Fatemeh Mehrpourbernety1 
, Ramin Fazloula *1 , Alireza Emadi1 , Nasrollah Javaheri2 , Mohammad ali Gholami Sefid Kouhi1
, Ramin Fazloula *1 , Alireza Emadi1 , Nasrollah Javaheri2 , Mohammad ali Gholami Sefid Kouhi1
1- Sari Agricultural Sciences and Natural Resources University
2- Omran Pardisan Water Consulting Company
2- Omran Pardisan Water Consulting Company
Abstract: (602 Views)
Introduction and Objectives: Floods are caused due to several reasons including rainfall intensity, vegetation destruction, and encroachment of rivers. The high power of floods damage the buildings, bridges, and existing structures, and also, reduce the capacity of the river bed. Also, the excessive volume of water leads to human and financial losses and the destruction of animal habitats. To deal with a flood and its damages, structural measures such as dam construction and non-structural measures such as increase in vegetation coverage, forecasting and flood warning systems are carried out. Flood forecasting is the process of estimating the time and place of flood occurrence and the volume of water and, as an efficient and low-cost tool of flood management and damage reduction, has received a lot of attention in recent years. Rainfall-runoff modeling is one of the measures of flood management. In order to understand the relationship between rainfall and runoff parameters, as well as to determine the peak discharge value and the time to reach the peak discharge, simulation is done using hydrological models. One of the hydrological software packages in this field is the HEC-HMS software. By considering three components of the basin, meteorological, and control specification models, the value of losses, runoff, base flow and routing are calculated using existing methods, and finally, optimization is performed to reduce the difference between observed and simulated hydrographs. Precipitation is one of the most important input parameters in simulating floods. Therefore, the correct estimation of its amount is considered necessary and important. Considering the number of rain gauge stations and the lack of sufficient stations in the country, especially in mountainous areas, the use of numerical weather prediction model information and satellite rainfall data plays an important role in flood forecasting. Numerical weather prediction models predict weather conditions with the help of mathematical models. Forecasts are divided into three short-range, medium-range, and long-range categories, and also, into regional and global models. One of these models is the numerical weather prediction model, called GFS, which predicts and provides data such as temperature, wind, and precipitation. Heavy rainfall, destruction of forests, sand and gravel harvesting and construction in floodplains are among the causes of floods in Mazandaran province and especially Tajan river in recent years. The main goal of this research was to estimate the value of peak discharge by simulating flood events and evaluating the results using the precipitation information of GFS model in Tajan watershed located in Sari city in Mazandaran province.
Materials and Methods: In this research, the data were collected from the hydrometric stations of the Tajan watershed, including the hourly measurements of recorded floods, as well as the information required by the evaporation and rain gauge stations in this area, including precipitation obtained by Mazandaran Regional Water Company for 10-year period of 2011-2021. Also, precipitation data were received online (from the following webpage: https://openweathermap.org) through the output of GFS numerical weather prediction model in the mentioned period. By using land use and soil hydrological group layers in ArcGIS software, the curve number of each subbasin was determined and the physiographic characteristics of Tajan watershed were extracted using HEC-GeoHMS extension. Then, four events 04October2011, 01December2011, 14November2016, and 01December2017 were simulated using the physiographic characteristics of the sub-basins, the precipitation data of the Tajan watershed, and the flood discharge of obtained by Mazandaran Regional Water Company in HEC-HMS software. Soil Conservation Service curve number method was used to calculate losses, SCS unit hydrograph method was used to calculate runoff method, and lag method was used for routing. Subsequently, to determine the sensitivity of curve number, lag time, and initial abstraction parameters, sensitivity analysis was performed. In order to determine the optimal values of the parameters in optimization process, 9 objective functions available in the HEC-HMS software including Mean of Absolute Residuals, Mean of Squared Residuals, Peak-Weighted Root Mean Square Error, Peak-Weighted Variable Power, Percent Error in Peak Discharge, Root Mean Square Error, Sum of Absolute Residuals, Sum of Squared Residuals and Time-Weighted RMSE were used. In the next step, validation has been performed by (event 01December2017) using the optimal values of the parameters. Finally, after HEC-HMS software optimization and verification, by using the data of the GFS numerical weather prediction model, the aforementioned flood events were simulated.
Results: The results showed a strong correlation between observed and calibrated hydrographs. Also, the best objective function was peak-weighted variable power. The results of the sensitivity analysis showed that the peak discharge is more sensitive to the changes in the initial abstraction and curve number parameters. To verify the validity of the results obtained in the calibration process, validation was performed and, the results indicated that there was no significant difference between the averages of two groups of observed and calibrated flow rates. Also, the simulation results using GFS numerical weather prediction model showed that there is no significant difference (at a 95% confidence level) between the observed and simulated hydrographs.
Conclusion: According to the results, by using the precipitation data of the GFS numerical weather prediction model and the HEC-HMS rainfall-runoff software, it is possible to simulate the flood with acceptable confidence in predicting the peak discharge of flood.
Materials and Methods: In this research, the data were collected from the hydrometric stations of the Tajan watershed, including the hourly measurements of recorded floods, as well as the information required by the evaporation and rain gauge stations in this area, including precipitation obtained by Mazandaran Regional Water Company for 10-year period of 2011-2021. Also, precipitation data were received online (from the following webpage: https://openweathermap.org) through the output of GFS numerical weather prediction model in the mentioned period. By using land use and soil hydrological group layers in ArcGIS software, the curve number of each subbasin was determined and the physiographic characteristics of Tajan watershed were extracted using HEC-GeoHMS extension. Then, four events 04October2011, 01December2011, 14November2016, and 01December2017 were simulated using the physiographic characteristics of the sub-basins, the precipitation data of the Tajan watershed, and the flood discharge of obtained by Mazandaran Regional Water Company in HEC-HMS software. Soil Conservation Service curve number method was used to calculate losses, SCS unit hydrograph method was used to calculate runoff method, and lag method was used for routing. Subsequently, to determine the sensitivity of curve number, lag time, and initial abstraction parameters, sensitivity analysis was performed. In order to determine the optimal values of the parameters in optimization process, 9 objective functions available in the HEC-HMS software including Mean of Absolute Residuals, Mean of Squared Residuals, Peak-Weighted Root Mean Square Error, Peak-Weighted Variable Power, Percent Error in Peak Discharge, Root Mean Square Error, Sum of Absolute Residuals, Sum of Squared Residuals and Time-Weighted RMSE were used. In the next step, validation has been performed by (event 01December2017) using the optimal values of the parameters. Finally, after HEC-HMS software optimization and verification, by using the data of the GFS numerical weather prediction model, the aforementioned flood events were simulated.
Results: The results showed a strong correlation between observed and calibrated hydrographs. Also, the best objective function was peak-weighted variable power. The results of the sensitivity analysis showed that the peak discharge is more sensitive to the changes in the initial abstraction and curve number parameters. To verify the validity of the results obtained in the calibration process, validation was performed and, the results indicated that there was no significant difference between the averages of two groups of observed and calibrated flow rates. Also, the simulation results using GFS numerical weather prediction model showed that there is no significant difference (at a 95% confidence level) between the observed and simulated hydrographs.
Conclusion: According to the results, by using the precipitation data of the GFS numerical weather prediction model and the HEC-HMS rainfall-runoff software, it is possible to simulate the flood with acceptable confidence in predicting the peak discharge of flood.
Keywords: Sensitivity analysis, Peak discharge, Modeling, Numerical weather prediction model, HEC-GeoHMS.
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