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High spatial resolution landscape indicators show promise in explaining water quality in urban streams

机译:高空间分辨率景观指标显示在城市溪流中解释水质的承诺

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摘要

Urban streams are subject to a myriad of complex stressors associated with impervious surfaces, which impact delivery of pollutants. Landscape indicators (e.g. the amount and arrangement of land cover) are widely used to help monitor water quality, yet their application in highly urbanized settings remains poorly understood. Here, we explored the utility of landscape indicators for explaining water chemistry and bacterial concentrations in streams throughout the Greater Vancouver Regional District, British Columbia, Canada. First, we compared high and moderate spatial resolution imagery to evaluate their relative efficacy in characterizing impervious surfaces. Second, we linked a suite of landscape indicators to major chemical properties and pollutants (e.g. dissolved oxygen, nitrate, turbidity, fecal coliform, E. Coli.) using a series of comparative statistical models. Land cover at 30-m resolution often over-estimated the proportional area of impervious surface by 0.10-0.30, sometimes doubling the amount detected using finer resolution imagery. Finer 5- and 2-m resolution imagery demonstrated little difference in estimating impervious cover. Therefore, 5-m resolution imagery was adopted for spatial analysis in the study region. Watershed-level landscape indicators explained nearly 50% of the variability in wet season concentrations of dissolved oxygen and fecal coliform. When considering the spatial configuration of impervious areas, edge density within the riparian zone explained more than 30% of the variability in fecal coliform and E. Coli. Our approach is potentially transferable to many cities worldwide facing similar challenges in monitoring urban streams.
机译:城市溪流受到与不透水表面相关的无数复杂的压力,影响污染物的递送。景观指示器(例如,陆地覆盖的金额和排列)被广泛用于帮助监测水质,但它们在高度城市化环境中的应用仍然很差。在这里,我们探讨了景观指标的效用,以解释在加拿大不列颠哥伦比亚不列颠哥伦比亚省大温哥华地区流域的水化学和细菌浓度。首先,我们比较了高度的空间分辨率图像,以评估其特征在不透水表面的相对功效。其次,我们将一套景观指标与主要的化学性质和污染物联系起来(例如,溶解氧氧,硝酸盐,浊度,粪便大肠杆菌,大肠杆菌。)使用一系列比较统计模型。 30米分辨率的陆地覆盖经常过度估计不透水表面的比例区域0.10-0.30,有时使用更精细的分辨率图像检测到检测的量加倍。更精细的5-和2米分辨率图像显示估计不透水盖的差异很小。因此,采用5米分辨率的图像在研究区域中用于空间分析。流域水平景观指示器解释了湿季浓度溶解氧和粪便大肠菌型近50%的变异性。在考虑不透水区域的空间配置时,沿着山脉内的边缘密度在粪便大肠杆菌和大肠杆菌中解释了超过30%的变异性。我们的方法可能会转移到全球许多城市,在监测城市溪流中面临着类似的挑战。

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