Natural Hazards

, Volume 91, Issue 1, pp 179–199 | Cite as

Hydrological modeling of storm runoff and snowmelt in Taunton River Basin by applications of HEC-HMS and PRMS models

Original Paper
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Abstract

Reliable predictions of storm runoff from rainfall and snowmelt are important for flood hazard mitigation and resilience. In this study, the HEC-HMS and PRMS hydrological models have been applied to simulate storm runoff in Taunton River Basin for the storm event in 2010 when maximum rainfall intensity reached approximate 5 in/day in March, and the snowfall reached about 11 inches in December. Model parameters were calibrated, and model performance was evaluated by comparing model-simulated daily stream flow with observations. For the rainstorm period during March–April, results indicate that both HEC-HMS and PRMS provide very good predictions of rainfall runoff with the correlation values above 0.95, and PRMS produces lower root-mean-square errors than those from HEC-HMS. Over the 12-month period including the snowfall in December, the time series of flow by PRMS match better with observations than those from the HEC-HMS. The 12-month overall correlation values for HEC-HMS and PRMS are 0.91 and 0.97 at Bridgewater Station, and 0.89 and 0.97 at Threemile Station, respectively. For an extreme storm scenario of the maximum historical 36.7-inch snowfall in early February in combination with the rainstorm in March–April of 2010, model simulations indicate that the flow would substantially increase by about 50% or more. Comparisons between HEC-HMS and RPMS models have been analyzed to provide references for storm runoff modeling.

Keywords

Storm runoff modeling Snowmelt HEC-HMS PRMS Taunton River 

Notes

Acknowledgements

This study is supported in part by the Coastal Resilience Center, Department of Homeland Security, through the University of North Carolina. The authors also thank the advices for snowmelt modeling in HEC-HMS by Tom Brauer and Mike Bartles at Hydrologic Engineering Center of U.S. Army Corps of Engineers.

References

  1. Amengual A, Romero R, Alonso S (2008) Hydro-meteorological ensemble simulations of flood events over a small basin of Majorca Island, Spain. Q J R Meteorol Soc 134:1221–1242CrossRefGoogle Scholar
  2. Anderson ML, Chen ZQ, Kavvas ML, Feldman A (2012) Coupling HEC-HMS with atmospheric models for prediction of watershed runoff. J Hydrol Eng 7(4):312–318CrossRefGoogle Scholar
  3. Beighley RE, Melack JM, Dunne T (2003) Impacts of California’s climatic regimes and coastal land use change on streamflow characteristics. J Am Water Resour 39(6):1419–1433CrossRefGoogle Scholar
  4. Beighley RE, Eggert KG, Dunne T, He Y, Gummadi V, Verdin KL (2009) Simulating hydrologic and hydraulic processes throughout the Amazon River Basin. Hydrol Process 23:1221–1235CrossRefGoogle Scholar
  5. Chang H, Jung IW (2010) Spatial and temporal changes in runoff caused by climate change in a complex large river basin in Oregon. J Hydrol 388(3–4):186–207CrossRefGoogle Scholar
  6. Chen C, Huang W (2013) Hydrological modeling of typhoon-induced extreme storm runoffs from Shihmen watershed to reservoir, Taiwan. Nat Hazards 67(2):747–761CrossRefGoogle Scholar
  7. Chen Y, Ren Q, Huang F, Xu H, Cluckie I (2011) Liuxihe model and its modeling to river basin flood. J Hydrol Eng 16(1):33–50CrossRefGoogle Scholar
  8. Chow VT (1959) Open channel hydraulics. McGraw-Hill Book Company, New YorkGoogle Scholar
  9. Christiansen DE, Markstrom SL, Hay LE (2011) Impacts of climate change on growing season in the United States. Earth Interact 15(33):1–17CrossRefGoogle Scholar
  10. Cunderlik JM, Simonovic SP (2007) Inverse flood risk modeling under changing climatic conditions. Hydrol Process 21(563):577Google Scholar
  11. Dressler KA, Leavesley GH, Bales RC, Fassnacht SR (2006) Evaluation of gridded snow water equivalent and satellite snow cover products for mountain basins in a hydrologic model. Hydrol Process 20(4):673–688CrossRefGoogle Scholar
  12. Du SQ, Shi PJ, Van Rompaey A, Wen JH (2015) Quantifying the impact of impervious surface location on flood peak discharge in urban areas. Nat Hazards 76(3):1457–1471CrossRefGoogle Scholar
  13. Gaytán R, Anda J, Nelson J (2008) Computation of changes in the runoff regimen of the Lake Santa Ana watershed. Lakes Reserv Res Manag 13:155–167CrossRefGoogle Scholar
  14. Goleij H, Haghiabi AH, Parsaie A (2017) An experimental study on plunging depth of density currents. Front Struct Civ Eng.  https://doi.org/10.1007/s11709-017-0417-7 Google Scholar
  15. Halwatura D, Najim MMM (2013) Application of the HEC-HMS model for runoff simulation in a tropical catchment. Environ Model Softw 46:155–162CrossRefGoogle Scholar
  16. Hay LE, Wilby RL, Leavesley GH (2000) A comparison of delta change and downscaled GCM scenarios for three mountainous basins in the United States. J Am Water Resour As 36:387–397CrossRefGoogle Scholar
  17. Hay LE, Leavesley GH, Clark MP, Markstrom SL, Viger RJ, Umemoto M (2006a) Step-wise, multiple objective calibration of a hydrologic model for a snowmelt-dominated watershed. J Am Water Resour 42(4):877–890CrossRefGoogle Scholar
  18. Hay LE, Leavesley GH, Clark MP (2006) Use of remotely sensed snow-covered area in watershed model calibration for the Sprague River. In: Oregon in joint 8th federal interagency sedimentation conference and 3rd federal interagency hydrologic modeling conference, 2–6 April 2006, Reno, NevadaGoogle Scholar
  19. HEC-HMS User Manual (2016) Hydrologic modeling system (HEC-HMS) user manual: version 4.2.0., USACE (U.S. Army Corps of Engineers), Hydrologic Engineering Center, Davis, CAGoogle Scholar
  20. IPCC Report (2013) Climate change 2013: the physical science basis. http://www.climatechange2013.org/
  21. Knebl MR, Yang ZL, Hutchison K, Maidment DR (2005) Regional scale flood modeling using NEXRAD rainfall, GIS, and HEC-HMS/RAS: a case study for the San Antonio River Basin Summer 2002 storm event. J Environ Manag 75(4):325–336CrossRefGoogle Scholar
  22. Laouacheria F, Mansouri R (2015) Comparison of WBNM and HEC-HMS for Runoff hydrograph prediction in a small Urban Catchment. Water Resour Manag 29(8):1–17CrossRefGoogle Scholar
  23. Li JF, Chen YD, Zhang L, Zhang Q, Chiew FHS (2016) Future changes in floods and water availability across China: linkage with changing climate and uncertainties. J Hydrometeorol 17(4):1295–1314.  https://doi.org/10.1175/JHM-D-0074.1 CrossRefGoogle Scholar
  24. Markstrom SL, Niswonger RG, Regan RS, Prudic DE, Barlow PM (2008) GSFLOW—coupled ground-water and surface-water flow model based on the integration of the precipitation-runoff modeling system (PRMS) and the modular ground-water flow model (MODFLOW-2005). Techniques and methods 6-D1. U.S. Geological Survey, Reston, ViginiaGoogle Scholar
  25. Markstrom SL, Hay LE (2009) Integrated watershed scale response to climate change for selected basins across the United States. Water Resour Impact 11(2):8–10Google Scholar
  26. Markstrom SL, Regan RS, Hay LE, Viger RJ, Webb RMT, Payn RA, LaFontaine JH (2015) PRMS-IV, the precipitation-runoff modeling system, version 4: U.S. Geological survey techniques and methods, book 6, chap. B7. https://pubs.usgs.gov/tm/6b7/
  27. McLin SG, Springer EP, Lane LJ (2001) Predicting floodplain boundary changes following the Cerro Grande wildfire. Hydrol Process 15:2967–2980CrossRefGoogle Scholar
  28. Meenu R, Rehana S, Mujumdar PP (2013) Assessment of hydrologic impacts of climate change in Tunga-Bhadra river basin, India with HEC-HMS and SDSM. Hydrol Process 27(11):1572–1589CrossRefGoogle Scholar
  29. Mandal A, Stephenson TS, Brown AA, Campbell JD, Taylor MA, Lumsden TL (2016) Rainfall-runoff simulations using the CARIWIG simple model for advection of storms and hurricanes and HEC-HMS: implications of Hurricane Ivan over the Jamaica Hope River watershed. Nat Hazards 83(3):1635–1659Google Scholar
  30. Neshaei MAL, Ghanbarpour F (2017) The effect of sea level rise on beach morphology of Caspian sea coast. Front Struct Civ Eng.  https://doi.org/10.1007/s11709-017-0398-6 Google Scholar
  31. Onusluel GG, Harmancioglu N, Gul A (2010) A combined hydrologic and hydraulic modeling approach for testing efficiency of structural flood control measures. Nat Hazards 54(2):245–260CrossRefGoogle Scholar
  32. Najafi MR, Moradkhani H, Jung IW (2011) Assessing the uncertainties of hydrologic model selection in climate change impact studies. Hydrol Process 25(18):2814–2826CrossRefGoogle Scholar
  33. Niswonger RG, Allander KK, Jenton AE (2014) Collaborative modelling and integrated decision support system analysis of a developed terminal lake basin. J Hydrol 517:521–537CrossRefGoogle Scholar
  34. Tian Y, Zheng Y, Wu B, Wu X, Liu J, Zheng CM (2015) Modeling surface water–groundwater interaction in arid and semi-arid regions with intensive agriculture. Environ Model Softw 63:170–184CrossRefGoogle Scholar
  35. USACE (U.S. Army Corps of Engineers) (2010) Snowmelt modeling in HEC-HMS. Flood and Coastal Storm Damage Reduction R&D Program, Engineering Center, DavisGoogle Scholar
  36. US EPA (2015) BASINS 4.1 (Better Assessment Science Integrating point & Non-point Sources) Modeling Framework. National Exposure Research Laboratory, RTP, North Carolina. https://www.epa.gov/exposure-assessment-models/basins. Accessed 1st Jan 2016
  37. Verdhen A, Chahar BR, Sharma OP (2013) Snowmelt runoff simulation using HEC-HMS in a himalayan watershed. In: World environmental and water resources congress 2013: showcasing the future 3206–3215Google Scholar
  38. Wu B, Zheng Y, Wu X, Tian Y, Han F, Liu J, Zheng CM (2015) Optimizing water resources management in large river basins with integrated surface water–groundwater modeling: a surrogate-based approach. Water Resour Res 51(4):2153–2173CrossRefGoogle Scholar
  39. Yates D, Warner TT, Brandes EA, Leavesley GH, Sun J, Mueller CK (2001) Evaluation of flash-flood discharge forecasts in complex terrain using precipitation. J Hydrol Eng 6(4):265–274CrossRefGoogle Scholar
  40. Yilmaz AG, Imteaz MA, Ogwuda O (2012) Accuracy of HEC-HMC and LBRM models in simulating snow runoffs in upper Euphrates Basin. J Hydrol Eng 17:342–347CrossRefGoogle Scholar
  41. Wang D, Hagen SC, Alizad K (2013) Climate change impact and uncertainty analysis of extreme rainfall events in the Apalachicola River basin, Florida. J Hydrol 480(2013):125–135CrossRefGoogle Scholar
  42. Zarriello PJ, Bent GC (2011) Elevation of the March–April 2010 flood high water in selected river reaches in central and eastern Massachusetts: U.S. Geological Survey Open-File Report 2010–1315Google Scholar
  43. Zarriello PJ, Ahearn EA, Levin SB (2012) Magnitude of flood flows for selected annual exceedance probabilities in Rhode Island through 2010 (ver. 1.2, revised 27 Mar 2013): U.S. Geological Survey Scientific Investigations Report 2012–5109. http://pubs.usgs.gov/sir/2012/5109
  44. Zhang Q, Chen YD, Chen XH, Li JF (2011) Copula-based analysis of hydrological extremes and implications of hydrological behaviors in the Pearl River Basin, China. J Hydrol Eng 16(7):598–607.  https://doi.org/10.1061/(ASCE)HE.1943-5584.0000350 CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2017

Authors and Affiliations

  1. 1.Department of Hydraulic Engineering, College of Civil EngineeringTongji UniversityShanghaiChina
  2. 2.Department of Civil and Environmental EngineeringFlorida A&M University - Florida State UniversityTallahasseeUSA
  3. 3.School of OcenographyUniversity of Rhode IsalndNarraganssetUSA

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