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    毕早莹, 李艳忠, 林依雪, 卜添荟, 黄蓉. 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
    引用本文: 毕早莹, 李艳忠, 林依雪, 卜添荟, 黄蓉. 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 Zaoying, Li Yanzhong, Lin Yixue, Bu Tianhui, Huang Rong. 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
    Citation: Bi Zaoying, Li Yanzhong, Lin Yixue, Bu Tianhui, Huang Rong. 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

    基于Budyko理论定量分析窟野河流域植被变化对径流的影响

    Quantitative assessment on the effects of vegetation changes on runoff based on Budyko theory in the Kuyehe River Basin of northern China

    • 摘要:
        目的  植被变化可影响流域下垫面条件,改变水文过程和水资源可持续利用量。揭示植被时空变化格局,明确其对径流变化的贡献是流域水资源管理规划的前提,也是植被恢复工程实施效果评价的依据。
        方法  本研究以植被恢复的典型半干旱区窟野河流域为研究区,基于遥感植被指数NDVI和水文、气象数据,通过基于Budyko假设的弹性系数法,分析了1982—2015年植被变化对径流变化的影响。
        结果  (1)径流突变点在1998年左右,突变点前后,径流和人类取耗水变化率分别达到−55.5%和92.3%,存在显著性差异(P < 0.05);降水、干燥指数分别增加2.6%和1.9%,前后两个时段差异不显著(P > 0.05)。(2)流域植被指数NDVI在突变点前后差异显著,88.7%以上区域呈显著增加趋势(P < 0.001),尤以下游明显,表明植被得到了极大恢复。Budyko弹性模型中表征流域属性信息的参数最优值为2.37,拟合出来的参数系数和常数项分别为20.407和−1.868(P < 0.05),表明拟合效果较好,适用性较强。(3)植被变化对径流的贡献率达到84.9%,气候变化和人类活动影响分别为9.3%和5.8%。
        结论  窟野河流域内植被得到了极大的恢复;植被变化成为决定径流变化的主导因素,其次为气候变化和人类活动。植被变化的长期生态水文效应有待进一步加强研究,本研究结果可为生态恢复工程实施和政策制定提供参考依据。

       

      Abstract:
        Objective  Significant restoration of vegetation in arid area can affect underlying surface conditions of the basin and change the hydrological process, which in turn affects the sustainable use of water resources in the basin. Assessing the spatial and temporal variation pattern of vegetation and clarifying its contribution to the runoff change is the premise of water resources management. This will also be helpful for evaluating the implementation effect of the vegetation restoration project.
        Method  Taking the typical semi-arid area of vegetation restoration, Kuyehe River Basin of northern China as the study area, based on the normalized difference vegetation index (NDVI), hydrological and meteorological data, this paper analyzes the impact of vegetation changes on runoff change during 1982−2015 based on the Budyko hypothesis of the Fu’s model.
        Result  (1) The break point of observed runoff occurred around year 1998, and the changing rates of runoff and human water consumption reached −55.5% and 92.3%, respectively before and after the break point, with a significant difference (P < 0.05); while the precipitation and dryness index increased by 2.6% and 1.9%, respectively, without significant difference (P > 0.05). (2) The basin NDVI was significantly different before and after the break point. Approximately 88.7% of basin area showed a significant increase trend (P < 0.001), especially in the downstream, indicating that the vegetation was greatly restored. The optimal solution of the watershed parameter was 2.37, and the fitted parameter and constant term were 20.407 and −1.868, respectively (P < 0.05), demonstrating that the fitting effect was good, and the applicability was strong. (3) The contribution rate of vegetation change to runoff reached 84.9%, while the contribution rates of climate change and human activity impact to runoff were 9.3% and 5.8%, respectively.
        Conclusion  It shows that the vegetation in the basin has been greatly restored; the greening of vegetation becomes the dominant factor determining the change of runoff, followed by climate change and human activities. The long-term ecological hydrological effects of vegetation changes need to be further investigated. The results of this study can provide a reference for the implementation of ecological restoration projects and decision-making.

       

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