RESUMO
The strategy of considering a model that is comparable to the Soil Conservation Service Curve-Number (SCS-CN) method that employs land use maps to estimate the effects of land use on the water quality has considerable potential for application. This paper presents the LUPC (Land Use Pollutant Contribution) Model to estimate water pollution from the watershed land use obtained by satellite image classification (Sentinel-2). It defines that each land use produces a specific pollutant load per unit area, called Pollutant Standard Index (PSI), which undergoes degradation and/or retention until it reaches the river. This decay estimate is based on a Kernel Function. Organic matter (OM) was the pollutant chosen for the definition of the LUPC model and fractions of labile and refractory organic matter (LOM, ROM). The model was applied to the Barigüi River basin, and five samples were collected at 12 points along the river. Water quality parameters such as dissolved organic carbon (DOC) and UV-Visible absorbance in addition to chemical and biological oxygen demand (COD and BOD), dissolved oxygen (DO), and nitrogen and phosphorus fractions were the reference for modeling purposes. The results indicate that organic loads can be estimated from watershed characteristics, despite influence from seasonal influences captured by the PSI values and the basin shape parameter. Considering its versatile response, the LUPC model can be used for integrated water resources and land use planning and management and be indicator of the potential pollution of rivers by OM.
Assuntos
Poluentes Ambientais , Poluentes Químicos da Água , Qualidade da Água , Monitoramento Ambiental/métodos , Rios , Poluição da Água/análise , Poluentes Químicos da Água/análise , Fósforo/análiseRESUMO
The increasing advances in technologies used in autonomous vehicles have improved the reliability of their controls, making them more likely to be accepted by drivers and thus more common on the streets. When all vehicles become autonomous, traffic lights will need to be more efficient. In this sense, this article presents a computational model to manage the crossing of autonomous vehicles at road intersections, so that they can flow continuously along the roads without needing to stop, except in extreme cases. Based on the developed model, we implemented an algorithm and a simulator to control the behavior of autonomous vehicles with different lengths when crossing an intersection. In order to evaluate the performance of this method, we carried out 10 thousand simulations for each combination of the intersection controller's distances of action and vehicle group size, in a total of 600 thousand simulations. Thus, a relationship was observed between the method's efficiency and the controller's range, where the number of collisions was zero for distances greater than or equal to 2300 m. Method efficiency was also related to the average speeds at which the vehicles crossed the intersection, which was close to their average initial speed.