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Showing 3 results for Flood Frequency Analysis
The Estimating of Synthetic Unit Hydrograph Using Regional Flood Analysis and Geomorphologic Parameters (Case Study: Kanisavaran and Marenj Watersheds, Kurdistan)
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.
A Hybrid Fuzzy- PSO Algorithm for Catchment Regionalization in Relation to Flood Occurrence
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.

Simulation of Design Flood Hydrographs in Aydooghmush Basin with HEC-HMS Model
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.

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