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千岛湖地区上梧溪流域地表径流非点源氮污染分类识别
引用本文:俞珂,严琰,唐张轩,张方方,何圣嘉,姜培坤.千岛湖地区上梧溪流域地表径流非点源氮污染分类识别[J].环境科学,2023,44(7):3923-3932.
作者姓名:俞珂  严琰  唐张轩  张方方  何圣嘉  姜培坤
作者单位:浙江农林大学环境与资源学院, 杭州 311300;浙江农林大学省部共建亚热带森林培育国家重点实验室, 杭州 311300
基金项目:浙江省重点研发项目(2019C03121);浙江省自然科学基金项目(LY21D010001);国家自然科学基金项目(41807154)
摘    要:非点源污染的准确定量是流域非点源污染控制和治理的基本前提和重要保障.在综合考虑基流非点源污染的前提下,对传统输出系数模型(ECM)进行优化和改进,建立以周为时间步长的输出系数模型(IECM),实现上梧溪流域不同土地利用类型地表径流非点源总氮(TN)污染更加准确的定量识别.结果表明,IECM可以有效实现该流域TN负荷的模拟定量,校准期与验证期的纳什系数(NSE)分别为0.82和0.77,R2分别为0.87和0.84.基于IECM得到的上梧溪流域2020年11月至2021年10月地表径流和基流的TN输出强度分别为5.74 kg·(hm2·a)-1和9.85 kg·(hm2·a)-1,分别占总径流负荷的36.80%和63.20%.相较于IECM,ECM由于未考虑基流对非点源污染的贡献,其估算的地表径流TN负荷量较IECM高54.21%.显然,直接将基流非点源污染归结于地表径流将导致地表径流负荷输出强度的严重高估.基于IECM计算得到的上梧溪流域水田、草地、林地、旱地和人居地的以地表径...

关 键 词:非点源污染    输出系数模型  基流  数字滤波
收稿时间:2022/7/21 0:00:00
修稿时间:2022/9/19 0:00:00

Classification and Identification of Non-point Source Nitrogen Pollution in Surface Flow of the Shangwu River Watershed in the Qiandao Lake Region
YU Ke,YAN Yan,TANG Zhang-xuan,ZHANG Fang-fang,HE Sheng-ji,JIANG Pei-kun.Classification and Identification of Non-point Source Nitrogen Pollution in Surface Flow of the Shangwu River Watershed in the Qiandao Lake Region[J].Chinese Journal of Environmental Science,2023,44(7):3923-3932.
Authors:YU Ke  YAN Yan  TANG Zhang-xuan  ZHANG Fang-fang  HE Sheng-ji  JIANG Pei-kun
Institution:College of Environmental and Resource Sciences, Zhejiang A&F University, Hangzhou 311300, China;State Key Laboratory of Subtropical Silviculture, Zhejiang A&F University, Hangzhou 311300, China
Abstract:Accurate quantification of non-point source pollution is an important step for non-point source pollution control and management at the watershed scale. Considering the non-point source pollution from baseflow, an improved export coefficient model (IECM) on a weekly scale was established based on the traditional export coefficient model (ECM), which was then used to estimate the surface flow non-point source total nitrogen (TN) loads contributed by different land use types of the Shangwu River watershed in the Qiandao Lake Region. The results showed that IECM performed well for the predictions of TN loads in the studied watershed, with the Nash-Sutcliffe efficiency coefficient (NSE) and R2values of 0.82 and 0.77 (P<0.01) for the calibration period and 0.87 and 0.84 (P<0.01) for the validation period, respectively. The IECM estimated TN exports through surface flow and baseflow were 5.74 kg·(hm2·a)-1and 9.85 kg·(hm2·a)-1 from the Shangwu River watershed in the period of Nov. 2020 to Oct. 2021, which accounted for 36.80% and 63.20% of the corresponding streamflow TN load, respectively. Without consideration of the baseflow non-point source TN pollution, the ECM-estimated surface flow TN loading was 54.21% higher than that estimated by IECM. Obviously, attributing baseflow non-point source pollution to surface flow directly would lead to a serious load overestimation of surface flow. According to IECM, the estimated TN export intensity through surface flow from paddy fields, grasslands, woodlands, rainfed croplands, and residential lands was 10.95, 5.42, 5.20, 12.34, and 2.77 kg·(hm2·a)-1, respectively, which accounted for 5.80%, 4.00%, 26.55%, 0.38%, and 0.03% of the corresponding total streamflow TN loads. Therefore, the future management of non-point source nitrogen pollution in the studied watershed should focus mainly on the prevention and management of groundwater non-point source pollution and control of load export from surface flow on cultivated land (paddy fields and rainfed croplands).
Keywords:non-point source  nitrogen  export coefficient model  baseflow  digital filter
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