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Problems caused by urban heat have prompted the exploration of urban greenery and blue spaces for heat mitigation. Various numerical models can simulate heat-related processes, but their use as support-tools to urban planners remains underexplored, particularly at the city-scale, due to high computational demand and complexity of such models. This study investigates the spatial relationships between urban heat, urban form and urban green and blue spaces with the fast climate model TARGET (The Air-temperature Response to Green/blue-infrastructure Evaluation Tool), which only requires minimal inputs of standard meteorological data, land cover and building geometry data. Using the City of Zurich as our case study, we: (i) validated the TARGET model against air temperature measurements from private sensor networks, (ii) performed a sensitivity analysis to identify key variables affecting urban heat, and (iii) investigated urban heat relationships with blue-green cover at locations frequented by pedestrians. Presence of urban green and blue spaces across the region shows potential for reducing local air temperatures by up to 5.2 °C (with urban forest). Investigating this relationship at different locations in the city revealed key districts that should potentially be targeted for reduction of pedestrian heat-impacts, due to their high pedestrian traffic, fewer green and blue spaces and high daytime air temperatures. Our results not only provide insights into the cooling effect of different amounts of green and blue features in the urban environment, but also demonstrates the application and integration potential of simplified models like TARGET to support the planning of more liveable future cities., 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 © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Urban floods will continue to be an alarming issue worldwide due to climate change and urban expansion. The costly and less environmentally friendly grey infrastructure is not always the most adequate solution to resolve urban pluvial flooding issues. The combination of grey and blue-green infrastructures, also called hybrid infrastructure, has been considered a promising solution for urban stormwater management. Existing approaches for identifying suitable hybrid solutions frequently rely on global multi-objective optimization algorithms. We developed a pre-screening method that decomposes a drainage network into clusters of pipes connected to sub-catchments, based on pipe hydraulic characteristic that allows for the impact of infrastructure combinations (blue-green and grey) to be mapped. Four impact matrices are proposed to map the total, local, upstream, and downstream flood reduction of all possible blue-green, grey, and hybrid solutions. Using an urban catchment in Guangzhou (China) as a case study, results showed that such an exercise could identify prime candidate locations for blue-green and grey infrastructure while filtering out ineffective locations for flood reduction. Furthermore, the impact matrices enabled the identification of flood zones where blue-green infrastructure could handle flood mitigation without the need of local grey infrastructure upgrades. As such, they are not only useful for quick screening of suitable interventions for each flooded zone, but can also potentially serve as a priori knowledge before diving into the data and computationally expensive process of finding the most effective flood mitigation solutions., 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 © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Primary considerations for urban blue-green infrastructure (BGI) encompass sustainable stormwater/urban heat management while biodiversity conservation is often considered an inherent benefit rather than a core planning requirement. However, ecological function of BGI as 'stepping stones' or linear corridors for otherwise fragmented habitats is undisputed. While quantitative approaches for modelling ecological connectivity in conservation planning are well established, mismatches in scope and scale with models that support the planning of BGI makes their adoption and integration difficult across disciplines. Technical complexities have led to ambiguity around circuit and network-based approaches, focal node placement, spatial extents, and resolution. Furthermore, these approaches are often computationally intensive, and considerable gaps remain in their use for identifying local-scale critical "pinch-points" that urban planners may respond to with the integration of BGI interventions that address biodiversity enhancement among other ecosystem services. Here, we present a framework that simplifies and integrates the merits of regional connectivity assessments with a focus on urban areas to prioritise BGI planning interventions while reducing computational demands. Our framework facilitates: (1) modelling potential ecological corridors at a coarse regional scale, (2) prioritising local-scale BGI interventions based on the relative contribution of individual nodes in this regional network, and (3) inferring connectivity hot- and cold-spots for local-scale BGI interventions. We illustrate this in the Swiss lowlands, demonstrating how, compared to previous work, we are able to identify and rank different priority locations across the region for BGI interventions in support of biodiversity enhancement and how their local-scale functional design may be benefited by addressing specific environmental variables., 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 © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Human impacts such as habitat loss, climate change and biological invasions are radically altering biodiversity, with greater effects projected into the future. Evidence suggests human impacts may differ substantially between terrestrial and freshwater ecosystems, but the reasons for these differences are poorly understood. We propose an integrative approach to explain these differences by linking impacts to four fundamental processes that structure communities: dispersal, speciation, species-level selection and ecological drift. Our goal is to provide process-based insights into why human impacts, and responses to impacts, may differ across ecosystem types using a mechanistic, eco-evolutionary comparative framework. To enable these insights, we review and synthesise (i) how the four processes influence diversity and dynamics in terrestrial versus freshwater communities, specifically whether the relative importance of each process differs among ecosystems, and (ii) the pathways by which human impacts can produce divergent responses across ecosystems, due to differences in the strength of processes among ecosystems we identify. Finally, we highlight research gaps and next steps, and discuss how this approach can provide new insights for conservation. By focusing on the processes that shape diversity in communities, we aim to mechanistically link human impacts to ongoing and future changes in ecosystems., (© 2022 The Authors. Ecology Letters published by John Wiley & Sons Ltd.)

Constant urban growth exacerbates the demand for residential, commercial and traffic areas, leading to progressive surface sealing and urban densification. With climate change altering precipitation and temperature patterns worldwide, cities are exposed to multiple risks, demanding holistic and anticipatory urban planning strategies and adaptive measures that are multi-beneficial. Sustainable urban planning requires comprehensive tools that account for different aspects and boundary conditions and are capable of mapping and assessing crucial processes of land-atmosphere interactions and the impacts of adaptation measures on the urban climate system. Here, we combine Computational Fluid Dynamics (CFD) and Geographic Information System (GIS) capabilities to refine an existing 2D urban micro- and bioclimatic modelling approach. In particular, we account for the vertical and horizontal variability in wind speed and air temperature patterns in the urban canopy layer. Our results highlight the importance of variability of these patterns in analysing urban heat development, intensity and thermal comfort at multiple heights from the ground surface. Neglecting vertical and horizontal variability, non-integrated CFD modelling underestimates mean land surface temperature by 7.8 °C and the Universal Thermal Climate Index by 6.9 °C compared to CFD-integrated modelling. Due to the strong implications of wind and air temperature patterns on the relationship between surface temperature and human thermal comfort, we urge caution when relying on studies solely based on surface temperatures for urban heat assessment and hot spot analysis as this could lead to misinterpretations of hot and cool spots in cities and, thus, mask the anticipated effects of adaptation measures. The integrated CFD-GIS modelling approach, which we demonstrate, improves urban climate studies and supports more comprehensive assessments of urban heat and human thermal comfort to sustainably develop resilient cities., Competing Interests: Declaration of competing interest The authors declare that they have no competing interests., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Increasing urbanization degrades quantity, quality, and the functionality of spatial cohesion of natural areas essential to biodiversity and ecosystem functioning worldwide. The uncontrolled pace of building activity and the erosion of blue (i.e., aquatic) and green (i.e., terrestrial) landscape elements threaten existing habitat ranges and movability of wildlife. Local scale measures, such as nature-inspired engineered Blue-Green Infrastructure (BGI) are emerging mitigation solutions. Originally planned to promote sustainable stormwater management, adaptation to climate change and improved human livability in cities, such instruments offer interesting synergies for biodiversity in support of existing ecological infrastructure. BGI are especially appealing for globally declining amphibians, a rich and diverse vertebrate assemblage sensitive to urbanization. We integrated biological and highly resolved urban-rural land-cover data, ensemble models of habitat suitability, and connectivity models based on circuit theory to improve multi-scale and multi-species protection of core habitats and ecological corridors in the Swiss lowlands. Considering a broad spectrum of amphibian biodiversity, we identified distributions of amphibian biodiversity hotspots and four landscape elements essential to amphibian movability at the regional scale, namely i) forest edges, ii) wet-forest habitats, iii) soils with variable moisture and iv) riparian zones. Our work shows that cities can make a substantial contribution (e.g., up to 15% of urban space in the study area) to wider landscape habitat connectivity. We highlight the importance of planning BGI locally in strategic locations across urban and peri-urban areas to promote the permeability and availability of 'stepping stone' habitats in densely populated landscapes, essential to the maintenance of regional habitat connectivity and thereby enhancing biodiversity and ecosystem functioning., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Illicit discharges in urban stormwater drains are a major environmental concern that deteriorate downstream waterway health. Conventional detection methods such as stormwater drain visual inspection and dye testing have fundamental drawbacks and limitations which can prevent easy location and elimination of illegal discharges in a catchment. We deployed 22 novel low-cost level, temperature and conductivity sensors across an urban catchment in Melbourne for a year to monitor the distributed drainage network, thereby detecting likely illicit discharges ranging from a transitory flow with less than 10 minutes to persistent flows lasting longer than 20 hours. We discuss rapid deployment methods, real-time data collection and online processing. The ensemble analysis of all dry weather flow data across all sites indicates that: (i) large uncertainties are associated with discharge frequency, duration, and variation in water quality within industrial and residential land uses; (ii) most dry weather discharges are intermittent and transient flows which are difficult to detect and not simply due to cross-connections with the sewerage network; (iii) detectable diurnal discharge patterns can support mitigation efforts, including policies and regulatory measures (e.g., enforcement or education) to protect receiving waterways; and, (iv) that it is possible to cost effectively isolate sources of dry weather pollution using a distributed sensor network.

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.)

Planning for future urban development and water infrastructure is uncertain due to changing human activities and climate. To quantify these changes, we need adaptable and fast models that can reliably explore scenarios without requiring extensive data and inputs. While such models have been recently considered for urban development, they are lacking for stormwater pollution assessment. This work proposes a novel Future Urban Stormwater Simulation (FUSS) model, utilizing a previously developed urban planning algorithm (UrbanBEATS) to dynamically assess pollution changes in urban catchments. By using minimal input data and adding stochastic point-source pollution to the build-up/wash-off approach, this study highlights calibration and sensitivity analysis of flow and pollution modules, across the range of common stormwater pollutants. The results highlight excellent fit to measured values in a continuous rainfall simulation for the flow model, with one significant calibration parameter. The pollution model was more variable, with TSS, TP and Pb showing high model efficiency, while TN was predicted well only across event-based assessment. The work further explores the framework for the model application in future pollution assessment, and points to the future work aiming to developing land-use dependent model parameter sets, to achieve flexibility for model application across varied urban catchments.

High-resolution data collection of the urban stormwater network is crucial for future asset management and illicit discharge detection, but often too expensive as sensors and ongoing frequent maintenance works are not affordable. We developed an integrated water depth, electrical conductivity (EC), and temperature sensor that is inexpensive (USD 25), low power, and easily implemented in urban drainage networks. Our low-cost sensor reliably measures the rate-of-change of water level without any re-calibration by comparing with industry-standard instruments such as HACH and HORIBA's probes. To overcome the observed drift of level sensors, we developed an automated re-calibration approach, which significantly improved its accuracy. For applications like monitoring stormwater drains, such an approach will make higher-resolution sensing feasible from the budget control considerations, since the regular sensor re-calibration will no longer be required. For other applications like monitoring wetlands or wastewater networks, a manual re-calibration every two weeks is required to limit the sensor's inaccuracies to ±10 mm. Apart from only being used as a calibrator for the level sensor, the conductivity sensor in this study adequately monitored EC between 0 and 10 mS/cm with a 17% relative uncertainty, which is sufficient for stormwater monitoring, especially for real-time detection of poor stormwater quality inputs. Overall, our proposed sensor can be rapidly and densely deployed in the urban drainage network for revolutionised high-density monitoring that cannot be achieved before with high-end loggers and sensors.

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.)

In many parts of the world, small towns are experiencing high levels of population growth and development. However, there is little understanding of how urban growth in these regional towns will impact urban runoff. We used the case study of Wangaratta, located in South-East Australia, between 2006 and 2016, to investigate land cover changes and their impacts on urban runoff discharge. Detailed spatio-temporal analysis (including neighbourhood composition analysis and supervised classification of aerial imagery) identified that population, land use and land cover changes in Wangaratta, although subtle, were mostly driven by residential growth in the outskirts of the town, where there were large increases in impervious surface area. Overall, the urban growth was minimal. However, in spite of these small changes, a sub-catchment only SWMM model showed that the increase in impervious surface area nevertheless resulted in a statistically significant increase in total runoff across the town. Particularly, this increase was most pronounced for frequent and shorter storms. The analysis of urban development pattern changes coupled with urban hydrological modelling indicated that land cover changes in regional towns, especially when analysed in detail, may result in hydrological changes in the urban region (likely to be exacerbated in coming years by changing climate) and that adaptation efforts will need to adopt a variety of approaches in both existing and growth zones. Our findings highlight the necessity of detailed fine-scale analyses in small towns as even subtle changes will have substantial future implications and robust planning and adaptation decisions are even more important when compared to larger cities due to the greater economic constraints that small towns face and their important relationship with the surrounding hinterlands., Competing Interests: Declaration of competing interest None., (Copyright © 2020 The Author(s). Published by Elsevier B.V. All rights reserved.)

Surface characteristics play a vital role in simulations for urban bioclimatic conditions. Changing relationships and distribution patterns of sealed and vegetated surfaces as well as building geometry across different scales in urban environments influence surface temperatures. Cities comprise different urban forms, which, depending on their surface characteristics, enhance the heating process, increasing the emergence of urban heat islands (UHIs). Detecting priority areas to introduce multi-beneficial climate change adaptation measures is set to be a key task for the cities long-term strategies to improve climatic conditions across different urban structures and scales. We introduce a simple and fast spatial modelling approach to carry out fine-scale simulations for land surface temperature (LST), mean radiant temperature (MRT) and Universal Thermal Climate Index (UTCI) in a 2D environment. Capabilities of our modelling approach are demonstrated in evaluating urban thermal comfort in the alpine city of Innsbruck, the capital of Tyrol in western Austria. Results show a major contrast between sealed and vegetated surfaces reflected in the distributional patterns and values of LST, MRT and UTCI, correlating with the appearance and frequency of specific surface classes. We found the Sky View Factor to have a substantial impact on calculations for bioclimatic conditions and see high-albedo surfaces decrease LST but increase the apparent temperature (MRT and UTCI values) effecting human thermal comfort. Furthermore, MRT and UTCI are more sensitive to changes in emissivity values, whereas LST is more sensitive to changes in Bowen Ratio values. Application of our modelling approach can be used to identify priority areas and maximise multi-functionality of climate change adaptation measures, to support urban planning processes for heat mitigation and the implementation of policy suggestions to achieve sustainable development goals and other political objectives., 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 The Author(s). Published by Elsevier B.V. All rights reserved.)

Current Water Sensitive Urban Design (WSUD) models are either purely technical or overly simplified, lacking consideration of urban planning and stakeholder preferences to adequately support stakeholders. We developed the Urban Biophysical Environments and Technologies Simulator (UrbanBEATS), which integrates stormwater management with urban planning to support the design and implementation of WSUD. This study specifically describes and tests UrbanBEATS' WSUD Planning Module, which combines spatial analysis, infrastructure design, preference elicitation and Monte Carlo methods to generate feasible stormwater management and harvesting infrastructure options in greenfield and existing urban environments. By applying UrbanBEATS to a real-world greenfield development case study in Melbourne, Australia (with data sourced from the project's water management plans and design consultants), we explore the variety of options generated by the model and analyse them collectively to demonstrate that UrbanBEATS can design similar WSUD systems (e.g. select suitable technology types, their sizes and locations) to actual infrastructure choices., Competing Interests: Declaration of competing interest None., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Recent developments in high- and middle-income countries have exhibited a shift from conventional urban water systems to alternative solutions that are more diverse in source separation, decentralization, and modularization. These solutions include nongrid, small-grid, and hybrid systems to address such pressing global challenges as climate change, eutrophication, and rapid urbanization. They close loops, recover valuable resources, and adapt quickly to changing boundary conditions such as population size. Moving to such alternative solutions requires both technical and social innovations to coevolve over time into integrated socio-technical urban water systems. Current implementations of alternative systems in high- and middle-income countries are promising, but they also underline the need for research questions to be addressed from technical, social, and transformative perspectives. Future research should pursue a transdisciplinary research approach to generating evidence through socio-technical "lighthouse" projects that apply alternative urban water systems at scale. Such research should leverage experiences from these projects in diverse socio-economic contexts, identify their potentials and limitations from an integrated perspective, and share their successes and failures across the urban water sector.

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.)

Distributed green stormwater management infrastructure is increasingly applied worldwide to counter the negative impacts of urbanisation and climate change, while providing a range of benefits related to ecosystem services. They are known as Water Sensitive Urban Design (WSUD) in Australia, Nature Based Solutions (NBS) in Europe, Low Impact Development (LID) in the USA, and Sponge City systems in China. Urban planning for WSUD has been ad-hoc, lacking strategy and resulting in sub-optimal outcomes. The purpose of this study is to help improve strategic WSUD planning and placement through the development of a Planning Support System. This paper presents the development of Spatial Suitability ANalysis TOol (SSANTO), a rapid GIS-based Multi-Criteria Decision Analysis tool using a flexible mix of techniques to map suitability for WSUD assets across urban areas. SSANTO applies a novel WSUD suitability framework, which conceptualises spatial suitability for WSUD implementation from two perspectives: 'Needs' and 'Opportunities' for WSUD. It combines biophysical as well as socio-economic, planning and governance criteria ('Opportunities') with criteria relating to ecosystem services ('Needs'). Testing SSANTO through comparing its results to work done by a WSUD consultancy successfully verified its algorithms and demonstrated its capability to reflect and potentially enhance the outcomes of planning processes. Manual GIS based suitability analysis is time and resource intensive. Through its rapid suitability analysis, SSANTO facilitates iterative spatial analysis for exploration of scenarios and stakeholder preferences. It thus facilitates collaborative planning and deeper understanding of the relationship between diverse and complex urban contexts and urban planning outcomes for WSUD., (Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.)

To support sustainable urban planning and the design of water pollution mitigation strategies, the spatial and temporal trends of water quality in urban streams needs to be further understood. This study analyses over ten years of surface water quality data from 53 upstream catchments (20 of them predominated by a single type of land use) and two lowland sites across Greater Melbourne, Australia. We evaluated the impact of various catchment characteristics, especially urban land uses, on spatial and temporal urban water quality trends. Here, we focused on common urban pollutants: total suspended solids (TSS), total phosphorous (TP), total nitrogen (TN), zinc (Zn), copper (Cu) and nickel (Ni). Site median nutrient and heavy metal concentrations were negatively correlated with the catchment's elevation and its average annual rainfall. Further analysis shows that such trends were driven by the geographical pattern of Melbourne - i.e. low-laying sites tend to have less rainfall and be more urbanised. Only median concentrations of heavy metals (Zn and Cu) were correlated to catchment imperviousness. Further characterising of the urban environment was done into specific land uses (residential, industrial and commercial), yet median concentrations of all pollutants were not significantly correlated with land uses. This is because simple metrics, such as land use proportions, do not adequately reflect the significant variability in pollution sources that can exist even within the same land use type. Indeed, our temporal analysis found that the water quality difference between catchments with similar land uses is likely caused by their site-specific pollutant sources (construction and illegal discharge) and environmental management actions (wastewater management actions) regardless of similarities in land use. A 3-stage urbanisation cycle (development, operation and renewal) is suggested to further explain the urban water quality variance, but more data from small areas of an urban catchment is required to directly understand the unique impact of each urbanisation stage on water quality., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Pollution build-up and wash-off processes are often included in urban stormwater quality models. However, these models are often unreliable and have poor performance at large scales and in complicated catchments. This study tried to improve stormwater quality models by adopting the genetic programming (GP) approach to generate new build-up algorithms for three different pollutants (total suspend solids - TSS, total phosphorus - TP and total nitrogen - TN). This was followed by testing of the new models (also traditional build-up and wash-off models as benchmark) using data collected from different catchments in Australia and the USA. The GP approach informed new sets of build-up algorithms with the inclusion of not just the typical antecedent dry weather period (ADWP), but also other less 'traditional' variables - previous rainfall depth for TSS and maximum air temperatures for TP and TN simulation. The traditional models had relatively poor performance (Nash-Sutcliffe coefficient, E < 0.0), except for TP at Gilby Road (GR) (E = 0.21 in calibration and 0.43 in validation). Improved performance was observed using the models with new build-up algorithms informed by GP. Taking TP at GR for example, the best performing model had E of 0.46 in calibration and 0.54 in validation. The best performing models for TSS, TP, and TN are often different, suggesting that specific models shall be used for different pollutants. Insights into further improvements possible for stormwater quality models were given. It is recommended that in addition to the typical build-up and wash-off process, new generations of stormwater quality models should be able to account for the non-conventional pollutant sources (e.g. cross-connections, septic tank leakage, illegal discharges) through stochastic approaches. Emission inventories with information like intensity-frequency-duration (IFD) of pollutant loads from each type of non-conventional source are suggested to be built for stochastic modelling., (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.)

This study showcases the dynamic simulation capabilities of the Urban Biophysical Environments And Technologies Simulator (UrbanBEATS) on a Melbourne catchment. UrbanBEATS simulates the planning, design and implementation of water sensitive urban design (WSUD) infrastructure in urban environments. It considers explicitly the interaction between urban and water infrastructure planning through time. The model generates a large number of realizations of different WSUD interventions and their evolution through time based on a user-defined scenario. UrbanBEATS' dynamics was tested for the first time on a historical case study of Scotchman's Creek catchment and was trained using historical data (e.g. planning documents, narratives, urban development and societal information) to adequately reproduce patterns of uptake of specific WSUD technologies. The trained model was also used to explore the implications of more stringent future water management objectives. Results highlighted the challenges of meeting this legislation and the opportunities that can be created through the mix of multiple spatial scales.

With global change bringing about greater challenges for the resilient planning and management of urban water infrastructure, research has been invested in the development of a strategic planning tool, DAnCE4Water. The tool models how urban and societal changes impact the development of centralised and decentralised (distributed) water infrastructure. An algorithm for rigorous assessment of suitable decentralised stormwater management options in the model is presented and tested on a local Melbourne catchment. Following detailed spatial representation algorithms (defined by planning rules), the model assesses numerous stormwater options to meet water quality targets at a variety of spatial scales. A multi-criteria assessment algorithm is used to find top-ranking solutions (which meet a specific treatment performance for a user-defined percentage of catchment imperviousness). A toolbox of five stormwater technologies (infiltration systems, surface wetlands, bioretention systems, ponds and swales) is featured. Parameters that set the algorithm's flexibility to develop possible management options are assessed and evaluated. Results are expressed in terms of 'utilisation', which characterises the frequency of use of different technologies across the top-ranking options (bioretention being the most versatile). Initial results highlight the importance of selecting a suitable spatial resolution and providing the model with enough flexibility for coming up with different technology combinations. The generic nature of the model enables its application to other urban areas (e.g. different catchments, local municipal regions or entire cities).

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.)

The management of stormwater pollution has placed particular emphasis on the first flush phenomenon. However, definition and current methods of analyses of the phenomena contain serious limitations, the most important being their inability to capture a possible impact of the event size (total event volume) on the first flush. This paper presents the development of a novel approach in defining and assessing the first flush that should overcome these problems. The phenomenon is present in a catchment if the decrease in pollution concentration with the absolute cumulative volume of runoff from the catchment is statistically significant. Using data from seven diverse catchments around Melbourne, Australia, changes in pollutant concentrations for Total Suspended Solids (TSS) and Total Nitrogen (TN) were calculated over the absolute cumulative runoff and aggregated from a collection of different storm events. Due to the discrete nature of the water quality data, each concentration was calculated as a flow-weighted average at 2 mm runoff volume increments. The aggregated concentrations recorded in each increment (termed as a 'slice' of runoff) were statistically compared to each other across the absolute cumulative runoff volume. A first flush is then defined as the volume at which concentrations reach the 'background concentration' (i.e. the statistically significant minimum). Initial results clearly highlight first flush and background concentrations in all but one catchment supporting the validity of this new approach. Future work will need to address factors, which will help assess the first flush's magnitude and volume. Sensitivity testing and correlation with catchment characteristics should also be undertaken.

Elevated serum levels of creatine kinase (CK) were found in a patient with small-(oat) cell carcinoma of the lung. Fractionation of the enzyme showed markedly elevated CK-MB and CK-BB isoenzymes. Clinical and subsequent pathological examination showed no evidence of infarction, inflammation, or tumor involvement of the heart; however, analysis of tumor tissue for CK showed predominance of CK-MB and CK-BB isoenzymes, thus implicating tumor as the source of the circulating levels of CK-MB and CK-BB. Our case is the first to document CK-MB from neoplastic tissue homogenates, and illustrates that markedly elevated circulating levels of CK-MB, or increased levels of CK-MB in combination with CK-BB may point away from a myocardial source, and toward the existence of a malignancy.

To establish the prevalence and to characterize the types of cardiac involvement in Friedreich's ataxia, 75 consecutive patients (39 male and 36 female), aged 10 to 66 years (mean 24) were prospectively studied. Electrocardiograms were performed in all patients, vectorcardiograms in 34 and echocardiograms in 58. Electrocardiographic and vectorcardiographic abnormalities occurred in 69 (92%) of the 75 patients. Electrocardiograms revealed ST-T wave abnormalities in 79%, right axis deviation in 40%, short PR interval in 24%, abnormal R wave in lead V1 in 20%, abnormal inferolateral Q waves in 14% and left ventricular hypertrophy (voltage and repolarization criteria) in 16%. Echocardiograms revealed concentric left ventricular hypertrophy in 11%, asymmetric septal hypertrophy in 9% and globally decreased left ventricular function in 7%. Progression from a normal echocardiogram to concentric left ventricular hypertrophy, asymmetric septal hypertrophy or globally decreased left ventricular function was identified in one patient in each category, although the study was not designed for longitudinal follow-up. Two patients died, and necropsy revealed in both a minimally dilated but flabby left ventricle. On the basis of electrocardiographic and vectorcardiographic and echocardiographic data, 95% of patients had one or more disorders. The most common abnormality was segmental myocardial "dystrophy" (electrocardiographic QRS initial force abnormalities), but global left ventricular hypokinesia occurred more often than previously recognized.(ABSTRACT TRUNCATED AT 250 WORDS)