The hydrological effects of varying vegetation characteristics in a temperate water-limited basin: Development of the dynamic Budyko-Choudhury-Porporato (dBCP) model
The hydrological effects of varying vegetation characteristics in a temperate water-limited basin: Development of the dynamic Budyko-Choudhury-Porporato (dBCP) model
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DOI：
10.1016/j.jhydrol.2016.10.035
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发表时间：
2016-12
影响因子：
6.4
通讯作者：
Qiang Liu;T. McVicar;Zhifeng Yang;R. Donohue;L. Liang;Yuting Yang
中科院分区：
文献类型：
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作者：
Qiang Liu;T. McVicar;Zhifeng Yang;R. Donohue;L. Liang;Yuting Yang
植被格局受水分供应的影响，而水分供应反过来又影响水文分配和区域水平衡，特别是在水资源有限的地区。考虑到植被在流域水量分配中的重要作用，最近发展的Budyko- choudhury -Porporato（或BCP）模型将Porporato的关键生态水文过程模型纳入了Choudury的Budyko水文气候框架形式。本文通过将动态生态水文过程纳入稳态BCP模型，并将其与典型的桶式土壤水分平衡模型相结合，扩展了稳态BCP模型（即动态BCP模型）。本文使用dBCP模型评估了温带限水流域（即华北黄河流域）植被对水平衡的影响，该流域生长季节物候主要受低温限制。结果表明：(1)将动态生长季（fs）和动态有效生根深度（Ze）条件纳入dBCP模型后，与原BCP模型相比，结果有所改善；（ii） dBCP模型的结果因所用的时间步长而异（即，我们测试了年平均值到月平均值），这反映了汇水变量的影响，例如：、集水区面积、集水区平均气温、干燥指数、ze；(3)实际蒸散发(E)对平均风暴深度（α）的变化最为敏感，p、Ze、dep次之。当考虑到四个生态水文变量中每一个的观测变率时，z的变化导致最大的变率inE，通常其次是panda α和ep。dBCP结果表明，将动态生态水文过程纳入Budyko框架可以改善区域水平衡年际变化的估计。这有助于了解水资源需求，并建立适当的水资源管理战略，以适应长江三角洲的气候变化。dBCP模式对强迫数据的要求不高，可应用于全球其他盆地。
Vegetation patterns are affected by water availability, which, in turn, influences the hydrological partitioning and regional water balance, especially in water-limited regions. Considering the important role of vegetation in partitioning the catchment water yield, the recently developed Budyko-Choudhury-Porporato (or BCP) model incorporated Porporato’s model of key ecohydrological processes into Choudury’s form of the Budyko hydroclimatic framework. Here we extend the steady state BCP model by incorporating dynamic ecohydrological processes into it and combining it with a typical bucket soil water balance model (resulting in the dynamic BCP, or dBCP, model). The dBCP model is used here to assess the impacts of vegetation on the water balance in a temperate water-limited basin (i.e., the Yellow River Basin (YRB) in north China), where growing season phenology is primarily constrained by low temperatures. The results show that: (i) the incorporation of dynamic growing season (fs) and dynamic effective rooting depth (Ze) conditions into the dBCP model improves results when compared to the original BCP model; (ii) dBCP model’s results vary depending on time-step used (i.e., we tested mean-annual to monthly), which reflected the influence of catchment variables,e.g., catchment area, catchment-average air temperature, dryness index andZe; and (iii) actual evapotranspiration (E) is more sensitive to changes in mean storm depth (α), followed byP,Ze, andEp. When taking into account observed variability of each of four ecohydrological variables, changes inZecause the greatest variability inE, generally followed by variability inPandα, and thenEp. The dBCP results indicate that incorporating dynamic ecohydrological processes into the Budyko framework can improve the estimation of inter-annual variability of the regional water balance. This can help to understand the water requirement and to establish suitable water management strategies to adapt to climate change in the YRB. The dBCP model has modest forcing data requirements and can be applied to other basins globally.