نوع مقاله : پژوهشی

نویسندگان

1 دانشگاه تبریز

2 استاد دانشکده عمران دانشگاه تبریز

چکیده

هدف از مطالعه حاضر مانیتورینگ اثرات فعالیتهای اکتشاف و ذوب بر پوشش گیاهی منطقه است. با توجه به اینکه در این منطقه برای ذوب طلا از روش هیپ لچینگ استفاده می‌شود، احتمال اینکه مواد شیمیایی استفاده شده در سرویسهای ذوب در محیط زیست پخش و یا در عمق نفوذ نماید، بیشتر است. پوشش گیاهی یکی از پدیده‌هایی هست که به شدت از آلودگی محیط، به ویژه نشت و نفوذ سیانور متاثر شده و کاهش می‌یابد. بنابراین بررسی روند پوشش گیاهی می‌تواند بر چنین دغدغه‌ای پایان دهد. لذا منطقه مورد مطالعه به سه بخش منطقه 1 (منطقه معدن‌کاوی شده)، منطقه 2 (منطقه بکر و دست نخورده) و منطقه 3 (پایین دست منطقه 1) تقسیم و آزمون من کندال-من کندال دنباله‌ای و همبستگی بین پوشش گیاهی آنها در فرضیه‌های مختلف صورت گرفت. بدین منظور، داده‌های تصاویر ماهواره‌ای لندست 5 و 8 در بازه زمانی 1984-2019 بصورت سری زمانی و داده های دما و بارش ایستگاه ورزقان در بازه زمانی 1989-2017 مورد استفاده قرار گرفت. با بکارگیری شاخص گیاهی تفاضلی نرمال شده (NDVI) تراکم پوشش گیاهی استخراج و در مقیاس پیکسل (هر 900 مترمربع)، روش آماری ناپارامتریک من-کندال در سطوح اطمینان 95 و 99 درصد بر NDVI اعمال شد. سپس مساحت منطقه کاهش یافته معنی‌دار با استفاده از آزمون من-کندال دنباله‌ای به منظور بررسی نقطه شروع کاهش معنی‌داری در هر سه منطقه، مورد تحلیل قرار گرفت. نتایج نشان دهنده عدم نفوذ مواد شیمیایی در محیط زیست است و اقلیم کنترل کننده تغییرات پوشش گیاهی منطقه مورد مطالعه است.

کلیدواژه‌ها

عنوان مقاله [English]

Investigating the Effect of Gold Mining on Land Cover Trend at pixel scale using a combination of remote sensing data and Mann-Kendall Test in Northwestern Iran, Case study: Andaryan region, East Azerbaijan

نویسندگان [English]

  • soghra andaryani 1
  • Vahid Nourani 2

1 storesentore nord

2 Center of Excellence in Hydroinformatics, Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran

چکیده [English]

1-Introduction
Mining industry has almost negative and destructive effects on the environment and ecosystems of regions and can affect the health of humans and other living organisms including animals, plants, soil, water, and the entire biosystem of the region on a local and regional scale.
2-Methodology
The study area is located in East Azerbaijan and it belongs to the sub-basins of the western part of the Aras Basin.
2.1-Data
Landsat 5, 8 data available in July (1984-2019), monthly and annually value of temperature and precipitation data (1998-2017) in Varzeqan station.
2.2-Method
In the present study, land-cover density using Normalized Differential vegetation Index (NDVI) was extracted from satellite imagery of Landsat (Thematic Mapper and Operational Land Imager) as time series for the period of June 1984-2019. 27 images were analyzed after correction and NDVI extraction. See question 1:
                                                 (1)
Where, NIR is reflectance value of near infrared and RED is reflectance value of red band.
To determine the trend in vegetation, first, the land-cover density extracted from satellite images were pre-whited in time series and then the trend analysis was done by Mann-Kendall (MK) method in each of the pixels, and also beginning of the trends were

 

analyzed by Mann-Kendall sequence (SMK) in per case studies. SMK was used in MATLAB software (Ye et al., 2013; Moraes et al., 1998). 
3-Results and Discussion
The average values of land-cover in all three case studies (i.e., case 1, case 2, and case 3) have increased in the period 1984-2019 and have almost had the same fluctuations over the period under study. Therefore, that linear regression was derived between the land-cover of cases 1 and 2, 1 and 3, and finally 2 and 3 with the average correlation coefficient of 96%, 96%, and 98%, respectively. The highest vegetation peak was in 1992, 2004, 2013, and 2018 to 2019, however, such an increase in the average occurred in all three study units. The peak of average land-cover density in different years is consistent with the peak of precipitation and decrease in temperature on an annual scale. According to the results, in studying the trend of vegetation changes, it is not possible to generalize the numerical average of vegetation for the whole region or analyze the trend. By emphasizing this result in each of the pixels as a time series, trend analysis was performed by MK method. Case 1 experienced the most fluctuation and case 3 (downstream of the mined area) experienced the least fluctuation trends. The significant decreasing trend in both levels of reliability, 95% and 99% has the highest level of the mining area (Fig. 1).
 




 
Fig. (1): Classification of trend analysis at 95% and 99% confidence levels, (a) case 1, (b) case 2 and (c) case 3. Figures 1-3, which have been resulted from Fig. 6 (a), indicate areas with significant decrease. Figs. 1 and 2 are the mining areas and Fig. 3 is the Andaryan village
0.48% of the case 1 area is under the significant decreasing trend, which is 0.18% and 0.22% in case 2 and 3, respectively. Therefore, there is a significant decrease in all three case studies. Approximately, 5%, 2%, and 3% of the area of cases 1, 2, and 3 have a decreasing trend, respectively. The percentage of areas with a significant increasing trend at both 95% and 99% confidence levels are equal to 35.5%, 54%, and 36.5% for each of the 1-3 case studies, respectively. According to Varzeqan station data, these areas have received good rainfall in the last decade, so the area of vegetation has increased significantly. The existence of 88% correlation between the area where the mining took place and the area that is untouched in terms of exploration operations shows the insignificant impact of exploration operations and smelting services on the vegetation of the area. Although most of land-cover of about 51 hectares has been lost due to road construction on steep slopes for mining and smelting services, based on sustainable development goals, the affected vegetation can be restored to the original state and at the same time to make the best use of existing minerals and consider future generations (Thenepalli et al., 2019).
 



4- Conclusion
The results show fluctuations in land-cover density; however, in general, high dense areas in terms of vegetation are observed in all three areas. The case studies 1- 2, 1 - 3, and 2 -3 have a correlation of 96%, 96%, and 98% with each other, respectively. Therefore, using the Mann- Kendall statistical model, NDVI values were analyzed pixel by pixel as a time series. The results show a significant decrease in the vegetation of regions 1-3 equal to 0.48%, 0.19% of the area in all three regions, respectively. The results of the Mann-Kendall sequence and correlation in the areas with a significant reduction in vegetation and the considered various hypotheses showed no chemical leakage to downstream of the basin.
Keywords: Impact of mining, Land-cover, NDVI, Mann-Kendall Test, Varzegan, Northwestern Iran
 
5-References
Ye, X., Zhang, Q., Liu, J., Li, X., & Xu, C.Y. (2013). Distinguishing the relative impacts of climate change and human activities on variation of streamflow in the Poyang Lake catchment, China. Journal of Hydrology, 494, 83–95.
Moraes, J.M., Pellegrino, H.Q., Ballester, M.V., Martinelli, L.A., Victoria, R.L., & Krusche, A.V. (1998). Trends in hydrological parameters of southern Brazilian watershed and its relation to human induced changes. Water Resources Management, 12, 295–311.
Thenepalli, T., Chilakala, R., Habte, L., Quang Tuan, L., & Sik Kim, C. (2019). A Brief Note on the Heap Leaching Technologies for the Recovery of Valuable Metals. Sustainability, 11, 334.
 

کلیدواژه‌ها [English]

  • Impact of mining
  • Land cover
  • NDVI
  • Mann-Kendall Test
  • Varzegan
Andaryani, S., Nourani, V., Trolle, D., Dehghani, M., & Mokhtari Asl, A. (2019). Assessment of land use and climate change effects on land subsidence using a hydrological model and radar technique, Journal of Hydrology, https://doi.org/10.1016/j.jhydrol.2019.124070.
Boadi, N., Twumasi, SK., & Ephraim, J.H. (2009). Impact of Cyanide Utilization in Mining on the Environment, International Journal of Environmental Research, 3(1), 101-108.
Choi, Y., Song, J. (2016). Sustainable Development of Abandoned Mine Areas Using Renewable Energy Systems: A Case Study of the Photovoltaic Potential Assessment at the Tailings Dam of Abandoned Sangdong Mine, Korea, Sustainability, 8, 1320.
Gandini, M.L., & Usunoff, E.J. (2004). SCS curve number estimation using remote sensing NDVI in a GIS environmental, Journal of Environmental Hydrology, 12, 168-179.
Hoye, R., (1987). Gold/Silver Heap Leaching and Management Practices that Minimize the Potential for Cyanide Releases; EPA/600/2-88/002; Final Report; U.S. Environmental Protection Agency: Washington, DC, USA, 1–113.
Khosravian, M., Entezari, A., Rahmani, A., & Baaghide, M. (2018). Monitoring the Disturbance of Lake District Water Level Changes Using Remote Sensing Indices, Hydrogeomorphology, 4 (13), 99-120., In Persian.
Li, Z., Liu, W-Z., Zhang, X-C., & Zheng, F-L. (2009). Impacts of land use change and climate variability on hydrology in an agricultural catchment on the Loess Plateau of China, Journal of Hydrology, 377, 35–42.
Manning, T.J., Kappes, D.W. (2016). Chapter 25 - Heap Leaching of Gold and Silver Ores. Gold Ore Processing (Second Edition) Project Development and Operations, 413-428.
Moraes, J.M., Pellegrino, H.Q., Ballester, M.V., Martinelli, L.A., Victoria, R.L., & Krusche, A.V. (1998). Trends in hydrological parameters of southern Brazilian watershed and its relation to human induced changes, Water Resources Management, 12, 295–311.
Nguyen, U., Glenn, E. P., Nagler, P. L., & Scott, R. L. (2015). Long-term decrease in satellite vegetation indices in response to environmental variables in an iconic desert riparian ecosystem: The Upper San Pedro, Arizona, United States, Ecohydrology, 8, 610–625.
Petersen, J. (2016). Heap leaching as a key technology for recovery of values from low-grade ores-A brief overview, Hydrometallurgy, 165, 206–212.
Rezaei Moghadam, M.S., Andaryani, S., Almaspour, Farhad., Valizadeh Kamran, KH., & Mokhtari, A. (2014). Investigating the land use/cover changes effects on floods and runoff (case study: Alavian dam basin), Hydrogeomorphology, 1, 41-57., In Persian.
Rouse, J.W., Haas, R.H., Schell, J.A., & Deering, D.W. (1973). Monitoring Vegetation Systems in the Great Plains with ERTS. Third ERTS Symposium, NASA SP-351 I: 309-317.
Rumora, L., Miler, M., & Medak, D. (2019). Contemporary comparative assessment of atmospheric correction influence on radiometric indices between Sentinel-2A and Landsat 8 imagery, Geocarto International, https://doi, 10.1080/10106049.2019.1590465.
Subrahmanyam T. V. (1989). Recovery problems in gold ore processing with emphasis on heap leaching, Journal Mineral Processing and Extractive Metallurgy Review, 4, 201–215.
Thenepalli, T., Chilakala, R., Habte, L., Quang Tuan, L., & Sik Kim, C. (2019). A Brief Note on the Heap Leaching Technologies for the Recovery of Valuable Metals, Sustainability, 11 (12), 3347, https://doi, 10.3390/su11123347.
Vicente-Serrano, S. M., Gouveia, C., Camarero, J. J., Beguera, S., Trigo, R., López-Moreno, J. I., & et al. (2013). Response of vegetation to drought time-scales across global land biomes, Proceedings of the National Academy of Sciences, 110, 52–57.
Wagesho, N., Goel, N.K., & Jain, M.N. (2012). Investigation of non-stationarity in hydro-climatic variables at Rift Valley lakes basin of Ethiopia, Journal of Hydrology, 444–445, 113-133.
Wan, Z., Zhang, Y., Zhang, Q., & Li, Z.-L. (2004). Quality assessment and validation of the MODIS global land surface temperature, International Journal of Remote Sensing, 25, 261–274.
Yang, Y., & Tian, F. (2009). Abrupt change of runoff and its major driving factors in Haihe River Catchment, China, Journal of Hydrology, 374, 373–383.
Ye, X., Zhang, Q., Liu, J., Li, X., & Xu, C.Y. (2013). Distinguishing the relative impacts of climate change and human activities on variation of streamflow in the Poyang Lake catchment, China, Journal of Hydrology, 494, 83–95.
Zargar, A., Sadiq, R., Naser, B., & Khan, F. I. (2011). A review of drought indices, Environmental Reviews, 19, 333–349.
Zhu, Z., Fu, Y., Woodcock, C. E., Olofsson, P., Vogelmann, J. E., Holden, C., & et al. (2016). Including land cover change in analysis of greenness trends using all available Landsat 5, 7, and 8 images: A case study from Guangzhou, China (2000–2014), Remote Sensing of Environment, 185, 243–257.