Abstract

The nationwide Sponge City Construction (SCC) program was launched by the Chinese government in 2014. There is a lack of an integrated model system to assist the efforts throughout all the SCC phases, including planning, design, construction, evaluation and maintenance stages. In this study, an integrated stormwater system named Uwater was developed based on a Geographic Information System (GIS) platform, in which a comprehensive open-source urban stormwater runoff model called Storm Water Management Model (SWMM) was embedded. The platform utilized the spatial data management tools in GIS to extract the discrete spatial information such as land use and vegetation cover condition to obtain the composite hydrologic parameters required in the SWMM simulations. The system also fully uses the visualization capabilities of GIS to assist visual design of the Low Impact Development (LID) facilities and Capital Improvement Projects frequently used in the SCC programs. Furthermore, it could be used to assess the drainage capacity of the stormwater system and the corresponding inundation limits for further optimization of the design plans. Finally, a study case using the platform was conducted to test and verify the reliability and applicability of the Uwater system. Results show that the Uwater platform has great strengths and potential to assist the whole life cycle in the SCC program.

INTRODUCTION

China has suffered water problems brought on by its rapid urbanization process. Hence a nationwide ‘Sponge City Construction’ (SCC) program was launched by the Chinese government in late 2014. Since then, a series of SCC demonstration cities has been selected throughout China. Because of the significant scale as well as the total amount of capital invested, the SCC in China has drawn great international attention. A sponge city means that the city can act like sponges, absorbing, storing, seeping and purifying water when it rains and making use of the stored water when necessary (Li et al. 2017; Wang et al. 2018). The concept of a sponge city is quite similar to the Low Impact Development (LID) in the USA, the Sustainable Drainage System (SuDS) in the UK and Water Sensitive Urban Design (WSUD) in Australia. They all represent a new way of viewing stormwater, i.e. not as a waste but as a resource. The whole life cycle of SCC projects consists of several stages: planning, design, construction, evaluation and maintenance.

In all stages, a rainfall runoff model is needed to lay out, design and evaluate the LID-based Capital Improvement Projects (CIP) (Liu 2016). SWMM (Storm Water Management Model), an open source software developed by the US Environmental Protection Agency (EPA) in 1971, marks the beginning of the urban storm runoff model. It has become one of the most popular urban stormwater management tools. At present, the most commonly used commercial software for urban stormwater simulations are developed based on the code of EPA SWMM including Info SWMM and InfoWorks, Mike Urban, XP SWMM, PC SWMM and Storm and Sanitary Analysis (Guan et al. 2015; Palla & Gnecco 2015; Warsta et al. 2017). The basic structure and simulation principles of these commercial software are similar to those of SWMM with three basic modules: hydrological and hydraulic simulations and water quality simulation.

However, during the implementation of the SCC projects, it was found that these stages are typically isolated and hence created corporation problems between different agents. Despite technology advances, new research has been made in stormwater management systems to combine different agents to assist hazard-relief and decision-making efforts. Through literature review, it was found that challenges remain in the SCC systems in China. First, SCC in China has its unique side as the SCC not only deals with stormwater but has been expanded to a combination of a wide range of water programs, including stormwater management, flood control, Combined Sewer Overflow control, and water body restoration. The facilities need to be considered at the master planning/zoning phase to combine all aspects, and to form a complete system to reach the ultimate goal. More agencies are involved, including the manufacture and supply company, engineering, ecologists, zoning, and landscaping. Second, SCC projects contain a special and complex indexes system including the total annual runoff control rate, pollution control rate and stormwater resource utilization rate. These indicators are not easy to quantify directly in engineering practices. Hence they are decomposed into depressed green space rates, permeable pavement rates, green roof rates, and total storage volumes etc. Then these indexes are allocated into each street lot, so as to facilitate the implementation of the construction projects. Therefore, in the process of planning and design, it is necessary to decompose the control index according to the actual construction land types of each lot to design the layout of LID facilities. Last, there is a need to evaluate the performance of the SCC Capital Investment projects as well as the environmental benefits. The performance of SCC projects will be evaluated in four categories including aqua-ecological restoration effects, aqua-environmental restoration effects, water resources utilization effects and flood hazards (Lucia et al. 2015; Maharjan et al. 2016; Xia et al. 2017) within the whole demonstration region, and is carried out by a special committee in each demonstration city.

In recent years, with the development of computer and communication technology, monitoring systems apply the high-tech data exchange and sharing mode, and become important management tools of municipal facilities (Peng et al. 2016; Jarvelainen et al. 2017; Chang et al. 2018). The stormwater model system could be calibrated and refined using the monitored precipitation, runoff and pollutant load data. In terms of drainage and waterlogging prevention, the United States has established the Local Flood Warning system (LFWS) and the automatic Real-Time Assessment system (ALERT). The Singaporean public can obtain stormwater disaster control and emergency information through the early warning service data system. Chang et al. (2018) developed a two-dimensional real-time flood forecasting system to prevent urban inundation in Taiwan, integrating the SOBEK model into flood forecasting in the platform of the DelFT-FEWS (flood warning system) platform. In the area of water environment quality monitoring, the WATERS system was developed aimed at monitoring the environmental parameters of the water body of the Venice salt lake. Tsinghua University developed the environmental monitoring platform, TEMP, which is capable of realizing water quality monitoring in large areas and providing data for policy making. Lucia et al. (2015) developed a system for pollution detection, alert and pollution propagation simulation on the Cyberwater platform. The system can release pollution early warnings based on the analysis of monitoring water parameters.

However, with the continuous advancement of the sponge city development in China, there is a consensus among researchers, practitioners and policymakers that it is necessary to develop an integrated information system of stormwater model that can assist the whole process of the SCC. The existing stormwater management systems generally are not applicable to the SCC projects in China. In this paper, an integrated stormwater management system named Uwater was developed on a Geographic Information System (GIS) platform, in which a comprehensive open-source urban stormwater runoff model called SWMM was embedded. A Uwater platform was applied in one of the largest SCC demonstration cities in China with functions of visual design, performance evaluation and prediction.

METHODOLOGY

Uwater was designed and developed for scientists, engineers, policymakers and other relevant personnel to provide more effective decisions, in response to the need for assisting and visualizing the whole process of SCC. The platform provides information and technical support information for the whole life cycle of the SCC project including planning, design, construction, evaluation and maintenance. With the feedback from the on-site monitoring system, it forms a closed loop system that is self-adaptive (Figure 1).

Figure 1

A self-adaptive closed loop system.

Figure 1

A self-adaptive closed loop system.

The integrated system could be divided into five layers: device, service, data, platform and application layer. The system architecture diagram is shown in Figure 2. The GIS-based Uwater is designed based on the structure language of C/S with the idea of stratification. The individual functional component is formed by analyzing the functions of the system. Then the corresponding modules are built on the basis of these functional components. It forms the simulation chain of the whole process, from mathematical models, functional structures to input and output modes.

Figure 2

The framework of the integrated Uwater stormwater management system.

Figure 2

The framework of the integrated Uwater stormwater management system.

Key methods used in the development of Uwater include: data resource database construction, multi-source data integration (Li & Zhang 2017; Xu & Yu 2017; Zhang et al. 2017), geo-spatial data computing, design and evaluation visualization. In the stage of planning and design, Uwater can be used to allocate and refine the SCC mandatory indexes and visualize the design of LID projects. In the evaluation stage, the qualitive evaluation of the urban stormwater CIP is carried out for different layouts and scale of LID facilities design plans. The discharge capacity of the stormwater system and inundation limits are compared and evaluated for further optimization. The post-construction maintenance and management system, such as real-time monitoring and flood warning information releasing, is formed based on the technologies of the Internet of Things, Big Data and Cloud Computing, and combined with the related standards of the sponge city. The Internet of Things refers to a network that extends its client end to any object on the basis of the internet for information exchange and communication. Large data is a large-scale data set, which cannot be acquired, stored, managed and analyzed by traditional database software tools. It has four characteristics: massive data scale, rapid data flow, diverse data types and low value density. Cloud computing is a style of computing in which dynamically scalable and often virtualized resources are provided as a service over the internet (Chen & Zhang 2014; Chen et al. 2014; Fang et al. 2014; Wei et al. 2014; Wu et al. 2014; Zanella et al. 2014; Al-Fuqaha et al. 2015).

Multi-source data integration

The SCC program involves all levels of stormwater project planning including master plan, special plan, project plan, site plan and site design as well as post-construction management that needs input and data from different agencies. However, the design agents or land developers commonly use CAD software to carry on the site design where GIS and SWMM-family software are often used in planning and evaluation. The data structure in CAD is not rigorous enough topologically. As a result, it is difficult to carry out complex spatial analysis such as location identification and composite parameter calculations needed by the SWMM engine. In order to use the CAD drawings provided by the design agents or land developers, it is necessary to transfer the data into a GIS format for further spatial calculation and visual evaluation of different design plans. Hence, a set of data sharing mechanisms needs to be established to realize the data exchange between multi-environment and multi-system.

The framework of multi-source data integration is shown in Figure 3. The data exchange mechanism among different data formats, such as Excel, GIS, CAD and SWMM, is constructed following these techniques:

  • (1)

    ETL (Extract Transform Load) technology is used to realize the exchange and collaboration of Excel data. A uniform data storage format is set as the data standard. The required data is extracted, sorted and reformatted from the Excel data source. The extracted data is finally loaded into a pre-defined data warehouse that exists in the platform.

  • (2)

    A connection center was formed with the technical standards of geographic information industry for communications between GIS data from different sources. It can provide a uniform interface and realize spatial data transmission between different systems.

  • (3)

    A cooperative data transmission mechanism among CAD, GIS and SWMM software is established to achieve data integration among these data sources. The data of the transmission terminal is encapsulated and a specific data transmission channel is established by using Socket technology. The data is parsed and checked at the receiving end, then converted according to the target format. A spatial data conversion module is developed to realize data transmission and data structure conversion.

Figure 3

The framework of the multi-source data integration method.

Figure 3

The framework of the multi-source data integration method.

Based on the data organization structure of the SWMM model, the same data structure is established on the GIS and CAD side. GIS data encapsulation and attribute definition are carried out based on a layer and attribute table, and CAD data definition is carried out according to the entity structure. Lastly, SWMM, GIS and CAD have the same geographic entity and attribute structure.

By controlling data version and access, data consistency among GIS, CAD and SWMM is ensured, and data semantic mapping and integration among GIS, CAD and SWMM are realized.

Geo-database development

Uwater contains a sophisticated geo-database structure with GIS technology and other advanced technology. Discrete spatial data (terrain, surface coverage, catchment area, soil, etc.), 3D scene data, infrastructure data including stormwater pipe, control and detention system and other comprehensive information data used in SCC are conveniently integrated into a geodatabase in different formats including shapefiles, raster files and database tables. SWMM simulation results such as flowrate and velocity, flood height and inundation limits are all stored in the geodatabase in the form of tables.

In the Uwater stormwater model platform, a localized parameter database was developed that includes rainfall data, accumulation and wash-off functions of runoff pollutants, typical LID design parameters used in China SCC, etc. Hence an integrated information system of stormwater model suitable for SCC in China is developed.

Computing engine

In this study, EPA SWMM 5.1 is taken as the engine of calculation. The capabilities of the SWMM model have been extended with the utilization of GIS tools. As a typical distributed hydrological model for simulating the storm runoff process, SWMM shows good versatility. Both urban catchment areas and natural watersheds can be simulated accurately with SWMM. In SWMM, the rainfall runoff processes and the adjoint runoff pollutants generation and transport process can be simulated continuously. It contains three modules: hydrological module, hydraulic module and water quality module that simulates the whole rainfall-runoff-transport-retention-discharge process. A fully hydraulic dynamic model is imbedded in SWMM, where the unsteady flow in conduits is described by the Saint Venant equation:  
formula
 
formula
where x is distance, m; t is time, sec; A is flow cross-sectional area, m2; Q is flow rate, cms; H is hydraulic head of water in the conduit (Z+Y), m; Z is conduit invert elevation, m; Y is conduit water depth, m; is friction slope; and g is acceleration, m/sec2.

Hence it could be used to simulate complex hydraulic conditions that occur frequently in urban stormwater systems, such as pressurized flow, reverse flow and backwater impacts. For more detailed information on SWMM, the SWMM user's manual and reference manual can be referred to (Rossman 2015, 2016, 2017).

Geo-spatial data computing

Since the introduction of the SWMM model, it has become the most widely used urban stormwater simulation software. However, a large number of parameters are needed for each catchment by SWMM including soil permeability and infiltration capability, percentage of impervious area and Manning coefficient, etc. Runoff generation in the catchment area is affected by heterogeneous factors such as surface soil and topography. These data are discrete in nature, which makes it difficult to determine a composite parameter for the whole catchment, vegetation and land use types. The input parameter calculations are difficult and time consuming in general.

However, with the assistance of GIS tools, this problem could be solved. The accurate calculation of discrete catchment parameters can be realized by applying the overlay, statistics and zonal tools provided by GIS which basically calculate the area-weighted average of discrete data. The technical route of extracting the catchment parameters is shown in Figure 4.

Figure 4

The framework of extracting the composite catchment parameters.

Figure 4

The framework of extracting the composite catchment parameters.

In this way, the key hydrological parameters can be calculated accurately. Hence the simulation accuracy of SWMM can be improved significantly.

Visualization analysis

Visual design of LID facility layout

In the Uwater platform, the layout of LID facilities and stormwater CIP projects is carried out with visualization tools developed using GIS tools. This is very useful to combine the engineering runoff control infrastructures with urban landscape to gain environmental benefits. In addition, an assessment algorithm was established based on a user-defined financial index to evaluate the economic aspects of LID facilities. The regulation index system mandatorily required by SCC was converted to the required storage capacity of LID facilities. After the preliminary visualization design of the LID facility is completed, SWMM is run, and then the design storage volume and the effective storage volume of the LID facilities can be calculated. The effective storage volume is compared with the required volume to check if the plan can meet the requirements. A spatial optimization could be carried out if the requirements are not met. The technical route for LID efficiency evaluation and spatial optimization is shown in Figure 5.

Figure 5

Visual design of LID facility layout.

Figure 5

Visual design of LID facility layout.

Effectiveness evaluation of drainage network system

Outputs in SWMM are not user friendly in general. In traditional stormwater network design, the rational method is usually used to calculate the peak flowrate based on rainstorm intensity. Then the maximum discharge capability of the pipe segment is estimated by using Manning equations which assume the flow in the pipe is gravitational. However, the rainfall recurrence period calculated by the traditional method neglects the hydrograph reformation and the hydraulic boundary conditions of the downstream pipe network. The accuracy is low. So it is difficult to truly reflect the stormwater discharge capacity of the pipe network system. Therefore, in this study, a GIS based visualization method for evaluating the effectiveness of the drainage network system based on SWMM dynamic wave simulation is established, which is capable of realizing the calculation of recurrence period and space rendering of the urban drainage pipe network. The way to implement this method is shown in Figure 6. The rainfall data of different recurrence periods are designed according to the local rainstorm intensity formula. Different levels of the pipeline recurrence period are defined that correspond to different rainfall recurrence periods. Then SWMM is utilized to calculate the value of node overflow and pipe water depth under different rainfall recurrence periods. Starting from the smaller rainfall recurrence period, if the simulation results satisfy the following conditions, the discharge capacity of the pipe segment is determined as the pipeline return period corresponding to the rainfall recurrence period.

  • (1)

  • (2)

where is the maximum water depth in the pipe; is the pipe diameter; is the number of overflow nodes in the downstream pipe network.

Figure 6

Effectiveness evaluation of drainage network system.

Figure 6

Effectiveness evaluation of drainage network system.

Risk evaluation of inundation area

GIS tools were used to visualize the flooding level calculated in SWMM. The SWMM model was used to simulate and calculate the node overflow in the drainage network system at a certain time. Two sets of raster dataset, the local terrain data of the flooding point and the flood water height data, are generated for linear interpolation of flood level. Then a topo analysis was run to compare the water surface elevation with the land surface elevation to obtain the inundation areas (Figure 7). Dynamic submergence simulation is formed by connecting the submergence surface at each simulation time in the process of rainfall.

Figure 7

Risk evaluation of inundation area.

Figure 7

Risk evaluation of inundation area.

The monitoring information system

Monitoring data feedback

Another important subsystem in the Uwater system is the online monitoring and information subsystem. Based on the related standards and specifications of sponge city, a multi-bit operation and maintenance monitoring management information system, such as real-time monitoring, 3D display and sponge facility management, was established with the key technologies such as Internet of Things, Big Data, Cloud Computing and 3D geographic information.

The operation information of the aqua-ecological restoration effects, aqua-environmental restoration effects, and water resources utilization effects in SCC is monitored. The stormwater model system could be calibrated and refined using the monitored precipitation, runoff and pollutant load data. The monitoring data collected from each monitoring station is also utilized to build a large data system to create statistics on the control indexes of urban runoff pollution, water resource utilization rate, total annual runoff control rate, and pollutant reduction rate.

Early warning and information release

After the process of design, evaluation and optimization in the SCC project, a set of sound stormwater system models is developed and integrated into the Uwater platform system. According to the forecasting meteorological information, the stormwater system model is used to simulate, predict, and make short-term warnings. The concerned public is informed about the water environmental quality and flood disaster so that emergency measures can be taken in time.

The forecast data and visual chart information can be consumed by users of a wide variety of web and mobile application services for the sake of taking corresponding emergency measures in time, as long as the Uwater client is installed. Therefore, with the results of monitoring and early warning analysis publicly released, these are widely accessible to emergency managers and the concerned public and not limited to scientists.

In addition, the stormwater network automation design method based on the dynamic wave theory proposed in Shao et al. (2017a) is integrated into the Uwater system, which avoids the limitation of insufficient precision of the traditional design method. The method of constructing a dynamic discharge-stage rating curve for a multistage stormwater outlet structure (Shao et al. 2017b) is also integrated in the model, which extends the function of existing stormwater software for large-scale stormwater storage and comprehensive utilization simulation.

CASE STUDY

Application

The Uwater platform was applied in one of the largest SCC demonstration cities in China, Yuelai, Chongqing. The application of the integrated system in the whole process of SCC is illustrated. The different subsystems in Uwater, including planning, design, evaluation and maintenance, described in the previous sections, were tested.

The topography and geomorphology of Yuelai have the typical characteristics of hilly cities. The stormwater model platform was used to assist the construction of sponge city in Yuelai, which can provide valuable experience for the SCC in hilly cities. The planned construction land area of Yuelai is 18.67 km2, which consists of three parts: a highly developed area (Yuelai Convention and Exhibition City), a developing area (Yuelai Ecological City), and an undeveloped area (Yuelai Intelligent City).

Stormwater network system construction

First of all, relevant information was collected and imported into the Uwater system, then a stormwater system model of existing conditions was built.

Collecting the data from the current urban drainage network, the land use, and rainfall etc., the corresponding CAD data is imported into the Uwater system by the CAD data import interface. The imported CAD scheme was further designed on the basis of the stormwater network automatic design function of Uwater.

Combined with grade and slope analysis, the runoff path of the whole watershed was determined and used to delineate the catchments. Yuelai was divided into three major watersheds: Zhangjiaxi, Houhe and Binjiang, discharged into different water bodies. The study area was further divided into 28 stormwater management zones according to the stormwater network system and the confluence. The spatial parameter extraction, statistics and calculation function of Uwater are used to obtain the catchment parameters such as slope, characteristic width and infiltration coefficient etc. All the corresponding parameters in the model were assigned to complete the preliminary building of the stormwater system model. The preliminary process of establishing the stormwater system model is shown in Figure 8.

Figure 8

The preliminary process of establishing the stormwater system model.

Figure 8

The preliminary process of establishing the stormwater system model.

LID facilities design and optimization

The required total annual runoff volume and pollutant control index of sponge city were allocated to each lot. Then the layout of LID facilities in each lot was designed visually according to the allocated control index. With the built-in model localized database, the parameters of LID facilities were assigned to build the model.

The target storage volume of the LID facility was calculated according to the required control index. After setting up the LID facilities, the actual storage volume was calculated and compared with the required storage volume. Then the design scheme of LID was further optimized (Figure 9).

Figure 9

The design and optimization process of LID facilities.

Figure 9

The design and optimization process of LID facilities.

Stormwater system evaluation

Thirdly, using the stormwater system capability evaluation function provided in the Uwater platform, the discharge capacity of each pipe in the stormwater network was evaluated. Then the possible location, depth and area of the inundation points with the design scheme were analyzed according to the visualization inundation evaluation function of Uwater described above. The design scheme was further optimized according to the evaluation results. The interface of stormwater system discharge capacity and inundation evaluation is shown in Figure 10.

Figure 10

The interface of stormwater system discharge capacity and inundation evaluation.

Figure 10

The interface of stormwater system discharge capacity and inundation evaluation.

Monitoring information system

Combined with the previously established stormwater system model, the monitoring and information service platform of Yuelai sponge city was built, so as to manage the whole process of the SCC.

The monitoring and information service platform consists of six subsystems: (1) management and decision; (2) planning and evaluation; (3) hydrologic short-term warning; (4) hydrologic medium- and long-term simulation; (5) three-dimensional display; (6) public information release. Figure 11 shows the overall architecture of the system.

Figure 11

The framework of the integrated stormwater model and information system.

Figure 11

The framework of the integrated stormwater model and information system.

The platform monitors the operation performance of selected SCC projects in four aspects: aqua-ecological restoration effects, aqua-environmental restoration effects, water resources utilization effects and flood hazards. The Internet of Things technology is used to realize the omnidirectional monitoring of the sponge city water cycle process. There are 28 stormwater management zones in Yuelai, with 36 municipal stormwater outfalls discharged into natural water bodies. Therefore, 36 regional hydrological and water quality monitoring stations have been set up in the outfalls to assess stormwater emission and water quality. At the same time, in order to facilitate the assessment of each lot by the SCC management department, a hydrological and water quality monitoring station was set up at the stormwater outlet of each lot to monitor the stormwater emission and water quality. Considering the actual development progress of Yuelai and the needs of Yuelai SCC assessment, 147 hydrological and water quality monitoring stations were set up in 178 lots. According to the principle that two or three rainfall stations need to be set up every 20 km2, three rainfall stations were set up in Yuelai. Different kinds of water quality and water quantity sensing equipment were installed to monitor the important position in the stormwater system (Figure 12). Afterwards, based on the forecast meteorological information, early warnings for hydrology and water quality can be realized using the simulation results. The relevant information was released to the public. Both the monitoring data and model simulation results can be used to evaluate and improve the sponge cities' construction.

Figure 12

Sponge city monitoring system.

Figure 12

Sponge city monitoring system.

DISCUSSION

Through the study of the above case, it can be shown that Uwater has good application in all stages of planning, design, construction, evaluation and maintenance of SCC. The results of simulation evaluation and monitoring data evaluation of Yuelai sponge city show that the planning and design phases are reasonable. The assessment indexes of SCC, such as the total annual runoff control rate, pollution control rate and stormwater resource utilization rate, could meet the assessment requirements.

In the process of sponge city planning and design, the CAD design scheme of the project was directly imported into the platform, which enables the designers to operate the system and greatly improves the working efficiency. According to the planning control indexes, such as the rate of green space and the density of the buildings in the special plan of the sponge city, the LID facilities index of each lot was preliminarily determined. Whether the construction indexes of each lot meet the requirements of the planning was intuitively judged with the use of the LID facility evaluation function in Uwater. The flooding simulation analysis of the scheme was carried out to preliminarily test the planning results. Afterwards, the flooding points and its inundation area could be determined. The design of the corresponding stormwater network and LID facilities were optimized to effectively avoid the blind rebuilding and to reduce the risk of urban waterlogging from the source. The platform was used to realize the information management of the maintenance process of the sponge city. Combined with monitoring data and the optimized model, the large data analysis system of sponge city was formed, generating the online monitoring report for the SCC demonstration site. In addition, the short-term early warning of hydrology and water quality disaster could be realized by using the forecasted meteorological information.

The case study, while demonstrating the reliability and applicability of the Uwater framework and model, also emphasizes the inherent limitations of the Uwater, such as it being highly dependent on the monitored meteorological data, model structures, and model parameters. Furthermore, the establishment of the stormwater model and the calibration of relevant parameters require a large number of data, such as stormwater network system, terrain data, meteorological data for many years, and soil infiltration coefficient, etc. For some areas, there is not sufficient and reliable data to build the model.

CONCLUSION

In this study, an integrated stormwater management system, Uwater, was developed on a GIS platform coupling an open source SWMM model. The Uwater platform was applied in one of the largest SCC demonstration cities in China. The platform provides information and technical support information for the whole life cycle of the SCC project including planning, design, construction, evaluation and maintenance. With the feedback from the on-site monitoring system, it forms a self-adaptive closed loop system.

The following technologies have been developed in Uwater. The data exchange mechanism among different data formats, such as Excel, GIS, CAD and SWMM, is established in Uwater for data sharing between different data sources such as basic geospatial data, 3D data, and the comprehensive information data of the SCC sites. The geographic data management and spatial calculation functions of GIS are coupled with SWMM to calculate discrete spatial parameters needed in SWMM simulations. Tools for visual design of the LID facilities, visual evaluation of the drainage capacity of the stormwater pipe system and the inundation limits were developed using GIS functions for further optimization of the design plans. The operation and maintenance monitoring information management service system is developed with Big Data, Internet of Things and Cloud Computing technology. The integrated system can be used for simulation analysis and decision-making in different stages of SCC.

A case was used to test and verify the reliability and applicability of Uwater system in the whole process of SCC. It shows that Uwater has great application potential for supporting rapid SCC progress in China.

ACKNOWLEDGEMENTS

The research reported here is supported by the National Key R&D Program of China, non-point source pollution control and stormwater management technology in hilly cities, the Ministry of Science and Technology, PR China (No. 2017YFC0404704).

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