Evaluation of SWAT sub-daily runoff estimation at small agricultural watershed in Korea

详细信息    查看全文

• 作者：Ganga Ram Maharjan (1)
  Youn Shik Park (2)
  Nam Won Kim (3)
  Dong Seok Shin (4)
  Jae Wan Choi (4)
  Geun Woo Hyun (5)
  Ji-Hong Jeon (6)
  Yong Sik Ok (7)
  Kyoung Jae Lim (1)
  
• 关键词：Soil and Water Assessment Tool (SWAT) ; sub ; daily simulation ; runoff ; rainfall
• 刊名：Frontiers of Environmental Science & Engineering
• 出版年：2013
• 出版时间：February 2013
• 年：2013
• 卷：7
• 期：1
• 页码：109-119
• 全文大小：466KB
• 参考文献：1. Shrestha S, Babel M S, Gupta A D, Kazama F. Evaluation of annualized agricultural nonpoint source model for a watershed in the siwalik hills of Nepal. Environmental Modelling & Software, 2006, 21(7): 961-75 CrossRef
  2. Wischmeir W H, Smith D D. Predicting rainfall erosion losses. Agricultural Handbook, 1978
  3. Knisel WG. CREAMS, A field scale model for chemical, runoff and erosion from agricultural management systems. Conservation Report, 1980
  4. Beasley D B, Huggins L F, Monke E J. ANSWERS: A model for watershed planning. Transactions of the ASAE. American Society of Agricultural Engineers, 1980, 23(4): 938-44
  5. Williams J R. SPNM, a model for predicting sediment, phosphorus, and nitrogen yields from agricultural basins. Water Resources Bulletin, 1980, 16: 843-48 CrossRef
  6. Williams J R, Dyke P T, Jones C A. EPIC-A model for assessing the effects of erosion and soil productivity. In: Proceedings of the Third International Conference on State-of-the Art in Ecological Modeling. 1982, 156-58
  7. Williams J R, Nicks A D, Arnold J G. SWRRB: simulator for water resources in rural basins. ASCE Hydraulics Journal, 1985, 111(6): 970-86 CrossRef
  8. Leonard R A, Knisel W G, Still D A. GLEAMS: groundwater loading effects of agricultural management systems. Transactions of the ASAE. American Society of Agricultural Engineers, 1987, 30(5): 1403-418
  9. Lim K J, Engel B A. Extension and enhancement of national agricultural pesticide risk analysis (NAPRA) www Decision Support System to Include Nutrients. Computers and Electronics in Agriculture, 2003, 38(3): 227-36 CrossRef
  10. Lane L J, Nearing M A. USDA -Water erosion prediction project: Hillslope profile model documentation. NSERL Report, 1989
  11. Young R A, Onstad C A, Bosch D D, Anderson W P. Agricultural non-point source pollution model. AGNPS User’s Guide, USDAARS, Version 4.03, 1994
  12. Clemente R S, Prasher S O, Barrington S F. PESTFADE, a new pesticide fate and transport model: model development and verification. Transactions of the ASAE. American Society of Agricultural Engineers, 1993, 36(2): 357-67
  13. Donigian A S, Bicknell B R, Imhoff J C. Hydrological simulation programe Fortran (HSPF). In: Singh, VP. Computer Models of Watershed Hydrology. Colorado: WRP, Highlands Ranch, 1995, 395-42
  14. Arnold J G, Allen P M. Estimating hydrologic budgets for three Illinois watersheds. Journal of Hydrology (Amsterdam), 1996, 176(1-): 57-7 CrossRef
  15. Shepherd B, Harper D M, Millington A. Modeling catchment-scale nutrient transport to watercourses in the U.K. Hydorbiologia, 1999, 395/396: 227-37 CrossRef
  16. Kannan N, White S M, Worrall F, Whelan M J. Hydrological modeling of a small catchment using SWAT-2000-Ensuring Correct Flow Partitioning for Contaminant Modeling. Journal of Hydrology (Amsterdam), 2007, 334(1-): 64-2 CrossRef
  17. Cotter A. Critical Evaluation of TMDL data requirements for agricultural watersheds. Dissertation for the Master Degree. Fayetteville: University of Arkansas, 2002, 76-8
  18. Tripathi M P, Panda R K, Raghuwanshi N S. Identification and prioritization of critical subwatershed for soil conservation management using the SWAT model. Biosystems Engineering, 2003, 85(3): 365-79 CrossRef
  19. King K W, Arnold J G, Bingner R L. Comparison of Green-Ampt and Curve Number Methods on Goodwin Creek Watershed Using SWAT. Transactions of the ASAE. American Society of Agricultural Engineers, 1999, 42(4): 919-25
  20. Rawls W J, Ahuja L R, Brakenseik D L, Shirmohammadi A. Infiltration and Soil Water Movement. In: Maidment D R, editor, Handbook of Hydorogy. New York: McGraw-hill. 1993, 313-25
  21. Diluzio M, Arnold J G. Formulation of a hybrid calibration approach for a physically based distributed model with NEXRAD data input. Journal of Hydrology (Amsterdam), 2004, 298(1-): 136-54 CrossRef
  22. Debele B, Srinivasan R, Parlange J. Hourly analyses of hydrological and water quality simulations using the ESWAT model. Water Resources Management, 2009, 23(2): 303-24 CrossRef
  23. Di Luzio M, Mitchhell G, Sammons N. AVSWAT-X short tutorial Watershed Modeling using SWAT 2003. In: Proceedings of Third Conference on Watershed Management to Meet Water Quality Standards and Emerging TMDL. Georgia: Sheraton Atlanta, 2005, 5-
  24. Neitsch S L, Arnold J G, Kiniry J R, Srinivasan R, Williams J R. Soil and water assessment tool user’s manual version 2000. Water Resources Institute, College Station, Texas TWRI Report, TR-192. 2002
  25. Kim J G, Park Y S, Yoo D, Kim N, Engel B A, Kim S, Kim K S, Lim K J. Development of a SWAT patch for better estimation of sediment yield in steep sloping watersheds. Journal of the American Water Resources Association, 2009, 45(4): 963-72 CrossRef
  26. Heo S, Jun M S, Park S, Kim K S, Kang S K, Ok Y S, Lim K J. Analysis of soil erosion reduction ratio with changes in soil reconditioning amount for highland agricultural crops. Journal of Korean Society on Water Quality, 2008, 24: 185-94
  27. Santhi C, Arnold J G, Williams J R, Dugas W A, Srinivasan R, Hauck L M. Validation of the SWAT model on a large river basin with point and nonpoint sources. Journal of the American Water Resources Association, 2001, 37(5): 1169-188 CrossRef
  28. Lenhart T, Eckhardt K, Fohrer N, Frede H G. Comparison of two different approaches of sensitivity analysis. Physics and Chemistry of the Earth, 2002, 27: 645-54 CrossRef
  29. Moriasi D N, Arnold J G, van Liew MW, Bingner R L, Harmel R D, Veith T. Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of the ASABE, 2007, 50(3): 885-00
  
• 作者单位：Ganga Ram Maharjan (1)
  Youn Shik Park (2)
  Nam Won Kim (3)
  Dong Seok Shin (4)
  Jae Wan Choi (4)
  Geun Woo Hyun (5)
  Ji-Hong Jeon (6)
  Yong Sik Ok (7)
  Kyoung Jae Lim (1)
  
  1. GIS Environmental System Laboratory, Department of Regional Infrastructure Engineering, Kangwon National University, Chuncheon, 200-701, R. O. Korea
  2. Department of Agricultural and Biological Engineering, Purdue University, West Lafayette, IN, 47907, USA
  3. Water Resource Research Department, Korea Institute of Construction Technology, Goyang, 411-712, R. O. Korea
  4. National Institute of Environmental Research, Incheon, 404-708, R. O. Korea
  5. Department of Water Research Division, Gangwon Institute of Health and Environment, Chuncheon, 200-822, R. O. Korea
  6. Department of Environmental Engineering, Andong National University, Andong, 760-380, R. O. Korea
  7. Department of Biological Environment, Kangwon National University, Chuncheon, 700-71, R. O. Korea
  
• ISSN：2095-221X

文摘

A study was undertaken for the prediction of runoff flow from 0.8 ha field-sized agricultural watershed in South Korea using Soil and Water Assessment Tool (SWAT) sub-daily. The SWAT model with sub-daily configuration predicted flow from the watershed within the range of acceptable accuracy. The SWAT sub-daily simulations were carried out for a total of 18 rainfall events, 9 each for calibration and validation. Overall trend and extent of matching simulated flow for the rainfall events in 2007-008 with measured data during the calibration process were coefficient of determination (R 2) value of 0.88 and Nash and Sutcliffe Efficiency (E NS) value of 0.88. For validation, R 2 and E NS values were 0.9 and 0.84, respectively. Whereas R 2 and E NS values for simulation results using daily rainfall data were 0.79 and ?.01, respectively, that were observed to be out of acceptable limits for the model simulation. The importance of higher time resolution (hourly) precipitation records for flow simulation were evaluated by comparing R 2 and E NS with 15 min, 2 h, 6 h and 12 h precipitation data, which resulted in lower statistics with increases in time resolution of precipitation data. The SWAT sub-daily sensitivity analysis was performed with the consideration of hydraulic parameter and was found as in the rank order of CN2 (curve number), ESCO (soil evaporation compensation factor), GW_DELAY (ground water delay time), ALPHA_BF (base flow alpha factor), GWQMN (a threshold minimum depth of water in the shallow aquifer required for return flow to occur), REVAPMN (minimum depth of water in shallow aquifer for re-evaporation to occur), LAT_TIME (lateral flow travel time) respectively. These sensitive parameters were evaluated at 10% higher and lower values of the parameters, corresponding to 70.5% higher and 23.2% lower in simulated flow out from the SWAT model. From the results obtained in this study, hourly precipitation record for SWAT sub-daily with Green-Ampt infiltration method was proven to be efficient for runoff estimation at field sized watershed with higher accuracies that could be efficiently used to develop sitespecific Best Management Practices (BMPs) considering rainfall intensity, rather than simply using daily rainfall data.