Roya Jafari; Mohsen Hosseinalizadeh; Hasan Rezaii Moghadam
Abstract
Accurate estimation of a watershed response to rainfall events plays an important role in its soil and water resources management as well as civil works design within watersheds and over or around its downstream rivers. Nowadays, due to improvement in our knowledge and understanding from watershed systems ...
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Accurate estimation of a watershed response to rainfall events plays an important role in its soil and water resources management as well as civil works design within watersheds and over or around its downstream rivers. Nowadays, due to improvement in our knowledge and understanding from watershed systems and enhancement in hardware and software technology as well as facilitation in learning and application of these technologies, researchers prefer to design and apply their required models themselves according to their aims and availability of data. The aim of this research is to develop a spatio- temporally distributed model within PCRaster GIS and programming environment to achieve a better representation of watershed processes at a small scale agricultural micro-watershed. In this study, based on the available local data, an event based rainfall – runoff hydrological simulation model was developed within PCRaster GIS and programming software and its performance was evaluated using observed data from a 27.6 ha agricultural micro-watershed discharging to the Shahrak – Behzisti residential area in the Gorgan city. This is a tightly coupled GIS model. During the research period, only two rainfall events leading to runoff generation occurred on 2/11/2014 and 16/9/2015 which were, respectively, used for calibration and validation of the model. Statistical comparison of the simulated and observed hydrographs of the rainfall - runoff events on 2/11/2014 and 16/9/2015 showed the correlation coefficients of of 0.69 and 0.65 and Nash-Sutcliffe criteria of 0.5 and 0.51, respectively. The results indicate that the developed model has a good performance at simulating rainfall-runoff processes during events.
