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随机森林模型在径流变化归因分析中的适用性研究

王艺璇 刘夏 沈彦军

王艺璇, 刘夏, 沈彦军. 随机森林模型在径流变化归因分析中的适用性研究[J]. 中国生态农业学报 (中英文), 2022, 30(5): 864−874 doi: 10.12357/cjea.20210652
引用本文: 王艺璇, 刘夏, 沈彦军. 随机森林模型在径流变化归因分析中的适用性研究[J]. 中国生态农业学报 (中英文), 2022, 30(5): 864−874 doi: 10.12357/cjea.20210652
WANG Y X, LIU X, SHEN Y J. Applicability of the random forest model in quantifying the attribution of runoff changes[J]. Chinese Journal of Eco-Agriculture, 2022, 30(5): 864−874 doi: 10.12357/cjea.20210652
Citation: WANG Y X, LIU X, SHEN Y J. Applicability of the random forest model in quantifying the attribution of runoff changes[J]. Chinese Journal of Eco-Agriculture, 2022, 30(5): 864−874 doi: 10.12357/cjea.20210652

随机森林模型在径流变化归因分析中的适用性研究

doi: 10.12357/cjea.20210652
基金项目: 国家自然科学基金项目(41807177)和河北省“三三三人才工程”项目(A202001062)资助
详细信息
    作者简介:

    王艺璇, 主要研究方向为流域生态水文模拟。E-mail: wangyixuanjy@foxmail.com

    通讯作者:

    沈彦军, 主要从事流域生态水文模拟与水环境管理方向研究。E-mail: shenyanjun@sjziam.ac.cn

  • 中图分类号: TV11

Applicability of the random forest model in quantifying the attribution of runoff changes

Funds: This research was supported by the National Natural Science Foundation of China (41807177) and “ 333 Talent Project” of Hebei Province (A202001062).
More Information
  • 摘要: 气候变化和人类活动是影响流域径流变化的两大因素, 定量识别二者对流域径流的影响对水资源合理开发和流域综合治理具有重要意义。随机森林模型作为一种易于使用的机器学习方法, 被越来越多地应用于水文学领域, 然而随机森林模型在径流变化归因分析中是否具有适用性值得探讨。本文以永定河上游的洋河流域为例, 基于随机森林模型对流域径流进行了模拟, 采用径流影响评价模型定量分析了气候变化和人类活动对径流变化的贡献率; 并利用基于物理机制的SWAT模型对研究结果进行了对比验证。研究结果表明: 1)在对不同子流域径流模拟效果方面, SWAT分布式水文模型对东洋河(柴沟堡东站)、南洋河(柴沟堡南站)、洋河(响水堡站)流域突变前的径流量模拟结果较为可信, 3个流域率定期和验证期的R2均在0.65以上, 纳什系数(NSE)也大部分在0.65以上; 随机森林模型对3个流域模拟径流的NSE和R2多在0.80以上, 均高于SWAT模型的NSE和R2, 随机森林模型模拟表现优于SWAT模型; 2)对比验证发现, 基于随机森林模型和SWAT模型的流域径流变化归因分析结果较为相近, 人类活动是导致永定河上游流域径流变化的主要原因, 对径流减少的贡献率为84.3%~97.6%。总体上, 随机森林模型在永定河上游流域径流变化归因研究中具有一定的适用性, 为流域径流变化贡献率的定量识别提供了一种新的方法和思路。
  • 图  1  洋河流域示意图

    Figure  1.  Schematic diagram of the Yanghe River Basin

    图  2  基于SWAT模型的东洋河、南洋河、洋河流域突变前月径流实测值和模拟值对比

    图中虚线左侧为率定期, 右侧为验证期。

    Figure  2.  Observed and simulated monthly runoff before abrupt change in the Dongyanghe River Basin, Nanyanghe River Basin, Yanghe River Basin based on SWAT

    In the figure, the left side of the dotted line is the calibration period, and the righ side of the dotted line is the verification period.

    图  3  基于随机森林模型的东洋河、南洋河、洋河流域突变前月径流实测值和模拟值对比

    Figure  3.  Observed and simulated monthly runoff before abrupt change in the Dongyanghe River Basin, Nanyanghe River Basin, Yanghe River Basin based on random forest model

    图  4  基于SWAT模型(a,b,c)和随机森林模型(d, e, f)的东洋河、南洋河、洋河流域径流影响评价模型结果

    Figure  4.  Observed and simulated monthly runoff after calibration and validation periods based on the SWAT and random forest model in the Dongyanghe River Basin, Nanyanghe River Basin, Yanghe River Basin

    表  1  洋河流域水文站、气象站基本信息

    Table  1.   Basic information of hydrological stations and weather stations in the Yanghe River Basin

    分类 Category站名 Name经度 Longitude (°)纬度 Latitude (°)海拔/控制面积 Altitude (m) /area (km²)时间序列 Period
    气象站
    Meteorological station
    天镇 Tianzhen 114.1 40.4 1015.61984—2015
    尚义 Shangyi114.041.11358.61984—2015
    怀安 Huai’an114.440.71142.41984—2015
    宣化 Xuanhua115.041.6629.31984—2015
    崇礼 Chongli115.341.01246.71984—2015
    涿鹿 Zhuolu115.240.3529.61984—2015
    兴和 Xinghe113.940.91253.11984—2015
    水文站
    Hydrometric station
    柴沟堡东 Chaigoubu East114.140.736741984—2015
    柴沟堡南 Chaigoubu South114.440.724271984—2015
    响水堡 Xiangshuibu115.240.514 5071984—2015
    下载: 导出CSV

    表  2  基于SWAT模型的气候变化及人类活动对东洋河、南洋河、洋河流域径流变化影响的贡献率(1986—2015年)

    Table  2.   Contribution rates of climate change and human activities to runoff changes in the Dongyanghe River Basin, Nanyanghe River Basin, Yanghe River Basin based on SWAT model (1986 to 2015)

    水文站
    Hydrometric station
    时段
    Time interval
    实测径流
    Observed
    runoff
    (×108 m3)
    模拟径流
    Simulated
    runoff
    (×108 m3)
    径流变化量
    Runoff
    variation
    (×108 m3)
    贡献值
    Variable quantity (×108 m3)
    贡献率
    Contribution rate (%)
    气候变化
    Climate change
    人类活动
    Human activities
    气候变化
    Climate change
    人类活动
    Human activities
    柴沟堡东
    Chaigoubu East Station
    突变前
    Before abrupt change
    0.93
    突变后
    After abrupt change
    0.420.85−0.51−0.08−0.4315.784.3
    柴沟堡南
    Chaigoubu South Station
    突变前
    Before abrupt change
    0.47
    突变后
    After abrupt change
    0.190.45−0.28−0.01−0.275.095.0
    响水堡
    Xiangshuibu Station
    突变前
    Before abrupt change
    2.14
    突变后
    After abrupt change
    0.952.04−1.20−0.11−1.098.991.1
    下载: 导出CSV

    表  3  基于随机森林模型的气候变化和人类活动对东洋河、南洋河、洋河流域径流变化的贡献率(1986—2015年)

    Table  3.   Contribution rate of climate change and human activities to the runoff changes in the Dongyanghe River Basin, Nanyanghe River Basin, Yanghe River Basin based on the random forest model (1986−2015)

    水文站
    Hydrometric station
    时段
    Time interval
    实测径流
    Observed
    runoff
    (×108 m3)
    模拟径流
    Simulated
    runoff
    (×108 m3)
    径流变化量
    Runoff
    variation
    (×108 m3)
    贡献值
    Variable quantity (×108 m3)
    贡献率
    Contribution rate (%)
    气候变化
    Climate change
    人类活动
    Human activities
    气候变化
    Climate change
    人类活动
    Human activities
    柴沟堡东
    Chaigoubu East Station
    突变前
    Before abrupt change
    0.93
    突变后
    After abrupt change
    0.420.87−0.51−0.06−0.4511.588.5
    柴沟堡南
    Chaigoubu South Station
    突变前
    Before abrupt change
    0.47
    突变后
    After abrupt change
    0.190.46−0.28−0.01−0.27 2.497.6
    响水堡
    Xiangshuibu Station
    突变前
    Before abrupt change
    2.14
    突变后
    After abrupt change
    0.952.10−1.20−0.04−1.15 3.496.6
    下载: 导出CSV
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  • 收稿日期:  2021-09-27
  • 录用日期:  2021-12-30
  • 网络出版日期:  2021-12-31
  • 刊出日期:  2022-05-18

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