Assessing the performance and uncertainty analysis of the SWAT and RBNN models for simulation of sediment yield in the Nagwa watershed, India

Singh, Ajai K.; Imtiyaz, M.; Isaac, R. K.; Denis, D. M.

doi:10.1080/02626667.2013.872787

Cited by 58 publications

(27 citation statements)

References 24 publications

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“…The influence of BMPs, such as winter cover crops, on nitrate flux to streams has not been measured in situ at scales larger than field, because of the substantial residence time of leached N in groundwater and the difficulty of monitoring over long time periods (McCarty et al, 2008). A few field studies have demonstrated cover crop nitrate reduction efficiencies at the field scale (e.g., Shipley et al, 1992;Staver and Brinsfield, 2000). Hively et al (2009) used satellite remote sensing images and field sampling data to estimate winter cover crop biomass production and N uptake efficiency at the landscape scale.…”

Section: I-y Yeo Et Al: Assessing Winter Cover Crop Nutrient Uptakmentioning

confidence: 99%

“…The values of those statistical measures were compared to the model evaluation criteria set for various water quality parameters (Moriasi et al, 2007). The prediction uncertainty of the model was assessed using the 95 % prediction uncertainty (95 PPU), the P factor, and the R factor (Singh et al, 2014). They were computed using all simulation outputs obtained during the manual calibration process.…”

Section: Calibration and Validation Of Swat Modelmentioning

confidence: 99%

“…The P factor indicates the percentage of observed data falling within 95 PPU band, and the R factor is the average thickness of the 95 PPU bands by the standard deviation of the observed data. The R factor can vary between 0 (i.e., achievement of a small uncertainty bound) and infinity, while the P factor can vary from 0 to 100 % (i.e., all observations bracketed by the prediction uncertainty) (Singh et al, 2014).…”

Section: Calibration and Validation Of Swat Modelmentioning

confidence: 99%

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Assessing winter cover crop nutrient uptake efficiency using a water quality simulation model

Yeo

Lee

Sadeghi

et al. 2014

Hydrol. Earth Syst. Sci.

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Abstract. Winter cover crops are an effective conservation management practice with potential to improve water quality. Throughout the Chesapeake Bay watershed (CBW), which is located in the mid-Atlantic US, winter cover crop use has been emphasized, and federal and state cost-share programs are available to farmers to subsidize the cost of cover crop establishment. The objective of this study was to assess the long-term effect of planting winter cover crops to improve water quality at the watershed scale (∼ 50 km 2 ) and to identify critical source areas of high nitrate export. A physically based watershed simulation model, Soil and Water Assessment Tool (SWAT), was calibrated and validated using water quality monitoring data to simulate hydrological processes and agricultural nutrient cycling over the period of 1990-2000. To accurately simulate winter cover crop biomass in relation to growing conditions, a new approach was developed to further calibrate plant growth parameters that control the leaf area development curve using multitemporal satellitebased measurements of species-specific winter cover crop performance. Multiple SWAT scenarios were developed to obtain baseline information on nitrate loading without winter cover crops and to investigate how nitrate loading could change under different winter cover crop planting scenarios, including different species, planting dates, and implementation areas. The simulation results indicate that winter cover crops have a negligible impact on the water budget but significantly reduce nitrate leaching to groundwater and delivery to the waterways. Without winter cover crops, annual nitrate loading from agricultural lands was approximately 14 kg ha −1 , but decreased to 4.6-10.1 kg ha −1 with cover crops resulting in a reduction rate of 27-67 % at the watershed scale. Rye was the most effective species, with a potential to reduce nitrate leaching by up to 93 % with early planting at the field scale. Early planting of cover crops (∼ 30 days of additional growing days) was crucial, as it lowered nitrate export by an additional ∼ 2 kg ha −1 when compared to late planting scenarios. The effectiveness of cover cropping increased with increasing extent of cover crop implementation. Agricultural fields with well-drained soils and those that were more frequently used to grow corn had a higher potential for nitrate leaching and export to the waterways. This study supports the effective implementation of cover crop programs, in part by helping to target critical pollution source areas for cover crop implementation.

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Section: I-y Yeo Et Al: Assessing Winter Cover Crop Nutrient Uptakmentioning

confidence: 99%

Section: Calibration and Validation Of Swat Modelmentioning

confidence: 99%

Section: Calibration and Validation Of Swat Modelmentioning

confidence: 99%

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Assessing winter cover crop nutrient uptake efficiency using a water quality simulation model

Yeo

Lee

Sadeghi

et al. 2014

Hydrol. Earth Syst. Sci.

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“…For instance, Singh et al (2014) compared the SWAT model with an artificial neural network model (RBNN, radial basis neural network) in terms of performance in simulating sediment yield and uncertainty. The SWAT model calibration and uncertainty analysis were performed with SUFI-2, whereas bootstrap methodology was applied for the uncertainty analysis of the RBNN model.…”

Section: Introductionmentioning

confidence: 99%

Comparing calibrated parameter sets of the SWAT model for the Scandinavian and Iberian peninsulas

Malagó

Pagliero

Bouraoui

et al. 2015

Hydrological Sciences Journal

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Different SWAT models have been set-up to predict water discharge at the European scale, applying an innovative modelling protocol that involves sensitivity analysis, multi-variable calibration and regionalization of the calibrated parameters. In this application, two large regions have been considered: the Scandinavian and the Iberian peninsulas, with the main objectives: (a) to study the spatial variation of calibrated parameter sets obtained for selected sub-basins, and (b) identification of the most relevant hydrological processes in each region. The results of the analysis highlight that snow processes are dominant in Scandinavia; groundwater processes are significant in both the Scandinavian and Iberian peninsulas, while lateral flow is not significant in either region. Calibrated soil hydraulic parameters have different ranges of values in each region, reflecting a difference in runoff-generating mechanisms between the two studied regions. The contribution of this analysis is the assessment of the main differences between hydrological processes across Europe and understanding of the major transport pathways for pollutants.Key words large-scale model; multi-variable calibration; sensitivity analysis; spatial variability; SWAT model; parameter regionalization; Scandinavia; Iberian Peninsula Comparaison de jeux de paramètres calés de modèles SWAT pour les péninsules ibérique et ScandinaveRésumé Différentes modèles SWAT (Soil and Water Assessment Tool) ont été mises en place afin de prévoir les débits à l'échelle européenne selon un protocole de modélisation innovant comprenant une analyse de sensibilité, une calage multi-variable ainsi que la régionalisation des paramètres calés. Nous avons considéré dans cette application deux grandes régions: les péninsules scandinave et ibérique. Les objectifs principaux de cette recherche sont (a) d'étudier la variation spatiale des jeux de paramètres calés obtenus dans les sous-bassins sélectionnés et (b) d'identifier les processus hydrologiques dominants dans chaque région. Les résultats de l'analyse indiquent que les processus affectant le manteau neigeux sont dominants en Scandinavie, que les processus d'écoulements souterrains sont importants dans les deux péninsules, alors que l'écoulement latéral dans la zone non saturée n'est significatif dans aucune des deux régions. Les paramètres hydrauliques calés des sols varient sensiblement d'une région à l'autre, indiquant une différence des mécanismes de génération des écoulements. Notre analyse a contribué à une meilleure connaissance des processus hydrologiques à travers l'Europe, permettant ainsi une détermination plus précise des principales voies de transport des polluants.

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“…The p-factor indicates the percentage of observed data falling within 95PPU band and the r-factor is the average thickness of the 95PPU bands by the standard deviation of the observed data. The r-factor can vary between 0 and infinity, while the p-factor can vary from 0 to 100% [45]. The goodness of fit and the degree to which the model accounts for uncertainties are assessed by the above two measures.…”

Section: Model Calibration Sensitivity and Uncertainty Analysismentioning

confidence: 99%

On the Use of NLDAS2 Weather Data for Hydrologic Modeling in the Upper Mississippi River Basin

Wang

2019

Water

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Weather data are the key forces that drive hydrological processes so that their accuracy in watershed modeling is fundamentally important. For large-scale watershed modeling, weather data are either generated by using interpolation methods or derived from assimilated datasets. In the present study, we compared model performances of the Soil and Water Assessment Tool (SWAT), as driven by interpolation weather data, and NASA North American Land Data Assimilation System Phase Two (NLDAS2) weather dataset in the Upper Mississippi River Basin (UMRB). The SWAT model fed with different weather datasets were used to simulate monthly stream flow at 11 United States Geological Survey (USGS) monitoring stations in the UMRB. Model performances were evaluated based on three metrics: coefficient of determination (R2), Nash–Sutcliffe coefficient (NS), and percent bias (Pbias). The results show that, after calibration, the SWAT model compared well at all monitoring stations for monthly stream flow using different weather datasets indicating that the SWAT model can adequately produce long-term water yield in UMRB. The results also show that using NLDAS2 weather dataset can improve SWAT prediction of monthly stream flow with less prediction uncertainty in the UMRB. We concluded that NLDAS2 dataset could be used by the SWAT model for large-scale watersheds like UMRB as a surrogate of the interpolation weather data. Further analyses results show that NLDAS2 daily solar radiation data was about 2.5 MJ m−2 higher than the interpolation data. As such, the SWAT model driven by NLDAS2 dataset tended to underestimate stream flow in the UMRB due to the overestimation in evapotranspiration in uncalibrated conditions. Thus, the implication of overestimated solar radiation by NLDAS2 dataset should be considered before using NLDAS2 dataset to drive the hydrological model.

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Assessing the performance and uncertainty analysis of the SWAT and RBNN models for simulation of sediment yield in the Nagwa watershed, India

Cited by 58 publications

References 24 publications

Assessing winter cover crop nutrient uptake efficiency using a water quality simulation model

Assessing winter cover crop nutrient uptake efficiency using a water quality simulation model

Comparing calibrated parameter sets of the SWAT model for the Scandinavian and Iberian peninsulas

On the Use of NLDAS2 Weather Data for Hydrologic Modeling in the Upper Mississippi River Basin

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