School of Environmental and Biological Sciences, Rutgers University, New Brunswick, NJ 08901, USA.
Department of Chemistry and Environmental Science, New Jersey Institute of Technology, University Heights, Newark, NJ 07102, USA.
J Environ Manage. 2018 May 1;213:309-319. doi: 10.1016/j.jenvman.2018.02.075.
Understanding the relationship between land use and water quality is essential to improve water quality through carefully managing landscape change. This study applies a linear mixed model at both watershed and hydrologically sensitive areas (HSAs) scales to assess such a relationship in 28 northcentral New Jersey watersheds located in a rapidly urbanizing region in the United States. Two models differ in terms of the geographic scope used to derive land use matrices that quantify land use conditions. The land use matrices at the watershed and HSAs scales represent the land use conditions in these watersheds and their HSAs, respectively. HSAs are the hydrological "hotspots" in a watershed that are prone to runoff generation during storm events. HSAs are derived using a soil topographic index (STI) that predicts hydrological sensitivity of a landscape based on a variable source area hydrology concept. The water quality indicators in these models are total nitrogen (TN), total phosphorus (TP) and total suspended solids (TSS) concentrations in streams observed at the watershed outlets. The modeling results suggest that presence of low density urban land, agricultural land and wetlands elevate while forest decreases TN, TP and/or TSS concentrations in streams. The watershed scale model tends to emphasize the role of agricultural lands in water quality degradation while the HSA scale model highlights the role of forest in water quality improvement. This study supports the hypothesis that even though HSAs are relatively smaller area compared to watershed, still the land uses within HSAs have similar impacts on downstream water quality as the land uses in entire watersheds, since both models have negligible differences in model evaluation parameters. Inclusion of HSAs brings an interesting perspective to understand the dynamic relationships between land use and water quality.
了解土地利用和水质之间的关系对于通过精心管理景观变化来改善水质至关重要。本研究在美国一个快速城市化地区的 28 个新泽西州中北部流域中,应用线性混合模型在流域和水文敏感区(HSAs)尺度上评估这种关系。两个模型的区别在于用于推导出量化土地利用状况的土地利用矩阵的地理范围。流域和 HSAs 尺度上的土地利用矩阵分别代表这些流域及其 HSAs 的土地利用状况。HSAs 是流域中的水文“热点”,在暴雨事件中容易产生径流。HSAs 是使用土壤地形指数(STI)来推导的,该指数根据可变源区水文学概念预测景观的水文敏感性。这些模型中的水质指标是在流域出口处观测到的溪流中的总氮(TN)、总磷(TP)和总悬浮固体(TSS)浓度。建模结果表明,低密度城市土地、农业土地和湿地的存在会增加,而森林会降低溪流中的 TN、TP 和/或 TSS 浓度。流域尺度模型倾向于强调农业用地在水质退化中的作用,而 HSAs 尺度模型则强调森林在水质改善中的作用。本研究支持这样的假设,即使 HSAs 与流域相比面积较小,但 HSAs 内的土地利用对下游水质的影响与整个流域的土地利用相似,因为这两个模型在模型评估参数方面差异可以忽略不计。HSAs 的纳入为理解土地利用和水质之间的动态关系提供了一个有趣的视角。