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Evaluating the efficiency of concentration time estimation models in some sub-basins in northwest of Iran

Document Type : Research Paper

Authors

1 Professor at Department of Soil Science, Faculty of Agriculture, University of Zanjan, Zanjan, Iran

2 Ph.D. Graduated, Department of Soil Science, Faculty of Agriculture, University of Zanjan, Zanjan, Iran and Watershed Management Expert in East Azerbaijan Department of Natural Resources and Watershed Management

Abstract

Introduction
The concentration time of catchments is one of the most important and common effective features in hydrological studies, particularly in determining the flow discharge for designing watershed management projects. Most of the catchments in the world especially in Iran were not equipped with hydrometric stations, and project managers are forced to use traditional empirical models to estimate concentration time and peak flow. The review of previous studies shows that experimental models for estimating concentration time have unfavorable results due to the change of environmental conditions outside the place where the model is presented. On the other hand, there is not enough information about the effectiveness of experimental models for estimating concentration time in many catchments in Iran, especially in semi-arid areas. The purpose of this study is to evaluate the accuracy of some experimental models for estimating concentration time in the sub-basins of the semi-arid region of the northwest of the country and to identify its determining factors.
 
Materials and methods
This study was conducted in eight sub-basins including Alanagh, Ordakloo, Shekaralichay, Shiramin, Kurjan, Kalaleh and Livar from Urmia Lake and Araz River basins in Northwest Iran. Meteorological and hydrometric data were obtained from the Natural Resources of East Azerbaijan and stations belonging to the Ministry of Energy. The characteristics of the basin such as area, length, slope, height and shape were determined through field studies and drawing maps in the GIS platform. The concentration time was calculated using the hydrograph of the flows in the statistical period of 30 years (from 1367 to 1397) and it was estimated through six experimental models including Kirpich (1940), Kerby (1959), Chow (1962), Federal Aviation Administration (1972), Bransby-Williams (1980) and Ventura (2007). The relationship between concentration time and catchment characteristics was investigated by correlation matrix, Pearson's method. Nash-Sutcliffe efficiency coefficient, average error and root mean square error were used to evaluate the accuracy of the models.
 
Results and discussion
According to the results, Shekaralichay sub basin has the shortest (66 minutes) and the Kalaleh sub basin has the longest concentration time (132 minutes). Bransby-Williams model had the lowest error (6.8 %) and the highest efficiency coefficient (73%); while the estimation error (36.2 %) and the Nash-Sutcliffe efficiency of Federal Aviation Administration model were 36.2% and-14.4% respectively. The slope was the most important main factor on the estimation of concentration time of the assessment in the Kirpich model (r= 0.83), Chow (r= 0.82) and Bransby-Williams (r= 0.73). Federal Aviation Administration model (1972) and Ventura model (2007) have a weak estimate in sub-basins with low slope and length.
 
Conclusions
The results showed that among the physical characteristics of the basin, the area, slope and length of the sub-basin play a more important role in changes in concentration time. This study showed that the slope percentage of the basin is the most important factor in reducing concentration time, peak discharge and increasing the speed of flooding in the studied sub-basins, so it is suggested to use soil protection plans in order to increase the concentration time for sub-basins that have a higher slope percentage. The evaluation of concentration time estimation models in eight catchments showed that the Bransby-Williams (1980) model with an average error of 6.80% and Nash-Sutcliffe efficiency coefficient of 73% provides the best estimation among others, so the use of this model in similar basins which do not have measuring stations, it is suggested.

Keywords

References
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Watershed Engineering and Management
Volume 16, Issue 3
September 2024
Pages 432-449
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