The Impact of Underground Longwall Mining on Prime Agricultural Land: A Review and Research Agenda

Abstract

Coal mining and agriculture have repeatedly come into conflict when they co-occur. Although seemingly benign when compared with surface mining, underground coal extraction techniques (including longwall mining) cause subsidence of agricultural land and loss of productivity. Despite growing concerns for global food security and increasing demand for coal resources, there is little peer-reviewed literature on the impacts of longwall mining in prime agricultural areas. In this paper, we examined the present knowledge of subsidence impacts of longwall mining on agriculture and how this may be interpreted for specific locations such as Australia. The review found that subsidence affects soil properties, hydrology and topography. The main impacts on agriculture are altered soil and groundwater hydrology, modified topography associated with increased erosion or waterlogging risk, and zones of compaction or cracking that cause soil physical and chemical changes. Agricultural productivity is also reduced through altering the types of farming practices that are suited to subsided non-uniform landscapes, decreasing farming efficiency through increasing paddock heterogeneity and decreasing ease of workability. There is a need to consider these multiple impacts under local conditions, with particular regard to the interaction of mine subsidence-associated disturbances with farming practices. We conclude by describing future research directions required for Australia and other countries outside of the USA-where most of the research has been conducted. Australia has unique soil and climatic conditions making extrapolation of studies from the USA on subsidence impacts and mitigation problematic. Figure 7. Australian wheat yield (with the trend over time removed) has fluctuated with variations in the southern oscillation index (Adapted from BOM, 2013a). This figure is available in colour online at wileyonlinelibrary.com/journal/ldr. 1661 LONGWALL MINING REVIEW

Carbon Dynamics of Reclaimed Coal Mine Soil under Agricultural Use: A Chronosequence Study in the Dongtan Mining Area, Shandong Province, China

“…Coal mining is one of the key drivers of land degradation worldwide both in developed nations such as USA, England, Australia, and Spain and emerging economies such as China, India, and Africa [5]. Meanwhile, coal production also is an important economic pillar for many countries especially in emerging economies.…”

A Review of Fine-Scale Land Use and Land Cover Classification in Open-Pit Mining Areas by Remote Sensing Techniques

“…Guan et al [28] formed seven classes for land use classification and change detection in a coal mining area: open stope, stripping area, waste-dump area, mine industrial area, farmland, urban area, and the original landscape (grassland) ( Table 1). Lechner et al [29] grouped 22 fine-scale land cover categories into six land cover classes based primarily on disturbance type (Table 1). Karan et al [30] investigated seven distinct classes with three surface-mining related land cover types (Table 1).…”

“…References opencast stope, mineral processing land, dumping site 3 [35] reclaimed herbaceous vegetation, reclaimed woody vegetation, barren (including haul roads, active quarries, land disturbed by mining) 3 [22][23][24] mine-reclaimed grassland (including reclaimed land within mine sites and valley fills dominated by herbaceous vegetation) 1 [25] open stope, stripping area, waste-dump area, mine industrial area 4 [26] active, disturbed vegetation and pasture, rehabilitation, remnant, spoil/waste, and water management 6 [27] coal deposit, over burden dump, mine dump 3 [28] tree cover, dense grass, sparse grass, bare ground 4 [29] coal mining excavation cities, coal dump areas 2 [30] active mine, reclaimed mine (including grass, woodland, forest) 2 [16] opencast mining (coal), overburden dump 2 [12] bare tailings, exposed lime, water/wet tailings 3 [31] tailings zone, dry vegetation zone, transition zone, vegetated islands 4 [32] mine, dump, coal stockpile 3 [33,34] …”

“…For LCCMA, the following remote sensing data have been utilized: (1) Landsat images [14,18,28,30,32]; (2) high-resolution images such as ZiYuan-3 [27,41], RapidEye [24][25][26], SPOT-5 [31], IKONOS [35,36], and QuickBird [35,36]; (3) airborne aerial images [24,29,33,34]. For details, see Table 2.…”

“…ZiYuan-3 stereo satellite imagery [41] RapidEye [24] RapidEye, LiDAR [25,26] Landsat 5 TM, Landsat 8 OLI [28,30] Aerial imagery from Bing Maps, Google Maps imagery, NAIP [27,29] SPOT-5 imagery, DEM from aerial photographic stereo pairs [31] Landsat TM, Landsat ETM+, Landsat ETM [32] Landsat MSS, Landsat TM, Landsat ETM+ [18] Landsat MSS, Landsat TM, IRS LISS-II [14] Airborne high spatial and spectral resolution Compact Airborne Spectrographic Imager, hyperspectral data acquired with the Probe-1 airborne imager [33] Hyperspectral data acquired with the TRWIS III [34] IKONOS, QuickBird [35,36] HR images often have four bands; thus, identifying land cover at a fine scale using only spectral curves becomes difficult. In previous research employing HR images, the widely used spectral band and several spectral indexes, such as vegetation index [30,35], were considered as the input features of the classification process.…”