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The landslide influence parameters used for this study are geology, relative permeability, land use/land cover, precipitation, elevation, slope, aspect, total curvature, plan curvature, profile curvature, wetness index, stream power index, sediment transportation capacity index, distance to drainage, distance to fault, drainage density, fault density, and spring density maps.
The model is based on weights assigned by expert judgment and organized in a number of components such as slope angle, internal relief, slope shape, geological formation, active faults, distance to drainage, distance to springs, geomorphological subunits and existing landslide zones.
The maximum gas drainage flow for a single hole can reach 8.1 m3/min and the effective drainage distance can be extended up to 150 m or more.
The maximum gas drainage flow of a single hole can reach 8.1 m3/min, and the effective drainage distance can be extended up to 150 m or more. .
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The increase of column's diameter causes the increase of drainage at distance about 1 1.5 m from column center, this is while at distance more than 1.5 m, the increase in column's diameter dose not influence pore water drainage.
Wang (2011) carried out a theoretical study on methane flow laws when stereoscopic methane drainage between short distance coal seam groups was applied; however, how the methane distribution after drainage changed was not examined.
Partial cadastral map showing property boundaries, buildings, names of property owners, roads, drainage, and radial distances from waterfront.
Initial investigations of this kind (Garrott et al. 2005) indicated that the effects of wolves (Canis lupus) on elk (Cervus elaphus) dynamics could vary considerably within the same river drainage system and distances less than 40 km apart, making generalizations strictly from protected areas equivocal.
Using binary logistic regression, the probability of occurrence of suitable tsetse habitat decreased with increased distance from drainage lines.
Ten factors which influence landslide occurrence, i.e., slope, aspect, curvature, distance from drainage, lithology, distance from lineaments, soil type, landcover, rainfall precipitation, and normalized difference vegetation index (ndvi), were extracted from the spatial database and the logistic regression coefficient of each factor was computed.
The probability of hydrological and sedimentological connectivity is assessed by combining soil erosion risk and extended drainage network with flow distance calculation.
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