Budyko框架下黄河流域蒸散发时空变化影响因素研究

王亚琴, 杨巍, 邢博, 罗毅. Budyko框架下黄河流域蒸散发时空变化影响因素研究[J]. 水文地质工程地质, 2023, 50(2): 23-33. doi: 10.16030/j.cnki.issn.1000-3665.202205066
引用本文: 王亚琴, 杨巍, 邢博, 罗毅. Budyko框架下黄河流域蒸散发时空变化影响因素研究[J]. 水文地质工程地质, 2023, 50(2): 23-33. doi: 10.16030/j.cnki.issn.1000-3665.202205066
WANG Yaqin, YANG Wei, XING Bo, LUO Yi. A study of influencing factors of spatio-temporal evapotranspiration variation across the Yellow River Basin under the Budyko framework[J]. Hydrogeology & Engineering Geology, 2023, 50(2): 23-33. doi: 10.16030/j.cnki.issn.1000-3665.202205066
Citation: WANG Yaqin, YANG Wei, XING Bo, LUO Yi. A study of influencing factors of spatio-temporal evapotranspiration variation across the Yellow River Basin under the Budyko framework[J]. Hydrogeology & Engineering Geology, 2023, 50(2): 23-33. doi: 10.16030/j.cnki.issn.1000-3665.202205066

Budyko框架下黄河流域蒸散发时空变化影响因素研究

  • 基金项目: 中国科学院战略重点研究计划项目(XDA20060301);国家重点研发计划项目(2016YFC0501603)
详细信息
    作者简介: 王亚琴(1987-),女,博士,助理研究员,主要从事生态水文和遥感监测工作。E-mail:wangyq.14b@igsnrr.ac.cn
    通讯作者: 罗毅(1966-),男,博士,博士生导师,研究员,主要从事生态水文研究和教学工作。E-mail:luoyi@igsnrr.ac.cn
  • 中图分类号: P641.69

A study of influencing factors of spatio-temporal evapotranspiration variation across the Yellow River Basin under the Budyko framework

More Information
  • 蒸散发是水循环过程中的重要环节,研究蒸散发时空变化影响因素,有利于认识区域水资源的时空分异规律。黄河流域地处干旱半干旱地区,水资源短缺且时空分布不均,水问题突出。在黄河流域分析蒸散发对变化环境的响应,揭示气候变化、植被季节性和物候变化的水文水资源效应,对地区水资源可持续发展和规划管理等具有重要的理论意义和现实意义。基于多元自适应回归样条(MARS)非参数模型,采用黄河流域内30个子流域的全球监测与模型研究组(GIMMS)制作的第三代归一化植被指数(NDVI3g)数据集、气象数据、土壤数据、土地利用/覆盖数据以及地形地貌数据,在Budyko框架下分析了水热耦合控制参数ϖ与环境变量因子的关联性,探讨了变化环境对流域蒸散发的影响机制。结果表明:(1)流域水平衡关系的空间变异与流域水热耦合季节性、地形地貌空间变异性、降水的季节性特征(平均暴雨深度和降水变异系数)显著相关。(2)年际尺度上:流域水热的不同步性是影响流域水平衡年际分异最重要的气候季节性指数,水热的不同步性增大,流域的蒸散比减小,产流增加;降水越集中、年内变异程度越高、降水的季节性越明显,流域蒸散比越小;植被的季节性特征是影响流域水平衡的重要因素,植被生长越强,生长季长度越长,流域的蒸散比越大,产流系数越小。(3)环境变量之间存在较强的自相关性,协同演化并作用于流域蒸散发。

  • 加载中
  • 图 1  研究区位置及植被类型示意图(2010年)

    Figure 1. 

    图 2  研究方法和流程

    Figure 2. 

    图 3  流域水热耦合季节性指数与流域植被覆盖度的关系

    Figure 3. 

    图 4  ϖ年际变化率与植被和气候季节性年际变化率的关系

    Figure 4. 

    图 5  植被-气候相互作用对ϖ年际变异的影响

    Figure 5. 

    表 1  变化环境因子指标体系

    Table 1.  List of indicators associated with the changed environment

    静态变量动态变量
    影响因素初选表征因子计算方法影响因素初选表征因子计算方法
    地形地貌高程/m(x1
    相对高程/m(x2
    高程变异(x3
    坡度/(°)(x4
    DEM数据
    空间统计
    气候条件水热耦合季节性指数(x11
    平均暴雨深度/mm(x12
    降水集中指数(x13
    降水变异系数(x14
    降水季节性指数(x15
    气象数据[14,18]
    土壤条件相对土壤入渗能力(x5
    植被-土壤相对蓄水能力(x6
    土壤性质
    气候条件[33]
    植被条件植被覆盖度(x16
    年平均NDVI(x17
    非生长季NDVI(x18
    生长季NDVI最大值(x19
    生长季振幅(x20
    生长季合成植被指数(x21
    生长季活跃累积量(x22
    生长季总累积量(x23
    植被指数
    时间序列[21]
    土地利用/覆盖结构林地比例(x7
    灌丛比例(x8
    草地比例(x9
    农田比例(x10
    土地利用
    空间统计
    物候信息相对生长季长度(x24
    下载: 导出CSV

    表 2  30个子流域的MARS最终模型和精度评价

    Table 2.  MARS final models and accuracy evaluation for 30 sub-catchments

    流域号水文站面积/km2ϖMARS最终模型及节点MAERMSER2
    1#民和15342 2.560.521×(0.861−x11)+−0.053×(x13-16.9)+−103×(x20-0.452)+0.080.100.65
    2#武山80802.530.026×(x12−109)+−95.1×(0.391−x24)+0.230.300.60
    3#靖远52073.55−2.57×(x14−0.969)+−0.018×(92.9−x12)+0.150.180.65
    4#郭城驿54703.36−0.282×(x11−0.962)++0.514×(0.962−x11)+−1.96×(x14−1.03)+0.220.300.38
    5#秦安98053.45−80.4×(0.415−x24)++1.38×(0.653−x11)+0.220.270.62
    6#社棠18463.700.019×(140−x12)+−21.5×(x22−3.54)+−13.6×(3.54−x22)+0.310.390.64
    7#千阳35052.860.016×(x12−123)+−21.6×(x22−4.57)+−8.92×(4.57−x22)+0.450.540.54
    8#景村402813.253.25+0.008×(x12−132)+−0.015×(132−x12)+−2.76×(x14−1.02)+0.180.220.72
    9#张河15062.960.017×(x12−135)+−0.565×(x19−0.573)+0.280.350.45
    10#柳林7972.050.016×(x12−135)++8.11×(0.87−x14)+0.490.620.41
    11#雨落坪190193.350.020×(x12−124)+−3.89×(x14−0.982)+0.380.530.51
    12#庆阳106032.84−0.588×(x11−0.914)++2.2×(0.902−x15)+0.190.250.53
    13#郭家桥52161.80127×(3.15−)+×(−0.14)++284×(3.15−)+×(0.14−)+0.120.150.70
    14#横山24152.74−0.191×(x11−0.892)++0.775×(0.892−x11)+−51.5×(0.327−x19)+0.150.190.71
    15#绥德38932.140.446×(1.37−x11)++10.7×(x19−0.36)++0.064×(18.4−x13)+0.100.120.83
    16#韩家峁24521.930.154×(2.24−x11)++0.004×(x12−93.5)+−0.009×(93.5−x12)++0.89×(1.24−x14)+0.070.080.85
    17#申家湾11212.386.81×(x22−1.35)+−0.181×(x11−1.02)+0.160.210.56
    18#神木72982.4817.5×(x19−0.325)+−46.2×(0.325−x19)+−0.262×(x11−1.04)+0.170.220.65
    19#龙头拐11451.9699.7×(x18−0.127)++66.3×(0.127−x18)+0.190.240.36
    20#新庙15272.015.36×(x23−3.04)+0.200.250.77
    21#上静游11902.590.755×(1.02−x11)−0.096(x13−18.7)+0.200.250.48
    22#林家坪18732.761.32×(0.792-x11)+−14.7×(−18)+×(0.175)+0.220.260.55
    23#高家川32531.64−0.201×(x11−1.83)++33.7×(x20−0.152)++0.004×(x12−121)+0.090.110.76
    24#后大成41022.190.655×(0.966−x11)++38.9×(x24−0.421)+−16.6×(x18−0.219)+0.160.190.59
    25#裴沟10232.591.04×(1−x11)+0.310.390.45
    26#大宁39923.071.95×(x22−3.52)+−0.371×(x11−0.55)+0.190.260.48
    27#新市河16623.690.011×(x12−130)+−0.018×(130-x12)+−3.78×(x14−1.01)+0.200.240.74
    28#大村21423.28−106×(x20−0.456)+0.240.320.31
    29#吉县4362.631.11×(0.797−x11)++116×(x24−0.456)++0.006×(x12−119)+0.300.370.62
    30#柴庄338003.09−5.72×(x15−0.795)++0.019×(x12−124)+−2.87×(−124)+×(0.342−)+0.360.500.49
    注:变量表示2个相互作用的变量。(xn-a)+指括号内值恒正,如果为负值,则括号内该项为0;其中a为节点值。
    下载: 导出CSV
  • [1]

    FIELD C, BARROS V, STOCKER T, et al. Managing the risks of extreme events and disasters to advance climate change adaptation: A special report of working groups I and II of the intergovernmental panel on climate change[R]. Cambridge University Press, 2012:1-19..

    [2]

    STOCKER T F, QIN D, PLATTNER G K, et al. Climate change 2013: The physical science basis, intergovernmental panel on climate change, working group I contribution to the IPCC fifth assessment report (AR5)[M]. New York: Press CU Editor, 2013.

    [3]

    刘昌明,张学成. 黄河干流实际来水量不断减少的成因分析[J]. 地理学报,2004,59(3):323 − 330. [LIU Changming,ZHANG Xuecheng. Causal analysis on actual water flow reduction in the mainstream of the Yellow River[J]. Acta Geographica Sinica,2004,59(3):323 − 330. (in Chinese with English abstract) doi: 10.3321/j.issn:0375-5444.2004.03.001

    [4]

    ZHAO Yifei,ZOU Xinqing,ZHANG Jianxiang,et al. Spatio-temporal variation of reference evapotranspiration and aridity index in the Loess Plateau Region of China,during 1961-2012[J]. Quaternary International,2014,349:196 − 206. doi: 10.1016/j.quaint.2014.06.050

    [5]

    GAO Xuerui,SUN Miao,ZHAO Qi,et al. Actual ET modelling based on the Budyko framework and the sustainability of vegetation water use in the loess plateau[J]. Science of the Total Environment,2017,579:1550 − 1559. doi: 10.1016/j.scitotenv.2016.11.163

    [6]

    王文科. 陆域蒸散发及资源环境效应[J]. 水文地质工程地质,2021,48(3):I − II. [WANG Wenke. Terrestrial evapotranspiration and its effects on resources and environment[J]. Hydrogeology & Engineering Geology,2021,48(3):I − II. (in Chinese with English abstract)

    [7]

    王周锋,王文科,李俊亭. 蒸散发水源组成与测定方法研究进展[J]. 水文地质工程地质,2021,48(3):1 − 9. [WANG Zhoufeng,WANG Wenke,LI Junting. A review of the advances in water source composition and observation methods of evapotranspiration[J]. Hydrogeology & Engineering Geology,2021,48(3):1 − 9. (in Chinese with English abstract) doi: 10.16030/j.cnki.issn.1000-3665.202012042

    [8]

    WANG Weiguang,ZOU Shan,SHAO Quanxi,et al. The analytical derivation of multiple elasticities of runoff to climate change and catchment characteristics alteration[J]. Journal of Hydrology,2016,541:1042 − 1056. doi: 10.1016/j.jhydrol.2016.08.014

    [9]

    DONOHUE R J,RODERICK M L,MCVICAR T R. Roots,storms and soil pores:Incorporating key ecohydrological processes into Budyko’s hydrological model[J]. Journal of Hydrology,2012,436/437:35 − 50. doi: 10.1016/j.jhydrol.2012.02.033

    [10]

    LI Hongyi,SIVAPALAN M,TIAN Fuqiang,et al. Functional approach to exploring climatic and landscape controls of runoff generation:1. Behavioral constraints on runoff volume[J]. Water Resources Research,2014,50(12):9300 − 9322. doi: 10.1002/2014WR016307

    [11]

    YANG Dawen, SHAO Weiwei, YEH P J F, et al. Impact of vegetation coverage on regional water balance in the nonhumid regions of China[J]. Water Resources Research, 2009, 45(7).

    [12]

    YE Sheng,LI Hongyi,LI Shuai,et al. Vegetation regulation on streamflow intra-annual variability through adaption to climate variations[J]. Geophysical Research Letters,2015,42(23):10307 − 10315.

    [13]

    NING Tingting,LI Zhi,LIU Wenzhao. Vegetation dynamics and climate seasonality jointly control the interannual catchment water balance in the Loess Plateau under the Budyko framework[J]. Hydrology and Earth System Sciences,2017,21(3):1515 − 1526. doi: 10.5194/hess-21-1515-2017

    [14]

    XING Wanqiu,WANG Weiguang,SHAO Quanxi,et al. Identification of dominant interactions between climatic seasonality,catchment characteristics and agricultural activities on Budyko-type equation parameter estimation[J]. Journal of Hydrology,2018,556:585 − 599. doi: 10.1016/j.jhydrol.2017.11.048

    [15]

    FENG Xiaoming,FU Bojie,PIAO Shilong,et al. Revegetation in China’s Loess Plateau is approaching sustainable water resource limits[J]. Nature Climate Change,2016,6(11):1019 − 1022. doi: 10.1038/nclimate3092

    [16]

    LIANG Wei,BAI Dan,WANG Feiyu,et al. Quantifying the impacts of climate change and ecological restoration on streamflow changes based on a Budyko hydrological model in China’s Loess Plateau[J]. Water Resources Research,2015,51(8):6500 − 6519. doi: 10.1002/2014WR016589

    [17]

    WANG Yaqin,LUO Yi,SHAFEEQUE M. Interpretation of vegetation phenology changes using daytime and night-time temperatures across the Yellow River Basin,China[J]. Science of the Total Environment,2019,693:133553. doi: 10.1016/j.scitotenv.2019.07.359

    [18]

    WANG Yaqin,LUO Yi,SHAFEEQUE M. Using a Gaussian function to describe the seasonal courses of monthly precipitation and potential evapotranspiration across the Yellow River Basin,China[J]. Journal of Hydrometeorology,2019,20(11):2185 − 2201. doi: 10.1175/JHM-D-19-0019.1

    [19]

    王亚琴,孙林,李洪宇等. 黄河流域上中游地区月度 8-km网格气象数据集(1980–2015)[J]. 全球变化数据学报,2022,6(1):25 − 36. [WANG Yaqin,SUN Lin,LI Hongyu,et al. Monthly/8km grid meteorological dataset at the middle and upper reaches of the Yellow River Basin of China (1980–2015)[J]. Journal of Global Change Data & Discovery,2022,6(1):25 − 36. (in Chinese with English abstract)

    [20]

    吴炳方, 钱金凯, 曾源, 等. 中华人民共和国土地覆被地图集(1∶10 000 000)[M]. 北京: 中国地图出版社, 2017

    WU Bingfang, QIAN Jinkai, ZENG Yuan, et al. Land cover atlas of the People’s Republic of China (1∶10 000 000)[M]. Beijing: China Cartographic Publishing House, 2017. (in Chinese)

    [21]

    JONSSON P,EKLUNDH L. Seasonality extraction by function fitting to time-series of satellite sensor data[J]. IEEE Transactions on Geoscience and Remote Sensing,2002,40(8):1824 − 1832. doi: 10.1109/TGRS.2002.802519

    [22]

    BUDYKO M I, MILLER EEEB D H. Climate and life [M]. New York: Academic, 1974.

    [23]

    傅抱璞. 论陆面蒸发的计算[J]. 大气科学,1981,5(1):23 − 31. [FU Baopu. On the calculation of the evaporation from land surface[J]. Scientia Atmospheric Sinica,1981,5(1):23 − 31. (in Chinese with English abstract) doi: 10.3878/j.issn.1006-9895.1981.01.03

    [24]

    DU C,SUN F,YU Jingjie,et al. New interpretation of the role of water balance in an extended Budyko hypothesis in arid regions[J]. Hydrology and Earth System Sciences,2015,20:393 − 409.

    [25]

    ALLEN R G, PEREIRA L S, RAES D, et al. Crop evapotranspiration: Guidelines for computing crop water requirements[C]//Irrigation and Drainage Paper 56. Food and Agriculture, Organization. Rome, 1998: 56.

    [26]

    李云凤,王文科,王国庆,等. 黄河源区潜在蒸散量估算方法适用性分析[J]. 水文地质工程地质,2021,48(3):10 − 19. [LI Yunfeng,WANG Wenke,WANG Guoqing,et al. The applicability of various potential evapotranspiration estimation methods in the headwater area of the Yellow River[J]. Hydrogeology & Engineering Geology,2021,48(3):10 − 19. (in Chinese with English abstract) doi: 10.16030/j.cnki.issn.1000-3665.202011044

    [27]

    阴晓伟,吴一平,赵文智,等. 西北旱区潜在蒸散发的气候敏感性及其干旱特征研究[J]. 水文地质工程地质,2021,48(3):20 − 30. [YIN Xiaowei,WU Yiping,ZHAO Wenzhi,et al. Drought characteristics and sensitivity of potential evapotranspiration to climatic factors in the arid and semi-arid areas of northwest China[J]. Hydrogeology & Engineering Geology,2021,48(3):20 − 30. (in Chinese with English abstract) doi: 10.16030/j.cnki.issn.1000-3665.202012012

    [28]

    ZHANG L,DAWES W R,WALKER G R. Response of mean annual evapotranspiration to vegetation changes at catchment scale[J]. Water Resources Research,2001,37(3):701 − 708. doi: 10.1029/2000WR900325

    [29]

    ABATZOGLOU J T,FICKLIN D L. Climatic and physiographic controls of spatial variability in surface water balance over the contiguous United States using the Budyko relationship[J]. Water Resources Research,2017,53(9):7630 − 7643. doi: 10.1002/2017WR020843

    [30]

    MILLY P C D. Climate,interseasonal storage of soil water,and the annual water balance[J]. Advances in Water Resources,1994,17(1/2):19 − 24.

    [31]

    SHAO Quanxi, TRAYLEN A, ZHANG Lu. Nonparametric method for estimating the effects of climatic and catchment characteristics on mean annual evapotranspiration[J]. Water Resources Research, 2012, 48(3): W03517.

    [32]

    DE LAVENNE A,ANDRÉASSIAN V. Impact of climate seasonality on catchment yield:A parameterization for commonly-used water balance formulas[J]. Journal of Hydrology,2018,558:266 − 274. doi: 10.1016/j.jhydrol.2018.01.009

    [33]

    孙福宝. 基于Budyko水热耦合平衡假设的流域蒸散发研究[D]. 北京: 清华大学, 2007

    SUN Fubao. Study on watershed evapotranspiration based on the budyko hypothesis[D]. Beijing: Tsinghua University, 2007. (in Chinese with English abstract)

    [34]

    FRIEDMAN D. Evolutionary games in economics[J]. Econometrica,1991,59(3):637. doi: 10.2307/2938222

    [35]

    EAGLESON P S. Ecohydrology: Darwinian expression of vegetation form and function[M]. Cambridge: Cambridge University Press, 2002

    [36]

    FU Jianyu,WANG Weiguang. On the lower bound of Budyko curve:the influence of precipitation seasonality[J]. Journal of Hydrology,2019,570:292 − 303. doi: 10.1016/j.jhydrol.2018.12.062

  • 加载中

(5)

(2)

计量
  • 文章访问数:  1097
  • PDF下载数:  26
  • 施引文献:  0
出版历程
收稿日期:  2022-05-05
修回日期:  2022-07-15
刊出日期:  2023-03-15

目录