Rainfall-runoff simulation in ungauged tributary streams using drainage area ratio-based multivariate adaptive regression spline and random forest hybrid models
For various reasons, it is not always possible to obtain adequate and reliable long-term
streamflow records in a river basin. It is known that streamflow records are even shorter …
streamflow records in a river basin. It is known that streamflow records are even shorter …
Hybrid modeling for stream flow estimation: integrating machine learning and federated learning
In the face of mounting global challenges stemming from population growth and climate
fluctuations, the sustainable management of water resources emerges as a paramount …
fluctuations, the sustainable management of water resources emerges as a paramount …
Estimation of flow duration and mass flow curves in ungauged tributary streams
The mastery in forecasting the streamflow rates is of great importance in the design,
planning and resilience against droughts. Likewise, the application of flow duration and …
planning and resilience against droughts. Likewise, the application of flow duration and …
A comparative study of statistical methods for daily streamflow estimation at ungauged basins in Turkey
In this study, a comparative evaluation of the statistical methods for daily streamflow
estimation at ungauged basins is presented. The single donor station drainage area ratio …
estimation at ungauged basins is presented. The single donor station drainage area ratio …
Efficacy of statistical algorithms in imputing missing data of streamflow discharge imparted with variegated variances and seasonalities
Y Gao, M Taie Semiromi, C Merz - Environmental Earth Sciences, 2023 - Springer
Streamflow missing data rises to a real challenge for calibration and validation of
hydrological models as well as for statistically based methods of streamflow prediction …
hydrological models as well as for statistically based methods of streamflow prediction …
Supplementing missing data using the drainage-area ratio method and evaluating the streamflow drought index with the corrected data set
E Turhan, S Değerli Şimşek - Water, 2023 - mdpi.com
In water resources management, it is essential to have a full and complete set of
hydrological parameters to create accurate models. Especially for long-term data, any …
hydrological parameters to create accurate models. Especially for long-term data, any …
An effective framework for improving performance of daily streamflow estimation using statistical methods coupled with artificial neural network
This study presents an effective framework that combines artificial neural network (ANN) and
statistical methods to more efficiently, consistently, and reliably estimate the daily streamflow …
statistical methods to more efficiently, consistently, and reliably estimate the daily streamflow …
Development of ensemble approaches based on performance of statistical methods for daily streamflow estimation
This study presents an extension of an existing performance-based weighting system to
combine statistical streamflow estimates for ungauged basins. Three statistical methods …
combine statistical streamflow estimates for ungauged basins. Three statistical methods …
[PDF][PDF] Comparison of different machine learning techniques in river flow prediction
Purpose: River flow forecasting to ensure optimized use of water planning in future years
Theory and Methods: In this study, a hybrid model was obtained and analysed by comparing …
Theory and Methods: In this study, a hybrid model was obtained and analysed by comparing …
Streamflow Data Infilling Using Machine Learning Techniques with Gamma Test
Length, completeness, and quality of hydrological time-series can affect considerably the
efficiency of decisions in water resources engineering. Regrettably, obtaining short …
efficiency of decisions in water resources engineering. Regrettably, obtaining short …