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基于降水等级分异方法的低影响开发小区雨水径流污染负荷削减率的评估

王生愿 陈江海 陈小龙

王生愿,陈江海,陈小龙.基于降水等级分异方法的低影响开发小区雨水径流污染负荷削减率的评估[J].环境工程技术学报,2022,12(5):1492-1499 doi: 10.12153/j.issn.1674-991X.20210413
引用本文: 王生愿,陈江海,陈小龙.基于降水等级分异方法的低影响开发小区雨水径流污染负荷削减率的评估[J].环境工程技术学报,2022,12(5):1492-1499 doi: 10.12153/j.issn.1674-991X.20210413
WANG S Y,CHEN J H,CHEN X L.Evaluation of reduction rate of rainwater runoff pollution load in low impact development community based on rainfall grade differentiation method[J].Journal of Environmental Engineering Technology,2022,12(5):1492-1499 doi: 10.12153/j.issn.1674-991X.20210413
Citation: WANG S Y,CHEN J H,CHEN X L.Evaluation of reduction rate of rainwater runoff pollution load in low impact development community based on rainfall grade differentiation method[J].Journal of Environmental Engineering Technology,2022,12(5):1492-1499 doi: 10.12153/j.issn.1674-991X.20210413

基于降水等级分异方法的低影响开发小区雨水径流污染负荷削减率的评估

doi: 10.12153/j.issn.1674-991X.20210413
基金项目: 国家重点研发计划项目(2016YFC0802407)
详细信息
    作者简介:

    王生愿(1987—),男,工程师,硕士,主要从事流域水环境综合整治等方面研究,153749527@qq.com

  • 中图分类号: X52

Evaluation of reduction rate of rainwater runoff pollution load in low impact development community based on rainfall grade differentiation method

Funds: REN B Z.Study on monitoring the operation of facilities in residential sponge project[J].Urbanism and Architecture,2019,16(20):174-176.
  • 摘要:

    为定量评估低影响开发(LID)技术对雨水径流污染负荷的削减率,选取嘉兴市柳岸禾丰小区作为LID小区,与其临近且下垫面类型相似的浅水湾小区作为传统小区,同步监测小区的外排水量和TP浓度,根据降水等级分异计算2个小区同等降水情景下单位面积污染负荷量,再以传统小区的单位面积污染负荷量为基准核算LID小区的雨水径流污染负荷削减率。结果表明:小雨时,LID设施可消纳其服务范围内的所有径流及所携带的污染物,污染负荷削减率达100%;当降水量增至超过LID设施功能阈值时,污染物削减率开始降低,中雨时降至67%,大雨时降至46%,年均雨水径流污染负荷削减率约为66%。整体来看,LID设施雨水径流污染负荷削减率表现出明显的降水等级差异。采用降水等级分异的方法能够减少降水等级所造成的误差,确保评估结果的精准程度,为小区LID设施建设提供可靠的决策依据。

     

  • 图  1  LID小区及传统小区监测点位

    Figure  1.  Map of monitoring points in LID community and traditional community

    图  2  2014年嘉兴市5 min步长降水量分布

    Figure  2.  Distribution map of 5 min step length rainfall in Jiaxing in 2014

    图  3  3种情景下LID小区及传统小区的排口流量分布和单位面积产流量对比

    Figure  3.  Comparison of Discharge distribution and yield per unit area between LID and traditional communities under three rainfall scenarios

    图  4  中雨和大雨情景下LID小区及传统小区TP浓度分布及TP负荷量

    Figure  4.  TP concentration distribution and TP load of LID and traditional communities under moderate rain and heavy rain

    图  5  不同情景下LID小区及传统小区单位面积污染负荷量对比

    Figure  5.  Comparison of pollution load per unit area between LID and traditional communities under different scenarios

    表  1  嘉兴市典型年份(2014年)降水等级划分

    Table  1.   Rainfall grade division of Jiaxing in typical year (2014)

    降水等级日降水量/mm累计降水量/mm降水天数/d
    大雨(含暴雨)25~49.9577.315
    中雨10~24.9371.124
    小雨≤10320.997
    下载: 导出CSV

    表  2  小雨情景下传统小区污染负荷核算

    Table  2.   Pollution load calculation of traditional communities under light rain

    时间/min间隔时间段
    流量/L
    TP平均
    浓度/(mg/L)
    总污染
    负荷量/mg
    076.200.129.14
    5121.200.2327.88
    10126.300.0911.37
    20186.300.1324.22
    3049.800.157.47
    60720.600.19136.91
    90261.900.1539.29
    120318.600.1135.05
    合计1 860.90291.32
    下载: 导出CSV

    表  3  中雨情景下LID小区及传统小区污染负荷核算

    Table  3.   Pollution load accounting of LID and traditional communities under moderate rain

    时间/min间隔时间段流量/LTP浓度/(mg/L)总污染负荷量/mg
    LID小区传统小区LID小区传统小区LID小区传统小区
    0 797.881 080.720.130.15106.12166.43
    5472.321 442.340.110.1253.37174.52
    10460.50919.860.100.1246.05113.14
    20443.341 452.180.100.1244.33171.36
    301 624.983 966.480.110.13183.62511.68
    60658.863 456.660.080.1052.71342.21
    9045.1810.590.100.104.521.09
    1204.146.120.090.110.370.64
    合计4 507.2012 334.95491.101 481.07
    下载: 导出CSV

    表  4  大雨情景下LID小区及传统小区污染负荷核算

    Table  4.   Pollution load calculation of LID community and traditional communities under heavy rain

    时间/min间隔时间段流量/LTP平均浓度/(mg/L)总污染负荷量/mg
    LID小区传统小区LID小区传统小区LID小区传统小区
    01.568 723.100.140.160.221 369.53
    51 745.3413 797.300.100.14179.771 973.01
    104 764.3016 271.100.100.15466.902 473.21
    2015 042.8456 027.400.130.142 015.747 675.75
    4041 128.86112 511.400.140.195 922.5621 264.65
    7061 743.72108 763.500.160.1810 125.9719 251.14
    10050 469.9063 590.760.150.167 570.4910 301.70
    13047 798.5856 109.960.160.177 695.579 258.14
    16017 954.6421 564.480.150.172 729.113 665.96
    合计240 649.74457 359.0036 706.3277 233.10
    下载: 导出CSV
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  • 收稿日期:  2021-08-16

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