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。水文模型可用于评估预期气候变化对融雪驱动的流域的影响，但受到数据有限的阻碍。 即使在仪器仪表齐全的盆地中，关于积雪变量的数据记录也太短，无法描述积雪、积雪深度和融雪的长期变化。年轮在水文学中的应用有着悠久的历史，为数据限制提供了解决方案。树木年轮特性，例如年轮宽度、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，能够提供此类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延续几个世纪到几千年。该项目是第一次专门为了研究融雪特性和积雪而组装和解释树木年轮网络的努力。 这项研究是沿着美国河进行的，美国河是加利福尼亚州的重要水源。 该研究的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化。对水文变量时空变化的科学认识将通过改进可持续水资源规划和流域管理实践使社会受益。该研究将包括实地采样、树木年轮的开发以及积雪相关变量的重建。 由此产生的数据将通过扩大可用的古气候数据网络来增强水文气候变化研究和教育的基础设施。该项目包括培养本科生和研究生以及一名博士后研究员。 此外，它还与利益相关者举行会议，以加深公众对科学的理解。 近几十年来不断变化的积雪和融雪状况给美国的水资源管理带来了越来越大的挑战。较早的融化和积累的减少与冬季和春季气温升高以及降水以雨而非雪的形式增加有关。许多盆地现有的观测网络不具备时空分辨率来充分表征与这些变化相关的参数的变化。具体而言，对于美国西部地区，人们对水文变量的年内和空间分布知之甚少，因为现有的山区实地观测资料稀缺且持续时间短。这项跨学科研究的假设是，内华达山脉的关键水文特征，如积雪特性、降水、土壤湿度和温度，可以利用树木年轮的年内特征来限制。此外，还可以识别季节性雪线演变等流域尺度特征以及干旱等极端事件特征。这项研究的新颖之处在于在发生后几天到几周内确定了关键的水文特征。该研究将探索在融雪驱动的流域中沿高程横断面使用多个树种和地点的年轮内特性，其目标是（a）改善对融雪过程重要的地表过程的表示和尺度复杂地形；(b) 开发一种方法来检测不断变化的积雪和土壤湿度的空间变化和季节性。 研究流域是美国河的北叉，流经加利福尼亚州内华达山脉的西侧。通过将密集的观测网络和最先进的陆地表面模型模拟相结合，将得出采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演变，并为描述各种积雪特征的空间变化的代理记录的开发提供依据。