Abstract

In areas with scarce water resources, it is so important to analyze the connection between the different elements of a river basin and the water collected by the basin’s reservoir, to determine and predict the spatial and temporal variability of water on it. In this paper, we use the basic principles of hydrological modelling to develop a model for the exploitation of rainfall in reservoir basins in the province of Malaga, Spain. The monthly water input data of the seven reservoirs in the province of Malaga, provided by the Hidrosur Network of the Automatic Hydrological Information System (SAIH), as well as the precipitation and daily temperature of the stations of the State Meteorological Agency (AEMET) associated with the basins of each of these reservoirs were used. We assume that the entrance to a reservoir in a given month must depend on the precipitation produced in its watershed (both the amount of rain and the intensity with which it fell), the precipitation collected from the previous months (and the way in which it was produced) and the evapotranspiration produced during that period. For each reservoir, we propose a model with nine parameters to simulate the arrival of rainfall to the reservoir, covering aspects from the amount and intensity of rain, past and present, to the level of evapotranspiration on a given area for a given date. These nine parameters are optimally adjusted through an artificial intelligence algorithm to maximize the correlation between real and simulated contributions. The results show how this model, adjusted for each reservoir, will let us predict how changes in the rainfall and temperature patterns, predicted, for example, by the IPCC models, will affect the future water levels at the studied reservoirs.

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