基于GWLF模型的于桥水库入库河流水文模拟及氮磷负荷估算

流域模型技术应用是当前开展面源污染防治的重要工具,而水文过程的准确模拟是进行污染负荷估算的首要环节和关键步骤。为了弄清近年来于桥水库入库河流氮、磷输入负荷,选取GWLF模型对水平口子流域的水文过程进行模拟,首先利用2006—2018年气象、水文资料率定模型水文参数,然后将参数推广到整个流域,对2019—2020年3条主要入库河流流量进行模拟,最后乘以相应河流断面的总氮、总磷浓度估算氮磷输入负荷。结果显示：GWLF模型适用于研究区的水文过程模拟,校准期和验证期的纳氏系数分别为0.89和0.91,平均相对误差分别为12.2%和13.1%;2020年总氮入库负荷为3 977.0 t,其中引滦调水贡献占57.0%,3条入库河流共贡献43.0%;总磷入库负荷为48.8 t,其中引滦调水贡献占68.6%,3条入库河流共贡献31.4%。GWLF模型输入数据需求量较少,模型参数较少,模拟效果较好,适用于中小型流域的水资源和水环境管理,具有一定的推广应用前景。     

北京市水环境非点源污染监测与负荷估算研究

文章对北京全市域范围开展水环境非点源污染监测以及污染负荷估算研究。监测结果表明,天然降雨氨氮、总氮污染程度高;城区典型下垫面降雨径流的有机污染十分严重,其中屋面降雨径流总氮和氨氮污染最严重,路面降雨径流COD和总磷污染最严重;下垫面降雨径流汇入城市排水管网后,由于冲洗下水道中的沉积物,使得水质污染进一步恶化。农业典型小流域面源污染对水质影响也很明显。城市非点源污染负荷估算选用SWMM暴雨径流模型,农业非点源污染负荷模型选用改进的输出系数模型,估算结果表明:城市非点源污染主要来自大气湿沉降、综合用地、路面和屋面等,农业非点源污染主要来自耕地和林地;全市污染物排放总量中,点源排放总量与非点源排放总量基本各占50％左右。为进一步挖掘污染减排空间,完善总量减排体系提供了依据。     

桂林市相思江流域氮磷分布特征解析及空间变化预测

通过2019年6—12月对相思江流域（临桂段）丰水期和枯水期的水质监测分析,并采用主成分分析（PCA）对污染初步溯源和反距离加权插值（IDW）对氮磷质量浓度空间变化插值预测。结果表明：研究区内氮磷污染严重,TN和TP质量浓度范围分别为0.312 mg/L～14.744 mg/L和0.004 mg/L～0.452 mg/L,TN质量浓度枯水期高于丰水期,TP两水期大致相等。研究区内非点源氮磷呈现出明显空间变异性,上游氮磷污染最为严重。农业面源污染中禽畜养殖和生活污水是流域内主要污染因子。     

基于去耦合直接法的兰江流域地表水水质预测方法研究

针对影响因素众多、耦合机制复杂情况下的地表水污染物浓度预测问题，将河道污染物浓度的变化量表示为各种影响因子一阶偏导项和二阶偏导项的线性叠加。其中，一阶偏导项可描述影响因子变化与污染物浓度变化的直接关系，二阶偏导项可描述影响因子之间交互作用对污染物浓度变化的影响。在此基础上，提出了用以模拟地表水污染物浓度的去耦合直接法。采用2014—2016年兰江流域将军岩、低田、半潭、沈村、焦岩5个断面的水文和氨氮、高锰酸盐指数、总氮、总磷4项污染指标逐日实测数据，通过差分法求解了一阶和二阶偏导项，并采用2017—2019年实测数据对模型进行了验证和评价。结果表明：去耦合直接法能够有效预测地表水主要污染物浓度的变化方向和变化量，且模拟结果和实测结果的符合情况较好，4项污染指标模拟值的Nash-Sutcliffe系数为0.479～0.654,模拟值与实测值的偏差为0.070～0.352;汇流区面积增加后，影响因子不确性对污染物浓度的扰动减小，污染物浓度变化的规律性增强，去耦合直接法的模拟精度升高。与SWAT模型的对比分析结果显示，在污染成因不发生显著变化的情况下，去耦合直接法的模拟精度优于SWAT模型。     

城市小流域面源污染输出特征及污染负荷分类核算研究

以南京市上秦淮片区二横沟小流域为例,在污染源调查的基础上,采用分类法,利用改进后的污染输出系数模型进行流域污染负荷核算,得到外源污染物入河负荷量及各污染源的贡献率。研究结果表明,上秦淮片区二横沟流域内污染物排放负荷总量为COD 229.9 t/a、TN 25.8 t/a、NH3-N 22.4 t/a、TP 1.7 t/a,入河负荷量为COD 47.1 t/a、TN 5.5 t/a、NH3-N 4.6 t/a、TP 0.36 t/a,主要来自面源污染,点源污染较小。其中,生活面源污染年入河贡献率最高,为44.5%,林地面源污染贡献率最低,为0.1%,水产面源、道路面源、水田面源和旱地面源贡献率分别为31.6%、16.2%、6.2%和1.4%。     

基于DPeRS模型的渭河典型断面汇水区面源污染评估及污染成因分析

近年来甘肃渭河桦林断面月度水质不稳定达标的问题引起了管理部门的广泛关注,掌握桦林断面汇水范围面源污染现状,对控制流域面源污染和促进水质稳定达标具有重要意义。采用遥感分布式污染估算（DPeRS）面源污染评估模型,对2018年黄河流域甘肃桦林断面汇水区面源污染空间分布特征进行分析,开展多类型污染量产排特征解析。结果表明：农业面源污染量方面,2018年甘肃桦林断面汇水区总氮（TN）、总磷（TP）、氨氮（NH⁺₄-N）、重铬酸盐指数（COD_Cr）面源污染排放量分别为11 591,2 697,7 141和1 458 t,入河量分别为2 184,512,1347,263 t;空间分布上,氮型（TN和NH⁺₄-N）排放负荷高值区主要分布在陇西县、武山县县段和岷县县段;武山县县段TP排放负荷较为突出;COD_Cr型面源污染高负荷区主要分布在陇西县、渭源县县段和武山县县段。农业面源污染物入河排放负荷空间分布差异明显,氮磷型（TN、NH⁺₄-N和TP）入河高负荷区主要分布在武山县县段、陇西县、临洮县县段;COD_Cr型面源污染入河高负荷区呈分散分布。漳县西部地区水土流失量较高,漳县西部、陇西县和渭源县县段北部局部地区泥沙负荷量较高。枯水期污染治理仍是保障水质稳定达标的关键期,农田径流是渭河桦林断面所在汇水区氮磷型面源污染的首要污染类型,畜禽养殖是COD_Cr型面源污染的首要污染类型。     

基于多元统计分析的石头口门水库汇水流域水质综合评价

根据石头口门水库汇水流域的4个监测断面2001～2007年的水质监测数据,应用多元统计分析方法(聚类分析与因子分析)确定主要污染因子并计算权重,从而对流域的水质进行综合评价。结果表明,通过因子分析,提取了3个公因子,第一主因子主要包括溶解氧、氨氮、总氮、高锰酸盐指数、化学需氧量、生化需氧量;第二主因子的主要代表指标是总磷;氟化物、总大肠菌群数对第三主因子贡献明显。由综合评价结果得出,石头口门水库总体属Ⅲ类水质,主要污染因子为总磷;饮马河(烟筒山断面)和岔路河(星星哨水库断面)水质属Ⅲ类,主要受第一主因子影响;双阳河(新安断面)水质属Ⅴ类。流域水质主要受到了农业非点源污染和生活污染的影响。     

2016—2019年长江经济带总磷污染及治理特征分析

基于环境统计数据分析了长江经济带工业源和生活源总磷污染及治理特征。结果表明,2016—2019年,长江经济带工业源和生活源总磷排放量总体下降,但占全国比例逐年增加。工业源涉磷企业主要分布在江苏、浙江、四川、湖北等省,主要涉及纺织、农副食品、化工、电镀等行业;下游的南通、苏州、宁波、绍兴和杭州等城市"三磷"企业总磷产生量也较大。工业源总磷治理存在污水处理设施建设和现有治理能力不足的问题。四川、江苏、湖南等地的生活源总磷排放量较大,贵州、江西、云南等地的人均总磷排放量较高。长江经济带上游流域、地区生活污水处理率、总磷去除率较低。建议加强工业源涉磷企业监管和治理力度,强化上游地区生活污水处理设施建设和提标改造,减少总磷污染。     

基于SWAT模型的松花江流域哈尔滨段径流量模拟

应用SWAT模型对朱顺屯—大顶子山断面(66 km)的松花江流域进行小区域径流模拟,选取2010—2013年的月实测数据进行参数的率定和验证,并对模型几个重要参数敏感性分析,总结参数取值变化对模拟结果的影响规律。结果表明:模拟结果的相对误差(Re)、相关系数(R2)和月径流模拟效率系数(Ens)分别为0.09、0.84、0.78,均在保证值范围内,说明SWAT模型适用于小范围流域内分布式水文模型的建立,对松花江哈尔滨段水文模型的建立具有指导作用。     

黄河流域甘肃段面源污染估算与空间分析

采用遥感分布式面源污染评估模型（DPeRS）,对2018年黄河流域(甘肃段)面源污染空间分布特征进行分析,具体包括多类型污染量产排特征解析和流域优先管控单元识别。结果表明,污染量上,2018年黄河流域（甘肃段）总氮(TN)、总磷(TP)、氨氮(NH₃^-N)、化学需氧量(COD_Cr)的面源污染排放负荷分别为65.6,11.8,19.1和77.2 kg/km²,入河量分别为836.7,33.3,220.2和1 353.3 t;空间分布上,氮型(TN和NH₃^-N)排放负荷高值区主要分布在流域中部和东部局部地区,流域大部分地区TP排放负荷均较高,COD_Cr面源污染排放负荷高值区分布较为零散。与排放负荷相比,黄河流域（甘肃段）面源污染入河负荷并不突出,这与该地区水资源量少有密切关系。筛选出黄河流域（甘肃段）面源污染优先控制单元15个,面积占比为85.2%,I类优控单元主要分布在庆阳市、天水市、兰州市和白银市等地区,II类优控单元主要分布在甘南藏族自治州,且TN、TP、NH₃^-N和COD_Cr面源污染优控单元识别结果的平均精度达到80%。     

高纬区阿什河面源氮和磷污染输出特征

基于阿什河2008—2010年水质监测和流量监测结果,利用改进的埃特金和相关性拟合插值法,补全监测条件限制造成的缺失数据,再利用基流分割法,估算阿什河面源氮和磷污染输出量,分析其污染特征。结果显示:阿什河进入松花江的污染负荷峰值一般出现在3—5月或者7—9月,主要由春汛或夏汛造成,峰值出现时污染来源以面源污染为主。2008—2010年阿什河面源污染输出量表现出TP减少,TN和NH_4~+-N增加的趋势。阿什河年均输出量TN约为5 436.6 t,NH_4~+-N约为3 057.8 t,TP约为554.8 t,其中,点源污染为2 775.8、1 440.7、250.8 t,面源污染为2 660.7、1 630.7、304.1 t,面源污染占总量的50%左右。     

Evaluating Phosphorus Loss for Watershed Management: Integrating a Weighting Scheme of Watershed Heterogeneity into Export Coefficient Model

The identification of critical source areas (CSAs) and critical source periods (CSPs) are essential prerequisites for cost-effective practices of non-point source (NPS) pollution control. A simple empirical tool combining Export Coefficient Model (ECM) and a Geographic Information Systems (GIS)-based weighting scheme of watershed heterogeneity was proposed to estimate annual and monthly phosphorus loss, to identify critical source areas and periods, and to assess pollution control practices. The GIS-based weighting scheme was developed to represent the transport potential of runoff to move phosphorus from the land surfaces to waters, as a supplement to the source-based ECM. The empirical tool was applied to the Dianchi Lake watershed of China. The results showed that the total phosphorus loss from NPS in 2008 was 352.3 tons. The agricultural land was recognized as the largest and the most spatially various source type. The lakeside plain and the terraces of the watershed were identified as CSAs, which generated more than 90 % of non-point phosphorus. The early part of wet season (from May to August) was the CSPs, when about 70 % of non-point phosphorus was lost. The reduction of phosphorus fertilizers and the vegetated buffer strips (VBS) were effective in controlling phosphorus loss from NPS in the watershed. A reduction of 20 % in phosphorus fertilizer application combined with the set-up of VBS in both riparian area of the main watercourses and the lakeside areas would decrease 25 % of phosphorus loss.     

Load estimation and source apportionment of nonpoint source nitrogen and phosphorus based on integrated application of SLURP model, ECM, and RUSLE: a case study in the Jinjiang River, China

The nonpoint source (NPS) pollution is difficult to manage and control due to its complicated generation and formation. Load estimation and source apportionment are an important and necessary process for efficient NPS control. Here, an integrated application of semi-distributed land use-based runoff process (SLURP) model, export coefficients model (ECM), and revise universal soil loss equation (RUSLE) for the load estimation and source apportionment of nitrogen and phosphorus was proposed. The Jinjiang River (China) was chosen for the evaluation of the method proposed here. The chosen watershed was divided into 27 subbasins. After which, the SLURP model was used to calculate land use runoff and to estimate loads of dissolved nitrogen and phosphorus, and ECM was applied to estimate dissolved loads from livestock and rural domestic sewage. Next, the RUSLE was employed for load estimation of adsorbed nitrogen and phosphorus. The results showed that the 12,029.06 t?a^?1 pollution loads of total NPS nitrogen (TN) mainly originated from dissolved nitrogen (96.24 %). The major sources of TN were land use runoff, which accounted for 45.97 % of the total, followed by livestock (32.43 %) and rural domestic sewage (17.83 %). For total NPS phosphorous (TP), its pollution loads were 570.82 t?a^?1 and made up of dissolved and adsorbed phosphorous with 66.29 and 33.71 % respectively. Soil erosion, land use runoff, rural domestic sewage, and livestock were the main sources of phosphorus with contribution ratios of 33.71, 45.73, 14.32, and 6.24 % respectively. Therefore, land use runoff, livestock, and soil erosion were identified as the main pollution sources to influence loads of NPS nitrogen and phosphorus in the Jinjiang River and should be controlled first. The method developed here provided a helpful guideline for conducting NPS pollution management in similar watershed.     

Modeling of land use and reservoir effects on nonpoint source pollution in a highly agricultural basin

Nonpoint source (NPS) pollution is tightly linked to land use activities that determine the sources and magnitudes of pollutant loadings to stream water. The pollutant loads may also be alleviated within reservoirs because of the physical interception resulting from changed hydrological regimes and other biochemical processes. It is important but challenging to assess the NPS pollution processes with human effects due to the measurement limitations. The objective of this study is to evaluate the effects of human activities such as land uses and reservoir operation on the hydrological and NPS pollution processes in a highly agricultural area-the Iowa River Basin-using the Soil and Water Assessment Tool (SWAT). The evaluation of model performance at multiple sites reveals that SWAT can consistently simulate the daily streamflow, and monthly/annual sediment and nutrient loads (nitrate nitrogen and mineral phosphorus) in the basin. We also used the calibrated model to estimate the trap efficiencies of sediment (～78%) and nutrients (～30%) in the Coralville Reservoir within the basin. These non-negligible effects emphasize the significance of incorporating the sediment and nutrient removal mechanisms into watershed system studies. The spatial quantification of the critical NPS pollution loads can help identify hot-spot areas that are likely locations for the best management practices.     

Modeling the effect of land use/land cover on nitrogen,phosphorous and dissolved oxygen loads in the Velhas River using the concept of exclusive contribution area

Non-point source water pollution is a major problem in most parts of the world, but is also very difficult to quantify and control since it is not easily separated from point sources and can theoretically originate from the whole watershed. In this article, we evaluate the relationship between land use and land cover and four water pollution parameters in a watershed in Southeast Brazil. The four parameters are nitrate, total ammonia nitrogen, total phosphorous, and dissolved oxygen. To help concentrate on non-point source pollution, only data from the wet seasons of the time period (2001–2013) were analysed, based on the fact that precipitation causes runoff which is the main cause of diffuse pollution. The parameters measured were transformed into loads, which were in turn associated with an exclusive contribution area, so that every measuring station could be considered independent. Analyses were also performed on riparian zones of different widths to verify if the effect of the land cover on the water quality of the stream decreases with the increased distance. Pearson correlation coefficients indicate that urban areas and agriculture/pasture tend to worsen water quality (source). Conversely, forest and riparian areas have a reducing effect on pollution (sink). The best results were obtained for total ammonia nitrogen and dissolved oxygen using the whole exclusive contribution areas with determination coefficients better than R²≈0.8. Nitrate and total phosphorous did not produce valid models. We suspect that the transformation delay from total ammonia nitrogen to nitrate might be an important factor for the poor result for this parameter. For phosphorous, we think that the phosphorous sink in the bottom sediment might be the most limiting factor explaining the failure of our models.     

通榆河南段控制单元最大日负荷估算及分配研究

以通榆河南段控制单元为研究区，利用现有的平原感潮河网区水量模型、面源污染负荷统计模型和水环境容量模型，估算研究区2010年污染物最大日负荷总量（TMDL），并进行负荷削减和分配研究。结果表明：研究区COD、氨氮（NH3-N）90％保证率（2004年）下的水环境容量分别为7．76万t,0．37万t；xCN2010年污染物入河量，COD、NH3-N的最大年负荷分别为1．99万t,0．28万t。在研究区涉及的各县市中，海安、姜堰、东台是负荷削减的重点区域；对于不同的污染源，城镇生活点源和农业面源是研究区污染物总量控制的关键。     

太湖流域果园种植面源氮磷输出强度及其定量评估方法

以太湖流域上游地区无锡阳山地区果园种植典型区域为研究对象,通过现场试验,调查了果园种植面源氮磷输出动态变化过程,计算并分析了氮磷输出强度,构建了果园种植面源氮磷输出强度定量评估模型。结果表明:取样监测期间,果园种植径流及淋溶氮磷指标变化幅度均超过200%;果园种植面源氮磷径流输出强度与其淋溶输出的变化一致,径流总氮的输出强度最高(13.201 kg/hm~2),淋溶硝酸盐输出强度最大(4.077 kg/hm~2);所建立的评估方程能较好地反映降雨量等环境因素对果园种植面源氮磷径流及淋溶输出强度的影响情况,模拟方程的复相关系数均在0.9左右。     

湖州合溪新港污染物入湖通量估算与分析

根据2021年5月—2022年4月合溪新港河流水量、水质(TN和TP)的同步监测数据，利用通量模型核算了合溪新港污染物(TN和TP)通量。通过测算合溪新港TN、TP通量与断面降雨强度、水质的响应关系，分析了该区域的污染类型及特点，为后期水质污染调查及通量研究提供了新思路。结果表明：合溪新港流量与降雨量存在明显相关关系，在强降雨期(7—8月)水体流量最高，占监测周期总流量的57.77%;少雨期则流量最低，且会出现湖水倒灌现象(11—12月)。通过分析合溪新港TN、TP通量与流量、水质的相关关系，确定了该流域污染类型为点源污染及农业面源污染共存的混合型污染，且在高强度降雨时污染物负荷量较大。综上，可针对农业面源污染对该流域治理提出相关对策，建立农业面源污染防治体系，以有效降低TN和TP污染物的入湖通量，减少太湖TN和TP污染物负荷量。