Cities, through the process of urbanization, have altered natural surface energy balances (Oke et al., 2017) and water cycles (Coutts et al., 2012). The conversion of vegetated surfaces to hard impervious surfaces with higher heat storage capacity, reduced shading of surfaces from shrinking vegetated urban canopies (Brunner and Cozens, 2013), and reductions in available water for evapotranspiration (Spronken-Smith and Oke, 2010; Middel and Krayenhoff, 2019; Cheung et al., 2022) result in increased canopy air and surface temperatures (Martilli et al., 2020; Nice et al., 2022) and greater risks to health (Nicholls et al., 2008; Loughnan et al., 2010; Nazarian et al., 2022). Urban heat will be further exacerbated by climate change, projected to bring increasingly frequent and intense heat waves (Perkins-Kirkpatrick and Lewis, 2020), increasing droughts (IPCC, 2021), and localized warming (Zhao et al., 2021).

Strategies to mitigate urban heat can involve methods such as surface albedo changes, vegetation cover, irrigation, and the use of water (Krayenhoff et al., 2021). Vegetation and water have been widely recognized to provide urban cooling benefits through evapotranspiration and shading (Bowler et al., 2010; Coutts et al., 2012, 2015; Demuzere et al., 2014a). Replacement of hard impervious surfaces with pervious vegetated surfaces provides additional cooling (Middel and Krayenhoff, 2019). The use of water provides urban cooling through evaporative cooling from large water bodies (Theeuwes et al., 2013; Völker et al., 2013). Additionally, irrigation of vegetated surfaces (Broadbent et al., 2017; Cheung et al., 2021) as well as impervious surfaces (Hendel et al., 2016; Solcerova et al., 2018) can provide cooling benefits.

Stormwater water management frameworks, to protect urban areas from flooding and provide waterway and pollution protections (Whiteoak, 2019; Renouf et al., 2020), also enable the provision of alternative water supplies. The physical infrastructure required for these frameworks, e.g., blue-green infrastructure (BGI), can also provide cooling benefits (Demuzere et al., 2014b; Jamei and Tapper, 2019; Probst et al., 2022). The frameworks include Water Sensitive Urban Design (WSUD) (Wong and Brown, 2009; Newton and Rogers, 2020), Sponge Cities (Jia et al., 2020), Sustainable Urban Drainage Systems (SUDS) (Woods-Ballard et al., 2007), among others. Integrated Water Management (IWM), defined by Global Water Partnership (2000) as ‘a process which promotes the coordinated development and management of water, land and related resources, in order to maximise the resultant economic and social welfare in an equitable manner without compromising the sustainability of vital ecosystems' provides the mechanisms for frameworks such as WSUD.

The growing adoption of IWM across governments and water providers, such as the Australian state of Victoria's IWM framework (State of Victoria, 2017), enables the adoption of cooling strategies based on increased urban vegetation and water. To explore the expected benefits from these strategies, the literature can provide some data, but ultimately a full exploration will require modelling. Cooling magnitudes from irrigation of green space varies with background climate. In most cities in the world in different climate types, the expected benefit is approximately 1°C in air temperature reductions, where arid cities see reductions of up to 1.65°C (Cheung et al., 2021). Surface temperature cooling from short vegetation (Santamouris et al., 2017; Yang et al., 2020) can range from 1-2°C whereas surface temperatures under tree canopies (Shashua-Bar and Hoffman, 2000; Cheung and Jim, 2018; Jia and Wang, 2021) can be up to 15°C cooler while air temperature reductions are more modest at 1–2°C. Artificial wetlands have been found to provide surface temperature reductions of up to 11°C and 1-2°C in air temperature, while water bodies were found to provide on average 2.5°C air temperature reductions (Theeuwes et al., 2013; Völker et al., 2013; Manteghi et al., 2015; Broadbent et al., 2017).

This study examines the potential cooling that can be provided through the additional BGI infrastructure enabled through IWM in all the major cities in Australia. We utilise the Air-temperature Response to Green/blue-infrastructure Evaluation Tool (TARGET) (Broadbent et al., 2019), a local-scaled climate model designed to efficiently evaluate heat mitigation benefits of blue-green infrastructure and to predict temporal and spatial patterns of air and surface temperatures at the neighbourhood to city scale. TARGET is efficient and easy to use, with fewer user-defined parameters and less model input data required than other urban climate models. The model utilises an idealised urban canyon representation with an aggregation of land cover types of grass, irrigated grass, trees, concrete, asphalt, buildings, and water. The modelling approach allows multiple IWM interventions to be tested across present day climate conditions as well as projected future climate conditions. The hypothesis that will be tested is that IWM interventions that increase fractions of vegetation cover and amounts of irrigated vegetation and water bodies, subsequently reducing fractions of hard impervious surfaces, will result in significantly cooler urban areas both in the present day and under future climate conditions. Results will test seasonal and diurnal variations across multiple years as well as across multiple cities in different climate zones (temperate and tropical). Finally, the potential to offset climate change warming will be tested under a range of IWM interventions.

To run the TARGET model, two sources of information are required: (1) meteorological time series of air temperature, humidity, wind speed, air pressure, and incoming short- and longwave radiation, and (2) gridded land cover fractions that include percentages of roof, road, water, concrete, vegetation (i.e., trees), dry grass, and irrigated grass.

Since TARGET will be applied over seven capital cities (Adelaide, Brisbane, Canberra, Darwin, Melbourne, Perth, and Sydney) and two regional centres (Albury-Wodonga and Townsville), which do not all have the required input data readily available, these datasets are sourced from generic and state-of-the-art data sources and re-structured to fit the requirements of this project.

Scenario modeling with TARGET was performed for all LCZ classes and their IWM variations (BAU, MODERATE, HIGH) for all cities using ERA5 2010–2020 present day climate conditions as well as CMIP6-adjusted 2030 and 2050 SSP 1.2-6, 3.7-0, and 5.8-5 future climate scenarios. The complete results data set is available at https://doi.org/10.5281/zenodo.10099762 and summaries of the full set of results for each of the nine Australian cities in Appendix 2. The summary data are average daily values for 10-year time periods centered on 2015 (historical data), 2030, and 2050. Cooling for all cities associated with implementation of IWM is calculated as moderate [MOD] or high [HIGH] minus business as usual [BAU] temperatures.

The Australian Department of Agriculture, Water, and the Environment (DAWE) commissioned this study to evaluate the healthcare cost savings from reducing urban heat through Integrated Water Management (IWM) practices. A key requirement from DAWE was the application of a uniform method across seven capital cities and two regional centers, ensuring a thorough and consistent analysis in diverse urban environments to fully understand the wide-ranging impacts and benefits of IWCM strategies under varying geographical and projected climate change scenarios. The complexity of the task was heightened as none of the nine urban centers had all necessary input data readily available. To address this, a flexible, consistent, and robust approach was developed, including the use of (i) the Local Climate Zone (LCZ) typology as a universal method to depict present-day land surface cover and integrate IWM policy guidelines, (ii) globally available ERA5 reanalysis data providing a basis for current climate simulations, enhanced by CMIP6 climate change projections for future scenarios, and iii) the TARGET model proven to be effective in modeling air temperatures and capturing the spatial temperature variability within and between Australian cities.

This methodical and scalable approach led to significant findings, characterized by its comprehensive nature and adaptability for different urban settings. Climate change was found to lead to warmer (mean daily, maximum, and minimum) temperatures across all Australian cities compared to business as usual with the overall warming greatest for the SSP5-8.5 emissions pathway for 2050. In Australian cities, summers are warming slightly more than annual temperatures, and winter temperatures slightly less.

To provide adaptations to these changes, two scenarios of IWM implementation were explored based on current policy and IWM was found capable of reducing urban air temperatures. The HIGH IWM scenario provided greater reductions in mean daily maximum air temperature. In general, IWM reduces mean daily maximum temperatures during the day, yet increases mean minimum temperatures at night. The net effect of this is a reduction in mean daily temperatures. The largest reductions in temperature from IWM are seen in the mean daily maximum temperatures during summer. The impact of IWM on temperature varies between cities and is more evident in cities with a hotter and drier climate (such as Albury and Perth) resulting in large reduction in mean maximum temperature, particularly in summer. The impact of IWM on temperature is less evident in more humid, tropical cities (such as Darwin and Townsville). Impacts of IWM implementation on projected temperatures under climate change vary between cities, and again larger reductions are seen in cities with hotter and drier climates. The variations in temperature for each city resulting from IWM, are very similar under all climate change scenarios.

IWM has the potential to offset some warming impacts from climate change. In hotter and drier cities, a MOD level of IWM implementation is effective in offsetting the projected mean maximum daily summer warming in 2050 under SSP3-7.0, and some of the warming in more humid, tropical cities. A HIGH level of IWM is needed to offset mean maximum daily summer warming in 2050 under SSP3-7 in humid, tropical cities. IWM generally results in warmer night-time minimum temperatures. However, additional urban heat mitigation measures will be needed to help offset this warming, particularly in summer. A range of options are available including increasing the albedo of urban surfaces (such as roofs and roads), controlling building heights and street widths, and reducing waste heat production (from building energy use and transport).

While the study successfully utilized the TARGET model as an effective tool for modeling air temperatures and capturing both the inter-city and intra-city spatial variability of temperatures in Australian cities, there are some notable limitations. The use of Local Climate Zones (LCZs) for providing a holistic and uniform land surface cover data allowed for the efficient modeling setup, but inherently this approach may oversimplify the complex urban environments. Also the use of ERA5 data and the superimposed CMIP6 climate change data, although robust, may not completely capture the localized microclimatic variations within cities. Finally, other heat mitigation strategies are available, such as increasing the albedo of urban surfaces (such as roofs and roads), controlling building heights and street widths, and reducing waste heat production (from building energy use and transport). These options could be explored in future work using TARGET and the approach used here.

Despite the above, this study's findings are highly relevant in terms of policy making and planning. The detailed data provided by the study can inform urban planning and development, guiding strategies to mitigate urban heat islands and improve climate resilience. Policymakers can use this information to formulate targeted policies and allocate resources effectively, particularly in healthcare and urban infrastructure. Moreover, understanding the economic and environmental benefits of IWM measures can justify investments in green and blue infrastructure, aiding stakeholders in decision-making processes. Additionally, the utilization of simple and uniform data facilitates clearer communication and mutual understanding across different departments and stakeholders. This shared “language” in interpreting data ensures that all parties are aligned and can collaboratively work toward common goals, enhancing the efficacy of policy implementation and stakeholder engagement.

The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: https://doi.org/10.5281/zenodo.10099762.

KN: Conceptualization, Formal analysis, Methodology, Software, Writing – original draft, Writing – review & editing. MD: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Visualization, Writing – original draft, Writing – review & editing. AMC: Writing – review & editing, Methodology, Investigation, Conceptualization. NT: Conceptualization, Funding acquisition, Methodology, Writing – original draft, Writing – review & editing.