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首页> 外文期刊>Hydrology and Earth System Sciences >Landscape heterogeneity drives contrasting concentration–discharge relationships in shale headwater catchments
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Landscape heterogeneity drives contrasting concentration–discharge relationships in shale headwater catchments

机译:景观异质性驱动页岩源水集水区的浓度-流量关系形成对比

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Solute concentrations in stream water vary with discharge in patterns thatrecord complex feedbacks between hydrologic and biogeochemical processes. Ina comparison of three shale-underlain headwater catchments located inPennsylvania, USA (the forested Shale Hills Critical Zone Observatory), andWales, UK (the peatland-dominated Upper Hafren and forest-dominated UpperHore catchments in the Plynlimon forest), dissimilar concentration–discharge (C–Q) behaviorsare best explained by contrasting landscape distributions of soil solutionchemistry – especially dissolved organic carbon (DOC) – that have beenestablished by patterns of vegetation and soil organic matter (SOM).Specifically, elements that are concentrated in organic-rich soils due tobiotic cycling (Mn, Ca, K) or that form strong complexes with DOC (Fe, Al)are spatially heterogeneous in pore waters because organic matter isheterogeneously distributed across the catchments. These solutes exhibitnon-chemostatic behavior in the streams, and solute concentrations eitherdecrease (Shale Hills) or increase (Plynlimon) with increasing discharge. Incontrast, solutes that are concentrated in soil minerals and form only weakcomplexes with DOC (Na, Mg, Si) are spatially homogeneous in pore watersacross each catchment. These solutes are chemostatic in that their streamconcentrations vary little with stream discharge, likely because thesesolutes are released quickly from exchange sites in the soils duringrainfall events. Furthermore, concentration–discharge relationships ofnon-chemostatic solutes changed following tree harvest in the Upper Hore catchment in Plynlimon, while no changes were observed for chemostaticsolutes, underscoring the role of vegetation in regulating theconcentrations of certain elements in the stream. These results indicatethat differences in the hydrologic connectivity of organic-rich soils to thestream drive differences in concentration behavior between catchments. Assuch, in catchments where SOM is dominantly in lowlands (e.g., Shale Hills),we infer that non-chemostatic elements associated with organic matter arereleased to the stream early during rainfall events, whereas in catchmentswhere SOM is dominantly in uplands (e.g., Plynlimon), these non-chemostaticelements are released later during rainfall events. The distribution of SOMacross the landscape is thus a key component for predictive models of solutetransport in headwater catchments.
机译:溪流水中的溶质浓度随流量的变化而变化,记录了水文和生物地球化学过程之间的复杂反馈。比较位于美国宾夕法尼亚州(森林茂密的页岩山临界区天文台)和英国威尔士(泥炭地为主的上哈弗伦和普林利蒙森林中以森林为主的UpperHore流域)的三个页岩盆地水源流域,不同的浓度-流量( C – Q )行为可以通过对比土壤溶液化学(尤其是溶解有机碳(DOC))的景观分布来最好地解释,土壤分布化学是由植被和土壤有机质(SOM)模式建立的具体来说,由于生物循环(Mn,Ca,K)而集中在富含有机物的土壤中或与DOC(Fe,Al)形成强配合物的元素在孔隙水中在空间上是非均质的,因为有机物在流域内是异质分布的。这些溶质在物流中表现出非化学行为,并且溶质浓度随着排放量的增加而减少(页岩山)或增加(Plynlimon)。相反,集中在土壤矿物质中且仅与DOC(Na,Mg,Si)形成弱复合物的溶质在每个集水区的孔隙水中在空间上均一。这些溶质具有趋化性,因为它们的流浓度随流排放而变化不大,这可能是因为这些溶质在降雨过程中从土壤中的交换位点快速释放出来。此外,非化学溶质的浓度-排放关系在Plynlimon上游Hore流域的树木采伐后发生了变化,而化学溶质没有观察到变化,这突出了植被在调节河流中某些元素的浓度中的作用。这些结果表明,富含有机物的土壤与河流之间的水文连通性差异驱动了集水区之间浓度行为的差异。因此,在SOM主要位于低地的集水区(例如,页岩山)中,我们推断与有机物质相关的非化学元素在降雨事件发生的早期释放到河流中,而SOM主要位于高地的集水区(例如,Plynlimon) ,这些非化学元素会在降雨事件后释放。因此,SOMa在整个景观中的分布是源头集水区溶质运移预测模型的关键组成部分。

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