4.2. Calculating the Evaluation Level
(1) By analyzing the construction performance of China’s domestic sponge cities in recent years, selecting 11 sponge cities with distinct construction effects, Xixian City’s Xixian New District, Urumqi City’s sponge city, Pingliang City’s sponge city, Xining City’s sponge city, Lanzhou City’s sponge city, Golmud City’s sponge city, Yan’an City’s sponge city, Weinan City’s sponge city, Xinjiang Nova City’s sponge city, Qingyang City’s sponge city, and Tianshui City’s sponge city, and establishing an interval gray target model decision matrix. In view of the sponge city construction performance evaluation index system containing mostly qualitative indicators, by inviting 30 experts in the field of urban construction, according to the constructed index system, the scoring range for the 11 sponge city evaluation scoring is (0, 1), as shown in
Table 7.
(2) Specific information on the 11 sponge cities is as follows:
Xi’an Xixian New District, located in the Guanzhong Plain, solves waterlogging through rain gardens, ecological wetlands, and permeable paving, and combines those elements with the ecological restoration of the Weihe River to enhance storage capacity. Urumqi, located in the arid zone, uses roof water harvesting, underground cisterns, and artificial wetlands as the core to alleviate water shortages, as well as to prevent wind and stabilize sand. Pingliang, located on the Loess Plateau, uses terraced rainwater retention ponds and vegetated buffer strips to manage soil erosion and improve soil water retention. Xining, in view of the cold and arid climate of the plateau, constructs sunken green space and a snow water collection system to alleviate the pressure of spring flooding. Lanzhou, along the Yellow River layout, combines permeable paving, storage pools, river ecological slope, flood control, and pollution synergistic management. Geermu promotes water-saving drip irrigation green space and saline–alkali land improvement technology in the Qaidam Basin to optimize the use of rainwater resources. Yan’an controls soil erosion in loess hilly areas with silt dams and ecological slopes, and repairs vegetation to nourish water sources. Weinan has constructed floodplains and intelligent drainage systems to deal with the Wei River floods, synchronized with the restoration of wetland ecology. Xinxing City in Xinjiang has adopted permeable materials and intelligent monitoring to optimize water resource allocation in arid areas. Qingyang manages ecologically fragile areas through ditch-head protection and terrace water storage, and synergizes oilfield groundwater protection. Tianshui relies on mountainous terrain to create stepped rain gardens and ecological filters to mitigate the threat of flash floods. Each region is adapting to local conditions, highlighting the synergy of “seepage, stagnation, storage, purification, utilization and drainage”, and promoting the harmonious development of water.
(3) The sponge city is divided into five grades, generating programs I–V, corresponding to “excellent”, “good”, “medium”, “poor ”, and “poor”; each grade is divided into the following ranges: [0.8, 1), [0.6, 0.8), [0.4, 0.6), [0.2, 0.4), and [0, 0.2]. The evaluation indexes of each program are taken as the middle value of the corresponding grade, and the data of each index of 11 sponge cities are sequentially put into the to-be-determined columns of
Table 8 as the 6th program, and the comprehensive measurement calculation is carried out to arrive at the evaluation results of each city.
(4) Determine the positive and negative bull’s-eye interval values of indicators
Taking Tianshui city as an example, its indicator data were put into the pending columns of
Table 8, according to the decision matrix and Equations (27) and (28), and the positive and negative bull’s-eye interval values were obtained of Tianshui city indicators,
and
. The results are shown in
Table 9.
(5) Determining the positive and negative bull’s-eye distances of the indicators and the comprehensive bull’s-eye distance
Taking Tianshui city as an example, Equations (29) and (30) were used to calculate the distance,
, between the interval value of each secondary indicator in sample 1 and the positive bull’s-eye interval value,
, and the distance,
, between the interval value of each secondary indicator in sample 1 and the negative bull’s-eye interval value,
. Subsequently, Equation (31) was used to obtain the comprehensive bull’s-eye distance of each secondary indicator; the results are summarized in
Table 10. The same calculation method was applied to other samples.
According to Equation (32), , , .
The results of the calculation of the comprehensive measure of the sponge city in TSW and the pre-determined five evaluation scenarios were ranked, as shown in
Table 11 below.
According to Equation (32),
. The calculation results of the comprehensive measure of the sponge city in Urumqi and the pre-determined five evaluation schemes were ranked, as shown in
Table 12 below.
According to Equation (32),
The calculation results of the comprehensive measure of the sponge city in Pingliang City and the pre-determined five evaluation schemes were ranked, as shown in
Table 13 below.
According to Equation (32),
. The calculation results of the comprehensive measure of the sponge city in Xining City and the pre-determined five evaluation schemes were ranked, as shown in
Table 14 below.
According to Equation (32), .
The calculation results of the comprehensive measure of the sponge city in Lanzhou City and the pre-determined five evaluation schemes were ranked, as shown in
Table 15 below.
According to Equation (32), .
The results of the calculation of the comprehensive measure of the sponge city in Golmud and the pre-determined five evaluation programs were ranked, as shown in
Table 16 below.
According to Equation (32),
. The calculation results of the comprehensive measure of the sponge city in Yan’an City and the pre-determined five evaluation schemes were ranked, as shown in
Table 17 below.
According to Equation (32), .
The results of the calculation of the comprehensive measure of the sponge city in Weinan City and the pre-determined five evaluation scenarios were ranked, as shown in
Table 18 below.
According to Equation (32),
. The results of the calculation of the sponge city composite measure for Nova City and the pre-determined five evaluation scenarios were ranked, as shown in
Table 19 below.
According to Equation (32),
. The calculation results of the comprehensive measure of the sponge city in Qingyang City and the pre-determined five evaluation schemes were ranked, as shown in
Table 20 below.
According to Equation (32),
. The calculation results of the comprehensive measure of Xi’an Xixian sponge city and the pre-determined five evaluation schemes were ranked, as shown in
Table 21 below.
The results of the above calculations show that Tianshui City, with a sponge city comprehensive measurement of 0.652, is located between programs II and III, so the evaluation results of the sponge city construction project are “good”. Similarly, the Urumqi City and Yan’an sponge city evaluation results are “poor”, the Pingliang City, Lanzhou, Golmud, and Weinan sponge city evaluation results are “medium”, the Xining City and Xinjiang Nova City sponge city evaluation results are “good”, the Qingyang City sponge city evaluation results are “poor”, and the Xi’an City, Xixian New District sponge city evaluation results are ”excellent”.
4.3. Analysis of Evaluation Results
This study constructs a comprehensive performance evaluation framework to evaluate sponge city construction projects and combines cases to derive the evaluation results of each sponge city construction project to provide reference for other sponge city development.
Water resource management and ecological improvement are very important in the Tier 1 indicators. In terms of water resource management, a higher proportion of integrated water resource utilization and rainwater resource reserves indicates that the city is efficient in collecting, storing, and utilizing rainwater, reducing dependence on traditional water resources. In terms of ecological environment improvement, the increase in biodiversity and microclimate regulation capacity indicates that sponge city facilities effectively optimize the habitat of organisms and mitigate the urban heat island effect. At the level of secondary indicators, the improvement of biodiversity reflects the city’s focus on ecological protection and the provision of suitable habitats for organisms through the construction of green roofs, rain gardens, and other facilities. The high level of storm waterlogging mitigation indicates that the city’s drainage system and sponge facilities work well in synergy, effectively reducing waterlogging and ensuring urban safety. However, the low score on the rate of green space for rainwater use indicates that further optimization is still needed in the integration of rainwater resource use and green space construction.
Comprehensive measurements were calculated and graded for the 11 sponge cities, and the results show that Xi’an Xixian New District is excellent, and Xinxing City and Xining City are good, indicating that they have significant results in ecological environment improvement, water resource management, and technological innovation. For example, Xi’an Xixian New Area synchronized rain gardens with the ecological restoration of the Wei River, which enhanced biodiversity and mitigated flooding from heavy rains, deeply integrating ecology and engineering construction. Qingyang City, on the other hand, was rated as poor and Yan’an City as worse, mainly due to poor soil erosion management, low socio-economic benefits, and urban construction that did not coordinate well with industrial development. Geographically, the Urumqi and Golmud regions have arid climates and high rates of integrated water resource utilization, but poor microclimate regulation. Pingliang and Yan’an are located on the Loess Plateau, with deficiencies in floodwater storage and soil water retention; water storage and ecological slope protection measures must be strengthened.
Significant differences emerge across cities on each indicator. Some cities have not performed well in terms of socio-economic benefits, with low indicators of land value appreciation and industrial development promotion, indicating that the process of urban construction has not driven the development of the local economy, which may be related to factors such as the small scale of construction and imperfect industrial policies. In terms of technology and management innovation, some cities have a better technology application rate and management policy innovation, which greatly enhance the construction effect. In conclusion, sponge city construction projects have achieved certain effects, but there are still some limitations. From the previous research results, the evaluation of sponge city construction projects only focuses on some specific aspects, which cannot be used to measure the overall performance of the project. In this paper, the DCS algorithm is used to optimize the projection tracing model to determine the objective weights, and the evaluation results are more in line with the reality, and the indicators are specifically analyzed to find out the problems in the construction process in time. For example, the biodiversity enhancement indicator is high, reflecting the city’s focus on ecological protection; the low score of the rainwater utilization rate indicates that the city has problems in the utilization of rainwater resources, and the city managers should increase the investment in rainwater utilization in future construction to promote the high-quality development of sponge city construction.