Modeling the isotopic evolution of snowpack and snowmelt: Testing a spatially distributed parsimonious approach.
Modeling the isotopic evolution of snowpack and snowmelt: Testing a spatially distributed parsimonious approach.
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DOI：
10.1002/2017wr020650
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发表时间：
2017-07
影响因子：
5.4
通讯作者：
Soulsby C
中科院分区：
文献类型：
--
作者：
Ala-Aho P;Tetzlaff D;McNamara JP;Laudon H;Kormos P;Soulsby C
稳定水同位素的使用在使用示踪剂辅助建模量化水文系统中的水流路径和旅行时间方面越来越受欢迎。在受雪影响的集水区，融雪产生可追踪的同位素信号，由于积雪中的同位素分馏，该信号与原始降雪同位素组成不同。雪中的这些分馏过程相对较好地理解，但在示踪剂辅助研究中表现其时空变异性仍然是一个挑战。我们提出了一种新的，简约的建模方法来解释积雪同位素分馏和估计同位素比在融雪水在一个完全空间分布的方式。我们的模型引入了两个校准参数，单独占的同位素分馏所造成的升华从拦截和地面积雪储存，和融雪分馏逐步丰富的融雪径流。同位素程序链接到一个通用的过程为基础的积雪拦截-积累-融化模型，便于模拟空间分布的融雪径流。我们使用一个合成的建模实验，以证明在不同的景观位置和不同的冠层特征下的模型算法的功能。我们还提供了一个概念验证模型测试，并成功地再现了在两个长期实验集水区与对比冬季条件下，用融雪蒸渗仪采样的融雪径流中的同位素比率。据我们所知，该方法是第一个这样的工具，允许估计空间分布的性质，在积雪和由此产生的同位素比在融雪径流同位素分馏。因此，该方法可以为示踪剂辅助建模提供一个有用的工具，以更好地了解雪影响的集水区的流动，混合和传输过程的综合性质。我们提出了一种新的积雪同位素分馏建模方法，以估计融雪中同位素比的时空变化我们的简约模型使用两个校准参数，单独考虑雪升华和融化引起的同位素分馏我们提供了一个建模实验来证明模型的功能和使用融雪同位素数据的概念验证比较。
Use of stable water isotopes has become increasingly popular in quantifying water flow paths and travel times in hydrological systems using tracer‐aided modeling. In snow‐influenced catchments, snowmelt produces a traceable isotopic signal, which differs from original snowfall isotopic composition because of isotopic fractionation in the snowpack. These fractionation processes in snow are relatively well understood, but representing their spatiotemporal variability in tracer‐aided studies remains a challenge. We present a novel, parsimonious modeling method to account for the snowpack isotope fractionation and estimate isotope ratios in snowmelt water in a fully spatially distributed manner. Our model introduces two calibration parameters that alone account for the isotopic fractionation caused by sublimation from interception and ground snow storage, and snowmelt fractionation progressively enriching the snowmelt runoff. The isotope routines are linked to a generic process‐based snow interception‐accumulation‐melt model facilitating simulation of spatially distributed snowmelt runoff. We use a synthetic modeling experiment to demonstrate the functionality of the model algorithms in different landscape locations and under different canopy characteristics. We also provide a proof‐of‐concept model test and successfully reproduce isotopic ratios in snowmelt runoff sampled with snowmelt lysimeters in two long‐term experimental catchment with contrasting winter conditions. To our knowledge, the method is the first such tool to allow estimation of the spatially distributed nature of isotopic fractionation in snowpacks and the resulting isotope ratios in snowmelt runoff. The method can thus provide a useful tool for tracer‐aided modeling to better understand the integrated nature of flow, mixing, and transport processes in snow‐influenced catchments. We present a novel modeling method for snowpack isotope fractionation to estimate spatiotemporal variability of isotope ratios in snowmelt Our parsimonious model uses two calibration parameters that alone account for the isotopic fractionation caused by snow sublimation and melt We provide a modeling experiment to demonstrate the model functionality and a proof‐of‐concept comparison using snowmelt isotope data