Optimal Calibration and Uncertainty Analysis of SWAT for an Arid Climate (original) (raw)
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Calibration and Uncertainty of the SWAT Model Using the SUFI-2 Algorithm
In the application of models, less attention is paid to the quantitative determination of the importance of uncertainty that predicts variability and input parameter values. Hydrological models require a lot of input parameters that are not fully known. Because of this uncertainty, the models are not able to accurately describe hydro-logic and chemical processes under normal conditions. In this study, the SWAT model was used to simulate flow in the Maroon Dam basin. The model was implemented for the period 1994-2001. Moreover, uncertainty testing was through using the SUFI program. The results showed that the SWAT model could be a useful tool for simulating river flow intensity. In this investigation we adjust and calibrate an unified hydrological model using the Soil and Water Assessment Tool (SWAT) program. various elements of water resources are simulated and water quality are measured at the Hydrological Response Unit (HRU) level. The water resources are computed at subbasin level with monthly periods. The use of comprehensive, high-resolution water resources models enables steady and inclusive investigation of unified system behavior through physically-based, data-driven simulation. In this investigation we examine issues with data accessibility, calibration of large-scale distributed models, and outline methods for model calibration and uncertainty analysis. The methods technologically advanced are overall and can be practical to any large zone around the universe. Multi-objective hydrological model calibration can indicate a valorous solution to diminish model equifinality and parameter uncertainty. The Soil and Water Assessment Tool (SWAT) model is extensive used to considerate water quality and water management issues in catchment. Keywords: Uncertainty - SWAT - Runoff Simulation - SUFI2
CALIBRATION AND UNCERTAINTY ANALYSIS OF SWAT MODEL IN A JAPANESE RIVER CATCHMENT
Journal of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering), 2011
Calibration and uncertainty analysis is necessary to perform the best estimation and uncertainty identification of hydrological models. This paper uses the Soil and Water Assessment Tool-Calibration and Uncertainly Procedures (SWAT-CUP) model to analyze the uncertainty of SWAT model in a Japanese river catchment. The GLUE and SUFI-2 techniques used in this analysis show quite good results with high value of R 2 as 0.98 and 0.95 for monthly simulation. Daily simulation results during calibration and validation are also good with R 2 as 0.86 and 0.80. For uncertainty results, the 95% prediction uncertainty (95PPU) brackets very well with the observation. The p-factors of uncertainty analysis for the calibration and validation periods are 92% and 94%. The calibration result by using GLUE shows better than that by using SUFI-2. However, the processing time of the GLUE approach is longer than SUFI-2 approach when they were run in the SWAT-CUP. The uncertainty analysis indicates that the parameters of effective hydraulic conductivity in main channel alluvium (CH_K2) and base-flow alpha factor for bank storage (ALPHA_BNK) play important roles for calibration and validation of SWAT model.
Sensitivity Analysis And Interdependence Of The SWAT Model Parameters
2007 Minneapolis, Minnesota, June 17-20, 2007, 2007
In contrast to lumped-parameter models, the distributed and processed-based hydrologic models take into account the spatial distribution of the hydrologic processes but became highly parameterized. In the Soil and Water Assessment Tool (SWAT) for example, the watershed is subdivided into spatial units (subbasins and hydrologic response units, HRU's) and each spatial unit has its own unique parameters that are utilized in SWAT simulation. Sensitivity analyses had been used as screening tools for reducing the number of parameters in model calibration. The objective of this study was to analyze the sensitivity of the objective functions to changes in parameters used in the multiobjective automatic calibration of the SWAT model. We used a Bayesian network to estimate the interdependencies of the SWAT parameters. The direct and indirect effect of the parameters on the model output was also explored. Where there are multiple objectives, the parameters and their interaction in searching for the Pareto optimum change with position along the Pareto front. The information derived from the Bayesian network requires redefining sensitivity to include a description of the interaction of parameters in the calibration search process.
SWAT: Model Use, Calibration, and Validation
Transactions of the ASABE, 2012
SWAT (Soil and Water Assessment Tool) is a comprehensive, semi-distributed river basin model that requires a large number of input parameters, which complicates model parameterization and calibration. Several calibration techniques have been developed for SWAT, including manual calibration procedures and automated procedures using the shuffled complex evolution method and other common methods. In addition, SWAT-CUP was recently developed and provides a decision-making framework that incorporates a semi-automated approach (SUFI2) using both manual and automated calibration and incorporating sensitivity and uncertainty analysis. In SWAT-CUP, users can manually adjust parameters and ranges iteratively between autocalibration runs. Parameter sensitivity analysis helps focus the calibration and uncertainty analysis and is used to provide statistics for goodness-of-fit. The user interaction or manual component of the SWAT-CUP calibration forces the user to obtain a better understanding of the overall hydrologic processes (e.g., baseflow ratios, ET, sediment sources and sinks, crop yields, and nutrient balances) and of parameter sensitivity. It is important for future calibration developments to spatially account for hydrologic processes; improve model run time efficiency; include the impact of uncertainty in the conceptual model, model parameters, and measured variables used in calibration; and assist users in checking for model errors. When calibrating a physically based model like SWAT, it is important to remember that all model input parameters must be kept within a realistic uncertainty range and that no automatic procedure can substitute for actual physical knowledge of the watershed.
COMPARISON OF CALIBRATION AND UNCERTAINTY ANALYSIS METHODS: CASE STUDY OF NZOIA RIVER SWAT MODEL
This paper presents comparison of different optimization and uncertainty analysis methods in distributed hydrological modeling. A distributed hydrological model using the Soil and Water Assessment Tool (SWAT) has been built to simulate daily flow in Nzoia River in Kenya. Model parameters of SWAT were calibrated using four different optimization algorithms: parameter solution (PARASOL), adaptive clustering covering (ACCO), genetic algorithm (GA) and multi start (M-Simplex).
2010
This study simulated the watershed flow and sediment responses based on calibration of the SWAT model in the semi-arid Chinese Loess Plateau (LP) where soil erosion intensively occurs. After the model's initiation and manual modification, a 7-year inconsecutively observed flow and sediment data from 1984 to 1990 was used to analyze the model's application in the selected watershed called AJW in the Chinese LP region. The model procedure included sensitivity analysis, parameter calibration and model validation. The best parameter set was finally determined based on the combination of parameter localization and auto-calibration. Then the model was assessed for its accuracy based on the NSE estimation, resulting in 0.77 and 0.67 for calibration and 0.46 and 0.32 for validation on simulations for flow and sediment, respectively, which is a moderately satisfactory accuracy among the applications of the SWAT model. Annual watershed assessment on flow and sediment with the calibrated SWAT model resulted in a multiyear averaged annual runoff coefficient of about 2.7% and an erosion modulus of 797 t/(km 2 $a -1 ) in the AJW, indicating a beneficial consequence from the implementation of the historical soil and water conservations.
Engineering, 2018
The Ganga River, the longest river in India, is stressed by extreme anthropogenic activity and climate change, particularly in the Varanasi region. Anticipated climate changes and an expanding populace are expected to further impede the efficient use of water. In this study, hydrological modeling was applied to Soil and Water Assessment Tool (SWAT) modeling in the Ganga catchment, over a region of 15 621.612 km 2 in the southern part of Uttar Pradesh. The primary goals of this study are: ① To test the execution and applicability of the SWAT model in anticipating runoff and sediment yield; and ② to compare and determine the best calibration algorithm among three popular algorithms-sequential uncertainty fitting (SUFI-2), the generalized likelihood uncertainty Estimation (GLUE), and parallel solution (ParaSol). The input data used in the SWAT were the Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM), Landsat-8 satellite imagery, soil data, and daily meteorological data. The watershed of the study area was delineated into 46 sub-watersheds, and a land use/land cover (LULC) map and soil map were used to create hydrological response units (HRUs). Models utilizing SUFI-2, GLUE, and ParaSol methods were constructed, and these algorithms were compared based on five categories: their objective functions, the concepts used, their performances, the values of P-factors, and the values of R-factors. As a result, it was observed that SUFI-2 is a better performer than the other two algorithms for use in calibrating Indian watersheds, as this method requires fewer runs for a computational model and yields the best results among the three algorithms. ParaSol is the worst performer among the three algorithms. After calibrating using SUFI-2, five parameters including the effective channel hydraulic conductivity (CH_K2), the universal soil-loss equation (USLE) support parameter (USLE_P), Manning's n value for the main channel (CH_N2), the surface runoff lag time (SURLAG), and the available water capacity of the soil layer (SOL_AWC) were observed to be the most sensitive parameters for modeling the present watershed. It was also found that the maximum runoff occurred in sub-watershed number 40 (SW#40), while the maximum sediment yield was 50 t•a −1 for SW#36, which comprised barren land. The average evapotranspiration for the basin was 411.55 mm•a −1. The calibrated model can be utilized in future to facilitate investigation of the impacts of LULC, climate change, and soil erosion.
Water, 2021
The quantitative prediction of hydrological components through hydrological models could serve as a basis for developing better land and water management policies. This study provides a comprehensive step by step modelling approach for a small agricultural watershed using the SWAT model. The watershed is situated in Petzenkirchen in the western part of Lower Austria and has total area of 66 hectares. At present, 87% of the catchment area is arable land, 5% is used as pasture, 6% is forested and 2% is paved. The calibration approach involves a sequential calibration of the model starting from surface runoff, and groundwater flow, followed by crop yields and then soil moisture, and finally total streamflow and sediment yields. Calibration and validation are carried out using the r-package SWATplusR. The impact of each calibration step on sediment yields and total streamflow is evaluated. The results of this approach are compared with those of the conventional model calibration approac...
Open Journal of Modern Hydrology, 2020
Management of reservoir water resources requires the knowledge of flow inputs in this reservoir. Hydrological rainfall-runoff model is used for this purpose. There are several types of hydrological model according the description of the hydrological processes: black-box models, conceptual models, deterministic physical based model. SWAT is a semi-distributed hydrological model designed for water quality and quantity. This versatile tool has been used all around the world to assess and manage water resources. The main objective of the paper is to calibrate and validate the SWAT model on the watershed of Bafing located between 10˚30' and 12˚30' north latitude and between 12˚30' and 9˚30' west longitude to assess climate change on this river flows. A DEM with a resolution of 12.5 m × 12.5 m, the daily average flows and the daily observed precipitations on the period 1979-1986 (long period) are used as inputs for the calibration, while precipitations for the period 1988-1994 are used for the validation. The sensitivity analysis was done to detect the most determining coefficients during the calibration step. It shows that 19 parameters are required. Then, the effect of the period on the parameters calibration is checked by considering first the whole period of study and then each year of the period of study. The Nash criterion was used to compare the calculated and the observed hygrographs in each case. The results showed that the longer is the period of calibration, the more accurate is the Nash criterion. The calibration per year gave a best Nash criterion except for a single year. During the validation, the parameters calculated on the long period lead to the best Nash criterion. The values of the Nash criterion calibration and validation are very suitable. These results of calibration can be used How to cite this paper:
IPEAT+: A Built-In Optimization and Automatic Calibration Tool of SWAT+
Water
For almost 30 years, the Soil and Water Assessment Tool (SWAT) has been successfully implemented to address issues around various scientific subjects in the world. On the other hand, it has been reaching to the limit of potential flexibility in further development by the current structure. The new generation SWAT, dubbed SWAT+, was released recently with entirely new coding features. SWAT+ is designed to have far more advanced functions and capacities to handle challenging watershed modeling tasks for hydrologic and water quality processes. However, it is still inevitable to conduct model calibration before the SWAT+ model is applied to engineering projects and research programs. The primary goal of this study is to develop an open-source, easy-to-operate automatic calibration tool for SWAT+, dubbed IPEAT+ (Integrated Parameter Estimation and Uncertainty Analysis Tool Plus). There are four major advantages: (i) Open-source code to general users; (ii) compiled and integrated directly...