Water quality monitoring and assessment of an urban Mediterranean lake facilitated by remote sensing applications

Degradation of water quality is a major problem worldwide and often leads to serious environmental impacts and concerns about public health. In this study, the water quality monitoring and assessment of the Koumoundourou Lake, a brackish urban shallow lake located in the northeastern part of Elefsis Bay (Greece), were evaluated. A number of water quality parameters (pH, temperature, dissolved oxygen concentration, electrical conductivity, turbidity, nutrients, and chlorophyll-a concentration) were analyzed in water samples collected bimonthly over a 1-year period from five stations throughout the lake. Moreover, biological quality elements were analysed seasonally over the 1-year period (benthic fauna). Statistical analysis was performed in order to evaluate the water quality of the lake and distinguish sources of variation measured in the samples. Furthermore, the chemical and trophic status of the lake was evaluated according to the most widely applicable classification schemes. Satellite images of Landsat 5 Thematic Mapper were used in order for algorithms to be developed and calculate the concentration of chlorophyll-a (Chl-a). The trophic status of the lake was characterized as oligotrophic based on phosphorus and as mesotrophic–eutrophic based on Chl-a concentrations. The results of the remote sensing application indicated a relatively high coefficient of determination (R ²) among point sampling results and the remotely sensed data, which implies that the selected algorithm is reliable and could be used for the monitoring of Chl-a concentration in the particular water body when no field data are available.     

Water Quality Changes in Chini Lake, Pahang, West Malaysia

A study of the water quality changes of Chini Lake was conducted for 12 months, which began in May 2004 and ended in April 2005. Fifteen sampling stations were selected representing the open water body in the lake. A total of 14 water quality parameters were measured and Malaysian Department of Environment Water Quality Index (DOE-WQI) was calculated and classified according to the Interim National Water Quality Standard, Malaysia (INWQS). The physical and chemical variables were temperature, dissolved oxygen (DO), conductivity, pH, total dissolved solid (TDS), turbidity, chlorophyll-a, biochemical oxygen demand (BOD), chemical oxygen demand (COD), total suspended solid (TSS), ammonia-N, nitrate, phosphate and sulphate. Results show that base on Malaysian WQI, the water in Chini Lake is classified as class II, which is suitable for recreational activities and allows body contact. With respect to the Interim National Water Quality Standard (INWQS), temperature was within the normal range, conductivity, TSS, nitrate, sulphate and TDS are categorized under class I. Parameters for DO, pH, turbidity, BOD, COD and ammonia-N are categorized under class II. Comparison with eutrophic status indicates that chlorophyll-a concentration in the lake was in mesotrophic condition. In general water quality in Chini Lake varied temporally and spatially, and the most affected water quality parameters were TSS, turbidity, chlorophyll-a, sulphate, DO, ammonia-N, pH and conductivity.     

Selection of appropriate sampling stations in a lake through mapping

Much valuable information is obtained from water quality measurements and monitoring of lakes around the world. A powerful tool is the use of mapping techniques, as it offers potential use in water quality research. Both remote sensing techniques and traditional water quality monitoring are required to collect data at sampling stations. This study suggests another approach to determine the most appropriate distribution of sampling stations in water reservoirs that will be mapped for water quality parameters. Tests were conducted for the proposed approach for Secchi disc depth (SDD), chlorophyll-a, turbidity and suspended solids parameters in Lake Beysehir, Turkey. Results of analysis are available for a total of 30 sampling stations in August 2006. Ten sampling stations were used to model Lake Beysehir while the others were used for validation of the model. Sampling stations that offered the best representation of the lake for each parameter were determined. Then, the best representative sampling stations for all parameters in the study were determined. Moreover, in order to confirm the accuracy of these re-determined sampling stations, modelling was performed on the results of the analysis of June 2006, and it was found that the values obtained from the re-determined sampling stations were acceptable.     

洋河水库水质主成分分析

自20世纪80年代以来,洋河水库每年夏季都爆发“水华”现象,水质不断恶化。为研究水库水体水质年变化情况,于2005年对水库5个采样点的叶绿素a(Chl-a)、总磷(TP)等12项水化学指标进行为期1年的监测。采用基于因子分析的主成分分析方法,将洋河水库水质参数概括为5个主要成分,并分析各个主成分的含义以及其月均值随时间的变化规律。最后结合空间数据,分析了5个主成分年均值的空间分布特征和意义。结果表明,南库区的水质要明显好于北库区。     

Fuzzy Logic Model to Estimate Seasonal Pseudo Steady State Chlorophyll-A Concentrations in Reservoirs

A fuzzy logic model is developed to estimate pseudo steady state chlorophyll-a concentrations in a very large and deep dam reservoir, namely Keban Dam Reservoir, which is also highly spatial and temporal variable. The estimation power of the developed fuzzy logic model was tested by comparing its performance with that from the classical multiple regression model. The data include chlorophyll-a concentrations in Keban lake as a response variable, as well as several water quality variables such as PO₄ phosphorus, NO₃ nitrogen, alkalinity, suspended solids concentration, pH, water temperature, electrical conductivity, dissolved oxygen concentration and Secchi depth as independent environmental variables. Because of the complex nature of the studied water body, as well as non-significant functional relationships among the water quality variables to the chlorophyll-a concentration, an initial analysis is conducted to select the most important variables that can be used in estimating the chlorophyll-a concentrations within the studied water body. Following the outcomes from this initial analysis, the fuzzy logic model is developed to estimate the chlorophyll-a concentrations and the advantages of this new model is demonstrated in model fitting over the traditional multiple regression method.     

三峡库区大宁河回水段水华暴发时空分布特征分析

对三峡库区一级支流大宁河巫山段2004年到2008年常规监测、水华期间加密监测以及单个测点水华垂线24小时监测数据进行了统计、分析及评价。结果发现,该河段水华暴发具有明显的时空分布特征,时间上,全年各月份均有出现,但主要集中在3～6月,占观测频次的79%;24小时内叶绿素a含量在下午16:00～18:00时间段内达到最大值;空间上,总体呈现出离入长江口越近暴发的频次越高,回水河湾较平直河道,宽阔河段较狭窄河段更重的趋势,主要集中在大宁河的开阔河段(小三峡三个峡谷之间及其上、下游开阔河段);24小时内水华垂线分布明显,0.5～5m的叶绿素a含量上层高于下层,水面下30m及以下区域叶绿素a含量变化不显著。     

宁波市饮用水源地爆发蓝藻水华时微囊藻毒素的污染分析

通过固相萃取净化,建立了超高效液相色谱-串联四极杆质谱法测定水中微囊藻毒素MC-LR和MC-RR的方法,并用该方法监测了宁波市两个饮用水源地爆发蓝藻水华时水体中的微囊藻毒素.监测结果表明,姚江水体中的微囊藻毒素污染水平低,MC-LR和MC-RR没有被检出;梅湖水库水体中MC-RR也未被检出,采取措施后,虽MC-LR有时被检出,但最高时也低于国家标准值(1.0μg/L).     

Long-term trends and short-term variability of water quality in Skive Fjord, Denmark – nutrient load and mussels are the primary pressures and drivers that influence water quality

Nineteen years of monitoring data from the eutrophic Skive Fjord, Denmark were examined for linkages to external pressures and drivers, including nutrient inputs, meteorology and stocks of blue mussels. Linkages were examined by: 1) time-series analysis to document effects of nutrient reduction programs, 2) Pearson Rank correlations, 3) multivariate statistical analysis (PLS) to identify water quality variables with high predictability and their linkages to pressures, and 4) regression analysis to quantify relationships between pressures and water quality. Freshwater input, nitrogen load and phosphorus load showed decreasing trends through the period 1984–2002. The load reductions were only partially translated into trends in water quality: phosphorus decreased in most seasons, while total nitrogen decreased during winter and spring only. Phosphorus concentration had the highest predictability (explained by seasonal temperature variation) followed by transparency, silicate, tot-N, chlorophyll-a, primary productivity, phytoplankton diversity and phytoplankton turnover. The variation in pressures other than nutrient input confounded the relations between loads and water quality. High biomass of mussels led to reduced chlorophyll-a and increased transparency, while short-term variability in water column mixing led to changes in chlorophyll-a due to nutrient entrainment and coupling to benthic mussels.     

Microcystins and cyanobacteria trends in a 14 year monitoring of a temperate eutrophic reservoir (Aguieira, Portugal)

A monitoring program of cyanobacteria and cyanotoxins in the framework of the surveillance of the Water Treatment Plant efficiency of the municipality of Santa Comba D?o (Portugal) was conducted from 1994 until 2007. With these data we aimed to answer the question, are MCs produced evenly over the years in a single water body? Samples were taken by the local health authorities in the site of the Water treatment plant and analyzed for total phytoplankton, cyanobacteria and the hepatotoxic cyanotoxins microcystins (MCs). Apart from 1999 and 2000, cyanobacteria represented a high proportion of total phytoplankton, attaining during several months of the year more than 90% of total phytoplankton density. A total of 24 cyanobacteria species were identified and Microcystis aeruginosa, Anabaena flos-aquae and Aphanizomenon flos-aquae were the main potentially toxic cyanobacteria species present throughout the period. MC concentration varied between 0.3 μg MC-LR eq l?1 in October 98 and 87.0 μg MC-LR eq l?1 in September 2001. The evolution of the average cell quota does not reveal any especial trend, although in 2001 the quota was the highest but not significantly different from the other years. The threshold limit of 5000 cells per ml of Microcystis aeruginosa should be taken into consideration in monitoring programs because the 10,000 cells per ml proposed by several other national programs might not be enough to prevent human health risks. Due to high annual variation in MC cell quota, monitoring programs of cyanobacteria and MC should be extended in time, since short term studies do not provide us the data needed for a safe management of a water body used for human purposes.     

Determination of chlorophyll-a amount in Golden Horn, Istanbul, Turkey using IKONOS and in situ data

The objective of this research was to explore an accurate and fast way of estimating chlorophyll-a amount, a water quality parameter (WQP), using IKONOS satellite sensor image and in situ measurements. Since the in situ data of WQPs are limited with the number of sampling locations, deriving a correlation between these measurements and remotely sensed image allows synoptic estimates of the related parameter over large areas even if the areas are in remote and inaccessible locations. In this study, simultaneously collected satellite image data and in situ measurements of chlorophyll-a were correlated using multivariate regression model. Different experiments were designed by changing the numbers and distributions of in situ measurements. Regression coefficients of each design and differences between model-derived data and in situ measurements were calculated to find out the optimum design to produce chlorophyll-a map of study region. Results illustrated that both the number and distribution of in situ measurements have impact on regression analysis, therefore should be selected attentively. Also, it is found that IKONOS imagery is an efficient and effective source to derive chlorophyll-a map of the large areas using limited number of ground measurements.