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Journal of Geographical Sciences >

2018 , Vol. 28 >Issue 5: 656 - 668

DOI: https://doi.org/10.1007/s11442-018-1497-6

Research Articles

Rainfall-runoff risk characteristics of urban function zones in Beijing using the SCS-CN model

  • YAO Lei , 1 ,
  • WEI Wei 2 ,
  • YU Yang 2 ,
  • XIAO Jun 2 ,
  • CHEN Liding , 2, *
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  • 1. College of Geography and Environment, Shandong Normal University, Jinan 250014, China
  • 2. State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, CAS, Beijing 100085, China

Author: Yao Lei (1989-), PhD, specialized in landscape ecology and urban hydrological process.E-mail:

*Corresponding author: Chen Liding (1965-), PhD and Professor, specialized in landscape ecology.
E-mail:

Received date: 2017-05-08

  Accepted date: 2017-06-28

  Online published: 2018-03-30

Supported by

National Natural Science Foundation of China, No.41701206

The Major Program of National Natural Science Foundation of China, No.41590841

Copyright

Journal of Geographical Sciences, All Rights Reserved
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Abstract

Urbanization significantly increases the risk of urban flooding. Therefore, quantitative study of urban rainfall-runoff processes can provide a scientific basis for urban planning and management. In this paper, the built-up region within the Fifth Ring Road of Beijing was selected as the study area. The details of land cover and urban function zones (UFZs) were identified using GIS and RS methods. On this basis, the SCS-CN model was adopted to analyze the rainfall-runoff risk characteristics of the study area. The results showed that: (1) UFZs within different levels of runoff risk varied under different rainfall conditions. The area ratio of the UFZs with high runoff risk increased from 18.90% (for rainfall return period of 1a) to 54.74% (for period of 100a). Specifically, urban commercial areas tended to have the highest runoff risk, while urban greening spaces had the lowest. (2) The spatial characteristics of the runoff risks showed an obvious circular distribution. Spatial cluster areas with high runoff risk were mainly concentrated in the center of the study area, while those with low runoff risk were mainly distributed between the fourth and fifth ring roads. The results indicated that the spatial clustering characteristic of urban runoff risk and runoff heterogeneity among different UFZs should be fully considered during urban rainwater management.

Key words： SCS-CN model; urban function zone; spatial cluster; runoff risk

Cite this article

YAO Lei , WEI Wei , YU Yang , XIAO Jun , CHEN Liding . Rainfall-runoff risk characteristics of urban function zones in Beijing using the SCS-CN model[J]. Journal of Geographical Sciences, 2018 , 28(5) : 656 -668 . DOI: 10.1007/s11442-018-1497-6

1 Introduction

As a special ecological system, urban areas act as unified regions that integrate the residents and their surrounding environment. Urbanization alters the original environment significantly, bringing dramatic change during the transition from natural to artificial landscapes. Along with urban construction and expansion, the original land cover, such as forests and lawns, are gradually replaced by larger amounts of impervious surfaces. The land cover alterations lead to significant reduction in urban rainwater interception and infiltration capacity (Shuster, 2005; Sunde et al., 2016). In addition, local climate changes deeply affect storm drainage in urban and surrounding areas, resulting in urban areas becoming vulnerable to extreme rainfall of short duration and high intensity (Milly et al., 2002; Putro et al., 2016). These factors cause increased risks from rainfall and runoff, and from storm-related flood hazards in urban regions.
As the unit by which urban functions are realized, urban function zones (UFZs) refer to the areas assigned to different types of urban (social and economic) activities. According to different urban functions, UFZs can be divided into several types (i.e., residential, commercial, educational, and industrial zones) (Tian et al., 2010). These UFZs are closely related to daily urban activities. Therefore, studying the rainfall-runoff process from the perspective of UFZs will provide a better understanding of the spatial characteristics of urban rainfall-runoff risks.
However, due to the complexity and particularity of urban planning tasks (i.e., complex urban terrain, crisscrossed underground drainage networks, and the restrictions imposed by urban management), it is hard to acquire sufficient hydrological monitoring data. This increases the difficulty of urban rainfall-runoff research (Ebrahimian et al., 2016; Zhu et al., 2016). For this reason, methods involving such as hydrological models and 3S technology (GIS, RS, and GPS) are adopted for the study of urban rainfall-runoff issues (Atkinson, 2012; Gajbhiye and Mishra, 2012; Lin, 2000). All these methods help to understand, at multiple spatial scales, the mechanisms by which urbanization influences rainfall-runoff processes.
Recently, a great deal of hydrological research has been conducted in Beijing (Ouyang et al., 2012; Yao et al., 2016; Zhang et al., 2012b). However, most of these studies were focused on rainfall-runoff characteristics at the community scale, rather than urban scale. Therefore, this study aimed to explore the rainfall-runoff characteristics of the area inside Beijing’s Fifth Ring Road. In this study, the Soil Conservation Service-Curve Number (SCS-CN) model and GIS/RS technology were used to extract UFZs and land-cover details, and then to analyze the rainfall-runoff among different types of UFZs, in order to identify quantitatively, the high and low risk areas of rainfall-runoff.

2 Materials and methodology

2.1 Study area

Beijing is the social, economic, and cultural center of China, and is located on the northeast edge of the North China Plain. This city has a typical continental monsoon climate, an annual average temperature of ~11-12℃, and average rainfall of 585 mm. The rainfall is mainly concentrated in the flood season, which occurs in June-September (Yao et al., 2015).
Owing to rapid urbanization of this area, urban flooding hazards in Beijing have become more frequent. In the summer of 2012, Beijing suffered a severe flooding event that caused 78 deaths and enormous economic loss. This resulted in greater concern over urban flooding risks citywide, and a series of environmental management policies were adopted to address these issues (Pan et al., 2009). Therefore for this study, the built-up region within the Fifth Ring Road of Beijing was chosen as the study area, as shown in Figure 1.
Figure 1 The study area and its urban function zones

2.2 Data preparation

In this study, an IKONOS image (satellite-based) was used as the spatial data source. This image covers the whole region within the Fifth Ring Road of Beijing. The image was acquired on July 29, 2012 (summer) to ensure its clarity and its ability to determine vegetation and other land cover information. Then, all the five image bands were subjected to band-fusion to obtain high spatial resolution (1 m×1 m).

2.3 Methodology

2.3.1 Spatial identification
Before use, the IKONOS image was first geo-rectified using ArcGIS software (version 10.1) to meet the requirements of the following land cover classification and UFZ identification.
Then, the land cover details of the study area were classified by integrating the object-oriented and decision tree classification method. The remote sensing image was partitioned into segments (objects) by grouping neighboring pixels with similar feature values. A set of characteristic parameters for each object (i.e., spatial, textural, spectral, color, and band ratio) was compiled and then transferred to multiple rule sets. The study area was finally divided into six types of land cover: impervious land, water, bare land, forest, grassland, and farmland. The overall classification precision was 85.8% and the kappa coefficient was 0.75.
The UFZs of the study area were identified based on the IKONOS image. Referring to the UFZ identification work conducted by Sun et al. (2013), and the latest information on urban function in Beijing, this study set the standard for UFZ identification in Beijing, as shown in Table 1. This study was the first to define an urban function block (UFB) as a finer sub-area (similar to an urban block) within a UFZ. Considering that linear landscape elements in urban areas typically serve as the borders of UFZs, as well as sub-areas of urban sewer systems, several mesh regions (i.e., UFBs) were manually delineated for the entire study area, along with urban roads and canal networks. All these UFBs were treated as independent hydrological units and geo-coded with unique urban function types according to the UFZ standard in Table 1. Finally, 10 types of UFZ were identified, including a high-density residential zone (HRZ), low-density residential zone (LRZ), government zone (GOZ), industrial zone (INZ), commercial zone (COZ), recreational zone (REZ), preservation zone (PRZ), agricultural zone (AGZ), public service zone (PSZ), and development zone (DEZ), as shown in Figure 1.
Table 1 Standard of classification for urban functional zones in Beijing’s five-ring areas
UFZ Abbreviation Area (ha) Description
High-density
residential zone		 HRZ 21187.9 Services for citizens; typical residential communities in Beijing, including low-rise and high-rise buildings with a dense population.
Low-density
residential zone		 LRZ 450.0 Services for citizens; lower impervious fraction; mainly low-rise buildings with a sparse population.
Government zone GOZ 6119.2 Services for civil servants and students; government buildings, public organizations, research institutes, and campuses.
Industry zone INZ 9460.1 Services for production workers and laborers; city infrastructure and industrial factories, energy, and resources supply.
Commercial zone COZ 10100.6 Services for business and commercial workers; city malls, retail businesses, and public amenities such as restaurants, hotels, etc.
Recreational zone REZ 9204.5 Services for tourists and residents; urban parks, golf courses, and scenic areas with relatively high green coverage.
Preservation zone PRZ 225.1 Services for tourists and residents; open space with natural and artificial green space such as forest parks.
Agricultural zone AGZ 751.9 Services for agricultural workers; cultivated land, greenhouses, and orchards.
Public service zone PSZ 3704.6 Services for citizens, such as hospitals, libraries, museums, stadiums, and city squares.
Development zone DEZ 4302.1 Services mainly for construction workers; undeveloped open space and demolition areas.
2.3.2 Hydrological modeling
Rainfall-runoff characteristics of UFZs were simulated using the Soil Conservation Service Curve Number (SCS-CN) model in this study. The SCS-CN model was developed by the United States Department of Agriculture (USDA), in order to study the rainfall-runoff processes in agricultural and urbanized watersheds. Many urban eschatology studies have used this model to simulate various runoff scenarios, ranging from small urban sites (e.g., highway or residential lots) to neighborhoods, to large urban watersheds (Gajbhiye and Mishra, 2012; Kadam et al., 2012; Singh et al., 2013; Zuo et al., 2016). Meanwhile, the USDA also provides a Curve Number (CN) look-up table with assignments of different types of land cover to facilitate hydrological simulation (NRCS, 1986).
Compared with natural and agricultural watersheds, urbanized areas have relatively high CN values due to greater impervious coverage, indicating more sensitive rainfall-runoff responses. On this basis, researchers conducted a series of studies to explore the rainfall-runoff characteristics of urbanized watersheds at multiple spatial scales (i.e., watershed (Kadam et al., 2012), community (Skotnicki and Sowiński, 2013; Yao et al., 2017; Yao et al., 2016), and plot (Singh et al., 2013)). In addition, many distributed hydrological models (i.e., SWAT, SWMM, and HEC-HMS) are based on the theory of the SCS-CN model for estimating runoff (Baker and Miller, 2013; Zhou et al., 2013). These factors demonstrate that the SCS-CN model can well estimate the rainfall-runoff risk in highly urbanized areas.
Minimal input data are needed for this model to simulate surface runoff. Specifically, the calculations require only rainfall abstraction, without considering other complex factors (e.g., groundwater recharge and base flow). Three parameters are used to calculate surface runoff: rainfall depth, initial abstraction of the rainfall, and the potential maximum storage of the soil (NRCS, 1986). The model formula is as follows:
where Q is the runoff depth (mm), P is the rainfall depth (mm), Ia is the initial abstraction of the rainfall (mm), and S represents potential maximum soil-water capacity. A quantitative relationship exists between Ia and S (Ia = 0.2S) (NRCS, 1986). CN is a dimensionless parameter (ranging from 0 to 100), representing the hydrological performance of various land cover categories. Higher CN indicates greater potential for surface runoff and less surface storage.
According to the user manual for the SCS-CN model, reliable hydrological modeling depends on determination of the CN value for each type of land cover (NRCS, 1986). This task needs to make explicit the hydrology soil groups (HSG), land cover details, and antecedent soil moisture condition (AMC) (Fan et al., 2013). USDA has created several different hydrologic soil groups (A, B, C, and D groups: HSGs), to represent different infiltration capacities of soils. To determine the HSGs for the city of Beijing, Fu et al. (2013) found that the soils of Beijing can be classified as B-group after testing the saturated hydraulic conductivity of these soils using the constant head method. Land cover details of the study area were determined from the IKONOS image. Then, referring to the CN look-up table (NRCS, 1986), CN values were assigned to the various land-cover types and AMCs of the study area, as shown in Table 2.
Table 2 Curve numbers assigned with various land cover types and antecedent moisture conditions (AMC)
Land use AMC I AMC II b AMC III
Impervious land 98 98 98
Farmland 60 78 90
Forest 37 58 78
Grassland 40 61 80
Bare land 81 91 97
Water a 0 0 0

a Runoff generated from water do not exert extra influence on surrounding landscapes, thus its CN value can be treated as 0;

b Moderate antecedent moisture condition is selected to represent the average rainfall-runoff conditions of Beijing (NRCS, 1986).

For design of urban drainage systems, rainfall intensity can be determined according to a rainfall formula, and the rainfall duration can refer to the average runoff concentration time of the drainage area. In Beijing, runoff concentration time was usually less than 120 min, representing a relatively quick flow time. Therefore, in this study, different rainfall conditions were selected with various return periods according to the rainfall formula appropriate in Beijing (Wang et al., 2011). These rainfall return periods were labeled 1a, 3a, 5a, 10a, 25a, 50a, and 100a; and the rainfall duration was set as 120 min. The designed rainfall amounts (P) were (39.7, 55.2, 62.4, 72.1, 84.9, 94.7, and 104.4) mm, respectively.
Finally, the SCS-CN model was built using the modeling tools in ArcGIS. The runoff characteristics under different rainfall conditions were simulated after inputting the CN values and rainfall data. The rainfall-runoff data for different types of UFZ were analyzed using spatial analysis and analysis of variance (ANOVA in SPSS), to investigate the runoff differences between the different UFZs.
2.3.3 Runoff risk identification
Spatial autocorrelation analysis can identify the potential aggregation characteristics of geographical phenomena. This method can use indicators including the global autocorrelation coefficient (Moran’s I) and partial autocorrelation coefficient (Local Moran’s I) to describe the spatial characteristics.
Moran’s I can be calculated by the following formula:
where, n is the number of geographical phenomena for analysis, xi and xj are the values of geographical phenomena of i and j, x is the average value of all the geographical phenomena, wij is the weighting matrix between geographical phenomena of i and j. The I value ranges from -1 to 1: I>0 indicates positive spatial autocorrelation (aggregate spatial distribution condition); I<0 indicates negative spatial autocorrelation (discrete spatial distribution condition); and I = 0 indicates no spatial autocorrelation (random spatial distribution condition).
The partial autocorrelation coefficient is visible on the LISA map, representing the specific spatial distribution conditions for the local area. From the LISA map, the study area was divided into four types of region with different correlation significance, showing higher autocorrelation (HH), lower autocorrelation (LL), high-low negative correlation (HL), and low-high negative correlation (LH). For this purpose, the HH regions can be identified as “hot spot areas”, the LL regions, by contrast, are “cold spot areas”; and the HL and LH regions indicate “isolated areas” with significant contrast.
This study conducted a spatial autocorrelation analysis to explore the spatial characteristics of the rainfall-runoff risks of different types of UFZs using Geoda software. This was done to make explicit the regularity of the spatial distribution of the “hot spots” and “cold spots” in the study area.

3 Results and discussions

3.1 Details of urban function zones

Eventually, a total of 5116 UFBs were delineated within the study area, as shown in Table 1. The largest were the residential (including HRZ and LRZ: 217.17 km2) and industrial (including INZ and DEZ: 138.75 km2) zones. These were followed by the commercial zone (COZ: 101.89 km2), greening zone (REZ, PRZ, and AGZ: 102.27 km2), educational and governmental zone (GOZ: 62.00 km2), and the public zone (PSZ: 37.67 km2).
Gradational distribution characteristics of the UFZs were found along the ring roads of the study area, as shown in Figure 1. Within the Third Ring Road, the composition of UFZs showed slight differences between the ring roads. Outside the Third Ring Road, the proportion of commercial land gradually declined, while that of industrial land (INZ and DEZ) increased. Between the fourth and fifth ring roads, the proportions of green land (REZ, PRZ, and AGZ) and industrial land both increased significantly. This reflected the concentric mode of development in Beijing.
Figure 2 Land-cover composition of each type of urban functional zone
In addition, as shown in Figure 2, the land cover composition of these UFZs showed obvious differences. Among them, HRZ, INZ, COZ, GOZ, and PSZ had similar land cover composition, with relatively high impervious coverage (>70%). Compared to HRZ, LRZ exhibited a lower impervious ratio and greater vegetation coverage. The urban development region, DEZ, had the greatest coverage of bare land; while REZ and PRZ had greater forest coverage, indicating their recreational and ecological conservation functions. AGZ had the most farmland and a small amount of impervious surfaces (mainly these were farming sheds and greenhouses).

3.2 Runoff analyses

3.2.1 Runoff characteristics of the study area
The average runoff as well as the runoff ratio (α = runoff depth/rainfall depth) for the whole study area increased with increase in the rainfall return period, as shown in Figure 3. Specifically, the average runoff increased from 24.35 mm (under the rainfall return period of 1a) to 76.01 mm (under the rainfall return period of 100a). The corresponding α rose from 0.51 (1a) to 0.64 (100a), showing a logarithmic trend (y = 0.0705ln(x) + 0.4983, R2 = 0.97). However, the increasing trend slowed as the rainfall amount increased (Figure 3). This is mainly because 29% of the land surfaces in the study area were pervious. According to the hydrology budget principle, the rainfall falling on soil should first meet the budget for the depression storage of the adherent land surface, then generates runoff (Armson et al., 2013). Later, α increased from ‘0’ and tended to be stable (the maximum value) after the land surface reached condition of steady infiltration.
Figure 3 Average runoff ratios of the study area under different rainfall return periods
Table 3 Class assignments of the runoff risk areas
Rainfall-runoff risk level Runoff ratio (α)
Lowest risk α<0.35
Lower risk 0.35≤α<0.5
Moderate risk 0.5≤α<0.6
Higher risk 0.6≤α<0.7
Highest risk 0.7≤α
3.2.2 Runoff characteristics of urban function zones
The ANOVA analysis showed significant differences in the runoff among the UFZs under different rainfall conditions, and detailed runoff information for all these UFZs is shown in Table 5. Due to the highest greening (forest, grassland, and farmland, as shown in Figure 2) and water coverage, and the lowest imperviousness (leading to higher capacity of intercept and infiltration for rainwater), the runoff amounts generated from REZ, PRZ, and AGZ were the lowest (<15 mm under the rainfall return period of 1a). However, Table 2 shows that CNfarmland > CNgrassland > CNforest; thus, more runoff was generated from AGZ (included the most farmland) than from REZ and PRZ. By contrast, with relatively high imperviousness, COZ and INZ generated similarly large amounts of runoff under all rainfall conditions. Runoff generated from GOZ, PSZ, and HRZ reached greater amounts (>24 mm under the rainfall return period of 1a), while LRZ and DEZ (with higher greening, bare land, and coverage) generated smaller amounts of runoff than did GOZ, PSZ, and HRZ.
Table 4 Proportions of urban functional zones within each level runoff risk area (under the rainfall return period of 10a)
Urban function
zone		 Area ratio for each level runoff risk (%)
Highest risk Higher risk Moderate risk Lower risk Lowest risk
HRZ 37.41 46.26 32.98 8.21 0.52
LRZ 0.04 0.50 0.29 4.16 0.40
GOZ 6.98 11.77 18.25 8.69 2.00
INZ 15.18 16.65 17.00 12.22 4.72
DEZ 5.17 7.27 10.68 7.30 3.74
COZ 29.88 8.87 6.83 3.97 0.68
REZ 0.27 1.30 8.38 36.58 84.17
PRZ - - - 1.39 1.90
AGZ - 0.35 1.45 6.67 1.02
PSZ 5.07 7.03 4.14 10.81 0.83
Table 5 Comparison of the average runoff volume in each urban functional zone (UFZ) in different return periods of rainfall (mm)
UFZ 1a 3a 5a 10a 25a 50a 100a
GOZ 24.76±4.14e 36.40±5.78de 42.02±6.46de 49.77±7.31d 60.25±8.32d 68.45±9.02d 76.70±9.66d
COZ 27.74±3.71f 40.58±5.17f 46.70±5.77f 55.06±6.52e 66.28±7.42e 74.99±8.04e 83.69±8.60e
AGZ 12.00±4.83b 21.12±6.22b 25.87±6.80b 32.66±7.52b 42.17±8.40bc 49.79±9.02c 57.57±9.59c
PSZ 25.06±5.10e 36.84±7.11de 42.51±7.94de 50.33±8.96d 60.90±10.19d 69.16±11.04d 77.45±11.81d
HRZ 24.90±3.55e 36.60±4.96de 42.24±5.54de 50.02±6.26d 60.54±7.12d 68.77±7.72d 77.03±8.27d
LRZ 17.56±5.55c 26.45±7.78c 30.93±8.70c 37.27±9.85c 46.08±11.22c 53.12±12.18c 60.31±13.05c
INZ 25.42±5.78ef 37.43±7.98ef 43.21±8.88ef 51.16±10de 61.88±11.34de 70.26±12.26de 78.66±13.09de
DEZ 22.27±7.03d 33.59±9.61d 39.10±10.68d 46.74±12d 57.12±13.57d 65.26±14.66d 73.46±15.65d
REZ 13.55±6.40b 20.83±8.94b 24.64±9.99b 30.15±11.3b 37.97±12.86b 44.33±13.94b 50.90±14.93b
PRZ 7.36±3.10a 12.39±4.48a 15.28±5.06a 19.64±5.8a 26.12±6.69a 31.54±7.31a 37.26±7.88a

Note: The runoff values with different letters in the same column show significant difference (data represented as “means ± standard deviation”, p<0.05); the abbreviations of these urban function zones were: high-density residential zone (HRZ), low-density residential zone (LRZ), government zone (GOZ), industrial zone (INZ), commercial zone (COZ), recreational zone (REZ), preservation zone (PRZ), agricultural zone (AGZ), public service zone (PSZ), and development zone (DEZ)

As the rainfall return period increased, the runoff of all the UFZs rose and the runoff gaps among them narrowed gradually (Table 5). In the cases under lighter rainfall conditions, more runoff was mainly generated from the UFZs with higher impervious coverage (e.g., COZ, HRZ); while runoff generated from some types of UFZs (e.g., DEZ) became similarly high under heavier rainfall conditions.

3.3 Runoff risk analyses

3.3.1 Runoff risk categorization
The Code for Design of Outdoor Wastewater Engineering (Ministry of Construction of China) requires that necessary rainwater penetration and regulation countermeasures should be carried out for an urban built-up region if its runoff ratio (α) exceeds 0.7 (GB50014-2006, 2013). Referring to this rule, in this study, the whole study area was divided into five types of runoff risk area according to the runoff ratio (α) of each UFZ. The classification standard is shown in Table 3.
As shown in Figure 4, the proportions of the UFZs with the highest runoff risk increased significantly with increase in the rainfall return period. For the rainfall return period of 1a, the total area of the UFZs with the highest runoff risk accounted for 18.90% of the study area; while for the rainfall return period of 10a, this proportion increased to 38.62%. It continually increased to more than 50% when the rainfall condition had the return period of 100a.
Figure 4 Spatial distribution chart of runoff risk area under 3 types of rainfall conditions (1a, 10a, 100a)
In addition, proportions of UFZs within each runoff risk area showed obvious differences. Taking the rainfall condition for the return period of 10a as example (Figure 4 and Table 4), the urban greening UFZs (PRZ and REZ) occupied 86.07% of the area with the lowest runoff risk, which were mainly distributed outside the Fourth Ring Road, as well as in a few scattered urban parks in the central urban area. The rest of these greening UFZs belonged mainly to the runoff areas with lower and moderate risk. On the contrary, most of the UFZs with the highest runoff risk were distributed within the Fourth Ring Road, mainly HRZ (37.41%), INZ (15.18%), and COZ (29.88%). However, the proportions of GOZ and DEZ in the area of the highest runoff risk were relatively low, at 6.98% and 5.17%, respectively.
3.3.2 Spatial cluster analysis for runoff risk
The results of global autocorrelation analysis showed that the value of Moran’s I coefficient was 0.139 (p<0.001), indicating that the spatial distribution of the runoff risk areas in the study area presented significant aggregation characteristics.
The local autocorrelation analysis result is shown in Figure 5. HH areas (marked in red) illustrated the spatial cluster of UFZs with high runoff risk, and were mainly distributed in the urban core area (average runoff ratio of 0.82). These areas were mainly HRZ (nearly 41%) and COZ (nearly 36%), accounting for nearly 80% of the impervious surfaces.
Figure 5 LISA map for runoff risk analysis
LL areas (marked in blue) showed the spatial cluster of UFZs with low runoff risk, which were mainly distributed between the fourth and fifth ring roads. The UFZ composition of this area was mainly greening UFZs (nearly 32%, such as large urban parks and natural greenbelts) as well as some scattered LRZ (nearly 22%). The impervious coverage of these areas was lower than the average level (65%) of the whole study area, and their average runoff ratio reached 0.56 (far lower than that of the HH areas).

3.4 Implications

As shown in Figure 5, the HH areas are mainly located in the core built-up region of Beijing, with a mostly flat landscape (Yao et al., 2015). Here, the municipal drainage system is the main provision for discharge of rainwater. Also, this area is away from the waterways (that might accept water from urban drainage) of the urban watershed. These factors mean that the surface runoff cannot be discharged quickly enough; thus increasing the drainage burden of these areas. These areas constitute the cluster of UFZs with high runoff risks, which typically deliver excess rainfall to the surrounding areas. When confronted with heavy rainfall, these areas are susceptible to urban flooding due to supersaturation of the drainage system. Even worse, the HH areas are mainly urban commercial and residential areas, where higher social and economic loss due to urban flooding is more likely than in other urban areas. Therefore, these HH areas should be paid more attention during future municipal drainage planning, to strengthen their drainage systems.
This study also demonstrated that the cluster areas with low runoff risk (LL areas) were mainly urban green spaces that have been shown to improve canopy interception, evaporation, and land surface infiltration to mitigate excessive rainfall and runoff efficiently (Dunnett et al., 2008; Gill et al., 2007; Jarden et al., 2015). Zhang et al. (2012a) and Yao et al. (2015) explored the potential reduction in urban runoff by green spaces in Beijing, and estimated the amount to be 2494 m3·ha (in 2009) and 4258 m3·ha (in 2012). This indicates that the urban green spaces can thus not only provide huge ecological benefits, but can also greatly alleviate the pressure on urban drainage. Therefore, rational urban green space planning and construction are needed while strengthening the construction of drainage facilities in the urban areas with high runoff risk.
During the planning of urban flood control, the differences in runoff risks among the UFZs should be fully recognized. These differences are mainly caused by the heterogeneities in landscape patterns and configurations of these UFZs (Su et al., 2017). Thus, based on different conditions of rainfall or flood return periods, how to arrange the urban and UFZ landscape in ways more scientific and reasonable, becomes the key solution for future urban rainwater management. Meanwhile, different drainage schemes are needed to accommodate the drainage needs of different UFZs with various runoff risks.
In addition, the “advantages” of the urban area itself should be put to full use to alleviate the drainage pressure from UFZs with high runoff risks. Based on the “source-sink” landscape theory (Jiang et al., 2013), the HH areas (Figure 5) could be treated as the “source” areas for urban runoff, with the LH areas (the light blue area in Figure 5, indicating the transitional regions between the UFZs with high and low runoff risks) as the “sink” areas. By building landscape corridors (i.e., diversion canals, drainage pipelines) for runoff drainage between the HH and LH areas, redundant rainwater from HH areas can be conveyed to LH areas timely. This task could not only alleviate the flooding risk of UFZs with high runoff risks efficiently, but also reduce the construction cost for building drainage systems and improve the urban water conservation function.

4 Conclusions

Urbanization will be an inevitable trend in China for a long time. Thus, relieving the urban flood hazard caused by urbanization should be treated as a long-term goal for urban planning and management. In this study, quantitative research was conducted on the rainfall-runoff characteristics within the built-up region of Beijing, which may provide scientific implications for science-based urban planning and management. The conclusions from the study results can be as follows.
(1) The average runoff ratio of the whole study area increases with increase of the rainfall return period. However, spatial differences in the runoff of different UFZs were found: the low runoff risk areas were mainly distributed outside the Fourth Ring Road; the areas with higher runoff risks were mainly distributed within the Fourth Ring Road (mainly commercial and residential areas).
(2) The runoff characteristics varied significantly among different UFZs. The main reason was the degree of impervious coverage within the different UFZs.
(3) A significantly positive spatial autocorrelation of runoff risk was found in the study area, and showed a spatial pattern with a cluster region of higher runoff risks within the urban center, and a circular distribution pattern of lower runoff risks around the Fifth Ring Road. In particular, the runoff ratio of the high runoff risk areas (HH: composed of commercial and residential areas) was higher than that of the whole study area. The low runoff risk areas (LL) were mainly composed of urban greening spaces.
(4) The emphasis in urban planning should be put on UFZs with greater runoff area (the HH zones), in order to alleviate risks from urban runoff. Meanwhile, the heterogeneity of the landscape pattern should be fully considered to tap potential ecological advantages and thereby reduce the pressure on the urban drainage system.

The authors have declared that no competing interests exist.

References

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[1]
Armson D, Stringer P, Ennos A R, 2013. The effect of street trees and amenity grass on urban surface water runoff in Manchester, UK.Urban Forestry & Urban Greening, 12(3): 282-286.It is well known that the process of urbanization alters the hydrological performance of an area, reducing the ability of urban areas to cope with heavy rainfall events. Previous investigations into the role that trees can play in reducing surface runoff have suggested they have low impact at a city wide scale, though these studies have often only considered the interception value of trees.This study assessed the impact of trees upon urban surface water runoff by measuring the runoff from 9 m(2) plots covered by grass, asphalt, and asphalt with a tree planted in the centre. It was found that, while grass almost totally eliminated surface runoff, trees and their associated tree pits, reduced runoff from asphalt by as much as 62%. The reduction was more than interception alone could have produced, and relative to the canopy area was much more than estimated by many previous studies. This was probably because of infiltration into the tree pit, which would considerably increase the value of urban trees in reducing surface water runoff. (C) 2013 Elsevier GmbH. All rights reserved.

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[2]
Atkinson S, 2012. A storm water runoff investigation using GIS and remote sensing [D]. Unviersity of North Texas.

[3]
Baker T J, Miller S N, 2013. Using the Soil and Water Assessment Tool (SWAT) to assess land use impact on water resources in an East African watershed.Journal of Hydrology, 486(8): 100-111.Land cover and land use changes in Kenya Rift Valley have altered the hydrologic response of the River Njoro watershed by changing the partitioning of excess rainfall into surface discharge and groundwater recharge. The watershed contributes a significant amount of water to Lake Nakuru National Park, an internationally recognized Ramsar site, as well as groundwater supplies for local communities and the city of Nakuru. Three land use maps representing a 17-year period when the region underwent significant transitions served as inputs for hydrologic modeling using the Automated Geospatial Watershed Assessment (AGWA) tool, a GIS-based hydrologic modeling system. AGWA was used to parameterize the Soil and Water Assessment Tool (SWAT), a hydrologic model suitable for assessing the relative impact of land cover change on hydrologic response. The SWAT model was calibrated using observation data taken during the 1990s with high annual concordance. Simulation results showed that land use changes have resulted in corresponding increases in surface runoff and decreases in groundwater recharge. Hydrologic changes were highly variable both spatially and temporally, and the uppermost reaches of the forested highlands were most significantly affected. These changes have negative implications for the ecological health of the river system as well as Lake Nakuru and local communities.

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[4]
Dunnett N, Nagase A, Booth Ret al., 2008. Influence of vegetation composition on runoff in two simulated green roof experiments.Urban Ecosystems, 11(4): 385-398.

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[5]
Ebrahimian A, Gulliver J S, Wilson B N, 2016. Effective impervious area for runoff in urban watersheds.Hydrological Processes, 30(20): 3717-3729.Abstract Effective impervious area (EIA), or the portion of total impervious area (TIA) that is hydraulically connected to the storm sewer system, is an important parameter in determining actual urban runoff. EIA has implications in watershed hydrology, water quality, environment, and ecosystem services. The overall goal of this study is to evaluate the application of successive weighted least square (WLS) method to urban catchments with different sizes and various hydrologic conditions to determine EIA fraction. Other objectives are to develop insights on the data selection issues, EIA fraction, EIA/TIA ratio, and runoff source area patterns in urban catchments. The successive WLS method is applied to 50 urban catchments with different sizes from less than 1a to more than 2000a in Minnesota, Wisconsin, Texas, USA as well as Europe, Canada, and Australia. The average, median, and standard deviation of EIA fractions for the 42 catchments with residential land uses are found to be 0.222, 0.200, and 0.113, respectively. These values for the EIA/TIA ratio in the same 42 catchments are 0.50, 0.48, and 0.21, respectively. While the EIA/TIA results indicate the importance of EIA, 95% prediction interval of the mean EIA/TIA is found to be 0.07 to 0.93, which shows that using an average value for this ratio in each land use to determine EIA from TIA in ungauged urban watersheds can be misleading. The successive WLS method was robust and is recommended for determining EIA in gauged urban catchments. Copyright 2016 John Wiley & Sons, Ltd.

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[6]
Fan F L, Deng Y B, Hu X Fet al., 2013. Estimating composite curve number using an Improved SCS-CN Method with Remotely Sensed Variables in Guangzhou, China.Remote Sensing, 5(3): 1425-1438.The rainfall and runoff relationship becomes an intriguing issue as urbanization continues to evolve worldwide. In this paper, we developed a simulation model based on the soil conservation service curve number (SCS-CN) method to analyze the rainfall-runoff relationship in Guangzhou, a rapid growing metropolitan area in southern China. The SCS-CN method was initially developed by the Natural Resources Conservation Service (NRCS) of the United States Department of Agriculture (USDA), and is one of the most enduring methods for estimating direct runoff volume in ungauged catchments. In this model, the curve number (CN) is a key variable which is usually obtained by the look-up table of TR-55. Due to the limitations of TR-55 in characterizing complex urban environments and in classifying land use/cover types, the SCS-CN model cannot provide more detailed runoff information. Thus, this paper develops a method to calculate CN by using remote sensing variables, including vegetation, impervious surface, and soil (V-I-S). The specific objectives of this paper are: (1) To extract the V-I-S fraction images using Linear Spectral Mixture Analysis; (2) To obtain composite CN by incorporating vegetation types, soil types, and V-I-S fraction images; and (3) To simulate direct runoff under the scenarios with precipitation of 57mm (occurred once every five years by average) and 81mm (occurred once every ten years). Our experiment shows that the proposed method is easy to use and can derive composite CN effectively.

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[7]
Fu S H, Wang H Y, Wang X Let al., 2013. The runoff curve number of SCS-CN method in Beijing.Geographical Research, 32(5): 797-807. (in Chinese)Soil Conservation Service curve number(SCS-CN) is widely used to calculate runoff because it only needs one parameterunoff curve number(CN) which reflects the soil and landuse characteristics.The purpose of this study is to identify the curve number in the SCS-CN method in Beijing.The rainfall and runoff data of 64 runoff plots in three counties of Miyun,Yanqing and Mentougou,were used to calculate runoff curve number.The constant water head method was used to measure the saturated hydraulic conductivity of main soil types and landuse types in Beijing.The empirical equation was used to calculate the saturated hydraulic conductivity of the 64 runoff plots.The saturated hydraulic conductivity was used to determine the hydrologic soil groups of runoff plots in Beijing.The runoff curve numbers under different hydrologic soil groups and landuse types in Beijing were provided.The results show that the hydrologic soil groups could be identified into and B.The B hydrologic soil group covers most parts of Beijing.The curve number was greatly affected by land use,soil conservation measures,land use cover and antecedent moisture condition.When the other conditions remained unchanged,the curve number obtained from Beijing's runoff plots was greater than that provided by Soil Conservation Service.These results can be served as runoff prediction and landuse management.

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[8]
Gajbhiye S, Mishra S, 2012. Application of NRSC-SCS curve number model in runoff estimation using RS & GIS,International Conference on Advances in Engineering, Science and Management, IEEE, 346-352.This study aims to determine the runoff depth using NRCS-CN method with Remote sensing and Geographical Information System (GIS) and the effect of slope on runoff generation. This study was carried out in Bamhani catchment located in Mandla district of Madhya Pradesh. The USDA NRCS- CN method was applied for estimating the runoff depth in the Bamhani catchment. Soil map, Land Use and slope map were generated in GIS (Geographical Information System) Environment. The curve number method was followed to estimate runoff depth for selected storm events in the watershed. Effect of slope on CN values and runoff depth was determined. Statistically positive correlations were detected between between estimated and observed runoff depth is 0.77 and slope adjusted vs. observed runoff depth is 0.76. The result showed that the CN unadjusted value are lower in comparison to CN adjusted with slope. Remote sensing and GIS is very reliable technique for the preparation of most of the input data required by the SCS curve number model.

[9]
GB50014, 2013. Code for Design of Outdoor Wastewater Engineering. (in Chinese)

[10]
Gill S, Handley J, Ennos Aet al., 2007. Adapting cities for climate change: The role of the green infrastructure.Built Environment, 33(1): 115-133.The urban environment has distinctive biophysical features in relation to surrounding rural areas. These include an altered energy exchange creating an urban heat island, and changes to hydrology such as increased surface runoff of rainwater. Such changes are, in part, a result of the altered surface cover of the urban area. For example less vegetated surfaces lead to a decrease in evaporative cooling, whilst an increase in surface sealing results in increased surface runoff. Climate change will amplify these distinctive features. This paper explores the important role that the green infrastructure, i.e. the greenspace network, of a city can play in adapting for climate change. It uses the conurbation of Greater Manchester as a case study site. The paper presents output from energy exchange and hydrological models showing surface temperature and surface runoff in relation to the green infrastructure under current and future climate scenarios. The implications for an adaptation strategy to climate change in the urban environment are discussed.

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[11]
Jarden K M, Jefferson A J, Grieser J M, 2015. Assessing the effects of catchment-scale urban green infrastructure retrofits on hydrograph characteristics.Hydrological Processes, 291(1): 6-14.Run-off from impervious surfaces has pervasive and serious consequences for urban streams, but the detrimental effects of urban stormwater can be lessened by disconnecting impervious surfaces and redirecting run-off to decentralized green infrastructure. This study used a beforefter-control-impact design, in which streets served as subcatchments, to quantify hydrologic effectiveness of street-scale investments in green infrastructure, such as street-connected bioretention cells, rain gardens and rain barrels. On the two residential treatment streets, voluntary participation resulted in 32.2% and 13.5% of parcels having green infrastructure installed over a 2-year period. Storm sewer discharge was measured before and after green infrastructure implementation, and peak discharge, total run-off volume and hydrograph lags were analysed. On the street with smaller lots and lower participation, green infrastructure installation succeeded in reducing peak discharge by up to 33% and total storm run-off by up to 40%. On the street with larger lots and higher participation, there was no significant reduction in peak or total stormflows, but on this street, contemporaneous street repairs may have offset improvements. On the street with smaller lots, lag times increased following the first phase of green infrastructure construction, in which streetside bioretention cells were built with underdrains. In the second phase, lag times did not change further, because bioretention cells were built without underdrains and water was removed from the system, rather than just delayed. We conclude that voluntary green infrastructure retrofits that include treatment of street run-off can be effective for substantially reducing stormwater but that small differences in design and construction can be important for determining the level of the benefit. Copyright 2015 John Wiley & Sons, Ltd.

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[12]
Jiang M, Chen H, Chen Q, 2013. A method to analyze “source-sink” structure of non-point source pollution based on remote sensing technology.Environmental Pollution, 182: 135-140.With the purpose of providing scientific basis for environmental planning about non-point source pollution prevention and control, and improving the pollution regulating efficiency, this paper established the Grid Landscape Contrast Index based on Location-weighted Landscape Contrast Index according to the “source–sink” theory. The spatial distribution of non-point source pollution caused by Jiulongjiang Estuary could be worked out by utilizing high resolution remote sensing images. The results showed that, the area of “source” of nitrogen and phosphorus in Jiulongjiang Estuary was 534.42km 2 in 2008, and the “sink” was 172.06km 2 . The “source” of non-point source pollution was distributed mainly over Xiamen island, most of Haicang, east of Jiaomei and river bank of Gangwei and Shima; and the “sink” was distributed over southwest of Xiamen island and west of Shima. Generally speaking, the intensity of “source” gets weaker along with the distance from the seas boundary increase, while “sink” gets stronger.

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[13]
Kadam A K, Kale S S, Pande N Net al., 2012. Identifying potential rainwater harvesting sites of a semi-arid, basaltic region of Western India, using SCS-CN method.Water Resources Management, 26(9): 2537-2554.Upper Karha watershed from semi-arid part of Deccan Volcanic Province, India was investigated to identify the potential sites to construct rainwater harvesting structures with the help of remote sensing and geographical information system. Attempt was made to understand the basaltic terrain in spatial context to find out the rainwater harvesting structures like farm ponds, percolation tank, check dams and gully plugs deriving from thematic layers, such as landuse/landcover, slope, soil, drainage and runoff from Landsat Thematic Mapper imagery and other collateral data. Subsequently, these layers were processed to derive runoff from Soil Conservation Service Curve Number (SCS-CN) method using Arc-CN runoff tool. The SCS-CN method shows that the high runoff potential is from water-body, agriculture land (including harvested land) and followed by settlement, open scrub, dense scrub and low for the open forest, dense forest area. Parameters like hydro-geomorphology, geology were considered as per Integrated Mission for Sustainable Development specifications for identification of the structures. The thematic layers overlaid using intersection based on these specifications. Derived sites were investigated for its suitability and implementation by ground truth field verification. In conclusion, the method adopted in present study deciphers the more precise, accurate and ability to process large catchment area than other methods.

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[14]
Lin F T, 2000. GIS-based information flow in a land-use zoning review process.Landscape and Urban Planning, 52(1): 21-32.This work describes a geographical information system (GIS)-based information flow for a land-use zoning review process. GIS technology is employed not only to edit and display maps as conventional GIS applications, but also to enhance work quality. These enhancements include an exploration of hidden information, the production of tentative zoning maps, recognizing potentially problematic areas, conducting crucial site investigations, facilitating informative public hearing, and presenting potential policies. In the case of the Yanginghan (YMS) National Park, Taiwan, a GIS-based information flow is employed to assist in the land-use zoning review process. This GIS-based information system reveals several features including: (1) a new, more complicated and effective information flow; (2) close coordination of computing and noncomputing sub-processes; (3) prior identification of over and under-regulated areas to avoid potential appeals and conflicts; (4) economical and effective site investigations, and (5) potential policies established for both private and public land. The case of the YMS National Park is encouraging. We believe that the application of a GIS-based information flow is beneficial to both the zoning plan production and the review process.

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[15]
Milly P, Wetherald R, Dunne Ket al., 2002. Increasing risk of great floods in a changing climate.Nature, 415: 514-517.

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[16]
NRCS, 1986. Urban hydrology for small watersheds.Technical Release, 55: 2-6.

[17]
Ouyang W, Guo B, Hao Fet al., 2012. Modeling urban storm rainfall runoff from diverse underlying surfaces and application for control design in Beijing.Journal of Environmental Management, 113(1): 467-473.Managing storm rainfall runoff is paramount in semi-arid regions with urban development. In Beijing, pollution prevention in urban storm runoff and storm water utilization has been identified as the primary strategy for urban water management. In this paper, we sampled runoff during storm rainfall events and analyzed the concentration of chemical oxygen demand (COD), total suspended solids (TSS) and total phosphorus (TP) in the runoff. Furthermore, the first flush effect of storm rainfall from diverse underlying surfaces was also analyzed. With the Storm Water Management Model (SWMM), the different impervious rates of underlying surfaces during the storm runoff process were expressed. The removal rates of three typical pollutants and their interactions with precipitation and underlying surfaces were identified. From these rates, the scenarios regarding the urban storm runoff pollution loading from different designs of underlying pervious rates were assessed with the SWMM. First flush effect analysis showed that the first 20% of the storm runoff should be discarded, which can help in utilizing the storm water resource. The results of this study suggest that the SWMM can express in detail the storm water pollution patterns from diverse underlying surfaces in Beijing, which significantly affected water quality. The scenario analysis demonstrated that impervious rate adjustment has the potential to reduce runoff peak and decrease pollution loading.

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[18]
Pan A, Zhang S, Meng Qet al., 2009. Initial concept of stormwater and flood management in Beijing city.China Water & Wastewater, 25(22): 9-12. (in Chinese)The acceleration of urbanization progress brings some water problems such as flood water,water scarcity,water pollution and so on.The rainwater harvesting measures in buildings and residential areas have better effect on control and utilization of design storm.But it is difficult to deal with larger storm especially over-design storm.Therefore,it is necessary that an integral stormwater and flood management in the whole city should be established based on the prediction,monitoring and simulation of rainfall runoff,stormwater drainage network and flood river to solve this problem.Based on the current condition of Beijing City,the initial concept of stormwater and flood management and some key problems needing further study are put forward with a view to promote the implementation of Beijing City stormwater and flood management and the construction of livable city.

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[19]
Putro B, Kjeldsen T R, Hutchins M Get al., 2016. An empirical investigation of climate and land-use effects on water quantity and quality in two urbanising catchments in the southern United Kingdom.Science of The Total Environment, 548/549: 164-172.Using historical data of climate, land-use, hydrology and water quality from four catchments located in the south of England, this study identifies the impact of climate and land-use change on selected water quantity and water quality indicators. The study utilises a paired catchment approach, with two catchments that have experienced a high degree of urbanisation over the past five decades and two nearby, hydrologically similar, but undeveloped catchments. Multivariate regression models were used to assess the influence of rainfall and urbanisation on runoff (annual and seasonal), dissolved oxygen levels and temperature. Results indicate: (i) no trend in annual or seasonal rainfall totals, (ii) upward trend in runoff totals in the two urban catchments but not in the rural catchments, (iii) upward trend in dissolved oxygen and temperature in the urban catchments, but not in the rural catchments, and (iv) changes in temperature and dissolved oxygen in the urban catchments are not driven by climatic variables.

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[20]
Shuster W D, Bonta J, Thurston Het al., 2005. Impacts of impervious surface on watershed hydrology: A review.Urban Water Journal, 2(4): 263-275.Increased impervious surface area is a consequence of urbanization, with correspondent and significant effects on the hydrologic cycle. It is intuitive that an increased proportion of impervious surface brings with it shorter lag times between onset of precipitation and subsequently higher runoff peaks and total volume of runoff in receiving waters. Yet, documentation on quantitative relationships between the extent and type of impervious area and these hydrologic factors remains dispersed across several disciplines. We present a literature review on this subject to better understand and synthesize distinctions among different types of impermeable surface and their relative impacts, and describe the manner in which these surfaces are assessed for their putative impacts on landscape hydrology.

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[21]
Singh P K, Yaduvanshi B K, Patel Set al., 2013. SCS-CN based quantification of potential of rooftop catchments and computation of ASRC for rainwater harvesting.Water Resources Management, 27(7): 2001-2012.Rooftop rainwater harvesting, among other options, play a central role in addressing water security and reducing impacts on the environment. The storm or annual storm runoff coefficient (RC/ASRC)...

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[22]
Skotnicki M, Sowiński M, 2013. The influence of depression storage on runoff from impervious surface of urban catchment.Urban Water Journal, 12(3): 207-218.This paper contains results of a depression storage investigation based on simulations of runoff using SWMM 5 software and measurements from a real urban catchment in Poznan, Poland. The catchment area is 6.7 km2 and its average imperviousness has been evaluated as 29 %. Altogether, 46 rainfall events, registered by tipping-bucket raingauges in years 20060900092010 in three stations, have been analysed. The best agreement of the computed outflow hydrographs with the results of measurements has been obtained for a depression storage depth of 1.5 mm. The influence of spatial distribution of impervious surface depression on the shape of the computed hydrographs has been found to not be significant.

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[23]
Su M, Zheng Y, Hao Yet al., 2017. The influence of landscape pattern on the risk of urban water-logging and flood disaster.Ecological Indicators, doi:10.1016/j.ecolind.2017.03.008Most Chinese cities face a series of ‘urban diseases’ or problems during rapid urbanization, and of which urban precipitation and subsequent water-logging is a severe hotspot. A better understanding of the influence of urban land-use patterns on water-logging will be helpful for enhancing urban flood resistance. The relationship between the characteristics of land-use patterns and the risk of urban water-logging and flood disaster (UWLFD) was analyzed in this paper, using landscape pattern indicators to describe the land-use structure. These included patch density (PD), edge density (ED), landscape division index (DIVISION), contagion (CONTAG), Shannon’s evenness index (SHEI), and Shannon’s diversity index (SHDI). The risk of UWLFD was measured using the topographic slope and urban surface cover. Based on GIS and remote sensing data in 2003 and 2013, a case study of the metropolitan region of Kunming City showed that the risk of UWLFD had a positive correlation with landscape fragmentation (e.g., PD and ED), and strong negative correlation with landscape contagion (e.g., CONTAG) during the study period. This implied that landscape fragmentation aggravated the risk of UWLFD while landscape connectivity reduced the risk. Measures such as unified and long-term urban planning and design and the construction of green infrastructure will reduce the risk of UWLFD. The relationship between the landscape pattern and the risk of UWLFD provides a new perspective for systematic urban planning.

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[24]
Sun R, Lü Y, Chen Let al., 2013. Assessing the stability of annual temperatures for different urban functional zones.Building and Environment, 65(7): 90-98.The urban functional zone (UFZ) is the basic unit of urban planning, which is defined as an area of similar social and economic functions. Despite the importance of UFZs, the stability of their annual temperature between winter and summer has seldom been investigated. With an understanding of the thermal impacts that planning decisions can have, it is essential to know how UFZs can be designed to regulate temperatures in the urban environment. 690 UFZs were identified using ALOS images in 2009 in Beijing. Land surface temperature (LST) was extracted from daytime Landsat TM (2002) and ASTER (2009) images. The regional LST variation of 31 district-sized sub-regions was correlated to the types of UFZs in the region and structural features of the region such as area, size, diversity, complexity and connectivity. Results showed that: (1) UFZ types, in order from highest to lowest LST variation, were commercial, campus, high density residential, water, recreational, low density residential, road, preservation, and agricultural zones; (2) the regional LST variation was positively correlated with the area of campus, commercial, high density residential, water, and road zones, but negatively correlated with the area of agricultural and low density residential zones; (3) increased connectivity and complexity decreased regional LST variations. The results indicated that the stability of annual temperatures was determined not only by the UFZ type and size but also by the connectivity and complexity. These results are clearly useful and essential pieces of information that can be applied in urban planning to improve climate adaptability. Crown Copyright (c) 2013 Published by Elsevier Ltd. All rights reserved.

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[25]
Sunde M, He H S, Hubbart J Aet al., 2016. Forecasting streamflow response to increased imperviousness in an urbanizing Midwestern watershed using a coupled modeling approach.Applied Geography, 72: 14-25.Increased impervious surface (IS) cover is often the primary disturbance contributing to altered hydrology in urbanizing watersheds, affecting various components of the hydrologic balance. To improve the understanding of how future urban development will influence watershed streamflow characteristics, and to develop growth strategies that preserve water resources, it is necessary to combine detailed estimates of future IS cover with hydrologic models. A coupled modeling approach is presented to help address this problem. Pixel-based percentage IS cover for the period 2011–2031 was derived using the Imperviousness Change Analysis Tool (I-CAT) for three urban growth scenarios and coupled with the Soil Water Assessment Tool (SWAT) to simulate the potential hydrologic impacts of future urbanization in Hinkson Creek watershed, located in the Midwestern U.S. state of Missouri. Increases to average annual streamflow (+12.81% to+19.74%), increases to average annual surface runoff (+14.32% to+16.77%), reductions to evapotranspiration (618.68% to 6113.37%), and slight increases to baseflow were observed for the three growth scenarios. The approach used here created a range of possible future conditions for the study watershed and presented a framework that allows planners to couple realistic IS cover estimates with hydrologic models. Additionally, this study emphasized that a controlled, more environmentally conscious growth pattern does not necessarily produce less pronounced hydrologic impacts for the study watershed compared to an uncontrolled growth pattern, underscoring the importance of considering neighboring watersheds when analyzing the hydrologic impacts of urban development for an area.

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[26]
Tian G J, Wu J G, Yang Z F, 2010. Spatial pattern of urban functions in the Beijing metropolitan region.Habitat International, 34(2): 249-255.The morphology of a city affects its ecological and socioeconomic functions, and thus how a city is spatially structured has important bearings on urban sustainability. The paper analyzes the spatial pattern of Beijing in relation to its urban functions. Our results show that the 6 concentric ring-roads in Beijing provide a basic framework for the city's overall spatial pattern, and also give its apparent resemblance to the classic concentric zone theory. The paper identifies 5 concentric zones for Beijing based on a suite of urban functions. However, there are significant differences between the urban spatial pattern of Beijing and that depicted in the classic concentric zone theory. The study sheds new light on the urban morphology of one of the major Chinese cities, and provides needed information for developing plans to diffuse urban functions in Beijing.

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[27]
Wang Q, Zhang X, Wei Met al., 2011. Research summary of planning and design standards for storm water system in Beijing city.Water & Wastewater Engineering, 37(10): 34-39.According to the requirements of Beijing economic development and standards of flood control,based on the analysis of planning and design verification method,evaluation method and rainfall trend,series of planning and design criteria such as storm intensity formula,runoff coefficient,rainfall pattern and design rainfall return period were studied and revised,which were important for improving urban drainage system,ensuring urban safe operation and reducing flooding.

[28]
Yao L, Chen L, Wei W, 2017. Exploring the linkage between urban flood risk and spatial patterns in small urbanized catchments of Beijing, China.International Journal of Environmental Research and Public Health, 14(3): 239.In the context of global urbanization, urban flood risk in many cities has become a serious environmental issue, threatening the health of residents and the environment. A number of hydrological studies have linked urban flooding issues closely to the spectrum of spatial patterns of urbanization, but relatively little attention has been given to small-scale catchments within the realm of urban systems. This study aims to explore the hydrological effects of small-scaled urbanized catchments assigned with various landscape patterns. Twelve typical residential catchments in Beijing were selected as the study areas. Total Impervious Area (TIA), Directly Connected Impervious Area (DCIA), and a drainage index were used as the catchment spatial metrics. Three scenarios were designed as different spatial arrangement of catchment imperviousness. Runoff variables including total and peak runoff depth (Qt and Qp) were simulated by using Strom Water Management Model (SWMM). The relationship between catchment spatial patterns and runoff variables were determined, and the results demonstrated that, spatial patterns have inherent influences on flood risks in small urbanized catchments. Specifically: (1) imperviousness acts as an effective indicator in affecting both Qt and Qp; (2) reducing the number of rainwater inlets appropriately will benefit the catchment peak flow mitigation; (3) different spatial concentrations of impervious surfaces have inherent influences on Qp. These findings provide insights into the role of urban spatial patterns in driving rainfall-runoff processes in small urbanized catchments, which is essential for urban planning and flood management.

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[29]
Yao L, Chen L, Wei Wet al., 2015. Potential reduction in urban runoff by green spaces in Beijing: A scenario analysis.Urban Forestry & Urban Greening, 14(2): 300-308.Urban green space provides multiple ecological benefits, among which the reduction of rainfall runoff is important for sustainable urban development, particularly for cities experiencing severe flooding and water hazards. However, the effectiveness of urban green space in mitigating runoff has not been fully determined. We evaluated potential reductions in surface runoff associated with urban green space in central Beijing under a greening scenario using the Soil Conservation Service Curve Number method. The results show that urban green space offers significant potential for runoff mitigation. In 2012, a total of 97.9 million m 3 of excess surface runoff was retained by urban green space; adding nearly 11% more tree canopy was projected to increase runoff retention by >30%, contributing to considerable benefits of urban rainwater regulation. At a more detailed scale, there were apparent internal variations. Urban function zones with >70% developed land showed less mitigation of runoff, while green zones (vegetation >60%), which occupied only 15.54% of the total area, contributed 31.07% of runoff reduction. Runoff reduction by urban green space, however, is influenced by many factors, such as rainfall, soil condition, and urban morphology. In regulating urban runoff, therefore, the priorities and integrating adaptive approaches to urban greening should be combined with compensatory and complementary measures.

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[30]
Yao L, Wei W, Chen L, 2016. How does imperviousness impact the urban rainfall-runoff process under various storm cases?Ecological Indicators, 60: 893-905.Dramatic changes in imperviousness exert significant influence on the rainfall-runoff process in urban catchments. In urban rainwater management, imperviousness is generally adopted as an effective indicator for assessing potential runoff risk. However, the effects of imperviousness on rainfall-runoff at the scale of small urbanized drainage areas have not been fully determined, particularly when various storm characteristics are considered. In this paper, a model-based analysis is conducted in a typical urban residential catchment in Beijing, China, in which 69 subareas are delineated within the catchment as the basic drainage units. Two metrics, total impervious area (TIA) and directly connected impervious area (DCIA), are employed to quantify the spatial characteristics of imperviousness of the subareas. Three runoff variables within the delineated subareas including total runoff depth ( Q t ), peak runoff depth ( Q p ), and lag time ( T lag ) are simulated by using the Storm Water Management Model (SWMM) to represent the specific rainfall-runoff characteristics. Moreover, model input storms are designated to several typical flood-induced rainfall events with varying amounts, locations of rainfall peak, and durations for holistic assessment of imperviousness. Regression analyses are conducted to explore the contributions and relative significances of impervious metrics in predicting runoff variables under various storm cases. The results indicate that the performances of imperviousness with fine spatial scale (34mm) may vary markedly according to storm conditions. Specifically, TIA rather than DCIA acts as a dominate factor affecting total runoff, and its significance maintains relatively stable with various storm conditions. In addition, the combined use of both TIA and DCIA are more effective for predicting peak runoff than that using a single impervious metric; however, rainfall amount, peak location, and duration alter the contribution gaps between TIA and DCIA and the overall performance of the regression model. Moreover, DCIA is more likely to affect runoff lag time without the contribution of TIA; however, an increase in rainfall peak ratio or duration will significantly limit its performance. These results can provide insight into the hydrologic performance of imperviousness, which is essential for landscape design and runoff regulation in small urban catchments.

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[31]
Zhang B, Xie G, Zhang Cet al., 2012a. The economic benefits of rainwater-runoff reduction by urban green spaces: A case study in Beijing, China.Journal of Environmental Management, 100(10): 65-71.Abstract Urbanization involves the replacement of vegetated surfaces with impervious built surfaces, and it often results in an increase in the rate and volume of rainwater surface runoff. Urban green spaces play a positive role in rainwater-runoff reduction. However, few studies have explored the benefits of rainwater-runoff reduction by urban green spaces. Based on inventory data of urban green spaces in Beijing, the paper evaluated the economic benefits of rainwater-runoff reduction by urban green spaces, using the rainwater-runoff-coefficient method as well as the economic valuation methods. The results showed that, 2494 cubic meters of potential runoff was reduced per hectare of green area and a total volume of 154 million cubic meters rainwater was stored in these urban green spaces, which almost corresponds to the annual water needs of the urban ecological landscape in Beijing. The total economic benefit was 1.34 billion RMB in 2009 (RMB: Chinese currency, US$1=RMB6.83), which is equivalent to three-quarters of the maintenance cost of Beijing's green spaces; the value of rainwater-runoff reduction was 21.77 thousand RMB per hectare. In addition, the benefits in different districts and counties were ranked in the same order as urban green areas, and the average benefits per hectare of green space showed different trends, which may be related to the impervious surface index in different regions. This research will contribute to an understanding of the role that Beijing's green spaces play in rainwater regulation and in the creation and scientific management of urban green spaces. Copyright 2012 Elsevier Ltd. All rights reserved.

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[32]
Zhang X, Zhang X, Hu Set al., 2012b. Runoff and sediment modeling in a peri-urban artificial landscape: Case study of Olympic Forest Park in Beijing.Journal of Hydrology, 485: 126-138.

[33]
Zhou F, Xu Y, Chen Yet al., 2013. Hydrological response to urbanization at different spatio-temporal scales simulated by coupling of CLUE-S and the SWAT model in the Yangtze River Delta region.Journal of Hydrology, 485: 113-125.The Main objective of the study is to understand and quantify the hydrological responses of land use and land cover changes. The Yangtze River Delta is one of the most developed regions in China with the rapid development of urbanization which serves as an excellent case study site for understanding the hydrological response to urbanization and land use change. The Xitiaoxi River basin, one of the main upstream rivers to the Taihu Lake in the Yangtze River Delta, was selected to perform the study. The urban area in the basin increased from 37.8km 2 in 1985 to 105km 2 in 2008. SWAT model, which makes direct use of land cover and land use data in simulating streamflow, provides as a useful tool for performing such studies and is therefore used in this study. The results showed that (1) the expansion of urban areas had a slight influence on the simulated annual streamflow and evapotranspiration (ET) as far as the whole catchment is concerned; (2) surface runoff and baseflow were found more sensitive to urbanization, which had increased by 11.3% and declined by 11.2%, respectively; (3) changes in streamflow, evapotranspiration and surface runoff were more pronounced during the wet season (from May to August), while baseflow and lateral flow had a slight seasonal variation; (4) the model simulated peak discharge increased 1.6-4.3% and flood volume increased 0.7-2.3% for the selected storm rainfall events at the entire basin level, and the change rate was larger for smaller flood events than for larger events; (5) spatially, changes of hydrological fluxes were more remarkable in the suburban basin which had a relative larger increase in urbanization than in rural sub-basins; and (6) analysis of future scenarios showed the impacts of urbanization on hydrological fluxes would be more obvious with growth in impervious areas from 15% to 30%. In conclusion, the urbanization would have a slight impact on annual water yield, but a remarkable impact was found on surface runoff, peak discharge and flood volume especially in suburban basins in the study area. The study suggested that more attention must be paid for flood mitigation and water resources management in planning future urban development in the region.

DOI

[34]
Zhu Z, Chen Z, Chen Xet al., 2016. Approach for evaluating inundation risks in urban drainage systems.Science of The Total Environment, 553: 1-12.Abstract Urban inundation is a serious challenge that increasingly confronts the residents of many cities, as well as policymakers. Hence, inundation evaluation is becoming increasingly important around the world. This comprehensive assessment involves numerous indices in urban catchments, but the high-dimensional and non-linear relationship between the indices and the risk presents an enormous challenge for accurate evaluation. Therefore, an approach is hereby proposed to qualitatively and quantitatively evaluate inundation risks in urban drainage systems based on a storm water management model, the projection pursuit method, the ordinary kriging method and the K-means clustering method. This approach is tested using a residential district in Guangzhou, China. Seven evaluation indices were selected and twenty rainfall-runoff events were used to calibrate and validate the parameters of the rainfall-runoff model. The inundation risks in the study area drainage system were evaluated under different rainfall scenarios. The following conclusions are reached. (1) The proposed approach, without subjective factors, can identify the main driving factors, i.e., inundation duration, largest water flow and total flood amount in this study area. (2) The inundation risk of each manhole can be qualitatively analyzed and quantitatively calculated. There are 1, 8, 11, 14, 21, and 21 manholes at risk under the return periods of 1-year, 5-years, 10-years, 20-years, 50-years and 100-years, respectively. (3) The areas of levels III, IV and V increase with increasing rainfall return period based on analyzing the inundation risks for a variety of characteristics. (4) The relationships between rainfall intensity and inundation-affected areas are revealed by a logarithmic model. This study proposes a novel and successful approach to assessing risk in urban drainage systems and provides guidance for improving urban drainage systems and inundation preparedness. Copyright 2016 Elsevier B.V. All rights reserved.

DOI PMID

[35]
Zuo D, Xu Z, Yao Wet al., 2016. Assessing the effects of changes in land use and climate on runoff and sediment yields from a watershed in the Loess Plateau of China.Science of The Total Environment, 544: 238-250.The changes in runoff and sediment load in the Loess Plateau of China have received considerable attention owing to their dramatic decline during recent decades. In this paper, the impacts of land-use and climate changes on water and sediment yields in the Huangfuchuan River basin (HFCRB) of the Loess Plateau are investigated by combined usage of statistical tests, hydrological modeling, and land-use maps. The temporal trends and abrupt changes in runoff and sediment loads during 1954-2012 are detected by using non-parametric Mann-endall and Pettitt tests. The land-use changes between 1980 and 2005 are determined by using transition matrix analysis, and the effects of land-use and climate changes on water and sediment yields are assessed by using the Soil and Water Assessment Tool (SWAT) hydrological model and four scenarios, respectively. The results show significant decreasing trends in both annual runoff and sediment loads, whereas slightly decreasing and significantly increasing trends are detected for annual precipitation and air temperature, respectively. 1984 is identified as the dividing year of the study period. The land-use changes between 1980 and 2005 show significant effects of the Grain for Green Project in China. Both land-use change and climate change have greater impact on the reduction of sediment yield than that of water. Water and sediment yields in the upstream region show more significant decreases than those in the downstream region under different effects. The results obtained in this study can provide useful information for water resource planning and management as well as soil and water conservation in the Loess Plateau region.

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