2021
DOI: 10.26491/mhwm/143249
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Prediction of flood hydrograph using the modified Cunge-Muskingum method in an ungauged basin: a case study in the Kulsi river basin, India

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Cited by 2 publications
(2 citation statements)
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“…Given the complex nature of non-prismatic channels. Research conducted by Bharali and Misra [14] 2021, in the Kulsi river valley, India. Model performance was tested by root mean square error (RMSE), with a peak flow of 50.34 m3/s, peak flow error (39.73%), peak flow time error (-3.44%), total volume error (7.36%), relative error (7.36%), mean absolute error (33.5%), correlation coefficient (0.785), coefficient of efficiency (0.59) and Kling-Gupta efficiency (0.66).…”
Section: Literature Reviewmentioning
confidence: 99%
See 1 more Smart Citation
“…Given the complex nature of non-prismatic channels. Research conducted by Bharali and Misra [14] 2021, in the Kulsi river valley, India. Model performance was tested by root mean square error (RMSE), with a peak flow of 50.34 m3/s, peak flow error (39.73%), peak flow time error (-3.44%), total volume error (7.36%), relative error (7.36%), mean absolute error (33.5%), correlation coefficient (0.785), coefficient of efficiency (0.59) and Kling-Gupta efficiency (0.66).…”
Section: Literature Reviewmentioning
confidence: 99%
“…To calculate the effective rain loss used the SCS-CN method [14], from the rainfall Hyetograph of the 25 year return period. Cumulative rain loss was calculated using the following Equation 6:…”
Section: 21calculation Of Effective Rain Using Soil Conservation Serv...mentioning
confidence: 99%