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## Runoff simulation using SWAT model and SUFI-2 algorithm (Case study: Shafaroud watershed, Guilan Province, Iran) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

Caspian Journal of Environmental Sciences | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

مقاله 7، دوره 14، شماره 1، بهار 2016، صفحه 69-80
اصل مقاله (893 K)
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نوع مقاله: Research Paper | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

چکیده | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

Reliable estimates of runoff are required as a part of the information sets that help watershed managers make informed decisions on water resources planning and management. This study was carried out in Shafaroud watershed located in the north of Iran. In order to achieve the best runoff simulation in the study area, first rainfall data of four stations during 1998 to 2011 were collected and combined with other maps of the study area, such as Digital Elevation Model (DEM), land use and soil as input data in the form ofSoil and Water Assessment Tools (SWAT) model. After running the model, the Sequential Uncertainty Fitting (SUFI-2) algorithm in SWAT calibration and uncertainty program (SWAT-CUP) were 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 period. Finally, with multiple simulations, the uncertainty of the parameters was assessed with P-factor, R-factor, and NS coefficients. The results of validation period ( =0.85, NS=0.74) confirmed the potential of SUFI-2 algorithm of SWAT-CUP program for simulating runoff data in the study area. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

کلیدواژه ها | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

Shafaroud watershed؛ Simulation؛ SUFI-2؛ SWAT-CUP | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

اصل مقاله | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

(Received: May. 26.2015 Accepted: Nov. 11.2015)
Reliable estimates of runoff are required as a part of the information sets that help watershed managers make informed decisions on water resources planning and management. This study was carried out in Shafaroud watershed located in the north of Iran. In order to achieve the best runoff simulation in the study area, first rainfall data of four stations during 1998 to 2011 were collected and combined with other maps of the study area, such as Digital Elevation Model (DEM), land use and soil as input data in the form ofSoil and Water Assessment Tools (SWAT) model. After running the model, the Sequential Uncertainty Fitting (SUFI-2) algorithm in SWAT calibration and uncertainty program (SWAT-CUP) were 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 period. Finally, with multiple simulations, the uncertainty of the parameters was assessed with P-factor, R-factor, and NS coefficients. The results of validation period ( =0.85, NS=0.74) confirmed the potential of SUFI-2 algorithm of SWAT-CUP program for simulating runoff data in the study area.
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. Recently, rainfall-runoff models are widely used with hydrologists to simulate watersheds runoff and play a key role in water resources management (Bilondi The SWAT model (Arnoled The SWAT-CUP (Abbaspour Up to now, researchers used SUFI-2 algorithm for model calibration and uncertainty analysis of parameters of SWAT model. Narsimlu They used two different landuse scenarios (1985 and 2006, with reduced forest and increased cropland and urbanized area) in Jinjiang catchment. Shen
Shafaroud watershed is located in Guilan Province at north of Iran, between longitudes 48˚ 39´ 34˝ and 49˚ 8´ 11˝ East and latitudes 37˚ 24´ 58˝and 37˚ 34´ 18˝ north with a drainage area of 336.89 (Fig. 1). The altitude of the catchment ranges from 168 m to 2895 m. The main river with a total length about 40.95 km and located in the north of the catchment. The numbers of meteorology stations were four stations and discharge data was measured at one gauge, located at the outlet. The majority of land is used for forest, agriculture and pasture.
Soil and water assessment tools (SWAT) is a semi-physically based model for assessing the impact of management and climate on water supplies, sediment, and agricultural chemical yields in catchments (Narsimlu SWAT-CUP is a computer program for calibration of SWAT models. It enables sensitivity analysis, calibration, validation, and uncertainty analysis of SWAT models (Abbaspour
Uncertainty in Sequential Uncertainty Fitting (SUFI-2) algorithm is defined as the difference between simulated and observed variables (Rostamian
The P-factor (percentage of measured data bracketed by the 95% prediction boundary) often named 95PPU (Percentage Prediction Uncertainty). The 95PPU is calculated at the 2.5% and 97.5% levels of the cumulative
Distribution of an output variable obtained through Latin hypercube sampling (Abbaspour 2011). The range of the P-factor varies from 0 to 1, with values is close to 1 indicating good fitness between simulated and observed values (Yang
Another measure quantifying the strength of a calibration/uncertainty analysis is the R-factor, which is the average thickness of the 95PPU band divided by the standard deviation of the measured data. The calibrated parameter ranges can be generated with an acceptable value of the R-factor and P-factor.
The R-factor is given by Eq. (1) (Yang
Where and are the upper and lower boundaries of the 95UB and is the standard deviation of the observed data.
Nash-Sutcliffe function has been used for assessment of model performance. This
Function is calculated by using the following equation Eq. (2) (Nash & Sutcliffe 1970):
Where is the ground-based measurements; is the model predicted data and is the mean of the ground-based measurements.
The range of determination coefficient ( ) is 0 to 1 that explain the relationship between
Observed variance and simulated values. The is given by Eq. (3) (Pluntke
Where and are the observed and simulated values, respectively.
According to the Soil and Water Assessment Tools (SWAT) model, the following main data was used: landuse, soil characteristics, topography and climate data. First, the raster maps (e.g. topography, landuse, soil) were imported in ArcSWAT 2012 interface. In the next step, soil and landuse characteristics were overlaid for each sub-catchment. In addition, the weather data were defined. Finally, it was ran and simulated a 14-year period with 3 years warm-up from 1998 through 2011.
For calibration model we used SWAT-CUP program with SUFI-2 algorithm which can read output data from ArcSWAT interface. In this section, fourteen parameters were selected for calibration that influence streamflow. Sensitively analysis was performed and its results indicated the most sensitive parameters that illustrated in Table 1. According to Table 1, the most sensitive parameters are soil bulk density (SOL_BD) and SCS curve number for moisture condition II (CN2) because of P-value close to 0 and t-stat bigger than other parameters. In the next step, model simulated and compared monthly simulated and observed streamflows using SUFI-2 algorithm. We calibrated a 7-year period from 2001 to 2007 and validated a 4-year period from 2008 to 2011. Analysis of hydrographs indicates that the calibrated model slightly underestimate the peak runoff (Fig. 2). The size of uncertainty band (95PPU) is shown in Fig. 2 which confirms the uncertainty is very high. After defining the initial values of the fourteen parameters, it was specified for selecting appropriate parameters ranges. It could be reduce the band of uncertainty. Furthermore, after three iterations with 500 model runs, the best calibration illustrated in Fig. 3, where value was 0.86, P-factor of 0.51, R-factor of 0.54 and NS was 0.77. With this calibration, the best ranges of parameters were obtained (Table 2). According to the last calibration, the best parameters values were imported (Table 2) in SWAT model and validated using data set for the period of 2008 to 2011and compared the plot of observed and simulated data.
*dimensionless
Table 3 illustrates the values of P and R factors, and NS in calibration (2001 to 2007) and validation (2008 to 2011) periods. Taking an analysis of the catchment at the outlet had a positive correlation with surface runoff, with of 0.85, while P-factor, R-factor and NS were 0.63, 0.49 and 0.74 respectively (Fig. 4). In other words, the evaluation of the hydrograph plot showed good model match in validation period. Also coefficient of determination ( ) value of calibration and validation period showed a good correlation between observed and simulated values (Fig. 5).
Many hydrologic studies and applications has been used SWAT model and SWAT-CUP program for calibration and validation data with decreasing uncertainty (Schuol & Abasspour 2006; Stedinger Hosseini In SUFI-2 algorithm, all the uncertainties are combined and expressed through the P-factor, which is the percentage of measured data bracketed by the 95% prediction uncertainty (95PPU) with ranges from 0 to 1. Also, in uncertainty analysis used the R-factor, which is the average thickness of the 95PPU band divided by the standard deviation of the measured data (Yang The P-factor values close to 1 indicating a very high model performance, while the R-factor is the average width of the 95PPU band (Abbaspour These results to confirm the potential of SUFI-2 algorithm of SWAT-CUP program for simulating runoff data in Shafaroud watershed and matched well with those of the other authors (Tang Also this algorithm can be used in further evaluation of land use change, sediment, climate change, water quality and evapotranspiration effect assessment on water resources. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

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