Hossain shirani; Anis Asadi; ُSomayeh Sadr; Ali Asghar besalatpour; Isa esfandiarpoor
Abstract
Introduction
SWAT model is a suitable tool for simulating hydrological processes. This model requires many inputs that often cannot be measured directly and is considered one of the main sources of uncertainty in these models. The recalibration process can reduce the uncertainty in the model results ...
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Introduction
SWAT model is a suitable tool for simulating hydrological processes. This model requires many inputs that often cannot be measured directly and is considered one of the main sources of uncertainty in these models. The recalibration process can reduce the uncertainty in the model results by adjusting and adapting these inputs. The researches showed that calibrating a hydrological model by using the common automatic CV calibrating algorithms will not provide proper accuracy in the prediction of hydrological variables during the validation period, so PSO algorithm was used to calibrate the SWAT model. Since there is no mathematical and logical rule to determine the best combination of PSO algorithm parameters and these combinations are selected based on trial and error and among many different combinations, therefore trial and error based methods are very time-consuming and sometimes impossible. In this research, Taguchi method was used to determine the best combination of PSO algorithm parameters.
Materials and methods
In this research, the ability to use the SWAT model to simulate monthly runoff in the Javanmardi Watershed, one of the main sub-basins of the Lordegan Watershed with an area of 380 square kilometers, was investigated. In this study, the PSO algorithm parameters, including the number of simulations (A), the number of repetitions (B), the speed calculation weight (C) and the movement parameter (D), were defined in four levels. Then, these parameters were designed and implemented according to the experiments in the L16 orthogonal array (using the Taguchi experiments design method). The performance scale used to evaluate the algorithms was RPD (Relative Percentage Deviation). Considering the variable nature of the response in this study, the S/N index "the lower the better" was used to analyze the Taguchi test results. The selection of arrays and calculations were done in Minitab 16 software.
Results and discussion
In the sensitivity analysis stage, which was performed before the model recalibration, among the 28 parameters studied in this research, the model showed sensitivity to the changes of 22 parameters, and they were identified as variables influencing the simulation of runoff in Javanmardi Watershed. The results showed that the parameter of the runoff curve number (CN) is the most important factor and the parameters of soil apparent density in the wet state (SOL_BD) and average water usable by the plant (SOL_AWC) are among the most important factors controlling the flow rate in the study basin, respectively. Based on the results simulated by the PSO algorithm, it was found that the SWAT model has an acceptable accuracy for estimating the monthly runoff in the study area. So, in the recalibration phase, the r-factor and p-factor indices were 1.23 and 0.88, respectively, and the explanatory and Nash-Sutcliffe coefficients were 0.77 and 0.75, respectively. In the validation stage, the r-factor and p-factor indexes were 1.31 and 0.84, respectively and the explanatory and Nash-Sutcliffe coefficients were 0.72 and 0.73, respectively. In this study, the best combination resulting from the application of Taguchi method for the parameters of the number of simulations, the number of repetitions, the speed calculation weight and the appropriate parameters in the PSO algorithm were determined as 40, 100, 0.2 and 0.15 respectively (A4B4C4D3).
Conclusion
The results show that the SWAT model has an acceptable accuracy for estimating the monthly runoff in the Jawanmardi Watershed, and the PSO method is an effective algorithm in calibrating and determining the uncertainty of the model in this basin, and the use of the Taguchi test design method is a suitable way to determine the best combination of PSO algorithm parameters is for researchers who use this method to optimize the SWAT model.
Sadegh Momeneh; Arash Azari; Afshin Eghbalzadeh
Abstract
In this research, the effect of climate change on the groundwater level of Chamchamal Plain in the two 20-year periods was investigated. The GMS groundwater model was used to simulate the aquifer and was calibrated and verified for evaluation and validation of the model for two periods of 18 months, ...
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In this research, the effect of climate change on the groundwater level of Chamchamal Plain in the two 20-year periods was investigated. The GMS groundwater model was used to simulate the aquifer and was calibrated and verified for evaluation and validation of the model for two periods of 18 months, respectively. In order to investigate the effect of climate change on the fluctuations of groundwater level in the region, six AOGCM models were used under three emission scenarios A2, A1B, and B1 in the upcoming period. Then, two methods of weighting and extraction of probabilistic levels were used to consider the uncertainty prediction of climate change models for temperature and precipitation parameters. The predicted climatic variables for scenarios A2, A1B and B1, and two Probability levels 90% and 50%, respectively, show the average temperature changes of +0.57, +0.57, +0.57, -0.04 and +0.6 °C and average precipitation variation of +0.12, -1.8, +2.49, -31.78 and -2.33 during the period 2011-2030. Similarly, for the period 2046-2065, the average temperature changes were +1.92, +2.12, +1.46, +0.98 and +2.3°C, and the average precipitation variation was -20.59, -26.07, -19.55, -47.15 and -15.74 percent. Finally, the effect of climate change on the aquifer level was determined under scenarios. The results showed the groundwater level, under scenarios A2, A1B and B1 and two probabilistic levels of 90 and 50 percent for the periods 2011-2030 and 2046-2065 will drawdown between -9.6 to -17.92 meters, which is Compared to the period 1996-2015, it showed a change in level between -1.06 to -9.38 meters.
Mehdi Ahmadi; Bagher Ghermezcheshmeh
Abstract
In the last decades, greenhouse gases in atmosphere have increased as a result of natural and human activities and thus, earth temperature has increased. Rising global temperature, in turn, leads to significant changes in related fields, especially water resources and agriculture. So, investigating and ...
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In the last decades, greenhouse gases in atmosphere have increased as a result of natural and human activities and thus, earth temperature has increased. Rising global temperature, in turn, leads to significant changes in related fields, especially water resources and agriculture. So, investigating and modeling climate changes can be considered as a very important factor in water resources management planning. Different studies have been done in the field of climate change issues in the world, but, at the moment, AOGCM model is the most reliable tool to generate climate scenarios. It is necessary to downscale AOGCM data using different techniques in station scale and compare linear and nonlinear downscaling models. In liner method SDSM and in nonlinear method ANN programming were used in MATLAB. For investigating the amount of error, mean biomass monthly and annual and for extreme data, variance and for analyzing uncertainty Man-Witney test were used in 95 percent level. Results showed the amount of mean monthly errors are 0.75, 12, 11 and 7 mm in Ghaemshahr, Babolsar, Ghoran Talar and Bandpey in SDSM model and 3, 2, 26 and 4 mm in ANN model and the amount of mean annual errors are 9, 146, 141 and 87 mm in SDSM model and 45, 32, 321 and 48 mm in ANN model (increased or decreased), respectively. Examining the performance of variance showed that ANN model was somewhat better than SDSM model. Also, results of uncertainty for 12 months in Ghaemshar, Babolsar, Quran Talar and Bandpey stations showed 8, 3, 6 and 4 in SDSM model and 4, 2, 2 and 3 in ANN model, respectively. In general, this study showed that in studies on climate change effects on runoff, uncertainty, and when limited data are available, SDSM model should be used and when the aim is investigating the flood and its minimum and maximum estimation, it is better to use ANN model.
Ahmad Sharafati
Abstract
Rainfall runoff models are used mostly in simulation of flood events. Also, calibration of rainfall runoff model parameters is an important and challenging issue in flood simulation. Due to random characteristic of these parameters, the deterministic optimization is not a suitable approach for calibration ...
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Rainfall runoff models are used mostly in simulation of flood events. Also, calibration of rainfall runoff model parameters is an important and challenging issue in flood simulation. Due to random characteristic of these parameters, the deterministic optimization is not a suitable approach for calibration of rainfall runoff model. So, in this study, the SUFI (Sequential Uncertainty Fitting) algorithm is used as a stochastic approach and the optimized range of parameters were extracted. The obtain results shown, in calibration step, the correlation coefficient between observed hydrographs (three events) and the best generated hydrographs were more than 0.9 and also, the average difference between observed hydrographs and the best generated hydrographs were less than 5 percent. Furthermore, in validation step, the correlation coefficient between observed hydrograph and the best generated hydrograph was 0.99 and also, the average difference between observed hydrograph and the best generated hydrograph was 11 percent. So, the SUFI algorithm is a suitable approach in stochastic calibration of HEC-1 model.
Ahmad Nohegar; Arash Malekian; Majid Hosseini; Arashk Holisaz; Edris Taghvaye Salimi
Abstract
Two factors of cost and time are related directly to the accurate estimate of runoff in the watersheds. More detailed information on the status of rainfall runoff also facilitate decisions on future programs for watershed managers, a step towards the preservation of natural resources for sustainable ...
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Two factors of cost and time are related directly to the accurate estimate of runoff in the watersheds. More detailed information on the status of rainfall runoff also facilitate decisions on future programs for watershed managers, a step towards the preservation of natural resources for sustainable development. In this study, in order to achieve optimal amount of runoff in the Shafaroud watershed, first significant rainfall data of four stations during 1998 to 2011 were collected and combined with other maps of the study area, such as DEM, land use and soil as input data in the form of SWAT model was software. After running the model, the SUFI-2 and GLUE algorithms in SWAT-CUP program used to evaluate the data uncertainty and the most accurate simulation. The first three years (1998-2000) of rainfall data for warm-up and the next 7 years (2001-2007) for the calibration and final 4 years (2008-2011) were used for the validation. Finally, with multiple simulations, the uncertainty of the parameters assessed with P-factor, R-factor, and NS coefficients. The results indicated in runoff simulation, the SUFI2 algorithm ( =0.85, NS=0.74) is more accurate than GLUE algorithm ( =0.82, NS=0.71).
