International Journal of Advanced and Applied Sciences

Int. j. adv. appl. sci.

EISSN: 2313-3724

Print ISSN: 2313-626X

Volume 4, Issue 10  (October 2017), Pages:  15-19


Original Research Paper

Title: Analysis of rainfall intensity impact on the lag time estimation in tropical humid rivers

Author(s): Mohammed Seyam 1, *, Faridah Othman 2, Ahmed El-Shafie 2, Zaher Mundher Yaseen 3

Affiliation(s):

1Civil Engineering Programme, University College of Technology Sarawak, Sibu, Sarawak, Malaysia
2Civil Engineering Department, Faculty of Engineering, University of Malaya, Kuala Lumpur, Malaysia
3Civil and Structural Engineering Department, Faculty of Engineering and Built Environment, University Kebangsaan Malaysia, 43600 UKM Bangi, Selangor Darul Ehsan, Malaysia

https://doi.org/10.21833/ijaas.2017.010.003

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Abstract:

Rainfall intensity is considered as one of important hydrological variables affecting the lag time in tropical humid rivers. The lag time is the time interval from the time of maximum rainfall intensity to the time of the peak rate of stream flow. The main objective of this paper is to study the influence of the rainfall intensity and other related variables on the lag time between the upstream and downstream stations in tropical humid rivers. The lag time was estimated using 95 high rainfall-stream flow events. The Rainfall and water level data was collected from 4 upstream stations that were selected in accordance with data availability. The results indicated that the lag time is inversely proportional with rainfall intensity in a moderate strength relationship. The moderate relationship can be explained by the high complexity and the interaction of the other variables influencing the lag time. This approach is potential to be used in many future hydrological applications, especially those related to the surface water hydrology and river basin integrated management. 

© 2017 The Authors. Published by IASE.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Keywords: Hydrology, Rainfall, Surface water, Lag time

Article History: Received 10 January 2017, Received in revised form 20 July 2017, Accepted 23 July 2017

Digital Object Identifier: 

https://doi.org/10.21833/ijaas.2017.010.003

Citation:

Seyam M, Othman F,  El-Shafie A, and Yaseen ZM (2017). Analysis of rainfall intensity impact on the lag time estimation in tropical humid rivers. International Journal of Advanced and Applied Sciences, 4(10): 15-19

Permanent Link:

http://www.science-gate.com/IJAAS/V4I10/Seyam.html


References (25)

  1. Abon CC, David CPC, and Pellejera NEB (2011). Reconstructing the Tropical Storm Ketsana flood event in Marikina River, Philippines. Hydrology and Earth System Sciences, 15(4): 1283-1289. https://doi.org/10.5194/hess-15-1283-2011 
  2. Bezak N, Horvat A, and Šraj M (2015). Analysis of flood events in Slovenian streams. Journal of Hydrology and Hydromechanics, 63(2): 134-144. https://doi.org/10.1515/johh-2015-0014 
  3. Breemen MTJV (2008). Salt intrusion in the Selangor Estuary in Malaysia model—study with Delft3D. M.Sc. Thesis, University of Twente, Enschede, Netherlands.     
  4. Dvořáková Š, Kovář P, and Zeman J (2014). Impact of evapotranspiration on discharge in small catchments. Journal of Hydrology and Hydromechanics, 62(4): 285-292. https://doi.org/10.2478/johh-2014-0039 
  5. Evans J (1996). Straightforward statistics for the behavioral sciences. Brooks-Cole Publishing, Boston, USA.     
  6. Green JI and Nelson EJ (2002). Calculation of time of concentration for hydrologic design and analysis using geographic information system vector objects. Journal of Hydroinformatics, 4(2): 75-81.     
  7. Grimaldi S, Petroselli A, Tauro F, and Porfiri M (2012). Time of concentration: a paradox in modern hydrology. Hydrological Sciences Journal, 57(2): 217-228. https://doi.org/10.1080/02626667.2011.644244 
  8. Hassan AJ, Ghani AA, and Abdullah R (2004). Development of flood risk map using GIS for sg. selangor basin. National Hydraulic Research Institute of Malaysia, Malaysia. Available online at: redac.eng.usm.my/html/publish/2006_11.pdf 
  9. Li MH and Chibber P (2008). Overland flow time of concentration on very flat terrains. Journal of the Transportation Research Board, 2060: 133-140. https://doi.org/10.3141/2060-15 
  10. McMillan HK, Hreinsson EÖ, Clark MP, Singh SK, Zammit C, and Uddstrom MJ (2013). Operational hydrological data assimilation with the recursive ensemble Kalman filter. Hydrology and Earth System Sciences, 17(1): 21-38. https://doi.org/10.5194/hess-17-21-2013 
  11. Nelson BW (2002). An unusual turbidity maximum. Marine Science, 5: 483-497. https://doi.org/10.1016/S1568-2692(02)80035-3 
  12. Pavlovic SB and Moglen GE (2008). Discretization issues in travel time calculation. Journal of Hydrologic Engineering, 13(2): 71-79. https://doi.org/10.1061/(ASCE)1084-0699(2008)13:2(71) 
  13. Perugu M, Singam AJ, and Kamasani CSR (2013). Multiple linear correlation analysis of daily reference evapotranspiration. Water Resources Management, 27(5): 1489-1500. https://doi.org/10.1007/s11269-012-0250-7 
  14. Reusser DE, Blume T, Schaefli B, and Zehe E (2009). Analysing the temporal dynamics of model performance for hydrological models. Hydrology and Earth System Sciences, 13: 999-1018. https://doi.org/10.5194/hess-13-999-2009 
  15. Sabzevari T, Talebi A, Ardakanian R, and Shamsai A (2010). A steady-state saturation model to determine the subsurface travel time (STT) in complex hillslopes. Hydrology and Earth System Sciences, 14(6): 891-900. https://doi.org/10.5194/hess-14-891-2010 
  16. Saghafian B and Julien PY (1995). Time to equilibrium for spatially variable watersheds. Journal of Hydrology, 172(1-4): 231-245. https://doi.org/10.1016/0022-1694(95)02692-I 
  17. Samsudin R, Saad P, and Shabri A (2011). River flow time series using least squares support vector machines. Hydrology and Earth System Sciences, 15(6): 1835-1852. https://doi.org/10.5194/hess-15-1835-2011 
  18. Seyam M and Othman F (2014). The influence of accurate lag time estimation on the performance of stream flow data-driven based models. Water Resources Management, 28(9): 2583-2597. https://doi.org/10.1007/s11269-014-0628-9 
  19. Shafie A (2009). Extreme flood event: A case study on floods of 2006 and 2007 in Johor, Malaysia. Technical Report, Department of Civil and Environmental Engineering, Colorado State University, Fort Collins, Colorado, USA.     
  20. Simas MJ and Hawkins RH (1996). Lag time characteristics for small watersheds in the US. Water Resources Engineering, 98: 1290-1296.     
  21. Singh VP (1976). Derivation of time of concentration. Journal of Hydrology, 30(1-2): 147-165. https://doi.org/10.1016/0022-1694(76)90095-0 
  22. Singh VP (1988). Hydrologic systems: Rainfall-Runoff modeling. Prentice Hal, New Jersey, USA.     
  23. Subramaniam V (2004). Managing water supply In Selangor And Kuala Lumpur. THE Board of Engineers Malaysia, Kuala Lumpur, Malaysia.     
  24. Viessman W and Lewis GL (2003). Introduction to Hydrology. Prentice Hall India (P) Limited, India.     
  25. Yu B, Rose CW, Ciesiolka CCA, and Cakurs U (2000). The relationship between runoff rate and lag time and the effects of surface treatments at the plot scale. Hydrological Sciences Journal, 45(5): 709-726. https://doi.org/10.1080/02626660009492372