Analysis of Gamasyab River Flood by Multi-Regression Method

Estimating flood hit areas with limited or no statistical significant issues in the design of water structures and water resources management is a very important topic especially in arid and semi-arid areas. The aim of this study is to estimate the maximum river flood forecasting Gamasiab occurrence based on the environmental factors influencing the occurrence of floods. For this purpose, two simple logarithmic regression methods are used. First, the environment River catchment Gamasiab of GIS software and each sub-watershed were identified. Then the necessary layers, called effective layers, were determined.  These layers are geomorphological, geological, land use, drainage density layer and climatic data for each basin and sub-basin Gamasiab that were extracted separately. Using dominant distribution log normal 3 parameters for each basin floods with return periods of 2, 5, 10, 20, 25, 50, 75 and 100 years were calculated, then the amount of discharge with different return periods at stations above and the factors influencing flood above them, using simple and multiple regression using log and forward, backward and forward, backward and step-relationship models were presented. The results showed that the most important factor is the area of ​​the peak discharge of a flood area in which there is a significant relationship between the level of 0/99. Moreover, the basin area, drainage density, and average annual rainfall have the highest effect on flood respectively.