Determination of the minimum soil infiltration rate of sunken green space considering the annual runoff collection ratio, sunken depth and sunken green space area of Hefei city, China.

Sunken green space is one of the urban rainwater collection facilities, which belongs to Low Impact Development (LID) techniques. It plays a key role in the construction of sponge city, and the amount of runoff collection is usually affected by the area of the sunken green space, the infiltration rate of the soil, and the annual runoff collection rate. To determine the minimum soil infiltration rate of sunken green space considering the annual runoff collection ratio of sponge cities, this paper selects a residential district in Hefei city, China, as the case study. Based on 45 years of precipitation data, the designed rainfall corresponding to annual runoff collection ratios of 75%, 80% and 85% is 21.3 mm, 23.4 mm and 27.5 mm, respectively. The characteristics of rainfall infiltration in sunken green space are analyzed by using the water balance model and runoff yield and conflux model. The results reveal that the soil infiltration rate is 1.16×10-4 cm/s~3.88×10-3 cm/s when the sunken depth is 0.1 m~0.3 m and that the ratio of green space area is 5%~25%. The runoff collection of the reconstructed sunken green space is 2.87 times and 1.98 times that of the nonsunken green space and the nonreconstructed sunken green space, respectively. That is to say, under the comprehensive performance of the sunken depth, sunken green space area, the steady soil infiltration rater of the reconstructed sunken green space cannot be less than the value obtained in this paper. Otherwise, the requirements of annual total runoff reduction ratio of the sponge city cannot be met. Therefore, this study provides references for realizing the ratio of annual runoff collection and sponge city construction in similar urban areas. It can also be applied to optimal selection of sunken green space in some sponge city projects.

Optimization of water quality evaluation index using information sensitivity method and variable fuzzy model for the Guo River, China.

The more water quality evaluation indicators, the greater the amount of water quality evaluation calculation. Under the requirements of evaluation accuracy, the index screening method is usually used to optimize water quality evaluation index to reduce the calculation amount of water quality evaluation. Taking Mengcheng Gate of Guo River as an example, the information sensitivity index screening method was used to simplify the water quality evaluation index system from 17 to 12 indicators. The variable fuzzy comprehensive evaluation method was used to compare and evaluate the original index system and the optimal index system. The results showed that the water quality results of the optimal index system are consistent with the original index evaluation results. And the water quality of Mengcheng Gate is basically stable at class I level. The information sensitivity method reduced the number of indicators by 29.41%. The error between the water quality evaluation results based on the optimal indicators and the original indicators is less than 10%. The maximum error, minimum error, and average error are 8.92%, 0.08%, and 2.46%, respectively. It revealed that the information sensitivity method can eliminate the information redundancy while retaining the information of the original index system. It can also reduce the calculation amount of water quality evaluation in the future. The variable fuzzy comprehensive evaluation method can reasonably reflect the complex nonlinear relationship between water quality index and water quality category. This accuracy has practical significance for guiding the optimization of water quality evaluation index system, improving the efficiency of water quality evaluation. This model provides a scientific basis for indicator selection methods in similar river water quality evaluations.