Showing 2 results for P. Fathi
A. Shirzadi, K. Chapi, P. Fathi,
Volume 15, Issue 58 (winter 2012)
Abstract
Estimation of flood hydrograph is of necessities in hydrological studies such as flood mitigation projects. This estimation in un-gauged watersheds is usually taken place using geomorphological characteristics of watersheds. The objective of this research is to estimate synthetic unit hydrograph using regional flood frequency analysis and geomorphological parameters of watersheds. 1-hour and 2-hour hydrographs of two watersheds, Kanisavaran and Maranj Watersheds, were generated using maximum discharge data based on regional flood frequency analysis. Estimated hydrographs were compared with observed data and the efficiency of the model was evaluated using Nash-Sutcliffe coefficient, absolute and bias errors. The results showed that multiple regression models give more acceptable results among others for the computation of synthetic unit hydrograph (higher coefficient of determination). The Nash-Sutcliffe coefficient was 0.98 for 1-hour hydrograph while it was 0.93 for the 2-hour hydrograph. The absolute error in 1-hour hydrograph and 2-hour hydrograph was 0.13 and 1.2, respectively. The bias error was close to zero for both hydrographs, indicating that the proposed model is efficient. The model may be used for estimation of synthetic unit hydrograph in similar un-gauged watersheds.
S. Azizpour, P. Fathi, K. Nobakht-Vakili,
Volume 16, Issue 60 (Summer 2012)
Abstract
Soil saturated hydraulic conductivity (k) and effective porosity (f) are the most important parameters to simulate the processes associated with irrigation, drainage, hydrology, leaching and other agricultural and hydrological processes. Present methods to measure these parameters are often difficult, time consuming and costly. Therefore, a method which provides more accurate estimates of these parameters is essential and is considered inevitable. The purpose of this study was simultaneous estimation of k and f using approach inverse problem. In this study, analytical drainage model of Glover-Dam was used to simulate the inverse problem method. Also, genetic algorithm was used as an optimization technique for determination of optimal values of k and f. In order to measure the data required for calibration and evaluation of the proposed inverse problem model, a physical model was designed and constructed in the laboratory. The results showed that the proposed method is good for simultaneosly estimating simultaneous soil k and f. Also with variable f assumption, the prediction error of water table around the drainage was reduced significantly.
