Remote sensing supported surveillance of tailings dams and impoundments: A case study of a Finnish paste tailings impoundment

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1 Remote sensing supported surveillance of tailings dams and impoundments: A case study of a Finnish paste tailings impoundment Anssi Rauhala, Anne Tuomela, Pekka M. Rossi Water Resources and Environmental Engineering, University of Oulu, Finland, anssi.rauhala@oulu.fi Corine Davids Norut Northern Research Institute, Norway

2 Background Mining produces vast amounts of tailings, i.e., fine-grained waste material generated during mineral extraction. The generated tailings are typically deposited into an impoundment within the mining site. Tailings have been typically deposited as a slurry with high water content, but dewatering of tailings in order to promote steeper deposition slopes has gained popularity. However, fairly little research is available on the effects of cold climate on dewatered, thickened tailings. Steeper deposition angles and cold climate with seasonal freeze-thaw effects can lead to for example stability issues. 2

Background We had an opportunity to perform measurements at the Laiva mine site and tailings impoundment where production has been on halt since 2014.

3 Background We had an opportunity to perform measurements at the Laiva mine site and tailings impoundment where production has been on halt since The aim was to increase our knowledge on tailings behavior at a cold climate and simultaneously explore the applicability of Unmanned Aerial Vehicles (UAVs) to impoundment-scale monitoring. 3

Field and laboratory measurements Field and laboratory testing was performed to characterize in situ conditions and tailings properties In situ: temperature loggers, frost depth pipes.

4 Field and laboratory measurements Field and laboratory testing was performed to characterize in situ conditions and tailings properties In situ: temperature loggers, frost depth pipes. Laboratory: particle-size analysis, soil suction tests, frost heave tests, rheometry. Both field and laboratory testing has produced wealth of information which gives general knowledge on the situation and can be utilized for example in modelling. 4

5 Percent passing Laboratory measurements Particle size analysis indicated that the tailings consist of sandy clayey silt. Clay Silt Sand Gravel Particle size distribution also indicated that the material is frost susceptible. 5 Grainsize (mm) Fig: Hietala (2017)

Laboratory measurements Frost heave measurements were performed simultaneously for two samples (with and without excess water source below the sample to simulate ground water

6 Laboratory measurements Frost heave measurements were performed simultaneously for two samples (with and without excess water source below the sample to simulate ground water conditions). The material was confirmed as moderately/highly frost susceptible. Frost heave ratio for the wet sample was 0.2 after 48 hours (sample height increase from 10 cm to 12 cm) 6

The measurements provide validation data for one-dimensional geothermal simulations performed with a model developed by Knutsson

7 Field measurements Temperature loggers (every 20 cm down to 2 meters) and frost pipes have been utilized to measure the depth of the frozen layer. The measurements provide validation data for one-dimensional geothermal simulations performed with a model developed by Knutsson et al. (2017) at the LTU Mentioned laboratory measurements and local weather data are used as input data. The model simulates the geothermal regime in tailings with a possibility to include tailings deposition (tailings height with time). 7

8 Geothermal modelling The model seems to predict the depth of the frozen layer well. It has some simplifications and uncertainties such as snow depth. The model can give information on the thermal regime and the associated freeze-thaw phenomena. It is possible to run the model in cyclic fashion in order to determine whether the frozen layer has time to melt and if permafrost pockets are likely to form. In the absence of deposition of tailings, the frozen layer certainly melts, but during active disposal the model can aid management of deposition to avoid formation of permafrost. 8

9 CFD modelling CFD (computational fluid dynamics) modelling started by Timo Kulju and continued by Reeta Tolononen. The idea has been to model processes that occur during the filling of impoundment and to achieve a tool for management of tailings storage facilities. Laboratory measurements provide material parameters and UAV data can be used for calibration and validation. Tailings velocity profile during deposition. There has been several problems due to computational difficulties 9 - The area is large and thus computationally expensive. - CFD seems to be more suitable for the simulation of situations where the time steps are quite short, not years.

UAV measurements Fixed-wing UAVs and Structure from Motion technique were utilized to produce orthophotos and digital elevation models (DEMs).

10 UAV measurements Fixed-wing UAVs and Structure from Motion technique were utilized to produce orthophotos and digital elevation models (DEMs). Surveys were performed during summers 2015, 2016, and 2017 to assess if UAVs are suitable for monitoring tailings settlement. The utilized equipment changed for each summer, so two surveys were performed during 2017 in order to assess the accuracy and reproducibility of the method and 2016 surveys operated by Norut June/August surveys operated by Maailmasta Oy (subcontracted by Mitta Oy) 10

11 11 Structure from Motion

12 12 Structure from Motion

13 Structure from Motion For example, during the June 2017 campaign, 894 images were taken. Black dots highlight the camera/plane location during the acquisition. Colors highlight the number of images covering each portion of the images. 13

14 14 Structure from Motion

15 Structure from Motion For example, during the June 2017 campaign, 20 Ground Control Points were installed on the ground and their coordinates were measured with accurate RTK GNSS. Colors and shapes of the points highlight the distance between the input GCPs and their location estimated from the images. 15

16 Structure from Motion Model produced with Agisoft Photoscan: 16

17 Surveys Orthomosaics: : 10 cm/pix : 5 cm/pix : 2 cm/pix 17

Surveys Orthophotos - 2015: 10 cm/pix - 2016: 5 cm/pix - 2017: 2 cm/pix

18 Surveys Orthophotos : 10 cm/pix : 5 cm/pix : 2 cm/pix Digital elevation models : 20 cm/pix : 10 cm/pix : 5 cm/pix 18

19 Surveys 114 RTK GPS checkpoints were collected on the road surrounding the impoundment to provide ground truth data. Can be used to estimate data quality. 19

20 Results: DEM elevation compared to the collected GPS checkpoints / /08 Flight altitude (m) Camera pixels (Mpix) Ground resolution (cm/pix) Mean average error (cm) Standard deviation (cm) st quartile (cm) Median (cm) rd quartile (cm)

21 Results: Digital elevation models allow to track changes between different years. Can generate tailings subsidence maps. Comparably stable service roads surrounding the impoundment provide baseline for accuracy assessment. 21

22 Results: Subsidence Distribution of Point to Point distances in Z-direction: Stable ground (road): Tailings surface: 22

23 Results: Practical accuracy limits Distribution of Point to Point distances in Z-direction: Stable ground (road): Tailings surface: 23

24 Conclusions Wealth of laboratory and field data has been produced and it is currently utilized in modelling. The accuracy and resolution of UAV-produced DEMs is more than sufficient for volume and slope calculations, and other similar impoundment management operations. The method is sufficient to track displacements larger than ~10-20 cm, but it is too inaccurate for dam monitoring, and its use is further limited in snow and water-covered surfaces. - Camera and ground control network quality has siqnificant impact on the accuracy. - Enhancing the ground resolution even further (e.g., lowering the flight altitude) could allow measurement of smaller displacements, the cost being more laborous field work and more computationally expensive processing. 24

25 THANK YOU!

Remote sensing supported surveillance of tailings dams and impoundments: case Laiva mine

Remote sensing supported surveillance of tailings dams and impoundments: case Laiva mine Anssi Rauhala, Anne Tuomela, Pekka M. Rossi Water Resources and Environmental Engineering, University of Oulu, Finland,