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Binquan?LiEmail authorView authors OrcID profile Zhongmin?Liang Yingqing?He Lin?Hu Weimin?Zhao Kumud?Acharya 《Stochastic Environmental Research and Risk Assessment (SERRA)》2017,31(5):1045-1059
Parameter uncertainty in hydrologic modeling is crucial to the flood simulation and forecasting. The Bayesian approach allows one to estimate parameters according to prior expert knowledge as well as observational data about model parameter values. This study assesses the performance of two popular uncertainty analysis (UA) techniques, i.e., generalized likelihood uncertainty estimation (GLUE) and Bayesian method implemented with the Markov chain Monte Carlo sampling algorithm, in evaluating model parameter uncertainty in flood simulations. These two methods were applied to the semi-distributed Topographic hydrologic model (TOPMODEL) that includes five parameters. A case study was carried out for a small humid catchment in the southeastern China. The performance assessment of the GLUE and Bayesian methods were conducted with advanced tools suited for probabilistic simulations of continuous variables such as streamflow. Graphical tools and scalar metrics were used to test several attributes of the simulation quality of selected flood events: deterministic accuracy and the accuracy of 95 % prediction probability uncertainty band (95PPU). Sensitivity analysis was conducted to identify sensitive parameters that largely affect the model output results. Subsequently, the GLUE and Bayesian methods were used to analyze the uncertainty of sensitive parameters and further to produce their posterior distributions. Based on their posterior parameter samples, TOPMODEL’s simulations and the corresponding UA results were conducted. Results show that the form of exponential decline in conductivity and the overland flow routing velocity were sensitive parameters in TOPMODEL in our case. Small changes in these two parameters would lead to large differences in flood simulation results. Results also suggest that, for both UA techniques, most of streamflow observations were bracketed by 95PPU with the containing ratio value larger than 80 %. In comparison, GLUE gave narrower prediction uncertainty bands than the Bayesian method. It was found that the mode estimates of parameter posterior distributions are suitable to result in better performance of deterministic outputs than the 50 % percentiles for both the GLUE and Bayesian analyses. In addition, the simulation results calibrated with Rosenbrock optimization algorithm show a better agreement with the observations than the UA’s 50 % percentiles but slightly worse than the hydrographs from the mode estimates. The results clearly emphasize the importance of using model uncertainty diagnostic approaches in flood simulations. 相似文献
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Rupture process of the 2015 Pishan earthquake from joint inversion of InSAR,teleseismic data and GPS
An earthquake of Mw6.4 occurred in Pishan County in Xinjiang Province, northwestern Tibetan Plateau, on July 3,2015. The epicenter was located on an active blind thrust system located at the northern margin of the Western Kunlun Mountain Orogenic Belt southwest of the Tarim Basin. We constructed a shovel-shaped fault model based on the layered-crust model with reference to the seismic reflection profile, and obtained the rupture process of the earthquake from the joint inversion of Interferometric Synthetic Aperture Radar(InSAR) measurements, far-field waveform data, and Global Positioning System(GPS) data. The results show that the seismic fault dips southward with a strike of 109°, and the rupture direction was essentially northward. The fault plane rupture distribution is concentrated, with a maximum recorded slip of 73 cm. The main features of the fault are as follows: low inclination angle(25°–10°), thrust slip at a depth of 9–13 km, rupture propagation time of about 12 s, no significant slip in soft or hard sedimentary layers at 0–4 km depth and propagation from the initial rupture point to the surrounding area with no obvious directionality. The InSAR time-series analysis method is used to determine the deformation rate in the source region within 2 years after the earthquake, and the maximum value is ~17 mm yr-1 in the radar line-of-sight direction. Obvious post-earthquake deformation is evident in the hanging wall, with a similar trend to the coseismic displacement field. These results suggest that the Pishan earthquake has not completely released the accumulated energy of the region, given that the multilayer fold structure above the blind fault is still in a process of slow uplift since the earthquake. Post-earthquake adjustment models and aftershock risk analysis require further study using more independent data. 相似文献
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通过对路由区海域的海底地形、地貌、浅层沉积结构的探测及对其自然环境资料的综合分析,在中韩两国之间选择了一条条件最佳的光缆路线,并对其环境进行了全面分析与评价 相似文献
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墨西哥西马德雷山脉中—新生代构造、岩浆演化及成矿特征 总被引:1,自引:0,他引:1
墨西哥西马德雷山脉是白垩纪—新生代岩浆活动和构造运动形成的。中新生代岩浆活动可以分为5个主要阶段:侏罗纪—早白垩世、晚白垩世—古新世、始新世—渐新世、中新世早期和中新世中期—现代。这些岩浆活动和构造运动与法拉隆(Farallon)板块向北美大陆俯冲和加利福尼亚湾打开相关。墨西哥中新生代的成矿作用与东太平洋板块边缘连续的俯冲过程密切相关,矿床类型多样,包括VMS(与火山相关的块状硫化物)型、斑岩型、IOCG(铁氧化物铜金)型、矽卡岩型等。 相似文献
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Coal and gas outburst disasters in coal seams are becoming more serious as coal mines extend deeper underground in China. Furthermore, the protective coal seam mining technology featured by economic efficiency has been proven to be the most effective and widely applied method for the prevention of coal and gas outburst disasters. However, the determinations of the protective area coal and gas outburst prevention in a pressure-relief boundary area are fundamental issues that research should be focused on. The technical method for determining stress distribution in pressure-relief boundary area during protective coal seam mining is put forward in this paper. The method is based on a stress-seepage coupled relationship within a gas-containing coal seam. The method includes complex lab experiments and on-site measurements at the Qingdong Coal Mine. The final data illustrate that the permeability and vertical stress in the pressure-relief boundary area of the coal sample form a negative exponential function relationship. Additionally, the permeability of the coal sample within the abovementioned area is significantly different compared with that located at the center of the pressure-relief area. In the pressure-relief boundary area, the gas pressure distribution gradient is 0.0375 MPa/m, while the vertical stress distribution gradient registers 0.56 MPa/m. Under this condition, coal and gas outburst disasters are prone to be triggered. Therefore, effective precautions against coal and gas outburst disasters can be put forward in accordance with stress distribution characteristics within the abovementioned “boundary area.” 相似文献