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

Modeling of Soil Water Distribution in a Small Mid-Latitude Watershed on the British Isle for Short Term Landslide and Flood Risk Assessment

The R-TopModel hydrological model coupled with two landslide and flood probability distribution models was applied to simulate the daily hydrological conditions of a small catchment in the Midlands of the British Isles, throughout 2017. Originally, the methodology was applied to a risk area in the tropical region. In this work, the application was extended to mid-latitude watersheds. The hydrographic basin around the Carsington Water dam (located in the Midlands of the Great Britain) is chosen because it presents risks. The model Nash-Sutcliffe Efficiency for the upstream discharge from the Carsington Water dam reached 50% with a correlation coefficient of the order of 70%, an acceptable value considering the seasonal effects of the dam on evapotranspiration and higher soil permeability. Modeling the distribution of soil moisture and excess surface water allowed obtaining the spatial distribution of the maximum conditional probability of landslides and floods in the Carsington Water catchment. These probability maps obtained are consistent with long-term susceptibility maps for Great Britai