their effects on algorithm performance are critical. Future EA-based applications to real-world problems require a fundamental shift of focus towards improving problem formulations, understanding general theoretic frameworks for problem decompositions, major advances in EA computational efficiency, and most importantly aiding real decision-making in complex, uncertain application contexts.

Water distribution networks throughout the world are ageing, which increasingly leads to sudden pipe failure. About 108 trunk-main pipe failures in an urban sub-network were investigated using a pipe failure data base and SCADA (Supervisory Control and Data Acquisition) data to understand the contribution of hydraulic pressure to pipe failure using multiple lines of evidence. The forensic investigation revealed a dominant system-wide failure mode which was characterized by predominately off-peak high speed pumping with limited pressure relief from downstream reservoirs. A frequency analysis was conducted for greater understanding of the dominant failure mode. [ABSTRACT FROM AUTHOR]

During the Millennium Drought in southeast Australia (2001-2009), dryland wetlands experienced widespread ecological deterioration, which highlighted their vulnerability to natural climate variability and the potential effects of drying climate change. Here we use 30-year observed streamflow data (1991-2020) and numerical models to assess the impacts of climate variability and climate change on the Macquarie Marshes (the Marshes), a large floodplain wetland complex in the semi-arid region of New South Wales, Australia. A fast ecohydrologic emulator based on network linear programming with side constraints was developed to simulate the spatial and temporal responses of different wetland vegetation types to water regime. The emulator represents the wetland by a series of inter-connected level-pool reservoirs with the volume-discharge relationship obtained from a calibrated quasi-2d hydrodynamic model. The emulator reproduces daily flows and volume with good accuracy (Nash-Sutcliffe statistic ranging from 0.61 to 0.96) with 1/26,000 of the computational effort. We use the emulator to simulate the potential effects of climatic variability on vegetation by running the model over 30 years of observed data and 1000 statistically representative 30-year streamflow time series, which were generated using a stochastic model calibrated to the gauged flows. The collection of results for all 1000 contemporary simulations indicates the Marshes experience severe conditions 43% (± 18%) of the time in a 30-year period. We then ran an additional 6000 simulations to assess the combined impacts of climate variability and future climate change at the end of the century. For the driest future climates (-60% and -30% reduction in runoff), the Marshes remain in severe condition 89% (± 6%) and 63% (± 16%) of the time, respectively, while no major differences with respect to the contemporary conditions were found for the wetter future. Our results highlight the importance of quantifying the extent and uncertainty in the degradation of these ecosystems due to climate variability and change for informing management decisions., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Dryland wetlands are resilient ecosystems that can adapt to extreme periodic drought-flood episodes. Climate change projections show increased drought severity in drylands that could compromise wetland resilience and reduce important habitat services. These recognized risks have been difficult to evaluate due to our limited capacity to establish comprehensive relationships between flood-drought episodes and vegetation responses at the relevant spatiotemporal scales. We address this issue by integrating detailed spatiotemporal flood-drought simulations with remotely sensed vegetation responses to water regimes in a dryland wetland known for its highly variable inundation. We show that a combination of drought tolerance and dormancy strategies allow wetland vegetation to recover after droughts and recolonize areas invaded by terrestrial species. However, climate change scenarios show widespread degradation during drought and limited recovery after floods. Importantly, the combination of degradation extent and increase in drought duration is critical for the habitat services wetland systems provide for waterbirds and fish.

Dryland wetlands are ecosystems of high ecological importance as they serve as habitat sanctuaries for aquatic and terrestrial biota in areas with very few resources; therefore, the study of such environments is of major importance for the conservation of biodiversity in arid and semi-arid areas. The vegetation organization in these ecosystems is driven by the water regime as the main driver, but local processes like seed banks and soil resources redistribution also play a crucial role in determining the spatial distribution of the vegetation. Assessment of vegetation dynamics and long-term resilience requires the use of realistic models that can integrate the water regime and that can continuously simulate vegetation extent and conditions under flood-drought cycles. Here we study the influence of the water regime as the main driver of the vegetation. We apply a vegetation-modelling framework to compare the performance of a simplified model at the cell scale and a model integrated at a patch scale. Our results show that aggregating the analysis of vegetation dynamics at the patch scale allows for the incorporation of the effects of both local drivers (acting within the patch) as well as the global drivers (acting over the patch as a whole). The water regime acts as a global driver for the vegetation and indirectly affects the local drivers. Our patch scale model successfully captures wetland vegetation dynamics using the water regime as the main driver for representing changes in the vegetation and assessment of the wetland resilience under flood-drought periods., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper, (Copyright © 2020 Elsevier B.V. All rights reserved.)