Collaborative Research: Interannual and seasonal variability of snowpack in the Sierra Nevada from tree rings.

合作研究：内华达山脉树木年轮积雪的年际和季节变化。

• 批准号: 1445895
• 负责人: David Meko
• 金额: $ 35.49万
• 依托单位: University of Arizona
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-05-01 至 2020-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1445895&HistoricalAwards=false
• 关键词: Collaborative; Research; Interannual; seasonal; variability

Changing snowmelt patterns associated with climate variability pose challenges to water resources management in river basins around the world. Hydrologic models are useful to assess impacts of expected climate variability on snowmelt-driven watersheds, but are hampered by limited data. Even in well-instrumented basins data records on snow variables are too short to describe the long-term variability of snow cover, snow depth, and snowmelt. Tree rings, with a long history of application in hydrology, offer a solution to the data limitations. Tree-ring properties, such as ring-width, wood density, and the anatomical structure of cells, are sensitive to changes in hydrologic variables. Moreover trees that can provide such data are often widely distributed over forested watersheds, and the records they provide can extend from centuries to millennia. This project is the first effort at assembling and interpreting a network of tree-ring chronologies specifically for the purpose of studying snowmelt properties and snowpack. The research is being conducted along the American River, a vital source of water supply to the State of California. A goal of the research is to develop transferrable, generally useful, research tools for better understanding of snowmelt processes and their variability in space and time. The scientific understanding of the spatiotemporal variability of the hydrologic variables will benefit society through improvements in sustainable water resources planning and watershed management practices. The research will include field sampling and development of tree-ring chronologies and reconstructions of snowpack-related variables. Resulting data will enhance the infrastructure for research and education on hydroclimatic variability by expanding the available palaeoclimatic data networks. The project includes training of undergraduate and graduate students and a post-doctoral researcher. In addition, it incorporates meetings with stakeholders to further the public understanding of science. Changing snow-accumulation and snowmelt regimes in recent decades pose an increasing challenge to water resources management in the United States. Earlier melt and decreases in accumulation have been linked to both increasing winter and spring temperatures and an increasing fraction of precipitation falling as rain instead of snow. The existing observational networks in many basins do not have the spatiotemporal resolution to adequately characterize the variability of parameters relevant to these changes. Specifically, for the western USA, the intra-annual and spatial distribution of hydrological variables is poorly understood, as existing in-situ observations in the mountains are scarce and of short duration. The hypothesis of this interdisciplinary research is that key hydrological characteristics of the Sierra Nevada such as snow pack properties, precipitation, soil moisture and temperature can be constrained using the intra-annual features of tree rings. In addition, basin scale characteristics such as seasonal snow-line evolution and features of extreme events such as droughts can be identified. The novelty of this research is identification of key hydrological characteristics within a few days to weeks of occurrence. The research will explore the use of intra-ring properties of tree rings from multiple tree species and sites along an elevation transect in a snowmelt-driven watershed with goals of (a) improving the representation and scaling of land surface processes important to snowmelt processes in complex terrain, and (b) developing a method to detect the spatial variability and seasonality of evolving snowpack and soil moisture. The study basin is the North Fork of the American River, which drains the western side of the Sierra Nevada Mountains, California. Hydrometeorological variables will be derived for the sampling locations by merging a dense observational network and state-of-the-art land-surface model simulations. The cross association among hydrological variables and tree ring indicators will enable a description of the seasonal evolution of hydrological processes and provide for the development of proxy records that describe the spatial variability of various snow pack features.

与气候多变性相关的融雪模式不断变化，给世界各地河流流域的水资源管理带来了挑战。水文模型有助于评估预期气候变异对融雪流域的影响，但受到数据有限的阻碍。 即使是在装备良好的流域，关于雪变量的数据记录也太短，无法描述积雪、雪深和融雪的长期变化。树木年轮在水文学中有着悠久的应用历史，为解决数据局限性提供了一种解决方案。树木年轮的特性，如年轮宽度、木材密度和细胞的解剖结构，对水文变量的变化很敏感。此外，能够提供这种数据的树木通常广泛分布在森林覆盖的流域，它们提供的记录可以从几个世纪延续到几千年。这个项目是第一次努力组装和解释一个网络的树轮年表，专门用于研究融雪性能和积雪。 这项研究是在沿着美国河进行的，美国河是加州州的重要水源。 研究的一个目标是开发可转移的，一般有用的，研究工具，更好地了解融雪过程及其在空间和时间上的变化。对水文变量的时空变异性的科学理解将通过改进可持续水资源规划和流域管理做法而造福社会。这项研究将包括实地取样和树木年轮年表的编制以及与积雪有关的变量的重建。 由此产生的数据将通过扩大现有的古气候数据网络，加强水文气候变异性研究和教育的基础设施。该项目包括培训本科生和研究生以及一名博士后研究员。 此外，它还包括与利益攸关方举行会议，以增进公众对科学的了解。 近几十年来不断变化的积雪和融雪制度对美国的水资源管理构成了越来越大的挑战。更早的融化和积累的减少与冬季和春季温度的升高以及越来越多的降水以雨而不是雪的形式下降有关。许多流域现有的观测网络没有时空分辨率，无法充分说明与这些变化有关的参数的可变性。具体而言，对于美国西部，水文变量的年内和空间分布知之甚少，现有的原位观测在山区是稀缺的，持续时间短。这项跨学科研究的假设是，内华达州的主要水文特征，如积雪特性，降水，土壤水分和温度可以限制使用年内特征的树木年轮。此外，还可以确定流域尺度的特征，如季节性雪线演变和干旱等极端事件的特征。这项研究的新奇是在几天到几周的时间内确定关键的水文特征。该研究将探讨使用年轮内属性的多个树种和网站沿着海拔样带在融雪驱动的流域与目标（a）改善的代表性和缩放的土地表面过程的重要性融雪过程在复杂的地形，（B）开发一种方法来检测不断变化的积雪和土壤水分的空间变异性和季节性。 研究流域是美国河的北支流，流经加州的内华达州山脉西侧。将通过合并一个密集的观测网络和最先进的陆面模型模拟，得出取样地点的水文气象变量。水文变量和树木年轮指标之间的交叉关联将能够描述水文过程的季节性演变，并提供替代记录的发展，描述各种积雪特征的空间变异性。