CAREER: Advancing the Mechanistic Understanding of Field-Scale Preferential Flow and Transport Processes in Soils using Geophysics
CAREER: Advancing the Mechanistic Understanding of Field-Scale Preferential Flow and Transport Processes in Soils using Geophysics
批准号:
1151294
负责人:
Stephen Moysey
金额:
$41.33万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-05-01 至 2018-04-30
中文摘要
职业:利用地球物理学推进对土壤中的场尺度优先流和输送过程的机理理解优先流和输送过程使水和污染物在不同的流动路径中被隔离,这些流动路径可以绕过大部分土壤。 尽管这种现象的普遍发生和地下水和溶质运动的基本控制,有几个工具可用于调查的机制,导致优先流在现场规模。 因此,有一个知识的差距,不同的机制之间的相互作用,导致优先流可以改变观察到的流动行为,特别是土壤和降雨条件经历了一年四季的变化。 该项目将通过测试以下假设来解决知识差距:(1)由于季节性依赖于前期含水量和水文强迫,控制全年优先流和运输转变的机制,以及(2)探地雷达(GPR)和电阻率数据可用于检测优先流行为并区分这些观察结果的机械原因。 本研究将通过在两个大型(32 m3体积)水文地球物理网格蒸渗仪在不同含水量和降雨特性下进行瞬态入渗和稳态示踪试验来进行。 每个蒸渗仪的底面设计用于收集从1m x 1m流出单元格网格中排放的水和溶质。 其中一个蒸渗仪将在实验室中建造,并填充有代表优先流条件的合成土壤异质性。 这种蒸渗仪的设计将允许主动优先流机制的基础上的流出模式的评价。 第二个蒸渗仪将位于克莱姆森实验森林的山坡上。 该蒸渗仪将代表自然土壤条件,并捕捉前期含水量变化和降雨特征变化的季节性影响。 在每次实验中,将使用延时三维探地雷达勘测和电阻率测量对蒸渗仪进行连续监测。 将使用数据简化技术分析蒸渗仪实验的水文和地球物理数据,以便对每组控制变量的结果进行定量比较。 因此,该项目将提供独特的,定量的见解如何瞬态优先流和运输过程的细节演变,以应对不断变化的环境条件。 了解优先流过程对社会至关重要,因为它影响流域的许多关键问题,包括洪水,污染物的命运和运输,农业,基础设施稳定性和生态系统健康。 例如,据估计,优先水流过程对生态系统服务的贡献价值每年超过3,040亿美元。 新的地球物理成像技术与渗透和运输研究的整合将提供独特的见解优先流在现场规模的动态?包括更好地理解对这些过程的季节性控制。 有一个迫切需要了解这些基本过程,使预测和明智的适应变化的流域行为的气候变化引起扰动,在传统的土壤行为。 在这项研究中获得的高分辨率数据将允许测试和完善现有的概念模型,在不同的水文条件下,在土壤中代表优先流。 该项目的教育方面将有助于介绍和准备新一代的水文学家?从中学女生到职场人士从越来越多的海量可用数据中提取信息,这些数据从水文资料库到高分辨率地球物理图像。 具体的教育活动包括本科生通过克莱姆森的创造性探究教学法参与该项目,这是一个关于水资源的实践教育模块,将通过克莱姆森向八年级女生提供。WISE项目夏令营,以及为专业人员举办的年度继续教育讲习班,以提高对水文地球物理应用的认识和理解。 在所有这三项活动中,将强调使用新一代的方法来感知环境和挖掘大型数据集,以促进我们对真实的实地水文过程的基本了解。
英文摘要
CAREER: ADVANCING THE MECHANISTIC UNDERSTANDING OF FIELD-SCALE PREFERENTIAL FLOW AND TRANSPORT PROCESSES IN SOILS USING GEOPHYSICSStephen MoyseyClemson UniversityPreferential flow and transport processes cause water and contaminants to be isolated within distinct flow paths that can by-pass a large portion of a soil. Despite the universal occurrence of this phenomenon and its fundamental control on water and solute movement in the subsurface, there are few tools available to investigate the mechanisms leading to preferential flow at the field scale. As a result, there is a gap in knowledge regarding how interactions between different mechanisms causing preferential flow can alter observed flow behaviors, particularly as soil and rainfall conditions undergo seasonal changes throughout the year. This project will address the knowledge gap by testing the hypotheses that: (1) mechanisms controlling preferential flow and transport shift throughout the year due to seasonal dependence on antecedent water content and hydrologic forcing, and (2) ground penetrating radar (GPR) and electrical resistivity data can be used to detect preferential flow behaviors and discriminate the mechanistic causes of these observations. This research will be carried out by performing transient infiltration and steady-state tracer tests in two large (32m3 volume) hydrogeophysical grid lysimeters under different water content and rainfall characteristics. The bottom face of each lysimeter is designed to collect distributed discharge of water and solutes from a grid of 1m x 1m outflow cells. One of the lysimeters will be constructed in the lab and filled with synthetic soil heterogeneities representative of conditions causing preferential flow. The design of this lysimeter will allow for evaluation of active preferential flow mechanisms based on patterns of the outflows. The second lysimeter will be located on a hillslope in the Clemson Experimental Forest. This lysimeter will represent natural soil conditions and capture seasonal effects of changing antecedent water content and variable rainfall characteristics. In each experiment, the lysimeters will be continuously monitored using time-lapse 3D GPR surveys and electrical resistivity measurements. The hydrologic and geophysical data from the lysimeter experiments will be analyzed using data reduction techniques that allow for quantitative comparison of the results for each set of control variables. As a result, the project will provide unique, quantitative insights into how the details of transient preferential flow and transport processes evolve in response to changing environmental conditions. Understanding preferential flow processes is of fundamental importance to society as it affects many critical issues in watersheds, including flooding, contaminant fate and transport, agriculture, infrastructure stability, and ecosystem health. For example, the contribution of preferential flow processes to ecosystem services to be worth is estimated to be over US$304 billion per year. The integration of novel geophysical imaging techniques with infiltration and transport studies will provide unique insights into the dynamics of preferential flow at the field scale ? including an improved understanding of seasonal controls on these processes. There is an urgent need for understanding these basic processes to enable prediction and informed adaptation to shifts in watershed behavior as climate change causes perturbations in traditional soil behaviors. The high-resolution data obtained in this study will allow for testing and refinement of existing conceptual models for representing preferential flow in soils under varying hydrologic conditions. The educational aspects of this project will help to introduce and prepare a new generation of hydrologists ? spanning middle school girls to working professionals ? to extract information from an increasingly overwhelming mass of available data that ranges from hydrologic repositories to high-resolution geophysical images. Specific educational activities include the involvement of undergraduate students in the project through the Creative Inquiry pedagogy at Clemson, a hands-on educational module on water resources to be delivered to eighth grade girls through Clemson?s Project WISE summer camp, and an annual continuing education workshop for professionals to increase the awareness and understanding of geophysical applications in hydrology. In all three of these activities, there will be an emphasis on using a new generation of methods for sensing the environment and mining of large data sets to advance our fundamental understanding of hydrologic processes at real field sites.
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