943 resultados para Water quality monitoring


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Anthropogenic carbon dioxide (CO2) emissions reduce pH of marine waters due to the absorption of atmospheric CO2 and formation of carbonic acid. Estuarine waters are more susceptible to acidification because they are subject to multiple acid sources and are less buffered than marine waters. Consequently, estuarine shell forming species may experience acidification sooner than marine species although the tolerance of estuarine calcifiers to pH changes is poorly understood. We analyzed 23 years of Chesapeake Bay water quality monitoring data and found that daytime average pH significantly decreased across polyhaline waters although pH has not significantly changed across mesohaline waters. In some tributaries that once supported large oyster populations, pH is increasing. Current average conditions within some tributaries however correspond to values that we found in laboratory studies to reduce oyster biocalcification rates or resulted in net shell dissolution. Calcification rates of juvenile eastern oysters, Crassostrea virginica, were measured in laboratory studies in a three-way factorial design with 3 pH levels, two salinities, and two temperatures. Biocalcification declined significantly with a reduction of ~0.5 pH units and higher temperature and salinity mitigated the decrease in biocalcification.

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The Rathbun Land and Water Alliance and partners have undertaken a highly effective approach to water quality protection through the Rathbun Lake Special Project. This approach is achieving a significant reduction in the sediment and phosphorus that impair water quality in Rathbun Lake and its tributaries as a result of the targeted application of best management practices (BMPs) for priority land in the watershed. This project application proposes to assist landowners to apply BMPs that will reduce sediment and phosphorus delivery from priority land in three targeted sub-watersheds as part of the Rathbun Lake Special Project. Features of this project are: (1) use of geographic information system (GIS) analysis to identify priority land that requires BMPs; (2) assistance for landowners to apply BMPs for 1,200 acres that will reduce the annual delivery of sediment by 1,800 tons and phosphorus by 6,000 pounds; (3) evaluation of the benefits from BMP application using GIS analysis and water quality monitoring; and (4) watershed outreach activities that encourage landowners to apply BMPs for priority land to protect water quality.

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The Rathbun Land and Water Alliance and partners have undertaken a highly effective approach to water quality protection through the Rathbun Lake Special Project. This approach is achieving a significant reduction in the sediment and phosphorus that impair water quality in Rathbun Lake and its tributaries as a result of the targeted application of best management practices (BMPs) for priority land in the watershed. This project application proposes to assist landowners to apply BMPs that will reduce sediment and phosphorus delivery from priority land in three targeted sub-watersheds as part of the Rathbun Lake Special Project. Features of this project are:(1) use of geographic information system (GIS) analysis to identify priority land that requires BMPs;(2) assistance for landowners to apply BMPs for 1,200 acres that will reduce the annual delivery of sediment by 1,800 tons and phosphorus by 6,000 pounds;(3) evaluation of the benefits from BMP application using GIS analysis and water quality monitoring; and (4) watershed outreach activities that encourage landowners to apply BMPs for priority land to protect water quality.

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A structural time series model is one which is set up in terms of components which have a direct interpretation. In this paper, the discussion focuses on the dynamic modeling procedure based on the state space approach (associated to the Kalman filter), in the context of surface water quality monitoring, in order to analyze and evaluate the temporal evolution of the environmental variables, and thus identify trends or possible changes in water quality (change point detection). The approach is applied to environmental time series: time series of surface water quality variables in a river basin. The statistical modeling procedure is applied to monthly values of physico- chemical variables measured in a network of 8 water monitoring sites over a 15-year period (1999-2014) in the River Ave hydrological basin located in the Northwest region of Portugal.

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Estuaries are areas which, from their structure, their fonctioning, and their localisation, are subject to significant contribution of nutrients. One of the objectif of the RNO, the French network for coastal water quality monitoring, is to assess the levels and trends of nutrient concentrations in estuaries. A linear model was used in order to describe and to explain the total dissolved nitrogen concentration evolution in the three most important estuaries on the Chanel-Atlantic front (Seine, Loire and Gironde). As a first step, the selection of a reliable data set was performed. Then total dissolved nitrogen evolution schemes in estuary environment were graphically studied, and allowed a resonable choice of covariables. The salinity played a major role in explaining nitrogen concentration variability in estuary, and dilution lines were proved to be a useful tool to detect outlying observations and to model the nitrogenlsalinity relation. Increasing trends were detected by the model, with a high magnitude in Seine, intermediate in Loire, and lower in Gironde. The non linear trend estimated in Loire and Seine estuaries could be due to important interannual variations as suggest in graphics. In the objective of the QUADRIGE database valorisation, a discussion on the statistical model, and on the RNO hydrological data sampling strategy, allowed to formulate suggestions towards a better exploitation of nutrient data.

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The dinoflagellates of Alexandrium genus are known to be producers of paralytic shellfish toxins that regularly impact the shellfish aquaculture industry and fisheries. Accurate detection of Alexandrium including A. minutum is crucial for environmental monitoring and sanitary issues. In this study, we firstly developed a quantitative lateral flow immunoassay (LFIA) using super-paramagnetic nanobeads for A. minutum whole cells. This dipstick assay relies on two distinct monoclonal antibodies used in a sandwich format and directed against surface antigens of this organism. No sample preparation is required. Either frozen or live cells can be detected and quantified. The specificity and sensitivity are assessed by using phytoplankton culture and field samples spiked with a known amount of cultured A. minutum cells. This LFIA is shown to be highly specific for A. minutum and able to detect reproducibly 105 cells/L within 30 min. The test is applied to environmental samples already characterized by light microscopy counting. No significant difference is observed between the cell densities obtained by these two methods. This handy super-paramagnetic lateral flow immnunoassay biosensor can greatly assist water quality monitoring programs as well as ecological research.

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The challenge on implementation of the EU Water Framework Directive (WFD) fosters the development of new monitoring methods and approaches. It is now commonly accepted that the use of classical monitoring campaigns in discrete point is not sufficient to fully assess and describe a water body. Due to this the WFD promote the use of modelling techniques in surface waters to assist all phases of the process, from characterisation and establishment of reference conditions to identification of pressures and assessment of impact. The work presented in this communication is based on these principles. A classical monitoring of the water status of the main transitional water bodies of Algarve (south of Portugal) is combined with advanced in situ water profiling and hydrodynamic, water quality and ecological modelling of the systems to build a complete description of its state. This approach extends spatially and temporally the resolution of the classical point sampling. The methodology was applied during a 12 month program in Ria Formosa coastal lagoon, the Guadiana estuary and the Arade estuary. The synoptic profiling uses an YSI 6600 EDS multi-parameter system attached to a boat and a GPS receiver to produce monthly synoptic maps of the systems. This data extends the discrete point sampling with laboratory analysis performed monthly in several points of each water body. The point sampling is used to calibrate the profiling system and to include variables, such as nutrients, not measured by the sensors. A total of 1427 samplings were performed for physical and chemical parameters, chlorophyll and microbiologic contamination in the water column. This data is used to drive the hydrodynamic, transport and ecological modules of the MOHID water modelling system (www.mohid.com), enabling an integrate description of the water column.

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Monitoring Earth's terrestrial water conditions is critically important to many hydrological applications such as global food production; assessing water resources sustainability; and flood, drought, and climate change prediction. These needs have motivated the development of pilot monitoring and prediction systems for terrestrial hydrologic and vegetative states, but to date only at the rather coarse spatial resolutions (∼10–100 km) over continental to global domains. Adequately addressing critical water cycle science questions and applications requires systems that are implemented globally at much higher resolutions, on the order of 1 km, resolutions referred to as hyperresolution in the context of global land surface models. This opinion paper sets forth the needs and benefits for a system that would monitor and predict the Earth's terrestrial water, energy, and biogeochemical cycles. We discuss six major challenges in developing a system: improved representation of surface‐subsurface interactions due to fine‐scale topography and vegetation; improved representation of land‐atmospheric interactions and resulting spatial information on soil moisture and evapotranspiration; inclusion of water quality as part of the biogeochemical cycle; representation of human impacts from water management; utilizing massively parallel computer systems and recent computational advances in solving hyperresolution models that will have up to 109 unknowns; and developing the required in situ and remote sensing global data sets. We deem the development of a global hyperresolution model for monitoring the terrestrial water, energy, and biogeochemical cycles a “grand challenge” to the community, and we call upon the international hydrologic community and the hydrological science support infrastructure to endorse the effort.

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Drinking water utilities in urban areas are focused on finding smart solutions facing new challenges in their real-time operation because of limited water resources, intensive energy requirements, a growing population, a costly and ageing infrastructure, increasingly stringent regulations, and increased attention towards the environmental impact of water use. Such challenges force water managers to monitor and control not only water supply and distribution, but also consumer demand. This paper presents and discusses novel methodologies and procedures towards an integrated water resource management system based on advanced ICT technologies of automation and telecommunications for largely improving the efficiency of drinking water networks (DWN) in terms of water use, energy consumption, water loss minimization, and water quality guarantees. In particular, the paper addresses the first results of the European project EFFINET (FP7-ICT2011-8-318556) devoted to the monitoring and control of the DWN in Barcelona (Spain). Results are split in two levels according to different management objectives: (i) the monitoring level is concerned with all the aspects involved in the observation of the current state of a system and the detection/diagnosis of abnormal situations. It is achieved through sensors and communications technology, together with mathematical models; (ii) the control level is concerned with computing the best suitable and admissible control strategies for network actuators as to optimize a given set of operational goals related to the performance of the overall system. This level covers the network control (optimal management of water and energy) and the demand management (smart metering, efficient supply). The consideration of the Barcelona DWN as the case study will allow to prove the general applicability of the proposed integrated ICT solutions and their effectiveness in the management of DWN, with considerable savings of electricity costs and reduced water loss while ensuring the high European standards of water quality to citizens.

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This paper aims to study the ecological system of the Pardo River, at the source and lower-order passages, which are in the Botucatu area, São Paulo State, Brazil. This study was carried out to determine water quality with some chemical-physical indicators, coliforms, and chemical species of samples taken monthly, 1995/02-1996/01, from eight sampling stations sited along the Pardo River. The results in the river monitoring are discussed based on annual averages, analysis of variance, and compared to Tukey's Studentized Range-HSD, and principal component analysis (PCA) was applied to normalize data to assess association between variables. We can conclude that the variables used are very efficient for identifying and that the dry season shows the worst water quality. These were caused by organic matter, nutrients (originate) from anthropogenic sources (spatial sources) and mainly municipal wastewater, affecting the quality and hydrochemistry of the river water, which have been differentiated and assigned to polluting sources. Meanwhile, the degree of degradation of the Pardo River is low (sewage treatment carried out by the city of Pardinho is efficient), leaving the water of the river suitable for use by the population of Botucatu, after conventional treatment (Conama, Resolucao No. 20, CONAMA, Brazilia DF, 09-23, 1986-the water of the Pardo river is classified as level 03). (C) 2001 Elsevier B.V. Ltd. All rights reserved.

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2-Methylisoborneol (MIB) and geosmin (GSM) are sub products from algae decomposition and, depending on their concentration, can be toxic: otherwise, they give unpleasant taste and odor to water. For water treatment companies it is important to constantly monitor their presence in the distributed water and avoid further costumer complaints. Lower-cost and easy-to-read instrumentation would be very promising in this regard. In this study, we evaluate the potentiality of an electronic tongue (ET) system based on non-specific polymeric sensors and impedance measurements in monitoring MIB and GSM in water samples. Principal component analysis (PCA) applied to the generated data matrix indicated that this ET was capable to perform with remarkable reproducibility the discrimination of these two contaminants in either distilled or tap water, in concentrations as low as 25 ng L-1. Nonetheless, this analysis methodology was rather qualitative and laborious, and the outputs it provided were greatly subjective. Also, data analysis based on PCA severely restricts automation of the measuring system or its use by non-specialized operators. To circumvent these drawbacks, a fuzzy controller was designed to quantitatively perform sample classification while providing outputs in simpler data charts. For instance, the ET along with the referred fuzzy controller performed with a 100% hit rate the quantification of MIB and GSM samples in distilled and tap water. The hit rate could be read directly from the plot. The lower cost of these polymeric sensors allied to the especial features of the fuzzy controller (easiness on programming and numerical outputs) provided initial requirements for developing an automated ET system to monitor odorant species in water production and distribution. (C) 2012 Elsevier B.V. All rights reserved.

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Mode of access: Internet.

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"IEPA/BOW/07-005."--Cover.

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"June 1996."