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. 2024 Nov 19;14:28666. doi: 10.1038/s41598-024-79938-3

Effective management of urban water resources under various climate scenarios in semiarid mediterranean areas

Ioanna Nydrioti 1, Ioannis Sebos 1,✉, Gianna Kitsara 2, Dionysios Assimacopoulos 1
PMCID: PMC11577078  PMID: 39562679

Abstract

Climate change has a significant impact on water resources, making it essential to re-evaluate water management strategies and incorporate climate scenarios in assessments. The Municipal Department of Aigeiros is located in the northern part of Greece. Water consumption is high in Aigeiros and the increased future temperatures projected during the summer period will create significant pressures on water resources. The water resources management study of the region is carried out using the simulations of the RCA4 Regional Climate Model (RCM) driven by the HadGEM-ES global climate model of the Met Office Hadley Centre (MOHC) under 3 different climate emission scenarios, namely RCP 2.6, RCP 4.5 and RCP 8.5. For the simulation of the urban water balance of Aigeiros, Komotini, Greece and the assessment of water demand and supply for three climate scenarios (RCP 2.6, 4.5, and 8.5) over a 30-year period, the Aquacycle software was used. The data used in the assessment included projected climatic conditions for the area (i.e., precipitation and evapotranspiration), domestic water consumption, and natural and spatial characteristics. The results indicate that drinking water demand is likely to increase in the coming decades for RCP 4.5 (1323 m3/d for 2041–2050) and RCP 8.5 (1330 m3/d for 2041–2050) scenarios compared to 2020 (1320 m3/d). However, simulations for water supply suggest an increase in groundwater recharge in the future, but also the potential for long drought periods during summer months in RCP 4.5 and RCP 8.5 scenarios. The simulation results show both the current situation and the climate scenarios and can be the reference basis for recording the different types of water consumption in urban areas. Therefore, it is possible to control and predict how much of the total consumption is due to the consumer usage profile within a household or to the irrigation needs of green areas in line with the climatic conditions, consumer behavior and technical parameters.

Keywords: Municipal water demand and supply, Climate change adaptation, Future projections, Aquacycle software, Aquifer recharge

Subject terms: Climate-change impacts, Projection and prediction

Introduction

Water scarcity is becoming an increasingly pressing issue due to the impacts of climate change. According to reports from UNESCO and FAO, over two billion people currently experience high water stress, a situation expected to worsen due to rising global temperatures and shifting precipitation patterns (UNESCO1, FAO2). Additionally, changes in precipitation patterns are exacerbating the problem by causing more intense droughts and making it increasingly difficult for people and communities to access clean water. This is particularly concerning as the global population continues to grow, increasing the demand for water and putting further strain on already limited resources. Regions with semi-arid climates, such as Mediterranean areas, are particularly vulnerable, as the combined effects of population growth and climate change intensify the strain on already limited water resources. Global models project that water demand will continue to increase due to both human consumption and agricultural needs, while water availability decreases in many regions due to higher evaporation rates and altered rainfall patterns (UNESCO3). The consequences of this are far-reaching and can have serious impacts on agriculture, energy production, and human health and well-being. Thus, finding sustainable solutions to manage water resources is becoming increasingly important in the face of these challenges4–6.

It is critical that we take immediate action to mitigate the devastating impacts of climate change and ensure that every person has access to clean and safe water. This requires a multi-faceted approach that incorporates improvements in water management practices, increased investment in infrastructure and technology to enhance water security, and comprehensive education and awareness campaigns to educate communities about the importance of water conservation and the dangers of climate change. Additionally, it is imperative that we take decisive steps to reduce greenhouse gas (GHG) emissions, which are the primary cause of global warming and the escalating frequency and intensity of extreme weather events. The evaluation of the effects of mitigation efforts is crucial in understanding the potential benefits and impacts of different strategies. Only by taking these necessary actions can we secure a sustainable future for communities across the world7–9.

Water resources in urban areas face increasing pressure from climate change, with phenomena such as prolonged droughts, extreme rainfall events, and floods disrupting water supply systems and contaminating water bodies, ultimately threatening water security and public health10–12. In response, cities across the globe, from Australia to South Africa and the southwestern United States, are adopting integrated water resource management strategies to address these challenges. These strategies include a mix of traditional and innovative approaches such as rainwater harvesting, wastewater reuse, and groundwater recharge, which are essential to safeguarding water resources13,14. As climate models predict more frequent droughts and changes in water availability, the need for such measures becomes even more critical15.

Research has highlighted the importance of addressing both technical and governance aspects of water management. For example, Alvarado et al.16 examined water management at the community level in rural areas, identifying barriers and opportunities in integrating water quality monitoring with broader management strategies. In urban contexts, Fulazzaky et al.17 stressed the need to strengthen governance structures and water management practices to mitigate the impacts of changing precipitation patterns and extreme weather events, ensuring that urban water systems are more resilient in the face of climate change.

In Mediterranean regions, particularly in southern Europe and North Africa, water management is heavily reliant on seasonal rainfall. Long, dry summers combined with higher water demands place significant pressure on urban water supply systems18. Research in Southern Europe has demonstrated that climate change exacerbates these challenges, particularly by impacting critical water sources like karstic aquifers. For instance, Valdes-Abellan et al.19 used the KAGIS model to simulate the hydrodynamic response of karstic aquifers to climate change, highlighting the reduction in water availability due to decreased precipitation and rising temperatures. Incorporating climate change projections into water management strategies is therefore essential to ensure long-term sustainability in regions like Spain and Italy20. Globally, other semi-arid regions, such as parts of Australia and the Middle East, are adopting similar approaches, exploring policy measures and technology-driven solutions to reduce water loss and improve efficiency21–24.

In areas where temperatures are rising, cities may need to implement measures to reduce water loss through evaporation. For example, shading or irrigation systems can be used to reduce evaporation and increase water efficiency. Additionally, cities may also need to consider how to reduce water consumption by promoting more efficient appliances, and encouraging water-saving behaviors among residents (Xueling et al., 2022;18.

Additionally, cities may need to invest in more resilient infrastructure to withstand extreme weather events, such as floods and hurricanes, to protect water resources and ensure continuity of supply. For example, this can include building more robust water treatment plants and water supply networks that can withstand extreme weather events and protect against contamination. It can also include building more resilient water storage infrastructure, such as dams and reservoirs, to store water during times of abundance for use during times of scarcity13, Wang et al., 2023).

Overall, urban water resources management must be adaptable, proactive and take into account the different possible future scenarios of climate change. This requires not only a comprehensive understanding of the current water resources and infrastructure, but also an ability to anticipate and plan for future challenges and opportunities. This requires a holistic approach to water resources management that considers not only the physical infrastructure, but also the social, economic, and environmental factors that affect water resources25,26.

The current approaches to urban water management primarily focus on meeting water supply demands without adequately considering the potential impacts of climate change on future water demand. However, with the constantly changing climatic conditions, it is imperative that water resource studies incorporate future emissions scenarios and forecasts of water demand in different climatic conditions. This paper aims to explore the current state of water resource studies and highlight the importance of incorporating climate change impacts in the planning and management of urban water systems27.

Given the global importance of addressing water scarcity in urban settings under changing climate conditions, this paper investigates the effective management of urban water resources in semi-arid Mediterranean areas. Specifically, it focuses on the case of Aigeiros, a municipal department in northern Greece, and assesses water demand and supply dynamics under different climate scenarios using the Aquacycle software. The study contributes to the growing body of knowledge on urban water resource management in the context of global climate change, offering valuable insights for both local and international water management strategies.

Materials and methods

Site description

The Municipal Department of Aigeiros is situated in the municipality of Komotini, located in the northern part of Greece, specifically in the Region of East Macedonia and Thrace (Fig. 1). Spanning an area of 51.1 square kilometers, is comprised of 11 settlements and it is home to 3493 permanent residents, as per the 2011 census28. Aigeiros is also a tourist destination that attracts numerous seasonal residents and visitors, particularly during the summer months.

Fig. 1.

Fig. 1

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Map of the study area in the Municipality of Komotini i.e., (1) Municipal Department of Komotini; (2) Municipal department of Aigeiros; (3) Municipal department of Neo Sidirochori.

The region boasts a Mediterranean climate, marked by warm winters, hot and dry summers, and a distinct arid period during the summer months. In contrast, the winter months are characterized by a higher level of precipitation, with the wettest month experiencing three times more precipitation compared to the driest month. According to data provided by the Komotini Municipal Water Supply Company, the daily water usage in Aigeiros is approximately 1320 cubic meters. Urban water needs are addressed by groundwater abstractions from 10 boreholes. The groundwater potential provides up to 480 cubic meters of water per hour (Fig. 2 and Table 1).

Fig. 2.

Fig. 2

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Location of boreholes in Aigeiros (Retrieved from Google Earth).

Table 1.

Groundwater abstraction flow rate of water supply boreholes.

Borehole Water supply (m3/h)
B1 50
B2 40
B3 70
B4 40
B5 40
B6 70
B7 70
B8 40
B9 40
B10 20
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The total water consumption in the Aigeiros municipal department amounts to 1,320,000 lt/d. According to the census by the Hellenic Statistical Authority in 2021, the permanent population of Aigeiros is 3,493 inhabitants. The per capita consumption is estimated at 377.9 lt/day. Average water consumption in Greece for 2020 is 294.2 lt per person per day based on Eurostat, while national legislation permits for rational water use, range from 100 to 250 lt/person/d.

Moreover, substantial water quantities are utilized in agricultural production within the region, leading to notable degradation in both quality and quantity of the aquifer systems that predominantly cater to the area’s water demands29–31. While the boreholes outlined in Table 1 primarily serve domestic water needs, the broader area is supported by 612 groundwater wells dedicated to agricultural water usage29.

Future Emission Scenarios (RCP) & Regional Climate Model (RCM)

A climate scenario is a representation of future concentrations of greenhouse gases, based on a series of assumptions about the causes of these emissions (social, political, economic, etc.) (IPCC, 2014). Their creation aims to investigate the possible effects of human interventions on the future climate. Climate projections are the main tool for developing climate scenarios. However, additional information is needed to create reliable scenarios. It is worth emphasizing that a scenario is not a forecast of the future state of the climate but rather a realistic assessment as possible.

This study utilized three greenhouse gas (GHG) concentration trajectories adopted by the IPCC (Intergovernmental Panel on Climate Change), specifically, the Representative Concentration Pathways (RCP) RCP 2.6, RCP 4.5, and RCP 8.5, for future simulations up to the year 2050. The three RCP scenarios have been introduced by the Fifth Assessment Report (AR5)32 to specify GHG concentrations and corresponding emission pathways for several radiative forcing targets (Table 2).

Table 2.

Description of the RCP Scenarios44–46.

Scenario Description
RCP 2.6 Maximum RF in 2040 at 3 W/m2 and stabilization at 2.6 W/m2 in 2100. Greenhouse gas emissions are constantly decreasing until 2100
RCP 4.5 RF at 4.5 W/m2 in 2100 and its stabilization in the middle of the next century. Little and gradual decline in GHG emissions is expected by 2100
RCP 8.5 Increase of RF to 8.5 W/m2 by 2100. Greenhouse gas emissions increase significantly by 2100
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The future emission scenarios (RCP 2.6, RCP 4.5, RCP 8.5) indicate the radiative forcing (RF) predicted in 2100. These climate scenarios were developed to lead to a specific radiative forcing by 2100 with a defined combination of greenhouse gas and aerosol concentrations (IPCC,32).

This study used three climate emission scenarios, RCP 2.6, RCP 4.5, and RCP 8.5, in simulations of the RCA4 Regional Climate Model (RCM). Climate simulations through RCMs were developed within the framework of the EURO-CORDEX program of the international CORDEX initiative, funded by the Climate Research Program (WRCP) to form an internationally coordinated framework for the production of improved climate forecasts regionally for all land areas worldwide.

As observational reference for evaluating the simulated temperature and precipitation data from a sub-set of GCMs/RCMs pairs (here after RCMs), measurements of mean air temperature and precipitation of the “Alexadroupoli” meteorological station (lon 25.95, lat 40.86) located in the nearby area of Aigeiros-Komotini were used. The observational daily meteorological data from the Alexadroupoli station, available from 1974 to 2004, were obtained from the Hellenic National Meteorological Service (HNMS).

Daily data regarding precipitation and temperature were retrieved from a set of five state-of-the-art RCM simulations carried out in the frame of EURO-CORDEX (Coordinated Regional Climate Downscaling Experiment) (http://www.euro-cordex.net) or available at C3S of Copernicus climate data store (CDS) (https://cds.climate.copernicus.eu), with a horizontal resolution of about 12 km (0.11°) for the same period (1974–2004). RCM simulations were retrieved for the closest model grid point of the Aigeiros area (lon 25.1981, lat 40.9672), near the long-term meteorological station of Alexadroupoli.

Specifically, these five GCMs/RCMs pairs (here after RCMs) used in this study are: The RCA4 regional climate model of the Swedish Meteorological and Hydrological Institute (SMHI) driven by 2 different global climate models: (1) the HadGEM2-ES of the Met Office Hadley Centre (RCA4-MOHC), (2) the EC-EARTH of the ECMWF, European Centre of Medium Range Weather Forecast (RCA4-ICEARTH), (3) The HIRHAM5 regional climate model of the Danish Meteorological Institute (DMI) driven by EC-EARTH global climate model (HIRHAM5-ICEARTH), (4) The CCLM4-8–17 regional climate model of the Danish Meteorological Institute (DMI) driven by EC-EARTH global climate model (CCLM4817-ICEARTH) and (5) the RACMO22E regional climate model of the Royal Netherlands Meteorological Institute (KNMI) driven by the CNRM-CM5 global climate model of the Meteo France Institute (RACMO22-CNRM-CM5).

For the evaluation analysis regarding the models’ performance, comparisons were made of daily and monthly mean air temperature and precipitation observations from the station with the corresponding simulations of the five RCMs, extracted from the closest model grid point to the Alexadroupoli meteorological station. The pattern of monthly average temperature values for the period 1974–2004 is similar with slight underestimation between the simulations of the five RCMs and the meteorological observations from Alexadroupolis station (Fig. 3). Good correlations were observed in daily Tmean values, with squared correlation coefficients (R2) that were 0.69 for HIR-HAM5-ICEARTH) 0.7 for CCLM4817-ICEARTH and RACMO22-CNRM-CM5, 0.72 for RCA4-ICEARTH, and 0.74 for RCA4-MOHC. Additionally, the low magnitude percentage bias (PBIAS) values were 0.5 for RCA4-MOHC, around -5 for CCLM4817-ICEARTH and HIRHAM5-ICEARTH, and -11 for RACMO22-CNRM-CM5 and RCA4-ICEARTH. These values indicate relatively accurate model simulations for daily temperatures.

Fig. 3.

Fig. 3

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Monthly average (a) mean air temperature and (b) total precipitation from Alexadroupoli meteorological station observations (black line) and the five RCM simulations (colored lines).

Comparisons for total monthly precipitation (PR) patterns (Fig. 3) showed similarities (with R2 around 0.8 for almost all RCMs) and some overestimation between observations and most of the RCMs data for the period 1974–2004. PBIAS values between daily PR simulation values from the five RCMs and the corresponding observations are around 20 (CCLM4817-ICEARTH, RCA4-MOHC, HIRHAM5-ICEARTH) and 45 (RACMO22-CNRM-CM5) indicating overestimations, while RCA4-ICEARTH shows underestimations (-33).

Two of the RCMs namely the RCA4-MOHC and CCLM4817-ICEARTH (RCA4-MOHC and HIRHAM5-ICEARTH) were closer to the temperature (or precipitation, respectively) evolution of the meteorological station.

Following the evaluation of all climate simulations, it was decided to proceed with the model giving the best results (statistically) for the Aigeiros region, namely the RCA4_MOHC as the best performing model for the Aigeiros area.

The MOHC model, in which each month consists of 30 days, was used to simulate daily values of mean air temperature (in oC), total precipitation (in mm) and sunshine duration (in sec) for the area of Aigeiros in a horizontal analysis of about 12 km, over a 30-year period (2021–2050) and for the 3 aforementioned RCP scenarios.

Method for simulating the water balance in urban areas

The urban water cycle encompasses drinking water supply systems, as well as the drainage of wastewater and rainwater. The water balance approach takes into account the full demand for water in an area and the quantity of wastewater and rainwater produced. The approach is based on the application of the principle of conservation of water mass in an area, the boundaries of which have been determined according to the needs of each study. The concept of water balance is used to capture the route of water in the water cycle for a defined area and for a defined time step33.

The water balance in the Aigeiros Municipal Department was estimated by calculating the demand and supply of drinking water for the three climate scenarios using the Aquacycle software. Aquacycle simulates the processes that take place in an urban area, based on the concept of water balance as presented in Fig. 4.

Fig. 4.

Fig. 4

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Urban water system as simulated by Aquacycle44.

The urban water cycle receives inputs through precipitation and water supply, which participate in the various processes of the system, e.g., drinking water, irrigation needs. The outputs of the system are evaporation, rainwater runoff and urban wastewater production. The simulation uses a daily time step to calculate the various urban water balance flows and the analysis is based on 3 management levels, the Unit Block, the Cluster and the Catchment (Fig. 5). A Unit Block represents the lowest scale of consumption and may include one or more buildings, impermeable surfaces, and green spaces. It could be a house, industrial facility, commercial establishment, or public facility. A Cluster is a neighborhood made up of a collection of Unit Blocks and encompasses roads and open spaces. A Catchment encompasses multiple Clusters34.

Fig. 5.

Fig. 5

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Spatial scales used in Aquacycle44.

Input data

The input data required for the simulation are the domestic water consumption, climatic data for the area, and natural and residential/spatial characteristics. The data required for the simulation and the model sequence are presented in Fig. 6, which is in line with similar studies reported in the literature35.

Fig. 6.

Fig. 6

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Flowchart of data and model sequence for model outputs assessment.

Input data: domestic water consumption

Household Water Usage represents the total volume of water utilized within the confines of a residential dwelling, e.g., for the kitchen, bathroom, washing machine and toilet. The distribution of this total value among the individual internal uses at Unit Block level is based on literature data in order to attribute some representative values as presented in Table 336.

Table 3.

Distribution of the total water consumption for the internal uses of a Unit Block36.

Kitchen (%) Bathroom (%) Toilet (%) Washing machine (%) Total (%)
22 34 18 26 100
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Input data: climatic data

The climatic data required for the Aquacycle simulation are the daily values of precipitation and potential evapotranspiration. The time series range and the simulation duration are 30 years (i.e., 2021–2050). For the RCP 2.6 climate scenario, high precipitation is observed during the fall and winter seasons, while the precipitation pattern remains consistent throughout all three decades as presented in Fig. 7. Projected precipitation values were also compared to projected precipitation data during 1997–2007.

Fig. 7.

Fig. 7

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Precipitation in the Municipal Department of Aigeiros for the RCP 2.6 scenario.

In the RCP 4.5 climate scenario, there is a uniform distribution of precipitation for the 3 decades. The months of January, February, March, and November experience increased precipitation when compared to the RCP 2.6 scenario, while for the months of May, June, July and September it is lower. In addition, the winter months’ experience increased precipitation intensity, whereas the summer months witness a noticeable de-crease in precipitation, compared to the precipitation recorded in the period 1997–2007 (Fig. 8).

Fig. 8.

Fig. 8

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Precipitation in the Municipal Department of Aigeiros for the RCP 4.5 scenario.

For the RCP 8.5 climate scenario, there is an almost uniform distribution of precipitation throughout the decades, except of a noticeable rise in October 2031–2040. In this scenario the greenhouse gas emissions increase significantly until 2100, therefore there are more intense occurrences as compared to the RCP 4.5 scenario, notably in the months of February, March, April, May, September, October, and December, with a heightened effect during the 2041–2050 decade (Fig. 9).

Fig. 9.

Fig. 9

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Precipitation in the Municipal Department of Aigeiros for the RCP 8.5 scenario.

Evapotranspiration in an urban area is difficult to be simulated and calculated due to the complexity of the surfaces and the microclimate of the area. In such cases, evapotranspiration values are based on indirect calculations that require different climatic data such sunlight duration and mean temperature. Evapotranspiration in the present study was estimated by the Thornthwaite method on a daily basis by entering theoretical sunshine (hours/day) and average temperature information. The following figures show the average values of potential evapotranspiration per month for the years 2021–2030, 2031–2040, 2041–2050 for the climate scenarios RCP 2.6 (Fig. 10), RCP 4.5 (Fig. 11), and RCP 8.5 (Fig. 12).

Fig. 10.

Fig. 10

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Potential evapotranspiration in the Municipal Department of Aigeiros for the RCP 2.6.

Fig. 11.

Fig. 11

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Potential evapotranspiration in the Municipal Department of Aigeiros for the RCP 4.5.

Fig. 12.

Fig. 12

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Potential evapotranspiration in the Municipal Department of Aigeiros for the RCP 8.5.

Input data: natural and residential characteristics

The simulation of Aigeiros takes into account its natural and residential features to provide an accurate representation of the different land uses within the area. In Aquacycle, water flows through different processes that are part of the urban water cycle. The processes of interception, storage, infiltration, inflow and drainage are modelled using conceptual stores with parameters37. Such parameters are the proportion of land covered by structures, including buildings and impenetrable surfaces such as roads and sidewalks, and the presence of permeable open areas covered with vegetation, such as gardens and parks. Surfaces are divided into pervious and impervious. Impervious surfaces (e.g., roofs, roads) are presented as single stores that overflow when reach a peak. Pervious areas are divided into areas which produce runoff during rainfall and those which do not37.

The model requires additional information, such as the demographic data such as the number of residents per household and the number of buildings, as well as the amount of water consumed per individual. The natural and residential characteristics needed for Aquacycle as well as the data sources from which the data were retrieved, are presented in Table 4.

Table 4.

Parameters representing natural and residential characteristics44 and their data sources.

Scale Parameter Unit Data sources
Unit Block Number of unit blocks Number Demographical data
Average household occupancy Number of people Demographical data
Area of unit block m2 Digital maps
Garden area of unit block m2 Digital maps
Roof area of unit block m2 Digital maps
Pavement area of unit block m2 Digital maps
Percentage of the garden area irrigated % Estimation
Cluster Total area m2 Digital maps
Road area m2 Digital maps
Public open space irrigated % Estimation
Water losses % Literature data
Catchment Total area km2 Digital maps
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The number of houses in all the settlements of the department is 2,896, the area of agricultural land is estimated at 37 km2 and the length of highways at 250 km. The entire area of the Municipal Department of Aigeiros has been divided into three clusters, each with its own distinct spatial and demographic characteristics, for the purposes of the simulation. The population of each cluster was calculated by summing up the individual population of each settlement belonging to each cluster. Therefore, for cluster 1 (involving the settlements of Aigeiros, Messouni, Meleti) the population is 1659 inhabitants, for cluster 2 (involving the settlements of Kallisti, Nea Kallisti, Porpi, Agrotiko Orfanototrofio) the population is 1010 inhabitants and for cluster 3 (involving the settlements of Arogi, Glyfada, Mesi, Mesi Beach, Fanari) the population is 842 inhabitants. The distribution of land uses within the boundaries of a cluster is classified in areas covered by buildings, road network and open areas. The area covered by buildings is further broken down into the roof, the paved area—sidewalk and the garden—area not covered by buildings. For each surface category there are also the corresponding parameters that characterize them (i.e., roof area (m2), garden area (m2), garden open space irrigated (%)). In the simulation it has been assumed that the open green areas are not irrigated by the water supply network and that 10% of the garden area of a house is irrigated with water from the water supply network. The number of buildings per cluster was calculated based on the population of each cluster and the average capacity of each house, which for Greece is 2.7. The area of the unit block was calculated from measurements on digital maps for each Cluster as well as the area of the garden, the area of the roof and the area of the sidewalk.

Model calibration–uncertainties

The calibration process entailed iteratively defining parameters critical to the main model output i.e., water use. Through a trial-and-error approach, key parameters such as pervious storage capacity, effective roof area, effective paved area, road area initial loss, effective road area, percentage of surface runoff as inflow, infiltration index, and trigger-to-irrigate ratios for garden and open space areas were identified. The aim was to establish a set of representative values that minimize model error. To achieve this, certain assumptions were made: all impervious areas were assumed to be 100% effective in runoff production, and the trigger-to-irrigate ratio for garden and open space areas was set at a very high level, indicating maximum soil moisture in the irrigated area. For the infiltration rate the value of 0.2 was chosen, based on a similar study in Greece since it depends on the network condition and construction materials34.

Results

Water demand for the 3 RCPs

The total water demand for a specific time frame is the result of the water use in each household, the irrigation needs (in case of not being covered by rainfall) and the losses of the water supply network. Water consumption in households constitutes the largest proportion of urban water consumption (about 1,043 m3/day). The irrigation needs covered by the water supply in the municipal department vary according to the levels of precipitation and evapotranspiration. A higher rate of water consumption for irrigation occurs mainly in the summer months when rainfall levels are significantly limited.

The main result of the simulation is the water demand in the municipal department of Aigeiros for all 3 climate scenarios (RCP 2.6, RCP 4.5, RCP 8.5) as shown in Fig. 13. The blue line represents the existing (for 2020) water demand in Aigeiros which amounts to 1,320 m3/day. For the RCP 2.6 scenario, where the gas emissions are reduced substantially over time, it seems that water demand will be lower than it was in 2020. In RCP 4.5 scenario, for which greenhouse gases remain stable, the demand for water will experience a decrease by 2040, however, it is expected to increase by 5 cubic meters per day in the period of 2041–2050 when compared to the demand in 2020. For scenario RCP 8.5, in which Greenhouse gases increase significantly, there is a significant increase in water consumption reaching almost 1330 m3/d. Water consumption in each scenario is compared with the current metered consumption in Aigeiros for 2020, as shown in Fig. 13.

Fig. 13.

Fig. 13

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Water consumption in the Municipal Department of Aigeiros from 2021 to 2050 for 3 RCPs.

Water consumption in Aigeros is very high in relation to its population, compared to the national legislation permits for rational water use, which ranges from 100 to 250 lt/person/d and average water consumption in Greece (294.2 lt/person/day) This trend is probably a result of the significant water losses in the water distribution network are caused by leaks, breaks, and unauthorized water usage. An additional factor of increased water consumption is the unaccounted for authorized water uses, such as municipal irrigation and maintenance, etc. It is difficult to determine these losses, as it is difficult to estimate the quantities due to incomplete measurements, water use for public services, as well as the quantities of water used for firefighting.

Water supply for the 3 RCPs

The water availability in the Aigeiros Municipal Department is solely reliant on the groundwater source obtained from 10 boreholes. This means that the supply depends on the recharge rate of the groundwater aquifer and its overall availability.

In the simulation, the initial water storage is assumed to be the amount of water stored in the aquifer at the first time step. The value of the renewable stocks of each system is used as the initial storage, meaning it is believed that the aquifer level is at its highest point when the simulation begins. Thus, the drilling is based on renewable resources and not on the permanent reserves of the groundwater aquifers. In this simulation, the water supply is defined as the total renewable reserves of the underground aquifers, also known as the groundwater aquifer recharge, which is the total amount of water that infiltrates the aquifer and is accessible for use38.

The average maximum recharge and consequently the water that can be pumped from the 10 boreholes of Aigeiros is presented in Fig. 14 for the 3 climate scenarios (RCP 2.6, RCP 4.5, RCP 8.5) and for the intervals 2021–2030, 2031–2040, 2041–2050. The recharge rate of the groundwater aquifer is closely tied to precipitation levels, which are estimated for the entire Aigeiros area, including both urban and non-urban areas. As a result, the results of the recharge calculation will be larger in scale compared to the demand for drinking water.

Fig. 14.

Fig. 14

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Groundwater aquifer recharge of the Municipal department of Aigeiros from 2021 to 2050 for 3 RCPs.

The water available for pumping is shown to increase in each climate scenario (RCP), and the largest quantities of available water are observed in the extreme (RCP 8.5) climate scenario. This is probably due to the rapid increase in heavy precipitation mainly during the winter months seen in the RCP 8.5 scenario.

Discussion

Based on the results of the simulation, for the RCP 2.6 climate scenario (reduction of greenhouse gases), drinking water demand in the Municipal Unit will have a small decrease compared to 2020 while for the RCP 4.5 scenario, in which emissions remain almost constant there will be a small increase of water demand. The largest increase in water supply demand relative to 2020 is foreseen in the RCP 8.5 climate scenario, in which greenhouse gases increase.

Future climate simulations based on RCPs (Representative Concentration Pathways) indicate that rising greenhouse gas emissions cause more frequent and intense extreme weather, especially prolonged droughts. This leads to an overall increase in global temperature, directly affecting the demand for drinking water which is expected to rise if greenhouse gas emissions continue at their current levels or increase further. A slight increase in drinking water demand is anticipated in Aigeiros. However, it is expected that the demand for drinking water will significantly escalate during future summer months, due to rising temperatures and the influx of seasonal tourists and residents, which could not be included as a variable in the Aquacycle model. Consequently, this modest increase in water demand projected for future climate scenarios suggests a trend that will be further intensified during the summer months, particularly in the face of heightened population loads.

The Municipal department of Aigeiros is particularly vulnerable to the impacts of climate change. The yearly groundwater recharge in the Aigeiros Municipal Department is forecasted to grow over time under various climate scenarios, however, the monthly recharge pattern reveals longer droughts during the summer months. This emphasizes the need to guarantee adequate water reserves in Aigeiros in case of extended drought (low rainfall) to secure the supply of drinking water. In addition, since the groundwater recharge is accounted for the hole Aigeiros area, groundwater is used also for agricultural purposes. Therefore, despite the growing groundwater recharge, domestic water use is highly competing with agriculture water use and its management could be further investigated connected to the competing and dominant agricultural water use for the specific study area.

Modelling of flood hydrographs and drought characteristics in different future emission scenarios39 could be combined in future studies with the projected groundwater aquifer recharge results, so as to better map the foreseen impacts and uptake targeted adaptation action plans. Also, non-stationary behavior in water consumption should also be accounted for in future water resources managements studies40 involving future climate scenarios, as trends in domestic water consumption may vary between summer and winter months (i.e., increased needs in summer period). In this study, only irrigation needs in a unit block basis (i.e., irrigation of garden) follow a non-stationary approach as they are interconnected to monthly precipitation levels.

To address these challenges, it is essential to have accurate and up-to-date information on water consumption patterns in the city of Aigeiros. Simulation results that encompass the current status and climate scenarios can serve as a basis for comparison for tracking various water usage in urban areas. Utilizing tools such as the Aquacycle software, it is feasible to monitor and forecast the portion of total consumption that stems from household consumer behavior, the portion related to green area irrigation needs, and the part influenced by climate and technical factors. This information can also be used as a tool for continuous calibration and feedback with information from the actual system.

Prolonged summer droughts are foreseen in future emission scenarios, so adequate groundwater aquifer recharge and therefore sufficient drinking water supply through abstraction in Aigeiros could be safeguarded through effective adaptation measures.

One such measure could be the installation of water meters and telemetry systems to keep track of and regulate leaks in the water distribution network and water levels. It is equally important to regularly monitor relevant climate and water management indicators, such as groundwater levels and private borehole numbers, in order to effectively plan and implement additional adaptation strategies. This proactive approach helps ensure a consistent and reliable source of drinking water during periods of drought, promoting the well-being and resilience of communities.

Stakeholder mapping and analysis could also be used as a tool for urban water resources management as it allows managers to identify key actors, their interests and concerns, potential partners for collaboration, and potential risks and opportunities associated with different water resources management strategies. By understanding the interests and concerns of different stakeholders, urban water resources managers can develop targeted strategies for effectively engaging with them and addressing their concerns, and identify potential risks and opportunities for the efficient and sustainable water resources management41.

Conclusions

This paper highlights the importance of understanding the impacts of diverse climate scenarios on water demand and supply dynamics. It presents a robust framework designed to integrate current climate data into water resource management practices effectively. An application example of integrated urban water resources in a water stressed region with Mediterranean climate is presented through the application of the framework in Aigeiros, Komotini in Greece, which could be replicated to various climatic and urban water management contexts. Gathering accurate water consumption data is crucial for effective resource management, with tools such as the Aquacycle software aiding in predicting different aspects of water usage.

Aquacycle constitues a versatile framework capable of application across diverse urban contexts. It integrates water supply, wastewater production, and stormwater drainage into a unified modeling structure. Remarkably, the model exhibits proficiency in accurately simulating water supply and wastewater production, even when employing monthly average evapotranspiration values. However, as outlined in other research studies34, the software does not have the capacity to incorporate short-term changes in water usage and wastewater discharge stemming from monthly fluctuations in population or temporal and spatial shifts in water usage profiles.

Simulation outcomes illustrate the present conditions as well as various climate scenarios, serving as a foundation for tracking diverse water consumption patterns in urban areas. Consequently, this enables effective monitoring and forecasting of the total consumption proportions attributed to household consumer usage profiles, green area irrigation requirements, and factors influenced by climatic conditions, consumer behavior, and technical parameters.

As greenhouse gas emissions continue to rise, the probability of severe extreme weather events, including droughts, escalates, thereby exerting pressure on water resources and accentuating the necessity for targeted adaptation strategies. By proactively addressing water management indicators and employing effective adaptation measures, communities can enhance their resilience to climate change impacts. This approach ensures a reliable drinking water source, promotes the well-being of the population, and supports the long-term sustainability of water resources in the region42,]43.

Finally, it is recommended that further research integrates diverse models and accounts for non-stationary water consumption behavior to develop a comprehensive understanding of the issue. Implementing suitable adaptation measures, including the installation of water meters and telemetry systems, is vital for protecting water supply during droughts. Consistent monitoring of climate and water management indicators will guide the creation and execution of additional strategies.

Author contributions

Conceptualization, I.N. and D.A.; Methodology, I.N., G.K. and I.S.; software, I.N.; Validation, I.N. and I.S.; Formal analysis, I.N., G.K. and I.S.; Investigation, I.N., G.K. and I.S.; Data curation, I.N. and G.K; Writing—original draft preparation, I.N. and I.S..; Writing—review and editing, I.S. and D.A.; Visualization, I.N. and G.K.; Supervision, D.A. All authors have read and agreed to the published version of the manuscript.

Funding

Funding for this research was received from the European Union’s (EU) LIFE program under the Grant Agreement LIFE17 IPC/GR/000006: “Project LIFE-IP AdaptInGR–Boosting the implementation of adaptation policy across Greece” & the Green Fund of Greece. The text reflects only the authors’ views, and the European Union is not liable for any use that may be made of the information contained therein.

Data availability

All data generated or analysed during this study are included in this published article.

Declarations

Competing interest

The authors declare no competing interests.

Ethical approval

All authors have read, understood, and have complied as applicable with the statement on "Ethical responsibilities of Authors" as found in the Instructions for Authors.

Footnotes

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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