scholarly journals Effect of Watershed Subdivision and Antecedent Moisture Condition on HEC-HMS Model Performance in the Maha Oya Basin, Sri Lanka

2018 ◽  
Vol 5 (2) ◽  
pp. 22-37
Author(s):  
M. Kamran ◽  
RL.H.L. Rajapakse

In large scale watersheds, the accuracy level of medium and low flow simulation could decrease due to uncertainty of the watershed parameters. In hydrological modeling, sub division of watershed would help to better implement decision-making related to water resources management, which relies heavily on hydrologic simulations. However, an important concern will be raised over problems associated with lumped hydrologic models with watershed subdivision broadly applied in so called semi-distributed hydrological models since scale issues would significantly affect model performance, and thus, lead to dramatic variations in simulation results. It is important to achieve the appropriate level of sub divisions (discretization). Further at times, the resulting flood level can be much higher than expected, due to storm events. This is unprecedented and the reason may be due to saturated moisture level in the soil layer. Therefore, the Antecedent Moisture Condition (AMC) is an important parameter to be investigated to check the accuracy and possibility of further improvement of the model. In this paper, Hydrologic Modeling System (HEC-HMS) was used for continuous simulation to investigate the effect of watershed subdivision on the model performance. Further, the antecedent moisture condition (AMC) events were used to study the impacts of AMC on the model performance. Badalgama watershed is selected as study area in Maha Oya Basin in Sri Lanka. Spatial extents of Maha Oya Basin and Badalgama watershed are 1553 km² and 1272 km², respectively. Four rainfall stations and one river gauging station were selected in Badalgama watershed. Nash–Sutcliffe (NASH) coefficient and Mean Ratio of Absolute Error (MRAE) were selected as objective functions for modeling. The main focus was on MRAE, as the objective function, but Nash coefficient was also estimated and checked for comparison. In particular, results show that generally the accuracy of the model decreased from six to sixteen sub divisions, which shows that variation in the total number of sub watersheds had very little effect on runoff hydrographs and improvements generally disappear when the number of subdivisions reaches a relatively small number, approximately between six and sixteen sub-watersheds. The accuracy of the model with AMC-III increased by 12.04% when compared to AMC-II hence showing more reliable results as compared with AMC-II condition. In this research, recession method was used for base flow estimation, which led to mass balance error exceeding 20%. Therefore it is recommended that for improving the accuracy, linear reservoir method for base flow estimation should be used in order to conserve the water balance and AMC-III should be used for fully saturated soil instead of AMC-II.

Author(s):  
Rekha Verma ◽  
Azhar Husain ◽  
Mohammed Sharif

Rainfall-Runoff modeling is a hydrological modeling which is extremely important for water resources planning, development, and management. In this paper, Natural Resource Conservation Service-Curve Number (NRCS-CN) method along with Geographical Information System (GIS) approach was used to evaluate the runoff resulting from the rainfall of four stations, namely, Bilodra, Kathlal, Navavas and Rellawada of Sabarmati River basin. The rainfall data were taken for 10 years (2005-2014). The curve number which is the function of land use, soil and antecedent moisture condition (AMC) was generated in GIS platform. The CN value generated for AMC- I, II and III were 57.29, 75.39 and 87.77 respectively. Using NRCS-CN method, runoff depth was calculated for all the four stations. The runoff depth calculated with respect to the rainfall for Bilodra, Kathlal, Navavas and Rellawada shows a good correlation of 0.96. The computed runoff was compared with the observed runoff which depicted a good correlation of 0.73, 0.70, 0.76 and 0.65 for the four stations. This method results in speedy and precise estimation of runoff from a watershed.


2013 ◽  
Vol 17 (9) ◽  
pp. 3577-3586 ◽  
Author(s):  
R. Gan ◽  
Y. Luo

Abstract. Base flow is an important component in hydrological modeling. This process is usually modeled by using the linear aquifer storage–discharge relation approach, although the outflow from groundwater aquifers is nonlinear. To identify the accuracy of base flow estimates in rivers dominated by snowmelt and/or glacier melt in arid and cold northwestern China, a nonlinear storage–discharge relationship for use in SWAT (Soil Water Assessment Tool) modeling was developed and applied to the Manas River basin in the Tian Shan Mountains. Linear reservoir models and a digital filter program were used for comparisons. Meanwhile, numerical analysis of recession curves from 78 river gauge stations revealed variation in the parameters of the nonlinear relationship. It was found that the nonlinear reservoir model can improve the streamflow simulation, especially for low-flow period. The higher Nash–Sutcliffe efficiency, logarithmic efficiency, and volumetric efficiency, and lower percent bias were obtained when compared to the one-linear reservoir approach. The parameter b of the aquifer storage–discharge function varied mostly between 0.0 and 0.1, which is much smaller than the suggested value of 0.5. The coefficient a of the function is related to catchment properties, primarily the basin and glacier areas.


2013 ◽  
Vol 15 (4) ◽  
pp. 609-618
Author(s):  
Sidoeun Ly ◽  
Hyun Seok Shin ◽  
Duck Hwan Kim ◽  
Beom Jun Kim ◽  
Hung Soo Kim

1982 ◽  
Vol 108 (2) ◽  
pp. 107-114
Author(s):  
Donald D. Gray ◽  
Peter G. Katz ◽  
Sharon M. deMonsabert ◽  
Neroli P. Cogo

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