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基于嵌套集水区的养分输入和迁移的数据分析。

Data-driven analysis of nutrient inputs and transfers through nested catchments.

机构信息

Department of Sustainable development, Environmental science and Engineering (SEED), Royal Institute of Technology (KTH), Stockholm, Sweden; Department of Physical Geography and the Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden; Department of Applied Hydraulics, Faculty of Civil Engineering, Architecture and Geodesy, University of Split, Split, Croatia.

Department of Sustainable development, Environmental science and Engineering (SEED), Royal Institute of Technology (KTH), Stockholm, Sweden.

出版信息

Sci Total Environ. 2018 Jan 1;610-611:482-494. doi: 10.1016/j.scitotenv.2017.08.003. Epub 2017 Sep 4.

Abstract

A data-driven screening methodology is developed for estimating nutrient input and retention-delivery in catchments with measured water discharges and nutrient concentrations along the river network. The methodology is applied to the Sava River Catchment (SRC), a major transboundary catchment in southeast Europe, with seven monitoring stations along the main river, defining seven nested catchments and seven incremental subcatchments that are analysed and compared in this study. For the relatively large nested catchments (>40,000km), characteristic regional values emerge for nutrient input per unit area of around 30T/yr/km for dissolved inorganic nitrogen (DIN) and 2T/yr/km for total phosphorus (TP). For the smaller nested catchments and incremental subcatchments, corresponding values fluctuate and indicate hotspot areas with total nutrient inputs of 158T/yr/km for DIN and 13T/yr/km for TP. The delivered fraction of total nutrient input mass (termed delivery factor) and associated nutrient loads per area are scale-dependent, exhibiting power-law decay with increasing catchment area, with exponents of around 0.2-0.3 for DIN and 0.3-0.5 for TP. For the largest of the nested catchments in the SRC, the delivery factor is around 0.08 for DIN and 0.03 for TP. Overall, the nutrient data for nested catchments within the SRC show consistency with previously reported data for multiple nested catchments within the Baltic Sea Drainage Basin, identifying close nutrient relationships to driving hydro-climatic conditions (runoff for nutrient loads) and socio-economic conditions (population density and farmland share for nutrient concentrations).

摘要

一种基于数据驱动的筛选方法被开发出来,用于估算有测量水流和沿河流网络的养分浓度的集水区的养分输入和保留-输送。该方法应用于萨瓦河流域(SRC),这是东南欧的一个主要跨界流域,在主要河流上有七个监测站,定义了七个嵌套集水区和七个递增的子集水区,本研究对这些集水区进行了分析和比较。对于相对较大的嵌套集水区(>40000km),每单位面积的养分输入特征区域值约为 30T/yr/km 的溶解无机氮(DIN)和 2T/yr/km 的总磷(TP)。对于较小的嵌套集水区和递增的子集水区,相应的值波动较大,表明有总养分输入为 158T/yr/km 的 DIN 和 13T/yr/km 的 TP 的热点地区。总养分输入质量的输送部分(称为输送因子)和相关的养分负荷与面积有关,随集水区面积的增加呈幂律衰减,DIN 的指数约为 0.2-0.3,TP 的指数约为 0.3-0.5。对于 SRC 中最大的嵌套集水区,DIN 的输送因子约为 0.08,TP 的输送因子约为 0.03。总体而言,SRC 内嵌套集水区的养分数据与波罗的海流域内多个嵌套集水区的先前报告数据一致,表明与驱动水文气候条件(养分负荷的径流量)和社会经济条件(人口密度和农田份额)的养分关系密切。

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