Análisis del Comportamiento de la Precipitación Estimada a partir de datos TRMM sobre Áreas de Intensa Deforestación en La Amazonía Legal en el Periodo 2001-2013

With 6.5 million km2, the Amazon basin is the largest hydrological system in the world, with estimated discharges of 209,000 m3s-1, it is the largest continuous extension of tropical forest. However, this region is the target of constant threats, whether due to deforestation or climate change. In this context, understanding the functioning of the system is essential, either to assist in decision-making or studies of future scenarios. The aim of this study was to analyze the spatial-temporal distribution of precipitation in areas with high deforestation rates in the Brazilian Amazon basin. For this analysis, NASA’s Tropical Rainfall Measuring Mission (TRMM), product 3B43_V6 during the period 2001-2013, estimated monthly rainfall data and the annual rate of deforestation estimated by PRODES are used. Rainfall estimation of the TRMM satellite show good correlations with the data of the observed stations, besides it represents satisfactorily the annual variations of precipitation during the studied period. For the years with the highest rate of deforestation (2001-2006 and 2008), there was a precipitation deficit represented by negative anomalies, while in the recovery period (2009-2013) positive correlations were obtained. Overall, deforestation seems to exert some influence on precipitation. The extensive application of remote sensing techniques using the new Earth Observation programs for monitoring of the correlation studied in The Legal Amazon as a future line areproposed.Con 6,5 millones de Km2, la cuenca Amazónica es el mayor sistema hidrológico del mundo, con descargas estimadas de 209.000 m3s-1, es la mayor extensión continua de bosque tropical. Sin embargo, esta región es el blanco de constantes amenazas, sea por deforestación o por alteraciones climáticas. En este contexto, comprender el funcionamiento del sistema es esencial, sea para auxiliar en la toma de decisiones o estudios de escenarios futuros. Este trabajo tuvo como objetivo analizar la distribución espacio-temporal de la precipitación sobre áreas con alta tasa de deforestación en la cuenca de La Amazonía Legal de Brasil. Para este análisis se utilizaron datos de precipitación mensual estimada por la misión Tropical Rainfall Measuring Mission (TRMM) de NASA, producto 3B43_V6 durante el periodo 2001-2013 y la tasa anual de deforestación estimada por PRODES. Las estimaciones de la precipitación del satélite TRMM muestran buenas correlaciones con los datos de las estaciones observadas, además representa satisfactoriamente las variaciones anuales de precipitación durante el periodo estudiado. Para los años de mayor tasa de deforestación (2001-2006 y 2008) existió un déficit de precipitación representado por las anomalías negativas mientras que en el periodo de recuperación (2009-2013) se obtiene correlaciones positivas. De modo general, se observó que la deforestación parece ejercer ciertas influencias sobre la precipitación. Se propone como línea futura la aplicación extensiva de técnicas de teledetección de los nuevos programas de Observación de la Tierra para el monitoreo de la correlación estudiada en La Amazonía Legal

Interannual variability in water storage over 2003-2008 in the Amazon Basin from GRACE space gravimetry, in situ river level and precipitation data

International audienceWe investigate the interannual variability over 2003-2008 of different hydrological parameters in the Amazon river basin: (1) vertically-integrated water storage from the GRACE space gravimetry mission, (2) surface water level of the Amazon River and its tributaries from in situ gauge stations, and (3) precipitation. We analyze the spatio-temporal evolution of total water storage from GRACE and in situ river level along the Amazon River and its main tributaries and note significant differences between the various parts of the basin. We also perform an Empirical Orthogonal Decomposition of total water storage, river level and precipitation over the whole basin. We find that the 2003-2008 period, is characterized by two major hydrological events: a temporary drought in late 2005 that affected the western and central parts of the basin and very wet conditions peaking in mid-2006, in the eastern, northern and southern regions of the basin. Derivative of basin-average water storage from GRACE is shown to be highly correlated with the Southern Oscillation Index (a proxy of ENSO -- El Niño-Southern Oscillation), confirming that the spatio-temporal change in hydrology of the Amazon basin is at least partly driven by the ENSO phenomenon, as noticed in previous studies

Development and analysis of the Soil Water Infiltration Global database

© Author(s) 2018. In this paper, we present and analyze a novel global database of soil infiltration measurements, the Soil Water Infiltration Global (SWIG) database. In total, 5023 infiltration curves were collected across all continents in the SWIG database. These data were either provided and quality checked by the scientists who performed the experiments or they were digitized from published articles. Data from 54 different countries were included in the database with major contributions from Iran, China, and the USA. In addition to its extensive geographical coverage, the collected infiltration curves cover research from 1976 to late 2017. Basic information on measurement location and method, soil properties, and land use was gathered along with the infiltration data, making the database valuable for the development of pedotransfer functions (PTFs) for estimating soil hydraulic properties, for the evaluation of infiltration measurement methods, and for developing and validating infiltration models. Soil textural information (clay, silt, and sand content) is available for 3842 out of 5023 infiltration measurements (∼76%) covering nearly all soil USDA textural classes except for the sandy clay and silt classes. Information on land use is available for 76ĝ€% of the experimental sites with agricultural land use as the dominant type (∼40%). We are convinced that the SWIG database will allow for a better parameterization of the infiltration process in land surface models and for testing infiltration models. All collected data and related soil characteristics are provided online in ∗.xlsx and ∗.csv formats for reference, and we add a disclaimer that the database is for public domain use only and can be copied freely by referencing it. Supplementary data are available at https://doi.org/10.1594/PANGAEA.885492 (Rahmati et al., 2018). Data quality assessment is strongly advised prior to any use of this database. Finally, we would like to encourage scientists to extend and update the SWIG database by uploading new data to it.status: publishe