Inter- and Intra-Annual Chemical Variability During the ice-Free Season in Lakes with Different Flushing Rates and Acid Deposition Histories

Quantifying chemical variability in different lake types is important for the assessment of both chemical and biological responses to environmental change. For monitoring programs that emphasize a large number of lakes at the expense of frequent samples, high variability may influence how representative single samples are of the average conditions of individual lakes. Intensive temporal data from long-term research sites provide a unique opportunity to assess chemical variability in lakes with different characteristics. We compared the intra- and inter-annual variability of four acidification related variables (Gran alkalinity, pH, sulphate concentration, and total base cation concentration) in four lakes with different flushing rates and acid deposition histories. Variability was highest in lakes with high flushing rates and was not influenced by historic acid deposition in our study lakes. This has implications for the amount of effort required in monitoring programs. Lakes with high flushing rates will require more frequent sampling intervals than lakes with low flushing rates. Consideration of specific lake types should be included in the design of monitoring programs.     

The feasibility of monitoring wilderness lake chemistry with remote sensing methods

Wilderness lakes in the U.S. are at risk to the effects of atmospheric pollution. The results of the EPA Western Lake Survey, for example, show that many of the lakes in the West have very low concentrations of dissolved constituents, and are sensitive to acidification. Lakes located in wilderness areas were found to be particularly sensitive: median ANC values of 91.4 eq/1 compared to 282.7 eq/1 in non-wilderness areas. Sampling remote wilderness lakes is difficult and expensive. For example, the cost of sampling each lake in the National surface water survey was about $ 4000 per lake. Remote sensing methods may provide an alternative means of monitoring the chemistry of wilderness lakes. This study defines the feasibility of the remote monitoring of lake chemistry in the Adirondack Park region of New York by comparing measured lake chemistry with field reflectance measurements, remote reflectance measurements from aircraft and satellite and laboratory and airborne laser fluorosensor data.Water samples collected from a representative population of Adirondack Park lakes were analyzed for pH, acid neutralizing capacity (ANC), dissolved organic carbon (DOC), total reactive aluminum and plant pigment concentration concurrent with the collection of remote sensing data. Lake parameters estimated from field reflectance measurements which directly effect lake optical properties, total pigments, DOC, and turbidity were estimated with less error and more precision than those parameters not directly related to lake optics, pH, ANC and A1 concentration. Results from airborne MSS and Landsat MSS data produced lower R² values than estimates using field reflectance.The concentration of DOC can be estimated remotely by using laser fluorosensing. The spectral-fluorescence properties of DOC were correlated with the pH and aluminum concentrations in the lake water. Remotely measurable DOC fluorescence spectra were used to estimate DOC, H, and A1 concentrations.Of the methods investigated, laser fluorosensing shows the most promise for the remote prediction of lake DOC, hydrogen ion and aluminum concentration in Adirondack lakes while reflectance measures may be used to estimate lake chlorophyll, DOC and transparency. Given the large number of wilderness lakes and the difficulty of sampling in remote wilderness, remote sensing methods may provide an alternative, while less precise, method of monitoring lake chemistry. The applicability of these findings to lakes in other wilderness areas is unknown. Similar studies of the feasibility of monitoring Western wilderness lake chemistry with remote sensing methods are being initiated.Supported by an A. W. Mellon Foundation Grant to Dr. G. E. Likens while a student in the Section of Ecology and Systematics, Cornell University, Ithaca, NY and a Fellow of the Institute for Ecosystem Studies, New York Botanical Garden, Mary Flagler Cary Arboretum, Millbrook, NY.Contribution from Fourth World Wilderness Congress-Acid Rain Symposium, Denver (Estes Park), Colorado, September 11–18, 1987.     

Issues in monitoring wilderness lake chemistry: A case study in the Sawtooth Mountains,Idaho

A probability-based sample of 48 of the 152 lakes in the Sawtooth Wilderness, Idaho was conducted in summer 1988. Results from this sample were compared to the Environmental Protection Agency's 1985 probability survey of lakes throughout the western United States, which included 17 lakes in the Sawtooth Wilderness. Although methods differed in several respects, including year, season, sampling location within the lakes, holding times, and sample size, general characterization of lake chemistry for the population of lakes in the wilderness based on the two surveys was very similar. The results indicate that general lake characterization in difficult-to-access wilderness areas of the West can be achieved with a modest investment in resources with the use of volunteers. However, accurate measurement of some non-conservative and low-level analytes such as NO ₃ ^– ,NH ₄ ⁺ , total P, and aluminiun in the lakes probably requires more rigorous attention to sampling protocols and holding times. A two-stage sampling strategy employing extensive use of conductivity on a large number of lakes and intensive detailed chemical characterization on a smaller number of lakes offers an alternative design for describing large populations of wilderness lakes. The relatively high concentrations of fluoride and sulfate in many of the study lakes reflect the weathering of minerals not usually identified on geologic maps. These natural sources of acid anions violate the assumptions in commonly employed empirical models of acidification.     

Temporal and spatial trends in water quality of Lake Taihu,China: analysis from a north to mid-lake transect, 1991–2011

Interpretations of state and trends in lake water quality are generally based on measurements from one or more stations that are considered representative of the response of the lake ecosystem. The objective of this study is to examine how these interpretations may be influenced by station location in a large lake. We addressed this by analyzing trends in water quality variables collected monthly from eight monitoring stations along a transect from the central lake to the north in Lake Taihu (area about 2,338 km²), China, from October 1991 to December 2011. The parameters examined included chlorophyll a (Chl a), total nitrogen (TN), and total phosphorus (TP) concentrations, and Secchi disk depth (SD). The individual variables were increasingly poorly correlated among stations along the transect from the central lake to the north, particularly for Chl a and TP. The timing of peaks in individual variables was also dependent on station location, with spectral analysis revealing a peak at annual frequency for the central lake station but absence of, or much reduced signal, at this frequency for the near-shore northern station. Percentage annual change values for each of the four variables also varied with station and indicated general improvement in water quality at northern stations, particularly for TN, but little change or decline at central lake stations. Sediment resuspension and tributary nutrient loads were considered to be responsible for some of the variability among stations. Our results indicate that temporal trends in water quality may be station specific in large lakes and that calculated whole-lake trophic status trends or responses to management actions may be specific to the station(s) selected for monitoring and analysis. These results have important implications for efficient design of monitoring programs that are intended to integrate the natural spatial variability of large lakes.     

A Screening Procedure for Identifying Acid-Sensitive Lakes from Catchment Characteristics

Monitoring of Wilderness lakes for potential acidification requires information on lake sensitivity to acidification. Catchment properties can be used to estimate the acid neutralizing capacity (ANC) of lakes. Conceptual and general linear models were developed to predict the ANC of lakes in high-elevation (2170 m) Wilderness Areas in Californias Sierra Nevada mountains. Catchment-to-lake area ratio, lake perimeter-to-area ratio, bedrock lithology, vegetation cover, and lake headwater location are significant variables explaining ANC. The general linear models were validated against independently collected water chemistry data and were used as part of a first stage screen to identify Wilderness lakes with low ANC. Expanded monitoring of atmospheric deposition is essential for improving the predictability of lake ANC.     

A feasible method to assess inaccuracy caused by patchiness in water quality monitoring

Patchiness is a typical property of water quality in lakes. However, in conventional water quality monitoring, patchiness is usually too expensive to take into account, due to the high number of required samples. This study examines a feasible methodology developed for estimating the representativeness of discrete chlorophyll a measurements. Four spatially extensive data sets were collected from the Enonselkä basin of Lake Vesijärvi in Southern Finland, using a flow trough system with a fluorometer in a moving boat. Data sets were used to estimate (1) the spatial representativeness of discrete sampling; (2) the effect of varying sample size on the detected mean chlorophyll a concentration and on the observed proportion of variance. Spatial representativeness was assessed using semivariogram analysis. Results indicate that the spatial representativeness of discrete sampling can remain undesirably low. Furthermore, in monitoring programs involving just one or only a few samples, there is a significant risk of obtaining a false estimate for the mean value and variance of chlorophyll a concentration over the whole monitoring area.     

地表水环境遥感监测关键技术与系统

介绍了地表水环境遥感监测的关键技术与系统及其典型应用,其代表性机理模型和应用示范成果主要来自于中国科学院遥感与数字地球研究所的高光谱遥感团队在最近几年中取得的一些研究进展,主要包括建立了基于改进双峰法的水体分布自动化遥感提取方法,实现了简单、高效和高精度的水体提取；提出了大型湖泊长时序水量估算方法,并以青藏高原湖区为例,重建了典型湖泊面积、水位和水量序列；发展了基于“软分类”的典型内陆水体叶绿素a浓度反演方法,构建了基于生物光学模型的高度浑浊水体悬浮物浓度遥感反演半解析方法,提高了反演方法的区域和季节适用性；构建了基于水色指数的大范围湖库营养状态和透明度遥感监测方法,实现了全球大型湖库营养状态遥感监测,以及全国大型湖库透明度遥感监测；在此基础上,开发了地表水环境遥感监测系统,提高了水环境遥感监测效率,促进了卫星遥感在水环境监测中的高精度业务化应用。     

A multi-variate methodology for analyzing pre-existing lake water quality data

Environmental agencies are given the task of monitoring water quality in rivers, lakes, and other bodies of water, for the purpose of comparing the results with regulatory standards. Monitoring follows requirements set by regulations, and data are collected in a systematic way for the intended purpose. Monitoring enables agencies to determine whether water bodies are polluted. Much effort is spent per monitoring event, resulting in hundreds of data points typically used solely for comparison with regulatory standards and then stored for little further use. This paper devises a data analysis methodology that can make use of the pre-existing datasets to extract more useful information on water quality trends, without new sample collection and analysis. In this paper, measured lake water quality data are subjected to statistical analyses including Principal Component Analysis (PCA) to deduce changes in water quality spatially and temporally over several years. It was found that the lake as a whole changed temporally by season, rather than spatially. Storm events caused the greatest shifts in water quality, though the shifts were fairly consistent across sampling stations. This methodology can be applied to similar datasets, especially with the recent emphasis by the U.S. EPA on protection of lakes as water sources. Water quality managers using these techniques may be able to lower their monitoring costs by eliminating redundant water quality parameters found in this analysis.     

Seasonal monitoring of heavy metals and physicochemical characteristics in a lentic ecosystem of subtropical industrial region, India

Assessment of seasonal changes in surface water quality is an important aspect for evaluating temporal variations of lentic ecosystem (lakes and reservoirs) pollution due to industrial effluent discharge. In this study, nine metals and 15 physicochemical parameters, collected from four sampling sites in a tropical lake receiving the discharge from thermal power plant, coal mine, and chloralkali industry, during the years from 2004 to 2005, were analyzed. For greater efficacy in monitoring of heavy metals, particle-induced X-ray emission has been used during present investigation. Different statistical techniques like analysis of variance, Pearson correlation, principal component analysis, and factor analysis were employed to evaluate the seasonal correlations of physicochemical parameters. Most of the metals and physicochemical parameters monitored in the present study exhibited high spatial and temporal variability. Pertaining to metal pollution, the most polluted site was Belwadah, i.e., waters and sediments had the highest concentration of all the relevant metals. The reference site was characterized by the presence of low concentrations of metals in waters and in sediments. Based on the high metal concentration recorded in lake ambient, drinking, bathing, and irrigation water should not be used by the local people at the effluent discharge points.     

Assessment of wadeable stream resources in the driftless area ecoregion in Western Wisconsin using a probabilistic sampling design

The Wisconsin Department of Natural Resources (WDNR), with support from the U.S. EPA, conducted an assessment of wadeable streams in the Driftless Area ecoregion in western Wisconsin using a probabilistic sampling design. This ecoregion encompasses 20% of Wisconsin’s land area and contains 8,800 miles of perennial streams. Randomly-selected stream sites (n = 60) equally distributed among stream orders 1–4 were sampled. Watershed land use, riparian and in-stream habitat, water chemistry, macroinvertebrate, and fish assemblage data were collected at each true random site and an associated “modified-random” site on each stream that was accessed via a road crossing nearest to the true random site. Targeted least-disturbed reference sites (n = 22) were also sampled to develop reference conditions for various physical, chemical, and biological measures. Cumulative distribution function plots of various measures collected at the true random sites evaluated with reference condition thresholds, indicate that high proportions of the random sites (and by inference the entire Driftless Area wadeable stream population) show some level of degradation. Study results show no statistically significant differences between the true random and modified-random sample sites for any of the nine physical habitat, 11 water chemistry, seven macroinvertebrate, or eight fish metrics analyzed. In Wisconsin’s Driftless Area, 79% of wadeable stream lengths were accessible via road crossings. While further evaluation of the statistical rigor of using a modified-random sampling design is warranted, sampling randomly-selected stream sites accessed via the nearest road crossing may provide a more economical way to apply probabilistic sampling in stream monitoring programs.     

Monitoring Studies of Augusta Bay Marine Waters

The monitoring of water quality today provides a great quantity of data consisting of the values of the parameters measured as a tunction of bme or as spatial function.In the marine environment, and especially in the suspended material, increasing importance is being given to the presence of particular pollution indices. With the increase in the number of sampling points, the amount of data increases and examining the results and their consequent interpretation becomes more difficult. To overcome such difficulties, numerous chemometric techniques have been introduced in environmental chemistry, such as Principal Component Analysis (PCA).The use of the PCA in this work has been applied to the analysis of twenty three different sampling points in three seasonal sampling cruises in the same year. This led to recognition of the influence and the localisation of wastewaters in the Augusta bay after measuring the water pollution parameters.The PCA made evident the difference between some sampling sites whose data were initially thought to be similar where the presence of hot industrial water discharge or urban wastewater determines the permanent water quality.Furthermore, it has allowed a choice of more significant parameters for monitoring programs and more representative sampling site locations.     

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.     

Assessing temporal representativeness of water quality monitoring data

The effectiveness of different monitoring methods in detecting temporal changes in water quality depends on the achievable sampling intervals, and how these relate to the extent of temporal variation. However, water quality sampling frequencies are rarely adjusted to the actual variation of the monitoring area. Manual sampling, for example, is often limited by the level of funding and not by the optimal timing to take samples. Restrictions in monitoring methods therefore often determine their ability to estimate the true mean and variance values for a certain time period or season. Consequently, we estimated how different sampling intervals determine the mean and standard deviation in a specific monitoring area by using high frequency data from in situ automated monitoring stations. Raw fluorescence measurements of chlorophyll a for three automated monitoring stations were calibrated by using phycocyanin fluorescence measurements and chlorophyll a analyzed from manual water samples in a laboratory. A moving block bootstrap simulation was then used to estimate the standard errors of the mean and standard deviations for different sample sizes. Our results showed that in a temperate, meso-eutrophic lake, relatively high errors in seasonal statistics can be expected from monthly sampling. Moreover, weekly sampling yielded relatively small accuracy benefits compared to a fortnightly sampling. The presented method for temporal representation analysis can be used as a tool in sampling design by adjusting the sampling interval to suit the actual temporal variation in the monitoring area, in addition to being used for estimating the usefulness of previously collected data.     

Investigations of mercury concentrations in walleye and other fish in the Athabasca River ecosystem with increasing oil sands developments

Recent studies have reported an increasing trend of mercury concentrations in walleye (Sander vitreus) from the Athabasca River, north eastern Alberta (Canada); these studies were based on three years of comparison and attributed the mercury increase to expanding oil sands developments in the region. In order to conduct a more comprehensive analysis of mercury trends in fish, we compiled an extensive database for walleye, lake whitefish (Coregonus clupeaformis), northern pike (Esox lucius) and lake trout (Salvelinus namaycush) using all available data obtained from provincial, federal, and industry-funded monitoring and other programs. Evidence for increasing trends in mercury concentrations were examined for each species by location and year also considering fish weight and length. In the immediate oil sands area of the Athabasca River, mercury concentrations decreased (p < 0.001) in walleye and lake whitefish over 1984-2011. In western Lake Athabasca and its delta, mercury concentrations decreased (p < 0.0001) in northern pike (1981-2009) although no trend was evident for walleye (1981-2005) and lake trout (1978-2009). Mercury concentrations in lake trout from Namur Lake, a small lake west of the oil sands area, were higher in 2007 than 2000 (p < 0.0001); it is difficult to ascribe this increase to an oil sands impact because similar increases in mercury concentrations have been observed in lake trout from similar sized lakes in the Northwest Territories. While mercury emissions rates have increased with oil sands development and the landscape become more disturbed, mercury concentrations remained low in water and sediments in the Athabasca River and its tributaries and similar to concentrations observed outside the development areas and in earlier decades. Our fish database was assembled from a series of studies that differed in study purpose, design, and analytical methods. Future monitoring programs investigating mercury trends in fish should be more rigorous in their design.     

A classification of freshwater Louisiana lakes based on water quality and user perception data

An index system developed for Louisiana lakes was based on correlations between measurable water quality parameters and perceived lake quality. Support data was provided by an extensive monitoring program of 30 lakes coordinated with opinion surveys undertaken during summer 1984. Lakes included in the survey ranged from 4 to 735 km² in surface area with mean depths ranging from 0.5 to 8.0 m. Water quality data indicated most of these lakes are eutrophic, although many have productive fisheries and are considered recreational assets. Perception ratings of fishing quality and its associated water quality were obtained by distributing approximately 1200 surveys to Louisiana Bass Club Associaton members. The ability of Secchi disc transparency, total organic carbon, total Kjeldahl nitrogen, total phosphorus, and chlorophyll a to discriminate between perception classes was examined using probability distributions and multivariate analyses. Secchi disc and total organic carbon best reflected perceived lake conditions; however, these parameters did not provide the discrimination necessary for developing a quantitative risk assessment of lake trophic state. Consequently, an interim lakes index system was developed based on total organic carbon and perceived lake conditions. The developed index system will aid State officials in interpretating and evaluating regularly collected lake quality data, recognizing potential problem areas, and identifying proper management policies for protecting fisheries usage within the State.     

A Season-dependent Variation of Genotoxicity of Surface Water Samples from Taihu Lake, Yangzte Delta

The present study is to assess a year round change of genotoxicity of surface water in Taihu Lake, Yangtze delta. The water samples were collected in spring, summer, autumn and winter of 2001, respectively. The bacterial L-arabinose resistance forward mutation test (ara test), along with the Ames test, was performed for the evaluation of time profile of mutagenicity of the surface water samples. The strong genotoxic potentials were detected in the near-shore area, especially in the vicinity to the major city. All the samples collected from the lake center and areas distant from dense human activity showed genotoxicity-free in year round time. Intensified human activity along the lake may play an important role for the genotoxic pollution. By comparison of the samples from year round, the winter samples showed the strongest mutagenic potential of all seasons, which indicates that meteorological and hydrological factors also affect the water quality. The impact of dense human activity, improper management and season change should be put into consideration for designing an effective remediation project in the lake basin area.     

Spatial analysis and land use regression of VOCs and NO2 in Dallas, Texas during two seasons

Passive air sampling for nitrogen dioxide (NO(2)) and select volatile organic compounds (VOCs) was conducted at 24 fire stations and a compliance monitoring site in Dallas, Texas, USA during summer 2006 and winter 2008. This ambient air monitoring network was established to assess intra-urban gradients of air pollutants to evaluate the impact of traffic and urban emissions on air quality. Ambient air monitoring and GIS data from spatially representative fire station sites were collected to assess spatial variability. Pairwise comparisons were conducted on the ambient data from the selected sites based on city section. These weeklong samples yielded NO(2) and benzene levels that were generally higher during the winter than the summer. With respect to the location within the city, the central section of Dallas was generally higher for NO(2) and benzene than north and south. Land use regression (LUR) results revealed spatial gradients in NO(2) and selected VOCs in the central and some northern areas. The process used to select spatially representative sites for air sampling and the results of analyses of coarse- and fine-scale spatial variability of air pollutants on a seasonal basis provide insights to guide future ambient air exposure studies in assessing intra-urban gradients and traffic impacts.     

Identification of Characteristic Regions and Representative Stations: A Study of Water Quality Variables in the Kattegat

Gradients in nutrient distributions and the effects of eutrophication are common features in most coastal marine areas. These structures occur in aquatic systems due to spatial differences in hydrography, nutrient loading and key biogeochemical processes. Two statistical methods, cluster analysis and probability mapping, have been used in the present study to determine characteristics and patterns in water quality variables. Combined, these two methods provide a useful tool to statistically determine spatial homogeneity and representativity of areas and stations. A case study is presented here in which water quality variables (salinity, dissolved inorganic nitrogen, dissolved inorganic phosphorus and chlorophyll) in surface waters of the Kattegat are analysed for the time period 1993-1997. It was found that morphology, the proximity to sources of nutrient loading from land, nutrient uptake and the infrequent water exchange between the Baltic Sea in the south and the Skagerrak in the north all contribute to create distinct regions of water quality. Regions with concentrations significantly different from the overall mean are identified. In addition to identification of regions with similar characteristics, representative stations (as well as not representative stations) for the respective regions were made. This type of information can be used to design new or revise old monitoring programs.     

基于多源大数据可视化的城市居民区绿地土壤环境监测点位布设及采样研究

为科学合理的监测城市居民区绿地土壤环境状况,对居民区绿地土壤监测点位布设和采样的方法进行研究,包括代表性居民区的选取、监测点采样位置的确定、点位数量的确定等。通过多源大数据可视化手段选取某城市代表性的居民区,对其居民区内绿地土壤重金属(镉、汞、砷、铅、铜、铬、锌和镍)进行监测。结果表明:多源大数据的应用对城市土壤监测布点具有积极作用和优势;不同建筑年代的居民区土壤中重金属含量存在一定差异,为全面监测居民区土壤环境状况应选取不同建筑年代的居民区作为监测对象;不同采样位置对居民区土壤样品中重金属含量无明显影响,优先于居民区内面积占比较大的绿地采样;同一居民区内不同监测点位样品存在差异性,每个居民区内至少布设3~4个监测点位可代表该居民区土壤环境状况。     

Littoral diatoms as indicators of recent water and sediment contamination by metals in lakes

We studied the response of benthic diatoms to recent metal contamination in littoral cores collected at 25 sites in 11 lakes situated at different distances from a smelter in the Rouyn-Noranda mining region (Quebec). Diatom response was described in terms of density, diversity, and taxonomic composition of the entire assemblages and as abundance of individual indicator taxa. Metal concentrations were measured in sediment and in the overlying water (as total dissolved and as free-ions). Sediment metal contamination was significantly higher in lakes located <10 km from the smelters than in lakes farther away. Such difference was not significant when metal concentrations in the overlying water were considered. Metal contamination did not affect diatom density, which indeed was highest in the most contaminated lake. Diversity (either measured as number of taxa or as Shannon and evenness indices) was instead significantly higher in lakes close to the smelter than elsewhere. Redundancy analysis indicated that diatom composition changed along a gradient in alkalinity (CO?) and one in sediment metal contamination (Cd, Hg, Cu). We identified three diatom taxa (Fragilaria construens var. venter, F. construens var. pumila, and Brachysira vitrea) that increased in relative and absolute abundance with metal contamination. Benthic diatom responses at the community (density, diversity, assemblage composition) and population levels (abundance of selected benthic taxa) were stronger to the sediment metal contamination than to the contamination of overlying water. Comparisons with available literature indicated that, for monitoring recent sediment contamination, diatoms in littoral sediments are preferable to invertebrates that mostly respond to overlying water. Diatoms in littoral cores are therefore unique as tools for monitoring recent contamination of lake sediments.