Soil moisture content can be used to predict drought impact on agricultural yield better than precipitation. Remote sensing is viable source of soil moisture data in instrument-scarce areas. However, space-based soil moisture estimates lack suitability for daily and high-resolution agricultural, hydrological, and environmental applications. This study aimed to assess the potential of the random forest machine learning technique to enhance the spatial resolution of remote soil moisture products from the SMAP satellite. Models were built using random forest for spatial downscaling of SMAP-L3-E, then visually and statistically evaluated for disaggregation quality. The impact of topography, soil properties, and precipitation on the downscaled soil moisture was examined. The relationship between downscaled soil moisture and in-situ soil moisture was analyzed. The results indicate that the pro...

La presente investigación permitió determinar la mejora en la gestión administrativa a partir de la certificación BASC en la Empresa Venture S.A. El diseño que se aplicó en la investigación fue de alcance descriptivo y enfoque cualitativo, lo que ayudó a encontrar dichas mejoras a través de herramientas de investigación como: la entrevista a profundidad. De esta manera, se compiló la información entrevistando a 9 colaboradores, conformados por jefes y asistentes de cada área. Los resultados permitieron determinar las mejoras, divididas en cuatro dimensiones: planificación, organización, dirección y control. A estas, se logró identificar sus respectivos elementos de cada dimensión logrando obtener una amplia mejora de cada una de estas, debido a la mejora alcanzada por la certificación BASC. Finalmente, se recomienda que la Empresa Venture S.A. aplique y continue mejora...

The Peruvian Andes are a hotspot of vulnerabilities to impacts in water resources due to the propensity for water stress, the highly unpredictable weather, the sensitivity of glaciers, and the socio-economic vulnerability of its population. In this context, we selected the Vilcanota-Urubamba catchment in Southern Peru for addressing these challenges aiming at our objectives within a particular hydrological high-mountain context in the tropical Andes: a) Develop a fully-distributed, physically-based glacier surface energy balance model that allows for a realistic representation of glacier dynamics in glacier melt projections; b) Design and implement a glacio-hydrological monitoring and data collection approach to quantify non-glacial contributions to water resources and the impact of catchments interventions; c) Mapping of human water use at high spatiotemporal resolution and determining ...