Influence factors and prediction of stormwater runoff of urban green space in Tianjin, China: laboratory experiment and quantitative theory model

Abstract

The effects of limiting factors such as rainfall intensity, rainfall duration, grass type and vegetation coverage on the stormwater runoff of urban green space was investigated in Tianjin. The prediction equation of stormwater runoff was established by the quantitative theory with the lab experimental data of soil columns. It was validated by three field experiments and the relative errors between predicted and measured stormwater runoff are 1.41, 1.52 and 7.35%, respectively. The results implied that the prediction equation could be used to forecast the stormwater runoff of urban green space. The results of range and variance analysis indicated the sequence order of limiting factors is rainfall intensity > grass type > rainfall duration > vegetation coverage. The least runoff of green land in the present study is the combination of rainfall intensity 60.0 mm/h, duration 60.0 min, grass Festuca arundinacea and vegetation coverage 90.0%. When the intensity and duration of rainfall are 60.0 mm/h and 90.0 min, the predicted volumetric runoff coefficient is 0.23 with Festuca arundinacea of 90.0% vegetation coverage. The present approach indicated that green space is an effective method to reduce stormwater runoff and the conclusions are mainly applicable to Tianjin and the semi-arid areas with main summer precipitation and long-time interval rainfalls.

A Novel Optimization of Water‐Soluble Compound Polysaccharides from Chinese Herbal Medicines by Quantitative Theory and Study on Its Characterization and Antioxidant Activities

“…When the solvent dosage is too small, polysaccharides in the raw material are not able to be fully extracted up. When the solvent dosage is too large, it will enhance difficulties of subsequent concentration and precipitation [31,32] . Therefore, it is significant to choose a suitable ratio of water to raw material for extraction of objective polysaccharides.…”

“…The L 9 (3 4 ) orthogonal experiments were applied to optimize the extraction conditions, which were shown in Table 5. The range analysis [31] was employed to obtain the optimal combination of the extraction yield of CPs. The variance analysis [31] was adopted to confirm the significance of each factor for the extraction yield of CPs.…”

“…The range analysis [31] was employed to obtain the optimal combination of the extraction yield of CPs. The variance analysis [31] was adopted to confirm the significance of each factor for the extraction yield of CPs. The quantitative theory was utilized to establish the prediction model of extraction yield of CPs, which was determined according to our reported method [31] …”

“…The central composite design (CCD) or Box-Behnken design (BBD), one response surface methodology (RSM), is usually applied to optimize the extraction parameters of polysaccharides. [31] The L 9 (3 4 ) orthogonal experiment design (9 runs) requires more fewer runs than BBD (27 runs) and CCD (30 runs) in the case of four factors and three levels. And only qualitative variables were used in the RSM.…”

“…The property of the system is reflected by the qualitative variable, which is not accounted in the quantity, such as extraction mode. The central composite design (CCD) or Box‐Behnken design (BBD), one response surface methodology (RSM), is usually applied to optimize the extraction parameters of polysaccharides [31] . The L 9 (3 4 ) orthogonal experiment design (9 runs) requires more fewer runs than BBD (27 runs) and CCD (30 runs) in the case of four factors and three levels.…”