Desert Ecosystem Engineering Journal

Desert Ecosystem Engineering Journal

Assessment and Sensitivity Analysis of Effective Parameters involved in Estimating Coastal Urban Areas’ Concentration Time: A Case Study of Bandar Abbass City, Iran

Document Type : Original Article

Authors
Maryam Heydarzadeh 1
Ahmad Nohegar 2
1 Assistant Professor Water engineering, Minab higher Education center, University of Hormozgan, Iran.
2 Professor, Faculty of environment, Tehran University
10.22052/jdee.2021.240308.1069
Abstract
This study set out to introduce the quantitative analysis of open surface water systems located at Bandar Abbass in southern Iran, seeking to identify the best applicable formulas for urban catchment and determine the sensitivity index in each formula. To this end, the observed concentration-time was compared with twenty-two empirical formulas already developed for concentration time. Moreover, the sensitivity index was assessed for each variable involved in formulas regarding the concentration time. The study's results indicated that from among all methodologies used in Gorsozan estuary, the F.A.A. method best fitted the concentration-time with the N.S. and RMSE values reported as being 0.66 and 1.61, respectively, and the Henderson and Wooding method best suited the Seyed Kamel estuary, with the N.S. and RMSE values found to be 0.892 and 2.541, respectively. Furthermore, The Yen and Chow's method with the N.S. and RMSE values of 0.88 and 1.15, and the Duran &Rangan method with the N.S. and RMSE values of -0.42 and 31.72 were the best results found for the overland time in Gorsozan and Seyed Kamel estuaries. Also, the results for the sensitivity index indicated that any decline in variables such as length, slope, and N Manning had a significant impact on the concentration-time. In addition, changes of slope and N Manning values in all overland-flow formulas considerably affected the low-slope surfaces.
Keywords
Concentration Time
Overland Time
Sensitivity index
Urban Area
Bandar Abbass
  1. Álvarez, A.G., Pérez, J.M., Zúñiga, B.M., Viloria-Marimón, O.M., Tesfagiorgis, K., Mouthón-Bello, J., 2020. Assessing the Performance of Different Time of Concentration Equations in Urban Ungauged Watersheds: Case Study of Cartagena de Indias, Colombia. Hydrology 2020, 7, 47; doi: 10.3390/ hydrology 7030047
  2. Abdul-Aziz, O.I., Al-Amin, S., 2016. Climate, land use and hydrologic sensitivities of stormwater quantity and quality in a complex coastal-urban watershed. Urban Water Journal, DOI: 10.1080 /1573062X .2014.991328.
  3. Ascough, J. C., Flanagan, D. C., Nearing, M. A., Engel, B.A., 2013. Sensitivity and First-order/monte Carlo uncertainty analysis of the Wepp Hillslope Erosion Model. American Society of Agricultural and Biological Engineers. Vol. 56(2): 437-452. ISSN 2151-0032.
  4. Aronica, G.T., Candela, A., 2007. Derivation of flood frequency curves in poorly gauged Mediterranean catchments using a simple stochastic hydrological rainfall–runoff model. Journal of Hydrology, 347, 132–142.
  5. Chow, V.T., 1962. Hydrologic determination of waterway areas for the design of drainage structures in small drainage basins. Engineering Experiment Station Bulletin n.462. Urbana, Ill.: University of Illinois College of Engineering, 104 p.,
  6. Cea, L., Legout, C., Darboux, F., Esteves, M., Nord, G., 2014. Experimental validation of a 2D overland flow model using high resolution water depth and velocity data. J. Hydrol. 513, 142e153. http://dx.doi.org/10.1016/jhydrol.2014.03.052.
  7. Dearden, R.A., Price, S.J., 2012. A Proposed Decision Making Framework for a National Infiltration
  8. Dooge, J.C.I., 1965. Synthetic unit hydrographs based on triangular inflow.1965, Iowa State University, 1956. 103 p. Thesis
  9. Duan, W., Takara, K., He, B., Luo, P., Nover, D., Yamashiki, Y., 2013. Spatial and temporal trends in estimates of nutrient and suspended sediment loads in the Ishikari River, Japan, 1985 to 2010. Sci. Total Environ. 2013, 461–462, 499–508. [CrossRef]
  10. Duan, W., He, B., Nover, D., Fan, J., Yang, G., Chen, W., Meng, H., Liu, C., 2016. Floods and associated socioeconomic damages in China over the last century. Nat. Hazards 2016, 82, 401–413. [CrossRef]
  11. De Almeida, I.K., Almeida, A.K., Steffen, J.L., Sobrinho, T.A., 2016. Model for Estimating the Time of Concentration in Watersheds. Water Resour Manage DOI 10.1007/s11269-016-1383-x.
  12. Fang, X., Thompson, D., Cleveland, T., Pradhan, P., Malla, R., 2008. Time of concentration Estimated Using Watershed Parameters Determined by automated and Manual Methods, Journal of Irrigation and Drainage Engineering, April 2008, Vol. 134, No. 2, p 202-211. (doi: 10.1061/(ASCE)0733-9437 (2008) 134:2(202))
  13. Federal Emergency Management Agency (FEMA), 2019. Guidance for Flood Risk Analysis and Mapping. In Hydrology: Rainfall-Runoff Analysis; U.S. Department of Homeland Security: Washington, DC, U.S.A., 2019.
  14. Gwenzi, W., Nyamadzawo, G., 2014. Hydrological impacts of urbanization and urban roof water harvesting in water-limited catchments: a review.2014, Environmental Processes, 1:573–593. Doi: 10.1007/s40710-014-0037-3
  15. Guermond, Y., 2008. the modeling process in geography. Wiley, New York
  16. Geberemariam, T.K., 2015. Urban Drainage Infrastructure Design Model Calibration and Output Uncertainty Minimization, Are Model Users Pursuing Accuracy and Model Calibration?, International Journal of Scientific Engineering and Research (IJSER), Volume 3 Issue 11, P 117-125
  17. Hejazi, M., Markus, M., 2009. Impacts of Urbanization and Climate Variability on Floods in Northeastern Illinois. J. Hydrol. Eng. 14, 606–616.
  18. Hupet, F., Vanclooster, M., 2001. Effect of the sampling frequency of meteorological variables on the estimation of the reference evapotranspiration. Journal of Hydrology 2001, 243:192-204.
  19. Hoogestraat, G.K., 2011. Flood hydrology and dam-breach hydraulic analyses of four reservoirs in the Black Hills, South. Dakota: U.S. In Geological Survey Scientific Investigations Report 2011–5011; U.S. Geological Survey (USGS): Reston, VA, U.S.A., 2011.
  20. Hou, L.G., Zou, S.B., Xiao, H.L., Yang, Y.G., 2013. Sensitivity of the reference evapotranspiration to key climatic variables during the growing season in the Ejina oasis northwest China. 2 (Suppl 1): S4. http:// www. springerplus. com/ content/2/S1/S4
  21. Heydarzadeh, M., Nohegar, A., Malekian, A., Khurani, A., 2017. Assessment and Sensitivity analysis quantity of runoff and drainage system in coastal urban area (Case study: Bandar Abbas coastal city). J. of Water and Soil Conservation, Vol. 24(3), 2017, http://jwsc.gau.ac.ir
  22. Jiang, Y., Liu, C., Li, X., Liu, L., Wang, H., 2015. Rainfall-runoff modeling, parameter estimation and sensitivity analysis in a semiarid catchment. 2015, Environmental Modelling & Software 67 (2015) 72e88.
  23. Konrad, C.P., 2014. Effects of urban development on floods. U.S. Geological survey fact sheet 076-03. http://pubs. usgs. gov /fs/ fs07603. Accessed 4 July 2014.
  24. Kirpich, T.P., 1940. Time of Concentration of Small Agricultural Watersheds. Journal of Civil Engineering, v.10, n.6, p. 362
  25. Kang, J.H., Kayhanian, M., Stenstorm, M.K., 2008. Predicting the existence of storm water first flush from the time of concentration. Water Research, v.42, p. 220-228.
  26. Koutroulis, A.G., Tsanis, I.K., 2010. A method for estimating flash flood peak discharge in a poorly gauged basin: Case study for the 13–14 January 1994 flood, Giofiros basin, Crete Greece. Journal of Hydrology, 385, 150–164.
  27. Liang, J., Melching, C.S., 2012, Comparison of Computed and Experimentally Assessed Times of Concentration for a V-Shaped Laboratory Watershed. 2012, Journal of Hydrologic Engineering, v. 17, n. 12, p. 1389 - 1396
  28. Lumbroso, D., Gaume, E., 2012. Reducing the uncertainty in indirect estimates of extreme flash flood discharges. J. Hydrol. 414e415, 16e30. http: //dx.doi.org /10.1016/ j.jhydrol. 2011. 08.048.
  29. Li, M.H., Chibber, P., 2008. Overland flow time of concentration on very flat terrains, Trans Res Rec 2060:133–140
  30. Li, X., Fang, X., Li, J., K.C. M., Gong, Y., Chen, G., 2018. Estimating Time of Concentration for Overland Flow on Pervious Surfaces by Particle Tracking Method. Water 2018, 10, 379; doi: 10.3390 /w10040379
  31. Mata-lima, H., Vargas, H., Carvalho, J., Goncalves, M., Caetano, H., Marques, A., Raminhos, C., 2007. Comportamento hidrológico de bacias hidrográficas: integração de métodos e aplicação a um estudo de caso. Revista Escola de Minas, v. 60, n. 3.
  32. McCuen, R.H., Wong, S.L., Rawls, W.J., 1984. Estimating urban time of concentration. Journal of Hydraulic Engineering, v.110, n.7, p. 887-904, 1984.
  33. Mügler, C., Planchon, O., Patin, J., Weill, S., Silvera, N., Richard, P., Mouchea, E., Comparison of roughness models to simulate overland flow and tracer transport experiments under simulated rainfall at plot scale. Journal of Hydrology, 402 (1–2), 25–40. doi:10.1016/j.jhydrol.2011.02.032.
  34. Nohegar, A., Heydarzadeh, M., Malekian, A., 2019. Simulation and determine hydraulic capacity Gorsouzan estuary in Urban Flood Whit Use HEC-RAS Model (Case Study: Part of Bandar Abbas). Volume 44, Issue 4, winter 2019, P 703-720. Doi: 22059 /J.E.S.2019 .235118. 1007449.
  35. Papadakis, C.N., Kazan, M.N., 1986. Time of concentration in small rural watersheds. Technical Report 101/08/86/CEE. Civil Engineering, Department, University of Cincinnati, Ohio
  36. Pavlovic, S.B., Moglen, G.E., 2008. Discretization issues in travel time calculation.2008, Journal of Hydrologic Engineering, v. 13, n. 2, p. 71 -79
  37. Pluntke, T., Pluntke, D., Bernhofer, C., 2014. Reducing uncertainty in hydrological modeling in a data sparse region, Environ Earth Sci 72:4801–4816. DOI 10.1007/s12665-014-3252-3
  38. Perdikaris, J., Gharabaghi, B., Rudra, R., 2018. Reference Time of Concentration Estimation for Ungauged Catchments. Earth Sci. Res. 2018, 7, 58. [CrossRef]
  39. Rana, G., Katerji, N., 1998. A measurement based sensitivity analysis of the Penman-Monteith actual evapotranspiration model for crops of different height and in contrasting water status,Theoretical and Applied Climatology 1998, 60:141-149.
  40. Silveira, A.L.L., 2005. Performance of time of concentration formulas for urban and rural basins. Brazilian J. Water Resources, 10: 5-23.
  41. Smith, M.W., Cox, N.J., Bracken, L.J., 2007. Applying flow resistance equations to overland flows. Prog. Phys. Geogr. 31(4), 363e387. http:// dx.doi.org/10.1177/ 0309 133307081289.
  42. Shit P.K., Maiti R., 2012. Rill hydraulics: An experimental study on Gully Basin in lateritic upland of Paschim Medinipur, West Bengal, India. J. Geogr. Geol. 4(4), 1e11. http:// dx.doi. org /10.5539/jgg.v4n4p1.
  43. Shin, K.J., Choi, Y.S., 2018. Sensitivity Analysis to Investigate the Reliability of the Grid-Based Rainfall-Runoff Model, Water 2018, 10, 1839; doi: 10.3390/w10121839
  44. Texas Department of Transportation (TxDOT), 2019. Hydraulic Design Manual (Revised); Texas Department of Transportation (TxDOT): Austin, TX, U.S.A., 2019
  45. Taghvaye Salimi, E., Nohegar, A., Malekian, A., Hoseini, M., Holisaz, A., 2016. Estimating time of concentration in large watersheds. 2017. Paddy Water Environ (2017). 15:123–132, DOI 10.1007/s10333-016-0534-2
  46. Upegui, J.J.V., Gutierrez, A.B., 2011. Estimación del tiempo de concentration y tiempo de rezago en la Cuenca experimental Urbana de la quebrada San Luis, Manizales. Dyna, v. 78, n. 165, p. 58-71, 2011.
  47. USACE (U.S. Army Corps of Engineers), 2001. HEC-HMS hydrologic modeling system, user's manual, version 2.2.1. Vicksburg, Mississippi: U.S. Army Corps of Engineers.
  48. S. Natural Resources Conservation Service (NRCS), 1997. Ponds planning design onstruction. In: Agriculture handbook, United States Department of Agriculture (USDA)
  49. Wong, T.S.W., 2009. Evolution of Kinematic Wave Time of Concentration Formulas for Overland Flow.2009, Journal of Hydrologic Engineering, v. 14, n. 7
  50. Water Resources Systems Planning and Management (WRSPM). Chapter 9. 2005, ISBN 92-3-103998-9 – © UNESCO 2005.
  51. Zhou, Z., Qu, L., Zou, T. 2015. Quantitative Analysis of Urban Pluvial Flood Alleviation by Open Surface Water Systems in New Towns: Comparing Almere and Tianjin Eco-City. Sustainability 2015, 7, 13378-13398; doi: 10.3390/su71013378.
  52. Zhang, S.T., Liu, Y., Li, M.M., Liang, B., 2016. Distributed hydrological models for addressing effects of spatial variability of roughness on overland flow. 2016, Water Science and Engineering (2016), http:// dx.doi.org /10.1016 /j.wse.2016.07.001
Desert Ecosystem Engineering Journal
Volume 3, Issue 2
September 2021
Pages 1-18