Discovering Preferential Flow Patterns Using Real-time Soil Moisture Monitoring Networks

优先流（PF）是一种重要的水文过程，它影响着各种地球表面过程（如径流、侵蚀、养分循环、地球化学动力学、生态功能、生物活动、气体排放和污染物归宿）。然而，PF量化和预测仍然是众所周知的难以捉摸。该项目旨在通过推进两个重要方面来突破这一瓶颈：1）检测和量化不同土壤景观中PF的实用方法，以及2）嵌入土壤景观镶嵌图中的动态PF网络的新概念。研究人员假设，虽然PF在现实世界土壤中存在的可能性是普遍存在的，但PF实际发生需要土壤和环境的正确组合。PF发生的控制可以分为场地因素（例如，地形单元和土壤类型）和时间因素（例如，初始土壤湿度、降水特征和植物生长阶段）。他们进一步假设，一个动态的PF流网络嵌入在地下类似（在某种程度上）一个短暂的流状网络，这是由一个双流制度。研究人员将使用大型实时土壤水分监测数据库来调查不同土壤景观中PF发生的条件，时间，频率和机制。将系统分析高密度和多深度土壤水分数据集，以确定土壤水分对降水事件的响应特征，并确定各种流动情景和相关机制。开发了一套有效和一致地分析土壤水分时间序列剖面的工具，包括PF和相关控制的确定和可视化。该项目解决了水文科学中的一个重大挑战，即，发展基本的水文原理和工具，以进一步了解通过不规则和相互关联的世界的流动和运输过程。由于水文学经常触发“热点”和“热点时刻”的生态地球化学反应和生态功能，提高检测和定量的PF也有相当大的影响，加强确定化学通量和生态系统功能。该项目将向科学界免费提供已完成的数据库和开发的工具箱。还将开发一个教育计算机程序，以激发学生和公众对复杂地下过程的兴趣和欣赏。研究生和本科生教育将是这个项目的一个组成部分。在AGU和AAAS年会上将组织一次关于优先流和基本水文学的小组讨论，并将举行一次关于该项目成果的公开网络研讨会。

Preferential flow (PF) is a fundamentally important hydrologic process that influences a variety of earth surficial processes (such as runoff, erosion, nutrient cycling, biogeochemical dynamics, ecological functions, biological activities, gas emission, and contaminant fate). However, PF quantification and prediction remain notoriously elusive. This project seeks to break through this bottleneck by advancing two important fronts: 1) A practical means of detecting and quantifying PF across diverse soil-landscapes, and 2) A new conceptualization of dynamic PF networks embedded in the soil-landscape mosaic. The investigators hypothesize that, while the potential for PF to occur in real-world soils is ubiquitous, it takes the right combination of soils and environments for PF to actually happen. The controls of PF occurrence can be grouped into site factors (e.g., landform unit and soil type) and temporal factors (e.g., initial soil moisture, precipitation characteristics, and plant growth stage). They further hypothesize that a dynamic PF flow network embedded in the subsurface resembles (to some extent) an ephemeral stream-like network, which is governed by a dual-flow regime. The investigators will use large real-time soil moisture monitoring databases to investigate the condition, timing, frequency, and mechanism of PF occurrence in diverse soil-landscapes. High-density and multiple depth soil moisture datasets will be systematically analyzed to identify soil moisture response signatures to precipitation events and to identify various flow scenarios and related mechanisms. A set of tools has been developed to efficiently and consistently analyze soil moisture time series profiles, including the determination and visualization of PF and related controls.This project addresses a grand challenge in hydrologic sciences, i.e., to develop basic hydrologic principles and tools to further understand flow and transport processes through an irregular and interconnected world. Since hydrology often triggers 'hot spots' and 'hot moments' of biogeochemical reactions and ecological functions, improved detection and quantification of PF also have considerable implications for enhanced determination of chemical fluxes and ecosystem functions. This project will make the completed databases and the toolbox developed freely available to the scientific community. An educational computer program will also be developed to spark interest and appreciation of complex subsurface processes among students and the general public. Graduate and undergraduate education will be an integral part of this project. A panel discussion on Preferential Flow and Fundamental Hydrology will be organized at the AGU and the AAAS annual meetings, and a public webinar on this project's outcomes will also be given.