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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

Bharali Biswadeep, Misra Utpal Kumar

Meteorology Hydrology and Water Management. Research and Operational Applications

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2021

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Vol. 9, Iss. 1-2

1--22

EN

The Cunge-Muskingum routing model is one of the most popular and widely used models for hydrologic channel flood routing. The application of Cunge-Muskingum model to an ungauged basin is hindered by the lack of hydro-meteorological data. In the present study, a method is proposed to predict the outflow hydrograph of an ungauged basin as a solution to this problem. The Cunge-Muskingum method is modified, considering the non-prismatic complex natural channel. The Soil Conservation Service Curve Number rainfall-runoff model is employed to obtain the inflow and lateral inflow hydrographs of the ungauged basins, and the Modified Cunge-Muskingum model is employed to anticipate the flood hydrograph at the outlet of the ungauged basin. The proposed approach is employed to the Kulsi River Basin, India, hypothetically treated as an ungauged basin, and the results are compared with the observed data at the outlet of the basin. The performance of the model is evaluated based on RMSE (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).The results reveal that the proposed Modified Cunge-Muskingum model is an efficient predictor of the flood hydrograph at the outlet of the ungauged basin.

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Flood frequency analysis for an ungauged Himalayan river basin using different methods: a case study of Modi Khola, Parbat, Nepal

Acharya Bibek, Joshi Bisesh

Meteorology Hydrology and Water Management. Research and Operational Applications

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2020

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Vol. 8, Iss. 2

46--51

EN

Predicting flood discharges in the rivers of an ungauged basin is tedious because essential hydrological data is lacking. In mountainous countries like Nepal, the design of hydraulic structures in these steeply sloped rivers is of prime importance for flood control, as well as for electricity generation where hydraulic head is gained over short, steep reaches. This study illustrates a variety of approaches that can be used to perform flood frequency analysis of typical ungauged mountainous rivers, where discharge data are available from hydrologically similar catchments. The various methods are evaluated by comparing the goodness of fit of an array of hydrologic distribution functions. From each probability density function or regional empirical method, we predict the multi-year return periods for floods, information that is generally required to design the hydraulic structures. The analysis was done based on the annual maxima, peaks above threshold, and widely used regional empirical methods. This analysis was accomplished using the discharge data of Nayapul station near Jhapre Bagar collected from the Department of Hydrology and Meteorology, Government of Nepal, Kathmandu. The analysis and results of this study paved the way for the hydraulic design of water systems in the ungauged study region and demonstrated how the information acquired can be used for water resource management in catchments with similar hydrologic features.

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Method of Prediction of the Stream Flows in Poorly Gauged and Ungauged Basins

Kuzmin Vadim, Pivovarova Inna, Shemanaev Kirill, Sokolova Daria, Batyrov Artur, Tran Ngoc Anh, Dang DinhKha

Journal of Ecological Engineering

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2019

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Vol. 20, nr 1

180--187

EN

The underlying principles and content of new technology for automated hydrological predictions of poorly gauged and ungauged basins were reviewed herein. Basin classification principles depending on the availability and spatial-temporal discreteness of the observations of meteorological and hydrological variables were proposed. The prediction procedure for large river systems insufficiently covered by hydrometeorological survey was outlined. The prediction methodology for Sông Sê San river basin, which is the left tributary of Mekong river, was tested. The possible options for preliminary calibration and validation of MLCM3 predictive model (Multi-Layer Conceptual Model, 3rd generation), developed within the framework of set task, were described. The software, implementing the streamflow prediction method for ungauged and poorly gauged special basins of large rivers tributaries, was tested.