Relevant bibliographies by topics / Monitoring of dams

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Academic literature on the topic 'Monitoring of dams'

Author: Grafiati
Published: 4 June 2021
Last updated: 10 February 2022

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Journal articles on the topic "Monitoring of dams"

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Bali, Haluk, and Salih Alcay. "The Methods Used in Monitoring of Large Dams in Turkey." Academic Perspective Procedia 3, no. 1 (2020): 236–45. http://dx.doi.org/10.33793/acperpro.03.01.51.

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Turkey is a very rich country in terms of water resources. However, in order to use these resources efficiently, water must be stored safely. In this context, the best form of storage is the construction of dams. In our country, large dams, which are among the world's important dams, are being built. Although there are many advantages of large dams, the loss of life and property will be so great in case of a possible deformation or destruction. The fact that dams are under the influence of various forces, as well as being located in the earthquake zone of our country, necessitates continuous monitoring of our dams. Dams are generally monitored using geodetic methods and geotechnical devices. However, mostly details of these two methods are evaluated separately in dam monitoring. Evaluating the results of both methods together is very important for the comprehensive monitoring of the dam and the correct interpretation of possible deformations. In this study, large dams in our country and monitoring studies carried out by using geodetic and geotechnical methods in these dams are given in detail.
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Dunnicliff, J. "Geotechnical monitoring systems for embankment dams." International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts 27, no. 2 (1990): A93. http://dx.doi.org/10.1016/0148-9062(90)95096-j.

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Eisma, Jessica A., and Venkatesh M. Merwade. "Investigating the environmental response to water harvesting structures: a field study in Tanzania." Hydrology and Earth System Sciences 24, no. 4 (2020): 1891–906. http://dx.doi.org/10.5194/hess-24-1891-2020.

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Abstract. Sand dams, a popular water harvesting structure employed by rural communities, capture and store water for use during the dry season in arid and semi-arid regions. Most sand dam research has been performed on the “ideal” sand dam, despite approximately 50 % of sand dams not functioning as intended. This research involves a 1-year long, in-depth field study of three sand dams in Tanzania, one of which is essentially non-functioning. The study investigated a sand dam's impact on macroinvertebrate habitat, vegetation, and streambank erosion and explored a sand dam's water loss mechanisms. Surveys of macroinvertebrate assemblage were performed each season. Vegetation surveys were performed every other month, and erosion was recorded semi-monthly. Water table monitoring wells were installed at each sand dam, and measurements were taken twice a day. The study found that sand dams are too homogeneous to provide the sustenance and refugia macroinvertebrates need at different life stages. The non-functioning sand dam has a thick layer of silt preventing infiltration of rainwater. The functioning sand dams store a significant amount of water, but most is lost to evapotranspiration within a few months of the last rainfall. Unlike the non-functioning sand dam, the functioning sand dams have a positive impact on local vegetation and minimal impact on erosion. Sand dams can increase the water security of a community, but site characteristics and construction methods must be strongly considered to maximize the sand dam's positive impact.
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Suwatthikul, Jittiwut, Rangsarit Vanijjirattikhan, Unpong Supakchukul, et al. "Development of Dam Safety Remote Monitoring and Evaluation System." Journal of Disaster Research 16, no. 4 (2021): 607–17. http://dx.doi.org/10.20965/jdr.2021.p0607.

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More than 4,000 dams are constructed in Thailand for several purposes, including water supply, flood control, irrigation, and hydropower generation. Among these dams, 14 large dams are operated by the Electricity Generating Authority of Thailand (EGAT). As a dam operator, EGAT is committed to ensuring dam safety by regularly conducting dam inspections and maintenance. This paper presents the development and practical applications of the Dam Safety Remote Monitoring System (DS-RMS). The objective of DS-RMS is to enhance the EGAT’s implementation of its dam safety program in terms of dam monitoring by instrumentation to satisfy international recommendations. DS-RMS consists of five subsystems: Dam Behavior, Reservoir Operation, Earthquake Monitoring, Expert System and Public Communication. DS-RMS has been deployed at 14 large EGAT-operated dams across the country since 2016. Results show that the novel features of DS-RMS enable faster and more reliable dam safety monitoring and evaluation processes.
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Monteiro, Gilberto Silva, Jorge Pacheco Neves, and Jorge Pereira Gomes. "Seismic Monitoring System of Baixo Sabor and Feiticeiro Dams." Civil Engineering Journal 6, no. 11 (2020): 2072–85. http://dx.doi.org/10.28991/cej-2020-03091603.

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In the last decade Portugal made a significant set of investments in new hydroelectric projects. According the Portuguese Dam Safety Regulation and Supporting Technical Documents, and the seismic risk for the regions where the dams were built, several seismic monitoring systems were implemented. One of the most important projects was the Baixo Sabor hydroelectric scheme which includes two large dams, namely the Baixo Sabor and Feiticeiro dams. These dams are located at northeast of Portugal and are very close to a major geological fault that crosses the Portuguese territory. Considering the seismic risk of the dam’s construction area, a seismic monitoring system was provided. That system incorporates stations in the dam’s galleries and remote stations along the reservoirs to detect eventual induced reservoir seismicity. This system has been in continuous operation and the data of the recorded earthquakes records has been analyzed and processed. This paper presents some aspects of the Portuguese legislation, refers the main studies that were used, presents a brief description of the regional Baixo Sabor geological and tectonic settings, describes the main features of the seismic monitoring system and presents some of the main results obtained during the first period of operation of the dams. Doi: 10.28991/cej-2020-03091603 Full Text: PDF
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Jiang, Zhenxiang, and Jinping He. "Detection Model for Seepage Behavior of Earth Dams Based on Data Mining." Mathematical Problems in Engineering 2018 (2018): 1–11. http://dx.doi.org/10.1155/2018/8191802.

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Seepage behavior detecting is an important tool for ensuring the safety of earth dams. However, traditional seepage behavior detection methods have used insufficient monitoring data and have mainly focused on single-point measures and local seepage behavior. The seepage behavior of dams is not quantitatively detected based on the monitoring data with multiple measuring points. Therefore, this study uses data mining techniques to analyze the monitoring data and overcome the above-mentioned shortcomings. The massive seepage monitoring data with multiple points are used as the research object. The key information on seepage behavior is extracted using principal component analysis. The correlation between seepage behavior and upstream water level is described as mutual information. A detection model for overall seepage behavior is established. Result shows that the model can completely extract the seepage monitoring data with multiple points and quantitatively detect the overall seepage behavior of earth dams. The proposed method can provide a new and reasonable means of quantitatively detecting the overall seepage behavior of earth dams.
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Fernández, Martina Inmaculada Álvarez, Celestino González Nicieza, Román Fernández Rodríguez, and Juan Ramón García Menéndez. "Earth Dam Monitoring in the Soil Take Care Project." Proceedings 2, no. 23 (2018): 1451. http://dx.doi.org/10.3390/proceedings2231451.

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The Cartagena-La Unión mountain range was the focus of an intense mining activity between early XIX and late XX centuries. Most of Spanish national production of lead and zinc was extracted from its mines. During the ore concentration process, contaminated wastes containing heavy metal minerals, cyanides and sulfates were produced and deposited in earth dams. The Spanish National Institute of Geology and Mining had catalogued 75 earth dams in the councils of Cartagena and La Unión. These deposits pose a potential risk for the environment and nearby populations. Without suitable and precautionary measures, contaminated particles can be transported far away due to the wind action and runoff water, and may be incorporated to the food chain. This risk is increase due to the fact that it is a seismically active area, and breakage of these dams can lead to the dumping of thousands of tons of contaminated wastes. The SOIL TAKE CARE Project is an international project co financed by the European Regional Development Fund (ERDF) through the Interreg Sudoe Cooperation Programme. It aims to improve the management and rehabilitation of contaminated soils in South-Western Europe that includes Spain, Portugal and south of France. The University of Oviedo takes part of that Project by the instrumentation and monitoring of two of those earth dams. Among the work realized so far highlights the perforation of two boreholes and the installation of several sensors. It aims a double objective: to analyze the erosion and infiltration capacity of rainfall into the dams and to detect possible symptoms of slope instability. Although the investigation is still in course, preliminary results shows fast rainfall infiltration into the superficial soil layers, being discharge curves much more extended. This water retention capacity, coupled with the existence of impermeable layers into the dams, could lead to a complete saturation of superficial soil layers and trigger slope instability processes.
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Čejka, F., V. Beneš, F. Glac, and Z. Boukalová. "Monitoring of seepages in earthen dams and levees." International Journal of Environmental Impacts: Management, Mitigation and Recovery 1, no. 3 (2018): 267–78. http://dx.doi.org/10.2495/ei-v1-n3-267-278.

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Anita, Rajesh Singh, Sushabhan Choudhury, and Bhupendra Singh. "Wireless Disaster Monitoring and Management System for Dams." Procedia Computer Science 48 (2015): 381–86. http://dx.doi.org/10.1016/j.procs.2015.04.197.

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Rhim, Hong C. "Condition monitoring of deteriorating concrete dams using radar." Cement and Concrete Research 31, no. 3 (2001): 363–73. http://dx.doi.org/10.1016/s0008-8846(00)00496-8.

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Dissertations / Theses on the topic "Monitoring of dams"

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Johansson, Sam. "Seepage monitoring in embankment dams." Doctoral thesis, KTH, Civil and Environmental Engineering, 1997. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-2477.

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<p>Internal erosion, which is one of the major reasons forembankment dam failure, causes an increased seepage flow due toloss of fines. A seepage measuring system is therefore a vitalpart of an embankment dam’s monitoring system. Manyexisting seepage monitoring systems are not however sensitiveenough to detect small changes in the seepage flow. Temperatureand resistivity measurements represent two methods for seepagemonitoring in embankment dams. They are able to detect effectscaused by time dependent processes such as internal erosion,where the relative accuracy is more important than the absoluteaccuracy. Temperature can normally be easily measured inexisting standpipes. Resistivity measurements are morecomplicated; they require a computer-based monitoring systemand minor technical installations on the dam.</p><p>The temperature in an embankment dam depends mainly on thetemperature in the air and the water temperature in theupstream reservoir. These two temperatures vary seasonally andcreate temperature waves propagating through the dam. Theseepage rate, and its change with time, can be evaluated frommeasurements repeated at regular intervals. The sensitivity ofthe method depends mainly on the distance between the dam crestand the measurement point, the size of the dam, the location ofthe standpipes, and the temperature variation in the reservoirat the inflow level. The seepage detection level of the methodis about 1 ml/sm2 for a typical Swedish dam with a height ofabout 30 m. The detection level depends linearly on the damheight. Results from field measurements show that the methodgives reasonable information concerning the condition of thedam. Zones with anomalous seepage rates have been located andseepage flow rates have been quantified. Changes in the seepageflow rate as well as the seepage pathway have also beenobserved.</p><p>The resistivity of the ground depends mainly on theporosity, saturation and clay content. When reservoir waterseeps through a dam, the properties of the water in thereservoir will also affect the resistivity in the dam. Theresistivity of the reservoir water is temperature dependent,but it is also a function of the total dissolved solids. Boththese parameters vary seasonally and this causes variations inthe dam. The seepage flow can be evaluated from the resistivitydata using methods similar to those employed for seepageevaluation from temperature data. The sensitivity is similar tothat of the temperature method but the resolution and accuracyis lower. Zones with anomalous leakage can be located. Groundpenetrating radar and borehole radar methods are based on themeasurement of material dependent properties. These are lesssensitive to seepage changes than flow dependent parameters.The relatively high accuracy obtained by borehole radarmeasurements compensates however for their lower sensitivity toporosity changes. Borehole radar based on tomographic analysiscan be a valuable method for mapping areas with increased andanomalous porosity formed as a consequence of increased seepageand internal erosion.</p><p><b>Key words:</b>embankment dams, internal erosion, seepagemonitoring, temperature, resistivity, ground penetratingradar</p>
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Mainali, Ganesh. "Monitoring of tailings dams with geophysical methods." Licentiate thesis, Luleå : Luleå university of Technology, 2006. http://epubl.luth.se/1402-1757/2006/07.

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Svensen, Daniel. "Numerical analyses of concrete buttress dams to design dam monitoring." Thesis, KTH, Betongbyggnad, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-189250.

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Old concrete buttress dams are sensitive to cracking if exposed to large temperature variations. The cracks can make dams sensitive to failure, depending on the size and location of the cracks. These problems can be overcome by lowering the temperature variations and stabilizing the dams. Insulation walls can be built to lower the temperature variations, and the area inside the insulation wall can be climate controlled to ensure a constant temperature. Stabilizing measures could be installing tendons, anchoring monoliths to the foundation or to keep parts of the monolith together. However, the best way to make sure the dam is functioning as expected is to monitor the behavior of the dam through different sensors. The sensors should be connected to some kind of dam monitoring software, which can indicate whether the dam is going to fail in a near future. For this to work, some kind of alert and alarm values has to be determined. The main purpose for this project is to develop a finite element model that could be used to simulate the real behavior of a concrete buttress dam and predict the future behavior of the dam. This makes it possible to determine alert and alarm values for monitoring equipment installed on the dam. Some steps are necessary to be able to create a finite element model representing the real behavior and to predict the future behavior of a dam. A first step is calibration of the model against real measurements, and during the calibration process it is important to evaluate the predictions made. A second step is to determine the normal variation in the behavior of the dam. A last step is to define suitable alert and alarm values, where the alert values are based on the normal variation of the dam and the alarm values are based on failure analyses. The results show that it is possible to calibrate a finite element model with sufficient accuracy in order for it to be used for predictions of the dams behavior. The results show two failure modes of the concrete buttress dam which deviate from previous research, where post-tensioned tendons were not included. From the results, information is given about where to place sensors to be able to capture a failure, how well the finite element model is calibrated, and what the alarm values should be. Furthermore, the results show that the evaluation of predictions made in the calibration process is of utmost importance to achieve a model representing the real behavior.<br>Gamla betonglamelldammar är känsliga för sprickbildning om de utsätts för stora temperaturvariationer. Sprickor kan göra dammarna känsliga för brott, beroende på storlek och placering av sprickorna. Dessa problem kan övervinnas genom att sänka temperaturvariationerna och stabilisera dammarna. Isoleringsväggar kan byggas för att sänka temperaturvariationerna, och området innanför isoleringsväggen kan klimatkontrolleras för att säkerställa en konstant temperatur. Stabiliserande åtgärder skulle kunna vara att installera spännkablar, förankring av monoliten till berggrunden eller att hålla ihop delar av monoliten. Emellertid är det bästa sättet att se till dammen fungerar som förväntat för att övervaka beteendet hos dammen genom olika sensorer. Givarna borde anslutas till någon form av programvara för dammövervakning, som kan indikera om dammen kommer att gå till brott inom en snar framtid. För att detta ska fungera måste någon form av mjuka och hårda larmvärden bestämmas. Huvudsyftet för detta projekt är att skapa en finit elementmodell som kan användas för att simulera det verkliga beteendet hos en betonglamelldamm och förutsäga framtida beteende av dammen för att kunna bestämma mjuka och hårda larmvärden för vald övervakningutrustning på dammen. Några steg är nödvändiga för att kunna skapa en finit elementmodell som representerar det verkliga beteendet och göra det möjligt att förutsäga det framtida beteendet av en damm. Ett första steg är kalibrering av modellen mot riktiga mätningar och under kalibreringsprocessen är det viktigt att utvärdera predikterade värden. Ett andra steg är att bestämma den normala variationen av dammens beteende. Ett sista steg är att definiera lämpliga värden för mjuka och hårda larmvärden, där de mjuka värdena baseras på dammens normala variation och de hårda larmvärdena på brottsanalyser. Resultaten visar att det är möjligt att kalibrera en finit elementmodell med tillräckligt god noggrannhet att den kan användas för prediktering av dammens beteende. Resultaten visar två brottmoder av betonglamelldammen som skiljer sig från tidigare studier där spännkablar inte hade inkluderats. Från resultaten ges information om var sensorer ska placeras för att kunna fånga ett brott, hur väl finita elementmodellen kalibrerats, och vilka de mjuka och hårda larmvärdena bör vara. Dessutom visar resultaten att utvärderingen av predikteringar som gjorts i kalibreringsprocessen är av yttersta vikt för att uppnå en modell som representerar det verkliga beteendet.
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Ahmadi-Nedushan, Behrooz 1966. "Multivariate statistical analysis of monitoring data for concrete dams." Thesis, McGill University, 2002. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=82815.

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Major dams in the world are often instrumented in order to validate numerical models, to gain insight into the behavior of the dam, to detect anomalies, and to enable a timely response either in the form of repairs, reservoir management, or evacuation. Advances in automated data monitoring system makes it possible to regularly collect data on a large number of instruments for a dam. Managing this data is a major concern since traditional means of monitoring each instrument are time consuming and personnel intensive. Among tasks that need to be performed are: identification of faulty instruments, removal of outliers, data interpretation, model fitting and management of alarms for detecting statistically significant changes in the response of a dam.<br>Statistical models such as multiple linear regression, and back propagation neural networks have been used to estimate the response of individual instruments. Multiple linear regression models are of two kinds, (1) Hydro-Seasonal-Time (HST) models and (2) models that consider concrete temperatures as predictors.<br>Univerariate, bivariate, and multivariate methods are proposed for the identification of anomalies in the instrumentation data. The source of these anomalies can be either bad readings, faulty instruments, or changes in dam behavior.<br>The proposed methodologies are applied to three different dams, Idukki, Daniel Johnson and Chute-a-Caron, which are respectively an arch, multiple arch and a gravity dam. Displacements, strains, flow rates, and crack openings of these three dams are analyzed.<br>This research also proposes various multivariate statistical analyses and artificial neural networks techniques to analyze dam monitoring data. One of these methods, Principal Component Analysis (PCA) is concerned with explaining the variance-covariance structure of a data set through a few linear combinations of the original variables. The general objectives are (1) data reduction and (2) data interpretation. Other multivariate analysis methods such as canonical correlation analysis, partial least squares and nonlinear principal component analysis are discussed. The advantages of methodologies for noise reduction, the reduction of number of variables that have to be monitored, the prediction of response parameters, and the identification of faulty readings are discussed. Results indicated that dam responses are generally correlated and that only a few principal components can summarize the behavior of a dam.
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Nilsson, Isak, and Leonard Sandström. "Behavior prediction of concrete dams." Thesis, KTH, Betongbyggnad, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-289385.

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As many dams were built around 1950, the expected life span of these dams are about tobe reached. With this, the need for monitoring and increased understanding of the damsstructural integrity increases. In order to prevent failures, two warning signals are defined;alert and alarm. The main difference being that the first indicates an unexpected changein behavior that needs to be addressed and evaluated in the near future, while the otherrequires that immediate action must be taken to ensure the safety of the dam.This report aims to evaluate the applicability of different models for designing alert values.In order to achieve this goal, two case studies have been performed. The first being onSchlegeis, an arch dam in Austria, and the second Storfinnforsen, a concrete buttress damin Sweden. The methods used are finite element modelling as well as data-based models.Data-based models work on the presumption that the dam behaviour is governed by variationsin environmental conditions such as temperature and water level. The report hasevaluated two commonly used data-based models, hydrostatic thermal time (HTT) and hydrostaticseasonal time (HST), as well as two machine learning based models artificial neuralnetworks (ANN) and boosted regression trees (BRT).The programs used in this report are BRIGADE plus for finite element method and MATLABfor the multi-linear regression analyses HTT and HST, as well as boosted regressiontrees. The neural networks were constructed in Python using TensorFlow and Keras API.The result from the case studies is that the commonly used data-based models HST andHTT perform well enough for creating predictions and alert levels when given a sufficientamount of historical data, approximately 3-5 years. Machine learning such as artificial neuralnetworks while comparable in prediction quality does not further increase the understandingof the dam behaviour and can due to the complexity of designing an appropriate networkstructure be less suited for this type of analysis. Finite element models can also capturethe behavior of the dam rather well. It is however not as accurate as data-based modelswhen sufficient data is available. An FE-model should be used for definition of alert valueswhen insufficient data exists after the dam conditions have been significantly altered, orwhen newly constructed. The main advantage that machine learning provides is that theyperform better for non-linear behavior than multi-linear regression.
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Hellgren, Rikard. "Condition assessment of concrete dams in cold climate." Licentiate thesis, KTH, Betongbyggnad, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-259719.

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Dams in many countries are approaching their expected service life. Proper assessment of the aging dams structural health increase the knowledge of the current safety, and allow for better planning of renovation and rebuilding investments. The behavior of concrete dams is, to a great extent, governed by the ambient variation in temperature and water level. In cold regions, the ice sheet formed in the reservoir may subject a pressure load on the dams. Theoretically, this load has a significant impact on the structural behavior of dams. Despite this, the maximum magnitude, as well as the seasonal variation of the ice load, constitute the most considerable uncertainty in the safety assessment of dams. This thesis presents research that examines how to model the expected behavior of dams in cold climate. The underlying problem is to predict the response of dams due to variation in the external conditions. Since the ice load is such a vital part of the external conditions in cold climate, the understanding and modeling of ice loads have been given extra attention. Models suitable to predict the long-term behavior of dams can be divided between theoretical, data-based, and hybrid. Prediction accuracy is essential to set alert thresholds, and in that regard, the data-based models are generally superior. The major contribution of this thesis is the design and installation of a prototype ice load panel with direct measurement of the ice pressure acting on a dam. The panel is attached on the upstream face of the dam and is large enough so that the whole thickness of the ice sheet is in contact with the panel. The predicted ice load from the best available model that includes loads from both thermal events and water level changes did not correspond to the measured ice loads. As there are no validated models or measurement methods for ice load on the dam, continued research is necessary, both through further measurements to increase knowledge and development of models.<br>I många länder närmar sig vattenkraftsdammarna deras förväntade tekniska livslängd. Korrekt utvärdering av dammens strukturella status ökar kunskapen om det nuvarande säkerhetsläget och möjliggör för bättre planering av renoveringar och ombyggnadsinvesteringar. Betongdammarnas beteende styrs till stor del av variationen i omgivande temperaturer och vattennivå. I kalla regioner kan is som bildas i magasinet utsätta dammen för en tryckande last. Teoretiskt har denna belastning en betydande inverkan på dammarsstrukturella beteende. Trots detta är den maximala storleken såväl som säsongsvariationen för islasten en av de mest betydande osäkerheterna vidsäkerhetsbedömningen av dammar. Denna uppsats presenterar forskning som undersöker hur förväntat beteendehos dammar i kallt klimat kan modelleras. Den underliggande frågeställningen är att förutsäga en damms respons orsakad av variation i de yttre förhållandena. Extra fokus har lagts på förståelsen och modelleringen av islasten då den är en viktig del av de yttre förhållandena för dammar i kalla klimat. Modeller som är lämpliga för att förutsäga dammars beteende kan delas upp i teoretiska, databaserad, och hybridmodeller. Förutsägbarhetsnoggrannhet är avgörande för att ställa in varningsnivåer, och i det avseendet är de databaserade modellerna i allmänhet överlägsna. Det huvudsakliga bidraget från detta projekt är utvecklandet och installationen av en prototyp av en islast panel, fäst på en damms uppströmssida. Panelen mäter istrycket direkt mot dammen och är tillräckligt stor så att helaisens tjocklek förblir i kontakt med panelen. Panelen bidrar till ökad kunskap om säsongsvariationen i istryck och mekanismen för islaster orsakad av variation i vattennivån. Den predikterade islaten från den bästa tillgängliga islastmodellen som inkluderar termiska islaster och islaster från vattennivåförändringar överensstämmer inte med de uppmätta islastpanelen som uppmätts med panelen. Då det saknas validerade modeller eller mätmetoder för islast är det viktigt med fortsatt forskning, dels genom ytterligare mätningar för att öka kunskapen men även fortsatt modellutveckling.<br><p>QC 20190926</p>
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Machado, William Gladstone de Freitas. "Monitoramento de barragens de contenção de rejeitos da mineração." Universidade de São Paulo, 2007. http://www.teses.usp.br/teses/disponiveis/3/3134/tde-31032008-154124/.

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Esta dissertação é uma contribuição, através de uma pesquisa bibliográfica, sobre o tema instrumentação e monitoramento em empreendimentos de barragens de rejeitos da mineração. Nesta pesquisa apresentam-se os objetivos básicos da instrumentação de barragens e suas características técnicas, metodologia construtiva das barragens de rejeitos e seu monitoramento através de auscultação da instrumentação. Como limitação do trabalho, devido à variedade de instrumentos que podem ser instalados em uma barragem, buscou-se pesquisar os instrumentos de medição de deslocamentos e controle de fluxo percolante, sendo os mais utilizados em barragens de terra e rejeitos. Justifica-se este tema motivado pelos últimos acidentes ocorridos em barragens de contenção de rejeitos, enfatizando a importância e a necessidade permanente da melhoria das condições de segurança e monitoramento das barragens brasileiras. Estes acidentes causam danos à população do entorno da barragem, econômicos ao empreendedor e ambientais. Como resultado obtido nesta pesquisa pode-se concluir que propiciou conhecimento atualizado ao meio técnico nacional de barragens.<br>This dissertation is a contribution, through a bibliographical research, on the subject of instrumentation and monitoring in enterprises of tailings dams. This research presents the basic objectives of the instrumentation of dams, their technical characteristics, the construction methodology of tailings dams and their monitoring through auscultation of the instrumentation. Due to the variety of instruments that can be installed in a dam, this work was limited to the analysis of two segments, instruments of measurement displacements and those for controlling percolation flow, which are the most commonly used in earth and tailings dams. This study is justified due to recent accidents occurring in tailings dams, which stress the importance and the permanent necessity of the improvement in security and monitoring conditions of Brazilian dams. These accidents cause social, economic and environmental damages to the enterprise. As a result of this research it can be concluded that it contributed with up-to-date knowledge to the national technical dam sector.
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Ikard, Scott. "Geoelectric monitoring of seepage in porous media with engineering applications to earthen dams." Thesis, Colorado School of Mines, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=3602502.

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<p> A monitoring methodology is developed for investigating seepage and internal erosion in earthen dams with time-lapse measurements of self-potential anomalies associated with conservative salt and non-conservative heat tracer migration in the subsurface. The method allows for 1) detecting seepage zones in earthen dams and determining the preferential flow paths through seepage zones in a non-invasive manner from the ground surface, 2) monitoring the transient evolution of seepage path geometry, flow velocity, and permeability in real-time if high frequency measurements can be made, and 3) long-term non-invasive monitoring with wired or wireless sensors The method is first theoretically developed and tested in a laboratory using a conservative tracer, and then demonstrated at a 12 m high, 100 m long leaking earthen dam with complex, unknown seepage paths. The method is shown to be capable of rapidly detecting seepage zones discovered during a reconnaissance survey, and delineates the predominant seepage directions through the dam from the time-lapse self-potential anomalies. The time-lapse monitoring approach ensures improved spatial resolution, increased measurement frequencies, and improved data analysis capabilities relative to traditional approaches to seepage detection, and a cost-reduction for the application of this methodology is anticipated to follow advancements in wireless sensing and monitoring technologies. This method is designed to be a more cost-effective means of interrogating earthen dams and levees to answer questions such as: Is the dam safe? What are the geometries of the seepage zones inside of the dam, and over what spatial scale does anomalous seepage occur? What are preferential paths through the seepage zones? Is internal erosion actively occurring? At what rates are the geometries, permeabilities and flow rates of preferential seepage paths evolving?</p>
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Fu, Jenny. "Evaluation of long-term performance of sodium silicate grouted in embankment dams." Thesis, KTH, Jord- och bergmekanik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-275740.

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Embankment dams is the most common type of dams in operation inSweden today. Due to the nature of embankment dams, seepage throughthem will always occur. If the seepage velocity exceeds a critical velocity,internal erosion is initiated, which could lead to damage in form of pipingand sinkholes. To treat this problem, remedial grouting has beenperformed involving a combination of conventional grouts, i.e. cement andcement-bentonite as well as sodium silicate, which is a chemical grout thatalso known as water glass. Regarding the sodium silicate grout, there isconcern about the long-term permanence.The aim of this thesis has been to study the potential performance ofsodium silicate grouted in embankment dams. The first part of this thesisis a literature review of the general behavior of sodium silicate as a grout,its degradation processes and the factors that could induce degradation.The second part suggests monitoring methods to control and evaluate theperformance of the treated dam and the grout if degradation has occurred.Findings from literature generally indicates a high risk of instability andlow permanence of sodium silicate when grouted in an embankment dam.This type of grout will undergo degradation mainly in two forms: syneresisinduced shrinkage and leaching due to grout erosion or dissolution. As thedegradation has developed, an increase in permeability of the repaireddam core is a potential consequence.How the potential degradation of sodium silicate will affect the treateddams is suggested to be observed by monitoring the permeability of thegrouted core. Applicable monitoring methods for this purpose aremeasurements of pore pressure and temperature using piezometers. Thesecond direct method of monitoring a changed dam behavior is suggestedto be leakage analysis, in order to detect potentially increased leakagebecause of the grout degradation. An indirect way to investigate the damperformance is suggested to be monitoring of the grout state. Measurementof ion concentration of sodium and silicon respectively in leakage waterusing selective-ion electrodes will reveal any increase in ion concentrationdue to the potential grout dissolution or leaching.
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Bukenya, Patrick. "Structural performance evaluation of concrete arch dams using ambient vibration monitoring and GNNS systems." Doctoral thesis, Faculty of Engineering and the Built Environment, 2021. http://hdl.handle.net/11427/32568.

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Societies around the world are heavily dependent on civil engineering infrastructures such as concrete dams that provide necessities such as water supply for irrigation, hydroelectric power generation and prevention of floods. As a result, it is important to ensure that concrete dams are protected such that their failure is avoided. To ensure the structural safety of these structures, concrete dams are continuously monitored by sensors installed on the dam to detect any unusual behaviour. Data collected by the sensors include environmental variables (temperature and water levels) and dam responses (deformations, stresses, strains, natural frequencies) which indicate the structural behaviour of dams. This implies that research in the analysis of the collected data is very important. Methods used in the analysis of dam monitoring data include data-driven models, physical-based models and hybrid models. Data-driven models utilise environmental variables as independent factors and dam responses as dependent factors. The trends in the dam responses can be learnt for purposes of monitoring and prediction by understanding the interactions between environmental variables and dam responses. Dam specialists have mainly focused on predicting the static deformations of dam walls using environmental variables through statistical modelling. Dynamic properties such as natural frequencies also provide valuable information on the structural behaviour of dams as they are influenced by the changes in environmental variables. To the best of my knowledge, there is no scientific literature that has studied the influence of environmental variables on natural frequencies through statistical modelling. The increase in the amount of data collected from monitoring devices installed on dams has led to the use of advanced statistical models to extract important information about the behaviour of dams. Machine learning algorithms have been developed to solve problems of large data sets and nonlinearity between variables. In particular, there are no studies that exist in the prediction of natural frequencies using measured environmental variables (water level and temperature). Therefore, the purpose of this study was to understand the effect of water level and temperature on natural frequencies and deformations. The case study used in this thesis is Roode Elsberg dam, a concrete arch dam located in South Africa. Natural frequency data used was collected between December 2014 and June 2017 while deformation data used was between January 2012 and June iii 2016. Observations indicated that water level was the dominant factor driving the variation of natural frequencies with temperature affecting the natural frequency variations in periods of constant water levels. On the other hand, temperature was the driving factor in deformation variations with water level also affecting deformation variation. Due to the nonlinear relationship between environmental variables and dam responses, a machine learning-based algorithm known as Gaussian process regression models were developed to predict natural frequencies. In Gaussian process regression, the choice of a covariance function is very important in producing good results. The ability of the different covariance functions in Gaussian process regression models, to predict natural frequencies and dam deformations, was studied. The performance of Gaussian process regression models was compared with other machine learning algorithms (BRT, SVR and ANN), multivariate adaptive regression splines and the commonly used MLR models in the prediction of natural frequencies and deformations. Results suggested that the GPR model is the most suitable and more accurate in the prediction of dam responses. Finally, robust statistics are introduced in the identification of anomalies in the collected data. Furthermore, univariate methods are used to identify any abnormalities in dam behaviour. Results indicated, there were no abnormalities in the dam behaviour.
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Books on the topic "Monitoring of dams"

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Penman, A. D. M. Instrumentation, monitoring and surveillance: Embankment dams. A.A. Balkema, 1999.

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Foundations, USSD Committee on Monitoring of Dams and their. General guidelines for automated performance monitoring of dams. U.S. Society on Dams, 2002.

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Abashidze, V. Geophysical monitoring of geodynamical processes in region of Enguri high dams. Pub. House Metsniereba, 2001.

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Protection, Alberta Alberta Environmental. Environmental monitoring of the Oldman River Dam: Eight years of progress. Alberta Environmental Protection, 1999.

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Peven, Charles M. Rock Island Dam smolt monitoring, 1988: Final report. U.S. Dept. of Energy, Bonneville Power Administration, Division of Fish and Wildlife, 1988.

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Stewart, Bill M. Investigation of acid production, leaching, and transport of dissolved metals at an abandoned sulfide tailings impoundment: Monitoring and physical properties. U.S. Dept. of the Interior, Bureau of Mines, 1995.

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Da ba an quan jian ce yu jian kong: Dam safety monitoring and controlling. Zhongguo shui li shui dian chu ban she, 2004.

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Commission, Mekong River. Social impact monitoring and vulnerability assessment: Report on a regional pilot study for the Mekong Corridor. Mekong River Commission, 2010.

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Tanner, Dwight Q. Data-collection methods, quality-assurance data, and site considerations for total dissolved gas monitoring, lower Columbia River, Oregon and Washington, 2000. U.S. Dept. of the Interior, U.S. Geological Survey, 2001.

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Tanner, Dwight Q. Data-collection methods, quality-assurance data, and site considerations for total dissolved gas monitoring, lower Columbia River, Oregon and Washington, 2000. U.S. Dept. of the Interior, U.S. Geological Survey, 2001.

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Book chapters on the topic "Monitoring of dams"

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Milanović, Petar, Nikolai G. Maximovich, and Olga Meshcheriakova. "Monitoring." In Dams and Reservoirs in Evaporites. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-18521-3_8.

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Oliveira, Sérgio, and André Alegre. "Seismic and Structural Health Monitoring of Dams in Portugal." In Seismic Structural Health Monitoring. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-13976-6_4.

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Inaudi, Daniele. "Optical Fiber Sensors for Dam and Levee Monitoring and Damage Detection." In Levees and Dams. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-27367-5_5.

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Cunha, José C., and Vítor Duarte. "Monitoring PVM programs using the DAMS approach." In Recent Advances in Parallel Virtual Machine and Message Passing Interface. Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/bfb0056585.

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Pinto, A. Veiga. "Monitoring and Safety Evaluation of Rockfill Dams." In Advances in Rockfill Structures. Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-011-3206-0_16.

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HOPKINS, J. K., J. M. REID, J. McCAREY, and C. BRAY. "Roadford Dam – 20 years of monitoring." In Managing dams Challenges in a time of change. Thomas Telford Ltd, 2010. http://dx.doi.org/10.1680/mdctc.40991.0016.

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Scudder, Thayer. "My Increasing Disillusionment with the Planning, Implementation, Monitoring, and Evaluation of Large Dams, Especially as Illustrated by The World Bank—The Largest and Most Influential Financier of Large Dams." In Large Dams. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-2550-2_4.

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Popescu, Theodor D. "Independent Component Analysis with Application to Dams Displacements Monitoring." In Advances in Automatic Control. Springer US, 2004. http://dx.doi.org/10.1007/978-1-4419-9184-3_19.

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Corsetti, Marco, Michele Manunta, Maria Marsella, Silvia Scifoni, Alberico Sonnessa, and Chandrakanta Ojha. "Satellite Techniques: New Perspectives for the Monitoring of Dams." In Engineering Geology for Society and Territory - Volume 5. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-09048-1_190.

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Salamon, Jerzy, William Dressel, and Daniel Liechty. "Monitoring of Dams Suffering from ASR at the Bureau of Reclamation." In Diagnosis & Prognosis of AAR Affected Structures. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-44014-5_4.

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Conference papers on the topic "Monitoring of dams"

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Plopeanu, Marin. "SPECIAL GEODETIC MONITORING OF ROCKFILL DAMS - RAU?OR DAM CASE." In 19th SGEM International Multidisciplinary Scientific GeoConference EXPO Proceedings. STEF92 Technology, 2019. http://dx.doi.org/10.5593/sgem2019/2.2/s09.039.

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OLIVEIRA, SÉRGIO, and ANDRÉ ALEGRE. "Seismic and Structural Health Monitoring Systems for Large Concrete Dams." In Structural Health Monitoring 2019. DEStech Publications, Inc., 2019. http://dx.doi.org/10.12783/shm2019/32396.

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Mittrup, Ingo, and Dietrich Hartmann. "Structural Monitoring of Dams Using Software Agents." In International Conference on Computing in Civil Engineering 2005. American Society of Civil Engineers, 2005. http://dx.doi.org/10.1061/40794(179)31.

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COLOMBO, MARTINA, MARCO DOMANESCHI, and ALDO GHISI. "Validation of Finite Element Models of Existing Concrete Dams, Through Monitoring Data." In Structural Health Monitoring 2015. Destech Publications, 2015. http://dx.doi.org/10.12783/shm2015/61.

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Castignolles, Nathalie, Michel Cattoen, and M. Larinier. "Automatic system for monitoring fish passage at dams." In SPIE's 1994 International Symposium on Optics, Imaging, and Instrumentation, edited by Andrew G. Tescher. SPIE, 1994. http://dx.doi.org/10.1117/12.186555.

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Coetzee, G. L. "Smart Construction Monitoring of Dams With UAVS - Neckartal Dam Water Project Phase 1." In 20th Biennial Conference of the British Dam Society. ICE Publishing, 2018. http://dx.doi.org/10.1680/sdar.64119.445.

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Oden, Charles. "Monitoring Earthen Dams and Levees Using Wireless Geophysical Sensors." In Symposium on the Application of Geophysics to Engineering and Environmental Problems 2011. Environment and Engineering Geophysical Society, 2011. http://dx.doi.org/10.4133/1.3614113.

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Siddula, Sai Sreekar, Phaneendra Babu, and P. C. Jain. "Water Level Monitoring and Management of Dams using IoT." In 2018 3rd International Conference On Internet of Things: Smart Innovation and Usages (IoT-SIU). IEEE, 2018. http://dx.doi.org/10.1109/iot-siu.2018.8519843.

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Lee, Keun-Soo, In-Ky Cho, Hee-Woo Lee, Hye-Jin Kang, Yeon-Jeong Kim, and Hwan-Ho Yong. "3D Effects on 2D Resistivity Monitoring in Embankment Dams." In Near Surface Geophysics Asia Pacific Conference, Beijing, China 17-19 July 2013. Society of Exploration Geophysicists, Australian Society of Exploration Geophysicists, Chinese Geophysical Society, Korean Society of Earth and Exploration Geophysicists, and Society of Exploration Geophysicists of Japan, 2013. http://dx.doi.org/10.1190/nsgapc2013-031.

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Li, Zhanchao, Jian Wang, Tengfei Bao, and Huijing Hou. "Improved Safety Monitoring Model of Crack in Concrete Dams." In 12th Biennial International Conference on Engineering, Construction, and Operations in Challenging Environments; and Fourth NASA/ARO/ASCE Workshop on Granular Materials in Lunar and Martian Exploration. American Society of Civil Engineers, 2010. http://dx.doi.org/10.1061/41096(366)57.

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Reports on the topic "Monitoring of dams"

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Griswold, Jim, Richard L. Townsend, and John R. Skalski. Monitoring and Evaluation of Smolt Migration in the Columbia Basin : Volume XV : Evaluation of the 2007 Predictions of the Run-Timing of Wild and Hatchery-Reared Salmon and Steelhead Smolts to Rock Island, Lower Granite, McNary, John Day, and Bonneville Dams using Program RealTime. Office of Scientific and Technical Information (OSTI), 2008. http://dx.doi.org/10.2172/947617.

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Burgess, Caitlin, and John R. Skalski. Monitoring and Evaluation of Smolt Migration in the Columbia Basin : Volume IX : Evaluation of the 2001 Predictions of the Run-Timing of Wild and Hatchery-Reared Migrant Salmon and Steelhead Trout Migrating to Lower Granite, Rock Island, McNary, and John Day Dams using Program RealTime. Office of Scientific and Technical Information (OSTI), 2001. http://dx.doi.org/10.2172/961879.

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Jörg, Leonhard, and Andreas Schibany. Bausteine für das Monitoring der aws-Technologieprogramme. Technopolis Forschungs- und Beratungsges.m.b.H, 2006. http://dx.doi.org/10.22163/fteval.2006.183.

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Griswold, Jim. Monitoring and Evaluation of Smolt Migration in the Columbia Basin, Volume XIV; Evaluation of 2006 Prediction of the Run-Timing of Wild and Hatchery-Reared Salmon and Steelhead at Rock Island, Lower Granite, McNary, John Day and Bonneville Dams using Program Real Time, Technical Report 2006. Office of Scientific and Technical Information (OSTI), 2007. http://dx.doi.org/10.2172/963283.

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Hillson, Todd, Sharon Lind, and William Price. McNary Dam, Ice Harbor Dam, and Lower Monumental Dam Smolt Monitoring Program; 1996 Annual Report. Office of Scientific and Technical Information (OSTI), 1997. http://dx.doi.org/10.2172/563834.

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Wagner, Paul. McNary Dam Smolt Monitoring Program; 1991 Annual Report. Office of Scientific and Technical Information (OSTI), 1992. http://dx.doi.org/10.2172/771550.

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Peven, Charles M., Diane H. Sheffield, and Paul C. Fielder. Rock Island Dam Smolt Monitoring, 1987 Final Report. Office of Scientific and Technical Information (OSTI), 1987. http://dx.doi.org/10.2172/766705.

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Peven, Charles M., and Paul C. Fielder. Rock Island Dam Smolt Monitoring, 1988 Final Report. Office of Scientific and Technical Information (OSTI), 1988. http://dx.doi.org/10.2172/766713.

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Peven, Charles M. Rock Island Dam Smolt Monitoring, 1991 Annual Report. Office of Scientific and Technical Information (OSTI), 1991. http://dx.doi.org/10.2172/766722.

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McDonald, Robert. Rock Island Dam Smolt Monitoring; 1996 Annual Report. Office of Scientific and Technical Information (OSTI), 1996. http://dx.doi.org/10.2172/564125.

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