The no. 11 coal seam in the deep area of Hancheng mining area is mining in recent years, which is threatened by the water inrush from the Ordovician limestone aquifer. Coal-floor water inrush is governed by the water abundance of coal-floor aquifer, the water-resisting performance of coal-floor aquitard, and the pathway connecting the water source and the working face. To make an accuracy risk assessment of water inrush from the no. 11 coal seam floor, a GIS-based vulnerability index method (VIM) is adopted for its superior comprehensive consideration of more controlling factors, powerful spatial analysis, and intuitively display functions. This study firstly established an index system including the water pressure of the coal-floor aquifer, the unit water inflow, the thickness, the core recovery percentage, the thickness ratio of brittle rocks to ductile rocks, the thickness of effective aquitard, and the accumulated length of faults and folds, of which the former six indexes governed the water abundance of the coal-floor aquifer which was combined with the last two factors to determine the risk of coal-floor water inrush. Secondly, the thematic map of each controlling factor is established by GIS using the geological prospecting data, and the weight of each factor is determined by the analytic hierarchy process (AHP) after consulting the expert review panel. At last, a vulnerability index is obtained and used to assess the risk of coal-floor water inrush of the no. 11 coal seam. The risk of water inrush of the no. 11 coal seam of the study area was ranked to three zones: the southeastern shallow area in red color is the dangerous zone, the wide northwestern area in green color is the safe zone, and the transition area in yellow color is the moderate-risk zone. Compared with the actual water-inrush incidents, the risk assessment result was verified to achieve an accuracy of 82.35%, which is proved to be a dependable reference for the prevention and controlling of coal-floor water inrush of the no. 11 coal seam in Hancheng mining area. 相似文献
We report new zircon U–Pb age, Hf isotopic, and major and trace element data for rhyolites from the Duolong Ore Concentration Area of the Southern Qiangtang Terrane. Building on previous studies, we constrain the tectonic setting and propose a model to explain the geodynamics and crustal growth during regional magmatism in the Early Cretaceous. The analysed rhyolites yield laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) zircon U–Pb ages of 115 and 118 Ma. The rocks are K-rich (K2O = 6.66–9.93 wt.%; K2O/Na2O = 8.2–19.7 wt.%), alkaline and peraluminous (A/CNK = 1.02–1.46), and are characterized by high SiO2 contents (72.8–78.8 wt.%) similar to highly fractionated I-type granites. Fractionation of Fe–Ti oxides, plagioclase, hornblende, Ti-bearing phases, apatite, monazite, allanite and zircon contributed to the variations in major and trace element chemistry. High K2O contents are likely due to partial melting of the continental crust. The samples have positive zircon εHf(t) values ranging from +7.1 to +11.2. These features, together with young zircon Hf crustal model ages of 489–721 Ma, indicate that the K-rich rhyolites were derived from juvenile lower crust with an input of a mantle-derived component. We suggest that the Early Cretaceous K-rich rhyolites formed in a continental arc setting during northward subduction of Bangong Co–Nujiang oceanic lithosphere. Basaltic magma underplating was responsible for vertical crustal growth, triggered by slab roll-back in the Duolong Ore Concentration Area in the Early Cretaceous. 相似文献
The quality of GIServices (QoGIS) is an important consideration for services sharing and interoperation. However, QoGIS is a complex concept and difficult to be evaluated reasonably. Most of the current studies have focused on static and non-scalable evaluation methods but have ignored location sensitivity subsequently resulting in the inaccurate QoGIS values. For intensive geodata and computation, GIServices are more sensitive to the location factor than general services. This paper proposes a location-aware GIServices quality prediction model via collaborative filtering (LAGCF). The model uses a mixed CF method based on time zone feature from the perspectives of both user and GIServices. Time zone is taken as the location factor and mapped into the prediction process. A time zone-adjusted Pearson correlation coefficient algorithm was designed to measure the similarity between the GIServices and the target, helping to identify highly similar GIServices. By adopting a coefficient of confidence in the final generation phase, the value of the QoGIS most similar to the target services will play a dominant role in the comprehensive result. Two series of experiments on large-scale QoGIS data were implemented to verify the effectivity of LAGCF. The results showed that LAGCF can improve the accuracy of QoGIS prediction significantly. 相似文献
Natural Hazards - Prediction in ungauged basins (PUB) is as crucial as it is challenging. Thus far, there have been abundant regionalization studies on PUB, whereas "regionalization" is... 相似文献
In the numerical simulation of groundwater flow, uncertainties often affect the precision of the simulation results. Stochastic and statistical approaches such as the Monte Carlo method, the Neumann expansion method and the Taylor series expansion, are commonly employed to estimate uncertainty in the final output. Based on the first-order interval perturbation method, a combination of the interval and perturbation methods is proposed as a viable alternative and compared to the well-known equal interval continuous sampling method (EICSM). The approach was realized using the GFModel (an unsaturated-saturated groundwater flow simulation model) program. This study exemplifies scenarios of three distinct interval parameters, namely, the hydraulic conductivities of six equal parts of the aquifer, their boundary head conditions, and several hydrogeological parameters (e.g. specific storativity and extraction rate of wells). The results show that the relative errors of deviation of the groundwater head extremums (RDGE) in the late stage of simulation are controlled within approximately ±5% when the changing rate of the hydrogeological parameter is no more than 0.2. From the viewpoint of the groundwater head extremums, the relative errors can be controlled within ±1.5%. The relative errors of the groundwater head variation are within approximately ±5% when the changing rate is no more than 0.2. The proposed method of this study is applicable to unsteady-state confined water flow systems.