Ramtin Sobhkhiz Foumani; Alireza Mardookhpour; Mohammadreza Fallah Ghavidel
Abstract
Extended abstractIntroductionToday, the estimation of the rainfall resulting from rainfall, especially in small basins with no statistics, is one of the main activities among hydrologists, and the estimation of the volume of runoff resulting from rainfall and the application of surface water collection ...
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Extended abstractIntroductionToday, the estimation of the rainfall resulting from rainfall, especially in small basins with no statistics, is one of the main activities among hydrologists, and the estimation of the volume of runoff resulting from rainfall and the application of surface water collection and containment methods, both in terms of water supply And it is very important in terms of flood prevention. In this research, by using the simulation of the conversion of rainfall to floods in a long statistical period of about 20 years between January 23, 2000 and September 23, 2021 in the Astana-Kochsafhan catchment area with HEC-HMS software, one of the main objectives of the selection effect The type of flow conversion hydrographs was checked on the amount of calculation error of the closed boundary flood. The main goal of this research was to investigate the importance of the dimensionless Muskingum coefficients in developing a flood distribution model in a computer simulator. Materials and methodsFor do this research, two types of models were used in extracting the flow hydrograph. The first model continued by using the integration of the general set of sub-basins until the stage where only 5 general sub-basins or 4 sub-basins in the upstream of the catchment area leading to the outlet of the range continued. The process of removing the sub-basins was done by combining the area and other physiographic parameters in the geographic information system environment and using the HEC_GeoHMS extension. Results and discussionIn addition to the principle of trending, by analyzing the results, it was found that each of the surface current conversion methods under known and more widely used titles have limitations, weaknesses and strengths that can be The title of local regressions was also considered for this transformation, the SCS method as the most well-known method, due to its lower limitation in models with local conventional scale in the limits of third-order watersheds, showed that the error of the obtained data It has been less than other cases. This amount of error was predictable in itself. Clark's method, which has a more structured approach, like Schneider's calculation method, calculates the error in its general form, as well as in the maximum values, moment of occurrence, volume, etc. slow In particular, Schneider's method is designed for large domains in its default. In this study, unlike the SCS method, in which the Nash function error number is 0.540 and the RMSE is 0.7, as well as the deviation percentage is 28.01, for the Clark method, the Nash function is 533. 0 and RMSE is 0.7 and the deviation percentage is 29.71. This calculation also confirms from the point of view of error measurement that one of the best criteria for observing the difference cannot be RMSE. In the model The detailed analysis of the trending effect, the error of 0.537 in the Nash function is very close to the figure calculated in the similar case (initial aggregated model). However, only this error measurement should not lead to the opinion that the creation of more detailed models cannot improve or destroy the structure of its numerical code. Because although the differences in measurement errors can be ignored in a certain way, the total amount of flow in the aggregated model was equal to 19672395 cubic meters. While the same parameter in the partial model has a difference of 277655 cubic meters. ConclusionIn general, separation of basic discharge with advanced methods such as WHAT cannot necessarily help to increase the correlation between observational data in a continuous model. On the other hand, calculating the discharges that leave the hydrographic network under the heading of deviation from the hydrographic network in the process of flood flows is the basic condition for reducing the model error, regardless of the type of hydrograph selected in the model.
