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Future climatic, demographic, technological, urban and socio-economic challenges call for more flexible and sustainable wastewater infrastructure systems. Exploratory modelling can help to investigate the consequences of these developments on the infrastructure. In order to explore large numbers of adaptation strategies, we need to re-balance the degree of realism of sewer network and ability to reflect key performance characteristics against the model's parsimony and computational efficiency. We present a spatially explicit algorithm for creating sanitary sewer networks that realistically represent key characteristics of a real system. Basic topographic, demographic and urban characteristics are abstracted into a squared grid of 'Blocks' which are the foundation for the sewer network's topology delineation. We compare three different pipe dimensioning approaches and found a good balance between detail and computational efficiency. With a basic hydraulic performance assessment, we demonstrate that we attain a computationally efficient and high-fidelity wastewater sewer network with adequate hydraulic performance. A spatial resolution of 250 m Block size in combination with a sequential Pipe-by-Pipe (PBP) design algorithm provides a sound trade-off between computational time and fidelity of relevant structural and hydraulic properties for exploratory modelling. We can generate a simplified sewer network (both topology and hydraulic design) in 18 s using PBP, versus 36 min using a highly detailed model or 1 s using a highly abstract model. Moreover, this simplification can cut up to 1/10 th to 1/50 th the computational time for the hydraulic simulations depending on the routing method implemented. We anticipate our model to be a starting point for sophisticated exploratory modelling into possible infrastructure adaptation measures of topological and loading changes of sewer systems for long-term planning., (Copyright © 2021. Published by Elsevier Ltd.)

Sustainable urban drainage systems (SuDS) help in stormwater management by reducing runoff volume, increasing runoff concentration time and thereby improving the drainage system capacity. This study investigated the potential and cost-effectiveness of SuDS in reducing combined sewer overflows (CSOs). We simulated the performance of four SuDS techniques (bioretention cell, permeable pavement, rain barrel and green roof) at incremental levels of spatial coverage for a small urban catchment with a combined sewer system. We also used an Analytic Hierarchy Process (AHP) considering end-point CSO, land use, imperviousness, slope and elevation criteria to identify priority areas for SuDS deployment. Results showed that CSO volume attenuation ranged a maximum of 50-99% for the catchment, depending on the deployment strategy and underlying mechanisms of each technology. We also found that deployment of SuDS in AHP-selected sub-catchments improved CSO reduction only for rain barrels and green roofs, but not for bioretention cells and permeable pavements. SuDS were also a cost-effective retrofit option: for a 40% volume reduction, the SuDS cost, at most, 25% of the equivalent cost required for a large CSO tank. Outcomes of this study demonstrate the efficacy of SuDS in controlling CSOs, adding yet another tangible benefit to their increasingly recognised multi-functionality., Competing Interests: Declaration of Competing Interest None., (Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.)

It is well known that rainwater harvesting (RWH) can augment water supply and reduce stormwater pollutant discharges. Due to the lack of continuous 2D modelling of urban flood coverage and its associated damage, the ability of RWH to reduce urban flood risks has not been fully evaluated. Literature suggests that small distributed storage spaces using RWH tanks will reduce flood damage only during small to medium flooding events and therefore cumulative assessment of their benefits is needed. In this study we developed a new integrated modelling framework that implements a semi-continuous simulation approach to investigate flood prevention and water supply benefits of RWH tanks. The framework includes a continuous mass balance simulation model that considers antecedent rainfall conditions and water demand/usage of tanks and predicts the available storage prior to each storm event. To do so, this model couples a rainfall-runoff tank storage model with a detailed stochastic end-use water demand model. The available storage capacity of tanks is then used as a boundary condition for the novel rapid flood simulation model. This flood model was developed by coupling the U.S. EPA Storm Water Management Model (SWMM) to the Cellular-Automata Fast Flood Evaluation (CA-ffé) model to predict the inundation depth caused by surcharges over the capacity of the drainage network. The stage-depth damage curves method was used to calculate time series of flood damage, which are then directly used for flood risk and cost-benefit analysis. The model was tested through a case study in Melbourne, using a recorded rainfall time series of 85 years (after validating the flood model against 1D-2D MIKE-FLOOD). Results showed that extensive implementation of RWH tanks in the study area is economically feasible and can reduce expected annual damage in the catchment by up to approximately 30 percent. Availability of storage space and temporal distribution of rainfall within an event were important factors affecting tank performance for flood reduction., 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 © 2019 Elsevier Ltd. All rights reserved.)

Stormwater harvesting (SWH) provides multiple benefits to urban water management. Other than providing water for human use, it also reduces the volume of polluted stormwater discharge to the environment. There are currently no methods available to quantify the additional environmental benefits, which could encourage greater uptake of the practice. This paper investigates a number of factors (climate and catchment characteristics, pollutant reduction targets, etc.) that could impact upon the benefits of SWH for pollution reduction through sensitivity analyses. A method was developed and tested for quantification of the pollution mitigation benefits by SWH under different scenarios. A novel indicator, Impervious Area Offset (IAO), was proposed to reflect the additional impervious area that can be left untreated to achieve the equivalent pollution load reduction targets due to the introduction of SWH. Results indicate significant correlations (p < 0.01) between IAO values and extraction rate (proportion of total annual runoff removed due to the harvesting system and water use substitution), system type, and pollutant reduction targets. The proposed linear empirical relationships between IAO values and extraction rate for different types of system configurations and pollution reduction targets were well represented by observed linear regression (average R 2  = 0.98 for all tested scenarios). Empirical relationships were validated successfully against different scenarios, with differences between predicted IAO and baseline IAO values being only ±4.5% for the majority of the validation scenarios. Using this simple and reliable method to rapidly quantify SWH benefits can further add to the growing business case of adopting SWH practices., 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 © 2019 Elsevier Ltd. All rights reserved.)

Nature-based solutions provide a variety of benefits in growing cities, ranging from stormwater treatment to amenity provision such as aesthetics. However, the decision-making process involved in the installation of such green infrastructure is not straightforward, as much uncertainty around the location, size, costs and benefits impedes systematic decision-making. We developed a model to simulate decision rules used by local municipalities to install nature-based stormwater treatment systems, namely constructed wetlands, ponds/basins and raingardens. The model was used to test twenty-four scenarios of policy-making, by combining four asset selection, two location selection and three budget constraint decision rules. Based on the case study of a local municipality in Metropolitan Melbourne, Australia, the modelled uptake of stormwater treatment systems was compared with attributes of real-world systems for the simulation period. Results show that the actual budgeted funding is not reliable to predict systems' uptake and that policy-makers are more likely to plan expenditures based on installation costs. The model was able to replicate the cumulative treatment capacity and the location of systems. As such, it offers a novel approach to investigate the impact of using different decision rules to provide environmental services considering biophysical and economic factors., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Long term planning of urban water infrastructure requires acknowledgement that transitions in the water system are driven by changes in the urban environment, as well as societal dynamics. Inherent to the complexity of these underlying processes is that the dynamics of a system's evolution cannot be explained by linear cause-effect relationships and cannot be predicted under narrow sets of assumptions. Planning therefore needs to consider the functional behaviour and performance of integrated flexible infrastructure systems under a wide range of future conditions. This paper presents the first step towards a new generation of integrated planning tools that take such an exploratory planning approach. The spatially explicit model, denoted DAnCE4Water, integrates urban development patterns, water infrastructure changes and the dynamics of socio-institutional changes. While the individual components of the DAnCE4Water model (i.e. modules for simulation of urban development, societal dynamics and evolution/performance of water infrastructure) have been developed elsewhere, this paper presents their integration into a single model. We explain the modelling framework of DAnCE4Water, its potential utility and its software implementation. The integrated model is validated for the case study of an urban catchment located in Melbourne, Australia., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

The first flush in urban runoff has been an important, yet disputed phenomenon amongst many researchers. The vast differences in the evidence could be solely due to limitations of the first flush current definition and the approach used for its assessment. There is a need for revisiting the first flush theory in the light of its practical applications to urban drainage management practices. We propose that a catchment's first flush behaviour is to be quantified by the runoff volume required to reduce a catchment's stormwater pollutant concentrations to background levels. The proposed method for assessment of this runoff volume starts by finding the average catchment pollutant concentrations for a given increment of discharged volume using a number of event pollutographs. Non-parametric statistics are then used to establish the characteristic pollutograph by pooling statistically indifferent runoff increments (known as slices) together. This allows the identification of the catchment's initial and background pollutant concentrations and for quantification of the first flush volume and its strength. The novel technique was used on seven catchments around Melbourne, Australia, with promising results. Sensitivity to the chosen increment of runoff (for which mean concentrations are calculated) indicated that when dealing with discrete flow-weighted water quality data, a suitable slice size should closely match the flow-weighting of samples. The overall sensitivity to runoff increment and level of significance was found to be negligible. Further research is needed to fully develop this method., (Copyright (c) 2010 Elsevier Ltd. All rights reserved.)