Collaborative Research: Investigating Timescales of Hydrologic Transport in Catchments Using Natural Tracer Time Series, Theoretical Models, and Laboratory-Scale Simulations

合作研究：利用自然示踪时间序列、理论模型和实验室规模模拟研究流域水文输送的时间尺度

• 批准号: 0125550
• 负责人: James Kirchner
• 金额: --
• 依托单位: University of California-Berkeley
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-03-01 至 2008-02-29
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0125550&HistoricalAwards=false
• 关键词: Collaborative; Research; Investigating; Timescales; Hydrologic

.0125550Kirchner The travel time of water through a catchment -- that is, the time it takes for rainfall to reach the stream -- is a fundamental hydraulic parameter controlling the persistence of soluble contaminants, and thus the downstream consequences of pollution episodes. A catchment is characterized by a distribution of travel times, reflecting the diverse flow paths that rainfall can take to the stream. Thus, quantifying catchments' travel time distributions should help to clarify the hydrologic mechanisms controlling flow routing in the subsurface. Understanding the timescales of transport and storage in catchments is also important for predicting how rainfall inputs will be chemically modified by reactions with catchment soils and bedrock. But despite the importance of catchment travel time distributions for watershed hydrology and geochemistry, they have rarely been quantified and the mechanisms controlling them are poorly understood. Catchment travel time distributions can be inferred from long-term time series of inert tracers, such as chloride, in rainfall and streamflow. It has recently been shown that catchment travel-time distributions can have unexpectedly long "tails", implying that they can retain soluble contaminants for much longer than would otherwise be expected [Kirchner, Feng, and Neal, Fractal stream chemistry and its implications for contaminant transport in catchments, Nature, 403, 524-527, 2000]. The proposed research program builds on this recent work, and has four main components:a) analyses of long-term time series of rainfall and streamflow concentrations of chloride (a naturally occurring nonreactive tracer) from humid forested catchments in diverse geological settings, using spectral, autocorrelation, and cross-correlation methods to infer each catchment's characteristic travel time distribution,b) development and testing of alternative conceptual models for the observed travel-time distributions, c) construction of laboratory-scale physical models to simulate the hypothesized mechanisms underlying these conceptual models, andd) analyses of reactive tracer data, to complement the passive tracer (chloride) studies. This integrated program of data analysis, conceptual modeling, and laboratory-scale physical models is designed to clarify the mechanisms that control catchment-scale transport, storage, and mixing of waters and their associated solutes. This project is expected to lead to:a) improved understanding of catchment flowpaths and travel time distributions, and the factors controlling them,b) improved understanding of how catchment flowpaths, and reactions between aqueous and solid phases, affect the mobility of reactive solutes at catchment scale,c) improved tools for using hydrologic and geochemical time series to probe the internal workings of catchments, andd) improved methods for testing catchment flow and routing models through comparisons with field data.

.0125550基什内尔水通过集水区的旅行时间-即降雨到达河流所需的时间-是控制可溶性污染物持续存在的基本水力参数，因此污染事件的下游后果。 集水区的特征是旅行时间的分布，反映了降雨进入溪流的不同流动路径。 因此，量化集水区的行程时间分布应有助于澄清水文机制控制流量路由在地下。 了解集水区的运输和储存时间尺度对于预测降雨输入如何通过与集水区土壤和基岩的反应而发生化学变化也很重要。 但是，尽管流域的水文和地球化学的重要性，流域旅行时间分布，他们很少被量化和控制它们的机制知之甚少。 集水区旅行时间分布可以从降雨和径流中惰性示踪剂（例如氯化物）的长期时间序列来推断。 最近的研究表明，集水区的传播时间分布可能会有意想不到的长“尾巴”，这意味着它们可以保留可溶性污染物的时间比预期的要长得多[Kirchner，Feng和Neal，Fractal stream chemistry and its implications for contaminant transfer in catchments，Nature，403，524-527，2000]。 拟议的研究计划建立在最近的工作基础上，有四个主要组成部分：a）分析降雨和水流中氯化物浓度的长期时间序列（一种天然存在的非反应性示踪剂），使用光谱、自相关和互相关方法来推断每个集水区的特征走时分布，B）为观察到的走时分布开发和测试替代概念模型，c）构建实验室规模的物理模型来模拟这些概念模型的假设机制，以及d）分析反应性示踪剂数据，以补充被动示踪剂（氯化物）研究。这个数据分析，概念建模和实验室规模的物理模型的综合方案的目的是澄清的机制，控制流域规模的运输，存储和混合的沃茨和它们相关的溶质。 该项目预计将导致：a）更好地了解汇水流动路径和旅行时间分布，以及控制它们的因素，B）更好地了解汇水流动路径，以及水相和固相之间的反应如何影响汇水规模的活性溶质的流动性，c）改进使用水文和地球化学时间序列探测汇水内部运作的工具，以及d）通过与现场数据的比较改进测试汇水流量和路由模型的方法。