ABSTRACT The estimation of evapotranspiration (ET) and crop water requirements are crucial for the proper management and allocation of water resources in terms of quantity, quality, and timeliness. Therefore, remote sensing estimation of ET using the SEBAL algorithm (Surface Energy Balance Algorithm for Land) can provide spatio-temporal, non-punctual data, unlike traditional calculations relying on the nearest meteorological station. This research analyzed ET using SEBAL, based on ten Landsat 8 satellite images processed with a program developed in the Model Builder of ArcGis® version 10.2. The analysis was conducted during the vegetative period of starchy corn from May to October 2016. Validation of the results happened with a drainage lysimeter installed in a monitoring plot. Additionally, the statistical indices - such as percentage relative error (PRE) (0,09), root mean square error (RMSE) (0,30), R2 (0,92), and Nash-Sutcliffe efficiency (NASH) (0,91) - indicated a good correlation of ET for starchy corn in the central highlands of Peru. The ET identified at ten monitoring points ranged from 1,05 to 7,79 mm d-1. (ET quantity quality timeliness Therefore Surface Land spatiotemporal, spatiotemporal spatio temporal, temporal spatio-temporal nonpunctual non punctual data station ArcGis 102 10 2 10.2 2016 plot Additionally PRE (PRE 0,09, 009 0,09 , 0 09 (0,09) RMSE (RMSE 0,30, 030 0,30 30 (0,30) R 0,92, 092 0,92 92 (0,92) NashSutcliffe Nash Sutcliffe NASH (NASH 0,91 091 91 (0,91 Peru 105 1 05 1,0 779 7 79 7,7 d1. d1 d 1. d-1 10. 201 00 0,0 (0,09 03 0,3 3 (0,30 0,9 9 (0,92 (0,9 1, 77 7, d- 20 0, (0,0 (0,3 (0, (0 (

Resumo A presente pesquisa avaliou a distribuição espacial do risco de seca na bacia hidrográfica do lago Titicaca localizada em território peruano para uma escala de distrito, com base em perigo e vulnerabilidade. O perigo foi quantificado com o déficit de precipitação usando índice de Precipitação Padronizado (SPI, por suas siglas em inglês), para uma escala de tempo de três meses; e a vulnerabilidade foi obtida de acordo com os indicadores socioeconômicas e físicas da bacia. Os resultados mostram que a seca é fortemente modulada por condições anômalas de TSM dos oceanos circundantes, principalmente pela região do Pacífico. Na Bacia do Lago Titicaca, foi identificado que aproximadamente 50% dos distritos apresentam alto a muito alto risco de seca, localizados principalmente no Noroeste, centro-leste, e centro-sul da bacia. Esses distritos apresentam um maior déficit de precipitação e apresentam indicadores mais vulneráveis ao perigo de seca devido ao facto de depender economicamente de uma agricultura de sequeiro precária e de um sistema de pecuária extensiva e mista. Nesta área estão as províncias mais importantes da região alto-andino, como Puno, San Roman, Azángaro, Melgar e Carabaya, e destacam-se distritos como Puno e Juliaca considerado o capital econômico do departamento de Puno.

Abstract The present research has assessed the spatial distribution of drought risk in the Titicaca Lake Basin located in Peruvian territory for a district scale, based on hazard and vulnerability. Drought hazard has been quantified with the deficit of precipitation using the Standardized Precipitation Index (SPI) for a time scale of 3-months, and the vulnerability has been obtained according to the socio-economic and physical indicators of the Basin. The results show that the drought is strongly modulated by anomalous SST conditions of the surrounding Oceans, mainly by the Pacific region. Over the Titicaca Lake Basin was identified that about 50% of districts present a high to very high risk of drought mainly, in the northwestern, central-east, and central-south of the Basin. These districts have a larger deficit of precipitation and showed indicators that are more vulnerable to the drought hazard due to that economically depends on precarious rainfed agriculture and an extensive and mixed livestock system. Within this area are the most important provinces of the high-Andean region, such as Puno, San Roman, Azángaro, Melgar, and Carabaya, and outstanding districts as Puno and Juliaca, considered the economic capital of the department of Puno.

This research evaluated climate change impacts on the streamflow offer in the middle and up-per Piura river basin in Peru using the Soil and Water Assessment Tool (SWAT) by the middle of the 21s century. The SWAT model was calibrated and validated for a period of 23 years (1986 - 2008) with daily weather data at six locations and monthly streamflow data at one location. For future evaluation, the HADGEM2- ES and CSIRO-Mk3-6-0, global climate models (GCM), climate data by Coupled Model Intercomparison Project Phase 5 (CMIP5) RCP4.5 and RCP8.5 of the Intergovernmental Panel on Climate Change (IPCC) were adopted. The future biased data (2025‐2054) were corrected using weather data of baseline period, and downscaled by the statistical method of MarkSim weather generator. The temperature and precipitation in the climate change scenarios projected an average increase of + 2.9°C and 39.3%, respectively, compared to the baseline condition. The future evapotranspiration showed a general tendency to decrease, with a slight increase in the north western region of the basin. In particular, the average trend of monthly streamflow to 2050s, in the four scenarios, indicates an increase of +71.8%, approx. 55.9 m³/s, from October to April with the highest increase in November. Whereas, from May to September, there is a decrease of -66.1%, approx. 12 m³/s, with the largest decrease in July

Esta investigación evaluó los impactos del cambio climático en la oferta hídrica superficial en la subcuenca media y alta del río Piura, Perú, con el modelo hidrológico Soil and Water Assessment Tool (SWAT) a mediados del siglo XXI. El modelo SWAT fue calibrado y validado para un periodo de 23 años (1986 - 2008) utilizando datos de clima diarios en seis ubicaciones, y caudales mensuales en una ubicación. Para las evaluaciones a futuro, se adoptaron los datos climáticos HADGEM2-ES y CSI-RO-Mk3-6-0, de los modelos climáticos globales (MCG), Coupled Model Intercomparison Project Phase 5 (CMIP5), en los escenarios RCP4.5 y RCP8.5. Los datos sesgados futuros (2025‐2054) se corrigieron utilizando los datos del clima del período de referencia, y se redujeron de escala con el generador de clima MarkSim. La temperatura y precipitación en los escenarios de cambio climático proyectan un aumento promedio de + 2,9°C y 39,3%, respectivamente, respecto del periodo observado. La evapotranspiración futura mostro una tendencia general a disminuir, con un ligero aumento en el lado noroccidental de la cuenca. En particular, la tendencia promedio de la escorrentía mensual al 2050, en los cuatro escenarios, indica para los meses entre octubre a abril un aumento de + 71,8%, aprox. 55,9 m³/s; con el mayor incremento en noviembre. Por otro lado, entre los meses de mayo a setiembre, se tiene una disminución de ‐66,1%, aprox. 12 m³/s, con el mayor descenso en julio