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Water temperature is fundamental to understand the functioning of aquatic systems. The objective of this study was to assess the effect of warm water discharge from a nuclear power plant on the wat...

Eutrophic reservoirs are characterized by excessive presence of plant and algal growth due to favourable environmental conditions, temperature, light and nutrients. Human activities accelerate this phenomenon and provoke dramatic changes to the aquatic ecosystems. The monitoring of water quality of these ecosystems and the study of the effects they have on the environment demand a large amount of spatial and temporal information, which is almost exclusively provided by Earth Observations (EO). This study uses a large temporal series of Sentinel-2 (S2; 2016 till 2019) images to characterize the temporal and spatial distribution of chlorophyll-a [Chl-a] in San Roque Reservoir, Cordoba Province, Argentina. A robust method that combines empirical modelling of [Chl-a] and data mining analysis is employed. Model results showed significant fit (R2 = 0.77) between [Chl-a] measured in the reservoir and the ratio between the NIR and red bands of S2. An analysis of spatio-temporal patterns demonstrated that [Chl-a] distribution in San Roque is complex and influenced by seasonal changes, aeolian forces, hydrodynamic flows, bathymetry, water levels, and pollution sources. The study also found a correlation between algae bloom events and areas with extreme levels of [Chl-a] (>850 mg/m3) in the water body. Additionally, advanced data mining tools such as slope analysis and spatial anomalies indexes, identified regions in the reservoir where water quality had improved or deteriorated. The results show the added value of using large Sentinel-2 data series to assess the concentration of Chlorophyll-a in eutrophic reservoirs over a variety of spatial and temporal scales., This research was supported by EC-H2020 EO-XPOSURE project (nr. 734541)

As part of a collaborative effort among researchers of several institutions and organizations, this project takes advantage of the Google Earth Engine (GEE) cloud computing environment to map algae bloom over the main water bodies and reservoirs of Latin America using Sentinel-2 imagery (2015 to present). The methodology based on the Normalized Difference Chlorophyll Index (NDCI) for chlorophyll-a and Trophic State Index (TSI) detection provided promising results. NDCI responds well to high levels of chlorophyll-a and, therefore, can be used as an indicator for algae blooms. The image processing as well as the display of maps and charts are being implemented into a GEE App to be freely available for general public use.

Mapping Human Exposure to Risky Environmental Conditions is key to quantify the vulnerability of population and economic assets. In order to develop novel tools, implementing the use of information layers from current and future Earth Observation (EO) missions is necessary. The EOxposure project that has been created and funded by the European Commission's Horizon 2020 research and innovation program covers this porpoise. Several topics involving human exposure to environmental risks are being studied, including water quality and pollution, which is addressed in this paper. The high productivity of biomass registered in eutrophic water bodies, leads to qualitative and quantitative changes in the phytoplankton community, resulting in massive algae blooms. This research work proposes a methodology that takes advantage of the temporal and spectral resolution of Sentinel-2 (S2) for monitoring eutrophic reservoir. Specifically, it uses large temporal series of S2 images and advanced data mining techniques to study the turbid and productive water of San Roque reservoir, Argentina. The spatial patterns and the temporal tendencies of these aquatic indicators are analysed and evaluated in order to assess their contribution to water quality models and a local water management program.&nbsp

El Salar de Atacama -ubicado en el desierto homonimo - representa un valioso recurso tanto desde el punto de vista hidrologico y ambiental como desde el punto de vista productivo, ya que es un medio propicio para la explotacion de litio. En este trabajo se propone un estudio exploratorio orientado a la caracterizacion y monitoreo de este tipo de ambientes a partir del uso de sensores remotos, mediante la utilizacion de tecnicas de teledeteccion optica y de Radar de Apertura Sintetica (SAR).

Winter snow packs in the Argentinean Andes are the primary source of surface runoff and water supply in the adjacent lowlands. The socioeconomic, environmental, and recreational benefits provided by the mountain snow packs are enjoyed by over 10 million people. Monitoring the spatial and temporal changes of seasonal snow cover helps to predict and mitigate floodings, avalanches, frost damage, among other hazards. It can also help estimating the supply for human consumption fresh water, irrigation and hydropower stations, and may contribute to the improvement of weather forecasts and the understanding of the climate system. This study is a first approach for evaluating and detecting changes in Argentinean Andes snow packs through temporal series of Sentinel-1 SAR images using the data available in Google Earth Engine (GEE). Additionally, the products of applying a wet snow mapping algorithm with images obtained in GEE, and the same images but pre-processed in SNAP coregistrating the images, were compared in order to assess the commission and omission classification errors.

A temporal-spatial analysis is made of the effect of an underwater artificial air diffusion system for the period 2008-2011, on the water quality of Embalse San Roque, Cordoba, through field data and LANDSAT5-TM satellite imagery. The temperature estimated using TM6 band, resulting with a determination coefficient of 0.94 and a mean square error of 0.4oC. A multiple regression model was used to calculate log(chlorophyll-a) by means of TM1 and TM4 bands, obtaining a determination coefficient of 0.64 which was validated with a control group with and agreement equal 83 %. The processed images show the localized effect of the underwater artificial air diffusion system, improving the water quality in their neighbours.

In this work we present novel results concerning water quality changes in an eutrophic water body connected with an artificial aeration system installed in it. Sixty one in-situ and laboratory measurements of biogeochemical variables were recorded monthly between October 2008 and June 2011 to evaluate temporal and spatial changes in San Roque reservoir (Argentina).t-Student mean difference tests, carried out over the whole period, showed with 95% confidence that a monitoring point located at the centre of the water body is representative of the chemical behaviour of the reservoir. Thermal stratification was observed in all sampling sites in the summer, but the frequency of these episodes was markedly lower in bubbling zones. Mean chlorophyll-a concentrations were 58.9 μg·dm−3and 117.0 μg·dm−3in the absence and in the presence of thermocline respectively. According to thet-Student test, this difference was significant, withp< 0.001. Phosphate release from sediments was corroborated under hypoxia conditions. ANOVA one way analysis did not show significant spatial differences for any variable. Mean normalize spatial index (MENSI) was developed to compare data from different regions affected by high temporal variability. It proved to be useful to quantify spatial differences. Structure analysis of temporal series was used to scrutinize both chemical and spatial association successfully. Three chemically different zones were determined in the reservoir. This study demonstrated that spatial comparisons by means of marginal statistics may not be an adequate method when high temporal variation is present. In such a case, temporal structure analysis has to be considered.

Understanding and modelling land use and land cover (LULC) change have become one of the major subjects of interest for environmental management due to the negative effects that human activities generate on the normal functioning and dynamics of freshwater resources. Remote sensing and geographic information systems (GIS) are essential tools for assessing the drivers that cause LULC change and its relationship with lake and reservoir water quality. The objective of this study was to assess the spatial and temporal dynamics of LULC change in the watershed of Los Molinos reservoir (Argentina), and to investigate its relationship with the reservoir's water quality. Four Landsat imagery was used to analyse the LULC change in the studied watershed and in different buffer zones from 1990 to 2020. Further, the Normalized Difference Vegetation Index (NDVI) derived from a MODIS time-series dataset (2001–2020) was used to explain the effects of LULC change on the status of the reservoir. Results showed that the most significant LULC change started two decades ago and it has intensified during the last ten years. This change is related to the intensification of agriculture activities, and to the increasing conversion into urban areas, mainly on the shores of Los Molinos reservoir. During the period 2010–2020, urbanization located in the 1 km buffer zone defined from the shore of the reservoir increased at an annual rate of 18.02%. The degradation trend of LULC in Los Molinos watershed significantly contributed to the degradation of water quality of the reservoir. This was corroborated by analysing the MODIS NDVI time-series, which showed that since 2014 the NDVI trend-line presented an increasing behaviour and extreme values of NDVI, related to algal blooms, were more frequently observed. Fil: Bonansea, Matias. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas Fisicoquímicas y Naturales. Instituto de Ciencias de la Tierra, Biodiversidad y Ambiente - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Ciencias de la Tierra, Biodiversidad y Ambiente; Argentina. Universidad Nacional de Río Cuarto. Facultad de Agronomía y Veterinaria; Argentina Fil: Bazán, Raquel del Valle. Comisión Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentina Fil: German, Alba. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Comisión Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentina Fil: Ferral, Anabella. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Comisión Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentina Fil: Beltramone, Giuliana Beatriz. Comisión Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Cossavella, Ana Maria. Universidad Nacional de Córdoba; Argentina Fil: Pinotti, Lucio Pedro. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas Fisicoquímicas y Naturales. Instituto de Ciencias de la Tierra, Biodiversidad y Ambiente - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Ciencias de la Tierra, Biodiversidad y Ambiente; Argentina

The new Sentinel-2 satellites present a significant scientific opportunity for the study of water quality. The objective of this study was to evaluate the suitability of Sentinel-2 imagery for estimating and mapping Secchi disk transparency (SDT) in Río Tercero reservoir (Córdoba-Argentina). Field observations and a dataset of atmospherically corrected Sentinel-2 images were used to generate and validate an algorithm to estimate water clarity in the studied reservoir. As a real application of the used methodology, the validated algorithm was used to obtain a spatial representation of water clarity in the reservoir during sampling campaigns. Results demonstrate capabilities of Sentinel-2 mission to make a substantial contribution to the current assessment and understanding of aquatic systems by estimating and mapping a water quality characteristic. Fil: Bonansea, Matias. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas Fisicoquímicas y Naturales. Instituto de Ciencias de la Tierra, Biodiversidad y Ambiente - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Ciencias de la Tierra, Biodiversidad y Ambiente; Argentina. Universidad Nacional de Río Cuarto. Facultad de Agronomía y Veterinaria. Departamento de Estudios Básicos y Agropecuarios; Argentina Fil: Ledesma, Micaela. Universidad Nacional de Río Cuarto. Facultad de Agronomía y Veterinaria. Departamento de Estudios Básicos y Agropecuarios; Argentina Fil: Bazán, Raquel. Universidad Nacional de Córdoba; Argentina Fil: Ferral, Anabella. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina Fil: German, Alba. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentina. Ministerio de Agua, Ambiente y Servicios Públicos. - Gobierno de la Provincia de Cordoba. Ministerio de Agua, Ambiente y Servicios Publicos.; Argentina Fil: O Mill, Patricia. Universidad Nacional de Córdoba; Argentina. Ministerio de Agua, Ambiente y Servicios Públicos. - Gobierno de la Provincia de Cordoba. Ministerio de Agua, Ambiente y Servicios Publicos.; Argentina Fil: Rodriguez, Claudia. Universidad Nacional de Río Cuarto. Facultad de Agronomía y Veterinaria. Departamento de Estudios Básicos y Agropecuarios; Argentina Fil: Pinotti, Lucio Pedro. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas Fisicoquímicas y Naturales. Instituto de Ciencias de la Tierra, Biodiversidad y Ambiente - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Ciencias de la Tierra, Biodiversidad y Ambiente; Argentina. Universidad Nacional de Córdoba; Argentina

In this column, we present a summary of the Third Remote Sensing Spring School at the Teófilo Tabanera Space Center, Córdoba, Argentina, 10–21 September 2018, to support the launch of the Satélite Argentino de Observación con Microondas (SAOCOM) 1A synthetic aperture radar (SAR) mission. Nearly all of the lecturers were IEEE Geoscience and Remote Sensing Society (GRSS) senior members. More than 90 specialists in a variety of areas and representing South and Central American countries and others around the world were present. Several international collaborations were proposed during discussions and meetings among participants and experts. Fil: Ferral, Anabella. Universidad Nacional de Córdoba; Argentina. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Scavuzzo, Carlos M.. Universidad Nacional de Córdoba; Argentina. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentina Fil: Solorza, Romina. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentina. Universidad Nacional de Córdoba; Argentina Fil: Marquez, Jorge. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentina. Universidad Nacional de Córdoba; Argentina Fil: Salvia, Maria Mercedes. Consejo Nacional de Investigaciónes Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Astronomía y Física del Espacio. - Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Astronomía y Física del Espacio; Argentina Fil: Gomez Deniz, Luis. Universidad de Las Palmas de Gran Canaria; España Fil: Notarnicola, Claudia. Instituto de Teledeteccion Aplicada; Italia Fil: Cigna, Francesca. Italian Space Agency; Italia Fil: Lopez Martinez, Carlos. Institute of Science and Technology ; Luxemburgo Fil: Bhattacharya, Avik. Indian Institute of Technology Bombay; India Fil: Li, Xiaofeng. National Oceanic and Atmospheric Administration; Estados Unidos Fil: Camps, Adriano. Universidad Politécnica de Catalunya; España Fil: Frery, Alejandro C.. Universidade Federal de Alagoas; Brasil

Throughout the world, bees fulfill a vital ecosystem function, as well as other insects that ensure the delicate balance of natural ecosystems. In fact, biodiversity and production of food depend largely on pollination carried out by bees. At present, there is a widespread concern due to the decrease in the number of hives, a strange phenomenon that occurs worldwide and until today little is known about its causes. Hence the importance to design beekeeping environmental policies to strengthen the activity and preserve bees. San Javier, Cordoba, Argentina presents an important beekeeping activity being leader as honey exporter in the region due to its favorable environmental conditions, constituting itself as a source rich in biodiversity. In order to carry out an optimal territorial order, it is necessary to consider environmental and legal aspects to lineout good apicultural practices. In this work we implement for the first time in Argentina geographic information systems (GIS) as a management tool for data collection, analysis and modelling in order to generate an aptitude map to carry out this activity. Based on georeferenced information collected by satellite sensors, field surveys and official institutions, new spatial data were generated through the elaboration of thematic maps that show the current situation of apicultural territorial order in the study zone. Particularly, distance of apiary sites to water bodies, to native forest, to urban areas, to cultivated areas and to roads are taken into account to make a decision tree model which generates an aptitude map to carry out beekeeping activity. Finally, it is contrasted against apiaries distribution in the study zone in order to provide support to the sector by showing number apiaries that should be relocated and best zones to settle new ones.

The protection and restoration of water-related ecosystems is one of the goals to be achieved by the United Nations’ 2030 Agenda for Sustainable Development. In this framework and requested by government Argentine institutions concerned with water, biodiversity and territorial management, this study analyzes the evolution of the flooded area within the Dulce River wetlands and Mar Chiquita Lake Nature Reserve (centered around 30.6°S, 62.6°W, 70 m above sea level) in Argentina since 2003, when the historical maximum extent was reached, until 2017. The Modified Normalized Difference Water Index (MNDWI) was calculated on atmospherically corrected NASA Landsat 5 Thematic Mapper (L5-TM) and Landsat 8 Operational Land Imager (L8-OLI) reflectance data over two-scene cloudless-sky mosaics to cover the whole Reserve. Mixed-water pixels constituted an important fraction of the total-water covered area, particularly during years of minimum water level in Mar Chiquita Lake. So, MNDWI values were analyzed along transects crossing two stable regional water bodies to determine precise thresholds for detection of non-water (MNDWI < −0.15 for L5-TM, MNDWI < −0.35 for L8-OLI), mixed-water (−0.15 < MNDWI < 0.4 for L5-TM, −0.35 < MNDWI < 0.5 for L8-OLI) and open-water (0.4 < MNDWI for L5-TM, 0.5 < MNDWI for L8-OLI) pixels. A higher spatial resolution image, SPOT5-HGR2, was used to validate the classification method. A confusion matrix was built which resulted in an overall accuracy of 99.2% and a Kappa coefficient of 0.98. In-situ Geo-referenced photographic registers were also taken simultaneously to a Landsat 8 overpass to confirm the classification thresholds. The analysis of simulated MNDWI response, by using the assumption of the linear mixture model, showed that mixed pixels should present from 9% to 76% of detectable open-water area. Maximum total flooded area extensions of about 3600 km 2 by 2003–2005 and a minimum one of 2050 km 2 by the end of 2011 were established, followed by a recent trend to the recovering with a total flooded area of about 3400 km 2 in the period 2015–2017. Open-water covered area follows closely the behavior of in-situ water level measurements of Mar Chiquita Lake, showing a maximum in year 2003 and a minimum towards the end of 2013, in a significant linear relation from which a topographical slope of the terrain of about 0.012% is inferred that agrees with previous bathymetric studies. Results show the powerful complement between a reliable water satellite monitoring tool and locally-measured parameters in so dynamic wetland regions. Fil: Ferral, Anabella. Universidad Blas Pascal; Argentina. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Luccini, Eduardo Alfredo. Provincia de Córdoba. Ministerio de Ciencia y Técnica. Centro de Excelencia en Productos y Procesos de Córdoba; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Aleksinkó, Alejandro. Secretaría de Recursos Hídricos y Coordinación de la Provincia de Córdoba; Argentina Fil: Scavuzzo, Carlos Matias. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina

La información de precipitación es crítica para la comprensión del equilibrio hidrológico a escala global. La lluvia, junto con otras variables ambientales tales como evapotranspiración, temperatura, humedad relativa, entre otras, representa un factor de interés para la producción agrícola. Debido a esto, surge la necesidad de llevar adelante estudios que posibiliten comprender mejor la variabilidad espacial y temporal de las mismas. En este trabajo se presenta una metodología que permite automatizar la descarga de series temporales de datos de precipitación de la Misión de Medición de la Lluvia Tropical (Tropical Rainfall Measuring Mission (TRMM)) desde la plataforma Google Earth Engine (GEE) y validar los datos obtenidos con una serie de datos históricos de una estación meteorológica. Con este fin se desarrolló un sistema bajo la plataforma GEE para la generación y descarga de datos TRMM. Como caso de estudio se fijó la cuenca del Arroyo Las Conchas de la Provincia de Entre Ríos, Argentina. Para la validación de los resultados, se generó un set de datos con la información de precipitaciones desde el 1 de enero del 2000 al 31 de diciembre del 2015, medida por pluviómetros, para el área de influencia de la estación meteorológica de la Estación Experimental Agropecuaria del INTA de Oro Verde, departamento de Paraná, provincia de Entre Ríos, Argentina. Los resultados obtenidos mediante el proceso de evaluación muestran que existe una estrecha relación entre ambas fuentes de información. La metodología propuesta permitirá generar sets de datos históricos de precipitación para estudiar el régimen hídrico en regiones de difícil acceso o en cuencas extensas y poco pobladas., Precipitation information is critical for understanding the hydrological equilibrium on a global scale. Rain, with other conditions, represents a factor of interest for agricultural production. Therefore, the need of carrying out studies that make possible to understand spatial and temporal variability of rain becomes evident. This paper presents a methodology that allows the automatic downloading of time series of precipitation data from the Tropical Rainfall Measurement Mission (TRMM) from the Google Earth Engine (GEE) platform and validate it with a series of meteorological data. The system was developed under the GEE platform for downloading the TRMM data. As a case of study, the Arroyo Las Conchas basin in the Entre Ríos province, in Argentina was established. To validate the results, a set of data was generated with rainfall information in 16 year period, by measuring the rain gauges for the area of influence at the meteorological station in the Instituto Nacional de Tecnología Agropecuaria (INTA) Station at Oro Verde, Paraná, Entre Ríos, Argentina. The results through the evaluation process show a close relationship between both sources of information. The proposed methodology will allow generating sets of historical rainfall data to study the hydrological regime of the Las Conchas Stream basin., Facultad de Ciencias Agrarias y Forestales

In thIS study we present advances in the analysis of environmental variables obtained from moderate resolution satellite images and their association with infestation indexes by Triatoma infestans (vector of Chagas disease). The environmental variables considered are the result of climatology and anomalY summaries derived from MODIS sensor time series (products MOD11A2 and MOD13A2) for the period 2000 to 2015), land use from Serena and precipitation from TRMM. The infestation, which was measured at the locality / rural LOCATION level, is expressed as a percentage of households with presence of T. infestans. Data was collected from the National Chagas service. Generalized linear models are proposed to associate the infestation with the environmental variables OBTAINED FROM SATELLITE IMAGES and other local conditions (characteristics of the dwellings and the presence of domestic animals). In general, the environmental variables considered in the models have more influence on Infestation indexes than the locals variables. The variables with the best adjustment were: annual average of LST of the years 2013 and 2015, the NDVI of 2014 and the anomalies of NDVI of the same year. These variables showed higher weights than the variables representing local conditions. From an eco-epidemiological perspective, the usage of products derived from sensors with Medium resolution with national coverage are tools which allow decision makers to generate more accurate responses in less time.

Water bodies eutrophication is a worldwide environmental problem characterized by excessive phytoplankton growth which often includes occurrence of harmful algal blooms events. Chlorophyll-a concentration is widely used as an indicator of biomass and can be quantified by optic sensors. In this work, we use a satellite derived Chlorophyll-a concentration time series for the period 2001–2014 obtained from MODIS/TERRA data to detect and characterize algal bloom events in an eutrophic reservoir. Our results demonstrate that fixed threshold methods identify too many bloom dates but a dynamic method based on frequencies analysis and statistical approach, performed better because it represents the normal phytoplankton mass and a bloom is identified like a deviation from it. This approach was tested in San Roque reservoir which supplies fresh water to Cordoba city, one of the most populated of Argentina. According to Carlson index values, this is an eutrophic to hypereutrophic water body. Validation of log10 (Chlorophyll-a concentration) derived from satellite model concentration with ground-based measurements data of Chlorophyll-a concentration demonstrates an acceptable error (RMSE = 0.59) considering data distribution. The implementation of the proposed method to identify blooms over a control data set and validated with LANDSAT 8 - OLI images, demonstrates that the approach described is robust and stable over time.

El agua historicamente ha sido considerada un recurso renovable, sin embargo, en el ultimo siglo se viene observando una degradacion sostenida de su calidad, tanto en sistemas continentales como oceanicos debido al impacto antropico. Sumado a esta problematica, aparece como una nueva amenaza el cambio climatico global, el cual se manifiesta causando severas sequias o extraordinarias inundaciones en diferentes regiones del planeta. En este marco, la gestion del recurso hidrico y el monitoreo satelital representan un punto central en las politicas publicas, ya que permiten anticiparse y adaptarse a estas perturbaciones. En este trabajo se utiliza informacion satelital para realizar un analisis de la evolucion anual de la calidad de agua del embalse San Roque, Cordoba, y su relacion con la ocurrencia de incendios, precipitaciones y crecimiento urbano para el periodo 2001-2016. La calidad de agua se evalua a partir de una serie temporal de clorofila-a generada con datos MODIS-TERRA y validada previamente para el cuerpo de agua en estudio. El area construida y quemada se calcula a partir de la clasificacion de imagenes LANDSAT-TM/ETM+/OLI para la cuenca. La precipitacion acumulada se obtiene a partir de los productos de la mision TRMM de la NASA. Se analiza tambien la variable temperatura en el agua del embalse, obtenida a partir de datos MODIS-TERRA. Por ultimo, se realizan analisis de correlacion entre las variables mencionadas.

In Argentina, the deforestation has reached a significant magnitude, particularly in the Chaco Serrano area. One of the main consequences of deforestation is the presence of bare soils which are vulnerable to precipitation, where runoff causes flash floods, particularly in the cities crossed by the river in Saldan stream basin, region Sierras Chicas – Cordoba. In this context geospatial techniques allow to quantify the spatial distribution and temporal evolution of prone zones to erosion based on models which incorporate climatic, edaphological, biological and anthropic variables. The RUSLE (Revised Universal Soil Loss Equation) model, calibrated by means of local factors, is used as base methodology to carry out the analysis. The calculation is made by merging satellite, archive and field information. The optical image classifications show a decrease in middle and low stratum of the vegetation cover for the period 2005-2013, a situation that directly impacts the erosion rate of soils close to urban piedmont populations.

Global climate change has different demonstrable effects on ecosystem structures and socio-economic factors throughout the entire planet. 90 percent of last decade natural hazards around the world were attributed to water-related disasters. Forest-land use change, deforestation, unplanned urbanization, localization of marginal population groups in vulnerable areas, wild fires, high temperatures, unusual precipitations, among others are some of the variables that increase the probability of a water-related catastrophe. Comprehensive hazard assessments and appropriated environmental policies orientated towards risk management complemented with planning and designing of hydraulic infrastructures may contribute to decrease flash flooding risk a well as the magnitude of the potential damages. The aim of this study is to develop a consistent methodology to determine the vulnerability, threat and risk of mountain urban areas that are particularly vulnerable to the effects of heavy, rapid rains and represent the obtained results in a risk map. Identifying risk prone areas can be achieved by adapting geological-geotechnical charts, hydrological models, field inventories and official census data from the town of Unquillo, in the province of Cordoba, Argentina. The analytic hierarchy process was used in order to determine the individual contribution of each vulnerability factor, together with geographical information systems used to combine the obtained information trough algebra and transformation of satellite imagery bands. The case of study show that 59% of the total flooding vulnerability relates to the buildings infrastructure, followed by the social factors which represent 33% of the total vulnerability equation. The threat map was validated using landmarks and remains obtained as a consequence of the flooding that occurred on February 15th 2015 in the study area.

Eutrophication is a phenomenon that affects many water bodies around the world. San Roque Dam is not an exception since it has been going through a huge increase in algae concentration. In this framework, its monitoring is a key matter, as is the source of water supply most important of Cordoba city. Remote sensing is a fundamental tool to complement traditional in situ monitoring and understand processes that occur in the reservoir. This study presents a semi-empirical algorithm obtained from MODIS data and in situ chlorophyll-a measurements, provided by the Ministry of Water Resources of Cordoba Province. From this model, a daily time chlorophyll-a time series was obtained from 2001 to 2014. Statistical analysis of the series indicate that water quality of the reservoir has worsened when comparing sets of last (2014–2010) and first (2010–2014) five years.

The local structure of the sulfur atom of methanethiolate and ethanethiolate on the Cu(111) and Cu(100) surfaces was investigated from first principles employing the periodic supercell approach in the framework of density functional theory. On the 111 surface, we investigated the (square root 3 x square root 3)R30 degrees and (2 x 2) structures, whereas on the 100 surface, we investigated the p(2 x 2) and c(2 x 2) structures. The landscape of the potential energy surface on each metal surface presents distinctive features that explain the local adsorption structure of thiolates found experimentally. On the Cu(111) surface, the energy difference between the hollow and bridge sites is only 3 kcal/mol, and consequently, adsorption sites ranging from the hollow to the bridge site were observed for increasing surface coverages. On the Cu(100) surface, there is a large energy difference of 12 kcal/mol between the hollow and bridge sites, and therefore, only the 4-fold coordination was observed. The high stabilization of thiolates on the hollow site of Cu(100) may be the driving force for the pseudosquare reconstruction observed experimentally on Cu(111). Density of states analysis and density difference plots were employed to characterize the bonding on different surface sites. Upon interaction with the metal d bands, the pi* orbital of methanethiolate splits into several peaks. The two most prominent peaks are located on either edge of the metal d band. They correspond to bonding and antibonding S-Cu interactions. In the case of ethanethiolate, all the back-bonds are affected by the surface bonding, leading to alternating regions of depletion and accumulation of charge in the successive bonds.

The adsorption of n-alkanethiols on the 1 1 1 surface of copper was studied by means of quantum mechanical calculations. Charge transfer processes between the adsorbates and the metal were investigated in order to elucidate the nature of the adsorbed species. The electronic structure of the adsorbates in the proximity of the Fermi level was also investigated to obtain a better understanding of the electronic states which contribute to scanning tunneling microscopy (STM) images. We found that the bonding of the n-alkanethiols is independent of the chain length when the adsorbates are perpendicular to the surface. This bonding mainly involved the sulfur p-orbitals and, to a lesser extent, the orbitals of the first methyl group. From the analysis of dipole moment curves and Mulliken populations, a charge transfer of 0.6 electrons from the metal towards the adsorbate was obtained, thus confirming the anionic nature of the adsorbate. A depletion of electron density was observed in the metal atoms of the primary chemisorption site as well as a net accumulation of charge around the sulfur atom. Constant current STM images of thiols adsorbed flat on the surface showed a pronounced protrusion on the position of sulfur due to the accumulation of electron density around this atom in the proximity of the Fermi level. However, for thiols adsorbed perpendicular to the surface, the STM images were found to be sensitive to the position of the terminal methyl group. A corrugation of 1.5 A was obtained for a methyl radical adsorbed perpendicular to the surface.