Modelling the effect of changing precipitation inputs on deep soil water utilization

Forests in the Southeastern United States are predicted to experience future changes in seasonal patterns of precipitation inputs as well as more variable precipitation events. These climate change‐induced alterations could increase drought and lower soil water availability. Drought could alter rooting patterns and increase the importance of deep roots that access subsurface water resources. To address plant response to drought in both deep rooting and soil water utilization as well as soil drainage, we utilize a throughfall reduction experiment in a loblolly pine plantation of the Southeastern United States to calibrate and validate a hydrological model. The model was accurately calibrated against field measured soil moisture data under ambient rainfall and validated using 30% throughfall reduction data. Using this model, we then tested these scenarios: (a) evenly reduced precipitation; (b) less precipitation in summer, more in winter; (c) same total amount of precipitation with less frequent but heavier storms; and (d) shallower rooting depth under the above 3 scenarios. When less precipitation was received, drainage decreased proportionally much faster than evapotranspiration implying plants will acquire water first to the detriment of drainage. When precipitation was reduced by more than 30%, plants relied on stored soil water to satisfy evapotranspiration suggesting 30% may be a threshold that if sustained over the long term would deplete plant available soil water. Under the third scenario, evapotranspiration and drainage decreased, whereas surface run‐off increased. Changes in root biomass measured before and 4 years after the throughfall reduction experiment were not detected among treatments. Model simulations, however, indicated gains in evapotranspiration with deeper roots under evenly reduced precipitation and seasonal precipitation redistribution scenarios but not when precipitation frequency was adjusted. Deep soil and deep rooting can provide an important buffer capacity when precipitation alone cannot satisfy the evapotranspirational demand of forests. How this buffering capacity will persist in the face of changing precipitation inputs, however, will depend less on seasonal redistribution than on the magnitude of reductions and changes in rainfall frequency.     

Developing constitutive models from EPR‐based self‐learning finite element analysis

A constitutive model that captures the material behavior under a wide range of loading conditions is essential for simulating complex boundary value problems. In recent years, some attempts have been made to develop constitutive models for finite element analysis using self‐learning simulation (SelfSim). Self‐learning simulation is an inverse analysis technique that extracts material behavior from some boundary measurements (eg, load and displacement). In the heart of the self‐learning framework is a neural network which is used to train and develop a constitutive model that represents the material behavior. It is generally known that neural networks suffer from a number of drawbacks. This paper utilizes evolutionary polynomial regression (EPR) in the framework of SelfSim within an automation process which is coded in Matlab environment. EPR is a hybrid data mining technique that uses a combination of a genetic algorithm and the least square method to search for mathematical equations to represent the behavior of a system. Two strategies of material modeling have been considered in the SelfSim‐based finite element analysis. These include a total stress‐strain strategy applied to analysis of a truss structure using synthetic measurement data and an incremental stress‐strain strategy applied to simulation of triaxial tests using experimental data. The results show that effective and accurate constitutive models can be developed from the proposed EPR‐based self‐learning finite element method. The EPR‐based self‐learning FEM can provide accurate predictions to engineering problems. The main advantages of using EPR over neural network are highlighted.     

超基性岩中含铜、钴块状硫化物矿床——德尔尼铜矿成因新认识

长期以来对德尔尼铜矿的成因存在着不同认识。从矿石组成和结构、构造来看,应属典型的块状硫化物矿石,矿床亦应属于含铜黄铁矿型矿床。但从其地质产状来看又与一般的黄铁矿型矿床大不相同,与一般的岩浆熔离铜镍硫化物矿床也有较多差异。这就是本矿床类型独特之处。近年来通过工作又取得一些新资料,特别是超基性岩和矿石的同位素年龄数据。本文在综合新老资料基础上,提出新看法,认为该矿床形成于上地幔,再就位于地壳浅部。其成因类型暂定为:“深部熔离—构造侵位矿床”。鉴于本矿床与一般块状硫化物矿床相比有其独特性,建议命名为“德尔尼型”。     

发挥行业和地域优势开辟经济发展新领域——矿业网站的建设设想

网络经济已成为新的社会生产力的代表。广西地质矿产勘查开发局应该利用其行业和地域方面的固有优势，积极参与网络经济，以期打开矿业市场。文章提出了建立矿业网站的设想和框架。     

Deep Processes of Basin Evolution:A Case Study of the Southern Songliao Basin and Adjacent Area,NE China in Mesozoic-Cenozoic

1IntroductionOne of the key factors related to basin geody-namics is deep process controlling formation and evolution of sedimentary basin. Depth and tempera-ture of asthenosphere,existence of mantle plume,occurrence of mantle melting,and amounts of melts under depressurization during thinning of lithosphere are controlling factors influenced formation and characteristics of extensional basin directly (Li,1994). Rifting is probably governed by frictional forces exerted on the base of litho…     

Tests and constraints on theories of galaxy formation and evolution

Tests and constraints on current theories of galaxy formation and evolution are presented. They are derived from observations of the Northern Hubble Deep Field with WFPC2 and NICMOS. Photometric redshifts, extinctions and spectral energy distributions are calculated for all objects in the field. The tests and constraints are derived from the output of this analysis. The tests of the predictions from hierarchical and pure luminosity evolution galaxy evolution calculations favor the hierarchical model. Constraints are provided by the current luminosity function and its evolution to a redshift of 6. This revised version was published online in August 2006 with corrections to the Cover Date.     

Reliability assessment of serviceability performance of braced retaining walls using a neural network approach

In urban environments, one major concern with deep excavations in soft clay is the potentially large ground deformations in and around the excavation. Excessive movements can damage adjacent buildings and utilities. There are many uncertainties associated with the calculation of the ultimate or serviceability performance of a braced excavation system. These include the variabilities of the loadings, geotechnical soil properties, and engineering and geometrical properties of the wall. A risk‐based approach to serviceability performance failure is necessary to incorporate systematically the uncertainties associated with the various design parameters. This paper demonstrates the use of an integrated neural network–reliability method to assess the risk of serviceability failure through the calculation of the reliability index. By first performing a series of parametric studies using the finite element method and then approximating the non‐linear limit state surface (the boundary separating the safe and ‘failure’ domains) through a neural network model, the reliability index can be determined with the aid of a spreadsheet. Two illustrative examples are presented to show how the serviceability performance for braced excavation problems can be assessed using the reliability index. Copyright © 2005 John Wiley & Sons, Ltd.     

Annual variation of atmospheric carbonyl sulfide in the marine atmosphere in the Southern Indian Ocean

Measurements of the concentrations of carbonyl sulfide (COS) in the marine atmosphere were made over a period of two years in the southern Indian Ocean (Amsterdam Island, 37°50 S–77°31 E; March 1987–February 1988 and April 1989–February 1990). The mean atmospheric COS concentration for the whole period was 475±48 pptv (n=544). Atmospheric COS concentrations show no significant seasonal variation with a summer to winter ratio of 1.05. Taking into account the observed variability of the atmospheric COS concentration (10%), a value of 1.4 yr is estimated as a lower limit for the atmospheric COS lifetime. A comparison of the COS data at Amsterdam Island with those obtained in the Southern Hemisphere in the past 12 yr does not reveal any significant trend in the tropospheric background COS mixing ratio.     

Mineralogy and geochemistry of the Texeo Cu–Co mine site (NW Spain): screening tools for environmental assessment

The Cu–Co–Ni Texeo mine has been the most important source of Cu in NW Spain since Roman times and now, approximately 40,000 m³ of wastes from mine and metallurgical operations, containing average concentrations of 9,263 mg kg⁻¹ Cu, 1,100 mg kg⁻¹ As, 549 mg kg⁻¹ Co, and 840 mg kg⁻¹ Ni, remain on-site. Since the cessation of the activity, the abandoned works, facilities and waste piles have been posing a threat to the environment, derived from the release of toxic elements. In order to assess the potential environmental pollution caused by the mining operations, a sequential sampling strategy was undertaken in wastes, soil, surface and groundwater, and sediments. First, screening field tools were used to identify hotspots, before defining formal sampling strategies; so, in the areas where anomalies were detected in a first sampling stage, a second detailed sampling campaign was undertaken. Metal concentrations in the soils are highly above the local background, reaching up to 9,921 mg kg⁻¹ Cu, 1,373 mg kg⁻¹ As, 685 mg kg⁻¹ Co, and 1,040 mg kg⁻¹ Ni, among others. Copper concentrations downstream of the mine works reach values up to 1,869 μg l⁻¹ and 240 mg kg⁻¹ in surface water and stream sediments, respectively. Computer-based risk assessment for the site gives a carcinogenic risk associated with the presence of As in surface waters and soils, and a health risk for long exposures; so, trigger levels of these elements are high enough to warrant further investigation.     

气举反循环采矿方法单井试验及应用探讨

湖南道县一个矿区,铁锰矿体储量约2200万t。由于复杂的水文地质和工程地质条件,从20世纪70年代发现后,一直没有开采。笔者通过多年大直径工程井的实践经验,查阅国内外资料后,提出了钻井-气举反循环法试开采的方法,并在现场进行了单孔开采试验,获得了比较满意的效果。以该矿体Ⅱ号矿为例,介绍了钻井-气举反循环法采矿的适用条件、工艺过程以及试采情况,并就以后大面积开采提出了若干技术措施。