An integrated statistical-machine learning approach for runoff prediction
Nowadays, great attention has been attributed to the study of runoff and its fluctuation over
space and time. There is a crucial need for a good soil and water management system to …
space and time. There is a crucial need for a good soil and water management system to …
The potential of a novel support vector machine trained with modified mayfly optimization algorithm for streamflow prediction
This paper focuses on the development of a robust accurate streamflow prediction model by
balancing the abilities of exploitation and exploration to find the best parameters of a …
balancing the abilities of exploitation and exploration to find the best parameters of a …
Short-term forecasts of streamflow in the UK based on a novel hybrid artificial intelligence algorithm
In recent years, the growing impact of climate change on surface water bodies has made the
analysis and forecasting of streamflow rates essential for proper planning and management …
analysis and forecasting of streamflow rates essential for proper planning and management …
Forecasting of stage-discharge in a non-perennial river using machine learning with gamma test
Abstract Knowledge of the stage-discharge rating curve is useful in designing and planning
flood warnings; thus, develo** a reliable stage-discharge rating curve is a fundamental …
flood warnings; thus, develo** a reliable stage-discharge rating curve is a fundamental …
Modeling stage–discharge–sediment using support vector machine and artificial neural network coupled with wavelet transform
Many real water issues involve rivers' sediment load or the load that rivers can bring without
degrading the fluvial ecosystem. Therefore, the assessment of sediments carried by a river is …
degrading the fluvial ecosystem. Therefore, the assessment of sediments carried by a river is …
Extending global river gauge records using satellite observations
Long-term, continuous, and real-time streamflow records are essential for understanding
and managing freshwater resources. However, we find that 37% of publicly available global …
and managing freshwater resources. However, we find that 37% of publicly available global …
A simple machine learning approach to model real-time streamflow using satellite inputs: Demonstration in a data scarce catchment
Real-time streamflow modeling is a challenging endeavor in regions where real-time ground-
based hydro-meteorological observations are scarce. Nevertheless, with the emergence of …
based hydro-meteorological observations are scarce. Nevertheless, with the emergence of …
Water level prediction using soft computing techniques: A case study in the Malwathu Oya, Sri Lanka
Hydrologic models to simulate river flows are computationally costly. In addition to the
precipitation and other meteorological time series, catchment characteristics, including soil …
precipitation and other meteorological time series, catchment characteristics, including soil …
Superiority of hybrid soft computing models in daily suspended sediment estimation in highly dynamic rivers
Estimating sediment flow rate from a drainage area plays an essential role in better
watershed planning and management. In this study, the validity of simple and wavelet …
watershed planning and management. In this study, the validity of simple and wavelet …
Potential of hybrid wavelet-coupled data-driven-based algorithms for daily runoff prediction in complex river basins
Accurate prediction of daily runoff's dynamic nature is necessary for better watershed
planning and management. This study analyzes the applicability of artificial neural network …
planning and management. This study analyzes the applicability of artificial neural network …