Opencast mines are used when the deposit lies near the surface. Overlying earth and rock can be moved by machine or washed away with water. Although opencast mining is cheaper than digging deep mines, some people feel that the environmental costs of it are high, as large areas of land are laid bare and wildlife destroyed. Nowadays great attention is often paid to landscaping the area after an opencast mine has been abandoned. Many are made into parks or wildlife refuges. Planting the areas also helps to stabilize heaps of spoil.
Opencast mining operation involves generation of massive mine waste, altering the existing landscapes, alterations to drainage patterns etc. As a result, significant areas of land are degraded and existing ecosystems are replaced by undesirable wastes. To mitigate the impact on environment, a structured and adoptable environment management practice is being continuously developed at NLCIL. Eco-friendly mining can be broadly brought up under conservation of natural resources, prevention and regulation of polluting activities and action plans for eco regeneration.
Opencast mining operations involve huge quantities of overburden removal, dumping and backfilling in excavated areas. A substantial increase in the rate of accumulation of waste dumps in recent years has resulted in greater height of the dump for minimum ground cover area and also given rise to danger of dump failures. Further, steeper open-pit slopes are prone to failure. These failures lead to loss of valuable human life and damage to mining machinery. There is a need for continuous monitoring of dump and pit slopes, as well as for providing early warning before the occurrence of slope failure. Different technologies have been developed for slope monitoring. After studying the features and limitations of existing slope monitoring systems, it determined that there is a need to provide a reliable slope stability monitoring and prediction system by using a solar power-based long-range wireless sensor network for continuous monitoring of different prevailing parameters of slope stability. An accurate prediction of slope failure using a multiparameters-based prediction model is required for giving warning per the danger levels of impending slope stability. Considering the requirement, a slope failure monitoring and prediction system has been developed by the authors, using a wireless sensor network for the continuous monitoring of slope failure and to provide early warnings. The chapter describes details of slope stability mechanism, parameters affecting slope failure and triggering aspects, monitoring systems, prediction software, and laboratory experiments for calibrating geosensors and field installation of the developed system.
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