Quantifying flow rate using stage-discharge rating curve and Scs runoff equation on upland watershed of Lake Tana Sub Basin, Ethiopia

Kumlachew, Yibeltal Zewdu; Tilahun, Seifu A.; Cherie, Fasikaw Fentie; Akale, Adugnaw T.; Kibret, Eshetu Adane; Alemie, Niway Asrat; Animut, Moges

doi:10.1007/s40899-022-00793-z

Cited by 4 publications

(1 citation statement)

References 15 publications

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“…A similar methodology was applied by Manyifika, [ 60 ], and Umugwaneza et al [ 59 ]. With regards to Birbal et al [ 61 ] and Kumlachew et al [ 62 ], the studies vow an excellent statistical performance of SRC with more than 0.95 correlation in actual versus calculated discharge values. The SRC similarly presents a great performance on the precipitations versus the flow rate ratios in Manyifika, [ 60 ].…”

Section: Methodsmentioning

confidence: 99%

Modelling the future climate impacts on hydraulic infrastructure development in tropical (peri-)urban region: Case of Kigali, Rwanda

Iradukunda,

Mwanaumo,

Kabika

2024

Heliyon

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Section: Methodsmentioning

confidence: 99%

Modelling the future climate impacts on hydraulic infrastructure development in tropical (peri-)urban region: Case of Kigali, Rwanda

Iradukunda,

Mwanaumo,

Kabika

2024

Heliyon

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Modeling water hyacinth (Eichhornia crassipes) distribution in Lake Tana, Ethiopia, using machine learning

Belayhun,

Mekuriaw

2024

Remote Sensing Applications: Society and Environment

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Assessing the effect of rating curve uncertainty in streamflow simulation on Kulfo watershed, Southern Ethiopia

Bekele Mena,

Ayele,

Chora

et al. 2024

Journal of Water and Climate Change

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Accurate streamflow simulation and comprehending its associated uncertainty are crucial for effective water resource management. However, the uncertainty of rating curves from which streamflow data is derived remains poorly understood. This study aims to simulate streamflow under rating curve uncertainty conditions. The bootstrap resampling technique (BSRT) was used to establish the rating curve and estimate associated uncertainty. Furthermore, it integrated with standalone and hybrid models (GRU, Bi-LSTM, and Conv1D-LSTM), to assess the effect of this uncertainty on streamflow simulation. Different lag times of rainfall and discharge are used as input for DL streamflow simulation models. Despite the complexity, the Conv1D-LSTM model did not outperform the Bi-LSTM model. However, it slightly outperforms the GRU model. Moreover, the rating curve uncertainty significantly propagates to streamflow simulation, particularly in high-flow regions. Consequently, the uncertainties related to rating curves on the Kulfo River led to a streamflow uncertainty of about 17.8 m3 s−1, representing 22% at peak discharge. The performance of the DL models was evaluated using different metrics (RMSE, MAE, NSE, and R2). The findings underscore the importance of considering rating curve uncertainty in streamflow simulation to enhance water resource management practices and support informed decision-making in the study area.

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Quantifying flow rate using stage-discharge rating curve and Scs runoff equation on upland watershed of Lake Tana Sub Basin, Ethiopia

Cited by 4 publications

References 15 publications

Modelling the future climate impacts on hydraulic infrastructure development in tropical (peri-)urban region: Case of Kigali, Rwanda

Modelling the future climate impacts on hydraulic infrastructure development in tropical (peri-)urban region: Case of Kigali, Rwanda

Modeling water hyacinth (Eichhornia crassipes) distribution in Lake Tana, Ethiopia, using machine learning

Assessing the effect of rating curve uncertainty in streamflow simulation on Kulfo watershed, Southern Ethiopia

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