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、底土和地貌特征在不同尺度上表现出异质性，排水这些地区的河流化学通常在空间和时间上因流域而异。然而，这些水源集水区构成了大部分景观，并负责在区域范围内设定水质。该项目旨在利用水文学框架，即水文和土壤发展的结合研究，解释水源集水区尺度上河流水化学的时空变化。这个框架提供了一个功能基础，可以将集水区离散到类似的区域，这些区域可以整合起来解释集水区径流和水质。与土壤形成（土壤发育）相关的化学反应在从土盆到山坡的尺度上进行，记录了反映主要水文流道的地球化学特征，并调节了排水山坡土壤序列的化学质量，最终确定了河流化学。水在流经河流的过程中，沿着景观中的水流路径进行化学演变的方式受到它所经过的土壤的强烈影响。在哈伯德溪实验森林的一个小水源集水区，将研究四个具有鲜明对比的河流化学的子集水区，这些集水区代表了整个新英格兰北部的森林溪流，以研究如何利用土壤发育的不同模式来解释溪流中溶质的来源。根据地形形状、底土类型（水文限制带）和土壤提取化学决定的土壤发育序列来预测水流路径。沿着这些路径，将使用人工示踪剂实验、地球化学模式和同位素地球化学示踪剂来预测溶质运输的模式和过程，这些模式和过程在每个子集水区产生流，并形成整个集水区的综合响应。该项目的总体目标是建立一个水文流动路径和土壤形成的地形控制预测模型，以解释溶质的保留和从土壤到山坡到集水区的出口。该项目将展示水文学如何强烈影响土壤发育和土壤化学，进而控制水源集水区的水质。了解水文学和土壤发展之间的联系可以为管理森林和溪流水质提供有价值的信息。土壤和水文之间的反馈导致可预测的土壤化学景观格局，这对理解不同生境要求或化学敏感性的物种在场地生产力和适宜性方面的空间梯度具有重要意义。需要识别和预测这些梯度的工具，以便最终为土地管理和造林决策提供指导。土壤科学、水文学和生物地球化学之间更好的整合将为水文学界提供所需的概念飞跃，以便能够更好地预测和解释河流水质的时空变异性，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.