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Simulation of vegetation and hydrology for climate change analysis of a mountain watershed.

机译:植被和水文模拟,用于山区流域的气候变化分析。

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Climate change is expected to have both direct and indirect effects on water resources. Hydrologic impacts of two indirect effects, vegetation density and stomatal conductance, are evaluated for the American River, a 200 km 2 watershed in the Cascade Range of Washington state. First, a set of distributed hydrology-biogeochemistry model structures are created by coupling DHSVM (Distributed Hydrology-Soil-Vegetation Model) and Biome-BGC (BioGeochemistry Cycles). The model structures are applied to idealized hillslopes and current and future climate scenarios for the watershed. Eleven model structures, differing in vertical 1-D hydrology parameterization, lateral water routing, timestep, slope and aspect, are tested. Sensitivity of hydrology and vegetation density (as measured by leaf area index, LAI) is evaluated with respect to model structure, lapsed climate (elevation), climate change, and soil thickness and nitrogen input rate. Lapsed climate accounts for the largest range in LAI, but choice of model structure is also significant, highlighting opportunities and problems in model development. LAI is water-limited at low elevations, temperature-limited at high elevations, and solar-limited at all elevations. All model structures predict increased LAI under the future scenario that includes reduced stomatal conductance—the conifer forest grows denser. Next, climate scenarios and LAI results from the idealized hillslope simulations are input to the hydrology model DHSVM for hydrologic analysis of the full American River watershed. Basin-average annual precipitation, streamflow, and evapotranspiration all increase under the future climate scenario. The direct effect of increased temperature causes the major hydrologic impact, reduced snowpack and altered seasonal timing of streamflow, and ET. Indirect effects of altered LAI and stomatal conductance on hydrology are minor in comparison to the direct effects. Future streamflow, and ET are essentially the same between the simplest treatment of climate change, involving fixed LAI and physical climate change only, and the most detailed treatment, involving variable LAI and reduced stomatal conductance in addition to physical climate change.
机译:预期气候变化将对水资源产生直接和间接影响。在华盛顿州喀斯喀特山脉的200 km 2 分水岭美国河上,评估了植被密度和气孔导度这两种间接影响对水文的影响。首先,通过耦合DHSVM(分布式水文学-土壤-植被模型)和Biome-BGC(生物地球化学循环)来创建一组分布式水文-生物地球化学模型结构。该模型结构适用于理想的山坡以及该流域当前和将来的气候情景。测试了11种模型结构,这些模型结构在垂直一维水文参数化,横向水路由,时间步长,坡度和坡向方面有所不同。针对模型结构,历时气候(海拔),气候变化以及土壤厚度和氮输入速率,评估了水文学和植被密度(通过叶面积指数,LAI衡量)的敏感性。滞后的气候在LAI中占最大范围,但是模型结构的选择也很重要,突出了模型开发中的机会和问题。 LAI在低海拔地区受水限制,在高海拔地区受温度限制,在所有海拔地区都受阳光限制。所有模型结构都预测在未来情况下LAI会增加,包括气孔导度降低-针叶林会变得更茂密。接下来,将理想的山坡模拟得出的气候情景和LAI结果输入到水文模型DHSVM中,以对整个美国河流流域进行水文分析。在未来的气候情景下,流域平均年降水量,水流量和蒸散量都将增加。温度升高的直接影响导致主要的水文影响,积雪减少以及溪流和ET的季节性变化。与直接影响相比,改变的LAI和气孔导度对水文学的间接影响较小。在仅涉及固定LAI和物理气候变化的最简单的气候变化处理与除了物理气候变化之外的涉及可变LAI和降低的气孔导度的最详细处理之间,未来的流量和ET基本上是相同的。

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