Urban water dissipation is a significant part of the urban hydrologic cycle and has a typical natural–social dualistic attribute. Besides natural evaporation, the water dissipation in people's daily life and production process cannot be ignored. This study developed an urban water dissipation model based on different land uses and applied it in urban-built areas in Beijing. The results showed that the water dissipation of buildings and green spaces occupied the dominant position, and the water dissipation intensity of each district exceeded 500 mm, among which the six core districts were 700–1,100 mm. Comparing the water dissipation contribution rate and area rate of each underlying surface, it showed that the water dissipation intensity from strong to weak was building, water surface, green spaces, and hardened ground. According to the dualistic analysis of urban water dissipation, the contribution rates of social water dissipation in the six core districts were 45.3–69.1%, which was higher than the 17.8–36.1% of other suburbs obviously. This study reflected that the higher the degree of regional urbanization, the greater the water dissipation intensity, and artificial water dissipation was the main influencing factor.

  • Developed a city-scale water dissipation calculation model based on urban land types.

  • Urban water dissipation includes traditional natural evapotranspiration and artificial water dissipation.

  • Buildings and green spaces are the major part of water dissipation in urban areas.

  • Regions with a high degree of urbanization in urban areas have greater water dissipation intensity.

Urban region is an area where human activities and the natural water cycle are coupled, and here, the water cycle presents an obvious ‘natural–social’ dualistic attribute (Wang et al. 2013; Zhou et al. 2019a). The water cycle, serving as a vital conduit for energy transfer, exerts a profound impact on urban ecosystems. As the process of urbanization continues to deepen, the population are steadily congregating in urban areas (Molina-Gómez et al. 2022). According to the 2020 report by UN-Habitat, the world will be further urbanized in the next 10 years, with the proportion of the global population residing in urban areas expected to rise from the current 56.2 to 60.4% by 2030. China, among the three major countries, is set to experience substantial growth in its urban population from 2018 to 2050 (United Nations Habitat 2020). In the process of urbanization, humans are progressively altering the Earth's surface, and such activities profoundly impact the near-surface climate by changing the energy and water balance of urban ecosystems (Chelu et al. 2022; Das et al. 2022; Tong et al. 2022). The natural underlying surfaces such as cultivated land and vegetation are gradually transformed into impervious surfaces such as buildings and roads (Sterling et al. 2013; Gao et al. 2020; Wang et al. 2021). The heterogeneity of the underlying surface coupled with the diversity in the processes of social water use makes the urban hydrological process more complex (Hao et al. 2015; Wang & Jia 2016; Wang et al. 2016; Fidal & Kjeldsen 2020). As a necessary part of the urban hydrological process, urban water dissipation refers to the myriad forms of water dissipation occurring in urban areas, serving as a pivotal source of urban water vapor and exerting a profound impact on urban dry and wet island effect (Wang et al. 2016; Zhou et al. 2019a; Luo et al. 2021a). Just like the urban water cycle, urban water dissipation is also divided into two components: one is the evapotranspiration that transpires on the natural underlying surface, including water surface evaporation, vegetation transpiration, and soil evaporation, and the other is the water dissipation engendered through the diverse domestic and production-related water utilization by human activities (Zhou et al. 2019a; Luo et al. 2021b).

Most previous studies believed that urban evapotranspiration predominantly arises from vegetation transpiration in green spaces (Loridan & Grimmond 2012; Jacobs et al. 2015). Many researchers have predicted evapotranspiration in urban areas based on energy balance equations and aerodynamics (Bowen 1926; Thornthwaite & Holzman 1939). The corresponding hydrological models were widely used in the estimation of urban evapotranspiration, including the SIMGRO model, the Urban Forest Effects-Hydrology, the SEBS model, the SPAC model, etc. (Noilhan & Lacarrere 1995; Su 2002; Wang et al. 2008; van Walsum & Veldhuizen 2011). Additionally, experiments have been employed as an important method for vegetation evaporation research. Some scholars have studied the transpiration and water consumption characteristics of urban plants through experimentation (von Allmen et al. 2015; Livesley et al. 2016). As urbanization causes natural vegetation, soil, and water surfaces to be replaced by artificial concrete underlying surfaces, some studies suggested that urban development would significantly reduce urban evapotranspiration (Dow & DeWalle 2000; Hao et al. 2015; Zheng et al. 2020). Nevertheless, it is crucial to recognize that evapotranspiration from natural underlying surfaces represents only a part of the urban water dissipation. Impervious ground and building roofs, as primary urban underlying surface, also contribute to evaporation following rainfall and artificial watering (Ramamurthy & Bou-Zeid 2014; Zhou et al. 2021). In addition to outdoor evapotranspiration, urban water dissipation includes the dissipation generated by various indoor water use activities (Zhou et al. 2018, 2019b), which constitutes a substantial portion of the social side of urban water dissipation (Zhou et al. 2019a). Given the dense concentration of buildings and the high intensity of human activities in urban areas, some researchers proposed the concept of building water dissipation, which believed that the water dissipation inside the building stems from a series of activities such as steam cooking, drying of clothes, water vapor bathing, floor wetting, and so on (Zhou et al. 2018, 2019a, 2019b). After considering the artificial activities, Zhou et al. (2020) calculated the water dissipation in Beijing in 2015, revealing that water dissipation in urban areas was greater than natural evapotranspiration, with water dissipation on the social side accounting for more than 40% in the central urban area. This underscores the pivotal role of artificial water dissipation in total urban water vapor, particularly in highly urbanized regions. Under the background of global urbanization, the connection between human and water use is closer, leading to more intense artificial water dissipation activities, which accelerates the transformation of water from liquid to gas and becoming an integral part of the urban hydrological cycle, directly impacting the urban water balance. However, most of the existing studies focus on evapotranspiration from natural underlying surfaces in urban areas, with limited attention paid to domestic and industrial production water dissipation (Zhou et al. 2017). Thus, it is necessary to quantitatively study the dualistic attribute of urban water dissipation, especially concerning the structure of artificial water dissipation inside buildings.

This study took Beijing as the research area, and analyzed the ‘natural–social’ dualistic attribute of urban water dissipation. It employed an urban water dissipation model to calculate water dissipation for different types at the district scale, comparing the water dissipation contribution rate and area rate of each land use type, and analyzed the water dissipation structure inside buildings. The research results further enrich the understanding of the urban hydrologic cycle and provide a reference for urban water flux calculation.

Urban water dissipation analysis framework

Based on the distinction of the underlying surface, this study divided urban water dissipation types into hardened ground, green spaces, building, water surface, and soil. The hydrological cycle in urban areas is a typical natural–social dualistic coupled system, and a natural–social dualistic analysis framework for urban water dissipation was established, as shown in Figure 1. The water dissipation on the natural side includes the intercepted rainwater evaporation from the hardened ground and buildings, the natural evaporation from the water surface, the natural transpiration of green spaces, the rainwater interception evaporation by vegetation, and the natural evaporation from soil. The water dissipation on the social side refers to artificial water dissipation, including evaporation of sprinkling water on hardened ground, evaporation of artificial irrigation in green spaces, and artificial water dissipation in buildings (daily water use, wetting area, evaporation of human body, water dissipation in industrial production).
Figure 1

Framework of urban water dissipation analysis.

Figure 1

Framework of urban water dissipation analysis.

Close modal

Urban water dissipation model

Based on the urban water dissipation analysis framework, the urban water dissipation calculation model can be obtained by aggregating the water dissipation from various types of underlying surfaces (Zhou et al. 2019a):
(1)
where WD is the annual water dissipation in the region, m3; WB is the annual total volume of water dissipated on urban buildings areas, m3; WH is the annual total volume of water dissipated on hardened ground, m3; WS is the annual total volume of evaporation from bare soil, m3; WW is the annual total volume of evaporation from water surface, m3; WG is the annual total volume of water dissipated on green spaces, m3.
Building water consumption can be expressed by the following formula:
(2)
where WBI is the annual water dissipation inside the building, m3; WBF is the annual evaporation of rainwater retained by the building roof, m3.
(3)
(4)
(5)
(6)
(7)
(8)
where WDU is the annual water dissipation generated by daily water use, m3; WWA is the annual water evaporation from wetting area inside the building, m3; WHB is the annual evaporation from human body, m3; WIP is the annual water dissipation for industrial production, m3; AB is the building area, m2; PH is the sum value of daily rainfall which is less than the maximum depth of rainwater intercepted by hardened ground, mm; is the runoff coefficient; PY is the annual rainfall, mm; D is the days in a year; PN is the number of people using water per day; IP is the daily water dissipation quota per capita, m3; is the proportion of wetting area inside the building; A is the floor area of the building, m2; Df is the water dissipation quota of wetting area, mm; AP is the body surface area of human, m2; Ti is the duration of activity i, h; Ereq is the evaporation required to maintain heat balance at a given core temperature and Emax is the maximal evaporative capacity of the environment, W/m2; WWI is the industrial water withdrawal, m3; WWD is the industrial displacement, m3. The relevant daily water dissipation parameters were obtained from the experiments and survey statistics of Zhou et al. (2017, 2019a). The detailed calculation method of human body evaporation was based on the research of Liu et al. (2022).
The water dissipation of hardened ground can be expressed by the following formula:
(9)
where AH is the hardened ground area, m2; AR is the total area of sprinkling roads, m2; HA is the depth of sprinkling, mm; dfrost is the days of frost, d; drain1 is the days with rainfall exceeding 1 mm, d; other parameters are the same meaning as described previously.
Soil evaporation can be expressed as:
(10)
where As is the soil area, m2; Δ is the slope of vapor pressure curve, kPa °C−1; Rn is the net radiant energy, MJ m−2 day−1; G is outgoing heat conduction into the soil, MJ m−2 day−1; is the mean air density at constant pressure, kg m−3; Cp is the specific heat of moist air, KJ kg−1°C−1; is the saturation vapor pressure deficit, kPa; ra is the aerodynamic resistance, s/m; is the latent heat of the vaporization of water, MJ kg−1; is the psychrometric constant, kPa °C−1; is the soil moist function or evaporation efficiency.
Water surface evaporation can be expressed as:
(11)
where AW is the water surface area, m2; An is advection energy to the water body, mm day−1U2 is wind speed at 2 m height, m s−1. Other parameters have the same meaning as described previously.
The water dissipation of green spaces can be expressed by the following formula:
(12)
where AG is the green space area, m2; Veg is the ratio of crop coverage; δ is the ratio of wet leaf area; Kc is the basic crop coefficient; EP is the potential vegetation transpiration of unit leaf area, which is calculated as the following formula:
(13)
where T is the mean temperature, °C; es is the saturated vapor pressure, kPa; ea is the ambient water vapor pressure, kPa.

Study area

This study took Beijing as the research area (115.25–117.65°E, 39.35–41.15°N). Beijing is the capital of the People's Republic of China. It is located at the junction of the North China Plain (Figure 2(a)), the Taihang Mountains and the Yanshan Mountains, covering an area of 16,410 km2. Land types include woodland, grassland, cropland, urban-built area, water area, etc. (Figure 2(b), the land use data were interpreted from the ESA WorldCover dataset with a resolution of 10 × 10 m, https://easygeodata.cn/). The annual average temperature is 11–12 °C, and the annual average precipitation amounts to approximately 585 mm.
Figure 2

Location of the study area: (a) geographical location; (b) land use types; and (c) the division and population distribution.

Figure 2

Location of the study area: (a) geographical location; (b) land use types; and (c) the division and population distribution.

Close modal

Beijing has experienced rapid urban development and rapid population growth over the past few decades, solidifying its status as a quintessential rapidly urbanizing city in China. By the end of 2020, Beijing was comprised of 16 districts with a permanent population of 21,893 million. The division and population distribution of Beijing are shown in Figure 2(c) (The population density data were obtained from the Worldpop database with a resolution of 100 × 100 m, https://www.worldpop.org/). The population density, urbanization rate, underlying surface characteristics, and development degree vary greatly among districts. The six core districts of Beijing are Dongcheng, Xicheng, Chaoyang, Haidian, Shijingshan, and Fengtai, which have a much higher urbanization degree than the other 10 districts, and most of the urban-built area is concentrated here. The human activities are intense in the six core districts and have a great impact on the hydrological cycle process.

Data collection

The data used in water dissipation calculation in this research mainly include meteorological data, land use data, population data, domestic water dissipation data, and industrial water use data. Meteorological data encompasses key parameters such as rainfall, temperature, humidity, wind speed, and so on, which were derived from daily scale monitoring data of the National Meteorological Station of Beijing Observatory, China (Station No. 54511). Land use data were from the Beijing Statistical Yearbook and Beijing Regional Statistical Yearbook. The population data were the permanent resident population of Beijing, which was sourced from the Beijing Statistical Yearbook. Industrial water use data were acquired from the Beijing Municipal Bureau Statistics and Beijing Municipal Ecology and Environment Bureau. The evaporative water dissipation of green spaces and the water surface were calculated by meteorological data based on the Penman model. The daily water dissipation in buildings was based on the experimental test and questionnaire results of Zhou et al. in Beijing (Zhou et al. 2017, 2019a). Experimental measurements were conducted on various daily water dissipation activities by the weighing method, and the average water dissipation of each daily activity was obtained. Combined with the questionnaire, the frequency of daily water dissipation was calculated, and the per capita daily water dissipation quota was established comprehensively. Based on population data, the total amount of daily water dissipation was further ascertained. For the calculation of evaporation water dissipation on the hardened ground, the selection of runoff coefficient was based on relevant Chinese specifications such as the Code for urban wastewater and stormwater engineering planning and standard for the design of outdoor wastewater engineering, combined with relevant research results (Zhou et al. 2017).

Water dissipation of different land types in urban-built areas of each district

Based on the urban water dissipation model above, the water dissipation of various land types in urban-built areas of Beijing for 2020 was calculated. As shown in Table 1, the total water dissipation reached 2.09 billion m³, of which water dissipation from green spaces reached 1.08 billion m³, water dissipation from buildings reached 800 million m³, water dissipation from roads reached 120 million m³, and water dissipation from water surface reached 97 million m³. Analyzing the water dissipation in each district, as shown in Figure 3, it can be seen that the water dissipation from buildings and green spaces far exceeded that from water surfaces and hardened grounds. In the six core districts, buildings accounted for the largest share of water dissipation, followed by green spaces. The water dissipation of buildings in Chaoyang and Haidian districts was much higher than in other districts because the urban-built area in these two districts was large and the urbanization degree was high, with a high building density and a large number of permanent population, thus intensifying artificial water dissipation inside buildings. In the other 10 districts, green spaces contributed the most to water dissipation, followed by buildings. Due to the degree of urbanization being lower than the six core districts, the artificial water dissipation activities in the building were relatively lower, and the total water dissipation was lower than that from green spaces.
Table 1

Water dissipation of different land types in Beijing in 2020

Land typeCalculated value (m³)
Green space 1.08 billion 
Building 800 million 
Water surface 97 million 
Road 120 million 
Total 2.09 billion 
Land typeCalculated value (m³)
Green space 1.08 billion 
Building 800 million 
Water surface 97 million 
Road 120 million 
Total 2.09 billion 
Figure 3

Water dissipation of different land types of each district in Beijing in 2020.

Figure 3

Water dissipation of different land types of each district in Beijing in 2020.

Close modal
Based on the water dissipation of different land types in each district above, the annual water dissipation intensity of urban-built areas in each district was calculated by area weighting, and the calculation results were mapped onto the respective districts, as shown in Figure 4. It can be seen that the annual comprehensive water dissipation intensity in six core districts far surpassed that of the other districts. The water dissipation intensity of the Dongcheng and Xicheng districts exceeded 900 mm, with the Xicheng district exceeding 1,000 mm. Chaoyang and Haidian districts were higher than 800 mm, and Fengtai and Shijingshan districts were higher than 700 mm. While the water dissipation intensity of the other 10 districts is within the range of 500–700 mm, the primary contributing factor was the high level of urbanization in the six core districts, characterized by greater building density and population density, which in turn resulted in more intense artificial water dissipation activities.
Figure 4

Water dissipation intensity of each district in Beijing in 2020.

Figure 4

Water dissipation intensity of each district in Beijing in 2020.

Close modal

Comparison of water dissipation intensity among each land use type

The radar map in Figure 5 shows the water dissipation contribution rate and area rate of different land use types in the urban-built areas of each district in Beijing for 2020. If the water dissipation contribution rate is higher than the area rate, it indicates that the water dissipation intensity of the corresponding land type is higher than the comprehensive water dissipation intensity of the region. Figure 5(a) shows the water surface water dissipation contribution rate and area rate of each district in Beijing. It can be seen that the water surface water dissipation contribution rate in Xicheng district was lower than the area rate, indicating that the water dissipation intensity in Xicheng district exceeded the evaporation intensity of the water surface. The water surface area rates of the other 15 urban areas were all smaller than the water dissipation contribution rate, and the gap between the area rate and water dissipation contribution rate in the six core districts was significantly smaller than that of the other 10 districts. Road water dissipation contribution rate and area rate are shown in Figure 5(b). The road was one of the main types of urban-built areas, while the water dissipation contribution rate was much smaller than the area rate. It should be noted the road area rate in each district ranged between 20 and 40%, but the corresponding water dissipation contribution rate was only between 3 and 9%. Although road accounts for a large proportion of urban-built areas in each district, most of the water dissipation generated by road came from natural rainfall interception evaporation, and the value was far less than the water dissipation intensity of each district. Figure 5(c) shows the water dissipation contribution rate and area rate of green spaces in each district. As shown in the figure, green space is one of the main land uses of urban-built areas and one of the main types of water dissipation. The area rate of each district exceeded 30%, and the water dissipation contribution rate exceeded 20%, of which the water dissipation contribution rate of districts outside the six core districts exceeded 50%. Comparing the area rate and the water dissipation contribution rate of green spaces in each district, it can be seen that the area rate of six the core districts was higher than the water dissipation contribution rate, and the area rate of the other 10 districts was smaller than the water dissipation contribution rate. It suggests that the water dissipation intensity was higher than the green space evaporation intensity in the six core districts, while the water dissipation intensity was lower than the green space evaporation intensity in the other 10 districts. The water dissipation contribution rate and area rate of buildings are shown in Figure 5(d). The water dissipation contribution rate surpassed the area rate in all districts, reflecting that the water dissipation intensity of the building exceeded the comprehensive water dissipation intensity in the region. This phenomenon was particularly pronounced in six core districts, where the area rate of buildings ranged between 15 and 27%, while the water dissipation contribution rate was between 45 and 71%. The higher building density and population density in the six core districts resulted in more intense artificial water dissipation activities, contributing to a substantial amount of water dissipation.
Figure 5

The water dissipation contribution rate and area rate of different land types of each district in Beijing in 2020: (a) water surface, (b) road, (c) green space, and (d) building.

Figure 5

The water dissipation contribution rate and area rate of different land types of each district in Beijing in 2020: (a) water surface, (b) road, (c) green space, and (d) building.

Close modal
The ratio of the water dissipation contribution rate and area rate was used to reflect the water dissipation intensity of each land type. The larger the ratio, the higher the water dissipation intensity of the land type. As shown in Figure 6, it can be seen that the building had the highest water dissipation intensity, and hardened ground was the smallest. The water dissipation intensity of water surface and green space ranked as the second and third.
Figure 6

Water dissipation intensity of different land types.

Figure 6

Water dissipation intensity of different land types.

Close modal
Building emerged as the primary contributor to high water dissipation in the urban area, with water dissipation inside buildings constituting the major component of artificial water dissipation. The calculation results showed that water dissipation generated from the roof of buildings reached 41.87 million m³, and water dissipation inside buildings reached 758.78 million m³, among which water dissipation from human daily water use was 320.47 million m³, water dissipation from industrial production was 224.89 million m³, and water dissipation from wetting area was 199.42 million m ³, and human body dissipation was 13.99 million m³. Figure 7(a) and 7(b) shows the building water dissipation structure of each district in Beijing for 2020. The building water dissipation included evaporation of interception rainwater on building roofs, water dissipation from people's daily water use inside the building, water dissipation from the wetting area in the building, human body evaporation and the water dissipation during the industrial production process. It can be seen that building water dissipation primarily stemmed from daily water use, wetting ground and industrial production, whereas human body evaporation and building roof rainwater interception evaporation account for a small proportion, ranging from 1 to 3% and 2 to 9% in each district, respectively. The proportion of industrial water dissipation in the Shunyi and Huairou districts reached 47 and 61%, respectively, which was the main part of building water dissipation, followed by human daily water dissipation and water dissipation from wetting ground. The largest proportion of water dissipation in other districts was human daily water dissipation, which exceeded 35%. Compared with other districts, the water dissipation of wetting ground in the six core districts was higher than water dissipation in the industrial production process. On the one hand, the urbanization degree of the six core districts was relatively high, with higher building density and building floors, and the proportion of water dissipation on wetting ground was significantly larger than in other districts. Additionally, the policy in Beijing aimed at relieving the non-capital functions of the six core districts has led to the relocation of industrial enterprises to other suburban areas, thereby reducing industrial water dissipation in these districts.
Figure 7

Building water dissipation structure of each district in Beijing in 2020: (a) building water dissipation and (b) contribution rate of building water dissipation.

Figure 7

Building water dissipation structure of each district in Beijing in 2020: (a) building water dissipation and (b) contribution rate of building water dissipation.

Close modal

Analysis on dualistic attribute of urban water dissipation

Figure 8 presents the water dissipation on the ‘natural’ and ‘social’ sides of each district in Beijing for 2020. Except for the six core districts, the water dissipation intensity on the social side in the other 10 districts was significantly lower than that on the natural side, with the contribution rate of water dissipation on the social side being less than 40%. As for the six core districts, the social water dissipation intensity in Dongcheng and Xicheng districts far surpassed that on the natural side, with the contribution rate of social water dissipation exceeding 60%. Chaoyang and Haidian districts were very close to the water dissipation intensity on the natural side and the social side, with the natural side slightly higher than the social side. The water dissipation intensity of the natural side in Fengtai and Shijingshan districts was also higher than the social side, with the water dissipation contribution rate of the social side slightly lower than that of Chaoyang and Haidian districts. The water dissipation contribution rate on the social side was found to be closely related to the degree of urbanization. The six core districts represented the most urbanized areas in Beijing, among which Dongcheng and Xicheng districts have achieved a 100% urbanization rate, and the contribution rate of water dissipation on the social side was significantly higher than that of other districts. Zhou et al. (2020) concluded that the proportion of water dissipation on the social side of the six core districts in Beijing was 45.3–65.9% in 2015, and 12.7–25.6% in other districts. In this study, the contribution rate of water dissipation on the social side of the six core districts was 45.3–69.1% in Beijing in 2020, and 17.8–36.1% in the other 10 districts, which was higher than the results of Zhou et al. (2020) in general. The difference in the results can be attributed to the inclusion of water dissipation generated by industrial production activities in this study, highlighting the significance of water dissipation in the industrial production process as an important part of urban artificial water dissipation.
Figure 8

Comparison of water dissipation dualistic attributes of each district in Beijing in 2020.

Figure 8

Comparison of water dissipation dualistic attributes of each district in Beijing in 2020.

Close modal

Discussion

Combining the water dissipation intensity of each district calculated in this study and summing it up to the whole of Beijing, it should be noted that the water dissipation intensity of the urban-built area in Beijing was about 705 mm in 2020. Cong et al. (2017) simulated the evapotranspiration in Beijing from 2003 to 2012 using the traditional SEBS model and found that the average annual evaporation was 348 mm. The calculation result of this study was nearly twice that of Cong et al. (2017), mainly because the traditional remote sensing model ignored the influence of anthropogenic heat (Cong et al. 2017). In megacities like Beijing human activities are highly intense, and human activities have an important impact on surface energy (McCarthy et al. 2010; Allen et al. 2011; Cong et al. 2017). Cong et al. (2017) improved the SEBS model after considering anthropogenic heat and other factors, and the simulation results showed that the evapotranspiration in urban areas was significantly higher than that in suburban areas. This study also supported the conclusion that water dissipation in the core districts was higher than that in the suburbs, driven by their higher level of urbanization and more intense artificial water dissipation activities. Domestic water dissipation inside buildings emerged as the main influencing factor of urban evapotranspiration (Cong et al. 2017). It further reflected the high water dissipation in central urban areas.

Indeed, various factors play a significant role in urban water dissipation. The water dissipation on the natural side is mainly affected by climate and other related factors. The water dissipation on the social side is mainly affected by human production and daily activities. In this study, the meteorological data used monitoring data from a Chinese national meteorological station. However, to achieve more accurate water dissipation calculations, it would be beneficial to incorporate data from weather stations within each district, as this would capture the impact of local microclimates on water dissipation more effectively. In addition, the domestic water dissipation inside the buildings was calculated by the water dissipation quota method, and the relevant water dissipation parameters were obtained from the experiments and survey statistics of Zhou et al. (2017, 2019a). It is important to consider that different regions and cities may exhibit varying water consumption habits and seasonal variations. When calculating water dissipation in other cities in the future, it is essential to fully account for the influence of these factors to improve the accuracy of the estimations.

In this study, an urban water dissipation model was developed based on different water dissipation types. Taking Beijing as the research area, the water dissipation of urban-built areas in 2020 was calculated, and the water dissipation contribution rates of various underlying surfaces were analyzed. The conclusions are as follows: (1) The water dissipation in urban areas was higher than that in the suburbs. In 2020, the water dissipation intensity of urban-built areas in the six core districts of Beijing ranged from 700 to 1,100 mm, while other suburbs ranged from 500 to 700 mm. (2) Building and green spaces were the main contributors to water dissipation. Comparing the water dissipation contribution rate and the area rate, it was observed that the water dissipation intensity from strong to weak was building, water surface, green spaces, and hardened ground. (3) As the high water dissipation underlying the surface, building water dissipation was composed of the rainwater interception evaporation outside and water dissipation inside. The water dissipation inside accounted for more than 90% and it was the main source of artificial water dissipation. (4) Water dissipation on the social side refers to artificial water dissipation and it is a significant component of urban water dissipation, which is positively correlated with the degree of regional urbanization. The contribution rate of water dissipation on the social side in the six core districts of Beijing was 45.3–69.1% in 2020, which was higher than 17.8–36.1% in other districts obviously. Under rapid urbanization, artificial activities in urban areas will be more intense and urban water dissipation will continue to increase in the future. Our study advances our understanding of urban water dissipation and could be a reference for water flux calculation in urban ecosystems.

This research was supported by the National Natural Science Foundation of China (Nos 51739011 and 51979285), the Chinese National Key Research and Development Program (No. 2021YFC3001400), and the Open Research Fund of Key Laboratory of River Basin Digital Twinning of the Ministry of Water Resources.

J.L. conceptualized the study; C.L. and J.L. prepared the methodology; C.L. and W.S. did formal analysis and investigated the study; C.L. wrote and prepared the original draft; C.L., X.D., X.S. wrote, reviewed, and edited the article; J.L. and X.D. supervised the study. All authors reviewed the manuscript.

We consent to the publication of our research and manuscript.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.

Allen
L.
,
Lindberg
F.
&
Grimmond
C. S. B.
2011
Global to city scale urban anthropogenic heat flux: model and variability
.
Int. J. Climatol.
31
(
13
),
1990
2005
.
https://doi.org/10.1002/joc.2210
.
Bowen
I. S.
1926
The ratio of heat losses by conduction and by evaporation from any water surface
.
Phys. Rev.
27
,
779
787
.
https://doi.org/10.1103/PhysRev.27.779
.
Chelu
A.
,
Zaharia
L.
&
Dubreuil
V.
2022
Estimation of climatic and anthropogenic contributions to streamflow change in southern Romania
.
Hydrol. Sci. J.
67
(
10
),
1598
1608
.
https://doi.org/10.1080/02626667.2022.2098025
.
Cong
Z.
,
Shen
Q.
,
Zhou
L.
,
Sun
T.
&
Liu
J.
2017
Evapotranspiration estimation considering anthropogenic heat based on remote sensing in urban area
.
Sci. China Earth Sci.
60
(
4
),
659
671
.
https://doi.org/10.1007/s11430-016-0216-3
.
Das
S.
,
Kumar Shit
P.
,
Bera
B.
&
Adhikary
P. P.
2022
Effect of urbanization on the dynamics of ecosystem services: an analysis for decision making in Kolkata urban agglomeration
.
Urban Ecosyst.
25
(
5
),
1541
1559
.
https://doi.org/10.1007/s11252-022-01246-3
.
Dow
C. L.
&
DeWalle
D. R.
2000
Trends in evaporation and Bowen ratio on urbanizing watersheds in eastern United States
.
Water Resour. Res.
36
(
7
),
1835
1843
.
https://doi.org/10.1029/2000WR900062
.
Fidal
J.
&
Kjeldsen
T. R.
2020
Accounting for soil moisture in rainfall-runoff modelling of urban areas
.
J. Hydrol.
589
,
125122
.
https://doi.org/10.1016/j.jhydrol.2020.125122
.
Gao
Y.
,
Chen
J.
,
Luo
H.
&
Wang
H.
2020
Prediction of hydrological responses to land use change
.
Sci. Total Environ.
708
,
134998
.
https://doi.org/10.1016/j.scitotenv.2019.134998
.
Hao
L.
,
Sun
G.
,
Liu
Y.
,
Wan
J.
,
Qin
M.
,
Qian
H.
,
Liu
C.
,
Zheng
J.
,
John
R.
,
Fan
P.
&
Chen
J.
2015
Urbanization dramatically altered the water balances of a paddy field-dominated basin in southern China
.
Hydrol. Earth Syst. Sci.
19
(
7
),
3319
3331
.
https://doi.org/10.5194/hess-19-3319-2015
.
Jacobs
C.
,
Elbers
J.
,
Brolsma
R.
,
Hartogensis
O.
,
Moors
E.
,
Márquez
M. T. R. C.
&
van Hove
B.
2015
Assessment of evaporative water loss from Dutch cities
.
Build. Environ.
83
,
27
38
.
https://doi.org/10.1016/j.buildenv.2014.07.005
.
Liu
C.
,
Liu
J.
,
Shao
W.
,
Lu
J.
&
Gao
H.
2022
The considerable water evaporation induced by human perspiration and respiration in megacities: quantifying method and case study in Beijing
.
Int. J. Environ. Res. Public Health
19
(
14
),
8638
.
https://doi.org/10.3390/ijerph19148638
.
Livesley
S. J.
,
McPherson
E. G.
&
Calfapietra
C.
2016
The urban forest and ecosystem services: impacts on urban water, heat, and pollution cycles at the tree, street, and city scale
.
J. Environ. Qual.
45
(
1
),
119
124
.
https://doi.org/10.2134/jeq2015.11.0567
.
Loridan
T.
&
Grimmond
C. S. B.
2012
Characterization of energy flux partitioning in urban environments: links with surface seasonal properties
.
J. Appl. Meteorol. Climatol.
51
(
2
),
219
241
.
https://doi.org/10.1175/JAMC-D-11-038.1
.
Luo
Z.
,
Liu
J.
,
Zhang
Y.
,
Zhou
J.
,
Shao
W.
,
Yu
Y.
&
Jia
R.
2021a
Seasonal variation of dry and wet islands in Beijing considering urban artificial water dissipation
.
npj Clim. Atmos. Sci.
4
(
1
),
1
9
.
https://doi.org/10.1038/s41612-021-00216-4
.
Luo
Z.
,
Liu
J.
,
Zhang
Y.
,
Zhou
J.
,
Yu
Y.
&
Jia
R.
2021b
Spatiotemporal characteristics of urban dry/wet islands in China following rapid urbanization
.
J. Hydrol.
601
,
126618
.
https://doi.org/10.1016/j.jhydrol.2021.126618
.
McCarthy
M. P.
,
Best
M. J.
&
Betts
R. A.
2010
Climate change in cities due to global warming and urban effects
.
Geophys. Res. Lett.
37
(
9
).
https://doi.org/10.1029/2010GL042845
.
Molina-Gómez
N. I.
,
Varon-Bravo
L. M.
,
Sierra-Parada
R.
&
López-Jiménez
P. A.
2022
Urban growth and heat islands: a case study in micro-territories for urban sustainability
.
Urban Ecosyst.
25
,
1379
1397
.
https://doi.org/10.1007/s11252-022-01232-9
.
Noilhan
J. A.
&
Lacarrere
P.
1995
GCM grid-scale evaporation from mesoscale modeling
.
J. Clim.
8
(
2
),
206
223
.
https://doi.org/10.1175/1520-0442(1995)008 < 0206:GGSEFM > 2.0.CO;2
.
Ramamurthy
P.
&
Bou-Zeid
E.
2014
Contribution of impervious surfaces to urban evaporation
.
Water Resour. Res.
50
(
4
),
2889
2902
.
https://doi.org/10.1002/2013WR013909
.
Sterling
S. M.
,
Ducharne
A.
&
Polcher
J.
2013
The impact of global land-cover change on the terrestrial water cycle
.
Nat. Clim. Change
3
(
4
),
385
390
.
https://doi.org/10.1038/nclimate1690
.
Su
Z.
2002
The Surface Energy Balance System (SEBS) for estimation of turbulent heat fluxes
.
Hydrol. Earth Syst. Sci.
6
(
1
),
85
100
.
https://doi.org/10.5194/hess-6-85-2002
.
Thornthwaite
C. W.
&
Holzman
B.
1939
The determination of evaporation from land and water surfaces
.
Mon. Weather Rev.
67
(
1
),
4
11
.
https://doi.org/10.1175/1520-0493(1939)67 < 4:TDOEFL > 2.0.CO;2
.
Tong
X.
,
Wang
P.
,
Wu
S.
&
Luo
M.
2022
Urbanization effects on high-frequency temperature variability over South China
.
Urban Clim.
42
,
101092
.
https://doi.org/10.1016/j.uclim.2022.101092
.
United Nations Habitat
2020
World Cities Report 2020: The Value of Sustainable Urbanization
.
van Walsum
P. E. V.
&
Veldhuizen
A. A.
2011
Integration of models using shared state variables: implementation in the regional hydrologic modelling system SIMGRO
.
J. Hydrol.
409
(
1–2
),
363
370
.
https://doi.org/10.1016/j.jhydrol.2011.08.036
.
von Allmen
E. I.
,
Sperry
J. S.
&
Bush
S. E.
2015
Contrasting whole-tree water use, hydraulics, and growth in a co-dominant diffuse-porous vs. ring-porous species pair
.
Trees
29
(
3
),
717
728
.
https://doi.org/10.1007/s00468-014-1149-0
.
Wang
H.
&
Jia
Y.
2016
Theory and study methodology of dualistic water cycle in river basins under changing conditions (in Chinese)
.
J. Hydraul. Eng.
47
(
10
),
1219
1226
.
https://doi.org/10.13243/j.cnki.slxb.20151297
.
Wang
J.
,
Endreny
T. A.
&
Nowak
D. J.
2008
Mechanistic simulation of tree effects in an urban water balance model
.
J. Am. Water Resour. Assoc.
44
(
1
),
75
85
.
https://doi.org/10.1111/j.1752-1688.2007.00139.x
.
Wang
H.
,
Jia
Y.
,
Yang
G.
,
Zhou
Z.
,
Qiu
Y.
,
Niu
C.
&
Peng
H.
2013
Integrated simulation of the dualistic water cycle and its associated processes in the Haihe River Basin
.
Chinese Sci. Bull.
58
(
27
),
3297
3311
.
https://doi.org/10.1007/s11434-012-5371-0
.
Wang
C.
,
Yang
J.
,
Myint
S. W.
,
Wang
Z. H.
&
Tong
B.
2016
Empirical modeling and spatio-temporal patterns of urban evapotranspiration for the Phoenix metropolitan area, Arizona
.
GISci Remote Sens.
53
(
6
),
778
792
.
https://doi.org/10.1080/15481603.2016.1243399
.
Wang
J.
,
Xiang
Z.
,
Wang
W.
,
Chang
W.
&
Wang
Y.
2021
Impacts of strengthened warming by urban heat island on carbon sequestration of urban ecosystems in a subtropical city of China
.
Urban Ecosyst.
24
(
6
),
1165
1177
.
https://doi.org/10.1007/s11252-021-01104-8
.
Zheng
Q.
,
Hao
L.
,
Huang
X.
,
Sun
L.
&
Sun
G.
2020
Effects of urbanization on watershed evapotranspiration and its components in southern China
.
Water
12
(
3
),
645
.
https://doi.org/10.3390/w12030645
.
Zhou
J.
,
Liu
J.
,
Dong
Q.
,
Wang
Z.
,
Wang
H.
,
Xiang
C.
&
Luan
Y.
2017
Simulation model for urban water dissipation (in Chinese)
.
Adv. Water Sci.
28
,
276
284
.
https://doi.org/10.14042/j.cnki.32.1309.2017.02.013
.
Zhou
J.
,
Liu
J.
,
Wang
H.
,
Wang
Z.
&
Mei
C.
2018
Water dissipation mechanism of residential and office buildings in urban areas
.
Sci. China-Technol. Sci.
61
(
7
),
1072
1080
.
https://doi.org/10.1007/s11431-017-9193-8
.
Zhou
J.
,
Liu
J.
,
Yan
D.
,
Wang
H.
,
Wang
Z.
,
Shao
W.
&
Luan
Y.
2019a
Dissipation of water in urban area, mechanism and modelling with the consideration of anthropogenic impacts: a case study in Xiamen
.
J. Hydrol.
570
,
356
365
.
https://doi.org/10.1016/j.jhydrol.2018.12.054
.
Zhou
J.
,
Liu
J.
,
Wang
H.
&
Wang
Z.
2019b
Simulation of water dissipation in urban buildings
.
Proc. Inst. Civ. Eng. – Water Manage.
172
(
6
),
311
322
.
https://doi.org/10.1680/jwama.18.00049
.
Zhou
J.
,
Wang
H.
,
Liu
J.
,
Wang
Z.
&
Zhang
Y.
2020
‘Nature-Social’ dual attribute and seasonal characteristics of urban water dissipation: a case study of Beijing (in Chinese)
.
J. Hydraul. Eng.
51
(
11
),
1325
1334
.
https://doi.org/10.13243/j.cnki.slxb.20200263
.
Zhou
J.
,
Liu
J.
,
Chu
Q.
,
Wang
H.
,
Shao
W.
,
Luo
Z.
&
Zhang
Y.
2021
Mechanisms and empirical modeling of evaporation from hardened surfaces in urban areas
.
Int. J. Environ. Res. Public Health
18
(
4
),
1790
.
https://doi.org/10.3390/ijerph18041790
.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY 4.0), which permits copying, adaptation and redistribution, provided the original work is properly cited (http://creativecommons.org/licenses/by/4.0/).