Kannan N, Santhi C, Williams J R, Arnold J G. Runoff curve number: Has it reached maturity? Journal of Hydrologic Engineering, 1996 1: 11–19. Journal of Agricultural Sciences, 1911 4(1): 1–24. Studies on soil physics, part I, the flow of air and water through soils. In Part 630: Hydrology: NRCS National Engineering Handbook, USDA National Resources Conservation Service, Washington, DC. Chapter 10: Estimation of direct runoff from storm rainfall. Journal of Environmental Quality, Published online. The role of interior watershed processes in improving parameter estimation and performance of watershed models. Yen H, Bailey R T, Arabi M, Ahmadi M, White M J, Arnold J G. History of model development at Temple, Texas. Williams J R, Arnold J G, Kiniry J R, Gassman P W, Green C H. The Soil and Water Assessment Tool: Historical development, applications, and future research directions. Gassman P W, Reyes M R, Green C H, Arnold J G. Sediment and nutrient modeling for TMDL development and implementation. The Open Hydrology Journal, 2011 5: 26–50.īorah D K, Yagow G, Saleh A, Barnes P L, Rosenthal W, Krug E C, Hauck L M. Watershed modeling and its applications: A state-of-the-art review. Int J Agric & Biol Eng, 2015 8(3): 54-68.ĭaniel E B, Camp J V, LeBoeuf E J, Penrod J R, Dobbins J P, Abkowitz, M D. Evaluation of alternative surface runoff accounting procedures using SWAT model. Keywords: Soil and Water Assessment Tool (SWAT), curve number method, Bayesian model averaging, uncertainty analysis hydrology, water qualityĭOI: 10.3965/j.ijabe.20150803.833 Online first on Ĭitation: Yen H, White M J, Jeong J, Arabi M, Arnold J G. Therefore, we recommend additional future SWAT calibration/validation research with an emphasis on the impact of SCSII on the prediction of other pollutants. In addition, the application of BMA has a positive effect on finding well performed solutions in the multi-dimensional parameter space, but the predictive uncertainty is not evidently reduced or enhanced. Results showed that SCSII and BMA associated approaches exhibit improved performance in both discharge and total NO3 predictions compared to SCSI. Applications of BMA provide an alternative approach to investigate the nature of structural uncertainty associated with both CN methods. The objectives of the research were: (1) to quantify the improvements in hydrologic and water quality predictions obtained through different surface runoff estimation techniques and (2) to examine how model uncertainty is affected by combining different surface runoff estimation techniques within SWAT using Bayesian model averaging (BMA). While improved runoff prediction with SCSII has been reported in several case studies, few investigations have been made on its influence to water quality output or on the model uncertainty associated with the SCSII method. From SWAT2005 and onward, an alternative approach has become available to apply the CN method by relating the runoff potential to daily evapotranspiration (SCSII). ![]() For surface runoff estimation in the Soil and Water Assessment Tool (SWAT) model, the curve number (CN) procedure is commonly adopted to calculate surface runoff by dynamically updating CN values based on antecedent soil moisture condition (SCSI) in field.
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