Using gemorphological markers to discriminate Neogene tectonic activity in the Precordillera of North Chilean forearc (24–25°S)

We study the Neogene tectonic activity in a sector of the Precordillera in the Andean forearc analysing aerial photographs, satellite images and fieldwork data. The interpretation of alluvial landforms, drainage organisation and evolution of intermittent river networks affecting post-Lower Miocene deposits allow us to recognize low intensity tectonic processes controlling the landscape evolution. All these geomorphological markers indicate no strike-slip offsets, but repeated and small tectonic pulses that reactivate previous structures originated under a transpressive context. The observed deformation pattern is the consequence of E–W orthogonal compression resulting in limited shortening, related to the accommodation of deformation in the Chilean forearc of the Neogene uplift of the Altiplano-Puna.     

Changes in climate variability and seasonal rainfall extremes: a case study from San Fernando (Spain), 1821–2000

Summary ?Small changes in the mean and standard deviation values can produce relatively large changes in the probability of extreme events. The seasonal precipitation record in San Fernando (SW Spain) for 1821–2000 is used to investigate how much the relative frequency of dry and wet seasons changes with changes in mean value and standard deviation. The percentiles P10, P25, P75 and P90 of the reference period 1961–1990 are used to define dry and wet seasons. The probability of extreme seasons as function of mean and standard deviation is analysed. The main conclusion is a non-linear relationship between changes in mean and standard deviation values and extreme seasons probability. With these threshold values, the main influence corresponds to changes in mean value. Results are discussed bearing in mind projections of General Circulation Models on future climate in southern Iberian Peninsula. Received June 11, 2001; Revised March 3, 2002     

应用随机反演改善储层表征的过程(英文)

为了适当地完成储层表征的过程,一个有效的方法就是把现场所有可以利用的信息融合成一个一致性的模型。在实际生产中实现这种融合并非简单的任务,所以有必要运用如地震反演等特殊方法。应用地震反演可以使测井数据和地震数据的有效结合成为可能,并且可以得到一个模型,该模型在预测过程中可通过流体数字模拟来验证。地震反演可以通过多种方法进行,主要分为两大类:一类是确定性方法(其代表是回归反演和约束稀疏脉冲反演),另一类是随机方法(其代表是地质统计学反演)。在本次研究中,通过随机反演结果和确定性反演结果的对比展示了随机反演是如何改进储层表征过程的。事实上,随机反演,可以运用较高的采样率(和储层模型的网格大小相接近),来产生一个更可靠的模型。随机反演的另一个好处就是随机方法可产生一些基本的统计测量值来改进解释精度,并且在储层表征过程中能生成大量的实现,从而使储层模型的不确定性研究成为可能。     

Agrometeorological models for forecasting the qualitative attributes of “Valência” oranges

Forecasting is the act of predicting unknown future events using available data. Estimating, in contrast, uses data to simulate an actual condition. Brazil is the world’s largest producer of oranges, and the state of São Paulo is the largest producer in Brazil. The “Valência” orange is among the most common cultivars in the state. We analyzed the influence of monthly meteorological variables during the growth cycle of Valência oranges grafted onto “Rangpur” lime rootstocks (VACR) for São Paulo, and developed monthly agrometeorological models for forecasting the qualitative attributes of VACR in mature orchard. For fruits per box for all months, the best accuracy was of 0.84 % and the minimum forecast range of 4 months. For the relation between °brix and juice acidity (RATIO) the best accuracy was of 0.69 % and the minimum forecast range of 5 months. Minimum, mean and maximum air temperatures, and relative evapotranspiration were the most important variables in the models.     

UNB3m_pack: a neutral atmosphere delay package for radiometric space techniques

Several hybrid neutral atmosphere delay models have been developed at the University of New Brunswick. In this paper we are presenting UNB3m_pack, a package with subroutines in FORTRAN and corresponding functions in MatLab which provides neutral atmospheric information estimated using the UNB3m model. The main goal of UNB3m is to provide reliable predicted neutral atmosphere delays for users of global navigation satellite systems (GNSS) and other transatmospheric radiometric techniques. Slant neutral atmosphere delays are the main output of the package, however, it can be used to estimate zenith delays, Niell mapping functions values, delay rates, mapping function rates, station pressure, temperature, relative humidity and the mean temperature of water vapor in the atmospheric column. The subroutines work using day of year, latitude, height and elevation angle as input values. The files of the package have a commented section at the beginning, explaining how the subroutines work and what the input and output parameters are. The subroutines are self-contained, i.e., they do not need any auxiliary files. The user has simply to add to his/her software one or more of the available files and call them in the appropriate way. The GPS Tool Box is a column dedicated to highlighting algorithms and source code utilized by GPS engineers and scientists. If you have an interesting program or software package you would like to share with our readers, please pass it along; e-mail it to us at gps-toolbox@ngs.noaa.gov. To comment on any of the source code discussed here, or to download source code, visit our website at . This column is edited by Stephen Hilla, National Geodetic Survey, NOAA, Silver Spring, Maryland, and Mike Craymer, Geodetic Survey Division, Natural Resources Canada, Ottawa, Ontario, Canada.     

On the Use of the Jesuit Order Private Correspondence Records in Climate Reconstructions: A Case Study from Castille (Spain) for 1634–1648 A.D.

This work analyses the climatic information content of more than 1000 letters belonging to the private correspondence of the Jesuit order during the period 1634–1648. The information obtained mainly originates in Castille, and it was codified to obtain quantitative indices representative of the evolution of the thermal and rainfall anomalies. The results show that intense rainfall and cold air waves predominated during the study period, in accordance with other results on the climatic evolution of the Iberian Peninsula during the Little Ice Age.     

Worth of secondary data compared to piezometric data for the probabilistic assessment of radionuclide migration

A common approach for the performance assessment of radionuclide migration from a nuclear waste repository is by means of Monte-Carlo techniques. Multiple realizations of the parameters controlling radionuclide transport are generated and each one of these realizations is used in a numerical model to provide a transport prediction. The statistical analysis of all transport predictions is then used in performance assessment. In order to reduce the uncertainty on the predictions is necessary to incorporate as much information as possible in the generation of the parameter fields. In this regard, this paper focuses in the impact that conditioning the transmissivity fields to geophysical data and/or piezometric head data has on convective transport predictions in a two-dimensional heterogeneous formation. The Walker Lake data based is used to produce a heterogeneous log-transmissivity field with distinct non-Gaussian characteristics and a secondary variable that represents some geophysical attribute. In addition, the piezometric head field resulting from the steady-state solution of the groundwater flow equation is computed. These three reference fields are sampled to mimic a sampling campaign. Then, a series of Monte-Carlo exercises using different combinations of sampled data shows the relative worth of secondary data with respect to piezometric head data for transport predictions. The analysis shows that secondary data allows to reproduce the main spatial patterns of the reference transmissivity field and improves the mass transport predictions with respect to the case in which only transmissivity data is used. However, a few piezometric head measurements could be equally effective for the characterization of transport predictions.     

Shallow landslide susceptibility mapping using high-resolution topography for areas devastated by super typhoon Haiyan

Super typhoon Haiyan, considered as one of the most powerful storms recorded in 2013, devastated the central Philippines region on 8 November 2013 with damage amounting to more than USD 2 billion. Hardest hit is the province of Leyte which is located in central Philippines. Rehabilitation of the areas that were devastated requires detailed hazard maps as a basis for well-planned reconstruction. Along with severe wind, storm surge, and flood hazard maps, detailed landslide susceptibility maps for the cities and municipalities of Leyte (7246.7 km²) province are necessary. In order to rapidly assess and delineate areas susceptible to rainfall-induced shallow landslides, Stability INdex MAPping (SINMAP) software was used over a 5-m Interferometric Synthetic Aperture Radar (InSAR)-derived digital terrain model (DTM) grid. Topographic, soil strength, and hydrologic parameters were used for each pixel of a given DTM grid to compute for the corresponding factor of safety. The landslide maps generated using SINMAP are highly consistent with the landslide inventory derived from high-resolution satellite imagery from 2002 to 2014 with a detection percentage of 97.5 % and missing factor of 0.025. These demonstrate that SINMAP performs well despite the lack of an extensive geotechnical and hydrological database in the study area. The detailed landslide susceptibility classification is useful to identify safe and unsafe areas for reconstruction and rehabilitation efforts. These maps complement the debris flow and structurally controlled landslide hazard maps that are also being prepared for rebuilding Haiyan’s devastated areas.