Investigation of rainfall temporal distribution patterns
Samira Sadri, Elham Shayegh, Hedieh Ahmadpari, Sahar Binesh
Precipitation is one of the important elements of climate and is one of the factors affecting the hydrological cycle. The amount of rainfall per unit of time is called the intensity of precipitation. During the rainfall, the intensity of precipitation is not constant and varies with time. Consideration of the persistence of precipitation in the temporal pattern depends on the physiographic characteristics of the basin and especially the reaction time of the system to rainfall. Further design of engineering facilities requires a comprehensive understanding of the extent of atmospheric precipitation moreover temporal distribution. The application of temporal distribution patterns of precipitation increases the accuracy of hydrological simulation of watersheds. One of the most important factors in preparing and developing a hydrological model of watersheds is understanding the temporal distribution of precipitation. Construction of dams and water installations requires extensive hydrological studies to develop water and soil designs and to supply potable and agricultural water. Some of these studies are for estimating and predicting floods and sediments that are that are very importance in reservoir design and dam overflow. One possible way to estimate a design flood in a basin is to use rainfall statistics in design rain selection. Design rain is characterized by several features such as: total amount of rain, total persistence, time distribution of rain, introduced and characterized. The temporal distribution pattern of precipitation, which is actually how the intensity of precipitation changes during rainfall, has a direct impact on the volume and flow rate of the flood peak and sediment volume. Numerous methods have been used in the temporal distribution of precipitation, including the methods of non-dimensional, triangular, intensity-duration-frequency, pilgrim, statistical distributions, SCS type and Huff models.