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.

与气候变化相关的融雪模式改变了世界各地河流盆地的水资源管理挑战。水文模型可用于评估预期气候变异性对融雪驱动的流域的影响，但受到有限数据的阻碍。 即使在受启发的盆地数据记录中，雪变量的数据记录也太短了，无法描述雪覆盖，雪深和融雪的长期变化。树环在水文学中有悠久的应用历史，为数据限制提供了解决方案。树环特性，例如环宽，木质密度和细胞的解剖结构，对水文变量的变化敏感。此外，可以提供此类数据的树木通常在森林流域广泛分布，并且它们提供的记录可以从几个世纪延长到数千年。该项目是组装和解释树环时间表网络的首次努力，专门为研究融雪的特性和积雪而言。 这项研究是在美国河上进行的，这是加利福尼亚州的供水的重要来源。 该研究的目的是开发可转让的，通常有用的研究工具，以更好地理解融雪过程及其在时空上的变化。对水文变量的时空变异性的科学理解将通过改善可持续水资源规划和流域管理实践来使社会受益。该研究将包括田间抽样和开发树环的时间表以及与积雪相关变量的重建。 最终的数据将通过扩展可用的古气候数据网络来增强有关氢化气候变异性研究和教育的基础架构。该项目包括对本科和研究生的培训以及博士后研究员。 此外，它结合了与利益相关者的会议，以进一步公众对科学的理解。 近几十年来，变化积雪和融化政权对美国水资源管理构成了越来越多的挑战。较早的融化和积累的减少与冬季和春季温度的升高以及降水量增加的降雨而不是降雪有关。许多盆地中现有的观察网络没有时空分辨率，无法充分表征与这些变化相关的参数的可变性。具体而言，对于美国西部来说，水文变量的年度和空间分布知之甚少，因为山区现有的现场观察值很少，而且持续时间很短。这项跨学科研究的假设是，可以使用树环的年度特征来限制内华达山脉的关键水文特征，例如雪包性能，降水，土壤水分和温度。此外，可以确定盆地规模的特征，例如季节性的雪线演化和极端事件（例如干旱）的特征。这项研究的新颖性是在发生的几天到几周内识别关键水文特征。该研究将探索从多个树种和融雪式驱动的分水岭沿高程样品的树环内部特性的使用，其目标是（a）（a）改善对复杂地形中雪线过程至关重要的土地表面过程的代表和缩放，以及（b）检测一种空间可变性和季节性的方法，以供不应求的是降雪和季节性的烟雾和土壤。 研究盆地是美国河的北叉，该河流排在加利福尼亚州内华达山脉的西侧。通过合并密集的观察网络和最先进的土地表面模型仿真，将为采样位置得出水文学变量。水文变量和树环指示器之间的交叉关联将能够描述水文过程的季节性演变，并提供了描述各种雪包特征空间可变性的代理记录的发展。