模糊数学识别火山岩岩性

针对火岩地层岩性识别成功率低的状况，应用模糊数学原理，建立模糊数学识别火山岩岩性模式，识别和划分火山岩地层岩性，以便进一步深入研究火山岩油气藏储层，选择8个反映火山岩岩性测井参数，确定阈值；利用所建立的火山岩岩性识别模式，对火山岩岩性进行分类；依据最大隶属原则，识别火山岩岩性，应用实地研究资料，识别10种火山岩岩性，并与岩心鉴定统计分析结果对比，一致性达85％。表明该方法识别火山岩岩性精度较高，在地质上具有很好的应用前景。     

Modeling and assimilation of root zone soil moisture using remote sensing observations in Walnut Gulch Watershed during SMEX04

Soil moisture status in the root zone is an important component of the water cycle at all spatial scales (e.g., point, field, catchment, watershed, and region). In this study, the spatio-temporal evolution of root zone soil moisture of the Walnut Gulch Experimental Watershed (WGEW) in Arizona was investigated during the Soil Moisture Experiment 2004 (SMEX04). Root zone soil moisture was estimated via assimilation of aircraft-based remotely sensed surface soil moisture into a distributed Soil-Water-Atmosphere-Plant (SWAP) model. An ensemble square root filter (EnSRF) based on a Kalman filtering scheme was used for assimilating the aircraft-based soil moisture observations at a spatial resolution of 800 m × 800 m. The SWAP model inputs were derived from the SSURGO soil database, LAI (Leaf Area Index) data from SMEX04 database, and data from meteorological stations/rain gauges at the WGEW. Model predictions are presented in terms of temporal evolution of soil moisture probability density function at various depths across the WGEW. The assimilation of the remotely sensed surface soil moisture observations had limited influence on the profile soil moisture. More specifically, root zone soil moisture depended mostly on the soil type. Modeled soil moisture profile estimates were compared to field measurements made periodically during the experiment at the ground based soil moisture stations in the watershed. Comparisons showed that the ground-based soil moisture observations at various depths were within ± 1 standard deviation of the modeled profile soil moisture. Density plots of root zone soil moisture at various depths in the WGEW exhibited multi-modal variations due to the uneven distribution of precipitation and the heterogeneity of soil types and soil layers across the watershed.     

Multi-dimensional analysis of soil moisture dynamics in trickle irrigated fields. II: Model testing

The mathematical model which was developed in part I of this work for multi-dimensional analysis of soil moisture in irrigated fields is converted into computer algorithms. The algorithms are capable of emulating many field conditions of practical applications during both design and operation phases. The model is subjected to various tests, the results of which are reported here. The tests in various modes of simulations verified the numerical performance of the model and the accuracy of its predictions. The model provides a powerful tool for detailed studies of soil moisture dynamics in one or multi-dimensional problems irrigated fields     

农业管理措施对土壤有机碳动态变化的影响

土壤碳固定问题已成为陆地生态系统碳循环研究的热点问题。土壤碳固定是缓解温室效应加剧的有效方法之一。土壤有机碳含量变化受土地利用方式和耕作措施的强烈影响。将自然土壤转变为耕作土壤会导致土壤碳库的迅速下降,使土壤损失有机碳4.1-5.0×1013kg之间。采用新的农业措施会使碳损失量的60-70%重新被固定。这些措施有保护性耕作(少耕或免耕)、合理施用肥料、覆盖作物、应用深根且富含木质素的作物等。土壤除了固定有机碳外,干旱和半干旱地区土壤还具有固定无机碳的巨大潜力。文章还简要介绍了评价土壤有机碳的两种方法,并对今后的工作提出了几点建议。     

长期酸化对红壤中活性固相铝库大小及亏损程度的影响

用连续分级提取和反复多次酸提取方法研究了长期土壤酸化对红壤固相铝库中铝含量及亏损程度的影响。研究结果表明:嵊县红壤的活性铝库大于永春红壤和屯溪红壤;因永春红壤和屯溪红壤的酸化程度大于嵊县红壤,前两者的有机铝库和无机铝库都比嵊县红壤的亏损,因此反复酸提取过程中铝的释放量也比嵊县红壤少;当高强度酸输入土壤后,弱键合的有机络合态铝可快速活化并亏损,剩余铝库因活性小而释放速率减小,但长期酸化过程中,动力学控制的低活性铝库的活化可能对铝的溶解量仍有重要贡献。     

原子吸收次灵敏线法直接测定土壤中Fe、Mn

用原子吸收次灵敏线法塞曼效应扣除背景测定土壤中Fe、Mn,实验结果表明:此方法有较好的准确度,精密度,操作简单,适合一般土壤中Fe、Mn的测定。     

Two-Dimensional Physical and Numerical Modeling of a Pile-Supported Earth Platform over Soft Soil

This paper focuses on the mechanisms occurring in a granular earth platform over soft ground improved by rigid piles. Two-dimensional physical model experiments were performed using the Schneebeli’s analogical soil to investigate the load transfer mechanisms by arching and the settlement reduction and homogenization. Experimental outputs are compared to results obtained on a numerical model using a plane strain continuum approach. The impact of the constitutive model complexity to simulate the platform material behavior was first assessed, but no large difference was recorded. As far as the proposed model, which takes the main features of the observed behavior satisfactorily into account, the numerical procedure could be validated and the parametric studies extended numerically. Both approaches of this study underlined the main geometrical and geotechnical parameters which should inevitably be taken into account in a simplified design method, namely the capping ratio, the platform height, and the platform material shear strength.     

影响土壤中PAHs降解的环境因素及促进降解的措施

土壤中的多环芳烃(PAHs)类有机污染物的生物有效性低,不易降解。本文综述了影响污染土壤中多环芳烃降解的环境因素和促进降解措施的研究进展。影响土壤中多环芳烃降解的因素,包括水分、养分、土壤物理条件等;促进土壤中多环芳烃降解的措施有:向污染土壤添加有机溶剂、利用冯顿反应、添加堆肥和有机物料等。从目前研究来看,应当通过促进多环芳烃从土壤上解吸和培育具有较高多环芳烃降解能力的微生物来促进多环芳烃污染土壤的修复。     

土壤因子对植物缺铁失绿的影响

本文主要从土壤 pH ,重碳酸盐 ,和氮素形态等几方面综述了各种土壤因子对土壤缺铁失绿的影响 ,并提出了进一步加强研究的方向     

构造性神经网络在测井岩性识别中的应用

测井岩性识别是石油勘探中十分重要的基础工作,准确的岩性识别结果可以为勘探和开发提供可靠的依据。人工神经网络方法可对复杂的高维数据进行非线性映射,在模式识别领域得到越来越广泛的应用。针对传统的BP神经网络算法存在收敛速度慢、隐层数以及隐层节点数难以确定等缺点,研究了一种构造性神经网络学习算法---级联算法（Cascade Correlation Algorithm,简称CC算法）及其在石油工程中的应用。采用该算法对甘肃镇原-泾川地区进行岩性识别研究,通过与BP神经网络的识别结果进行比较,体现出构造性神经网络的优越性。