Modelar redes de recogida de aguas pluviales con enfoques determinísticos y estocásticos del sector Las Pitas de la ciudad de Loja

Abstract

Abstract: Understanding the behavior of a time series is essential, if what we want is to mathematically predict a phenomenon. This research focuses on the Box-Jenkins methodology applied to Integrated Autoregressive Moving Average Models (ARIMA), the same that are iterative mathematical processes. For the development of the research, a period of 5 years has been selected, starting in January 2012 until December 2017, the data correspond to the monthly precipitation of the Meteorological Station M0033 "La Algeria". The Meteorological Station M0033 "La Algeria" is in an operational state and collects hourly information on the relative humidity of the air, precipitation, atmospheric pressure, air temperature, orientation and wind speed. To carry out the modeling, it is decided to develop a computer tool using Python 2.7 to streamline the calculations that determine the forecast function. The same that will be selected through various analysis tests, residual correlograms, mean square error and correlation coefficient. Finally, it is going to be predicted for a period after the series of precipitation obtained, that is, for 1 year.