ERM model analysis for adaptation to hydrological model errors

• Autorzy: Baymani-Nezhad M. , Han D.
• Języki publikacji: EN

Abstrakty

EN

Hydrological conditions are changed continuously and these phenomenons generate errors on flood forecasting models and will lead to get unrealistic results. Therefore, to overcome these difficulties, a concept called model updating is proposed in hydrological studies. Real-time model updating is one of the challenging processes in hydrological sciences and has not been entirely solved due to lack of knowledge about the future state of the catchment under study. Basically, in terms of flood forecasting process, errors propagated from the rainfall-runoff model are enumerated as the main source of uncertainty in the forecasting model. Hence, to dominate the exciting errors, several methods have been proposed by researchers to update the rainfall-runoff models such as parameter updating, model state updating, and correction on input data. The current study focuses on investigations about the ability of rainfall-runoff model parameters to cope with three types of existing errors, timing, shape and volume as the common errors in hydrological modelling. The new lumped model, the ERM model, has been selected for this study to evaluate its parameters for its use in model updating to cope with the stated errors. Investigation about ten events proves that the ERM model parameters can be updated to cope with the errors without the need to recalibrate the model.

Słowa kluczowe

EN

real time; model updating; forecasting errors; concentration time; time to peak

PL

czas rzeczywisty; aktualizowanie modelu; błędy prognozowania; czas koncentracji

• Wydawca: Instytut Geofizyki PAN ; Springer
• Czasopismo: Acta Geophysica
• Rocznik: 2018
• Tom: Vol. 66, no. 4
• Strony: 741--753
• Opis fizyczny: Bibliogr. 30 poz.

Twórcy

autor

Baymani-Nezhad M.

• Department of Civil Engineering, Karaj Branch Islamic Azad University, Karaj, Iran

autor

Han D.

• Water and Environmental Manager Center, University of Bristol, Bristol, UK

Bibliografia

• 1. Arnell NW (1999) The effect of climate change on hydrological regimes in Europe: a continental perspective. Glob Environ Change 9(1):5–23
• 2. Bartholmes J, Todini E (2005) Coupling meteorological and hydrological models for flood forecasting. Hydrol Earth Syst Sci Discuss 9(4):333–346
• 3. Baymani-Nezhad M, Han D (2013) Hydrological modeling using effective rainfall routed by the Muskingum method (ERM). J Hydroinform 15(4):1437–1455
• 4. Beven K (1993) Prophecy, reality and uncertainty in distributed hydrological modeling. Adv Water Resour 16:41–51
• 5. Brath A, Montanari A, Toth E (2002) Neural networks and nonparametric methods for improving real-time flood forecasting through conceptual hydrological models. Hydrol Earth Syst Sci Discuss 6(4):627–639
• 6. Charlton R, Fealy R, Moore S, Sweeney J, Murphy C (2006) Assessing the impact of climate change on water supply and flood hazard in Ireland using statistical downscaling and hydrological modelling techniques. Clim Change 74(4):475–491
• 7. Chiew F, Whetton P, McMahon T, Pittock A (1995) Simulation of the impacts of climate change on runoff and soil moisture in Australian catchments. J Hydrol 167(1):121–147
• 8. Dibike YB, Coulibaly P (2005) Hydrologic impact of climate change in the Saguenay watershed: comparison of downscaling methods and hydrologic models. J Hydrol 307(1):145–163
• 9. Fang X, Thompson DB, Cleveland TG, Pradhan P, Malla R (2008) Time of concentration estimated using watershed parameters determined by automated and manual methods. J Irrig Drain Eng 134(2):202–211
• 10. Fu B, Wang J, Chen L, Qiu Y (2003) The effects of land use on soil moisture variation in the Danangou catchment of the Loess Plateau, China. Catena 54(1):197–213
• 11. Hagg W, Braun L, Kuhn M, Nesgaard T (2007) Modelling of hydrological response to climate change in glacierized Central Asian catchments. J Hydrol 332(1):40–53
• 12. Haktanir T, Sezen N (1990) Suitability of two-parameter gamma and three-parameter beta distributions as synthetic unit hydrographs in Anatolia. Hydrol Sci J 35(2):167–184
• 13. Han D (2011) Flood risk assessment and management. Bentham Science Publishers
• 14. Izzard CF, Hicks W (1946) Hydraulics of runoff from developed surfaces. Highway Res Board Proc 26:129–150
• 15. Johnstone D, Cross WP (1949) Elements of applied hydrology. Ronald Press Company, New York
• 16. Kirpich Z (1940) Time of concentration of small agricultural watersheds. Civ Eng 10(6):362
• 17. Lardet P, Obled C (1994) Real-time flood forecasting using a stochastic rainfall generator. J Hydrol 162(3):391–408
• 18. McCalla GR, Blackburn WH, Merrill LB (1984) “Effects of live stock grazing on infiltration rates”. Edwards Plateau of Texas. J Range Manag 37:265–269
• 19. McCuen RH, Spiess JM (1995) Assessment of kinematic wave time of concentration. J Hydraul Eng 121(3):256–266
• 20. Morgali J, Linsley RK (1965) Computer analysis of overland flow. J Hydraul Div 91(3):81–100
• 21. Nguyen M, Sheath G, Smith C, Cooper A (1998) Impact of cattle treading on hill land: 2. Soil physical properties and contaminant runoff. N Z J Agric Res 41(2):279–290
• 22. Penning-Rowsell EC, Tunstall SM, Tapsell S, Parker DJ (2000) The benefits of flood warnings: real but elusive, and politically significant. Water Environ J 14(1):7–14
• 23. USDA SCS (US Department of Agricluture Soil Conservation Service) (1986) Urban hydrology for small watersheds, 2nd edn. Technical Release 55
• 24. Wilby R, Greenfield B, Glenny C (1994) A coupled synoptichydrological model for climate change impact assessment. J Hydrol 153(1):265–290
• 25. Wong TS, Chen C-N (1997) Time of concentration formula for sheet flow of varying flow regime. J Hydrol Eng 2(3):136–139
• 26. Xu C-Y (1999) Climate change and hydrologic models: a review of existing gaps and recent research developments. Water Resour Manag 13(5):369–382
• 27. Yakowitz S (1985) Markov flow models and the flood warning problem. Water Resour Res 21(1):81–88
• 28. Yang X, Michel C (2000) Flood forecasting with a watershed model: a new method of parameter updating. Hydrol Sci J 45(4):537–546
• 29. Younis J, Anquetin S, Thielen J (2008) The benefit of high resolution operational weather forecasts for flash flood warning. Hydrol Earth Syst Sci Discuss Discuss 5(1):345–377
• 30. Yu P-S, Chen S-T (2005) Updating real-time flood forecasting using a fuzzy rule-based model/mise a Jour de Prevision de Crue en Temps Reel Grace a un Modele a Base de Regles Floues. Hydrol Sci J 50(2):265–278