Pingxiang, Jiangxi Province, China, is located in the Hunan-Jiangxi watershed, which is a typical hilly region in the South of the Yangtze River. Most of the basin is mountainous and hilly, and only 11% is plain valley. During the rainstorm, the mountain flood comes rapidly, the river level rises sharply, and the phenomenon of river embankment overflow occurs in the plain valley. After the rain, the mountain flood subsided, the river lack of water supply, river flow is small, dry season almost dry. There are 4 historical water logging areas in the old city, and 84 low-lying potential water logging points are at high risk of water logging. Take wanlongwan water logging area with the most severe water logging as an example. On July 8, 2016, it rained 79.8 mm. Wanlongwan waterlogged an area of 1.2 square kilometers, with the maximum water depth exceeding 1 meter. The contradiction between city and nature, human and water is prominent. In view of the reality of frequent flood disasters and water shortage coexisting due to the hydro logical characteristics of the typical jiangnan hilly region, Pingxiang creatively proposed the systematic construction idea of "whole-domain control -- system construction -- zoning management".
Since the pilot project, sponge city construction in Jiangxi province has made some achievements, but the effect is far from ideal. Case based on this, through field visits and consulting for practitioners, found in the process of the sponge construction of city in jiangxi province, the imperfection of the laws, regulations and policies concerning the mechanism of management to organize the implementation of efficient enough, related technology is not mature, inadequate social participation degree, are the construction and maintenance of sponge carries risks.
5.2 Scoring boundary risk factors
After fitting the risk flow diagram of sponge city construction project, the boundary risk factors were identified, and the assignment values of 23 key risk factors and 5 risk subsystems were obtained through structural interview. The questionnaire was distributed to relevant practitioners and university researchers in the pilot cities of sponge cities. A total of 128 questionnaires were distributed, and 93 effective questionnaires were recovered, with an effective recovery rate of 73%. The reliability of the questionnaire was analyzed by SPSS software. The Cronbach coefficient (Cronbach) was 0.873, which had a high reliability. KMO = 0.79 > 0.7, significance level P = 0.000 < 0.01, indicating that the data is relatively valid and can be processed in the next step.
According to the above discussion on the theoretical basis, the possibility of risk occurrence and the severity of consequences are mainly considered, and the probability of risk occurrence and severity of consequences are divided into five grades, with 1–5 points respectively, with 1 point indicating the lowest degree and 5 points indicating the highest degree.The risk factor function is \(R=f\left(p,r\right)\). According to the multi-factor multiplication comprehensive analysis model commonly used in academia, its calculation formula is as follows:
$${R}_{ij}={P}_{ij}\times {C}_{ij}$$
5
Where, Rij represents the size score of the subject j on the risk factor i; Pij represents the score result of the respondent j on the occurrence possibility of the risk factor i; Cij represents the score of the respondent j on the risk degree of the risk factor consequence i. The initial value of this risk factor was obtained by averaging the scores of all survey experts, and the calculation formula was as follows:
$$\text{R}=\frac{1}{\text{n}}\sum _{\text{j}=1}^{\text{n}}{R}_{ij}$$
6
Where, n represents the number of respondents; Rij represents the scoring result of the respondent j on the risk of the risk factor i; R represents the initial value of the state variable.
The initial values of the risk factors obtained after averaging the values assigned to each risk factor by each expert (see Appendix 4 for details) are shown in Table 2.
Table 2
Initial values of risk factors
Risk factors
|
Regulatory risk
|
Management risk
|
Capital risk
|
Technical risk
|
social risk
|
Initial values
|
9.36
|
11.03
|
5.36
|
13.09
|
4.09
|
5.4 Establish the equations of each subsystem
The weight assignment obtained from Table 3 above is substituted into the prepared subsystem equation as follows:
1. Change in regulatory risk = 0.230×a1 + 0.148×a2 + 0.177×a3 + 0.196×a4 + 0.192×a5
2. Manage risk variability = 0.167×b1 + 0.147×b2 + 0.120×b3 + 0.151×b4 + 0.112×b5 + 0.089×b6 + 0.121×b7 + 0.108×b8
3. Variation of capital risk = 0.116×c1 + 0.196×c2 + 0.145×c3 + 0.163×c4 + 0.133×c5 + 0.142×c6 + 0.119×c7
4. Change in technical risk = 0.249×d1 + 0.201×d2 + 0.175×d3 + 0.124×d4 + 0.128×d5 + 0.150×d6
5. Changes in social risks = 0.189×e1 + 0.179×e2 + 0.178×e3 + 0.113×e4 + 0.176×e5 + 0.189×e6
6. Risk change of sponge city construction = 0.216×f1 + 0.234×f2 + 0.169×f3 + 0.222×f4 + 0.177×f5
7. Regulatory risk = INTEG (Change in regulatory risk, 9.36)
8. Management risk = INTEG (Management risk change, 11.03)
9. Capital risk = INTEG (Capital risk change, 5.36)
10. Technical risk = INTEG (Change in technical risk, 13.09)
11. Social risk = INTEG (Change in social risk, 4.09)
12. Sponge city construction risk = INTEG (Change in sponge city construction risk, 0)
5.5 Analysis of empirical results
After consulting relevant practitioners of sponge city construction in Jiangxi Province, it is found that the start-up phase is 1 month, the planning and design phase is 2 months, the construction phase is 6 months, and the operation and maintenance warranty period is 2 years. In order to have a better simulation effect, the simulation duration of the model is set as 15 months to simulate the risk changes from project approval to six months of operation. The above system equations were brought into the Vensim PLE software (Qifan 2009; Yongguang et al. 2013; Dickson et al. 2011), and the function changing with time was set for each auxiliary variable according to the existence time of each risk, and the operation results of each risk were observed.
5.5.1 Full life cycle simulation analysis of regulatory risks
In regulatory risk in this subsystem, incomplete "construction technology standard" and "operation maintenance rules are not perfect" both of these factors will exist in the construction and operational stage, so the time function as constraints, namely in the planning and design phase of the risk factors of risk value is set to 0, do so with the rest of the time the functions below. In order to further explore the dynamic impact of each risk factor on the regulatory risk subsystem, the initial value of each factor was reduced by 30% and other factors remained unchanged for sensitivity analysis. The adjustment scheme is shown in Table 4, and the final analysis result is shown in Fig. 9 (a).
Table 4
Description of regulatory risk sensitivity analysis scheme
Scenario name
|
Project instruction
|
A1
|
Keep the initial values of each factor unchanged
|
A2
|
Initial var of a5 is reduced by 30%
|
A3
|
Initial var of a1 is reduced by 30%
|
A4
|
Initial var of a2 is reduced by 30%
|
A5
|
Initial var of a4 is reduced by 30%
|
A6
|
Initial var of a3 is reduced by 30%
|
Through sensitivity analysis, it can be found that regulatory risk is most sensitive to a1 factor, followed by a5, and least sensitive to a4, indicating that promoting the construction of national regulations and the improvement of investment and financing laws in the start-up stage has a significant impact on the reduction of regulatory risk level.
The low sensitivity of factor a4 is mainly due to the fact that this factor begins to affect sponge city construction in the last stage of the whole life cycle. However, it can be seen from the change trend of each scheme after 9 months that a4 factor has a extreme influence on the decrease of regulatory risk level. In order to better analyze this factor, the model of the simulated time extended to 30 months, found that the factors effect on the risk regulations is not lower than the other factors except a1, this shows that in the future urban construction run longer sponge maintenance phase, a4 will risk occupy larger influence on construction of city sponge weights, as shown in Fig. 9 (b).
5.5.2 Life-cycle simulation analysis of management risk
In the management risk subsystem, the b7 factor appears after the planning stage, so it is constrained by a time function.
In order to further explore the dynamic impact of each factor on the management risk subsystem, the initial value of each factor was reduced by 30% and other factors remained unchanged for sensitivity analysis. The adjustment scheme is shown in Table 5, and the final analysis result is shown in Fig. 9 (c).
Table 5
Sensitivity analysis description of management risk
Scenario name
|
Project instruction
|
C1
|
Keep the initial values of each factor unchanged
|
C2
|
Initial var of R1 is reduced by 30%
|
C3
|
Initial var of b1 is reduced by 30%
|
C4
|
Initial var of b2 is reduced by 30%
|
C5
|
Initial var of b7 is reduced by 30%
|
C6
|
Initial var of b6 is reduced by 30%
|
C7
|
Initial var of b5 is reduced by 30%
|
C8
|
Initial var of b4 is reduced by 30%
|
C9
|
Initial var of b3 is reduced by 30%
|
Sensitivity analysis shows that regulatory risk can be effectively reduced by controlling regulatory risk at the initial stage of start-up. In the category of management risk subsystem, management risk is most sensitive to b1 factor, followed by b4 and b2, indicating that perfecting laws and regulations and performance appraisal mechanism, strengthening government attention and establishing overall management organization have obvious effect on reducing management risk in the start-up stage.
5.5.3 Life-cycle simulation analysis of capital risk
In the subsystem of capital risk, only the c1 factor exists in all stages of the whole life cycle, while the c4 factor only affects the planning and design stage, the c3 factor only affects the construction stage, and the c4 factor only appears in the operation and maintenance stage. Therefore, the time function is used as the constraint for these three factors. In order to further explore the dynamic impact of each factor on the capital risk system, the initial value of each factor was reduced by 30% and other factors remained unchanged for sensitivity analysis. The adjustment scheme is shown in Table 6, and the final analysis result is shown in Fig. 9 (d).
Table 6
Description of capital risk sensitivity analysis scheme
Scenario name
|
Project instruction
|
D1
|
Keep the initial values of each factor unchanged
|
D2
|
Initial var of R1 is reduced by 30%
|
D3
|
Initial var of R2 is reduced by 30%
|
D4
|
Initial var of R5 is reduced by 30%
|
D5
|
Initial var of c1 is reduced by 30%
|
D6
|
Initial var of c2 is reduced by 30%
|
D7
|
Initial var of c3 is reduced by 30%
|
Through sensitivity analysis, it can be found that the influence of regulation, management and social risk control is far greater than that of the internal factors of the fund subsystem. Among them, management risk has a particularly significant impact on capital risk, indicating that a perfect management mechanism plays an important role in capital investment and allocation. All risk factors under the capital subsystem have little influence on the system, among which operation and maintenance capital has a relatively high influence on the capital subsystem.
5.5.4 Full life cycle simulation analysis of technical risk
In the subsystem of technical risk, three sub-factors, d1, d2 and d3, respectively exist in the stages of planning, construction and operation and maintenance, all of which are constrained by time function. In order to further explore the influence of each sub-factor on the technical risk system, the initial value of each factor was reduced by 30% and other factors remained unchanged for sensitivity analysis. The adjustment scheme is shown in Table 7, and the final analysis result is shown in Fig. 9 (e).
Table 7
Sensitivity analysis description of technology risk
Scenario name
|
Project instruction
|
E1
|
Keep the initial values of each factor unchanged
|
E2
|
Initial var of R1 is reduced by 30%
|
E3
|
Initial var of R2 is reduced by 30%
|
E4
|
Initial var of R5 is reduced by 30%
|
E5
|
Initial var of d1 is reduced by 30%
|
E6
|
Initial var of d2 is reduced by 30%
|
E7
|
Initial var of d3 is reduced by 30%
|
Through sensitivity analysis can be found in the early stage of project startup management risk and regulatory risk control, can effectively reduce the sponge urban construction technical risk, but far less than the effects of poor planning and design technology, to reduce the risk of technical subsystem, should be in the prophase planning technology in the research and training.
5.5.5 Life-cycle simulation analysis of social risks
In the subsystem of social risk, e1, e2, e3 and e4 factors exist in all stages of the whole life cycle, so there is no need to use time function to constrain them. In order to further explore the impact of each factor on the social risk system, the initial value of each factor was reduced by 30% and other factors remained unchanged for sensitivity analysis. The adjustment scheme is shown in Table 8, and the final analysis result is shown in Fig. 9 (f).
Table 8
Sensitivity analysis description of society risk
Scenario name
|
Project instruction
|
F1
|
Keep the initial values of each factor unchanged
|
F2
|
Initial var of R1 is reduced by 30%
|
F3
|
Initial var of R2 is reduced by 30%
|
F4
|
Initial var of e3 is reduced by 30%
|
F5
|
Initial var of e1 is reduced by 30%
|
F6
|
Initial var of e2 is reduced by 30%
|
F7
|
Initial var of e4 is reduced by 30%
|
Through sensitivity analysis, it can be found that the control of management risks will have a significant impact on social risks, which may be due to the government's emphasis on publicity and education, and the improvement of public participation mechanism, so as to reduce social risks. In the category of social risk subsystem, social risk is sensitive to e1 and e3. With the control of such risks in the early stage of the project, social risks can be effectively reduced.
5.5.6 Life-cycle simulation analysis of sponge city construction risk
In order to analyze the influence of the sub-systems of legal risk, management risk, capital risk, technical risk and social risk on the total risk of sponge city construction, the initial risk value of each sub-system was reduced by 30%, and other factors remained unchanged, and the dynamic change of the total risk level was observed. The adjustment scheme is shown in Table 9, and the final analysis result is shown in Fig. 9 (g).
Table 9
Sensitivity analysis description of Sponge City Construction risk
Scenario name
|
Project instruction
|
G1
|
Keep the initial values of each factor unchanged
|
G2
|
Initial var of R1 is reduced by 30%
|
G3
|
Initial var of R2 is reduced by 30%
|
G4
|
Initial var of R3 is reduced by 30%
|
G5
|
Initial var of R4 is reduced by 30%
|
G6
|
Initial var of R5 is reduced by 30%
|
As can be seen from Fig. 9 (g), the risk level of management risk in all stages of the whole life cycle is high, and the management system needs to be further improved in the future. The risk level of legal risk in the start-up stage is high, but with the change of time, the proportion of the total risk of sponge city construction is getting lower and lower. In contrast, technological and social risks have become more and more important over time. The risk level of capital risk in all stages of the whole life cycle is obviously lower than that of other systems, which may be because jiangxi province has a high level of economic development, and the support of national and provincial pilot cities makes local governments have low economic worries in sponge city construction. Therefore, management risk and technical risk should be focused on in the whole life cycle stage, regulatory risk control should be strengthened in the start-up stage, and social risk control should be strengthened in the operation and maintenance stage.
5.5.7 Life-cycle key risk factors radar map
Will be entirely into the startup phase of mentioned above, planning and design stage, construction stage, completion acceptance and operation maintenance phase, each risk subsystem simulation results in 1 month, 3 months, in September and 15 months in the key points of the summary to the radar map, can be more intuitive to see changes in the different stages of the risk, as shown in Fig. 9 (h).
The data of system dynamics constructed in this study are mostly subjective and qualitative, and the simulation accuracy is low, so the precise value of risk level cannot be obtained. However, the dynamic change trend of risk level of each subsystem in the whole life cycle of sponge city can be discussed from the general change trend.
5.6 Suggestions on risk prevention and control of sponge city construction
The five dimensions of risk run through each life cycle stage of sponge city construction, but have different development trends. Therefore, risk management should also dynamically consider the impact of various risks on the overall project and put forward suggestions. Combined with simulation and sensitivity analysis, the following suggestions are proposed for the key factors of the five subsystems. (1) Sponge city pilot cities should actively carry out the compilation of operation and maintenance specifications in the future, and further revise them according to the actual project operation situation. (2) in the construction of the sponge, etc in the process of the organization as a whole, we should widely transferring backbone, each related department in order to establish a direct and strong, solid work, coordinate clear in different stages of the urban construction, the main responsibility of the sponge and setting up a long-term mechanism to sponge a gradual shift in urban construction are normalized to the construction of content. (3) Use technical means to build an intelligent scheduling platform for sponge facilities, assist scheduling management with comprehensive information, and realize the whole process comprehensive management of sponge city planning, construction, operation management and environmental performance. (4) Strengthen the publicity of sponge city concept, guide social participation, solicit public opinions, understand public preferences, and incorporate reasonable opinions into sponge city planning. (5) While strengthening sponge city publicity, effectively guide market participation and sustainable investment of capital, fully guide the enthusiasm of social capital to participate in sponge city construction, cultivate and guide the incubation of sponge city-related industries, and form new industrial momentum.