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河流网络关系的变化及流域电导率的地理空间预测。

Variation in stream network relationships and geospatial predictions of watershed conductivity.

作者信息

McManus Michael G, D'Amico Ellen, Smith Elizabeth M, Polinsky Robyn, Ackerman Jerry, Tyler Kip

机构信息

Center for Environmental Measurement and Modeling, Office of Research and Development, United States Environmental Protection Agency, 26 West Martin Luther King Drive, Cincinnati, Ohio 45268 USA.

Pegasus Technical Services c/o United States Environmental Protection Agency, 26 West Martin Luther King Drive, Cincinnati, Ohio 45268 USA.

出版信息

Freshw Sci. 2020 Dec 1;39(4):1-18. doi: 10.1086/710340.

Abstract

Secondary salinization, the increase of anthropogenically-derived salts in freshwaters, threatens freshwater biota and ecosystems, drinking water supplies, and infrastructure. The various anthropogenic sources of salts and their locations in a watershed may result in secondary salinization of river and stream networks through multiple inputs. We developed a watershed predictive assessment to investigate the degree to which topology, land-cover, and land-use covariates affect stream specific conductivity (SC), a measure of salinity. We used spatial stream network models to predict SC throughout an Appalachian stream network in a watershed affected by surface coal mining. During high-discharge conditions, 8 to 44% of stream km in the watershed exceeded the SC benchmark of 300 μS/cm, which is meant to be protective of aquatic life in the Central Appalachian ecoregion. During low-discharge conditions, 96 to 100% of stream km exceeded the benchmark. The 2 different discharge conditions altered the spatial dependency of SC among the stream monitoring sites. During most low discharges, SC was a function of upstream-to-downstream network distances, or flow-connected distances, among the sites. Flow-connected distances are indicative of upstream dependencies affecting stream SC. During high discharge, SC was related to both flow-connected distances and flow-unconnected distances (i.e., distances between sites on different branches of the network). Flow-unconnected distances are indicative of processes on adjacent branches and their catchments affecting stream SC. With sites distributed from headwaters to the watershed outlet, the extent of impacts from secondary salinization could be better spatially predicted and assessed with spatial stream network models than with models assuming spatial independence. Importantly, the assessment also recognized the multi-scale spatial relationships that can occur between the landscape and stream network.

摘要

次生盐渍化,即淡水中人为来源盐分的增加,威胁着淡水生物群和生态系统、饮用水供应以及基础设施。盐的各种人为来源及其在流域中的位置可能通过多种输入导致河流和溪流网络的次生盐渍化。我们开发了一种流域预测评估方法,以研究拓扑结构、土地覆盖和土地利用协变量对溪流电导率(SC,一种盐度度量)的影响程度。我们使用空间溪流网络模型来预测受地表煤矿开采影响的流域内阿巴拉契亚溪流网络的电导率。在高流量条件下,该流域8%至44%的溪流公里数超过了300 μS/cm的电导率基准,该基准旨在保护中阿巴拉契亚生态区的水生生物。在低流量条件下,96%至100%的溪流公里数超过了该基准。两种不同的流量条件改变了溪流监测站点之间电导率的空间依赖性。在大多数低流量期间,电导率是站点之间上下游网络距离或水流连接距离的函数。水流连接距离表明上游依赖性对溪流电导率的影响。在高流量期间,电导率与水流连接距离和水流不连接距离(即网络不同分支上站点之间的距离)都有关。水流不连接距离表明相邻分支及其集水区上影响溪流电导率的过程。随着站点从源头分布到流域出口,与假设空间独立性的模型相比,利用空间溪流网络模型可以更好地在空间上预测和评估次生盐渍化的影响程度。重要的是,该评估还认识到景观与溪流网络之间可能出现的多尺度空间关系。

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