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Predicting sedimentary bedrock subsurface weathering fronts and weathering rates: Dataset

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DataONE2022-08-10 更新2024-06-08 收录
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Although bedrock weathering strongly influences water quality and global carbon and nitrogen budgets, the weathering depths and rates within subsurface are not well understood nor predictable. Determination of both porewater chemistry and subsurface water flow are needed in order to develop more complete understanding and obtain weathering rates. In a long-term field study, we applied a multiphase approach along a mountainous watershed hillslope transect underlain by marine shale. Here we report three findings. First, the deepest extent of the water table determines the weathering front, and the range of annually water table oscillations determines the thickness of the weathering zone. Below the lowest water table, permanently water-saturated bedrock remains reducing, preventing deeper pyrite oxidation. Secondly, carbonate minerals and potentially rock organic matter share the same weathering front depth with pyrite, contrary to models where weathering fronts are stratified. Thirdly, the measurements-based weathering rates from subsurface shale are high, amounting to base cation exports of about 70 kmolc ha−1 y−1, yet consistent with weathering of marine shale. Finally, by integrating geochemical and hydrological data we present a new conceptual model that can be applied in other settings to predict weathering and water quality responses to climate change.

尽管基岩风化(bedrock weathering)对水质以及全球碳、氮收支具有显著影响,但目前学界对地下空间内的风化深度与速率仍缺乏充分认知与可靠预测能力。若要更全面地理解风化过程并准确获取风化速率,需同时测定孔隙水化学(porewater chemistry)与地下水流(subsurface water flow)特征。本研究依托一项长期野外实验,在以海相页岩(marine shale)为基底的山地流域山坡样带上采用了多阶段研究方法。本研究报告三项核心发现:其一,地下水位(water table)的最深埋深决定了风化前锋(weathering front)的位置,而年度地下水位波动幅度则决定了风化带的厚度。在最低地下水位以下,长期处于水饱和状态的基岩仍保持还原环境,从而阻止了更深层黄铁矿(pyrite)的氧化作用。其二,碳酸盐矿物与潜在的岩石有机质(rock organic matter)与黄铁矿具有相同的风化前锋深度,这与风化前锋呈分层分布的传统模型相悖。其三,基于实测数据得到的地下页岩风化速率较高,其碱阳离子(base cation)输出量约为70 kmolc ha⁻¹ y⁻¹,且与海相页岩的风化特征相符。最后,本研究通过整合地球化学与水文数据,提出了一种全新的概念模型,该模型可推广应用于其他区域,用以预测气候变化背景下的风化过程与水质响应。

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2022-08-10
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