The design of a drainage system for a roofing slate quarry was implemented by the enhancement of discharge peak estimation, and the uncertainty inevitably associated with the engineering model was reduced.
The development of a topographical, geological, and vegetation cover database developed from a Geographical Information System (GIS) allowed for the definition of the drainage network for a hydraulic system, along with the calculation of the runoff coefficient. This is applied to the digital model of accumulated flow (DMF) as a weight correction coefficient, using a matrix-based model at 5×5 m resolution. The new digital model of corrected accumulated flow (DMCF) is the result of combining the thematic maps with the map of slope <3%, which was previously created from the slope model. It is demonstrated that this new model allows to apply the “Rational Method” on cartographic units defined by the GIS.
The DMCF is compared with other traditional applications of the Rational Method based on the calculation of the discharge peak considering: (1) the drainage basin as a single watershed or (2) defining an average runoff coefficient in each sub-watershed. Both approaches have bigger discharge peaks than those obtained by the DMCF since the slope, lithology, and vegetation cover have average values, and the runoff coefficient is poorly defined, increasing the uncertainty in the discharge peak. 相似文献
The objective of this paper is to evaluate the importance of geomorphological expert knowledge in the generation of landslide susceptibility maps, using GIS supported indirect bivariate statistical analysis. For a test area in the Alpago region in Italy a dataset was generated at scale 1:5,000. Detailed geomorphological maps were generated, with legends at different levels of complexity. Other factor maps, that were considered relevant for the assessment of landslide susceptibility, were also collected, such as lithology, structural geology, surficial materials, slope classes, land use, distance from streams, roads and houses. The weights of evidence method was used to generate statistically derived weights for all classes of the factor maps. On the basis of these weights, the most relevant maps were selected for the combination into landslide susceptibility maps. Six different combinations of factor maps were evaluated, with varying geomorphological input. Success rates were used to classify the weight maps into three qualitative landslide susceptibility classes. The resulting six maps were compared with a direct susceptibility map, which was made by direct assignment of susceptibility classes in the field. The analysis indicated that the use of detailed geomorphological information in the bivariate statistical analysis raised the overall accuracy of the final susceptibility map considerably. However, even with the use of a detailed geomorphological factor map, the difference with the separately prepared direct susceptibility map is still significant, due to the generalisations that are inherent to the bivariate statistical analysis technique. 相似文献
The multivariate information conprehensive processing technique is especially important at present to the digital mineral prospecting. However, the GIS-based weights of evidence have provided us with powerful tool for the quantitative assessment of mineral resource potential. In this paper, the mineralization model is established, based on the achievements made by previous researchers, to mend such deficiencies ad few references on ore fields in Yujiacun, Yunnan Province and the shortage of quantitative prediction and assessment of mineral resources. In addition, the weights of evidence are used to make a systematic quantitative prediction and assessment of mineral resources there, so that 2 mineral prospecting target areas of grade Ⅰ and 8 mineral prospecting target areas of grade Ⅱ are delineated, providing the further mineral resource exploration with the basis for the selection of mineral deposits. 相似文献
