The model of low impact development of a sponge airport: a case study of Beijing Daxing International Airport

A sponge airport is a new concept of airport stormwater management, which can effectively relieve airport flooding and promote the usage of rainwater resources, often including the application of low impact development (LID) facilities. Although many airports in China have been chosen to implement sponge airport construction, there is a lack of quantitative evaluation on the effect of LID facilities. This paper takes Beijing Daxing International Airport as a case study and develops a comprehensive evaluation on the effect of LID facilities using the storm water management model (SWMM). The performance of four LID design scenarios with different locations and sizes of the rain barrel, the vegetative swale, the green roof, and the storage tank were analyzed. After LID, the water depth of J7 reduces from 0.6 m to 0.2 m, and duration of accumulated water reduces from 5 hours to 2.5 hours. The water depth of J17 reduces from 0.5 m to 0.1 m, and duration of accumulated water reduces from 2 hours to 15 minutes. The capacity of conduits has been greatly improved (Link 7 and Link 17). The application of LID facilities greatly improves rainwater removal capacity and effectively alleviates the waterlogging risk in the study area. doi: 10.2166/wcc.2020.195 s://iwaponline.com/jwcc/article-pdf/doi/10.2166/wcc.2020.195/648788/jwc2020195.pdf Jing Peng (corresponding author) Jiayi Ouyang College of Airport, Civil Aviation University of China, No. 2898 Jin Bei Road, Dongli District, Tianjin, People’s Republic of China E-mail: pengjingtd@163.com Lei Yu Tianjin Lonwin Technology Development Co., Ltd., No. 15 Longtan Road, Hedong District, Tianjin, China


INTRODUCTION
In recent years, the concept of resilience has been introduced into the engineering field, in particular related to disaster mitigation and management (Cimellaro et  The content of sponge city is to advocate the construction of a 'rainwater system' with low impact, so that cities can absorb, save, store, filter, and purify rainwater when it rains like a sponge. When there is demand, it can reasonably release and make full use of the stored rainwater resources (Zhang et al. ).
With the increase of airport scale and passenger flow, the contradiction between supply and demand of airport water resources has become increasingly obvious. The water consumption data of some airports have been studied by Carvalho et al. (), who reported that the average water consumption is about 20 L/passenger, with about 800 thousand m 3 of water consumption per year. In addition to potable water, a large amount of water is used to meet the non-potable water requirements (Carvalho et al. ). A variety of models has been established to calculate the cost of rainwater utilization (Fernandes Moreira Neto et al. ).
new airport has also carried out design planning for a sponge airport. Through the construction of a digital rainwater management system, the rainwater pipeline system of the new airport has been designed and checked, and the waterlogging risk caused by excessive rainfall evaluated (Ren et al. ; Xie et al. ).
In summary, the current rainwater utilization at the airport mainly focuses on the treatment method, utilization cost of rainwater. Few scholars have conducted research on the sponge airport, especially the impact of LID facilities on airport rainwater utilization using a model. Traditional airport construction focuses on the fast drainage mode of rainwater by various underground pipes or open channels.
The pressure of the water supply and drainage facilities increase when there is heavy rain, while the rainwater cannot be discharged quickly, increasing the frequency of waterlogging in the airport. Therefore, this paper first puts forward the construction concept of sponge airport, and the LID facilities are designed and built. The airport can respond to heavy rain disasters like a sponge city with good elasticity.
When it rains, it absorbs water, stores water, and seeps water. When it is needed, it releases stored water and uses it. Then the software was applied to establish models, which can simulate the runoff of rainstorms and evaluate the effects of LID facilities. The water depth, capacity of conduits, and the number of overflow junctions and conduits are compared before and after implementation of LID facilities.
The research can be applied both to sponge cities and airports. It will help to achieve the construction goal of 'safe airport, green airport, smart airport, humanities airport' and contribute to the construction of a green, environmentally friendly and harmonious sponge city.

Design of LID facilities
The purpose of sponge airport construction is to design and construct a sponge airport by setting LID facilities which can store and discharge naturally, and achieve reasonable infiltrating, detention, storage, purification, reuse, and drainage of rainwater resources in the airport. That can make sponge airports, like sponges, have good 'elasticity' in adaptation to environmental changes and response to rainstorm disasters. When it rains, the airport will absorb, store, infiltrate, discharge and purify water, and, if necessary, the storage water will be released and utilized. The construction of a sponge airport can reduce the airport waterlogging crisis, realize the recycling of airport rainwater resources, improve the ecological environment to the greatest extent, and realize the natural purification and infiltration of rainwater.
The LID facilities for a sponge city mainly include biological retention, grass planting ditch, rainwater bucket, permeable pavement, concave green space, and so on. The LID facilities for a sponge airport are designed according to the land use characteristics of the airport. The main method of rainwater collection and utilization is discharge and drainage in the runway, taxiway, and apron area. The LID facilities of seepage, stagnant storage rainwater can be adopted, such as the soil area of the flying area, terminal area, and pavement. In this paper, the performance of four LID facilities with different locations and sizes of the rain barrel, the vegetative swale, the green roof, and the storage tank are analyzed. The applied location and role of LID facilities can be seen in Table 1.

Software
Many researchers use models to predict flood, forecast river flow, and produce storm water management (Mosavi et al. Rabori & Ghazavi ). SWMM has good versatility, relatively low demand for research data, no time step limit, and no scale limit. Therefore, the study presented in this paper investigates how SWMM can be implemented to simulate flood of the study airport.

Study area
Beijing is located in the north of China, with uneven rainfall distribution in the year. There are many sudden rainstorms in summer, which often lead to flood disasters. Thus, Beijing Daxing International Airport is taken as an example to study. Beijing Daxing International Airport is located in the Daxing District of Beijing. It is about 50 km from the center of Beijing. The location is shown in Figure 1. The airport is being constructed and operated in stages. The planned land area for this period (2020) is about 27 km 2 .
In the first phase of airport construction, the flight area, maintenance area, and freight area is large. The hard-surfaced area of the airport accounts for 69%. It will naturally change the original characteristics (Ge et al. ).
According to the topography of Beijing Daxing International Airport, it can be divided into seven drainage zones, namely, N1, N2, N3, N4, N5, N6, and S1. Because the rainwater drainage of the airport is very complex, the rainwater drainage system of Catchment N1 is an independent system (Figure 2), so N1 was taken as an example for simulation. Other catchments (such as N2, N3, and so on) can be further studied in the future. Catchment N1 includes the maintenance area, part of the flight area, and the west part has an area of 1.0 × 10 5 m 2 and a capacity of 2.7 × 10 5 m 3 .
Storm water was conveyed to the storage N1 through the nearest channels or pipes in the form of catchment surface runoff. The layout of rainwater junctions, conduits, and storage N1 in Catchment N1 is shown in Figure 2.

Rainfall data
Beijing has a temperate continental climate, which is hot and rainy in summer and prone to severe rainstorms. The aim of this paper is to verify whether the rainwater drainage  On this basis, the model is simulated in a 1-hour rainfall scenario with a 100-year return period ( Figure 3). The rainfall series used in this simulation is assumed to be an independent rainfall event. There is no rainfall before it (if there is rainfall before it, the junctions and conduits may have water accumulation before simulation. The simulation results will be affected by the previous rainfall, so it is impossible to evaluate the effect of this rainfall).

Model parameters' setting
The parameters of SWMM include hydrologic parameters and hydraulic parameters. The hydraulic parameters include the diameter, length, shape, and elevation of rainwater drainage pipes, which can be set according to the drainage engineering design drawing. The hydrologic parameters include area of the sub-catchment, width, percent slope, percent of impervious, Manning's n of impervious (N-Imperv), depth of depression storage of pervious (Dstore-Imperv), and so on. Some parameters can be set according to land use type of the study area. Some parameters are purely empirical, or empirical parameters with certain physical significance.
It is found that the main sensitive parameters affecting the output of SWMM model are N-imperv, N-perv, Dstore-perv, conduit roughness (Hu ). The slope of sub-catchment is obtained by analyzing the slope of regional digital elevation model (DEM) data. Dstore-Imperv and Dstore-perv are obtained by analyzing subsurface properties of the airport.
Referring to the experience value of literature and combining with the actual situation, Manning's n can be set. After sensitivity analysis and simulation calculation, the appropriate parameter values are finally set. In this study, the rainwater drainage pipe is concrete channels. Manning's n of concrete channels is set to 0.013. Impervious area includes runway, taxiway and apron, which is mainly cement concrete pavement. N-imperv is set to 0.012. Permeable area is mainly soil surface area with grass. N-perv can be set to 0.2. Dstoreperv is set to 3 mm in the model without LID facilities.
Dstore-perv will be increased to 10 mm.
The infiltration parameters depend on which infiltration model was selected for the project: Horton, Green-Ampt, or curve number. Green-Ampt requires very high soil data.
Curve number only reflects the underlying surface of the basin and does not reflect the rainfall process. It is only suitable for large basins. Horton is often used in rainfall-runoff simulation of urban small watersheds. Therefore, Horton is adopted in this study.

RESULTS AND DISCUSSION
In this study, a traditional hydrological model was built The results of simulation show that part of the rainwater pipe network is the key to restricting the rainwater drainage system, and there is a bottleneck area. Due to the full flow of Link 6 and Link 7, rainwater cannot be discharged in time and quickly, resulting in water accumulation at J7 and J8.
Due to the full flow of Link 14, Link 15, and Link 16, rainwater cannot be discharged in time and quickly, resulting in water accumulation at J15, J16, and J17. These conduits are the cause of bottlenecks in the rainwater drainage system in the study area. In order to avoid water accumulation, the size of these conduits can be expanded. It is difficult to modify the size of conduits for the designed drainage system, so the LID facilities are adopted in the bottleneck area and studied to see whether they can improve the drainage capacity of the study area.

Simulation after applied LID facilities
It can be seen that many junctions and conduits appear as There is a large maintenance area in the sub-catchments S5-S8, and meanwhile they are the bottleneck area. Due to there being mainly runway, taxiway, and soil area in the subcatchments S15-S17, the vegetative swale is installed. In addition, in order to relieve the rainwater drainage pressure of Link 14, Link 15, and Link 16, it is necessary to set storage tanks along the way to store some rainwater. The storage tanks along the way are set up between J16 and J18, and the volume of storage is 4.0 × 10 4 m 3 . The situation of the applied LID facilities can be seen in Table 2.
Based on the analysis of simulation results of the model after setting LID facilities, the water elevation profiles and   Figure 7(a) is the water depth of J7 and J17 before the applied LID facilities. Figure 7(b) is the water depth of J7 and J17 after the applied LID facilities.  Table 3. The LID facilities greatly increase the reduction rate of surface runoff of rainwater, and also increase the reduction rate of the number of overflow junctions and full flow conduits to a certain extent. A series of LID facilities has been adopted to greatly improve the rainwater removal capacity and effectively alleviate the risk of waterlogging in the study area.

CONCLUSIONS
At present, the research on sponge airports mainly focuses on the design of LID facilities and the construction of sponge airports, and few researchers use software to simulate the implementation effect of LID facilities. In this paper, rainwater-runoff simulation models before and after implementation of LID facilities were developed using SWMM. The developed models were applied on a rainwater drainage system at a catchment of Beijing Daxing Airport. The sponge airport models were implemented to calculate the water depth, the number of full-flow conduits and overflow junctions, duration of accumulated water before and after applying LID facilities.
According to the results and discussions, the following key findings can be concluded:  There are some limitations in the study. For future research, more sensitivity of parameters should be studied in detail, and further calibration of the model with more practical measured data. In addition, we can further simulate the rainwater drainage system operation of other areas in Beijing Daxing Airport, selecting the optimal LID and control strategy and realizing accurate rainwater-runoff simulation and improving flood control and management.