Source Apportionment of Total Phosphorus Pollution in Poyang Lake Basin Based on Source-Sink Process Modeling
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摘要: 近年来鄱阳湖磷污染问题突出，总磷超标且浓度逐年增加，成为制约鄱阳湖流域（江西）经济社会可持续发展的重要因素.为科学解析鄱阳湖总磷污染来源，耦合多污染源污染负荷估算方法和SPARROW模型，建立基于源汇过程模拟的流域污染源解析技术方法，针对鄱阳湖流域13种总磷污染源开展负荷估算、模拟校核和入湖时空贡献定量解析.结果表明：①鄱阳湖总磷负荷以陆域输入为主（占90.8%），主要污染来源为农业和城镇生活源，贡献率分别为56.4%和30.6%；污染来源按贡献率的大小排序依次为种植业（29.3%）>城镇生活（24.6%）>畜禽养殖（17.2%）>水产养殖（9.9%）>内源释放（6.9%）>城市径流（6.0%）>农村生活（2.2%）>工业企业（1.6%）>其他源（0.46%）.②在空间贡献方面，总磷入湖负荷主要来自于滨湖区和赣江集水区，贡献率分别为33.5%和31.8%，其他集水区总磷贡献率较小（合计为25.5%），湖体贡献率为9.2%；同时，不同子流域污染源贡献结构也存在空间差异性.③在时间贡献方面，总磷入湖负荷量呈季节性波动特征，贡献峰值多出现在6月，雨季（3—8月）陆源输入负荷占全年的70%.④所构建的基于源汇过程模拟的污染源解析模型可用于流域水污染来源成因精细化解析.研究显示，鄱阳湖总磷污染来源具有明显时空差异性，建议围绕滨湖区和赣江集水区等高贡献区域设立优先管控区，重点针对种植业、城镇生活、畜禽养殖和水产养殖源，制定磷污染源汇过程减排政策措施，以改善鄱阳湖水环境质量.Abstract: In recent years, the total phosphorus (TP) pollution in Poyang Lake has worsened with increasing TP concentration year by year, limiting the sustainable development of the regional socio-economy in the Poyang Lake Basin (PLB) or Jiangxi Province. To completely and quantitatively identify the pollution sources of TP in Poyang Lake, a robust source-sink processes based framework for watershed pollution source apportionment has been developed by combining the traditional load estimation methods with the SPARROW model in this study. The methodology is applied in estimation and validation of TP pollution loads of a total of 13 sources in PLB and quantifying the corresponding spatio-temporal contributions. The results show that: (1) The major part of TP load in Poyang Lake comes from land area (accounting for 90.8% of basinal total), and the main pollution sources are related to agriculture and urban household, accounting for 56.4% and 30.6%, respectively. According to the percentage of contribution from different sources, the TP load contribution structure to Poyang Lake is: planting (29.3%) > urban household (24.6%) > livestock (17.2%) > aquiculture (9.9%) > sediment endogenous release (6.9%) > urban runoff (6.0%) > rural household (2.2%) > industry (1.6%) > other sources (on average 0.46%). (2) From the perspective of spatial contribution, the waterfront area and the Ganjiang watershed are two major contribution areas to Poyang Lake's TP load, accounting for 33.5% and 31.8%, respectively, and the other watersheds contribute 25.5% of TP load to Poyang Lake. In addition, different subbasins present different pollution source structures. (3) From the perspective of temporal contribution, it shows the seasonal variation of TP load into Poyang Lake and the total TP entering the lake from March to August accounts for 70% of the annual total, with the peak load in June. (4) The developed source-sink processes based on the watershed pollution source apportionment framework can be used to support basinal systematic and refined water pollution apportionment. Based on these findings, it can be concluded that the source of TP load entering Poyang Lake varies temporospatially. We suggest setting priority areas for TP pollution control especially in the Waterfront area and Ganjiang watershed, to carry out policies and measures for TP load reduction from the major sources (including planting, urban household, livestock, aquiculture, etc.) across corresponding source-sink processes, and to improve the water quality in Poyang Lake.
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图 2 基于源汇过程模拟的流域污染源解析技术框架
Figure 2. The framework of watershed pollution source apportionment based on source-sink processes modeling
图 3 基于SPARROW模型的污染物源汇过程耦合模拟/校核模型结构
Figure 3. Model structure of the SPARROW model based pollutant source-sink processes coupled simulation/validation
图 5 鄱阳湖流域总磷负荷合理性模拟校核结果
Figure 5. Validation results of TP load estimations in Poyang Lake Basin using source-sink processes simulation
图 6 鄱阳湖流域总磷污染源年均入湖总磷负荷情况
Figure 6. Annually mean TP loading to Poyang Lake Basin from different sources
图 7 鄱阳湖流域各集水区总磷入湖负荷总量空间分布
Figure 7. The amounts of TP loading to Poyang Lake Basin from watersheds
图 8 鄱阳湖流域内各子流域陆源总磷入湖负荷量和单位面积总磷入湖负荷强度空间分布
Figure 8. The amounts and intensities of TP loading to Poyang Lake Basin from subbasins for land area pollution sources
图 9 高贡献子流域(入湖负荷贡献率大于2%)陆域污染源贡献结构
Figure 9. Contribution structures of different TP pollution sources over high impact subbasins for land area pollution sources (contribution rate >2%)
图 10 鄱阳湖流域各类陆域污染源入湖负荷过程
Figure 10. Monthly TP loading processes to Poyang Lake Basin for land area pollution sources during 2016-2017
图 11 鄱阳湖流域各类陆域污染源总磷月入湖负荷贡献占比
Figure 11. Monthly TP loading structures to Poyang Lake Basin for land area pollution sources
表 1 流域水污染源分类、核算范围及核算方法
Table 1. Categories of water pollution sources and corresponding estimation scopes and methods
类型 核算范围 核算方法 工业企业 全流域涉水工业企业 依据实地调查、污染普查数据核定[16] 城镇生活 全流域城镇人口生活污水(散排和集中处理) 污染物产生总量按污染普查数据核定，其中经管网收集并集中处理后的排放量按照污水处理厂尾水水质监测数据核算，剩余计为散排负荷量 畜禽养殖 全流域畜禽养殖过程产排污(规模化和散养) 污染负荷量按排污系数法测算[15]，其中规模化养殖排污负荷量包括处理后直排量和还田后流失量；排污系数参考《第一次全国污染源普查畜禽养殖源产排污系数手册》，还田后负荷流失系数参考文献[34] 水产养殖 全流域水产养殖污染尾水排放 按产量乘以排污系数的方法测算，其中各类水产品单产排污系数参考《第一次全国污染源普查水产养殖业污染源产排污系数手册》 农村生活 全流域农村人口生活污水(面源) 按农村人口乘以人均日排污系数的方法测算，排污系数参考第一次污染普查中江西省所在大区五类城镇居民生活污水排放系数折算得到，取0.22 g/(d·人) 城市径流 全流域城市区域降雨径流负荷(面源) 针对城镇的屋面、绿地、街道和小区路面范围，采用SCS径流曲线法计算降雨径流量，乘以地表径流平均污染物浓度测算，相关计算方法及污染物浓度值参考文献[35-36] 种植业 全流域水田、旱地种植业的排污负荷 针对施肥和秸秆(按草谷比测算)还田，采用排放系数法测算.参考地区田间监测数据[34]，分别取水田和旱地肥料排放系数为0.031和0.062；秸秆还田率采用实地调查获得，农作物草谷比和秸秆磷含量参考文献[37] 船舶码头 湖体船舶航运和码头运行的直接入湖负荷 依据相关技术资料及港口吞吐量测算环鄱阳湖港口码头排污量，船舶生活污水中总磷浓度按5 mg/L计算 干湿沉降 湖体大气干湿沉降的直接入湖负荷 依据实测数据计算污染负荷通量，鄱阳湖湖面面积按2 692 km2计 内源释放 湖体底泥内源释放的直接入湖负荷 根据磷吸附/解吸平衡方程，鄱阳湖沉积物总磷释放量约为11 mg/kg，据多年统计的鄱阳湖底泥总磷向水界面扩散和面积关系，利用多年平均面积(2 100 km2)测算 候鸟粪便 湖体候鸟粪便排泄导致的直接入湖负荷 以候鸟数量×候鸟粪污产生系数×每年停留天数测算，其中候鸟平均每天粪便中磷排放量取0.49 g/羽，停留时间按182 d估算 采砂活动 湖区采砂活动导致的直接入湖负荷，湖体 依据2018年7月17—18日鄱阳湖可采区采砂作业废水排放量和前后污染物浓度调查数据估算 旅游业 湖体湖区旅游导致的直接入湖负荷 根据《鄱阳湖生态旅游示范区规划纲要》和《鄱阳湖生态旅游专项规划》中的发展现状数据，采用旅游人数×游客用水系数(25 L/人)×污水排放系数(0.8)×污水中污染物浓度(总磷浓度为5 mg/L)估算 
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表 2 研究区主要基础数据信息
Table 2. Main data sources used over the study area
数据类型 尺度 属性 数据来源 GIS 数字高程(DEM) 90 m×90 m网格 高程、坡度、坡长 中国科学院资源环境科学数据中心(http://www.resdc.cn) 土地利用 30 m×30 m网格 土地利用分类 土壤类型 1 000 m×1 000 m网格 土壤类型及其理化特征 气象 雨量站 86个(2009—2018年) 逐日降水量 中华人民共和国水文局 气象站 26个(2009—2018年) 日最高、最低气温 国家气象科学数据中心(http://data.cma.cn) 水文 水文站 7个(2009—2018年) 日径流量 中华人民共和国水文局 水质 水质站 58个(2016—2017年) 逐月总磷浓度 江西省生态环境厅 产排污 点源 排污口(2016—2017年) 逐月污水厂运行数据、排污负荷量 江西省生态环境厅 面源 系数定值 产污系数、排污系数 《污染源普查产排污系数手册》、文献调研 社会经济 行政区 100个区县(2016—2017年) 人口、施肥、养殖、作物产量等 江西省11个地级市统计年鉴(2017—2018年) 其他 相关区域 2016—2017年 粪便秸秆还田率、内源释放量、候鸟数量等 实地调研、文献资料调查
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表 3 模型主要参数率定及模拟精度结果
Table 3. Model parameters calibrated and simulation accuracy
项目 参数率定值 模拟精度 点源系数 面源系数 河网密度系数 降雨系数 一级河流衰减系数 二级河流衰减系数 R2 NSE 2016年 年度 0.618 5 1.204 6 9.643 7 -0.000 49 0.588 6 0.241 1 0.88 0.86 丰水期 0.789 4 0.873 3 9.699 8 0.001 32 0.253 6 0.237 2 0.84 0.82 枯水期 0.521 1 1.517 4 10.280 2 -0.003 34 0.256 6 0.188 4 0.89 0.89 2017年 年度 0.969 5 1.243 0 8.167 3 0.000 40 0.599 0 0.257 5 0.86 0.86 丰水期 1.040 7 1.107 0 8.763 1 -0.000 12 0.353 9 0.123 0 0.81 0.81 枯水期 0.922 9 1.232 9 9.354 8 -0.002 86 0.241 7 0.263 8 0.88 0.87
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表 4 模型主要参数显著性和标准差分析结果
Table 4. Statistical significance and standard deviation of model parameters
项目 点源系数 面源系数 河网密度系数 降雨系数 一级河流衰减系数 二级河流衰减系数 P值 2016年 0.056 6 0.002 8 <0.001 0.326 9 0.038 6 0.167 8 2017年 0.019 5 0.004 8 <0.001 0.355 8 0.041 1 0.177 9 标准差 2016年 0.317 2 0.384 6 1.417 2 0.000 5 0.277 4 0.172 4 2017年 0.402 1 0.421 8 1.777 6 0.000 4 0.285 9 0.188 6
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