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Partitioning snowmelt and rainfall in the critical zone: effects of climate type and soil properties

机译:临界区分区雪花和降雨:气候型和土壤性质的影响

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Streamflow generation and deep groundwater recharge may be vulnerable to loss of snow, making it important to quantify how snowmelt is partitioned between soil storage, deep drainage, evapotranspiration, and runoff. Based on previous findings, we hypothesize that snowmelt produces greater streamflow and deep drainage than rainfall and that this effect is greatest in dry climates. To test this hypothesis we examine how snowmelt and rainfall partitioning vary with climate and soil properties using a physically based variably saturated subsurface flow model, HYDRUS-1D. We developed model experiments using observed climate from mountain regions and artificial climate inputs that convert all precipitation to rain, and then evaluated how climate variability affects partitioning in soils with different hydraulic properties and depths. Results indicate that event-scale runoff is higher for snowmelt than for rainfall due to higher antecedent moisture and input rates in both wet and dry climates. Annual runoff also increases with snowmelt fraction, whereas deep drainage is not correlated with snowmelt fraction. Deep drainage is less affected by changes from snowmelt to rainfall because it is controlled by deep soil moisture changes over longer timescales. Soil texture modifies daily wetting and drying patterns but has limited effect on annual water budget partitioning, whereas increases in soil depth lead to lower runoff and greater deep drainage. Overall these results indicate that runoff may be substantially reduced with seasonal snowpack decline in all climates, whereas the effects of snowpack decline on deep drainage are less consistent. These mechanisms help explain recent observations of streamflow sensitivity to changing snowpack and highlight the importance of developing strategies to plan for changes in water budgets in areas most at risk for shifts from snow to rain.
机译:流出生成和深层地下水充电可能很容易遭受雪的丧失,这使得量化雪光如何在土壤储存,深排水,蒸发散热和径流之间分配。基于以前的发现,我们假设雪花产生更大的流流和深度排水,而不是降雨,并且这种效果在干燥气候中最大。为了测试这一假设,我们研究了使用物理上可变饱和的地下流量模型,氢气-1d的气候和土壤性能如何随着气候和土壤性能而变化。我们开发了使用来自山地地区的气候和人工气候投入的模型实验,这些气候投入将所有降水转化为雨,然后评估气候变异性如何影响具有不同液压性能和深度的土壤中的分区。结果表明,由于潮湿和干气度都有更高的先前湿度和投入率,散户比降雨量更高的雪光率较高。年径流也随着散耕剂分数而增加,而深入排水与雪花级分相关。深度排水的影响较小,因雪花降雨而受到降雨的变化,因为它受到深层土壤水分的控制超过更长的时间尺寸。土壤纹理改变日常润湿和干燥模式,但对年度水预算分区有有限的影响,而土壤深度的增加导致径流较低,深排水。总体而言,这些结果表明,所有气候中的季节性积雪下降可能会显着减少径流,而积雪衰落的深度排水的影响不太一致。这些机制有助于解释最近对改变积雪的流流敏感性的观察,并突显了发展战略的重要性,以便从雪地到下雨的危险面临的地区的水预算变化。

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