气候是控制柴达木盆地盐类沉积的主要因素之一,但是其作用机制尚待明确。作者以柴达木盆地察汗斯拉图盐湖的3个含盐剖面为研究对象,采用多接收电感耦合等离子质谱(MC-ICP-MS)铀系测年测定其沉积时代,并通过X射线粉晶衍射(XRD)分析测定其盐类矿物种类。铀系测年显示D18剖面石盐和芒硝层的沉积时代为13.1±2.0 ka BP~15.9±2.5 ka BP,其中芒硝沉积年代属于末次冰期MIS2晚期;MXK2剖面芒硝层的沉积时代分别为131.7±39.5 ka BP和158.3±10.8 ka BP,D12剖面芒硝层的沉积时代分别为166.6±20.2 ka BP和198.0±20.6 ka BP,可以对应于倒数第二次冰期MIS6。XRD分析确定了3个剖面的盐类矿物主要为芒硝、石盐和石膏。综合多个盐湖晚第四纪成盐数据,本文认为倒数第二次冰期MIS6和末次冰期MIS2是柴达木盆地晚第四纪重要的成盐期,冰期的冷干气候有利于石盐和芒硝等盐类沉积。柴达木盆地"冰期成盐"的根本原因,是由于冰期环境下盆地周边山体冰川规模的扩张以及干冷的冰期气候,共同造成了盐湖补给水量的减少。此外,晚第四纪MIS6和MIS2的冰期降温也是导致盆地中冷相盐类沉积的直接原因。 相似文献
A model integrating geo-information and self-organizing map (SOM) for exploring the database of soil environmental surveys was established. The dataset of 5 heavy metals (As, Cd, Cr, Hg, and Pb) was built by the regular grid sampling in Hechi, Guangxi Zhuang Autonomous Region in southern China. Auxiliary datasets were collected throughout the study area to help interpret the potential causes of pollution. The main findings are as follows: (1) Soil samples of 5 elements exhibited strong variation and high skewness. High pollution risk existed in the case study area, especially Hg and Cd. (2) As and Pb had a similar topo-logical distribution pattern, meaning they behaved similarly in the soil environment. Cr had behaviours in soil different from those of the other 4 elements. (3) From the U-matrix of SOM networks, 3 levels of SEQ were identified, and 11 high risk areas of soil heavy metal-contaminated were found throughout the study area, which were basically near rivers, factories, and ore zones. (4) The variations of contamination index (CI) followed the trend of construction land (1.353) > forestland (1.267) > cropland (1.175) > grassland (1.056), which suggest that decision makers should focus more on the problem of soil pollution surrounding industrial and mining enterprises and farmland.
Simulating land use/cover change (LUCC) and determining its transition rules have been a focus of research for several decades. Previous studies used ordinary logistic regression (OLR) to determine transition rules in cellular automata (CA) modeling of LUCC, which often neglected the spatially non-stationary relationships between driving factors and land use/cover categories. We use an integrated geographically weighted logistic regression (GWLR) CA-Markov method to simulate LUCC from 2001–2011 over 29 towns in the Connecticut River Basin. Results are compared with those obtained from the OLR-CA-Markov method, and the sensitivity of LUCC simulated by the GWLR-CA-Markov method to the spatial non-stationarity-based suitability map is investigated. Analysis of residuals indicates better goodness of fit in model calibration for geographically weighted regression (GWR) than OLR. Coefficients of driving factors indicate that GWLR outperforms OLR in depicting the local suitability of land use/cover categories. Kappa statistics of the simulated maps indicate high agreement with observed land use/cover for both OLR-CA-Markov and GWLR-CA-Markov methods. Similarity in simulation accuracy between the methods suggests that the sensitivity of simulated LUCC to suitability inputs is low with respect to spatial non-stationarity. Therefore, this study provides critical insight on the role of spatial non-stationarity throughout the process of LUCC simulation. 相似文献
In this paper, we present and evaluate three long-term wave models for application in simulation-based design of ships and marine structures. Designers and researchers often rely on historical weather data as a source for ocean area characteristics based on hindcast datasets or in-situ measurements. The limited access and size of historical datasets reduces repeatability of simulations and analyses, making it difficult to assess the sampling variability of performance and loads on marine vessels and structures. Markov, VAR and VARMA wave models, producing independent long-term time series of significant wave height (Hs) and spectral peak period (Tp), is presented as possible solutions to this problem. The models are tested and compared by addressing how the models affect interpretation of design concepts and the ability to replicate statistical and physical characteristics of the wave process. Our results show that the VAR and VARMA models perform sufficiently in describing design performance, but does not capture the physical process fully. The Markov model is found to perform worst of the tested models in the applied tests, especially for measures covering several consecutive sea states. 相似文献