PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Clarifcation of issues and long-duration hydrologic simulation SCS-CN-based proxy modelling

Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The aims of this paper are to (I) clarify some issues related to the popular rainfall–runoff SCS-CN (Soil Conservation Service Curve Number) methodology and (II) propose enhanced SCS-CN inspired models for simulation of long-duration (viz., bimonthly, monthly, seasonally, and annually) rainfall-generated runoff and compares its performance with the existing SCS-CN models and Mishra and Singh 1999 model. Issues of SCS-CN are: (a) both C (runoff coefficient) and CN (curve number) with P (rainfall) in contrast to that exhibited by field data, (b) F (infiltration) with Q (direct runoff), (c) Ia (initial abstraction) with S (potential maximum retention), and (d) CN that is also taken as an index of runoff potential. The performance of the proposed SCS-CN inspired models (M3-M8), the existing SCS-CN models (M1 and M2), Mishra and Singh 1999 model (M9), and a special case of M9 that hypothesizes that initial abstraction coefficient (λ)=0 (M10) are tested using rainfall–runoff data of four different agro-climatic river basins in Ethiopia. The performance of the models is evaluated using three statistical criteria involving NSE, RSR, and PBIAS. The resulting high NSE values and lowest RSR and PBIAS for the proposed models reveal that proposed models performed better to different (majority) duration datasets than the existing models. Similarly, the proposed models, when employed to the observed datasets of different timescales, performed satisfactorily in both calibration and validation for all watersheds, underlining the efficacy of the proposed models in field applications.
Czasopismo
Rocznik
Strony
729--756
Opis fizyczny
Bibliogr. 66 poz.
Twórcy
  • Department of Water Resources Development and Management, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand 247 667, India
  • Department of Water Resources Development and Management, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand 247 667, India
Bibliografia
  • 1. Ajmal M, Waseem M, Wi S, Kim TW (2015) Evolution of a parsimonious rainfall-runoff model using soil moisture proxies. J Hydrol 530:623–633
  • 2. Aragaw HM, Mishra SK (2021) Runoff curve number-potential evapotranspiration-duration relationship for selected watersheds in Ethiopia. Model Earth Syst Environ 6:1–12
  • 3. Aragaw HM, Goel MK, Mishra SK (2021) Hydrological responses to human-induced land use/land cover changes in the Gidabo River basin Ethiopia. Hydrol Sci J 66(4):640–655
  • 4. Arnold JG, Srinivasan R, Muttiah RS, Williams JR (1998) Large area hydrologic modeling and assessment part I: model development. J Am Water Resour Assoc 34(1):73–89
  • 5. Beretta L, Santaniello A (2016) Nearest neighbor imputation algorithms: a critical evaluation. BMC Med Inf Decision Mak 16(Suppl 3):871
  • 6. Bhunya PK, Jain SK, Singh PK, Mishra SK (2010) A simple conceptual model of sediment yield. Water Resour Manage 24(8):1697–1716
  • 7. Chakraborty S, Pandey RP, Mishra SK, Chaube UC (2015) Relation between runoff curve number and irrigation water requirement. Agric Res 4(4):378–387
  • 8. Chin DA (2018) On relationship between curve numbers and phi indices. Water Sci Eng 11(3):187–195
  • 9. Devia GK, Ganasri BP, Dwarakish GS (2015) A review on hydrological models. Aquatic Procedia 4:1001–1007
  • 10. Durbude DG, Jain MK, Mishra SK (2011) Long-term hydrologic simulation using SCS-CN-based improved soil moisture accounting procedure. Hydrol Process 25(4):561–579
  • 11. Garen DC, Moore DS (2005) Curve number hydrology in water quality modeling: Uses, abuses, and future directions. J Am Water Resour Assoc 41(2):377–388
  • 12. Geetha K, Mishra SK, Eldho TI, Rastogi AK, Pandey RP (2007) Modifications to SCS-CN method for long-term hydrologic simulation. J Irrig Drain Eng 133(4):395–406
  • 13. Geetha K, Mishra SK, Eldho TI, Rastogi AK, Pandey RP (2008) SCS-CN-based continuous simulation model for hydrologic forecasting. Water Resour Manage 22(2):165–190
  • 14. Gupta HV, Kling H, Yilmaz KK, Martinez GF (2009) Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling. J Hydrol 377(1–2):80–91
  • 15. Haith DA, Shoenaker LL (1987) Generalized watershed loading functions for stream flow nutrients. JAWRA J Am Water Resour Assoc 23(3):471–478
  • 16. Hapuarachchi HAP, Wang QJ, Pagano TC (2011) A review of advances in flash flood forecasting. Hydrol Process 25(18):2771–2784
  • 17. Hawkins RH (1993) Asymptotic determination of runoff curve numbers from data. J Irrig Drain Eng 1(August):334–345
  • 18. Hawkins RH, Jiang R, Woodward DE, Hjelmfelt AT, Van Mullem JA, Quan QD (2003) Runoff curve number method: examination of the initial abstraction ratio. World Water Environ Resour Congress 35:691–700
  • 19. Hawkins RH, Ward TJ, Woodward DE, Van Mullem JA (2009) Curve number hydrology: state of the practice. American Society of Civil Engineers, Virginia
  • 20. Hooshyar M, Wang D (2016) An analytical solution of Richards’ equation providing the physical basis of SCS curve number method and its proportionality relationship. Water Resour Res 52:6611–6620
  • 21. Jain MK, Mishra SK, Babu PS, Venugopal K, Singh VP (2006a) Enhanced runoff curve number model incorporating storm duration and a nonlinear IA-S relation. J Hydrol Eng 11(6):631–635
  • 22. Jain MK, Mishra SK, Babu PS, Venugopal K (2006b) On the Ia - S relation of the SCS-CN method. Nord Hydrol 37(3):261–275
  • 23. Jain MK, Mishra SK, Singh VP (2006c) Evaluation of AMC-dependent SCS-CN-based models using watershed characteristics. Water Resour Manage 20(4):531–552
  • 24. Jain MK, Durbude DG, Mishra SK (2012) Improved CN-based long-term hydrologic simulation model. J Hydrol Eng 17(11):1204–1220
  • 25. Kannan N, Williams SJR, Arnold JG (2007) Development of a continuous soil moisture accounting procedure for curve number methodology and its behaviour with different evapotranspiration methods. Hydrol Processes 2274:2267–2274
  • 26. Knisel, W. G., 1980. CREAMS: a field scale model for Chemicals, runoff, and erosion from agricultural management systems [USA]. Dept. of Agriculture, Science and Education Administration.
  • 27. Krause P, Boyle DP, Bäse F (2005) Comparison of different efficiency criteria for hydrological model assessment. Adv Geosci 5:89–97
  • 28. Lim KJ, Engel BA, Tang Z, Choi J (2006) Automated web GIS based hydrograph analysis tool, What. J Am Water Resour Assoc 1397(6):1407–1416
  • 29. 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):1–6
  • 30. Mishra SK, Singh VP (1999) Another look at SCS-CN Method. J Hydrol Eng 4(July):257–264
  • 31. Mishra SK, Singh VP (2003) Soil conservation service curve number (SCS-CN) methodology. Kluwer, Dordrecht, p 42
  • 32. Mishra SK, Singh VP (2004) Long-term hydrological simulation based on the soil conservation service curve number. Hydrol Process 18(7):1291–1313
  • 33. Mishra SK, Singh VP (2006) A relook at NEH-4 curve number data and antecedent moisture condition criteria. Hydrol Process 20(13):2755–2768
  • 34. Mishra SK, Jain MK, Singh VP (2004) Evaluation of the SCS-CN-based model incorporating antecedent moisture. Water Resour Manage 18(6):567–589
  • 35. Mishra SK, Jain MK, Bhunya PK, Singh VP (2005) Field applicability of the SCS-CN-based Mishra-Singh general model and its variants. Water Resour Manage 19(1):37–62
  • 36. Mishra SK, Sahu RK, Eldho TI, Jain MK (2006a) An improved Ia-S relation incorporating antecedent moisture in SCS-CN methodology. Water Resour Manage 20(5):643–660
  • 37. Mishra SK, Tyagi JV, Singh VP, Singh R (2006b) SCS-CN-based modeling of sediment yield. J Hydrol 324(1–4):301–322
  • 38. Mishra SK, Pandey RP, Jain MK, Singh VP (2008) A rain duration and modified AMC-dependent SCS-CN procedure for long duration rainfall-runoff events. Water Resour Manage 22(7):861–876
  • 39. Mishra SK, Rawat SS, Pandey RP, Chakraborty S, Jain MK, Chaube UC (2014) Relationship between runoff curve number and PET. J Hydrol Eng 19(5):355–365
  • 40. Mishra SK, Kumre SK, Pandey A (2019) SCS-CN method revisited in perspective of strange data. Int J Hydrol 3(4):488–498
  • 41. Moglen GE (2000) Effect of orientation of spatially distributed curve number in runoff calculations. Am Water Resour Assoc 36(6):1391–1400
  • 42. 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. Am Soc Agric Biol Eng 50(3):885–900
  • 43. Nash JE, Sutcliffe JV (1970) River flow forecasting through conceptual models part i–a discussion of principles*. J Hydrol 10(2):282–290
  • 44. Neitsch SL, Arnold JG, Kiniry JR, Williams JR, and King KW (2002) Soil and water assessment tool (SWAT): theoretical documentation, version 2000. Texas Water Resources Institute, College Station, Texas TWRI Report TR-191.
  • 45. Pérez-Sánchez J, Senent-Aparicio J, Segura-Méndez F, Pulido-Velazquez D, Srinivasan R (2019) Evaluating hydrological models for deriving water resources in peninsular Spain. Sustainability 11(10):1–36
  • 46. Ponce VM, Hawkins RH (1996) Runoff curve number: Has it reached maturity? J Hydrol Eng 2(3):145–148
  • 47. Rallison RE (1980) Origin and Evolution of the SCS runoff equation. In: A.S.C.E. Irrig. and Drain. Symp. on Watershed Management. New York: A.S.C.E., 912–924.
  • 48. Sahu RK, Mishra SK, Eldho TI, Jain MK (2007) An advanced soil moisture accounting procedure for SCS curve number method. Hydrol Process 2274:2267–2274
  • 49. Sahu RK, Mishra SK, Eldho TI (2010) An improved AMC-coupled runoff curve number model. Hydrol Process 24(20):2834–2839
  • 50. Satheeshkumar S, Venkateswaran S, Kannan R (2017) Rainfall–runoff estimation using SCS–CN and GIS approach in the Pappireddipatti watershed of the Vaniyar sub basin, South India. Modeling Earth Systems and Environment 3(1):1–8
  • 51. SCS, 1956. National Engineering Handbook, Section 4 Hydrology. Washington, DC.
  • 52. Seibert J (2001) On the need for benchmarks in hydrological modelling. Hydrol Process 15(6):1063–1064
  • 53. Sharpley AN and Williams J (1990) EPIC-Erosion/Productivity Impact Calculator. I: Model documentation. II: User manual. Technical Bulletin-United States Department of Agriculture.
  • 54. 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 Manage 31(5):1713–1727
  • 55. Singh VP, Frevert DK, Treviño MA, Meyer SP, Rieker JD (2006) The hydrologic modeling inventory. a cooperative research effort. Watershed Manag Op Manag 132(2):98–103
  • 56. Subramanya K (2013) Engineering Hydrology. Fourth Ed. New Delhi: (India) Pvt. Ltd.
  • 57. Tedela NH, McCutcheon SC, Campbell JL, Swank WT, Adams MB, Rasmussen C (2012a) Curve numbers for nine mountainous eastern united states watersheds: seasonal variation and forest cutting. J Hydrol Eng 17(11):1199–1203
  • 58. Tedela NH, McCutcheon SC, Rasmussen TC, Hawkins RH, Swank WT, Campbell JL, Adams MB, Jackson R, Tollner EW (2012b) Runoff curve numbers for 10 small forested watersheds in the mountains of the eastern united states. J Hydrol Eng 17(11):1188–1198
  • 59. Thornthwaite CW (1948) An approach toward a rational classification of climate C. Geogr Rev 38(1):55–94
  • 60. Tyagi JV, Mishra SK, Singh R, Singh VP (2008) SCS-CN based time-distributed sediment yield model. J Hydrol 352(3–4):388–403
  • 61. 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(21):1–20
  • 62. Verma RK, Verma S, Mishra SK, Pandey A (2021) SCS-CN-Based improved models for direct surface runoff estimation from large rainfall events. Water Resour Manage 35:2149–2175
  • 63. White D (1988) G K I D - B a s e d application of runoff curve numbers. Water Resour Plann Manag 114(6):601–612
  • 64. Young RA, Onstad CA, Bosch DD, Anderson WP (1989) AGNPS: a nonpoint-source pollution model for evaluating agricultural watersheds. Soil Water Conserv 44(2):168–173
  • 65. Yuan Y, Mitchell JK, Hirschi MC, Cooke RAC (2001) Modified SCS curve number method for predicting subsurface drainage flow. Trans Am Soc Agric Eng 44(6):1673–1682
  • 66. Zhou S-M, Warrington DN, Lei T-W, Lei Q-X, Zhang M-L (2015) Modified CN method for small watershed infiltration simulation. J Hydrol Eng 20(9):04014095
Uwagi
PL
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-9c5d043d-012d-4c52-a842-16e2b5584611
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.