Optical properties and light penetration in a deep,naturally acidic,iron rich lake: Lago Caviahue (Patagonia,Argentina)

The optical properties and light climate in the deep and extremely acid Lake Caviahue have been studied in order to better understand its characteristics and the possible influence upon the phytoplankton community. The absorption coefficients for the dissolved fraction were maximal in the ultraviolet (UV) region and the water absorption spectra showed a shoulder around 300 nm, which was attributed to the concentration of Fe(III). No radiation was detected in the water column below 360 nm. The depth of the 1% incident radiation was dependent of wavelength, showing its maximum of 13.3 m at 565 nm, compared to 1.7 m and 4.8 m at 400 nm and 700 nm, respectively. Phytoplankton biomass was low and showed an almost constant profile with depth despite the relative darkness of the water column. Optical climate of Lake Caviahue is not typical of high elevation lakes but is more similar to low elevation shallow lakes of the Andean region. The chemical composition of the water, mainly Fe oxidation state and concentration, is the responsible for the high attenuation of the UV radiation (UVR). Living organisms are protected of UVR because Lake Caviahue waters are a shield against UV-B.     

Quantifying the impact of no-till on sediment yield in southern Brazil at the hillslope and catchment scales

No-till (NT) is a soil management system designed to protect soil resources from water erosion and provide numerous benefits compared to conventional tillage through the increase of organic matter inputs into the soil. However, NT in isolation is not sufficient to control erosion processes caused by an excessive production of surface runoff. This study evaluated soil losses on agricultural hillslopes under no-till characterized by contrasted water, soil, and crop management conditions. To this end, water and soil losses were monitored between 2014 and 2018 at two scales, including four macroplots (0.6 ha; 27 events) and two paired zero-order catchments (2.4 ha; 63 events). The resulting dataset covered a wide range of rainfall conditions that occurred in contrasted soil, crop, and runoff management conditions. Hyetographs, hydrographs, and sedigraphs were constructed, and these data were used to evaluate the impact of management on sediment yields, including that of terraces, scarification, and phytomass on sediment yield. The installation of terraces reduced sediment yield by 58.7%, mainly through surface runoff control. Crop management including an increased phytomass input efficiently controlled soil losses (63%), although it did not reduce runoff volume and peak flow. In contrast, scarification had no impact on runoff and soil losses. The current research demonstrated the need to combine the installation of terraces and leaving a high amount of phytomass on the soil to control surface runoff and erosion and reduce sediment yield. The current research therefore reinforces the relevance of the monitoring strategy conducted at the scale of macroplots and zero-order catchments to evaluate the impact of contrasted water, soil, and crop management methods and select the most effective conservation agriculture practices.     

Analysis of Wind Roses Using Hierarchical Cluster and Multidimensional Scaling Analysis at La Plata,Argentina

Knowledge of frequency wind patterns is very important for air pollution modelling, especially in a city like La Plata (approximately 850,000 inhabitants) with high vehicular and industrial activities and no air monitoring network. An hourly wind analysis was carried out on data from two local weather stations (points A and J). An initial result was that, in spite of differences in data quality, the local weather stations observations were consistent with local and regional National Meteorological Service (NMS) monthly based observations. Two non conventional multivariate statistical methods were employed to further analyse hourly data at points A and J. Hierarchical cluster resulted in a good summarising tool to visualise prevailing hourly winds. Resultant vectors emerging from the clustering process showed good similarity between sites and seasons; this allowed a further visualization of the average diurnal wind development. Multidimensional scaling (MDS) permitted a pairwise comparison of a large number of hourly wind roses. These wind roses were more similar to each other in colder seasons and at site A (the one that is closer to the river) than in warmer seasons and at site J. Most of the observed variations regarding seasons and sites revealed by cluster and MDS analysis are explained in terms of the sea-land breeze circulations. The methodology applied proved to be of utility for simplifying the analysis of high dimensional data with numerous observations.     

Predicting forest fire in the Brazilian Amazon using MODIS imagery and artificial neural networks

The presented work describes a methodology that employs artificial neural networks (ANN) and multi-temporal imagery from the MODIS/Terra-Aqua sensors to detect areas of high risk of forest fire in the Brazilian Amazon. The hypothesis of this work is that due to characteristic land use and land cover change dynamics in the Amazon forest, forest areas likely to be burned can be separated from other land targets. A study case was carried out in three municipalities located in northern Mato Grosso State, Brazilian Amazon. Feedforward ANNs, with different architectures, were trained with a backpropagation algorithm, taking as inputs the NDVI values calculated from MODIS imagery acquired during five different periods preceding the 2005 fire season. Selected samples were extracted from areas where forest fires were detected in 2005 and from other non-burned forest and agricultural areas. These samples were used to train, validate and test the ANN. The results achieved a mean squared error of 0.07. In addition, the model was simulated for an entire municipality and its results were compared with hotspots detected by the MODIS sensor during the year. A histogram analysis showed that the spatial distribution of the areas with fire risk were consistent with the fire events observed from June to December 2005. The ANN model allowed a fast and relatively precise method to predict forest fire events in the studied area. Hence, it offers an excellent alternative for supporting forest fire prevention policies, and in assisting the assessment of burned areas, reducing the uncertainty involved in currently used methods.     

Geochronology and Landscape Development Along the Middle Río Quequén Grande at the Paso Otero Locality,Pampa Interserrana,Argentina

The Paso Otero Locality is a cluster of archaeological sites within the middle Río Quequén Grande basin located in the northern coastal plain of Argentina. The valley fill is Holocene alluvial, eolian, and palustrine sediment, including the top of the Guerrero Member (∼10,000 ¹⁴C yr B.P.), upper Río Salado Member (∼3000 ¹⁴C yr B.P.), and lower La Postrera Formation (∼2400 ¹⁴C yr B.P.). Regional soils include the Puesto Callejón Viejo (10,000 to 9400 ¹⁴C yr B.P.) and the Puesto Berrondo (∼4800 ¹⁴C yr B.P.). Radiocarbon sampling of buried A‐horizons on both sides of the river produced 17 dates considered reliable. The geoarchaeological information allows exploration of the implications for the formation of the archaeological record. Similar geological processes of differential intensity have resulted in contexts of different archaeological resolution and integrity. The Paso Otero Locality provides both a local and regional view of late Quaternary events and processes for the middle basin of the Río Quequén Grande.     

Conodont geothermometry of the lower Paleozoic from the Precordillera (Cuyania terrane), northwestern Argentina

The thermal history of the Precordillera terrane of northwestern Argentina has been constrained by the conodont colour alteration index (CAI) in combination with previously published paleothermal data (e.g., illite crystallinity and clay mineral assemblages). The pattern of paleotemperatures displays an increase in paleotemperatures to the west and south of the basin. This configuration shows a gradual and continuous transition from diagenesis to low-grade metamorphism, which is apparently not controlled by any of the morpho-structural subdivisions of the Precordillera (i.e., Western, Central, or Eastern). According to our results, the lower Paleozoic sedimentary burial played a secondary role in the heating of the Precordillera. Instead, the predominant component was loading by thrust sheets, which reflects the effects of the Devonian collision of Chilenia, particularly, in the Western Precordillera. Conversely, our paleothermometric data from the easternmost exposures of the Precordillera do not evidence anomalies referable to any of the accretionary events that contributed to the early Paleozoic building of the southern proto-Andean margin of Gondwana. Instead, the expected thermally altered conodonts from the Cuyania accretion are represented by metamorphosed conodont elements transported to the deeper settings of the west. The CAI data also suggest that overburden depth varied from ca. 3.6 km in the shelf region of the Eastern Precordillera to ca. 12 km in the slope to rise deposits of the Western Precordillera, thus providing constrains for the palinspastic restoration across the orogen. On the other hand, the smooth increase of peak paleotemperatures to the south of the Precordillera is associated with the exposure of deeper crustal levels at that sector, probably related to larger shortening due to stronger collisional effects, or alternatively, a weaker mechanical response of its elastic lithosphere.     

Co-seismic landslide detection after M 7.4 earthquake on June 23, 2020, in Oaxaca,Mexico, based on rapid mapping method using high and medium resolution synthetic aperture radar (SAR) images

Landslides are the fourth most common natural disasters in the world, with Costa Rica and southern Mexico being the most affected regions of Central America (Froude and Petley, 2018). In this work, we propose a semi-automated method to detect earthquake-triggered landslides for rapid mapping after a disaster event using open Sentinel-1 data. We used high-resolution TerraSAR-X data and very high-resolution Spot-7 images to compare and evaluate the accuracy of landslide distribution maps generated from the semi-automated method, applied to the M 7.1 earthquake on June 23, 2017, in Oaxaca, Mexico. The outcomes showed better accuracy in descending orbits due to ‘windward-leeward’ physiographic conditions, with a 50.56% quality percentage. This shows a reasonably good capacity to detect co-seismic landslides. However, the breaching factor was also high because several features, such as bare soils and agricultural areas, were incorrectly identified as co-seismic landslides. Finally, this semi-automated method establishes a basis for future improvements in methodologies applied to construct rapid mapping inventories using medium SAR scales.

     

Geostatistical facies simulation with geometric patterns of a petroleum reservoir

During exploration and pre-feasibility studies of a typical petroleum project many analyses are required to support decision making. Among them is reservoir lithofacies modeling, preferably using uncertainty assessment, which can be carried out with geostatistical simulation. The resulting multiple equally probable facies models can be used, for instance, in flow simulations. This allows assessing uncertainties in reservoir flow behavior during its production lifetime, which is useful for injector and producer well planning. Flow, among other factors, is controlled by elements that act as flow corridors and barriers. Clean sand channels and shale layers are examples of such reservoir elements that have specific geometries. Besides simulating the necessary facies, it is also important to simulate their shapes. Object-based and process-based simulations excel in geometry reproduction, while variogram-based simulations perform very well at data conditioning. Multiple-point geostatistics (MPS) combines both characteristics, consequently it was employed in this study to produce models of a real-world reservoir that are both data adherent and geologically realistic. This work aims at illustrating how subsurface information typically available in petroleum projects can be used with MPS to generate realistic reservoir models. A workflow using the SNESIM algorithm is demonstrated incorporating various sources of information. Results show that complex structures (e.g. channel networks) emerged from a simple model (e.g. single branch) and the reservoir facies models produced with MPS were judged suitable for geometry-sensitive applications such as flow simulations.     

Analysis of an illustrative interaction between structural features and earthworm populations in Brazilian ferralsols

Ferralsols are characterized by poorly-defined horizons, weak macrostructure and strong development of a fine granular structure comprising subangular micro-aggregates. In this study, the morphological and physical modifications caused by earthworm activity in a clayey ferralsol were analysed. After describing soil structures, undisturbed samples were taken for evaluating aggregates and determining clod bulk density and particle density. Soil water retention properties were measured and an inventory of soil invertebrate macrofauna was created. The structural and porous transformations were due to aggregates created by earthworm activity. Changes in bulk density can be associated with pore modifications caused by a change in the proportions of aggregate types, and a notable reduction of total porosity was measured, tending to increase soil volume with dense aggregates. Structural modifications affected the topsoil down to 0.5 m and water retention between −1 and −33 kPa, the principal water compartment of these soils.