To design sustainable water supply systems, utilities need to determine the average per capita water consumption along with factors that influence it. However, data on residents per building are often unavailable. This study introduces a GIS-based approach to estimate residents per building despite incomplete data. Building height and size were determined and spatially linked to water consumption data. These values were used to calculate the living space and the number of residents per building. A comparison with actual residents from Study Site 1 showed high agreement (correlation of 0.7), confirming the method’s reliability. With an accuracy of ±1 person, 66% of single-family homes and 17% of apartment buildings were correctly estimated. The analysis further showed that single-family home residents consume about 130 L per day, while those in apartment buildings use 105–114 L per day. The presence of swimming pools was identified as a significant factor. A resident in a single-family home with a pool consumes around 153 L per day, while one without a pool uses around 126 L per day. This approach provides a method to estimate per capita water consumption, enabling water utilities to plan sustainably, even in regions with limited register data.

The changing climate creates challenges for green spaces everywhere. A special case is presented by the urban tree, which has several harsh environmental conditions to deal with, i.e. compacted soil, polluted rainwater, etc. Climate adaptation strategies for cities involve the urban tree as a nature-based solution due to its high potential for heat island mitigation and reducing surface runoff. Managing water resources efficiently is receiving more attention with measures including alternative resources for irrigation or incorporating more drought-resistant species, while the effects of changing macro- and micro-climatic conditions on urban trees are only now becoming subject of scientific scrutiny. There are several important indicators for evaluating a tree’s living conditions and its water demand at a certain location. One such indicator is the start and end of the growing season. As temperatures rise, plants are seen to have shorter dormancy periods, resulting in earlier flowering and longer growing seasons, increasing both water demand and susceptibility to damage. In this study, we compare the growing cycles of urban trees across varying locations in the city of Graz during a period of over 20 years. Tree specific information is taken from the city’s tree register which gives important information about species, age and location of urban trees. Growing cycles are evaluated using a remote sensing approach where NDVI-timeseries are then calculated for the selected areas using openly available satellite imagery to identify changes in dormancy and evaluate a possible trend. The influence of parameters such as location, micro-climate, species and date of planting are investigated using statistical analysis. The generated knowledge is expected to help in the prediction of future urban green irrigation demand and choice of tree species.

Climate adaptation strategies for many cities include urban green infrastructure as nature-based solutions due to their potential to mitigate urban heat island effects and reduce surface runoff. However, rising temperatures, drought events and altered precipitation patterns are expected to impact plant phenology by shortening dormancy, resulting in earlier flowering and extended growing seasons. These changes can increase irrigation demand and susceptibility to damage, posing a risk to urban green infrastructure and its ecosystem functions.In this study, we investigated changes in the growing cycles of urban green infrastructure in four European cities (Birmingham, Paris, Graz, Barcelona) from 1984 to 2024.The approach is based on monitoring the Normalized Difference Vegetation Index (NDVI) from satellite images to assess long-term trends and analyze the potential effects of climate change on plant phenology in an urban environment. Although analyzing NDVI in urban environments is still relatively new, it is becoming more feasible due to the increased availability of long-term, high-resolution satellite images.Monthly NDVI values were derived from pre-processed Landsat satellite images to analyze changes in urban green infrastructure and plant phenology. Raster-based pixel counts with an NDVI value above 0.3 were normalized to highlight intra-annual vegetation peaks and seasonal shifts. Temporal trends in vegetation activity were assessed using the non-parametric Mann-Kendall trend test to identify upward or downward trends in the time series. The Theil-Sen Slope Estimator was subsequently applied to determine the magnitude and direction of the detected trends.The results showed that all four cities expanded their urban green spaces over the past 40 years, with Barcelona exhibiting a particularly substantial increase. Normalized NDVI values revealed an earlier occurrence of peak NDVI and decreases during summer months in certain years, indicating a possible link to drought events. Statistically significant increases in NDVI were observed in March, April, October, and November, indicating both an earlier onset and later offset of the growing season.Overall the study shows the current changes in plant phenology and developments of urban green infrastructure under climate change. Integrating remote sensing of vegetation with urban water management can support more efficient and adaptive management strategies for irrigating urban green spaces.

Climate change poses an increasing challenge to the sustainable management of urban green infrastructure. Rising air temperatures, changing precipitation patterns and an increasing frequency and intensity of droughts lead to greater water stress for urban vegetation and consequently a higher demand for irrigation. Urban green infrastructure can only provide its multifunctional ecosystem services, such as cooling, when sufficient water is available. This highlights the importance of reliably assessing future irrigation requirements. This work presents a methodological framework for the spatial and temporal estimation of irrigation requirements for urban green infrastructure under current and future climatic conditions.The presented approach is based on a quantitative assessment of irrigation deficit, which is defined as the difference between the water demand of the vegetation and the amount of effective precipitation. The methodological framework integrates evapotranspiration-based, vegetation-ecological and hydrological components, following established scientific approaches [1]. Reference evapotranspiration is calculated using the Hargreaves equation. Additionally, the study systematically assesses scenario-based changes in irrigation demand resulting from alternative urban green infrastructure development pathways.Vegetation-specific water demand is estimated using the landscape coefficient approach. For this purpose, specific landscape coefficients were derived for typical types of urban green infrastructure, integrating the effects of vegetation type, planting density, and water stress into a multiplicative coefficient. This enables a differentiated representation of the variety of vegetation structures and management strategies found in urban green spaces. Natural water supply is accounted for by estimating effective precipitation using the NRCS Curve Number method, which characterizes runoff and retention processes in urban areas and quantifies the proportion of precipitation available within the root zone.The spatial implementation is carried out within a grid-based framework with a spatial resolution of 100 m × 100 m across three case studies. Within each grid cell, the proportions of different vegetation types, the associated normalized difference vegetation index (NDVI), land use information, and soil parameters are compiled. Area-weighted vegetation coefficients and hydrological parameters are then aggregated to the grid areas, which serve as the basis for irrigation calculations.Analyses are performed for a historical reference period (1991–2020) and a future period (2031–2060) under different climate change scenarios (RCP2.6, RCP4.5, and RCP8.5). This allows a systematic evaluation of climate-driven changes in irrigation requirements. The results are evaluated monthly and visualized using box plots to illustrate changes in irrigation requirements and associated uncertainties. The results show a potential increase in irrigation demand in the case studies, with scenario-specific differences. In addition, the influence of different developments in green infrastructure on irrigation requirements is highlighted.Overall, the developed methodology provides a scalable, integrated, and scientifically robust tool for assessing the irrigation requirements of urban green infrastructure.Acknowledgements: The presented research is funded by the Federal Ministry for Agriculture and Forestry, Climate and Environmental Protection, Regions and Water Management Republic of AustriaReferences:Cheng, H.; Park, C.Y.; Cho, M.; Park, C. Water Requirement of Urban Green Infrastructure under Climate Change. Science of The Total Environment 2023, 893, 164887, doi:10.1016/j.scitotenv.2023.164887.

Urban greening is a cornerstone of climate adaptation strategies, yet its long-term sustainability under changing vegetation dynamics remains poorly understood. This study analyzes 40 years of Landsat data (1984–2024) using normalized difference vegetation index (NDVI) time series to quantify changes in vegetation extent, phenology and interannual stability across four European cities (Paris, Graz, Barcelona and Birmingham). The study investigates long-term phenological trends in heterogeneous urban green spaces. Results showed similar developments in greening measures at all four study sites: In Birmingham, Paris and Barcelona, vegetation extent increased by 12 to 23 absolute percentage points, while Graz showed a moderate increase of 4 percentage points. A general tendency towards a longer growing season was observed across the study sites, driven by directional changes towards an earlier Start of Season (SOS) and a delayed End of Season (EOS), although the magnitude and statistical significance varied between cities. Barcelona exhibited pronounced summer NDVI declines, whereas peak vegetation activity occurred earlier in Paris and slightly later in Birmingham. Interannual variation showed greater differences in smaller, fragmented open green spaces (Coefficient of Variation ≈ 0.3) compared to larger tree-dominated parks (Coefficient of Variation ≈ 0.1). These findings provide a harmonized long-term assessment of urban vegetation dynamics. European cities are becoming greener while simultaneously experiencing shifts in vegetation activity and, depending on location, strong declines during summer months. These long-term changes highlight the importance of considering vegetation dynamics when planning resilient urban green spaces under a changing climate.

Climate change, demographic development, increasing urbanization and growing tourism pose complex challenges for the water supply. To address these challenges, this study carried out a scenario analysis for a case study in Austria. For this purpose, different scenarios were derived that consider different trends in climate change, population growth, urban development, and tourism development. To estimate the change in peak water demand due to climate change, a random forest regression model was derived. The model uses climate indices such as hot days and mean air temperature as explanatory parameters for varying water demand. The model was trained and tested using historical water demand records. The quality of the modeling approach was evaluated using common methods such as the mean absolute percentage error. To predict the future water demand under climate change, climate projections for Austria from the RCP4.5 and RCP8.5 climate change scenarios were used. Different population trends were considered for the scenarios, ranging from a decline to a scenario with strong growth. In the tourism sector, a range from minimal growth in the number of overnight stays to a significant increase was assumed. For the industry, a range from minimal growth to a significant increase in the future was also considered. Various scenarios were developed that take into account the different developments of the individual factors and their range. By including the range of factors, the uncertainties in their future development are also represented. For each scenario, changes in peak water demand were derived for the period 2031-2060. The scenarios provide a variety of outlooks, ranging from minimal to significant changes in peak water demand. The results show a range of possible water demand developments for each scenario, given the uncertainties in the underlying factors. Several factors have been identified as critical to the development of future peak water demand. These include population growth, climate change, and, in some areas, seasonal tourism. The development of the housing situation is also an important factor, as water consumption differs significantly between residents of single-family homes and those of apartment buildings. Depending on the development of the housing situation, water demand can fluctuate considerably. Depending on the scenario, the future average water demand in one study site may increase by 3% to 15%. Population growth combined with urban development and the effects of climate change have been identified as the key factors for demand increase. By considering a variety of possible developments, the analysis provides a good basis for long-term water supply planning and can be used to raise awareness in a region for sustainable housing development