Obtenção da equação de erosividade da chuva em diferentes regiões do Estado do Ceará

Abstract

The rains can have a great capacity to cause soil losses in the places where it is precipitated. One of the main responsible for the process is the erosivity of the rain, which is a capacity of a supplied rain has to cause erosion. The most common method for obtaining erosivity is from rain total data, due to the greater ease of obtaining, although the erosivity forecast is more accurate when using rain intensity data. Countless authors have sought to obtain relationships between the erosivity of rain and the amount of precipitated rain in a given period. Erosion can be obtained through the rain coefficient, which was used for the first time in Brazil by Bertoni and Lombardi Neto (1975) for the city of Campinas - SP, with satisfactory results. The erosivity equation is obtained from the correlation between the average monthly erosivity indices (EI30), which are a function of the intensity and kinetic energy of people, with the rain coefficient, which is informed from the relationship between the volumes of the average monthly and annual rainfall. This work aims to obtain the rain erosivity equation of the cities of Guaramiranga and Jaguaribe, mandatory in the State of Ceará, from rain intensity data and to obtain the rain coefficient that correlates data of total rain with the erosivity index monthly. The results indicated correlation coefficients of 0.991 for Guaramiranga and 0.978 for Jaguaribe in the periods from 2009 to 2018, indicating a good association between the variable EI30 and the rain coefficient. The value of erosivity provided from rain intensity data was very similar to the erosivity found through the professional equations in this work. The formulas suggested for large regions, such as the one proposed by Silva (2001) for much of the Northeast, obtained changing values and classification in relation to erosivity for one of the cities studied in this work, thus demonstrating the importance of using close data of the study region to estimate how to more efficiently form rain erosivity.