Comparing the Performance of Different Loss Models in the Rainfall – Runoff Modeling of the Karoon III Basin

Document Type : Research Paper

Authors

Abstract

Different loss models of Soil and Conservation Services (SCS), Green and Ampt, Initial – Constant, Deficit – Constant, Constant Fraction, Exponential and Soil Moisture Accounting (SMA) methods have been compared using the HEC-HMS event-based rainfall–runoff simulation with respect to the effect of precipitation loss on the runoff generation in the Karoon III basin. The SMA method, with the maximum N.S., 0.81 and 0.69 and the minimum PW RMSE, 148 and 143 in calibration and verification was the best in the stream flow simulation and the SCS and Constant Fraction were better than others in validation, following the SMA. A comparison between the simulated and observed key variables showed that the SMA method with minimum average percent difference of simulated volume, peak flow and hydrograph time of peak occurrence, was the best one in calibration. In verification, the SMA was the best in hydrograph volume simulation, SCS and SMA in the peak flow, and Initial and Constant and Green and Ampt in time of peak occurrence.

Keywords


8. Ayka, A. 2008. Hydrological models
comparison for estimation of floods in
the Abaya-Chamo sub-basin M.S. thesis,
Addis Ababa University, School of
Graduate Studies.
9. Bennett, T.H. 1998. Development and
application of a continuous soil moisture
accounting algorithm for the Hydrologic
Engineering Center Hydrologic
Modeling System (HEC-HMS). MS
thesis, Dept. of Civil and Environmental
Engineering, University of California,
Davis.
10. Beven, k.j. 2005. Rainfall-runoff
modeling: Introduction, 1857-1868 In:
M.G. Anderson and J.R. McDonnell,
(Eds). Encyclopedia of hydrological
sceinces. 3: Wiley Publication.
11. Boughton, W., and O. Droop. 2003.
Continuous simulation for design flood
estimation—a review, Environ. Model.
& Software 18: 309–318.
12. Bondelid, T.R., R.H. McCuen, and T.H.
Jackson. 2007. Sensitivity of SCS
models to curve number variation. J.
Am. Water Resour. Associ. 18: 111–
116.
13. Boughton, W.C. 1989. A review of the
USDA SCS curve number method. Aust.
J. Soil Res. 27: 511 - 523.
14. Chahinian, N., R. Moussa, P. Andrieux,
and M. Voltz. 2005. Comparison of
infiltration models to simulate flood
events at the field scale. J. Hydrol. 306:
191–214.
15. Cunderlik, J.M., and S.P. Simonovic.
2004. a. Selection of calibration and
verification data for the HEC-HMS
hydrologic model, CFCAS project:
Assessment of water resources risk and
vulnerability to changing climatic
conditions, The University of Western
هجلِی هٌْذسی هٌاتع آب / سال ششن / زهستاى 1392 35
Ontario, Department of civil and
environmental engineering, Project
Report II.
16. Cunderlik, J.M., and S.P. Simonovic.
2004. b. Calibration, verification and
sensitivity analysis of the HEC-HMS
hydrologic model, CFCAS project:
Assessment of water resources risk and
vulnerability to changing climatic
conditions, The University of Western
Ontario, Department of Civil and
Environmental Engineering, Project
Report IV.
17. Cunge, J.A. 1969. On the subject of a
flood propagation computation method,
J. hydrau. Res. 7: 205-230.
18. Cydzik, K., and T.S. Hogue. 2009.
Modeling post fire response and
recovery using the Hydrologic
Engineering Center Hydrologic
Modeling System (HEC-HMS). J. Am.
Water Resour. Associ. 45: 702–714.
19. Flemming, M., and V. Neary. 2004.
Continuous hydrologic modeling study
with the hydrologic modeling system. J.
Hydrol. Eng. 9:175-183.
20. Garcia, A., A. Sainz, J.A. Revilla, C.
Alvarez, J.A. Juanes, and A. Puente.
2008. Surface water resources
assessment in scarcely gauged basins in
the north of Spain, J.hydrol. 356: 312–
326.
21. Golian, S., B. Saghafian, M. Elmi, and
R. Maknoon. 2010. Derivation of
probabilistic thresholds of spatially
distributed rainfall for flood forecasting.
Water Resour. Manage. 24: 3547-3559.
22. Grimaldi, S., A. Petroselli, and F. Nardi.
2012. A parsimonious geomorphological
unit hydrograph for rainfall–runoff
modelling in small ungauged basins,
Hydrol. Sci. J. 57: 73-83.
23. King, K.W., J.G. Arnold, and R.L.
Bingner. 1999. Comparison of Greenampt and curve number methods on
Goodwin Creek Watershed using
SWAT, Trans. ASAE. 42: 919-925.
24. Mc Lin, S.G., E.P. Springer, and L.G.
Lane. 2001. Predicting floodplain
boundary changes following the Cerro
Grande wildfire. Hydrol. Proc. 15:
2967–2980.
25. Mishra, S.K. and V.P. Singh. 2004.
Validity and extension of the SCS-CN
method for computing infiltration and
rainfall-excess rates. Hydrol.Proc. 18:
3323–3345.
26. Pincovschi, I., D.E. Gogoase Nistoran, I.
Armas, and E. Rotaru. 2007. Use of
HEC-HMS rainfall-runoff model in the
Subcarpathian Prahova Valley-Romania,
Geophysi. Res. Abst. 9: 05982.
27. Ponce, V.M. and R.H. Hawkins. 1996.
Runoff curve number: has it reached
maturity? J. hydrol.eng. 1: 11-19.
28. Quan, N.H. 2006. Rainfall-runoff
modeling in the ungauged Can Le
catchment, Saigon River Basin, M.S.
thesis, International Institute for GeoInformation sci. Earth observation.
Enschede, the Netherlands.
29. Schindler, H. and G. Gutknecht. 2006. A
tool for rapid flood Warning based on
HEC-HMS. Geophys. Res. Abst. 8:
08344.
30. Shi, Z.-H., L.-D.Chen, N.-F.Fang, D.-F.
Qin and Ch.-F. CAI. 2009. Research on
the SCS-CN initial abstraction ratio
using rainfall-runoff event analysis in
the Three Gorges Area, China Catena
77: 1-7.
31. US-ACE. 2000. Hydrologic modeling
system HEC-HMS. Technical reference
manual. US Army Corps of Engineers.
Hydrologic Engineering Center.
32. US-ACE. 2010. Hydrologic modeling
system HEC-HMS. User’s manual,
Version 3.5. US Army Corps of
Engineers, Hydrologic Engineering
Center.