soghra andaryani; Vahid Nourani
Abstract
1-IntroductionMining 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-MethodologyThe ...
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1-IntroductionMining 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-MethodologyThe study area is located in East Azerbaijan and it belongs to the sub-basins of the western part of the Aras Basin.2.1-DataLandsat 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 DiscussionThe 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 village0.48% 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- ConclusionThe 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.
Asadollah Hejazi; Sogra Andariani; Farhad Almaspour; Abolfazl Mokhtari Asl
Volume 2, Issue 3 , January 2017, , Pages 61-80
Abstract
Flood is the main destructive phenomena in Iran which causes human casualties and financial damages every year. The purpose of this research is to define flood susceptible zones in Ligcanchai Catchment. To achieve this end this study provided different information layers such as slope, elevation, ...
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Flood is the main destructive phenomena in Iran which causes human casualties and financial damages every year. The purpose of this research is to define flood susceptible zones in Ligcanchai Catchment. To achieve this end this study provided different information layers such as slope, elevation, soil hydrological units, curve number, runoff height, lithology, land use and landcover, hydrography density, compactness coefficient of 23 basins by using maps, reports, satellite images and field studies. All layers were then weighted with criteria and sub criteria. The study used the hierarchical method to weight criteria and fuzzy logic to weight sub criteria. Then 5 flood susceptible zones were defined by using multi-criteria evaluation and linear combination was weighted. The results show that around 28 percent of the Catchment has high and very high flood risk and that these areas are located near Tabriz city. Since flood events destroy the infrastructures and cause human casualties every year, substantial actions must be taken to prevent the high and very high flood risks. These activities must be planned in the integrated watershed management plans, and the flood risk management in order to improve the watershed vegetation in the watershed to minimize financial damages and human life losses.
