Advertisement

An Event-Based Sediment Yield and Runoff Modeling Using Soil Moisture Balance/Budgeting (SMB) Method

  • Sushindra Kumar GuptaEmail author
  • Jaivir Tyagi
  • Gunwant Sharma
  • A. S. Jethoo
  • P. K. Singh
Article
  • 10 Downloads

Abstract

The Soil Conservation Service Curve Number (SCS-CN) method is frequently used for the estimation of direct surface runoff depth from the small watersheds. Coupling the SCS-CN method with the Soil Moisture Balance (SMB) method, new simple 2-parameters rainfall-runoff model and 3-parametrs rainfall-sediment yield models are derived for computation of runoff and sediment yield respectively. The proposed runoff (R2) and sediment yield (S2) models have been tested on a large set of rainfall-runoff and sediment yield data (98 storm events) obtained from twelve watersheds from different land use/land cover, soil and climatic conditions. The improved runoff (R2) and sediment yield (S2) models show superior results as compared to the existing Mishra et al. (S1) and original SCS-CN (R1) models. The results and analysis justify the use of the proposed models for field applications.

Keywords

Sediment yield model Rainfall-runoff model SMB Watershed 

Notes

Acknowledgements

Authors gratefully acknowledge the National Institute of Hydrology, Roorkee for providing the essential data for the study. The first author acknowledge the Ministry of Human Resource Development (MHRD), Government of India for providing research assistantship for carrying out his Ph.D. Research work.

Compliance with Ethical Standards

Conflict of Interest

We have no conflicts of interest to disclose.

References

  1. Agriculture Department (Soil Conservation Section) (1990) Project on hydrological and sedimentation monitoring - Mansara watershed, flood prone river Gomati, unpub. Govt. of Uttar Pradesh, IndiaGoogle Scholar
  2. Ajmal M, Waseem M, Ahn J, Kim T (2015) Improved runoff estimation using event-based rainfall-runoff models. Water Resour Manag 29:1995–2010CrossRefGoogle Scholar
  3. Barnett AP, Rogers J (1966) Soil physical properties related to runoff and erosion from artificial rainfall. Transactions of the ASAE, 9(1):123–0125Google Scholar
  4. Bogardi I, Bardossy A, Fogel M, Duckstein,L (1986) Sediment yield from agricultural watersheds. J Hydr Div, ASCE 112(1):64–70Google Scholar
  5. Blackmarr WA (1995) Documentation of hydrologic, geomorphic, and sediment transport measurements on the Goodwin creek experimental watershed, Northern Mississippi, for the period 1982–1993: preliminary release, Research report No. 3, US Department of Agriculture, Agricultural Research Service, Channel and Watershed Processes Research Unit, National Sedimentation Laboratory, Oxford, MSGoogle Scholar
  6. Bradford JM (1988) Erosional development of valley bottom gullies in the upper western United States, lecture notes, Training course on Soil Erosion and its Control, IRTCES, Beijing, ChinaGoogle Scholar
  7. Brocca L, Melone F, and Moramarco T (2008) On the estimation of antecedent wetness conditions in rainfall–runoff modelling. Hydrological Processes: 22(5): 629-642Google Scholar
  8. Channel and Watershed Processes Research Unit, National Sedimentation Laboratory, Oxford, MS Brocca L, Melone F, and Moramarco T (2008) On the estimation of antecedent wetness conditions in rainfall–runoff modelling. Hydrological Processes: 22(5): 629–642Google Scholar
  9. Chong SK, Teng TM (1986) Relationship between the runoff curve number and hydrologic soil properties. J Hydrol 84(1-2):1–7Google Scholar
  10. Ekern PS (1953) Problems of raindrop impact erosion. Agric. Engng., 23–25Google Scholar
  11. Garen DC, Moore DS (2005) Curve number hydrology in water quality modeling: Uses, abuses, and future directions. J American Water Resources Association, 41(2):377–388Google Scholar
  12. Greer JD (1971) Effect of excessive-rate rainstorms on erosion. Journal of soil and water conservation, Washington, 26:196–201Google Scholar
  13. Hadley RF, Lai R, Onstad CA, Walling DE, & Yair A (1985) Recent developments in erosion and sediment yield studies. UNESCO (IHP) Publication, Paris, FranceGoogle Scholar
  14. Hawkins DH (1973) Improved prediction of storm runoff curve numbers in mountain watersheds. J Irrig Drain Div ASCE 99(4):519–523Google Scholar
  15. Hjelmfelt AT (1980) Empirical investigation of curve number technique. J.Hydr Div, ASCE 106(9):1471–1476Google Scholar
  16. Kalin L, Hantush MM (2003) Evaluation of sediment transport models and comparative application of two watershed models. US Environmental Protection Agency, Office of Research and Development, National Risk Management Research LaboratoryGoogle Scholar
  17. Kalin L, Govindaraju RS, Hantush MM (2003) Effect of geomorphologic resolution on modeling of runoff hydrograph and sedimentograph over small watersheds. J Hydrol 276:89–111CrossRefGoogle Scholar
  18. Kalin L, Govindaraju RS, Hantush MM (2004) Development and application of a methodology for sediment source identification. I: Modified unit sedimentograph approach. J. Hydrologic Eng., ASCE 9 (3): 184–193Google Scholar
  19. Kelly GE, Edwards WM, Harrold LL (1975) Soils of the North Appalachian experimental watersheds, Miscellaneous Pub. No. 1296, US Department of Agriculture, Agricultural Research Service, Washington, DCGoogle Scholar
  20. Knisel WG (1980) CREAMS: A field scale model for chemicals, runoff and erosion from agricultural management systems, Cons. Res. Report No. 26, USDA-SEA, Washington, DC, 643 pGoogle Scholar
  21. Kothyari UC, Tiwari AK, Singh R (1996) Temporal variation of sediment yield. J. Hydrol Engg, 1(4):169–176Google Scholar
  22. Kothyari UC, Jain SK (1997) Sediment yield estimation using GIS. Hydrological Sciences Journal, 42(6):833–843Google Scholar
  23. Leonard RA, Knisel WG, Still DA (1987) GLEAMS: Groundwater Loading Effects Of Agricultural Management Systems. Trans ASAE 30:1403–1418Google Scholar
  24. Li Y, Buchberger SG, Sansalone JJ (1999) Variably saturated flow in storm-water partial exfiltration trench. J Environ Eng, ASCE 125 (6):556–565Google Scholar
  25. Marquardat DW (1963) An algorithum for least-squares estimation of nonlinear parameters. J Soc Ind Appl Math 11(2):431–441CrossRefGoogle Scholar
  26. Michel C, Andréassian V, Perrin C (2005) Soil conservation service curve number method: how to mend a wrong soil moisture accounting procedure? Water Resour Res 41(2):1–6CrossRefGoogle Scholar
  27. Mishra SK, Nema RK (1998) A modified SCS-CN method for watershed modeling’, in Proceedings of International Conference on Watershed Management and Conservation, Central Board of Irrigation and Power, New Delhi, India, December 8–10Google Scholar
  28. Mishra SK Singh VP (1999) Another look at SCS-CN method. J Hydrol Eng 257–264Google Scholar
  29. Mishra SK, Singh VP (2002) SCS-CN method. Part I: derivation of SCS-CN-based modelsGoogle Scholar
  30. Mishra SK, Singh VP (2003) Soil Conservation Service Curve Number (SCS-CN) Methodology, Kluwer Academic Publishers, Dordrecht, The Netherlands, ISBN 1-4020-1132–6Google Scholar
  31. Mishra SK, Jain MK, Bhunya PK, and Singh VP (2005) Field applicability of the SCS-CN-based Mishra–Singh general model and its variants. Water Resour Manag 19(1):37-62.Google Scholar
  32. Mishra SK, Sahu RK, Eldho TI, Jain MK (2006a) A generalized relation between initial abstraction and potential maximum retention in SCS-CN-based model. Int J River Basin Manag 4(4):245–253CrossRefGoogle Scholar
  33. Mishra SK, Tyagi JV, Singh VP, Singh R (2006b) SCS-CN-based modeling of sediment yield. J Hydrol 324(1-4):301–322CrossRefGoogle Scholar
  34. Moriasi DN. Arnold JG, Van Liew MW, Bingner RL, Harmel RD, Veith TL (2007) Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of the ASABE, 50(3):885–900Google Scholar
  35. Nash JE, Sutcliffe JV (1970) River flow forecasting through conceptual models, part I - a discussion of principles. J Hydrol 10:282–290CrossRefGoogle Scholar
  36. Ragan RM, Jackson TJ (1980) Runoff synthesis using Landsat and SCS model. J Hydr Div, ASCE, 106(ASCE 15387)Google Scholar
  37. Ritter A, Muñoz-Carpena R (2013) Performance evaluation of hydrological models: Statistical significance for reducing subjectivity in goodness-of-fit assessments. J Hydro, 480:33–45Google Scholar
  38. Rode M, Frede HG (1997) Modification of AGNPS for agricultural land and climate conditions central Germany. J Environ Qua. 26(1):165–172Google Scholar
  39. SCS (1956) In Hydrology, National Engineering Handbook, Supplement A, Section 4, Chapter 10, Soil Conservation Service, USDA, Washinghatan W.C.Google Scholar
  40. Sahu RK, Mishra SK, Eldho TI (2007) An advanced soil moisture accounting procedure for SCS curve number method. Hydrol Process 21:2872–2881CrossRefGoogle Scholar
  41. Sahu RK, Mishra SK, Eldho TI (2010) An improved AMC-coupled runoff curve number model. Hydrol Process 24(20):2834–2839CrossRefGoogle Scholar
  42. Sahu RK, Mishra SK, Eldho TI (2012) Improved storm duration and antecedent moisture condition coupled SCS-CN concept-based model. J Hydrologic Eng, ASCE 17(11):1173–1179CrossRefGoogle Scholar
  43. Sansalone JJ, Buchberger SG (1997) Partitioning and first flush of metals in urban roadway storm water. J Environ Eng, ASCE 123(2):134–143Google Scholar
  44. Sansalone JJ, Koran JM, Smithson JA, Buchberger SG (1998) Physical characteristics of urban roadway solids transported during rain events. J Environ Eng, ASCE 125(6):556–565Google Scholar
  45. Santhi C, Arnold JG, Williams JR, Dugas, WA, Srinivasan R, Hauck LM (2001) Validation of the SWAT model on a large river basin with point and non-point sources. J American Water Resources Association, 37(5):1169–1188Google Scholar
  46. Seibert J (2001) On the need for benchmarks in hydrological modelling. Hydrol Process 15(6):1063–1064CrossRefGoogle Scholar
  47. Shi ZH, Chen LD, Fang NF, Qin DF, Cai CF (2009) Research on the SCS-CN initial abstraction ratio using rainfall-runoff event analysis in the three gorges area, China. Catena 77(1):1–7CrossRefGoogle Scholar
  48. Shi W, Huang M, Gongadze K, Wu L (2017) A modified SCS-CN method incorporating storm duration and antecedent soil moisture estimation for runoff prediction. Water Resour Manag 31(5):1713–1727Google Scholar
  49. Singh VP (1988) Hydrologic systems: watershed modeling (Vol. 2). Prentice Hall.Google Scholar
  50. Singh PK, Bhunya PK, Mishra SK, Chaube UC (2008) A sediment graph model based on SCS-CN method. J Hydrol 349:244–255CrossRefGoogle Scholar
  51. Singh PK, Mishra SK, Berndtsson R, Jain MK, Pandey RP (2015) Development of a modified SMA based MSCS-CN model for runoff estimation. Water Resour Manag 29(11):4111–4127CrossRefGoogle Scholar
  52. Tien H, Wu J, Hall A, Bonta JV (1993) Evaluation of runoff and Erosion models. J Irrigation Drainage Eng, ASCE 119(4):364–382Google Scholar
  53. Tyagi JV, Rai SP, Qazi N, Singh MP (2014) Assessment of discharge and sediment transport from different forest cover types in lower Himalaya using Soil and Water Assessment Tool (SWAT). Int J Water Resour Environ Eng, 6(1):49–66Google Scholar
  54. SWCD (Soil and Water Conservation Division) (1991) Evaluation of hydrologic data (Vol I and Vol II), indo-German bilateral project on watershed management, Ministry of Agriculture, Govt. of India, New Delhi, IndiaGoogle Scholar
  55. SWCD (Soil and Water Conservation Division) (1993) Evaluation of hydrologic data (Vol I and Vol II), indo-German bilateral project on watershed management, Ministry of Agriculture, Govt. of India, New Delhi, IndiaGoogle Scholar
  56. SWCD (Soil and Water Conservation Division) (1994) Evaluation of hydrologic data (Vol I and Vol II), indo-German bilateral project on watershed management, Ministry of Agriculture, Govt. of India, New Delhi, IndiaGoogle Scholar
  57. SWCD (Soil and Water Conservation Division) (1995) Evaluation of hydrologic data (Vol 1), Indo-German bilateral project on watershed management, Ministry of Agriculture, Govt of India, New Delhi, IndiaGoogle Scholar
  58. SWCD (soil and water conservation division) (1996) evaluation of hydrologic data (Vol. III), indo-German bilateral project on watershed management, Ministry of Agriculture, Govt. of India, New Delhi, IndiaGoogle Scholar
  59. Tyagi JV, Mishra SK, Singh R, Singh VP (2008) SCS-CN based time-distributed sediment yield model. J Hydrol 352:388–403CrossRefGoogle Scholar
  60. Van Mullen JA (1989) Runoff and peak discharge using green Ampt infiltration model. J Hydr Div, ASCE 102(9):1241–1253Google Scholar
  61. Van Liew MW, Saxton K.E (1984) Dynamic simulation of sediment discharge from agricultural watersheds. TransASAE 27(4):678–682Google Scholar
  62. Van Liew MW, Arnold JG, and Garbrecht JD (2003) Hydrologic simulation on agricultural watersheds: Choosing between two models. Transactions of the ASAE, 46(6):1539Google Scholar
  63. Verma S, Mishra SK, Singh A, Singh PK, Verma RK (2017) An enhanced SMA based SCS-CN inspired model for watershed runoff prediction. Environ Earth Sci, 76:736,1–20Google Scholar
  64. Wood MK, Blackburn WH (1984) An evaluation of the hydrologic soil groups as used in the SCS runoff method on rangelands. J American Water Resour Assoc, 20(3):379–389Google Scholar
  65. Williams JR, LaSeur WV (1976) Water yield model using SCS curve numbers. J Hydr Div ASCE, 102:1241–1253Google Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  • Sushindra Kumar Gupta
    • 1
    Email author
  • Jaivir Tyagi
    • 2
  • Gunwant Sharma
    • 1
  • A. S. Jethoo
    • 1
  • P. K. Singh
    • 3
  1. 1.Department of Civil EngineeringMalaviya National Institute of TechnologyJaipurIndia
  2. 2.Surface Water Hydrology DivisionNational Institute of HydrologyRoorkeeIndia
  3. 3.Water Resources System DivisionNational Institute of HydrologyRoorkeeIndia

Personalised recommendations