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.

与气候变率相关的融雪模式变化对世界各地河流流域的水资源管理构成挑战。水文模型对于评估预期气候变率对融雪驱动的流域的影响是有用的，但受到有限数据的阻碍。即使在仪器完备的流域，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的应用历史悠久，解决了数据的局限性。树木年轮特性，如年轮宽度、木材密度和细胞解剖结构，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流域，它们提供的记录可以从几个世纪到几千年不等。这个项目是第一个专门为研究融雪特性和积雪而组装和解释树木年轮年表网络的项目。这项研究是沿着美国河进行的，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、通常有用的研究工具，以便更好地了解融雪过程及其在空间和时间上的变异性。对水文变量时空变异性的科学认识将通过改善可持续水资源规划和流域管理实践造福社会。这项研究将包括实地取样和发展树木年轮年表以及重建与积雪有关的变量。由此产生的数据将通过扩大现有的古气候数据网络，加强水文气候变率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，它还包括与利益相关者的会议，以促进公众对科学的理解。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。融冰的提前和积雪的减少与冬季和春季气温的升高以及降水中以雨代替雪的比例的增加有关。许多流域现有的观测网络不具备充分表征与这些变化相关的参数变率的时空分辨率。具体而言，对于美国西部，由于山区现有的原位观测很少且持续时间短，因此对水文变量的年际和空间分布知之甚少。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和干旱等极端事件特征。这项研究的新颖之处在于在发生的几天到几周内确定关键的水文特征。该研究将探索在融雪驱动的流域沿高程样带的多种树种和地点的树木年轮的环内特性，目的是：(a)改善复杂地形中对融雪过程重要的地表过程的表征和尺度，(b)开发一种检测积雪和土壤水分演变的空间变异性和季节性的方法。研究的盆地是美国河的北福克，这条河流经加州内华达山脉的西侧。通过合并密集的观测网络和最先进的陆地表面模式模拟，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有助于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代理记录的发展。