Collaborative Research: Landform controls on hydrologic flowpaths and pedogenesis explain solute retention and export from pedon to catchment scales

水源集水区本身就很复杂。土壤，底土和地貌特性表现出不同尺度的异质性和流化学排水这些地区通常不同，从一个集水区到另一个在空间和时间。 然而，这些源头集水区构成了大部分景观，并负责在区域范围内设定水质。 该项目的目的是利用水文土壤学框架，即水文学和土壤发育的综合研究，解释在源头流域尺度上溪流水化学的时空变化。 该框架提供了一个功能的基础离散流域到类似的地区，可以集成到解释流域径流和水质。 与成土作用（土壤发育）相关的化学反应在从土壤到山坡的尺度上进行，记录了反映主要水文流径的地球化学特征，并调节排水山坡土壤序列的化学质量，最终确定流化学。 水在流向河流时，其化学性质沿着景观中的沿着流动路径演变的方式受到其所经过的土壤的强烈影响。 在哈伯德溪实验森林的一个小的源头集水区，四个子集水区，有对比流化学代表整个北方新英格兰森林溪流将进行研究，以研究如何不同的土壤发育模式可以用来解释在溪流中的溶质来源。 流动路径预测地形形状，底土类型（水文限制区）和土壤提取化学确定的土壤发育序列。 沿着这些途径，人工示踪剂实验，地球化学模式，和同位素地球化学示踪剂将被用来预测的模式和过程中产生的径流在每个子集水区，并形成整个集水区的综合响应的溶质运移。 该项目的总体目标是开发一个预测模型的地形控制水文流动路径和pedogensis解释溶质保留和出口从土壤到山坡集水规模。 该项目将展示水文学如何强烈影响土壤发育和土壤化学，并反过来控制水源集水区的河流水质。 了解水文学和土壤发育之间的联系，可以为管理森林和溪流水质提供宝贵的信息。 土壤和水文之间的反馈，导致可预测的土壤化学景观格局的影响，了解空间梯度的网站生产力和适合不同的栖息地要求或化学敏感性的物种。 需要工具来确定和预测这些梯度，最终可以为土地管理和造林决策提供指导。 土壤科学、水文学和土壤地球化学之间的更好整合将提供水文界所需的概念飞跃，以便能够更好地预测和解释河流水质的时空变化，并了解对河流流量有贡献的水源。

Headwater catchments are inherently complex. The soils, subsoils, and geomorphic properties exhibit heterogeneity at different scales and stream chemistry draining these areas typically varies from one catchment to another in space and time. Yet these headwater catchments comprise the majority of the landscape and are responsible for setting the quality of water at a regional scale. The project is aimed at explaining the spatial and temporal variation in stream water chemistry at the headwater catchment scale using a hydropedological framework, i.e. the combined study of hydrology and soil development. This framework provides a functional basis for discretizing the catchment into similar regions that can be integrated to explain catchment runoff and water quality. Chemical reactions related to pedogenesis (soil development) that operate at scales from the pedon to hillslope record the geochemical signature reflective of the dominant hydrologic flowpaths and regulate the chemical quality of water draining hillslope soil sequences, ultimately setting stream chemistry. The way water chemically evolves along flowpaths in the landscape as it travels to the stream is strongly influenced by the soils through which it passes. In a small headwater catchment at the Hubbard Brook Experimental Forest, four subcatchments that have contrasting stream chemistry representative of forested streams throughout northern New England will be studied to examine how distinct patterns of soil development can be used to interpret sources of solutes in stream water. Flow pathways are predicted from landform shape, subsoil type (hydrologic restriction zones) and soil development sequences determined by soil extraction chemistry. Along these pathways, artificial tracer experiments, geochemical patterns, and isotopic geochemical tracers will be used to predict the patterns and processes of solute transport that generates streamflow in each subcatchment and forms the integrated response of the entire catchment. The overall goal of the project is to develop a predictive model of landform control on hydrologic flowpaths and pedogensis that explains solute retention and export from pedon to hillslope to catchment scales. The project will demonstrate how hydrology strongly influences soil development and soil chemistry, and in turn, controls stream water quality in headwater catchments. Understanding the linkages between hydrology and soil development can provide valuable information for managing forests and stream water quality. Feedbacks between soils and hydrology that lead to predictable landscape patterns of soil chemistry have implications for understanding spatial gradients in site productivity and suitability for species with differing habitat requirements or chemical sensitivity. Tools are needed that identify and predict these gradients that can ultimately provide guidance for land management and silvicultural decision making. Better integration among soil science, hydrology, and biogeochemistry will provide the conceptual leap needed by the hydrologic community to be able to better predict and explain temporal and spatial variability of stream water quality and understand water sources contributing to streamflow.