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1951—2020年黄河上中游径流变化特征及归因分析

孙莉茹, 毕华兴, 马志瑾, 赵丹阳, 王宁, 刘泽晖, 王鑫

孙莉茹, 毕华兴, 马志瑾, 赵丹阳, 王宁, 刘泽晖, 王鑫. 1951—2020年黄河上中游径流变化特征及归因分析[J]. 北京林业大学学报, 2024, 46(1): 82-92. DOI: 10.12171/j.1000-1522.20230077
引用本文: 孙莉茹, 毕华兴, 马志瑾, 赵丹阳, 王宁, 刘泽晖, 王鑫. 1951—2020年黄河上中游径流变化特征及归因分析[J]. 北京林业大学学报, 2024, 46(1): 82-92. DOI: 10.12171/j.1000-1522.20230077
Sun Liru, Bi Huaxing, Ma Zhijin, Zhao Danyang, Wang Ning, Liu Zehui, Wang Xin. Runoff variation characteristics and attribution analysis of the upper and middle reaches of the Yellow River from 1951 to 2020[J]. Journal of Beijing Forestry University, 2024, 46(1): 82-92. DOI: 10.12171/j.1000-1522.20230077
Citation: Sun Liru, Bi Huaxing, Ma Zhijin, Zhao Danyang, Wang Ning, Liu Zehui, Wang Xin. Runoff variation characteristics and attribution analysis of the upper and middle reaches of the Yellow River from 1951 to 2020[J]. Journal of Beijing Forestry University, 2024, 46(1): 82-92. DOI: 10.12171/j.1000-1522.20230077

1951—2020年黄河上中游径流变化特征及归因分析

基金项目: 国家重点研发课题(2022YFF1300401),国家自然科学基金项目(31971725、U2243202)。
详细信息
    作者简介:

    孙莉茹。主要研究方向:林业生态工程。Email:sunliru2023@163.com 地址:100083 北京市海淀区清华东路35号

    责任作者:

    毕华兴,教授。主要研究方向:水土保持、林业生态工程。Email:bhx@bjfu.edu.cn 地址:同上。

  • 中图分类号: S715;P333

Runoff variation characteristics and attribution analysis of the upper and middle reaches of the Yellow River from 1951 to 2020

  • 摘要:
    目的 

    河川径流是地表重要的水资源,对其变化特征和原因进行解析,是流域水资源科学管理规划的前提。

    方法 

    本文采用Mann-Kendall趋势检验、Pettitt突变检验、Budyko弹性系数法等方法分析了黄河上游和中游近70年(1951—2020年)径流变化的趋势和成因。

    结果 

    (1)1951—2020年黄河上游年降水量呈不显著增加趋势(4.04 mm/(10 a),P > 0.05),中游呈不显著减少趋势(4.90 mm/(10 a),P > 0.05);上游、中游年潜在蒸散发均呈不显著增加趋势(1.77、2.23 mm/(10 a),P > 0.05);(2)黄河上游和中游1980—2020年土地利用/覆盖变化明显,主要表现在林草面积的增加,上游、中游年NDVI分别以0.025/(10 a)、0.042/(10 a)的速率显著增加(P < 0.01);(3)1951—2020年,上游和中游年径流量分别以3.46、7.46 mm/(10 a)的速率显著减少(P < 0.01),并分别在1986年、1990年发生突变;(4)上游和中游径流对降水变化最为敏感,其次是土地利用/覆盖变化、潜在蒸散发变化,且径流对各影响因子的敏感性逐年增强,即气候和土地利用/覆盖的变化将更容易引起径流的变化;(5)土地利用/覆盖变化是导致黄河上游和中游径流减少的主要原因,其次是降水和潜在蒸散,但各影响因子对径流变化的影响性质和程度在上游和中游不同区间存在一定的差异。其中,上游地区降水、潜在蒸散发、土地利用/覆盖变化对径流的影响性质和程度分别为−14.04%、1.30%、112.73%;中游地区分别为21.54%、3.63%、74.83%。

    结论 

    1951—2020年黄河上游和中游径流变化是气候变化和土地利用/覆盖变化共同作用的结果,但主要影响因素为人类活动主导的土地利用/覆盖变化,且各因子对径流的影响在不同区间存在一定的差异。本研究结果可为黄河上游和中游不同区间的水资源管理和综合治理提供理论支持。

    Abstract:
    Objective 

    River runoff is an important water resource on the surface of the earth, and the analysis of the characteristics and causes of its change is a prerequisite for the scientific management and planning of water resources in the basin.

    Method 

    This study used Mann-Kendall trend test, Pettitt mutation test, Budyko elasticity coefficient method and other methods to analyze trends and causes of runoff variation in the upper and middle reaches of the Yellow River in recent 70 years (1951−2020).

    Result 

    (1) From 1951 to 2020, the annual precipitation in the upper reaches of the Yellow River increased 4.04 mm/(10 year) (P > 0.05) and decrease 4.90 mm/(10 year) (P > 0.05) in the middle reaches of the Yellow River. The potential evapotranspiration in the upper and middle reaches showed no significant increase trend (1.77 mm/(10 year), 2.23 mm/(10 year), P > 0.05). (2) From 1980 to 2020, the changes of landuse/cover in the upper and middle reaches of the Yellow River are obvious, mainly in the increase of forest and grass area, and the NDVI in the upper and middle reaches of the Yellow River increased significantly at the rates of 0.025/(10 year) (P < 0.01) and 0.042/(10 year) (P < 0.01), respectively. (3) From 1951 to 2020, the runoff of upper and middle reaches decreased at the rate of 3.46 mm/(10 year) (P < 0.01) and 7.46 mm/(10 year) (P < 0.01), respectively, and changed abruptly in 1986 and 1990, respectively. (4) Runoff in the upper and middle reaches is most sensitive to precipitation change, followed by land use/cover change and potential evapotranspiration change, and the sensitivity of runoff to each influencing factor increased year by year, which showed that the change of climate and land use will easily cause runoff change. (5) Land use/cover change was the main cause of runoff decrease in the upper and middle reaches of the Yellow River, followed by precipitation and potential evapotranspiration, but there were some differences in the nature and degree of influencing factors on runoff change in different regions of the upper and middle reaches. Among them, the nature and degree of influence of precipitation, potential evapotranspiration, and land use/cover change on runoff in the upstream area were −14.04%, 1.30%, and 112.73%, respectively; the midstream area was 21.54%, 3.63%, and 74.83%, respectively.

    Conclusion 

    The runoff change in the upper and middle reaches of the Yellow River from 1951 to 2020 is the result of climate change and land use/cover change, but the main influencing factor is land use/cover change dominated by human activities, and the influence of each factor on runoff is different in varied intervals. The results of this study can provide theoretical support for water resource management and comprehensive control in different sections of the upper and middle reaches of the Yellow River.

  • 图  1   黄河上游和中游分区及水文气象站点分布

    Figure  1.   Zoning and distribution of hydrological and meteorological stations in the upper and middle reaches of the Yellow River

    图  2   1951—2020年黄河上游和中游年降水、潜在蒸散发变化趋势

    Figure  2.   Changing trend of annual precipitation and potential evaporation in the upper and middle reaches of the Yellow River from 1951 to 2020

    图  3   1982—2020年黄河上游和中游年植被指数变化趋势

    Figure  3.   Variation trend of annual NDVI in the upper and middle reaches of the Yellow River from 1982 to 2020

    图  4   1951—2020年黄河上游和中游年径流变化趋势

    Figure  4.   Variation trend of annual runoff in the upper and middle reaches of the Yellow River from 1951 to 2020

    图  5   降水、潜在蒸散发和土地利用/覆盖的弹性系数年际变化

    Figure  5.   Interannual variation of elasticity coefficients of precipitation, potential evapotranspiration and LUCC

    表  1   黄河上游和中游降水、潜在蒸散发Mann-Kendall趋势检验结果

    Table  1   Results of Mann-Kendall trend test for precipitation and potential evapotranspiration in the upper andmiddle reaches of the Yellow River

    区域 Region降水量 Precipitation潜在蒸散发 Potential evapotranspiration
    ZZ value显著性 Significance趋势 TrendZZ value显著性 Significance趋势 Trend
    上游 Upper reaches1.57NS上升 Raise1.13NS上升 Raise
    中游 Middle reaches−0.85NS下降 Descend0.91NS上升 Raise
    注:NS代表不显著。Note: NS represents not significant.
    下载: 导出CSV

    表  2   1980—2020年黄河上游和中游土地利用类型面积占比

    Table  2   Area proportion of land use types in the upper and middle reaches of the Yellow River from 1980 to 2020 %

    土地利用类型
    Land use type
    上游 Upper reaches 中游 Middle reaches
    1980 1990 2000 2010 2020 1980 1990 2000 2010 2020
    耕地 Cultivated land 12.95 13.06 13.47 13.23 12.99 40.40 40.60 40.53 39.59 37.34
    林地 Forest land 7.73 7.75 7.74 7.88 8.11 19.61 19.52 19.57 20.11 20.14
    草地 Grassland 62.66 62.79 62.06 61.78 62.72 34.35 34.32 34.48 34.49 35.24
    水域 Water area 2.01 1.85 1.88 1.87 2.00 1.11 1.05 0.99 1.05 1.04
    建设用地 Construction land 1.19 1.20 1.29 1.43 2.22 1.76 1.79 2.04 2.29 3.87
    未利用土地 Unused land 13.46 13.35 13.56 13.81 11.96 2.77 2.72 2.39 2.47 2.37
    下载: 导出CSV

    表  3   1980—2020年黄河上游和中游土地利用类型的转移矩阵

    Table  3   Transfer matrix of land use types in the upper and middle reaches of the Yellow River from 1980 to 2020 km2

    区域 Region 土地利用类型
    Land use type
    上游(2020) Upstream (2020)/中游(2020) Midstream (2020)
    耕地
    Cultivated land
    林地
    Forest land
    草地
    Grassland
    水域
    Water area
    建设用地
    Construction land
    未利用土地
    Unused land
    总计
    Sum
    上游(1980)
    Upper reaches (1980)
    耕地 Cultivated land 1 642.45 14 777.75 985.19 3 919.23 1 221.76 55 327.81
    林地 Forest land 1 176.14 12 803.56 216.00 265.17 532.04 33 013.47
    草地 Grassland 16 597.25 13 662.81 2 160.24 2 839.91 15 187.86 267 661.61
    水域 Water area 1 060.61 210.11 2 165.33 199.46 790.17 8 601.84
    建设用地 Construction land 2 046.17 162.55 1 041.10 111.01 143.34 5 092.62
    未利用土地 Unused land 1 865.18 932.99 19 916.89 884.19 664.84 57 426.06
    总计 Sum 55 526.79 34 631.48 267 918.19 8 532.78 9 477.06 51 037.14
    中游(1980)
    Middle reaches (1980)
    耕地 Cultivated land 8 925.19 36 861.29 1 241.20 8 183.97 452.14 138 708.52
    林地 Forest land 7 532.74 10 804.97 185.61 525.19 158.39 67 251.35
    草地 Grassland 32 310.17 11 454.86 639.71 2 094.88 2 347.58 117 911.51
    水域 Water area 1 356.22 187.80 612.35 212.61 64.55 3 805.52
    建设用地 Construction land 3 220.90 167.08 614.66 63.21 27.89 6 041.37
    未利用土地 Unused land 718.53 278.79 3 018.06 85.13 321.30 9 502.68
    总计 Sum 128 183.28 69 058.18 120 975.64 3 586.85 13 285.60 8 131.42
    下载: 导出CSV

    表  4   黄河上游和中游径流趋势及突变检验结果

    Table  4   Results of runoff trends and abrupt change tests in the upper and middle reaches of the Yellow River

    范围 Region Mann-Kendall趋势检验 Mann-Kendall trend test Pettitt突变检验 Pettitt mutation test
    ZZ value 显著性 Significance 趋势 Trend 突变年份 Mutation year 显著性 Significance
    上游 Upper reaches −3.22 ** 下降 Descend 1986 **
    中游 Middle reaches −6.07 ** 下降 Descend 1990 **
    注:**表示P < 0.01。Note: ** represents P < 0.01.
    下载: 导出CSV

    表  5   黄河上游和中游不同时期各气象水文要素特征值及弹性系数

    Table  5   Characteristic values and elasticity coefficients of each meteorological and hydrological element in different periods in the upper and middle reaches of the Yellow River

    范围 Region 时期 Period R/mm P/mm E0/mm R/P E0/P n 弹性系数 Elasticity coefficient
    εp εE0 εn
    上游 Upper reaches 全时段 Full period(1951—2020) 58.78 405.10 966.66 0.15 2.39 1.51 2.25 −1.25 −2.01
    基准期 Base period(1951—1986) 68.66 400.76 964.93 0.17 2.41 1.38 2.11 −1.11 −1.88
    变化期 Change period(1987—2020) 48.32 409.69 968.50 0.12 2.36 1.68 2.42 −1.42 −2.16
    中游 Middle reaches 全时段 Full period(1951—2020) 42.02 540.07 1021.87 0.08 1.89 2.41 3.10 −2.10 −2.30
    基准期 Base period(1951—1990) 54.51 552.26 1016.13 0.10 1.84 2.22 2.88 −1.88 −2.09
    变化期 Change period(1991—2020) 25.37 523.80 1029.53 0.05 1.97 2.81 3.56 −2.56 −2.70
    注:R. 径流量;P. 降水量;E0.潜在蒸散发量;n.经验参数,主要与流域土地利用类型、植被有关;εpεE0εn分别为径流对PE0和参数n的弹性系数。Notes: R represents runoff; P represents precipitation; E0 represents potential evapotranspiration; n represents empirical parameter which are mainly related to land use types and vegetation in watersheds; εp, εE0, εn, respectively represent the elastic coefficients of runoff for PE0 and n.
    下载: 导出CSV

    表  6   黄河上游和中游不同弹性系数绝对值Mann-Kendall趋势分析结果

    Table  6   Results of Mann-Kendall trend analysis of different absolute values of elasticity coefficients in the upper and middle reaches of the Yellow River

    范围 Region |εP| |εE0| |εn|
    Z
    Z value
    显著性
    Significance
    趋势
    Trend
    Z
    Z value
    显著性
    Significance
    趋势
    Trend
    Z
    Z value
    显著性
    Significance
    趋势
    Trend
    上游 Upper reaches 4.58 ** 上升 Raise 4.58 ** 上升 Raise 3.32 ** 上升 Raise
    中游 Middle reaches 6.83 ** 上升 Raise 6.83 ** 上升 Raise 5.55 ** 上升 Raise
    下载: 导出CSV

    表  7   黄河上游和中游径流变化归因分析结果

    Table  7   Results of attribution analysis of runoff changes in the upper and middle reaches of the Yellow River

    范围 Region 基准期
    Base period
    变化期
    Change period
    ΔRP/mm ΔRE0/mm ΔRLUCC/mm ΔR'/mm CP/% CE0/% CLUCC/%
    上游 Upper reaches 1951—1986 1987—2020 2.91 −0.27 −23.36 −20.72 −14.04 1.30 112.73
    中游 Middle reaches 1951—1990 1991—2020 −6.87 −1.16 −23.85 −31.88 21.54 3.63 74.83
    注:ΔRPΔRE0ΔRLUCC分别为降水量P、潜在蒸散发量E0和LUCC引起的径流变化量;ΔR' 为计算求得的径流变化量;CPCE0CLUCC 分别为降水、潜在蒸散发和LUCC对径流变化的影响性质和程度。Notes: ΔRP, ΔRE0, ΔRLUCC, respectively represent runoff changes caused by precipitation, potential evapotranspiration and LUCC. ΔR' represents runoff change calculated. CP, CE0, CLUCC, respectively represent the nature and degree of influence of precipitation, potential evapotranspiration and LUCC on runoff changes.
    下载: 导出CSV
  • [1]

    Zhai R, Tao F. Contributions of climate change and human activities to runoff change in seven typical catchments across China[J]. Science of the Total Environment, 2017, 605−606: 219−229.

    [2] 黄斌斌, 郝成元, 李若男, 等. 气候变化及人类活动对地表径流改变的贡献率及其量化方法研究进展[J]. 自然资源学报, 2018, 33(5): 899−910.

    Huang B B, Hao C Y, Li R N, et al. Research progress on the quantitative methods of calculating contribution rates of climate change and human activities to surface runoff changes[J]. Journal of Natural Resources, 2018, 33(5): 899−910.

    [3] 胡慧杰, 崔凯, 曹茜, 等. 黄河近百年径流演变特征分析[J]. 人民黄河, 2019, 41(9): 14−19.

    Hu H J, Cui K, Cao Q, et al. Analysis of the characteristics of the runoff evolution in Yellow River in recent 100 years[J]. Yellow River, 2019, 41(9): 14−19.

    [4] 鲍振鑫, 严小林, 王国庆, 等. 1956—2016年黄河流域河川径流演变规律[J]. 水资源与水工程学报, 2019, 30(5): 52−57.

    Bao Z X, Yan X L, W G Q, et al. The trend in streamflow of the Yellow River Basin during 1956–2016[J]. Journal of Water Resources and Water Engineering, 2019, 30(5): 52−57.

    [5] 刘昌明, 刘小莽, 田巍, 等. 黄河流域生态保护和高质量发展亟待解决缺水问题[J]. 人民黄河, 2020, 42(9): 6−9.

    Liu C M, Liu X M, Tian W, et al. Ecological protection and high-quality development of the Yellow River Basin urgently need to solve the water shortage problem[J]. Yellow River, 2020, 42(9): 6−9.

    [6]

    Gu C, Mu X, Gao P, et al. Changes in run-off and sediment load in the three parts of the Yellow River Basin, in response to climate change and human activities[J]. Hydrological Processes, 2019, 33(4): 585−601. doi: 10.1002/hyp.13345

    [7] 杨旭, 姬广兴, 杨元达, 等. 1961—2016年黄河中游区间径流变化及归因分析[J]. 河南科学, 2021, 39(12): 2007−2013.

    Yang X, Ji G X, Yang Y D, et al. Runoff changes and their attributions in the middle reaches of the Yellow River from 1961 to 2016[J]. Henan Science, 2021, 39(12): 2007−2013.

    [8]

    Li S, Yang G, Wang H. The runoff evolution and the differences analysis of the causes of runoff change in different regions: a case of the Weihe River Basin, Northern China [J/OL]. Sustainability, 2019, 11(19): 5295[2022−12−21]. https://doi.org/10.3390/su11195295.

    [9]

    Wang J, Hong Y, Gourley J, et al. Quantitative assessment of climate change and human impacts on long-term hydrologic response: a case study in a sub-basin of the Yellow River, China[J]. International Journal of Climatlology, 2010, 30(14): 2130−2137. doi: 10.1002/joc.2023

    [10]

    Zeng F, Ma M G, Di D R, et al. Separating the impacts of climate change and human activities on runoff: a review of method and application[J/OL]. Water, 2020, 12(8): 2201[2022−12−21]. https://doi.org/10.3390/w12082201.

    [11] 杨大文, 张树磊, 徐翔宇. 基于水热耦合平衡方程的黄河流域径流变化归因分析[J]. 中国科学: 技术科学, 2015, 45(10): 1024−1034. doi: 10.1360/N092015-00013

    Yang D W, Zhang S L, Xu X Y. Attribution analysis for runoff decline in Yellow River Basin during past fifty years based on Budyko hypothesis[J]. Scientia Sinica Technologica, 2015, 45(10): 1024−1034. doi: 10.1360/N092015-00013

    [12] 孙福宝, 杨大文, 刘志雨, 等. 基于Budyko假设的黄河流域水热耦合平衡规律研究[J]. 水利学报, 2007, 38(4): 409−416.

    Sun F B, Yang D W, Liu Z Y, et al. Study on coupled water-energy balance in Yellow River Basin based on Budyko hypothesis[J]. Journal of Hydraulic Science, 2007, 38(4): 409−416.

    [13]

    Ni Y, Yu Z, Lü X, et al. Spatial difference analysis of the runoff evolution attribution in the Yellow River Basin[J/OL]. Journal of Hydrology, 2022, 612: 128149[2022−12−21]. https://doi.org/10.1016 /j.jhydrol.2022.128149.

    [14]

    He Y, Mu X, Jiang X, et al. Runoff variation and influencing factors in the Kuye River Basin of the middle Yellow River[J/OL]. Frontiers in Environmental Science, 2022, 10: 877535[2022−12−21]. https://doi.org/10.3389/fenvs.2022.877535.

    [15]

    Allen R G, Pereira L S, Raes D, et al. Crop evapotranspiration: guidelines for computing crop water requirements: FAO irrigation and drainage paper 56[M]. Rome: Food and Agriculture Organization of the United Nations, 1998.

    [16] 徐洋, 杨雅萍. 1982–2020年中国5 km分辨率逐月NDVI数据集[J]. 中国科学数据(中英文网络版), 2022, 7(1): 99–107.

    Xu Y , Yang Y P. A 5 km resolution dataset of monthly NDVI product of China(1982–2020)[J]. China Academic Journal Electronic Publishing House, 2022, 7(1): 99–107.

    [17] 蓝云龙, 黎曙, 李霞, 等. 1956–2018年黄河源区降水变化规律分析[J]. 青海科技, 2021, 28(5): 107−112.

    Lan Y L, Li S, Li X, et al. Analysis of precipitation variation law in the source region of the Yellow River from 1956 to 2018[J]. Qinghai Science and Technology, 2021, 28(5): 107−112.

    [18] 田小靖, 赵广举, 穆兴民, 等. 水文序列突变点识别方法比较研究[J]. 泥沙研究, 2019, 44(2): 33−40.

    Tian X J, Zhao G J, Mu X M, et al. Comparison study on hydrological time series change-point testing methods[J]. Journal of Sediment Research, 2019, 44(2): 33−40.

    [19]

    Hamed K H. Trend detection in hydrologic data: the Mann-Kendall trend test under the scaling hypothesis[J/OL]. Journal of Hydrology, 2008, 349(3–4): 350–363.

    [20]

    Mann H B. Nonparametric tests against trend[J/OL]. Econometrica, 1945, 13(3): 245[2022−12−20]. https:// doi.org/10.2307/1907187.

    [21]

    Pettitt A N. A non-parametric approach to the change-point problem[J/OL]. Applied Statistics, 1979, 28(2): 126[2022−12−20]. https://doi.org/10.2307/2346729.

    [22] 廖慧, 舒章康, 金君良, 等. 1980–2015年黄河流域土地利用变化特征与驱动力[J]. 南水北调与水利科技(中英文), 2021, 19(1): 129−139.

    Liao H, Shu Z K, Jin J L, et al. Characteristics and driving forces of land use change in the Yellow River Basin from 1980 to 2015[J]. South-to-North Water Transfer and Water Science and Technology, 2021, 19(1): 129−139.

    [23]

    Choudhury B J. Evaluation of an empirical equation for annual evaporation using field observations and results from a biophysical model[J]. Journal of Hydrology, 1999, 216(1−2): 99−110.

    [24]

    Yang H, Yang D, Lei Z, et al. New analytical derivation of the mean annual water-energy balance equation[J]. Water Resources Research, 2008, 44(3): 893−897.

    [25]

    Yang Y, Tian F. Abrupt change of runoff and its major driving factors in Haihe River Catchment, China[J]. Journal of Hydrology, 2009, 374(3−4): 373−383.

    [26]

    Yang H, Yang D. Derivation of climate elasticity of runoff to assess the effects of climate change on annual runoff[J]. Water Resources Research, 2011, 47(7): 197−203.

    [27]

    McCuen R H. A sensitivity and error analysis CF procedures used for estimating evaporation[J]. Journal of the American Water Resources Association, 1974, 10(3): 486−497. doi: 10.1111/j.1752-1688.1974.tb00590.x

    [28]

    Xu X, Yang D, Yang H, et al. Attribution analysis based on the Budyko hypothesis for detecting the dominant cause of runoff decline in Haihe basin[J]. Journal of Hydrology, 2014, 510: 530−540. doi: 10.1016/j.jhydrol.2013.12.052

    [29]

    Wang H, Stephenson S. Quantifying the impacts of climate change and land use/cover change on runoff in the lower Connecticut River Basin[J]. Hydrological Processes, 2018, 32(9): 1301−1312. doi: 10.1002/hyp.11509

    [30] 毕早莹, 李艳忠, 林依雪,等. 基于Budyko理论定量分析窟野河流域植被变化对径流的影响[J]. 北京林业大学学报, 2020, 42(8): 61−71. doi: 10.12171/j.1000-1522.20190330

    Bi Z Y, Li Y Z, Lin Y X, et al. Quantitative assessment on the effects of vegetation changes on runoff based on Budyko theory in the Kuyehe River Basin of northern China[J]. Journal of Beijing Forestry University, 2020, 42(8): 61−71. doi: 10.12171/j.1000-1522.20190330

    [31]

    Jiang C, Zhang H, Wang X, et al. Challenging the land degradation in China’s Loess Plateau: benefits, limitations, sustainability, and adaptive strategies of soil and water conservation[J]. Ecological Engineering, 2019, 127: 135−150. doi: 10.1016/j.ecoleng.2018.11.018

    [32]

    Wang Y, Wang S, Wang C, et al. Runoff sensitivity increases with land use/cover change contributing to runoff decline across the middle reaches of the Yellow River Basin[J/OL]. Journal of Hydrology, 2021, 600: 126536[2021−07−05]. https://doi.org/10.1016/j.jhydrol.2021.126536.

    [33] 李芳, 曾彪, 李勋贵, 等. 气候变化和人类活动对黄河上游径流变化的差异性影响[J]. 人民珠江, 2022, 43(2): 101−111. doi: 10.3969/j.issn.1001-9235.2022.02.014

    Li F, Zeng B, Li X G, et al. Differential impact of climate change and human activities on runoff changes in the upper reaches of the Yellow River[J]. Pearl River, 2022, 43(2): 101−111. doi: 10.3969/j.issn.1001-9235.2022.02.014

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出版历程
  • 收稿日期:  2023-04-02
  • 修回日期:  2023-06-17
  • 网络出版日期:  2023-12-21
  • 刊出日期:  2024-01-24

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