Doctoral Dissertation Research: Streamwood Flux from Forested Mountain Watersheds Into Reservoirs in the Sierra Nevada, California

森林覆盖的山区流域占Streamwood流入和通过河道的很大比例，Streamwood的定义是长度超过1米、直径超过10厘米的活木材或死木材。Streamwood“预算”最近被提议追踪Streamwood的运动和河道外的运动，但几乎没有完成，因为除了最小的流域外，所有流域的实地工作都很复杂。一个很少被衡量的预算组成部分是出口变量。然而，堤坝阻碍了Streamwood从上游流域的移动，导致了沉积带，在那里可以进行特征描述。这项博士论文研究项目将使用遥感图像分析、视频监控和实地研究来确定Streamwood与水文、地貌和陆地机制之间在多个时空尺度上的潜在联系。这位博士生将分析与内华达山脉的两个加州水库有关的Streamwood聚集体：北福克尤巴河上的布拉德酒吧和图奥勒米河上的唐·佩德罗。将使用遥感软件方法分析从1982年到现在的多光谱30米分辨率的陆地卫星图像。验证将使用存档的1米分辨率数字正射影像四边形(DOQ)和国家农业影像计划(NAIP)图像，并通过当前几年的实地观测进行。将在研究水库的顶部安装数字视频监控，以记录Streamwood在季节性水文线上的运输量和速度，包括基流、冬季降水和积雪融化，以及如果发生雨雪洪水。实地调查将用于描述水库Streamwood和上游流域储存和分解过程的特征，这将大致解释简化Streamwood预算的投入(补充)部分(投入=出口+储存+分解)。将使用地理信息系统分析来了解流木产量和物理过程之间的关系，预期结果包括日、季、年和十年尺度的平均流材出口；流量-流木产量等级曲线；流木补充和储存潜力；流材流量-大坝流出、运输距离-流木属和腐烂分类-流木密度之间的回归关系。该项目将填补基本了解森林碳循环中重要的颗粒物有机组成部分-流木出口的区域变化的时空空白。了解Streamwood出口将有助于深入了解通过分水岭驱动Streamwood生产和运输的物理机制。新的方法可能会促进将Streamwood出口到其他地区水库的量化，这将导致对这一重要的生态和地貌河流组成部分的更深入了解。水库管理人员将提高根据流量和已知流域特征预测Streamwood出口的能力。增加到坝下生态系统恢复项目的Streamwood材积的科学建议可能会从根本上改变水库和河流的管理做法。作为博士论文研究改进奖，该奖项还将提供支持，使有前途的学生建立一个强大的独立研究生涯。

Forested mountain watersheds account for a large percentage of streamwood movements into and through river channels, with streamwood defined as live or dead wood greater than 1 m in length and greater than 10 cm in diameter. Streamwood "budgets" recently have been proposed to trace the movement of streamwood and in out of river channels, but few have been completed because of the complexity of field work in all but the smallest watersheds. One budget component that rarely has been measured is the export variable. Dams impede streamwood movement from upper watersheds, however, resulting in depositional zones where characterization can occur. This doctoral dissertation research project will use remotely sensed imagery analysis, video monitoring, and field studies to identify underlying linkages between streamwood and hydrologic, geomorphic, and terrestrial mechanisms at multiple spatial-temporal scales. The doctoral student will analyze streamwood aggregations associated with two California reservoirs in the Sierra Nevada: Bullard's Bar on the North Fork Yuba River and Don Pedro on the Tuolumne River. Remote sensing software methods will be used to analyze multispectral 30-m resolution Landsat images from 1982 to the present. Validations will be performed with archival 1-m resolution digital orthophoto quadrangle (DOQ) and National Agriculture Imagery Program (NAIP) images, and via field observations for current years. Digital video monitoring will be installed at the top of the study reservoirs to document streamwood transport volume and velocity across seasonal hydrographs, including baseflow, winter precipitation, and snow melt as well as rain-on-snow floods if they occur. Fieldwork will be used to characterize reservoir streamwood and upper watershed storage and decomposition processes, which will broadly explain the input (recruitment) component of a simplified streamwood budget (Inputs = Exports + Storage + Decomposition). GIS analyses will be used to understand the relationship between streamwood yield and physical processes, with expected results to include average streamwood export at daily, seasonal, yearly, and decadal scales; discharge-streamwood yield rating curves; streamwood recruitment and storage potentials; and regression relationships between streamwood discharge-dam outflow, transport distance-streamwood genera and decay classification-streamwood density.This project will fill spatial and temporal gaps in basic understanding regional variation of an important particulate organic component of the forest carbon cycle, streamwood export. Understanding streamwood export will provide insight into physical mechanisms that drive streamwood production and transport through a watershed. New methods may prompt quantification of streamwood export into reservoirs in other locales, which would lead to a deeper understanding of this important ecological and geomorphic river component. Reservoir mangers will have increased ability to predict streamwood export based on discharge and known watershed characteristics. Scientifically based recommendations of streamwood volume to be added to ecosystem rehabilitation projects below-dam could fundamentally alter reservoir and river management practices. As a Doctoral Dissertation Research Improvement award, this award also will provide support to enable a promising student to establish a strong independent research career.