Showing 6 results for Flood Frequency
S. Chavoshi, S.s. Eslamian,
Volume 3, Issue 3 (10-1999)
Abstract
Designers of hydraulic structures are often faced with the problem of estimating flood frequencies at stream sites, where little or no flow information is available. A regional regression model is widely used which relates physical and climatological parameters to flow characteristics. In this study, a new method is used which is based on the station-year technique and combined records for several stream-flow gaging stations to make a single composite sample. This method, named ‘hybrid’, was proposed by Hjalmarson and Thomas (1992). It was applied to a group of records from 17 apparently homogeneous stream gaging stations to determine regional flood frequency equations. The study area consists of two adjacent basins, Gavkhoony and North Karoon in the central part of Iran. Using area and mean elevation of the catchments as the most important criteria in relation to peak discharge, the interactive process of the hybrid method was performed, resulting in two-parameter models of regional flood frequency. The performance of the hybrid method was evaluated by comparison with the regional relations determined from a multivariate regression. The comparison revealed that the accuracy of the hybrid method was significantly better than the regression method for low return periods.
S.s. Eslamian, V. Salimi, S. Chavoshi,
Volume 4, Issue 2 (7-2000)
Abstract
Peak discharge is one of the basic parameters in the design of hydraulic structures. There are various methods for peak discharge determination. Regional flood frequency analysis is based on physical, climatological and hydrological characteristics of basins. The objective of this study is to examine different models for the estimation of quantiles for some catchments in western Iran (namely: Gharehsoo, Gamasiab, Kashkan, Seimareh, Sezar and Abshineh) for which only maximum daily mean discharge data exist. In this research, peak and maximum daily mean discharges for 11 stream gauging stations were collected for a 21-year period. The ratio of these two discharges (R) and mean and standard deviations of peak discharges and maximum daily mean discharges were computed. Catchment characteristics including catchment area, catchment perimeter, main channel length, mean elevation, mean slope equivalent rectangle length, circular ratio, Gravelius coefficient, drainage density, time of concentration, relief ratio and diameter of the circle having equal area with the catchment were computed. Linear regression analysis was performed between independent variables of the catchments and mean standard deviation of the parameter “R” to develop a relation. The results of this study can be applied to the estimation of extreme flow values for non-recording stream gauging stations (daily reading sites).
A. Shirzadi, K. Chapi, P. Fathi,
Volume 15, Issue 58 (3-2012)
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. Chavoshi,
Volume 22, Issue 4 (3-2019)
Abstract
Regional flood frequency studies are initialized by the delineation of the homogeneous catchments. This study was based on "Region of Influence" concept, aiming to find the similar catchments in the south of Caspian Sea. The methodology utilized the Particle Swarm Optimization Algorithm, PSO, to optimize the fuzzy system over a dataset of catchment properties. The main catchment variables in relation to flood were determined by the principle component analysis method and employed as the inputs in the fuzzy system. Catchments grouping was performed over these fuzzy input variables by the iterative process. The optimum similar groups were obtained by PSO, and the heterogeneous L-moment index was used as the termination criterion for the optimization process. A total of 61 hydrometric stations located in the study area were selected and their relevant catchments' physical, climatic and hydrologic properties in relation to flood were studied. Principle Component Analysis by Variomax Rotation Factor over the catchments datasets tended to four out of 16 physical variables, including area, mean elevation, Gravelious Factor and Form Factor, as the main parameters in terms of homogeneity with 84 percent of accumulative variance. These variables, as well as mean annual rainfall, were used as the input data to define the fuzzy system. PSO algorithm was then employed to optimize the developed fuzzy system. The developed algorithm tended to yield the best result in the 9th iteration with 26 and 22 for the minimum average and the optimum values of cost function, respectively. The topology of the resulting algorithm included inertia weight, local and acceleration rates, the number of generations and population size, with the values of 0.7298, 1.4962, 1.4962, 10 and 5, respectively. This study tended to a total of 61 regions of influence, proportional to the relevant 61 sites. According to the geographical location of the catchments in the region, it could be concluded that the geographical proximity doesn't necessarily involve homogeneity. The obtained results indicated the efficient potential of PSO-FES in the delineation of the homogenous catchments in the study area.
S. Chavoshi Borujeni, K. Shirani,
Volume 24, Issue 3 (11-2020)
Abstract
Selection of the appropriate distribution function and estimation of its parameters are two fundamental steps in the accurate estimation of flood magnitude. This study relied on the concept of optimization by meta heuristic algorithms to improve the results obtained from the conventional methods of parameter estimation, such as maximum likelihood (ML), moments (MOM) and probability weighted moments (PWM) methods. More specifically, this study aimed to improve flood frequency analysis using the Artificial Bee Colony algorithm (ABC). The overall performance of this algorithm was compared to the conventional methods by employing goodness of fit statistics, correlation coefficient (CC), coefficient of efficiency (CE) and root mean square error (RMSE). The study area, Babolrood catchment located in southern bank of Caspian Sea, has been subjected to annual flooding events. A total of 6 hydrometry stations in the study area were delineated and their data were used in the analysis of 6 distribution functions of Normal, Gumbel, Gamma, Pearson Type 3, General Extreme Value and General Logistic. This analysis indicated that Gamma and Pearson Type 3 were the most appropriate distribution functions for flood appraisal in the study area, according to the ABC and conventional methods, respectively. Also, the results showed that ABC outperformed ML, MOM and PWM; so, Gamma could be recommended as the most reliable distribution function for flood frequency analysis in the study area.
F. Naeimi Hoshmand, F. Ahmadzadeh Kaleybar,
Volume 26, Issue 3 (12-2022)
Abstract
Hydrological models for evaluating and predicting the amount of available water in basins, flood frequency analysis, and developing strategies to deal with destructive floods are expanding daily. In this study, HEC-GeoHMS and Arc Hydro extensions in ArcGIS software and the HEC-HMS model were used to simulate design flood hydrographs in the Aydooghmush basin in the northwest of Iran. SCS-CN, SCS-UH, Maskingham, and monthly fixed methods were used to calculate rainfall losses, rainfall-runoff transformation, flood routing, and base flow, respectively. In model calibration with two real flood events, the average of absolute values of the residuals, the sum of the remaining squares, and the weight of the peak mean the error squares for the flood volume were 2.75, 5.91, and 5.32, respectively and for peak discharge were 8.9, 8.0, and 8.0, respectively. Model validation was evaluated as acceptable with a one percent error rate in the peak of discharge and a 19 percent in the flood volume. For maximum 24-hour precipitation, the log-Pearson type 3 was determined as the most suitable distribution in the SMADA model and design precipitation was extracted in different return periods. Thus, for the return period of 2 to 1000 years, the peak discharge and volume of the design flood were simulated equally to 18.8 to 415.6 m3 s-1 and 5.7 to 87.9 MCM, respectively.
