Screening of polymers on selected Hawaii soils for erosion reduction and particle settling

In recent years, high‐molecular‐weight anionic polyacrylamides (PAMs) have been tested on a variety of soils, primarily in temperate climates. However, little information is available regarding the effectiveness of PAM for preventing soil loss through runoff in tropical settings. Screening tests were performed using three negatively charged PAMs and one positively charged PAM on five Hawaii soils (two Oxisols, one Vertisol, and two Aridisols) to determine erosion loss, sediment settling, and aggregate stability. A laboratory‐scale rainfall simulator was used to apply erosive rainfall at intensities from 5 to 8·5 cm h^?1 at various PAM doses applied in both dry and solution forms. Soil detachment due to splash and runoff, as well as the runoff and percolate water volumes, were measured for initial and successive storms. The impact of PAM on particle settling and aggregate stability was also evaluated for selected soil‐treatment combinations. Among the PAMs, Superfloc A‐836 was most effective, and significantly reduced runoff and splash sediment loss for the Wahiawa Oxisol and Pakini Andisol at rates varying between 10 and 50 kg ha^?1. Reduced runoff and splash sediment loss were also noted for PAM Aerotil‐D when applied in solution form to the Wahiawa Oxisol. Significant reductions in soil loss were not noted for either the Lualualei Vertisol or the Holomua Oxisol. It is believed that the high montmorillonite content of the Lualualei Vertisol and the low cation‐exchange capacity of the Holomua Oxisol diminished the effectiveness of the various PAMs tested. The polymers were also found to enhance sediment settling of all soils and helped improve their aggregate stability. This screening study shows the potential use of PAM for tropical soils for applications such as infiltration enhancement, runoff reduction, and enhanced sedimentation of detention ponds. Copyright © 2005 John Wiley & Sons, Ltd.     

Analytical solutions of one‐dimensional infiltration before and after ponding

This paper is a continuation of previous research, which obtained a convenient solution for arbitrary surface fluxes before ponding. By means of Fourier Transformation this has been extended to derive analytical solutions of a linearized Richards' equation for arbitrary input fluxes after surface saturation. Copyright © 2003 John Wiley & Sons, Ltd.     

北京地区两次沙尘(暴)天气过程对比分析

通过对 2 0 0 0年 4月 6日和 4月 9日北京地区两次沙尘 (暴 )天气过程的对比分析认为 :蒙古气旋型和不伴有气旋的西北槽型所造成的北京沙尘天气的严重程度不同 ;沙源地区中低层较强上升运动的主要作用是将当地沙尘垂直输送到空中 ,然后在70 0hPa较强西北气流的引导下将卷起的沙尘水平输送到下游地区 ;不稳定层结又加强了沙尘天气 ;沙尘暴区上空z 螺旋度分布的特征是高层为负值 ,低层为正值 ,对流层中低层螺旋度正的大值区与卫星云图显示的沙尘暴区具有较好的一致性 ,对沙尘暴的预报有一定的指示意义     

碳酸岩Sr、Nd、Pb 同位素地球化学研究评述

碳酸岩是出露相对较少的幔源岩石，其中Sr与Nd是研究地幔物质组成的主要对象之一。本文统计了世界上主要碳酸岩的锶、钕、铅同位素组成特征；研究显示，碳酸岩源区主要是洋岛玄武岩高U／Pb的HIMU端员和富集端员(EM1或EM2)的混合作用；此外大部分碳酸岩的锶、钕同位素落在大洋玄武岩范围内；这些均表明其成因与地慢柱有密切联系。碳酸岩及与之共生的硅酸岩的同源或独立源区模式部很难充分解释两者同位素组成特征，逭反映碳酸岩的演化模式涉及更复杂的过程。可能是俯冲作用使碳酸岩源区经历不同时间和程度的富集、亏损过程导致地幔源区成分不均一。     

Geochemical correlations between effusive and explosive silicic volcanics in the Saraykent region (Yozgat), central Anatolia,Turkey

Two main volcanic events are distinguished between Saraykent and Akçakışla in the Yozgat province of central Anatolia: (1) early Late Cretaceous–Palaeocene effusive activity, that produced a sequence of intermediate to felsic ‘basal lavas’; and (2) marginally later Palaeocene explosive activity that formed a series of covering ignimbrite flows. Due to their close temporal and spatial relation, geochemical comparisons were made between the silicic members of the lavas and ignimbrites, to identify chemical groups and their relative petrogenesis. The basal lavas range from calc‐alkaline basaltic andesites to dominant rhyolites. Based on trace element correlations three main geochemical groups were identified: the Akçakışla rhyolites (present as domes); Akçakışla rhyodacites‐dacites (lava flows); and Ozan‐Saraykent rhyolites (lava flows). Large‐ion lithophile elements have been mobile in all the groups, but mainly in the Akçakışla rhyolites. Rare earth element (REE) patterns show marked similarity between the Ozan and Saraykent basal lavas. The Akçakışla dome rhyolites are more fractionated with lower La_N/Yb_N ratios (c.10), whereas the Akçakışla basal lavas have much higher La_N/Yb_N ratios (c.30). The chemical coherence and petrographic similarities between the Saraykent and Ozan lavas suggest a single suite related via fractionation. Three geochemical groups were also established for the ignimbrites: Saraykent ignimbrite; Bağlıca ignimbrite‐Toklu‐Kızıldağ crystal tuffs; and Keklikpınar ignimbrite. The ignimbrites, like the basal lavas, display a pronounced depletion in Ba on ORG‐normalized plots. Relative to the basal lavas, chondrite‐normalized patterns for the ignimbrites are different in displaying negative Eu anomalies that indicate feldspar fractionation. The lack of geochemical overlap or coherence between any of the lava and ignimbrite groups suggests that they represent distinct eruptive events and are not related in any simple volcanic development and cogenetic sense. Two geochemical features are common to all the volcanic rock groups: (1) the presence of a Nb‐Ta anomaly, which is generally accepted as a crustal signature; and (2) the relatively low Y abundances which appear characteristic for the region as a whole. These fundamental features of the local silicic volcanism largely reflect source composition and effects. Copyright © 2002 John Wiley & Sons, Ltd.     

Finite element analysis of the effect of corrosion on the behavior of reinforced earth walls

A simple model for the corrosion‐induced loss of stiffness and strength of the steel strips of earth‐reinforced walls was introduced in a finite element simulation of the long‐term behavior of the wall, in which the backfill‐strips interactions are taken into account by means of a generalized homogenization procedure (called a multiphase model). The results show an initial phase of slow displacements induced by the loss of stiffness, followed after a few decades by a steep acceleration of the displacements, leading to wall failure. The influences of the parameter controlling corrosion, the backfill cohesion and the heterogeneity of the corrosion process are discussed. Results are used to discuss a strategy for reinforced earth wall surveillance. Copyright © 2011 John Wiley & Sons, Ltd.     

A mass ratio limit for primordial black holes

We augment our scenario for the formation of astronomical objects from macroscopic superstrings by the assumption that the central matter keeps its identity in the fragmentation. From the condition that the angular momentum per mass squared of this matter should be less than the Kerr limit G/c, we obtain upper limits for the ratio of the mass of central black holes M(BH) to the mass M of the host object. This limit is M(BH)/M ≈ 0.001, and, expressed in observed quantities, approximately M(BH)/M ≈ σ²/(v · c) where σ is the r.m.s. velocity, v the rotational velocity and c the velocity of light. The valuesM(BH) agree with the observed behaviour both in order of magnitude and in the variation with velocity dispersion. (© 2003 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

A comparative study of sequential minimal optimization-based support vector machines,vote feature intervals,and logistic regression in landslide susceptibility assessment using GIS

Landslide susceptibility assessment using GIS has been done for part of Uttarakhand region of Himalaya (India) with the objective of comparing the predictive capability of three different machine learning methods, namely sequential minimal optimization-based support vector machines (SMOSVM), vote feature intervals (VFI), and logistic regression (LR) for spatial prediction of landslide occurrence. Out of these three methods, the SMOSVM and VFI are state-of-the-art methods for binary classification problems but have not been applied for landslide prediction, whereas the LR is known as a popular method for landslide susceptibility assessment. In the study, a total of 430 historical landslide polygons and 11 landslide affecting factors such as slope angle, slope aspect, elevation, curvature, lithology, soil, land cover, distance to roads, distance to rivers, distance to lineaments, and rainfall were selected for landslide analysis. For validation and comparison, statistical index-based methods and the receiver operating characteristic curve have been used. Analysis results show that all these models have good performance for landslide spatial prediction but the SMOSVM model has the highest predictive capability, followed by the VFI model, and the LR model, respectively. Thus, SMOSVM is a better model for landslide prediction and can be used for landslide susceptibility mapping of landslide-prone areas.