Ripple Effects: Bed Form Morphodynamics Cascading Into Hyporheic Zone Biogeochemistry

低流变区 生物地球化学循环 涟漪 海滩形态动力学 环境科学 反硝化 水文学(农业) 生物地球化学 土壤科学 平流 河床 推移质 泥沙输移 沉积物 地质学 地貌学 氮气 环境工程 环境化学 化学 岩土工程 地表水 海洋学 工程类 物理 电气工程 电压 有机化学 热力学
作者
Lizhi Zheng,M. Bayani Cardenas,Lichun Wang,David Mohrig
出处
期刊:Water Resources Research [Wiley]
卷期号:55 (8): 7320-7342 被引量:38
标识
DOI:10.1029/2018wr023517
摘要

Abstract The water quality and ecosystem health of river corridors depend on the biogeochemical processes occurring in the hyporheic zones (HZs) of the beds and banks of rivers. HZs in riverbeds often form because of bed forms. Despite widespread and persistent variation in river flow, how the discharge‐ and grain size‐dependent geometry of bed forms and how bed form migration collectively and systematically affects hyporheic exchange flux, solute transport, and biogeochemical reaction rates are unknown. We investigated these linked processes through morphodynamically consistent multiphysics numerical simulation experiments. Several realistic ripple geometries based on bed form stability criteria using mean river flow velocity and median sediment grain size were designed. Ripple migration rates were estimated based primarily on the river velocity. The ripple geometries and migration rates were used to drive hyporheic flow and reactive transport models which quantified HZ nitrogen transformation. Results from fixed bed form simulations were compared with matching migrating bed form scenarios. We found that the turnover exchange due to ripple migration has a large impact on reactant supply and reaction rates. The nitrate removal efficiency increased asymptotically with Damköhler number for both mobile and immobile ripples, but the immobile ripple always had a higher nitrate removal efficiency. Since moving ripples remove less nitrogen, and may even be net nitrifying at times, consideration for bed form morphodynamics may therefore lead to reduction of model‐based estimates of denitrification. The connection between nitrate removal efficiency and Damköhler number can be integrated into frameworks for quantifying transient, network‐scale, HZ nitrate dynamics.

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