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的变化给世界各地河流流域的水资源管理带来了挑战。水文模型对评估预期气候变化对融雪流域的影响很有用，但受到有限数据的阻碍。即使在仪器齐全的盆地，关于雪变量的数据记录也太短，无法描述积雪覆盖、积雪深度和积雪融化的长期变异性。树木年轮在水文学中有着悠久的应用历史，为解决数据限制提供了一种解决方案。年轮特性，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，能够提供这类数据的树木通常广泛分布在森林覆盖的分水岭上，它们提供的记录可以从几百年到几千年。这个项目是第一次努力汇编和解释专门用于研究融雪特性和积雪的树轮年表网络。这项研究正在沿着美国河进行，这条河是加利福尼亚州的重要水源。这项研究的一个目标是开发可转移的、普遍有用的研究工具，以更好地了解融雪过程及其在空间和时间上的变异性。通过改进可持续水资源规划和流域管理做法，科学地了解水文变量的时空变异性将使社会受益。这项研究将包括树木年轮年表的现场采样和开发，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，加强研究和教育水文气候变异性的基础设施。该项目包括对本科生和研究生以及一名博士后研究员的培训。此外，它还包括与利益攸关方的会议，以促进公众对科学的理解。近几十年来，积雪和融雪制度的变化给美国的水资源管理带来了越来越大的挑战。更早的融化和累积的减少与冬季和春季气温的上升以及越来越多的降水以雨而不是雪的形式下降有关。许多盆地的现有观测网络没有时空分辨率，无法充分描述与这些变化有关的参数的可变性。具体地说，对于美国西部，水文变量的年内和空间分布知之甚少，因为现有的山区现场观测很少，而且持续时间很短。这项跨学科研究的假设是，内华达山脉的关键水文特征，如积雪性质、降水、土壤水分和温度，可以利用树木年轮的年内特征来约束。此外，还可以确定流域尺度特征，如季节性雪线演变和干旱等极端事件的特征。这项研究的新颖性是在发生后的几天到几周内确定关键的水文特征。这项研究将探索利用多个树种和地点的年轮内特性，沿着积雪驱动的分水岭的高程样带，目标是(A)改善对复杂地形中的融雪过程至关重要的陆地表面过程的表示和尺度，以及(B)开发一种方法来检测积雪和土壤水分演变的空间变异性和季节性。研究盆地位于加利福尼亚州内华达山脉西侧的美洲河北支流。通过合并密集的观测网络和最先进的地表模型模拟，将得出采样地点的水文气象变量。水文变量和树轮指标之间的交叉关联将能够描述水文过程的季节演变，并提供描述各种积雪特征的空间变异性的替代记录。