首页 | 本学科首页   官方微博 | 高级检索  
相似文献
 共查询到10条相似文献,搜索用时 93 毫秒
1.
Phytoplankton variation in large shallow eutrophic lakes is characterized by high spatial and temporal heterogenity. Understanding the pattern of phytoplankton variation and the relationships between it and environmental variables can contribute to eutrophic lakes management. In this study Taihu Lake, one of the largest eutrophic fresh water lake in China, was taken as study area. The water body of Taihu Lake was divided into five regions viz. Wuli bay (WB), Meilian Bay (MB), West Taihu Lake (WTL), Main Body of Taihu Lake (MBTL) and East Taihu Lake (ETL). Concentrations of chlorophyll-a and the related environmental variables were determined in each region in the period 2000–2003. Factor analysis and multivariate analysis were applied to evaluate the interactions between phytoplankton variation and environmental variables. Results showed that the highest average concentrations of TN, TP and Chl-a were observed in WB, followed in a descending order by MB and WTL, and the lowest concentrations of TN, TP and Chl-a were observed in MBTL and ETL. Chl-a and TP concentrations in most regions (except ETL) declined during the study period. It suggested that to some extent the lake was recovering from eutrophication. However, persistent ascending of TN and NH4–N in all five regions indicated the deteriorating of water quality in the study period. Results of multivariate showed that the relationships between phytoplankton biomass and environmental variables varied among regions. TP illustrated itself a controlling role on phytoplankton in WB, MB, WTL and MBTL according to the significant positive relations to phytoplankton biomass in these regions. Nitrogen could be identified as a limiting factor to phytoplankton biomass in ETL in view of the positive correlations between TN and phytoplankton and between NH4–N and phytoplankton. Spatial variation of interactions between phytoplankton and environmental parameters suggested proper eutrophication control measures were needed to restore ecological system in each region of Taihu Lake.  相似文献   

2.
A coupled three-dimensional hydrodynamic–ecological model was used for the assessment of water quality in Narva Bay during one biologically active season. Narva Bay is located in the south-eastern Gulf of Finland. Narva River with a catchment’s area covering part of Russia and Estonia discharges water and nutrients to Narva Bay. The ecological model includes phytoplankton carbon, nitrogen and phosphorus, chlorophyll a, zooplankton, detritus carbon, nitrogen and phosphorus, inorganic nitrogen, inorganic phosphorus and dissolved oxygen as state variables. Both the hydrodynamic and ecosystem models were validated using a limited number of measurements. The hydrodynamic model validation included comparison of time series of currents and temperature and salinity profiles. The ecological model results were compared with the monitoring data of phytoplankton biomass, total nitrogen and phosphorus and dissolved oxygen. The comparison of hydrodynamic parameters, phytoplankton biomass, surface layer total phosphorus and dissolved oxygen and near-bottom layer total nitrogen was reasonable. Time series of spatially mean values and standard deviations of selected parameters were calculated for the whole Narva Bay. Combining model results and monitoring data, the characteristic concentrations of phytoplankton biomass, total nitrogen and phosphorus and near-bottom dissolved oxygen were estimated. Phytoplankton biomass and total phosphorus showed seasonal variations, of 0.6–1.1 and 0.022–0.032 mg/l, respectively, during spring bloom, 0.1–0.3 and 0.015–0.025 mg/l in summer and 0.2–0.6 and 0.017–0.035 mg/l during autumn bloom. Total nitrogen and near-bottom oxygen concentrations were rather steady, being 0.25–0.35 and 2–6 mg/l, respectively. The total nitrogen and phosphorus concentrations show that according to the classification of Estonian coastal waters, Narva Bay water belongs to a good water quality class.  相似文献   

3.
Levels of selected metals Na, Ca, Mg, K, Fe, Mn, Cr, Co, Ni, Cd, Pb and Mn were estimated by flame atomic absorption spectrophotometry in groundwater samples from Kasur, a significant industrial city of Pakistan. Salient mean concentration levels were recorded for: Na (211 mg/l), Ca (187 mg/l), Mg (122 mg/l), K (87.7 mg/l), Fe (2.57 mg/l) and Cr (2.12 mg/l). Overall, the decreasing metal concentration order was: Na > Ca > Mg > K > Fe > Cr > Zn > Co > Pb > Mn > Ni > Cd. Significantly positive correlations were found between Na–Cr (r = 0.553), Na–Mn (r = 0.543), Mg–Fe (r = 0.519), Mg–Cr (r = 0.535), Pb–K (r = 0.506) and Pb–Ni (r = 0.611). Principal Component Analysis and Cluster Analysis identified tannery effluents as the main source of metal contamination of the groundwater. The present metal data showed that Cr, Pb and Fe levels were several times higher than those recommended for water quality by WHO, US-EPA, EU and Japan. The elevated levels of Cr, recorded as 21–42 fold higher compared with the recommended quality values, were believed to originate from the tanning industry of Kasur.  相似文献   

4.
A detailed study has been presented on heavy metal content of the Iture Estuary. Waters of the Sorowie and Kakum rivers that supply water into the Estuary were investigated to ascertain heavy metal pollution levels due to anthropogenic activities. Concentration s of Cd, Zn, Se and Pb were measured. The study shows pre-occupying pollution levels that constitute a threat to both terrestrial and aquatic ecosystems. The abundance of metals in the Estuary is in the order Zn > Pb > Cd > Se. The level of Cd in the Iture Estuary ranged between 0.011 mg/l and 0.041 mg/l while Se was in the range 0.018 mg/l to 0.029 mg/l, Pb 0.020 mg/l to 0.075 mg/l and Zn 0.040 to 2.45 mg/l. The impact of contaminated water from the Sorowie River on the Iture Estuary was outstanding and the study points out the importance of the Sorowie River as a primary pollution source to the Iture Estuary. The pollution of the Iture Estuary was found to be connected to human activities in its catchments.  相似文献   

5.
Management of stream nutrients is becoming increasingly important in order to protect both water quality and aquatic resources throughout the USA. Using an extensive water quality database from the long-term Maryland Biological Stream Survey (MBSS), we describe nutrient relationships to landscape characteristics as total nitrogen (TN) and total phosphorus (TP) of small-order, non-tidal streams in USEPA L2 and L3 ecoregions in Maryland and by MBSS stream order at the L2 and L3 ecoregion levels. To protect stream ecosystem integrity, preliminary reference nutrient estimates (TN and TP) as percentiles (25th of all stream reaches and 75th of stream reference reaches) for the six Maryland L3 ecoregions are: Blue Ridge TN 0.29 and 0.64 mg/L, TP 0.0065 and 0.0090 mg/L; Central Appalachians TN 0.40 and 1.0 mg/L, TP 0.0060 and 0.015 mg/L; Middle Atlantic Coastal Plains TN 0.93 and 2.5 mg/L, TP 0.094 and 0.065 mg/L; Northern Piedmont TN 1.6 and 1.8 mg/L, TP 0.010 and 0.015 mg/L; Ridge and Valley TN 0.40 and 0.98 mg/L, TP 0.0063 and 0.012 mg/L; and Southeastern Plains TN 0.33 and 0.82 mg/L, TP 0.016 and 0.042 mg/L. High levels of both TN and TP are present in many streams found in non-tidal watersheds associated with all Maryland ecoregions, but are especially elevated in the Northern Piedmont and Middle Atlantic Coastal Plain ecoregions, with the latter second-order streams (average TN?>?2.9 mg/L) significantly higher than all other ecoregion–order combinations. Across all six ecoregions, mean nutrient loading for both TN and TP was generally equivalent in first-order streams to nutrient concentrations seen in both second- and third-order streams, indicating a definite need to increase efforts in preventing nutrients from entering first-order streams. Small-order stream nutrient levels are the drivers for subsequent TN and TP inputs into the upper freshwater tidal reaches of the Chesapeake Bay, resulting in a potential risk for altered estuarine ecosystems.  相似文献   

6.
针对太湖湖滨带,均匀布设49个点位,分别于2009年12月、2010年4、8月开展浮游植物及水质监测。结果显示,湖滨带浮游植物群落多样性整体较低,优势种从枯水期到丰水期呈"鱼腥藻-鱼腥藻-微囊藻"的演变趋势;西北部湖区(竺山湖、梅梁湾、西部沿岸)浮游植物密度明显高于东南部湖区(东部沿岸、东太湖、南部沿岸);湖滨带浮游植物群落结构与湖体相似,密度比湖体高1个数量级;RDA排序筛选出在显著水平上解释浮游植物分布的最小变量组合为TN、CODMn、SS、p H、SD,且方差分解指出TN是相对最重要的变量;当物种适合度为50%~100%时,与TN具有较好梯度响应关系的是四尾栅藻及弓型藻,并且这2个种与TN、TP及综合营养状态指数的组合变量也有较好的梯度响应关系,具备指示太湖湖滨带富营养化的可能,但定量指示意义尚待进一步研究。  相似文献   

7.
Variability in horizontal zooplankton biomass distribution was investigated over 13 months in the Godavari estuary, along with physical (river discharge, temperature, salinity), chemical (nutrients, particulate organic matter), biological (phytoplankton biomass), and geological (suspended matter) properties to examine the influencing factors on their spatial and temporal variabilities. The entire estuary was filled with freshwater during peak discharge period and salinity near zero, increased to ~ 34 psu during dry period with relatively high nutrient levels during former than the latter period. Due to low flushing time (< 1 day) and high suspended load (> 500 mg L?1) during peak discharge period, picoplankton (cyanophyceae) contributed significantly to the phytoplankton biomass (Chl-a) whereas microplankton and nanoplankton (bacillariophyceae, and chlorophyceae) during moderate and mostly microplankton during dry period. Zooplankton biomass was the lowest during peak discharge period and increased during moderate followed by dry period. The zooplankton abundance was controlled by dead organic matter during peak discharge period, while both phytoplankton biomass and dead organic matter during moderate discharge and mostly phytoplankton biomass during dry period. This study suggests that significant modification of physico-chemical properties by river discharge led to changes in phytoplankton composition and dead organic matter concentrations that alters biomass, abundance, and composition of zooplankton in the Godavari estuary.  相似文献   

8.
于2007—2008年溪源水库蓄水前,2014—2015年溪源水库蓄水后对溪源宫水源地水体进行采样,分析了冬春季水体的理化指标、浮游植物生物量及群落组成。蓄水前共鉴定出浮游植物6门26属43种,水体水质状况较好,浮游植物细胞密度平均为7.31×10~5cells/L,以硅藻、绿藻门为优势门类,两者占浮游植物总生物量的比例约为54.7%、32.2%,水体呈贫-中营养状态。蓄水后,水体氮、磷营养盐浓度分别约为蓄水前的2.4倍、3倍,浮游植物细胞密度平均为1.42×10~7cells/L,约为蓄水前的20倍,且群落结构发生改变,优势门类为硅藻、蓝藻、绿藻,所占比例分别为40.2%、38.7%、14.4%,蓝藻门比例有显著提高,约为蓄水前的5倍。说明建库蓄水对浮游植物的影响显著。  相似文献   

9.
太湖氮磷大气干湿沉降时空特征   总被引:6,自引:0,他引:6  
为了探索太湖氮磷营养盐干湿沉降特征及对太湖营养盐输入的贡献,于2011年不同季节采集太湖不同位点的大气干湿沉降样品,分析干湿沉降中氮(N)和磷(P)的形态和沉降量。研究结果表明,输入太湖的磷以干沉降为主,而氮以湿沉降为主。在太湖干沉降中总无机氮(TIN)占总氮(TN)的77.1%,溶解性磷(DIP)占总磷(TP)的77.9%。干沉降中TIN主要以NH+4-N为主。西太湖是TN与TP通过大气干湿沉降输入太湖的最高湖区。太湖全年大气TN沉降总量为20 978 t,TP沉降总量为1 268 t,因此,氮磷大气干湿沉降是太湖营养盐输入的重要来源之一。  相似文献   

10.
2013年6月至2014年5月逐月对洞庭湖水体叶绿素a质量浓度和主要环境因子进行测定,分析洞庭湖水体叶绿素a质量浓度的时空分布特征,探讨洞庭湖水体叶绿素a质量浓度与环境因子的相关性。结果表明,洞庭湖水体叶绿素a质量浓度为0.11~8.62 mg/m~3,年均值为(1.89±1.23)mg/m~3,属贫营养;叶绿素a质量浓度随季节变化明显,总体呈现夏、秋季明显大于冬、春季的规律;在空间上,总体表现为西洞庭湖和东洞庭湖明显大于南洞庭湖。全湖叶绿素a质量浓度与水温、电导率、COD和TP呈极显著正相关,与DO、NH3-N、TN和TN/TP呈极显著负相关,与NO-3-N呈显著负相关,与p H和透明度无显著相关性。全湖TN/TP的年均值为28.5,磷可能是洞庭湖水体浮游植物生长的限制性营养盐。  相似文献   

设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号