Mohammad Javad Amiri; Hamid Jourkesh; Ahmad Nohegar
Abstract
Introduction: Flood is caused by a sudden increase in the water level of a river due to heavy rainfall, in which excess water flows out of the basin and the riverbed and enters adjacent areas, causing extensive damage to the region's ecosystems and infrastructure. In order to determine and implement ...
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Introduction: Flood is caused by a sudden increase in the water level of a river due to heavy rainfall, in which excess water flows out of the basin and the riverbed and enters adjacent areas, causing extensive damage to the region's ecosystems and infrastructure. In order to determine and implement a strategic plan in the direction of crisis management, understanding the mechanism and development of the flood phenomenon and the amount of runoff created as a result is a priority.Material and methods: In this study, three events of flood on 16 February 2017, 26 March, 2019 and 23 January 2020, when the average rainfall in the Shiraz watershed was 100 mm every three days, were selected and interacted with a synoptic approach. Atmospheric conditions and flood patterns were identified. Next, using by HEC-HMS hydrological model, the amount of rainfall to runoff conversion in each of the sub-basins in the Shiraz watershed was simulated.Results and discussion: The results showed that the maximum precipitation occurs in February and the minimum in July. The maximum annual rainfall is 627 mm in the mountainous areas of Qalat and Golestan and the minimum is 245 mm in Maharloo lake. Synoptic results showed that the establishment of low altitude and cold-water trough at the level of 500 hPa in the eastern Mediterranean along with the establishment of dynamic low pressure system in Iran caused surface air instability in Fars province and by injecting moisture from the Persian Gulf to the massif. The weather has caused floods in Shiraz. The results of rainfall-runoff modeling showed that the highest runoff in Sadra and Qalat sub-basins were 5773 and 5076 thousand m3, respectively, and the maximum peak discharge in Sadra and Qalat was 666 and 389 m3/sec, respectively. It happened at 17:00. The highest volume of rainfall penetration in Qalat and Chenar Rahdar was 5423 and 2546 thousand cubic meters, respectively, and the lowest level of penetration in the Quran Gate was 247 thousand m3, the main reason being the high density of residential-commercial use in this sub-basin.Conclusion: Therefore, it is suggested that in order to manage the flood crisis in Shiraz, controlling runoff produced in northern sub-basins such as Qalat, Golestan and Sadra and increasing the level of permeability can be effective in controlling floods.
Afshin Honarbakhsh; Seyed Javad Sadatinejad; Moslem Heydari; Mohamadreza Mozdianfard
Volume 9, Issue 1 , October 2011
Abstract
Lag time is a parameter that appears often in theoretical and conceptual models associated with river basin. The river basin lag time is an important factor in linear modeling of river basin response. Generally, all hydrologic analyses require at least one of the time parameters of river basin and, in ...
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Lag time is a parameter that appears often in theoretical and conceptual models associated with river basin. The river basin lag time is an important factor in linear modeling of river basin response. Generally, all hydrologic analyses require at least one of the time parameters of river basin and, in the majority of cases, time of concentration or lag time are used. In this research, storm data from 6 stations in the North Karoon river basin (in Iran) were analyzed. From this analysis, 23 events were selected. Then, in one experimental sub-basin located in this river basin, the lag time was calculated using field method. In this method, performed in the Darehbeed-Samsami study area, lag time was computed from a hydrograph generated by discharge measurement of a triangular scaled spillway. After that, 23 events were divided into two groups, including, one for a newly developed empirical model (70 percent) and another for validation of this model (30 percent). The results obtained from this research based on coefficient of determination (R2), root mean square error (RMSE) and relative error (%RE) statistical measures showed that the agreement between the computed(from new empirical model) and measured data is good.
