SEEPAGE MONITORING SYSTEM BASED ON FIBRE-OPTIC DISTRIBUTED TEMPERATURE SENSING AT THE TAILINGS DAMS AT HÖTJÄRN, SWEDEN (*)

Q. 97 98 R. 37 COMMISSION INTERNATIONALE DES GRANDS BARRAGES ------- VINGT-CINQUIÈME CONGRÈS DES GRANDS BARRAGES Stavanger, Juin 2015 ------- SEEPAGE MONITORING SYSTEM BASED ON FIBRE-OPTIC DISTRIBUTED TEMPERATURE SENSING AT THE TAILINGS DAMS AT HÖTJÄRN, SWEDEN (*) Sam JOHANSSON Ph. D., M. Sc. (Civ. Eng.), Dam Safety Monitoring, HydroResearch AB Pontus SJÖDAHL Ph. D., M. Sc. (Civ. Eng.), Dam Safety Monitoring, HydroResearch AB Jan BURSTEDT Process Engineer, Boliden Mineral AB SWEDEN 1. INTRODUCTION On-line seepage monitoring based on temperature measurements in optical fibres have recently been taken into operation in several hydropower and tailings dams in Sweden. The objective with these measurements is to provide complementary information to the conventional seepage and pressure measurements. The detailed information - given each meter all along the dams - have been found useful especially at extended dams such as levees and long tailings dams. Installation possibilities are excellent when new dams are constructed, allowing the cable to be installed at desired locations. Optical cables are now a standard installation in all new tailings dams owned by the two leading mining companies in Sweden. Until now, about 50 km cables have been installed in ten tailings dams at the four major mining areas in Sweden, Aitik, Boliden, Kiruna, and Malmberget (ongoing). (*) Système de mesures des infiltrations par mesure distribuée de température par fibre optique dans les barrages de stériles à Hötjärn, Suède. 563

Q. 98 97 R. 37 One example is the tailings dams at Hötjärn owned and operated by Boliden Mineral AB. About 13 km cables are installed in the two dams constructed in 2008-2011. A permanent monitoring system for continuous monitoring was taken into operation in 2012. Automatic data evaluation is carried out on-line since 2013, sending evaluated data and alarms to the dam owners SCADA system (ABB 800xA). Data is also presented on a WEB-interface for further evaluation. Experience from the first years of measurements have shown the ability to quantity seepage flow and identify areas with different flow regimes. The alarm function has also been tested. Some examples are shown in this paper. 2. HÖTJÄRN TAILINGS DAMS 2.1. GENERAL The deposit at Hötjärn, just outside Boliden, was constructed in 2008 to 2011. It is surrounded by two dams, Dam F and Dam H (Fig. 1). The area of the deposit is 230 ha, which will give a lifetime of about 20 years assuming present production. Dam F has a length of 0.9 km and Dam H is 2.7 km long. The maximum height is about 20 m at its final stage, with the crest level at +224.5 m. The crest level is at present +219.0 m. The dam has a till core, and is founded on moraine. Dam F Dam H Fig. 1 Hötjärn tailings dams, dam F and dam H. Barrages de stériles d Hötjärn, barrage F et barrage H. 564

Q. 97 98 R. 37 2.2. CONVENTIONAL MONITORING SYSTEM AND OPERATION Seepage water passing through the dams is collected in the drainage system placed along the dams. Three weirs along Dam F and five for Dam H are placed in a way that measurements can be made separately. The length for each part varies between 200 m and 900 m. The flow is measured automatically by pressure sensors, and the result can be seen on-line by the ADAS system (ABB 800xA). There are also monitoring sections equipped with piezometers, with automated measurements. 3. TEMPERATURE MEASUREMENTS USING OPTICAL FIBRES 3.1. FIBRE OPTIC TEMPERATURE MONITORING SYSTEM COMPONENTS Distributed temperature sensing (DTS) using optical fibres is performed using a monitoring unit and a cable with standard optical fibres. The method takes advantage of the fact that the reflection characteristics of laser light, travelling down an optical fiber, vary with temperature [1, 2] and strain [3]. The measuring instrument uses a laser to emit pulses of light into the sensing fiber. A detector measures the reflections from the fiber as the pulse of light travels down its length. Measuring the change in power and color of these reflections against time allows the instrument to calculate temperature at all positions along the fiber. The key feature is that the fiber itself is the sensor and it can be used to measure along its entire length. The accuracy may be down to 0.01 C with advanced systems. However, less expensive systems with an accuracy of <0.1 C are also available. Most systems have a measurement length of 10 km or less. The spatial resolution is normally 1 m, which is enough for most dam applications. Experiences from several installations can be found in [4-9]. To achieve the high performance as described above the installation must be done with great care. If the cable is damaged during construction signal losses will increase, which could significantly reduce the monitoring accuracy. There are also several monitoring aspects that must be considered as further described by [2]. The technology is still developing rapidly resulting in higher performance and lower costs. The monitoring units used at Hötjärn is Sensornet Halo for Dam F and Silixa Ultima-M for dam H (Fig. 2). The Sensornet Halo unit has four channels and a measuring range of 4 km. The sampling resolution is 2 m. Silixa Ultima-M is a more powerful unit with a larger measuring range (10 km in four channels), higher accuracy and higher sampling resolution (0.25 m). 565

Q. 98 97 R. 37 a) b) Fig. 2 Monitoring units at Dam F- Sensornet Halo (a) and Dam H- Silixa Ultima-M (b) Les unités de mesure au barrage F Sensornet Halo (a) et au barrage H Silixa Ultima-M (b) 3.2. INSTALLATION OF FIBRE OPTIC CABLES Installation of cable must be carried out carefully in order to not damage the fibres inside the cable. The signal was therefore measured several times during construction of the dam, when the installation of the cable was made by the contractor of dam construction. The signal in all cables in both Dam F and H are excellent. Three cables were installed in the dam toe (Fig. 3). One cable in the inner part of the drainage filter (called Cable filter) in order to detect the seepage through the moraine. A second cable was placed just upstream the drainage pipe in order to detect seepage both through the till core and passing through the foundation (called Cable drainage). A third cable (called Upper cable ) was placed closer to the surface in order to measure strain in two directions (Fig. 4). When the dam is raised to its final height it will also be used for detection of seepage and maybe also indicate the location of the ground water level. At present it is located above the ground water level, but will be more useful when the dam has reached its final height. 566

Q. 97 98 R. 37 Fig. 3 Location of the three cables in the tailing dams at Hötjärn. The dotted line shows the final extension of the dams. Emplacement des 3 câbles dans les barrages de stériles à Hötjärn. La ligne pointillée montre l extension finale des barrages. (1) Moraine - finer (1) Moraine - granulométrie la plus fine (2) Moraine -fine (2) Moraine - granulométrie fine (3) Filters (3) Filtres (4) Upper cable in moraine (4) Câble supérieur dans la moraine (5) Cable in filter (5) Câble dans le filtre (6) Cable in drainage (6) Câble dans le drain Fig. 4 Installation of the Upper cable at dam F, c.f. (4) in Fig. 3. Installation du câble supérieur dans le barrage F, r.e. (4) dans Fig. 3. 567

Q. 98 97 R. 37 3.3. INTEGRATION WITH ADAS Large amount of data is collected by the two monitoring units. At dam F every second meter along the dam is measured, resulting in data sets of 2854 data points. Measurements at Dam H are performed every meter giving in total 17429 values. However, measurements are taken in a loop (i.e. the dam is measured twice) so the amount of data can be reduced. Moreover, some parts of the fibre is outside the area of interest and just acting as data carrier. Those data can be neglected, the number of active data points can be reduced to 1220 in dam F and 8299 in dam H. The total number of data points too large to be exported in full to Boliden ADAS (ABB 800xA). It was therefore decided initially to export the calculated seepage flow values, integrated over selected sub-lengths (similar to the parts of the drainage collection for the seepage monitoring weirs), and the number of alarms occurring on the same length of the dam. This is done for the fibres Filter and Drainage. For the Upper cable only alarms are evaluated. Seepage calculations are not relevant as the cable is located about ground water level at present. The total number of exported values to ADAS is therefore reduced to 32 for Dam F and 57 for dam H. It was also initially decided to export all seepage values along the dam, assuming that seepage evaluation was relevant along the entire dam, and to later remove areas, where the assumptions for seepage calculations are not valid. All calculations and alarm evaluations are made by a computer (XSeepT) located close to the monitoring unit. From the computer data is exported to ADAS via Modbus protocol. 3.4. EXPERIENCES In general the operation performance has been excellent with reliable data collection and good data quality. However during a period with extremely low temperature it was found that the heating in the monitoring house was not sufficient, and the environment temperature became lower than the lowest operation temperature for the units (about +5 C). During spring 2014 the temperature control in the monitoring houses was improved, with a higher accuracy as result. The installation work was good and no additional signal losses can be seen. The calibration of the system can be done with good accuracy. 568

Q. 97 98 R. 37 4. MONITORING AND EVALUATION 4.1. BASIC PRINCIPLES The seepage evaluation method uses the natural seasonal temperature variation that occurs in all surface water (such as lakes, reservoirs and rivers). The seepage flow causes a seasonal temperature variation inside the dam. This seasonal temperature variation can be measured in the dam and used to evaluate the seepage flow. The method is a result of several research projects founded by the Swedish Power Association/Elforsk between 1988 and 1996 summarized in [10] and [11]. The objective with this work was to develop useful engineering tools for seepage interpretation. Fig. 5 Basic thermal processes in an embankment dam. Principaux processus thermiques dans un barrage en enrochement (1) Seasonal temperature variation (1) Variation de température saisonnière (2) Advective transport and heat conduction (2) Advection et conduction thermique (3) Heat exchange with air (3) Échange chaleur/air (4) Geothermal flow (4) Flux géothermique Theoretical analyses and field experience show that a significant interrelation between seepage flow and temperature response exist in an embankment dam. The temperature field is mainly given by seepage flow from the reservoir where seasonal temperature variation occurs; and by heat conduction from the surface creating a seasonal variation that can be ignored about ten meters below the dam surface. The temperature field inside the dam will thus be a result of the seasonal temperature variations on the surface of the dam and on the seepage flow rates passing through the dam. With increasing distance from the interface boundary 569

Q. 98 97 R. 37 between the reservoir water and the embankment there will be attenuation and a time lag of the seasonal variation. Effects of snow melting and heavy rain will also cause sudden temperature changes. The factors described above can be used for qualitative assessment and general considerations. More sophisticated evaluation can be made using FEmodelling of thermal processes. In these models the temperature distribution in the dam is a result of the coupled processes of heat flow and ground water flow through the dam. The problem is modelled using Richards equation, solving the flow in the saturated and unsaturated regions. The thermal process is described by heat conduction and convection. The boundary conditions are pressure (head) described by reservoir water level and downstream water level, and temperatures in water and air. Since those are time dependent a transient solution is needed. Numerical modelling for the two examples presented in this paper (section 4.2 and 4.3) has been performed using commercial software COMSOL (www.comsol.com), with the Subsurface Module (former Earth Science Module ). The software is capable of solving the coupled transient problem. Time dependent material properties are also allowed, either as real data or simplified analytic values. 4.2. TEMPERATURE CHANGES AT SUDDEN SEEPAGE INCREASE From an engineering point of view the ability to detect seepage flow changes are more important than to estimate the flow rates with high accuracy. Different sudden leakage increases was modelled to find out more of the detectability of the method. Some results were presented in [9] and one selected case in Fig. 6. The model was built for a small embankment dam where the temperature was measured close to the drainage beneath the downstream toe. An increased leakage was assumed to occur during 10 days, at different times of the year. The flow was increased by changing the hydraulic conductivity in a zone of the core so that the seepage after the 10 days was 3.7 times the original seepage flow. Even though the seepage flow remains very small, the temperature change is significant for all situations. The result has been valuable to develop and test alarm settings for detection of sudden leakages. 570

Q. 97 98 R. 37 (2) 25 20 15 10 5 (3) (4) (5) (6) (7) (8) 0 Jan 1 Jul 2 Jan 1 Jul 2 Jan 1 Jul 2 Jan 1 (1) Fig. 6 Calculated temperatures for intact dam (1st year), defect starting at different dates (2nd year), and increased constant flow (3rd year). Flow increases due to simulated defects are 3.7 times. Modélisation des températures d un barrage sain (1 re année), défauts relevés à différentes dates (2 e année) et augmentation du débit constant (3 e année). Les débits dus aux défauts simulés sont multipliés par 3,7. (1) Date [-] (1) Date [-] (2) Temperature [ C] (2) Température [ C] (3) No defect (3) Pas de défaut (4) Defect on February 5 (4) Défaut le 5 février (5) Defect on April 6 (5) Défaut le 6 avril (6) Defect on August 4 (6) Défaut le 4 août (7) Defect on December 2 (7) Défaut le 2 décembre (8) Reservoir water (8) Retenue 4.3. TEMPERATURE RESPONSE AT PROGRESSING INTERNAL EROSION Simulations of normal conditions can support interpretation of the flow regime in the dam. It can be used to verify that reasonable flows give rise to certain temperature variation inside the dam. In some cases it can be used to optimize the location for installation of temperature sensors or optical fibre. This can be of particular benefit for tailings dams, for which construction typically is ongoing during the operation of the mine and thus there is a possibility to build in equipment in the process. Numerical modelling can also be used to simulate different scenarios, such as a slow internal erosion processes. The simulated internal erosion scenario develops during ten years with the hydraulic conductivity doubled each year in a one meter high zone reaching some 200 m from the top of the tailings pond and beneath the base of the start dam (Fig. 7). This represents a study at another Boliden dam, where a specific question was if the existing piezometers would be able to detect changes in the deeper part of the dam. 571

Q. 98 97 R. 37 Fig. 7 Simulations of an internal erosion scenario in a large tailings dam. Situation after 4 years (a) and after full development of the defected zone (b). Simulations d'un scénario d'érosion interne dans une grande digue de stériles. Situation après 4 ans (a) et après le développement complet de la zone de défaut (b) (1) x [m] (1) x [m] (2) Elevation [-] (2) Cote [ C] (3) Temperature [ C] (3) Température [ C] The simulations show that in large dams the expected seasonal temperature variation is typically low if the dam perform as intended. However, it takes relatively small seepage rates for significant temperature variations to occur inside the dam. If the temperature can be measured in the seepage path there is excellent chances of early detection of a seepage increase and good possibilities of seepage quantification. 572

Q. 97 98 R. 37 4.4. SEEPAGE FLOW ESTIMATIONS Temperature data can be interpreted with different ambitions. The most basic evaluation involves comparing temperatures over time, i.e. is there an increasing trend or higher variations, etc. Another simple approach is to compare temperatures at different locations with similar conditions, for example the temperature is constant along the dam with a local anomalous exception. Next, the seepage may be estimated using different levels of complexity. Qualitative evaluation based on temperature data. Quantitative evaluation with simplified model (DamTemp) Quantitative evaluation with advanced FE-model The qualitative evaluation method is in many cases sufficient to detect leakage anomalies. Measurement over a long time period will improve the evaluation quality. Once the anomalous seepage is detected it can be evaluated using other types of monitoring or other methods of investigation. However, a detailed interpretation of the results may also be a way forward. Such a detailed interpretation of temperature measurements may consist of quantitative evaluation. The simplified 2D approach as described in [11], introduces some simplification assuming advective heat transport only in the seepage zone (outside the zone the seepage is assumed to be small and only heat conduction is considered). Moreover it disregards from affection from surface air temperatures. A major advantage is that seepage can be quantified just from temperature measurements and thermal properties and no data on hydraulic conductivity have to be assumed. The simplicity of this approach has made it suitable for automatic seepage calculations for continuous temperature monitoring, and it has been implemented in the system at Hötjärn. The conditions for seepage flow should always be considered regarding cable installation (such as installation depth and distance to the ground water). The method assumes that the energy flux is mainly a result of the advective energy transport. This will be valid at significant seepage flow rates, but will not be valid at low seepage flow rates. If the method is used at such conditions the calculated flow will be overestimated. The parts of the dam where the basic assumptions are not fullfilled can be removed after some years of measurements, as described in [9]. More advanced interpretation methods are based on numerical modelling, as described above. This is preferred when there is large variations in reservoir level, significant three-dimensional phenomena, known local concentrated leaks, etc. 573

Q. 98 97 R. 37 4.5. ALARMS FOR SUDDEN TEMPERATURE RESPONSE A sudden temperature change will occur at a significant change of the seepage flow rate as discussed above. Based on the temperature variation during the preceding year, the next value can be predicted and compared with the actual measured value. This is done for each measured value after each measurement is taken. If the difference between measured value and expected value is larger than a given threshold an alarm flags. Temperature difference maps illustrate where the largest changes are and may be helpful in setting alarm levels. The number of values exceeding the alarm limits will be summarized for each chosen zone of the dam. One example of a temperature difference plot from Dam F is given in Fig. 8. Fig. 8 Temperature difference between measured and predicted temperature between chainage 0+650 and 0+779 in Dam F. Différence de température entre la température mesurée et prévue entre les chaînages 0+650 et 0+779. (1) Dam chainage [m] (1) Longueur [m] (2) Date [-] (2) Date [-] (3) Temperature [ C] (3) Température [ C] The qualitative evaluation method is in many cases sufficient to detect leakage anomalies. Measurement over a long time period will improve the evaluation quality. Temperature maps are a powerful tool as they have the advantage of showing both changes in time and changes along the dam. 574

Q. 97 98 R. 37 5. RESULTS 5.1. TEMPERATURE MEASUREMENTS One useful way to present temperature data along the dam with time is to make color plots for each of the cables. Here, we will present data from two parts of dam H in order to describe how qualitative evaluations can be made. When the measured temperature is homogenous along the dam Fig. 9a, showing the temperature in the filter) it can mainly be a result of heat conduction from the air (indicating very low seepage because the energy transport from the advective flow can be ignored) or a homogenous seepage flow. The maximum temperature occurs in late August and the lowest in early May. A similar result can also be seen in the drainage (Fig. 9b), also indicating either that heat conduction from the surface occurs or that homogeneous seepage through the foundation is present or both. For this site, seasonal temperature variations from the surface at the location of the cables in the filter and drain has been estimated to about 5 C. This means that seepage flow estimations, assuming that heat conduction from the surface can be ignored, only can be done at larger seasonal temperature variation. Similar temperature along the dams can generally be found in both dams indicating that they are well constructed. No severe temperature anomalies have been found. However, only some minor temperature deviations exists, which can be seen in Fig. 10. The temperature in the filter is slightly higher at chainage 1+435 in the filter during the winter. The temperature is also higher here, as in chainage 1+370. There are also some minor deviations in the drainage at 1+440, were some smaller temperature variation occur. This indicate some inflow of groundwater, which agree well with observations during the construction of the dam. In this case it is probable that some of the ground water also will pass into the filter, and not only be collected in the drain. The temperature variation is still small, indicating low flow rates. Data will be used for comparison against coming year s data. Deviations from these seasonal temperature variations will be detected by the alarm algorithm; both when they exceed the alarm value and where the change is located. 575

Q. 98 97 R. 37 a) b) Fig. 9 Temperature in the filter (a) and in the drain (b) between chainage 0+601 and 0+699. Température dans le filtre (a) et dans le drain (b) entre les chaînages 0+601 et 0+699. (1) Dam chainage [m] (1) Longueur (m] (2) Date [-] (2) Date [-] (3) Temperature [ C] (3) Température [ C] 576

Q. 97 98 R. 37 a) b) Fig. 10 Temperature in the filter (a) and in the drain (b) between chainage 1+300 and 1+550. Température dans le filtre (a) et dans le drain (b) entre les chaînages 1+300 et 1+550. (1) Dam chainage [m] (1) Longueur (m] (2) Date [-] (2) Date [-] (3) Temperature [ C] (3) Température [ C] 577

Q. 98 97 R. 37 5.2. SEEPAGE ESTIMATIONS, INPUT AND DATA Temperature measurements are made for each meter in Dam H and each second meter for Dam F according to the different spatial resolution of the monitoring units. The calculated seepage flow rates is given as flow per meter dam. These values are integrated over the same drainage areas as the weirs. The seepage flow calculations are based on the thermal properties of the soil, water temperature in the upstream reservoir, and length from an assumed inflow point to the actual point on the fibre. These data is needed for the simplified approach for the automated seepage flow calculations as described above. There are no measurements yet made in the water, so the water temperature is assumed to vary between 0 and 20 C, based on relevant measurements in adjacent rivers and lakes in 2014. Result from the first year indicate calculated seepage flow rates are four times higher in Dam F and about seven times higher in Dam H compared with measured flows in the weirs (Fig. 11), after removing areas where impact from heat conduction is clearly dominates. The difference between the results from the dams can be explained by the size of the dams, where Dam H is larger, giving longer streaming lengths and larger impact from heat conduction. The measured seepage flow in the weirs indicate seepage flows about 0.001 l/(sm). This is lower than what can be detected using temperature measurements in these dams, i.e. seepage flow evaluation will be uncertain in this case, especially in Dam H. (1) 12 10 8 6 4 2 0 Weir H1 Weir H2 Weir H3 Weir H4 Weir H5 Weir F1 Weir F2 Weir F3 (2) (3) (4) Fig. 11 Measured seepage flow in weirs at dam H (H1-H3) and Dam F (F1-F3), measured from left and right, and calculated flow from temperature measurements for corresponding areas in filter and drain. Débit d'infiltration mesuré dans les déversoirs du barrage H (Weir H1-H3) et du barrage F (Weir F1-F3), mesuré à partir de la gauche vers la droite, et débit calculé à partir des mesures de température pour les zones de filtre et drainage correspondantes. (1) Seepage flow [m] (1) Débit d écoulement [m] (2) Measured flow [l/s] (2) Débit mesuré [l/s] (3) Calculated flow in filter [l/s] (3) Débit calculé dans le filtre (4) Calculated flow in drainage [l/s] (4) Débit calculé dans le drainage [l/s] 578

Q. 97 98 R. 37 6. DISCUSSION AND CONCLUSIONS Temperature distribution in tailings and embankment dams is dependent on the seepage regime. Experience from temperature measurements at Hötjärn tailings dams shows that the result can be used to identify areas with anomalous seepage areas and monitor changes along the entire dam. Automatic quantification of seepage flow rates will however be more difficult to perform in this case, because the geometry of the dam. Interpretation techniques range from basic qualitative comparisons of temperatures over time (or between different parts of the dam) to more sophisticated seepage quantification techniques, involving numerical modelling. In many cases a simplified approach can be used to estimate the seepage flow. This can be made on-line, and data can be exported to the ADAS system. The seepage flow which is measured in the weirs in the dams at Hötjärn indicate very low flow rates, and lower than the sensitivity for the temperature based system. The energy transport by heat conduction from the surface will then be more important than the advective flow by the seepage. From an engineering standpoint, detection of sudden increases in seepage flows has highest priority for seepage monitoring system. Alarm has been set to detect difference between measured and predicted temperature at each measurement point. This will give good possibilities to detect small seepage changes all along the dams. The geometry of tailings dams is often flat which gives long streaming path lengths and larger exposure for heat conduction from the surface. These two factors reduces the sensitivity to quantify the seepage flow, and the ability to detect small seepage flow changes at Hötjärn. Flow rates in the order of 0.02 l/(s,m) are however reasonably possible to detect, i.e. about 20 times higher flow rates than the mean flow measured today. These flow rates are still low, and the measuring approach can be classified as Early detection of internal erosion. Distributed temperature sensing systems using measurements in fibre-optic cables can efficiently measure temperature over several kilometres dam length as the case at Hötjärn. This measurement technique presents new possibilities for dam monitoring, especially its ability to give detailed local information about seepage flow changes in the dam. Therefore distributed temperature sensing may be a good complement to conventional seepage monitoring. 579

Q. 98 97 R. 37 ACKNOWLEDGEMENTS We are immensely grateful to Boliden Mineral AB who has been very supportive of this work and for allowing data from the Hötjärn dams to be published. We will also express our gratitude to Carl Nygren, HydroResearch, for all work with data evaluation and presentation. REFERENCES [1] Dakin, J.P., Pratt, D.J., Bibby, G.W., and Ross, J.N. (1985), Distributed optical fiber Raman temperature sensor using a semiconductor light source and detector, Electron. Lett., vol. 21, no. 13, pp. 569-570, June 1985. [2] Tyler, S. W., Selker J. S., Hausner, M. B., Hatch, C. E., Torgersen, T., Thodal, C. E., Schladow, S. G. (2009) Environmental temperature sensing using Raman spectra DTS fiber-optic methods, Water Resources Research, Vol. 45, W00D23, 11 pages. [3] Parker, T.R., Farhadiroushan, M., Handerek, V.A. and Rogers, A.J. (1997) A fully-distributed simultaneous strain and temperature sensor using spontaneous Brillouin backscatter. IEEE Photon. Technol. Lett., vol. 9, pp. 979-981, July 1997. [4] Aufleger, M., Strobl, T. and Dornstädter, J. (2000) Fiber optic temperature measurements in dam monitoring four years of experience. ICOLD Congress Q78, R.1, Beijing. [5] Aufleger, M., Conrad, M., Perzlmaier, S. and Porras, P. (2005) Improving a Fiber Optics Tool for Monitoring Leakage. HRW, September 2005, Vol. 13, Number 4, p. 18-23. [6] Johansson, S. and Farhadiroushan, M. (1999) Fiber-optic System for Temperature measurements at the Lövön Dam. Elforsk Report 99:36, Stockholm, 25p. (available at www.elforsk.se) [7] Johansson, S., Farhadiroushan, M. and Parker, T. (2000) Application of fiber-optics systems in embankment dams for temperature, strain and pressure measurements some comparisons and experiences. ICOLD Congress Q78, R.69, Beijing. [8] Johansson, S., Sjödahl, P. Viklander, P. (2012) Upgrading seepage monitoring system using temperature measurements experience from measurements and modelling at Seitevare dam. ICOLD Congress Q95, R.18, Kyoto. [9] Sjödahl, P., Johansson, S., Westerberg, P. (2012) Experience from two embankment dams equipped with on-line seepage monitoring system based on distributed temperature sensing using optical fibres. ICOLD Congress Q95, R.28, Kyoto. 580

Q. 97 98 R. 37 [10] CEATI REPORT No. T062700-0214, A GUIDE FOR SEEPAGE MONITORING OF EMBANKMENT DAMS USING TEMPERATURE MEASUREMENTS, 2009, 62 pages [11] Johansson, S. (1997) Seepage Monitoring in Embankment Dams, Doctoral Thesis, TRITA-AMI PHD 1014, ISBN 91-7170-792-1, Royal Institute of Technology, Stockholm. SUMMARY On-line seepage monitoring based on temperature measurements in optical fibres have recently been taken into operation in several hydropower and tailings dams in Sweden. The objective with these measurements is to provide complementary information to the conventional seepage and pressure measurements. The detailed information - given each meter all along the damshave been found useful especially at extended dams such as long tailings dams. Installation possibilities are excellent when new dams are constructed, allowing the cable to be installed at desired locations. Optical cables are now a standard installation in all new tailings dams owned by the two leading mining companies in Sweden. One example is the tailings dams at Hötjärn, where about 13 km cables are installed at the two dams constructed in 2008-2011. A permanent monitoring system for continuous monitoring was taken into operation in 2012. Automatic data evaluation is carried out on-line since 2013, sending evaluated data and alarms to the dam owners SCADA system. Data is also presented on a WEB-interface. Experience from the first years of measurements have proved the ability to quantity seepage flow and identify areas with different flow regimes. The alarm function has also been tested. The result is also compared with the conventional seepage monitoring system. Some examples are shown in the paper in order to describe how the system works and its practical use in tailings dams. RÉSUMÉ L auscultation en continu des infiltrations, basée sur des mesures de température dans les fibres optiques a été mise en œuvre récemment dans plusieurs barrages hydroélectriques et barrages de stériles en Suède. L'objectif de ces mesures est de fournir des informations complémentaires aux mesures d infiltration et de pression conventionnelles. Ces informations détaillées obtenues avec une résolution d un mètre tout au long des barrages se sont avérées particulièrement utiles pour les barrages de grande longueur comme les 581

Q. 98 97 R. 37 digues de stériles. Les options d installation sont nombreuses lors de la construction de nouveaux barrages, puisque les câbles peuvent être installés aux endroits souhaités. Les câbles optiques sont maintenant intégrés de manière standard dans tous les nouveaux barrages de stériles appartenant aux deux principales sociétés minières de Suède. Les barrages de stériles à Hötjärn en sont un exemple : quelque 13 km de câbles sont installés dans les deux barrages construits en 2008-2011. Un système de suivi pour la surveillance permanente a été mis en service en 2012. L'évaluation automatique des données est effectuée en continu depuis 2013 avec envoi des données et des alarmes au système SCADA du propriétaire. Les données sont également présentées sur une interface web. L'expérience des premières années de mesures a prouvé la capacité de quantifier les débits d'infiltration et d'identifier les zones présentant différents régimes d'écoulement. La fonction d'alarme a également été testée. Les résultats sont comparés avec le système de mesure d'infiltration classique. Quelques exemples sont présentés dans la communication afin de décrire le fonctionnement du système et son utilisation pratique dans les barrages de stériles. 582