Soft soil mapping using Horizontal to Vertical Spectral Ratio (HVSR) for seismic hazard assessment of Chandigarh city in Himalayan foothills,north India

The populated and expanding city of Chandigarh is located in the foothills of Himalaya, near the potentially active Main Frontal Thrust (MFT). A hazard assessment for this city is consequently of major importance. Thick sediments underlies the city and that can potentially amplify the earthquake shaking and contribute to an earthquake disaster in the city. The present study applies the Horizontal to Vertical Spectral Ratio (HVSR) ambient noise methodology to estimate the resonance frequency of the soft sediments and to obtain a first order estimate of sediment thickness. The study indicates that the soil thickness range from 30 to 270 m and that the resonance frequencies vary from 0.236 to 1.479 Hz. A smooth correlation function between soil thickness and resonance frequency is found, indicating relatively homogeneous soil.     

AWAPer: An R package for area weighted catchment daily meteorological data anywhere within Australia

Meteorological time-series data are a fundamental input to hydrological investigations. But sourcing data is often laborious and plagued with difficulties. In an effort to improve efficiency and rigor we present an R-package, named AWAPer ( https://github.com/peterson-tim-j/AWAPer ), for the efficient estimation of daily area weighted catchment average and spatial variance of meteorological variables, including evapotranspiration. The package allows creation and updating of a data-cube of gridded daily data from 1900 onwards. Once created, point and area weighted estimates can be extracted at user-defined locations and time periods for anywhere within Australia. Examples of point and catchment average extraction are presented.     

Remote sensing and GIS based determination of groundwater dependent ecosystems in the Western Cape, South Africa

Finding the location of groundwater dependent ecosystems (GDEs) is important in determining the extent of restrictions that need to be placed upon the abstraction of groundwater. Remote sensing was combined with geographical information system (GIS) modelling to produce a GDE probability rating map for the Sandveld region, South Africa. Landsat TM imagery identified the areas indicating the probable presence of GDEs and GIS assisted in their delineation. Three GIS models were generated: a GIS model predicting landscape wetness potential (LWP model) based on terrain morphological features; the LWP model was modified to highlight groundwater generated landscape wetness potential (the resulting GglWP model); and a groundwater elevation model was interpolated, combining groundwater level measurements in boreholes in the region with digital elevation model data. Biomass indicators generated from Landsat were classified and combined with the GIS models, followed by field verification of riverine and wetland GDEs. The LWP model provided the most accurate results of the three models tested for GDEs in this region.

Chevron Ridges and Runup Deposits in the Bahamas from Storms Late in Oxygen-Isotope Substage 5e

Landward-pointing V-shaped sand ridges several kilometers long are common along the windward margin of the Bahama Islands. Their axes share a northeast–southwest trend. Internally, the ridges contain low-angle oolitic beds with few erosional truncations. Commonly interbedded are tabular, fenestrae-rich beds such as those formed by the sheet flow of water over dry sand. Defined here as “chevron ridges,” these landforms appear to have originated in the rapid remobilization of bank margin ooid bodies by the action of long-period waves from a northeasterly source. Deposits along adjacent coastlines also preserve evidence of the impact of large waves. Reworked eolian sand bodies preserve beach fenestrae and hydraulic scour traces up to +40 m on older ridges. On cliffed coasts, 1000-ton boulders have been thrown well inland, recording the impact of large waves. Amino acid ratios confirm a correlation of the ridges across the archipelago, while stratigraphy, spacing, and cross-cutting relationships indicate emplacement as sea level fell rapidly from the substage 5e maximum at or above +6 m.     

污染分布下的Lp估计抗差测度

观测数据中含有粗差或异常值扰动的误差分布可视为污染分布。根据M估计理论,导出了Lp估计的影响函数,分析了Lp估计的抗差能力,并用效率来测度估计的优劣、综合抗差能力和效率,指出观测数据中含有粗差的扰动,应用p为[1．2．1．5]的Lp估计来进行处理。     

一定分布模式下的最优Lp估计

观测数据在一定的分布模式下,需从理论上解决究竟用多大的ｐ值进行Ｌｐ估计（最优ｐ值的确定）,本文基于渐近方差整体最小的原则,给出了最优Ｌｐ估计的定义。观测数据中含有粗差（异常值）的扰动,其误差分布可视为污染分布,作者分析了最优ｐ值的大小,结果表明,若观测数据中含有不同大小、数量的粗差,为使Ｌｐ估计差最小,则ｐ将取［１．２,１．５］中的某一定值,Ｌｐ估计结果最优,此结论对测量数据处理具有一定的参考价值