936 resultados para groundwater sampling


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We employ a moment-based approach to empirically analyse farmer’s decisions about adoption of tube-well technology under depleting groundwater resources using a farm level data from 200 farming households in the Punjab province, Pakistan. The results indicate that the higher the expected profit the greater the probability of adoption. Similarly, with increasing variance the probability of adopting tube-well increases significantly indicating that farmers choose to adopt tube-well technology in order to hedge against production risks. Statistical non-significant the third moment i.e., skewness indicates that farmer generally do not consider downside yield risk when decide to adopt tube-well technology whereas highly significant fourth moment (kurtosis) employ that probability of adoption decreases as a result of extreme events in profit distribution. In addition, we show that land tenureship and three other exogenous variables, i.e., extension services, access to different sources of information and off-farm income play a significant role in the adoption process.

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We discuss the development and performance of a low-power sensor node (hardware, software and algorithms) that autonomously controls the sampling interval of a suite of sensors based on local state estimates and future predictions of water flow. The problem is motivated by the need to accurately reconstruct abrupt state changes in urban watersheds and stormwater systems. Presently, the detection of these events is limited by the temporal resolution of sensor data. It is often infeasible, however, to increase measurement frequency due to energy and sampling constraints. This is particularly true for real-time water quality measurements, where sampling frequency is limited by reagent availability, sensor power consumption, and, in the case of automated samplers, the number of available sample containers. These constraints pose a significant barrier to the ubiquitous and cost effective instrumentation of large hydraulic and hydrologic systems. Each of our sensor nodes is equipped with a low-power microcontroller and a wireless module to take advantage of urban cellular coverage. The node persistently updates a local, embedded model of flow conditions while IP-connectivity permits each node to continually query public weather servers for hourly precipitation forecasts. The sampling frequency is then adjusted to increase the likelihood of capturing abrupt changes in a sensor signal, such as the rise in the hydrograph – an event that is often difficult to capture through traditional sampling techniques. Our architecture forms an embedded processing chain, leveraging local computational resources to assess uncertainty by analyzing data as it is collected. A network is presently being deployed in an urban watershed in Michigan and initial results indicate that the system accurately reconstructs signals of interest while significantly reducing energy consumption and the use of sampling resources. We also expand our analysis by discussing the role of this approach for the efficient real-time measurement of stormwater systems.

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Application of optimization algorithm to PDE modeling groundwater remediation can greatly reduce remediation cost. However, groundwater remediation analysis requires a computational expensive simulation, therefore, effective parallel optimization could potentially greatly reduce computational expense. The optimization algorithm used in this research is Parallel Stochastic radial basis function. This is designed for global optimization of computationally expensive functions with multiple local optima and it does not require derivatives. In each iteration of the algorithm, an RBF is updated based on all the evaluated points in order to approximate expensive function. Then the new RBF surface is used to generate the next set of points, which will be distributed to multiple processors for evaluation. The criteria of selection of next function evaluation points are estimated function value and distance from all the points known. Algorithms created for serial computing are not necessarily efficient in parallel so Parallel Stochastic RBF is different algorithm from its serial ancestor. The application for two Groundwater Superfund Remediation sites, Umatilla Chemical Depot, and Former Blaine Naval Ammunition Depot. In the study, the formulation adopted treats pumping rates as decision variables in order to remove plume of contaminated groundwater. Groundwater flow and contamination transport is simulated with MODFLOW-MT3DMS. For both problems, computation takes a large amount of CPU time, especially for Blaine problem, which requires nearly fifty minutes for a simulation for a single set of decision variables. Thus, efficient algorithm and powerful computing resource are essential in both cases. The results are discussed in terms of parallel computing metrics i.e. speedup and efficiency. We find that with use of up to 24 parallel processors, the results of the parallel Stochastic RBF algorithm are excellent with speed up efficiencies close to or exceeding 100%.

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Convex combinations of long memory estimates using the same data observed at different sampling rates can decrease the standard deviation of the estimates, at the cost of inducing a slight bias. The convex combination of such estimates requires a preliminary correction for the bias observed at lower sampling rates, reported by Souza and Smith (2002). Through Monte Carlo simulations, we investigate the bias and the standard deviation of the combined estimates, as well as the root mean squared error (RMSE), which takes both into account. While comparing the results of standard methods and their combined versions, the latter achieve lower RMSE, for the two semi-parametric estimators under study (by about 30% on average for ARFIMA(0,d,0) series).

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We consider a class of sampling-based decomposition methods to solve risk-averse multistage stochastic convex programs. We prove a formula for the computation of the cuts necessary to build the outer linearizations of the recourse functions. This formula can be used to obtain an efficient implementation of Stochastic Dual Dynamic Programming applied to convex nonlinear problems. We prove the almost sure convergence of these decomposition methods when the relatively complete recourse assumption holds. We also prove the almost sure convergence of these algorithms when applied to risk-averse multistage stochastic linear programs that do not satisfy the relatively complete recourse assumption. The analysis is first done assuming the underlying stochastic process is interstage independent and discrete, with a finite set of possible realizations at each stage. We then indicate two ways of extending the methods and convergence analysis to the case when the process is interstage dependent.

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Today a major responsibility for the contamination of soil and groundwater and surface water are establishments known as gas stations of fuel which has attracted increasing attention from both the general population as the state agencies of environmental control due to leaks in storage tanks and mainly to disruption of pipe corrosion of tanks and pumping. Other services, like oil changes and car wash are also causes for concern in this type of establishment. These leaks can cause or waste produced, and the contamination of aquifers, serious health problems and public safety, since most of these stations located in urban areas. Based on this, the work was to evaluate soil contamination of a particular service station and fuel sales in the city of Natal, through the quantification of heavy metals like Cd, Cu, Cr, Ni, Pb, Zn of total organic carbon (TOC) and organic matter using different techniques such as optical emission spectrometry with inductively coupled plasma source (ICP OES), Total Organic Carbon analyzer and gravimetric analysis respectively. And also to characterize the soil through particle size analysis. Samples were taken in 21 georeferenced points and collected in the same period. The soils sampled in sampling stations P3, P5, P6, P10, P11, P12, P13, P14, P15, P17, P18 and P20 showed the smallest size fractions ranging from fine sand to medium sand. The other study sites ranged from fine sand to medium sand, except the point P8 showed that only the type size medium sand and P19, indicating a particle size of the coarse type. The small correlation of organic matter with the elements studied in this work suggests that these are not of anthropogenic origin but geochemical support

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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O presente estudo avaliou a digestibilidade aparente da proteína e da energia de ingredientes (farelo de soja, farinha de peixe, farelo de trigo e milho) por juvenis de apaiari (Astronotus ocellatus) usando dois diferentes intervalos de coleta (30 min. e 12h). Os 160 juvenis de apaiari utilizados (22,37 ± 3,06 g de peso corporal) foram divididos em quatro tanques rede plásticos e cilíndricos, cada um colocado em um tanque de alimentação de 1.000 L. O experimento foi inteiramente casualizado em esquema fatorial 2 x 4 (2 intervalos de coleta de fezes e 4 ingredientes foram) com quatro repetições. Os testes estatísticos não detectaram efeito da interação entre o intervalo de coleta e tipo de ingrediente nos coeficientes de digestibilidade. O intervalo de coleta não afetou a digestibilidade da proteína e da energia. As características físicas das fezes dos juvenis de apaiari aparentemente as tornam menos sensíveis à perda de nutrientes por lixiviação, permitindo intervalos de coleta maiores. A digestibilidade da proteína dos ingredientes avaliados foi semelhante, mostrando que a digestibilidade aparente de ingredientes animais e vegetais por juvenis de apaiari é eficiente. Os coeficientes de digestibilidade da energia foram maiores para a farinha de peixe e o farelo de soja comparado a farelo de trigo e milho. Ingredientes ricos em carboidratos (farelo de trigo e milho) apresentaram os piores coeficientes de digestibilidade da energia e, portanto, não são usados eficientemente pelos juvenis de apaiari.

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O objetivo deste trabalho foi analizar a distribuição espacial da compactação do solo e a influência da umidade do solo na resistência à penetração. Esta última variável foi descrita pelo índice de cone. O solo estudado foi Nitossolo e os dados de índice de cone foram obtidos usando um penetrômetro. A resistência do solo foi avaliada a 5 profundidades diferentes, 0-10 cm, 10-20 cm, 20-30 cm, 30-40 cm e mais de 40 cm, porém o conteúdo de umidade do solo foi medido a 0-20 cm e 20-40 cm. As condições hídricas do solo variaram nas diferentes amostragems. Os coeficientes de variação para o índice de cone foram 16,5% a 45,8% e os do conteúdo de umidade do solo variaram entre 8,96% e 21,38%. Os resultados sugeriram elevada correlação entre a resistência do solo, estimada pelo índice de cone e a profundidade do solo. Sem embargo, a relação esperada com a umidade do solo não foi apreciada. Observou-se dependência espacial em 31 de 35 séries de dados de índice de cone e umidade do solo. Esta dependência foi ajustada por modelos exponenciais com efeito pepita variável de 0 a 90% o valor do patamar. em séries de dados o comportamento foi aleatório. Portanto, a técnica das distâncias inversas foi utilizada para cartografar a distribuição das variáveis que não tiveram estrutura espacial. Na krigagem constatou-se uma suavização dos mapas comparados com esses das distâncias inversas. A krigagem indicadora foi utilizada para cartografar a variabilidade espacial do índice de cone e recomendar melhor manejo do solo.

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The study that resulted in this dissertation was developed at OU RNCE PETROBRAS, in Natal, which implemented a project of rational use and reuse of water, including use of wastewater from a Sewage Treatment Plant (STP) already in place, diluted with water from own wells for irrigation of green area of the building complex corporate enterprise. Establish a methodology that can serve as guidelines for future projects controlled reuse of water like this was the objective of this research. Been proposed, implemented and evaluated three instruments of sanitary and environmental control: 1) adaptation of sewage treatment plant and quality control of the treated effluent 2) analysis of soil-nutrient interaction in the irrigated area, 3) knowledge of the local hydrogeology, especially with regard to the direction of flow of the aquifer and location of collection wells of Companhia de Águas e Esgotos do Rio Grande do Norte (CAERN) situated in the surroundings. These instruments have proven sufficient and appropriate to ensure the levels of sanitary and environmental control proposed and studied, which were: a) control of water quality off the STP and the output of the irrigation reservoir, b) control of water quality sub surface soil and assessment of progress on soil composition, c) assessment of water quality in the aquifer. For this, we must: 1) establishing the monitoring plan of the STP and its effluent quality sampling points and defining the parameters of analysis, improve the functioning of that identifying the adequacy of flow and screening as the main factors of operational control, and increase the efficiency of the station to a relatively low cost, using additional filters, 2) propose, implement and adapt simple collectors to assess the quality of water percolating into the soil of the irrigated area, 3) determine the direction of groundwater flow in the area study and select the wells for monitoring of the aquifer.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)