Abstract Changes in land use and land cover (LULC) can result in significant changes in a hydrographic basin flow regime. Future projections about LULC and its interference with water availability help to identify extreme events in advance and help propose appropriate management measures. Thus, this study aimed to make the LULC projection for the year 2030 for the Alto Rio Grande (ARG) sub-basin, located in Southeastern Brazil. This region was chosen because of its intense water resources use and for having recently faced water scarcity as result of prolonged droughts and inadequate water resources management. To identify the LULC trend for the year 2030, the Land Change Modeler (LCM) was used, the map obtained was inserted in the Soil and Water Assessment Tool (SWAT) model previously calibrated and validated for the region’ environmental and climatic conditions. The ARG sub-basin was affected by heavy rains in 2011, which resulted in changes in the landscape due to landslides. This particularity of the region contributed to the projection of LULC for the year 2030 to present an increase in forest and pastures to the agricultural areas detriment. When evaluating the impacts of these changes in water availability, it was observed that the SWAT model presented, for the same rainfall conditions, a reduction in peak streamflows of up to 59% and a reduction in the average monthly flow of up to 63% in 2030 in relation to the LULC observed in 2017. Thus, this study provides an important contribution by identifying a considerable reduction in water availability. These results will help to formulate strategies for water resources management and the adoption of measures to promote water security in the region.

Resumen Los cambios en el uso y la cobertura del suelo pueden resultar en cambios significativos en el régimen del flujo de una cuenca hidrográfica. Los estudios predictivos sobre el uso del suelo y su interferencia con la disponibilidad del agua ayudan a identificar eventos extremos con anticipación a fin de proponer medidas de gestión adecuadas. De esta forma, este estudio tuvo como objetivo realizar la predicción del uso del suelo para el año 2030 para la subcuenca del Alto Río Grande (ARG), ubicada en el sureste de Brasil. Esta región fue elegida por el uso intenso de los recursos hídricos y por haber enfrentado, recientemente, escasez de agua como resultado de sequías prolongadas y una gestión inadecuada de los recursos hídricos. Para la predicción del uso del suelo en 2030 se utilizó el Land Change Modeler (LCM), el mapa obtenido se insertó en el modelo Soil and Water Assessment Tool (SWAT) previamente calibrado y validado para las condiciones ambientales y climáticas de la región. La subcuenca ARG fue afectada por fuertes lluvias en 2011 que resultaron en cambios en el paisaje debido a deslizamientos de tierra. Esta particularidad de la región contribuyó para que la predicción del uso del suelo para el año 2030 presente un aumento de bosques y pastos en detrimento de las áreas agrícolas. Al evaluar los impactos de estos cambios en la disponibilidad del agua, se observó que el modelo SWAT presentó, para las mismas condiciones de precipitación, una reducción en los caudales pico de hasta 59% y una reducción en el caudal promedio mensual de hasta 63% en 2030 en relación con el uso del suelo observado en 2017. Es decir, este estudio hace un aporte importante al identificar una reducción considerable en la disponibilidad del agua. Estos resultados ayudarán a formular estrategias para la gestión de los recursos hídricos y la adopción de medidas para promover la seguridad hídrica en la región.

BACKGROUND The outbreak of sylvatic Yellow Fever (SYF) in humans during 2016-2017 in Brazil is one of the greatest in the history of the disease. The occurrence of the disease in areas with low vaccination coverage favoured the dissemination of the disease; therefore, it is necessary to identify the areas vulnerability to the YF virus (YFV) to assist in the adoption of preventive measures. OBJECTIVE To correlate the physical-environmental elements associated with the occurrence of SYF in humans via a multicriteria analysis. METHODS For the multicriteria analysis, preponderant elements related to SYF occurrences, including soil usage and coverage, temperature, precipitation, altitude, mosquito transmitters, and non-human primate occurrence areas, were considered. The results were validated by assessing the correlation between the incidence of SYF and the vulnerable areas identified in the multicriteria analysis. RESULTS Two regions with different vulnerability to the occurrence of the disease were identified in the multicriteria analysis, with emphasis on the southern areas of the state of São Paulo northeast areas of Minas Gerais, and the entire states of Rio de Janeiro and Espírito Santo. The map of SYF vulnerability obtained in the multicriteria analysis coincides with the areas in which cases of the disease have been recorded. The regions that presented the greatest suitability were in fact the municipalities with the highest incidence. MAIN CONCLUSIONS The multicriteria analysis revealed that the elements that were used are suited for and consistent in the prediction of the areas that are vulnerable to SYF. The results obtained indicate the proximity of the areas that are most vulnerable to the disease to densely populated areas where an Aedes aegypti infestation was observed, which confers a high risk of re-urbanisation of YF.