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Associating the spatial properties of a watershed with downstream Chl-a concentration using spatial analysis and generalized additive models

机译:使用空间分析和广义加性模型将流域的空间特性与下游Chl-a浓度相关联

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We examined the relationship between downstream algal growth potential and the spatial environmental factors of both upland areas and stream buffer zones using spatial analysis and generalized additive models (GAMS). The models employed site-representative concentrations of chlorophyll a (Chia) from a total of 688 national water quality monitoring stations and the spatial factors of the corresponding 688 watersheds. The spatial environmental factors included topography, climate, land use class, soil type, and proximity of the monitoring station to the weir downstream and wastewater treatment plants (WWTPs). The explanatory power (adjusted R-2 or R-adj(2)) of the models was used to compare different spatial influential scales defined by stream buffers and upstream circular buffers. The spatial environmental factors of the entire watershed area better explained the inter-station variation in Chl-a than did those of the stream buffer and/or upstream circular buffer areas. However, the spatial environmental factors of watershed areas more than 25 km upstream circular buffer zones had only minor influence on the explainability of the models with regards to the inter-station variation in Chl-a levels. Generally, land use patterns were more strongly related to the inter-station Chl-a variation than were point sources of pollutants such as WWTPs. The two most influencing land uses on the inter-station Chl-a variation were urban and agricultural land uses, with varying relative contributions depending on the spatial influential scale: In general relative contribution of urban land use was larger at a larger spatial influential scale while that of agricultural land use showed an opposite trend. In addition, the proximity to the weir downstream explained high Chl-a concentrations in the stream water. Relative importance and causal effects of the spatial environmental variables to instream Chl-a were established based on this national scale correlative analysis, leading to decision-making with the goal of controlling instream algal growth. (C) 2019 Elsevier Ltd. All rights reserved.
机译:我们使用空间分析和广义加性模型(GAMS)研究了下游藻类生长潜力与高地地区和河流缓冲区之间的空间环境因素之间的关系。该模型采用了总共688个国家水质监测站的叶绿素a(Chia)的代表浓度以及相应688个流域的空间因子。空间环境因素包括地形,气候,土地使用类别,土壤类型以及监测站与堰下游和废水处理厂(WWTP)的距离。模型的解释力(调整后的R-2或R-adj(2))用于比较由流缓冲区和上游循环缓冲区定义的不同空间影响尺度。与流缓冲区和/或上游圆形缓冲区相比,整个集水区的空间环境因素更好地解释了Chl-a的站间变化。然而,在Chl-a水平的站间变化方面,上游上游25 km以上的流域区域的空间环境因素对模型的可解释性影响很小。通常,土地利用方式与站间Chl-a变化的关系比污水处理厂等污染物的点源更紧密。站点间Chl-a变化中影响最大的两个土地用途是城市和农业土地用途,其相对贡献取决于空间影响力范围:通常,在较大的空间影响力范围内,城市土地利用的相对贡献较大。农业土地利用的变化趋势相反。另外,靠近堰下游的原因说明了溪流水中的Chl-a浓度很高。基于这一全国规模的相关分析,建立了空间环境变量对下游Chl-a的相对重要性和因果关系,从而做出了以控制上游藻类生长为目标的决策。 (C)2019 Elsevier Ltd.保留所有权利。

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