Evapotranspiration (ETo) is one of the most important variables of the water cycle when water requirements for irrigation, water resource planning or hydrological applications are analyzed. In this context, models based on artificial neural networks (ANN) of the retro-propagation type can be an alternative method to estimate ETo in highland regions using a number of input variables limited. The objective of this study is to develop ANN models to estimate ETo for the Peruvian highlands using input variables such as maximum air temperature (Tmax), minimum air temperature (Tmin), hours of sunshine (Sh), relative humidity (Rh) and wind speed (Wv), as an alternative method to FAO Penman–Monteith method (FAO-PM56) and Hargreaves–Samani (HS). Daily climatic datasets recorded at 12 meteorological stations between 1963 and 2015 were selected in this study. For evaluation reason, the ETo calcu...

La frecuencia y magnitud de los eventos climáticos extremos de precipitación han aumentado significativamente en varios países del mundo, incluido Perú. Estos hechos causan pérdidas económicas y humanas, especialmente en países en vías de desarrollo. La información y metodologías que permitan prevenir o diseñar estrategias para afrontarlas son escasas o inexistentes. El objetivo de esta investigación fue analizar la capacidad del producto satelital IMERG (Integrated Multi- satellitE Retrievals) del satélite GPM (Global Precipitation Measurement) y datos observados a partir de estaciones meteorológicas mediante un enfoque mixto para estimar la distribución de lluvias extremas en la región del Cusco ubicado al sur del Perú. Este enfoque mixto aprovechó las ventajas que ofrecen ambas fuentes de información como es la solidez de los datos observados a lo largo de varios aÃ...

The retreats of the planet’s tropical glaciers are natural indicators of the variation of precipitation, temperature, and other variables. The glaciers of the Alto Santa sub-basin are sources of freshwater storage for consumptive and non-consumptive use for different sectors. As a result of climatic variations, it is essential to analyze the dynamics of the snow cover area (SCA). The methodology consisted of processing 6578 MODIS Snow Cover MOD10A1 product images and generating 18-year time series using the Platform Google Earth Engine (GEE). Normalized Difference Snow Index (NDSI) was used to estimate the extent of snow cover, and to validate the MODIS snow cover product, we used the same overlapping date of Landsat 5 and 8 Surface Reflectance Tier 1, to examine the relationships between daily precipitation and temperature. The standardized correlation results gave good results with s...