Seasonal Impact of Agricultural Non-point Source Pollution on Water Environment of Dianshan Lake Basin in Shanghai City

Taken the Dalian lake region as the study area,which represents the typical agriculture production mode and agricultural non-point source pollution （ANSP） in Dianshan lake area in Shanghai City,basis on the characteristics of regional ANSP and combing with the seasonal water quality monitoring of Dalian Lake and reaches of its main influents,the laws of seasonal impact on the water environment were investigated.The results showed that,the seasonal change of TN and COD concentration of regional water had no significant correlation with the local ANSP emissions,while the seasonal changes of TP was consistent with seasonal emissions of regional TP pollution,and it had a significant correlation with Chl.a in four seasons,indicating that regional TP pollutant was the constriction factor influenced the eutrophication degree of Dalian lake.Because more than 80% of TP emissions came from the drainage of intensive pounds in winter,summer and fall,TP pollutant control should be adopted as the control target of regional ANSP control.

Impact of nutrient losses from agricultural lands on nutrient stocks in Dianshan Lake in Shanghai, China

Abstract： The water quality of Dianshan Lake in Shanghai Municipality, China, is impacted by nutrient losses from agricultural lands around the lake. In this study, nine types of agricultural land use were monitored in 2010 and 2011, and a correlation analysis between nutrient losses from agricultural non-point sources （NPS） and nutrient stocks in the lake was conducted over monthly and seasonal time periods. The results indicate that the monthly average concentration of total nitrogen （TN） ranged from 1.41 to 7.34 mg/L in 2010 and from 1.52 to 5.90 mg/L in 2011, while the monthly average concentration of total phosphorous （TP） ranged from 0.11 to 0.26 mg/L in 2010 and from 0.13 to 0.30 mg/L in 2011. The annual loss of TN from agricultural NPS was 195.55 tons in 2010 and 208.40 tons in 2011. The cultivation of water oat made the largest contribution to the loss of TN. The annual loss of TP was 44.58 tons in 2010 and 48.12 tons in 2011, and multi-vegetable cultivation made the largest contribution to the loss of TP. The results of correlation analysis show that the monthly stocks of TN and TP in the lake have a positive correlation with the monthly losses of TN and TP from agricultural NPS. According to the seasonal data, the stocks of TN and TP in the lake both have a much stronger correlation with the losses of TN and TP from agricultural NPS in summer than in other seasons. Agricultural NPS pollution control should be the main focus for the water resource conservation in this area.

Numerical simulation of an algal bloom in Dianshan Lake

A hydrodynamic model and an aquatic ecology model of Dianshan Lake,Shanghai,were built using a hydrodynamic simulation module and the water quality simulation module of Delft3D,which is an integrated modelling suite offered by Deltares. The simulated water elevation,current velocity,and direction were validated with observed data to ensure the reliability of hydrodynamic model. The seasonal growth of different algae was analyzed with consideration of observed and historical data,as well as simulated results. In 2008,the dominant algae in Dianshan Lake was Bacillariophyta from February to March,while it was Chlorophyta from April to May,and Cyanophyta from July to August. In summer,the biomass of Cyanophyta grew quickly,reaching levels much higher than the peaks of Bacillariophyta and Chlorophyta. Algae blooms primarily occurred in the stagnation regions. This phenomenon indicates that water residence time can influence algal growth significantly. A longer water residence time was associated with higher algal growth. Two conclusions were drawn from several simulations: reducing the nutrients inflow had little effect on algal blooms in Dianshan Lake; however,increasing the discharge into Dianshan Lake could change the flow field characteristic and narrow the range of stagnation regions,resulting in inhibition of algal aggregation and propagation and a subsequent reduction in areas of high concentration algae.

Hyper-spectrum models for monitoring water quality in Dianshan Lake,China

The correlation between water quality parameters and hyper-spectral reflectance is studied with models established for each parameter and applied in Dianshan Lake, in the upstream of the Huangpu River running through Shanghai, China. Models are for dissolved oxygen (DO in mg/L): R720/R680 = 20.362×(R720/R680)2?31.438×(R720/R680)+19.156; for turbidity (NTU): R*714.5 = 206.07× (R*714.5)2?582.5×R*714.5 + 423.24; and for total phosphorus (TP in mg/L): R*509.5 = 16.661× (R*509.5)2?32.646×R*509.5+16.116. The R2 values are 0.770 8, 0.660 4 and 0.738 7, respectively, showing strong positive relationships. The models were then applied to assess water quality of different times. Results are quite satisfactory for some samples.

CO_2 emission from Dianshan Lake in summer,East China

Shallow fresh water bodies in peat areas could be an important contributor to greenhouse gases in the atmosphere.In this study,the partial pressure of CO2 in the surface water of the Dianshan Lake was investigated insitu in August 2011.The average pCO2 in the study area was 2300μatm and fluctuated within the range of 989–5000μatm.pCO2 showed a reverse trend to the variations of pH and DO in the surface water of the Dianshan Lake.The water to air diffusion flux of CO2 of the upstream,middle lake and downstream were respectively 63,33 and 14mmol/m2/d.On average,the diffusion flux of CO2 of the whole lake was 31 mmol/m2/d.Consequently,our results show that during the sampling season,the Dianshan Lake appears to be a great source of CO2.It is also demonstrated that respiration could be the dominant biochemical reaction in the Dianshan Lake in summer.

Study on the Spatial and Temporal Distribution of Blue Algae in Lake Dianshan in Summer

To understand the spatial and temporal variation characteristics of blue algae in summer in Lake Dianshan,the phytoplankton in Lake Dianshan from June to September in 2009 was surveyed. It found 11 genera and 28 species blue algae in total. Microcystis,Oscillatoria and Chroococcus were the main composition communities of blue algae in Lake Dianshan in summer. In the survey period,the average density of blue algae in Lake Dianshan was 16.48×106 cells/L which changed during 1.01×106-59.76×106 cells/L. The characteristics were:September > July > August > June. The mass propagation and aggregation of Microcystis in September caused that the water blooms phenomenon in the partial water areas was serious. In the space,the average density of blue algae in the west and southwest parts of Lake Dianshan was bigger than in the east and southeast. When the nutritive matter was sufficient,the temperature was the main factor which affected the generation and disappearance of blue algae water blooms. The wind direction was also an important factor which affected the distribution of blue algae.

How to Purify a Polluted Lake Quickly—A Case Study from Shanghai, China

Water pollution has become a serious worldwide problem, especially for lakes with a large stagnant water body. Is it possible to develop high quality water from a heavily polluted river system quickly? This paper introduces an innovative technology termed SPP (separation, prevention and protection) for this purpose. Its feasibility is preliminarily examined using Dianshan Lake in Shang- hai as an example. Due to its very high population density and intensive industrial activities, almost all waterways in Shanghai are heavily polluted, including the lake. However, the data analysis shows that clean water always appears after heavy rains, especially in its suburban areas. Once the 1st flush water is discharged to downstream, high-quality water can be developed from its Dianshan Lake by using the SPP strategy. The Vollenweider model is used to analyze SPP’s feasibility. The results show that the water quality of the Dianshan Lake can be remediated as a drinking water source within 120 days if the SPP strategy is applied. It is suggested that Jinze reservoir’s water should come from the Dianshan lake, not Taipu River to improve the quality of water supply. It is highly recommended for other cities in the world to consider the SPP technology if needed.

上海黄浦江水系常见鱼类重金属含量及健康风险评价

黄浦江是兼具饮用水源、航运、排洪排涝、渔业、旅游等功能的上海“母亲河”,鱼类资源丰富。为了解黄浦江水系鱼类重金属污染状况,测定了黄浦江水系15种优势鱼类和主要经济鱼类肌肉中Cu、Zn、Fe、Mn、Pb、Cd、Cr、As、Hg的含量。结果表明,除As外,所有鱼体中的重金属含量均低于国家标准限值或农业行业标准限值。综合污染指数分析结果显示:淀山湖水域翘嘴鲌、大鳍■为重金属中度污染(2.03.0);苏州河水域翘嘴鲌、兴凯■为中度污染,大鳍■为重度污染。健康风险分析结果显示,除As外,Cu、Zn、Pb、Cd、Cr、Hg、Mn等的健康风险指数均小于1,对人群的健康风险不显著。复合重金属危害系数(TTHQ)分析结果显示:黄浦江水域似鳊的TTHQ值为0.957;苏州河水域光泽黄颡鱼、刀鲚、似鳊、翘嘴鲌、■、大鳍■、日本鳗鲡、兴凯■的TTHQ值均大于1;淀山湖水域泥鳅的TTHQ值接近1,翘嘴鲌、黄颡鱼、■、大鳍■的TTHQ值大于1。以上鱼类均存在复合重金属健康风险。目前,淀山湖水域仍有专业渔民开展捕捞作业,因此,应对当地居民重金属健康风险作长期监测。

淀山湖沉积物微生物群落结构特征及影响因素

湖泊沉积物微生物多样性及群落结构关系到水质与水生态系统稳定。采用高通量测序技术分析了淀山湖表层沉积物中微生物群落的结构特征及影响因素。结果表明:淀山湖沉积物受人为活动影响显著,其中Cd的污染程度较高。不同区域物种多样性表现为湖西南区>湖北区>湖中区>湖东区。从门水平来看,优势门类主要为Proteobacteria、Chloroflexi和Acidobacteriota等;从属水平分析,优势菌属集中在uncultured_f__Anaerolineaceae、unclassified_c__Thermodesulfovibrionia和uncultured_f__Steroidobacteraceae。优势微生物与环境因子的相关性分析表明,TN、TP、Cd、Sb、Cu和Zn对微生物群落结构影响较大,TP和重金属是群落结构的制约因素。此外,uncultured_f__Anaerolineaceae、unclassified_o__Vicinamibacterales和Luteitalea属对Cd、Sb、Cu、Ni和Zn表现出耐受性。预防磷和重金属污染输入,加强对微生物的监测是淀山湖水环境保护的重点。

天空地一体立体网络的水质遥感监测及其溯源初探——以淀山湖为例

利用卫星遥感、无人机和走航船等手段组成的天空地一体化立体水质监测网络对淀山湖水质进行监测,并对水质参数的空间分布进行溯源分析。结果表明:(1)构建的水质参数反演模型实现了对淀山湖区域高精度的水质反演。其中总磷质量浓度反演结果的均方根误差(RMSE)为0.0191 mg/L,决定系数(R^(2))=0.64(P<0.001);氨氮质量浓度反演结果的RMSE为0.0360 mg/L,R^(2)=0.83(P<0.001);(2)水质空间分布特征为淀山湖总磷和氨氮浓度均表现为西北高,中部和东西低;叶绿素a浓度呈现出北高南低、东高西低及岸边高、中心低的空间分布特征;(3)通过广义线性混合模型对淀山湖水质空间分布进行溯源分析发现,入湖支流、动力船只、农田和水生植物对淀山湖总磷、氨氮和叶绿素a浓度的分布格局均有显著影响,其中入湖支流的影响最大。该研究结果可为上海市水环境立体监测提供重要参考和科学依据。

2016-2020年淀山湖总磷的时空变化特征及成因分析

本文分析了2016-2020年淀山湖总磷及磷酸盐的年度变化、季节变化和空间分布特征,同时分析了总磷及磷酸盐与其他环境要素的相关性。结果表明受上游来水和沉水植物的影响,淀山湖近五年总磷呈现波动下降的年变化趋势;季节变化整体呈现冬春低,夏秋高的趋势,每年6月份开始上升,8月或9月出现浓度最高值,10月份后开始下降;受上游来水和流场的影响,空间上呈现北高南低、西高东低的分布特征。

基于InVEST模型的淀山湖片区生境质量评估及景观优化研究

随着城市化和农业规模化加剧,自然流域遭到破坏,生态环境面临严重威胁。基于开源软件InVEST模型对淀山湖片区2015年和2022年的生境质量进行评估。结果表明,城市化与农业扩张对生态系统造成了较大影响,导致淀山湖生境质量整体下降。针对不同的威胁因素与退化程度,总结出5种景观优化策略,并以柳河上游沿岸为例,进行景观设计改造。总体上说,采用的生态模型评估方法提供了淀山湖片区生境质量的时空分布信息,并以案例设计为决策者提供参考,有助于改进城市规划和发展,促进城市河湖沿线生境保护。

淀山湖“一湖一策”水环境保护及治理浅析

调研淀山湖水质及环境现状,结合区内水利工程现状,坚持“保护优先、系统治理、分类指导、共建共享”原则,分析淀山湖在开发利用中存在的主要问题,提出治理对策,以促进“一湖一策”方案落地生效,建设生态美丽淀山湖。

淀山湖水质变化趋势分析及其对蓝藻水华暴发影响因素浅析

本研究基于2001年至2023年淀山湖气象和水质等数据,对淀山湖水质变化趋势及其对蓝藻水华暴发的影响进行了分析。在过去20年中,淀山湖的风速呈现低风速变化趋势,而气温、日照时数、降雨量无显著趋势变化。水质方面,水温无显著趋势变化,总氮、氨氮、高锰酸盐指数、化学需氧量的浓度呈显著下降趋势,而总磷浓度则经历了先下降后升高的趋势;淀山湖叶绿素a浓度总体呈先下降再上升趋势,蓝藻密度呈现先平稳上升,后显著上升的趋势。淀山湖的水质呈现逐步改善的趋势,但氮磷浓度依然较高,是利于藻类生长的藻型生境。既使气温、光照和风力等外部条件适宜,淀山湖发生藻华的可能性仍然存在。

淀山湖夏季微囊藻毒素分布状况及其影响因素

为了解淀山湖夏季微囊藻毒素的昼夜、区域、垂直分布状况及其影响因素，在淀山湖上选择１１个采样点，每个采样点设４个采样深度，进行２４ｈ的４次采样．测定水样中总氮（ＴＮ），总磷（ＴＰ），微囊藻毒素（ＭＣ）浓度，同时记录采样时的水温（ＴＥＭ）、ｐＨ值、可见度（ＶＤＷＢ）、风向、风速．结果表明，ＭＣ分布具有明显的昼夜、区域差异，早晨和下午最高，西南水域明显低于其他区域，体现了光照、空气流动对ＭＣ分布的影响，同时ＭＣ的分布与总磷、ｐＨ值、可见度呈正相关（Ｐ＜０．０５），多因素分析显示，除光照、空气流动外，影响湖水ＭＣ分布的最主要因素为湖水可见度和水中总磷的含量．表明光照、空气流动、水体总磷含量是影响夏季淀山湖水体ＭＣ分布的主要原因．

淀山湖轮虫多样性及生物量时空变化

研究了2004年1月至2006年12月淀山湖轮虫种类组成、生物量的时空变化，并分析了水温、叶绿素a与轮虫生物量的关系。结果表明：3年共检出轮虫53种（属），平均生物量为2514ind·L^-1或2．94mg·L^-1，轮虫优势种为针簇多肢轮虫、角突臂尾轮虫、萼花臂尾轮虫、螺形龟甲轮虫、曲腿龟甲轮虫、长三肢轮虫、椎尾水轮虫等，2004、2005、2006年轮虫密度中优势种所占的比例分别为82．2％、82．7％和78．8％。轮虫最高密度出现在2005年3月马兰港（St6），达11700ind·L^-1。3年中轮虫生物量季节变化趋势一致：春季（4862ind·L^-1和5．45mg·L^-1）〉秋季（2300和3．45）〉夏季（1773和1．88）〉冬季（940和0．45）；轮虫生物量水平分布表现为湖心（St4）〉金家庄和水上运动场附近（St2）〉马兰港（St6）〉淀峰（St1）〉急水港进水口（St5）〉千墩湾网围区（St3）。3年轮虫平均多样性指数H为2．27（变幅为2．08～2．50），2006年轮虫H值显著低于2004年。淀山湖轮虫密度与水体叶绿素a含量呈显著相关。

淀山湖浮游动物的群落结构及动态

为帮助利用生物操纵技术进行淀山湖水体富营养化治理,2004年1月至2005年12月对淀山湖浮游动物群落结构,包括种类组成、种群动态、现存量进行了2周年的系统调查。淀山湖浮游动物有128种,其中浮游原生动物23属29种、轮虫23属51种、枝角类15属33种、桡足类15种。年均密度6 965ind/L,原生动物和轮虫分别占62.19%和36.77%,密度高峰出现在春季;生物量年均为6.00 mg/L,以轮虫和枝角类占优势,分别占51.65%和38.38%,生物量高峰出现在夏季。4个类群浮游动物多样性指数H′与其均匀度指数J呈显著正相关,原生动物群落多样性指数H′与其密度呈显著负相关。根据浮游动物密度及优势种组成特征判断,淀山湖水质为富营养型。原生动物多样性指数具有较好的水质指示作用。

淀山湖水体叶绿素a与水质因子的多元分析

根据2004年1月-2006年12月逐月对淀山湖水体叶绿素a含量及水质理化因子的测定结果，分析了叶绿素a的时空分布，评价了淀山湖水体营养状态，找出与叶绿素a显著相关的环境因子，并建立了多元逐步回归方程。3年期间，淀山湖叶绿素a含量均值为29．98mg／m^3，变幅3．48—141．63mg／m^3；每年分别在4—5月和7—9月出现峰值；水平分布上，Ⅱ站点金家庄附近叶绿素a含量最高，Ⅴ站点进水日和Ⅰ站点出水日含量较低。基于叶绿素a、透明度和总磷等参数，依据修正的卡尔森营养状态指数公式，计算得出淀山湖TSI平均值为71．6（〉53），全湖处于富营养化状态。应用SPSSWin和DPS等统计分析软件进行相关性分析结果表明叶绿素a与水温、pH、高锰酸盐指数、BOD5、硝酸氮呈极显著相关，而与磷酸盐呈极显著负相关；与氨氮、亚硝酸氮呈显著相关，而与总磷呈显著负相关。综合逐步回归方程表明，影响淀山湖叶绿素a的主要环境因子有高锰酸盐指数、BOD5、硝酸氮、溶氧、透明度和水温。

基于营养通道模型的淀山湖生态系统结构与能量流动特征

根据2008-2009年间对淀山湖湖区水生生物资源调查的结果,运用Ecopath with Ecosim 6.1软件构建了淀山湖生态系统的营养通道模型,初步分析了淀山湖水域生态系统的结构和能量流动特征。模型中涉及水鸟、鱼类、虾类、软体动物、底栖动物、浮游动物、浮游植物、碎屑等21个功能组分,基本涵盖了淀山湖生态系统的主要能量流动过程,分析结果表明,淀山湖生态系统总流量为4 098.50 t·km-2.a-1。从混合营养效应分析来看,渔业捕捞会对该生态系统的鱼类功能组产生负效应。生态网络分析显示,淀山湖生态系统各功能组的营养级范围为1～3.92,水鸟占据了营养层的最高层。系统的能量流动主要有5级,各营养级之间平均能量转换效率为11.7%。淀山湖生态系统的整体再循环率较低,能量利用效率有待改善和提高。生态系统参数:系统初级生产力/总呼吸量(TPP/TR)、连接指数CI和能量循环指数FCI分别为2.80、0.19和0.0189,表明淀山湖生态系统目前仍然处于幼态化生态系统状态。