Seasonal connections between meteoric water and streamflow generation along a mountain headwater stream

In snowmelt-driven mountain watersheds, the hydrologic connectivity between meteoric waters and stream flow generation varies strongly with the season, reflecting variable connection to soil and groundwater storage within the watershed. This variable connectivity regulates how streamflow generation mechanisms transform the seasonal and elevational variation in oxygen and hydrogen isotopic composition (δ¹⁸O and δD) of meteoric precipitation. Thus, water isotopes in stream flow can signal immediate connectivity or more prolonged mixing, especially in high-relief mountainous catchments. We characterized δ¹⁸O and δD values in stream water along an elevational gradient in a mountain headwater catchment in southwestern Montana. Stream water isotopic compositions related most strongly to elevation between February and March, exhibiting higher δ¹⁸O and δD values with decreasing elevation. These elevational isotopic lapse rates likely reflect increased connection between stream flow and proximal snow-derived water sources heavily subject to elevational isotopic effects. These patterns disappeared during summer sampling, when consistently lower δ¹⁸O and δD values of stream water reflected contributions from snowmelt or colder rainfall, despite much higher δ¹⁸O and δD values expected in warmer seasonal rainfall. The consistently low isotopic values and absence of a trend with elevation during summer suggest lower connectivity between summer precipitation and stream flow generation as a consequence of drier soils and greater transpiration. As further evidence of intermittent seasonal connectivity between the stream and adjacent groundwaters, we observed a late-winter flush of nitrate into the stream at higher elevations, consistent with increased connection to accumulating mineralized nitrogen in riparian wetlands. This pattern was distinct from mid-summer patterns of nitrate loading at lower elevations that suggested heightened human recreational activity along the stream corridor. These observations provide insights linking stream flow generation and seasonal water storage in high elevation mountainous watersheds. Greater understanding of the connections between surface water, soil water and groundwater in these environments will help predict how the quality and quantity of mountain runoff will respond to changing climate and allow better informed water management decisions.     

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.     

山区公路软基病害研究

随着高等级公路建设规模的扩大，山区公路所面临的路基病害特别是软土路基病害问题也逐渐增多。结合对陕南勉(县)一宁(强)高速公路工程实例分析，对山区软土成因及其特性进行了初步分析，认为山区软土属以坡洪积、湖积和冲积为主的软土，也有少量是由坡残积物堆积而形成。山区软土的特殊性表现在成分的复杂性、分布的不均匀性、隐蔽性和物理力学性质的特殊性。根据其特性以及中国山区公路软基普遍存在的病害问题，总结了山区公路软基的主要病害类型为剪切拉裂破坏、浸水沉陷破坏、剥蚀坍塌破坏、推挤滑动破坏。还提出了相应的软基处理方法及建议。     

广西岩溶区金属硫化物矿床风化与元素表生迁移特征

对广西岩溶区三个铅锌硫化物矿床风化带观测结果表明，中低山岩溶区硫化物矿床具有更强烈的风化淋滤作用，但次生晕面积较小；岩溶平原区硫化物矿床风化与元素表生迁移特征较相似于非岩溶区的情况，表现在可产生较宽的ｐＨ偏低带和较大面积的次生晕     

The hydrological influence of black locust plantations in the loess area of northwest China

Black locust (Robina pseudoacacia) has become one of the most important shelter species in the loess area of northwest China. This paper summarizes recent research concerning its hydrological influence, including canopy interception, litter absorption capacity, its effect on rainfall kinetic energy, infiltration rates, surface runoff, soil moisture, and evapotranspiration, and its role in soil conservation. Several predictive models are listed. on the basis of existing results, optimum characteristics for an effective plantation are defined, and problems requiring further research are identified.     

利用高光谱数据进行植被生化成分反演方法研究

高光谱数据包含着丰富光谱信息,能够定量地分析物质成分^[1]。由高光谱数据,可以运用多元逐步线性回归方法反演植被生化组分含量,从而达到监测植被生长状况的目的^[2]。本文具体介绍了多元逐步线性回归方法,及其在氮、木质素和纤维素含量估算中的应用。     

FUZZY COMPREHENSIVE EVALUATION OF CONTAINER TRANSPORTATION MODES ALONG THE CHANGJIANG RIVER MAIN LINE AND ITS DELTA AREA

The Changjiang River (Yangtze) is one of the fastest growth areas of container transportation in Chi-na. Rail, road and water transportation have competed against each other for container transportation in the Chang-jiang River main line and its delta area. It is of significance to assess these different transportation modes scientifi-cally in order to organize container transportation efficiently in this area and make decision for integral plan and construction of transportation system in this area. This paper outlines application of fuzzy comprehensive evaluation to appraise different modes of typical direction of containers. Twelve assessment indexes were decided. Membership functions were formulated. Evaluation results indicated that road transportation was optimal mode in the Changjiang River delta area, however water transportation was the primary way in the Changjiang River main line.     

藏北南羌塘盆地毕洛错地区下侏罗统曲色组石膏岩层

对西藏自治区北部南羌塘盆地毕洛错地区下侏罗统曲色组石膏岩层进行了研究。根据岩石地层和生物地层资料,确认毕洛错地区的石膏岩层和油页岩为曲色组的一部分,地质时代为早侏罗世,并确认下侏罗统曲色组在区域上可能是寻找油气、油页岩资源的重要层位之一。     

江西省武功山地区浒坑钨矿床的Re-Os年龄及其地质意义

浒坑钨矿床是位于江西省中部武功山成矿带的大型石英脉型黑钨矿床。为了确定该矿床的成矿时代,笔者选取了浒坑含钨石英脉中与黑钨矿共生的辉钼矿进行了高精度Re-Os同位素定年,并获得5个辉钼矿样品的Re-Os等时线年龄和模式加权平均年龄分别为150.2±2.2Ma和149.82±0.92Ma。测年数据表明浒坑钨矿床的成矿时代为150Ma左右,是华南地区中生代大规模成岩成矿作用高峰期的产物。辉钼矿含铼较低,表明成矿物质可能来自壳源,与形成浒坑花岗岩体的燕山期重熔S型花岗岩岩浆活动有关。该矿床形成于燕山期岩石圈伸展减薄环境。     

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.