Skip to main content
ARS Home » Research » Publications at this Location » Publication #332807
Title: Improving continuous hydrologic modeling of data-poor river basins using hydrologic engineering center's hydrologic modeling system: case study of Karkheh River Basin

Author
item DAVTALAB, RAHMAN - University Of Central Florida
item MIRCHI, ALI - University Of Texas - El Paso
item KHATAMI, SINA - University Of Melbourne
item Gyawali, Rabi
item MASSAH, ALIREZA - University Of Tehran
item FARAJZADEH, MANUCHEHR - University Of Tehran
item MADANI, KAVEH - Imperial College

Submitted to: Journal Hydrologic Engineering
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/19/2017
Publication Date: 4/19/2017
Citation: Davtalab, R., Mirchi, A., Khatami, S., Gyawali, R., Massah, A., Farajzadeh, M., Madani, K. 2017. Improving continuous hydrologic modeling of data-poor river basins using hydrologic engineering center's hydrologic modeling system: case study of Karkheh River Basin. Journal Hydrologic Engineering. DOI: 10.1061/(ASCE)HE.1943-5584.0001525.
DOI: https://doi.org/10.1061/(ASCE)HE.1943-5584.0001525

Interpretive Summary: This paper presents a method to estimate parameter values to account for soil moisture and snow-melt in HEC-HMS, a hydrologic modeling system developed by U.S. Army Corps of Engineers. A case study of Karkheh River basin, Iran and corresponding interior sub-basins shows that estimating parameter values that govern specific fall, winter and spring events increased the efficiency and accuracy of HMS model. This finding is particularly important for modeling large data poor basins with heterogeneous hydro-climatic conditions.

Technical Abstract: This paper aims to facilitate the use of HEC-HMS model using a systematic event-based technique for manual calibration of soil moisture accounting and snowmelt degree-day parameters. Manual calibration, which helps ensure the HEC-HMS parameter values are physically-relevant, is often a time-consuming procedure due to multitude of interacting parameters. To address this setback, key parameter values that govern specific fall, spring and winter events in the Karkheh River basin, Iran, were initially estimated in a pre-calibration step, facilitating model calibration via continuous simulations of daily streamflow in five main sub-basins. Model performance was analyzed based on goodness-of-fit criteria focusing on peak flows, low flows and hydrograph shape, which were affected by uncertainties associated with streamflow naturalization and use of average annual parameter values. Sensitivity analysis provided insights about the basin’s snowfall and melt characteristics, distinguishing antecedent temperature index cold rate coefficient and baseflow recession coefficient as key parameters affecting hydrograph shape and magnitude of the peak flow, respectively. Results suggest increased efficiency and accuracy of continuous HEC-HMS modeling of large, data-poor basins with heterogeneous hydro-climatic conditions.