La precipitación representa uno de los elementos más importantes dentro del ciclo del agua para la representación de la oferta hídrica en cuencas hidrográficas. Debido a una inadecuada distribución de estaciones, seguridad, relieve, accesibilidad, etcétera, existe escasez de estos datos en cuencas andinas del Perú. Esto representa uno de los principales inconvenientes que afrontan los investigadores en ciencias de la tierra y ciencia del clima para la representación de manera espacial y temporal de la precipitación. En los últimos años, el avance de las tecnologías permite la estimación de las variables hidrológicas a partir de técnicas de sensoramiento remoto. Estos datos deben ser evaluados con observaciones meteorológicas. En esta investigación se evaluaron 11 productos de precipitación estimada por sensoramiento remoto (PPEDsr) que estiman la precipitación. La evaluación de los PPEDsr se realizó para el periodo 1981-2018 a paso de tiempo: diario, de diez días y mensual. Se utilizaron los estadísticos descriptivos: error medio (ME), correlación de Pearson (R), raíz del error medio cuadrático (RMSE), error absoluto medio (MAE) y BIAS relativo (BIAS). Además, de los estadísticos categóricos: probabilidad de detección (POD), tasa de falsas alarmas (FAR), índice de éxito crítico (CSI). Los productos MSWEP, CHIRPS, TRMM-3B42 y PERSIANN-CDR resultaron ser más eficientes para representar la variabilidad espacial de las precipitaciones diarias y acumuladas en la cuenca del Vilcanota. Los datos de sensoramiento remoto mostraron ser útiles para representar la variabilidad espacio-temporal de la precipitación la cuenca Vilcanota, los resultados sugieren que los datos de sensoramiento remoto podrían ser utilizados para simular el balance hidrológico en cuencas hidrográficas de montaña andinas con escasa información in-situ.

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 current and future levels of water (in)security; and d) Integrate last objectives in a glacier - water security assessment model and evaluate the tool's capacity to support locally embedded climate change adaptation strategies. The RAHU project intends to transform the scientific understanding of the impact of glacier shrinkage on water security and, at the same time, to connect to and inform policy practices in Peru. It follows a "source to tap" paradigm, in which is planned to deliver a comprehensive and fully integrated water resources vulnerability assessment framework for glacier-fed basins, comprising state-of-the-art glaciology, hydrology, water demand characterisation, and water security assessment. It includes glacio-hydrological and water resources monitoring campaigns, to complement existing monitoring efforts of our project partners and collaborators, and new remotely sensed data sets. Those campaigns will be implemented using the principles and tools of participatory monitoring and knowledge co-creation that our team has pioneered in the tropical Andes. The datasets produced by this approach, combined with existing monitoring implemented by our team and collaborators, will allow us to build an integrated water supply-demand-vulnerability assessment model for glacierized basins, and to use this to evaluate adaptation strategies at the local scale. This research is part of the multidisciplinary collaboration between British and Peruvian scientists (Newton Fund, Newton-Paulet).

Water resources availability in the southern Andes of Peru is being affected by glacier and snow retreat. This problem is already perceived in the Vilcanota river basin, where hydro-climatological information is scarce. In this particular mountain context, any water plan represents a great challenge. To cope with these limitations, we propose to assess the space-time consistency of 10 satellite-based precipitation products (CMORPH–CRT v.1, CMORPH–BLD v.1, CHIRP v.2, CHIRPS v.2, GSMaP v.6, GSMaP correction, MSWEP v.2.1, PERSIANN, PERSIANN–CDR, TRMM 3B42) with 25 rain gauge stations in order to select the best product that represents the variability in the Vilcanota basin. For this purpose, through a direct evaluation of sensitivity analysis via the GR4J parsimonious hydrological model over the basin. GSMap v.6, TRMM 3B42 and CHIRPS were selected to represent rainfall spatial variability according with different statistical criteria, such as correlation coefficient (CC), standard deviation (SD), percentage of bias (%B) and centered mean square error (CRMSE). To facilitate the interpretation of statistical results, Taylor's diagram was used to represent the CC statistics, normalized values of SD and CRMSE.A distributed degree-day model was chosen to analyse the sensitivity of snow cover simulations and hydrological contribution. The GR4J rainfall-runoff model was calibrated (using global optimization) and applied to simulate the daily discharge and compared with the Distributed Hydrology and Vegetation Model with Glacier Dynamics (DHSVM-GDM) over the 2001-2018 period. Furthermore, the simulated streamflow was evaluated through comparisons with observations at the hydrological stations using Nash–Sutcliffe efficiency and Kling Gupta Efficiency (KGE). The results show that the snow-runoff have increased in recent years, so new water management and planning strategies should be developed in the basin. This research is part of the multidisciplinary collaboration between British and Peruvian scientists (Newton Fund, Newton-Paulet) through RAHU project.