Volume 16, Issue 1 (3-2026)
J Watershed Manage Res 2026, 16(1): 59-70 |
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Mehrpourbernety F, Fazloula R, Emadi A, Javaheri N, Gholami Sefidkouh M A. (2026). Flood Forecasting of the Tajan Watershed Using the Output of the Numerical Weather Prediction Model (GFS) and the HEC-HMS Hydrological Model. J Watershed Manage Res. 16(1), 59-70. doi:10.61882/jwmr.2024.1279
URL: http://jwmr.sanru.ac.ir/article-1-1279-en.html
URL: http://jwmr.sanru.ac.ir/article-1-1279-en.html
Fatemeh Mehrpourbernety1, Ramin Fazloula *1 
, Alireza Emadi1, Nasrollah Javaheri2, Mohammad Ali Gholami Sefidkouh1
, Alireza Emadi1, Nasrollah Javaheri2, Mohammad Ali Gholami Sefidkouh1
1- Department of Water Engineering, Sari Agricultural Sciences and Natural Resources University, Sari, Iran
2- Chief Executive Officer (CEO) of the AOP Engineering Consulting Company, Tehran, Iran
2- Chief Executive Officer (CEO) of the AOP Engineering Consulting Company, Tehran, Iran
Abstract: (990 Views)
Extended Abstract
Background: Floods are caused by several reasons, including rainfall intensity, vegetation destruction, and encroachment of rivers. The high power of floods damages buildings, bridges, and existing structures, and also reduces the capacity of the river bed. Moreover, the excessive volume of water leads to human and financial losses and the destruction of animal habitats. Structural measures (such as dam construction) and non-structural measures (such as increased vegetation coverage, forecasting, and flood warning systems) are carried out to deal with a flood and its damage. 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 for 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. Simulation is done using hydrological models 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. 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 Iran, 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 using 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, especially the 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 the GFS model in the Tajan watershed located in Sari City, Mazandaran Province.
Methods: In this research, 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 the Mazandaran Regional Water Company for the 10-year period of 2011-2021. Furthermore, precipitation data were received online (from the following webpage: https://openweathermap.org) through the output of the GFS numerical weather prediction model in the mentioned period. The curve number of each subbasin was determined using land use and soil hydrological group layers in ArcGIS software, and the physiographic characteristics of the Tajan watershed were extracted using the HEC-GeoHMS extension. Then, four events 04 October 2011, 01 December 2011, 14 November 2016, and 01 December 2017 were simulated using the physiographic characteristics of the sub-basins, the precipitation data of the Tajan watershed, and the flood discharge obtained by the Mazandaran Regional Water Company in HEC-HMS software. The Soil Conservation Service curve number method was used to calculate losses, the SCS unit hydrograph method was used to calculate the runoff method, and the lag method was used for routing. Subsequently, sensitivity analysis was performed to determine the sensitivity of the curve number, lag time, and initial abstraction parameters. The optimal values of the parameters in the optimization process were determined using nine 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. In the next step, validation was performed by event 01 December 2017 using the optimal values of the parameters. Finally, after HEC-HMS software optimization and verification, the aforementioned flood events were simulated using the data of the GFS numerical weather prediction model.
Results: The results showed a strong correlation between observed and calibrated hydrographs. Besides, the best objective function was peak-weighted variable power. The results of the sensitivity analysis showed that the peak discharge was more sensitive to the changes in the initial abstraction and curve number parameters. Validation was performed to verify the validity of the results obtained in the calibration process, and the results indicated no significant differences between the averages of the two groups, viz. observed and calibrated flow rates. Moreover, the simulation results using the GFS numerical weather prediction model showed no significant differences (at a 95% confidence level) between the observed and simulated hydrographs.
Conclusion: According to the results, using the precipitation data of the GFS numerical weather prediction model and the HEC-HMS rainfall-runoff software makes it possible to simulate the flood with acceptable confidence in predicting the peak discharge of floods.
Background: Floods are caused by several reasons, including rainfall intensity, vegetation destruction, and encroachment of rivers. The high power of floods damages buildings, bridges, and existing structures, and also reduces the capacity of the river bed. Moreover, the excessive volume of water leads to human and financial losses and the destruction of animal habitats. Structural measures (such as dam construction) and non-structural measures (such as increased vegetation coverage, forecasting, and flood warning systems) are carried out to deal with a flood and its damage. 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 for 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. Simulation is done using hydrological models 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. 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 Iran, 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 using 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, especially the 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 the GFS model in the Tajan watershed located in Sari City, Mazandaran Province.
Methods: In this research, 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 the Mazandaran Regional Water Company for the 10-year period of 2011-2021. Furthermore, precipitation data were received online (from the following webpage: https://openweathermap.org) through the output of the GFS numerical weather prediction model in the mentioned period. The curve number of each subbasin was determined using land use and soil hydrological group layers in ArcGIS software, and the physiographic characteristics of the Tajan watershed were extracted using the HEC-GeoHMS extension. Then, four events 04 October 2011, 01 December 2011, 14 November 2016, and 01 December 2017 were simulated using the physiographic characteristics of the sub-basins, the precipitation data of the Tajan watershed, and the flood discharge obtained by the Mazandaran Regional Water Company in HEC-HMS software. The Soil Conservation Service curve number method was used to calculate losses, the SCS unit hydrograph method was used to calculate the runoff method, and the lag method was used for routing. Subsequently, sensitivity analysis was performed to determine the sensitivity of the curve number, lag time, and initial abstraction parameters. The optimal values of the parameters in the optimization process were determined using nine 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. In the next step, validation was performed by event 01 December 2017 using the optimal values of the parameters. Finally, after HEC-HMS software optimization and verification, the aforementioned flood events were simulated using the data of the GFS numerical weather prediction model.
Results: The results showed a strong correlation between observed and calibrated hydrographs. Besides, the best objective function was peak-weighted variable power. The results of the sensitivity analysis showed that the peak discharge was more sensitive to the changes in the initial abstraction and curve number parameters. Validation was performed to verify the validity of the results obtained in the calibration process, and the results indicated no significant differences between the averages of the two groups, viz. observed and calibrated flow rates. Moreover, the simulation results using the GFS numerical weather prediction model showed no significant differences (at a 95% confidence level) between the observed and simulated hydrographs.
Conclusion: According to the results, using the precipitation data of the GFS numerical weather prediction model and the HEC-HMS rainfall-runoff software makes it possible to simulate the flood with acceptable confidence in predicting the peak discharge of floods.
Keywords: HEC-GeoHMS, Modeling, Numerical weather prediction model, Peak discharge, Sensitivity analysis
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