Secondary lahar hazard assessment for Villa la Angostura, Argentina, using Two-Phase-Titan modelling code during 2011 Cordón Caulle eruption

This paper presents the results of lahar modelling in the town of Villa La Angostura (Neuquén-Argentina) based on the Two-Phase-Titan modelling computer code. The purpose of this exercise is to provide decision makers with a useful tool to assess lahar hazard during the 2011 PuyehueCordón Caulle Volcanic Complex eruption. The possible occurrence of lahars mobilized from recent ash falls that could reach the city was analysed. The performance of the TwoPhase-Titan model using 15 m resolution digital elevation models (DEMs) developed from optical satellite images and from radar satellite images was evaluated. The output of these modellings showed inconsistencies that, based on field observations, were attributed to bad adjustment of the DEMs to real topography. Further testing of results using more accurate radar-based 10 m DEM, provided more realistic predictions. This procedure allowed us to simulate the path of flows from Florencia, Las Piedritas and Colorado creeks, which are the most hazardous streams for debris flows in Villa La Angostura. The output of the modelling is a valuable tool for city planning and risk management especially considering the glacial geomorphic features of the region, the strong urban development growth and the land occupation that has occurred in the last decade in Villa La Angostura and its surroundings.Fil: Córdoba, G.. Universidad de Nariño; ColombiaFil: Villarosa, Gustavo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones En Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Reg.universidad Bariloche. Instituto de Investigaciones En Biodiversidad y Medioambiente; ArgentinaFil: Sheridan, M.. State University of New York at Buffalo; Estados UnidosFil: Viramonte, Jose German. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Investigaciones en Energia No Convencional. Universidad Nacional de Salta. Facultad de Ciencias Exactas. Departamento de Física. Instituto de Investigaciones en Energia No Convencional; ArgentinaFil: Beigt, Debora. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones En Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Reg.universidad Bariloche. Instituto de Investigaciones En Biodiversidad y Medioambiente; ArgentinaFil: Salinas de Salmuni, Nelida Graciela. Comision Nacional de Actividades Espaciales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Estimación de área de nieve húmeda con datos SAR en la cuenca del río Tupungato, Mendoza, Argentina

Los datos provenientes de sensores remotos, en particular de Radares de Apertura Sintética (SAR), poseen gran potencial en el estudio de la nieve ya que proveen información independientemente de la condición atmosférica reinante. En este trabajo se investiga la capacidad de la banda C en la detección de nieve húmeda, en la cuenca del río Tupungato, provincia de Mendoza, Argentina. Para ello se utilizaron imágenes Sentinel 1, procesadas siguiendo la metodología desarrollada por Nagler y Rott (2000) que emplea la técnica de detección de cambios respecto a una imagen tomada como referencia, en condición libre de nieve o con nieve seca. Este algoritmo requiere la adecuación de parámetros en función a las características particulares del área de estudio. El análisis realizado en la cuenca indicó que el umbral óptimo para identificar coberturas de nieve húmeda es -2dB. Los resultados fueron validados indirectamente a partir de datos de temperatura de superficie y área cubierta de nieve, obtenidos con imágenes ópticas LANDSAT 8. De esta forma, se verificó la correcta clasificación con SAR de pixeles correspondientes a nieve húmeda. Los mapas de nieve húmeda generados con datos SAR son de mucha utilidad ya que nutren a modelos hidrológicos para el pronóstico de caudal en zonas con régimen nival.The data coming from remote sensing, in particular Synthetic Aperture Radars (SAR), have great potential in the study of snow since they provide information regardless of weather conditions. In this work, the capacity of the C band in wet snow detection is investigated, in the Tupungato river basin, province of Mendoza, Argentina. To this scope, Sentinel 1 images were used, processed following the methodology developed by Nagler and Rott (2000), which adopts a change detection technique by considering an image taken as a reference, in a snow-free or dry snow condition. This algorithm requires the adaptation of parameters according to the particular characteristics of the study area. The analysis carried out in this basin indicates that the optimal threshold to identify wet snow is -2dB. The results were validated indirectly by using information of surface temperature and snow cover area, obtained with LANDSAT 8 optical images. In this way, it was verified the correct classification with SAR of pixels corresponding to wet snow. Wet snow maps generated with SAR data are very useful to nourish hydrological models for the forecast of flow in mountain areas dominated by snow regime.Fil: Teverovsky Korsic, Sofia Andrea. Comision Nacional de Actividades Espaciales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Pascual, Ignacio G.. Comision Nacional de Actividades Espaciales; ArgentinaFil: Notarnicola, Claudia. No especifíca;Fil: Salinas de Salmuni, Nelida Graciela. Comision Nacional de Actividades Espaciales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaIEEE Biennial Congress of ArgentinaSan Miguel de TucumánArgentinaUniversidad Nacional de TucumánUniversidad Tecnológica Nacional. Facultad Regional Tucumá

Arsenic contamination of natural waters in San Juan and La Pampa, Argentina

Arsenic (As) speciation in surface and groundwater from two provinces in Argentina (San Juan and La Pampa) was investigated using solid phase extraction (SPE) cartridge methodology with comparison to total arsenic concentrations. A third province, Río Negro, was used as a control to the study. Strong cation exchange (SCX) and strong anion exchange (SAX) cartridges were utilised in series for the separation and preservation of arsenite (AsIII), arsenate (AsV), monomethylarsonic acid (MAV) and dimethylarsinic acid (DMAV). Samples were collected from a range of water outlets (rivers/streams, wells, untreated domestic taps, well water treatment works) to assess the relationship between total arsenic and arsenic species, water type and water parameters (pH, conductivity and total dissolved solids, TDS). Analysis of the waters for arsenic (total and species) was performed by inductively coupled plasma mass spectrometry (ICP-MS) in collision cell mode. Total arsenic concentrations in the surface and groundwater from Encon and the San José de Jáchal region of San Juan (north-west Argentina within the Cuyo region) ranged from 9 to 357 μg l−1 As. Groundwater from Eduardo Castex (EC) and Ingeniero Luiggi (LU) in La Pampa (central Argentina within the Chaco-Pampean Plain) ranged from 3 to 1326 μg l−1 As. The pH range for the provinces of San Juan (7.2–9.7) and La Pampa (7.0–9.9) are in agreement with other published literature. The highest total arsenic concentrations were found in La Pampa well waters (both rural farms and pre-treated urban sources), particularly where there was high pH (typically > 8.2), conductivity (>2,600 μS cm−1) and TDS (>1,400 mg l−1). Reverse osmosis (RO) treatment of well waters in La Pampa for domestic drinking water in EC and LU significantly reduced total arsenic concentrations from a range of 216–224 μg l−1 As to 0.3–0.8 μg l−1 As. Arsenic species for both provinces were predominantly AsIII and AsV. AsIII and AsV concentrations in San Juan ranged from 4–138 μg l−1 to <0.02–22 μg l−1 for surface waters (in the San José de Jáchal region) and 23–346 μg l−1 and 0.04–76 μg l−1 for groundwater, respectively. This translates to a relative AsIII abundance of 69–100% of the total arsenic in surface waters and 32–100% in groundwater. This is unexpected because it is typically thought that in oxidising conditions (surface waters), the dominant arsenic species is AsV. However, data from the SPE methodology suggests that AsIII is the prevalent species in San Juan, indicating a greater influence from reductive processes. La Pampa groundwater had AsIII and AsV concentrations of 5–1,332 μg l−1 and 0.09–592 μg l−1 for EC and 32–242 μg l−1 and 30–277 μg l−1 As for LU, respectively. Detectable levels of MAV were reported in both provinces up to a concentration of 79 μg l−1 (equating to up to 33% of the total arsenic). Previously published literature has focused primarily on the inorganic arsenic species, however this study highlights the potentially significant concentrations of organoarsenicals present in natural waters. The potential for separating and preserving individual arsenic species in the field to avoid transformation during transport to the laboratory, enabling an accurate assessment of in situ arsenic speciation in water supplies is discussed