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Streamflow forecasting method with a hybrid physical process-mathematical statistic
The complex topology of river networks and the numerous factors influencing streamflow make it challenging to forecast streamflow in large river...
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Comparison of data-driven techniques for daily streamflow forecasting
Four artificial intelligence methods are compared for streamflow forecasting. The models are tested using 20 years of daily streamflow values in...
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Machine learning modeling structures and framework for short-term forecasting and long-term projection of Streamflow
Reliable short-term forecasting and long-term projection of streamflow are essential. However, few research models for machine learning structures...
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Do non-linearity and non-Gaussianity truly matter in streamflow forecasting? A comparative study between PAR(p) and vine copula for Brazilian streamflow time series
This study evaluates the joint impact of non-linearity and non-Gaussianity on predictive performance in 23 Brazilian monthly streamflow time series...
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Long-lead streamflow forecasting using computational intelligence methods while considering uncertainty issue
While some robust artificial intelligence (AI) techniques such as Gene-Expression Programming (GEP), Model Tree (MT), and Multivariate Adaptive...
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Improving short-term streamflow forecasting by flow mode clustering
Runoff prediction with high accuracy is vital to protect people’s properties and lives. In this study, a Short-Term Streamflow Forecasting Framework...
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Comparative analysis of data-driven and conceptual streamflow forecasting models with uncertainty assessment in a major basin in Iran
Streamflow forecasting is a critical aspect of water resource management, particularly in regions where surface water is scarce. In this study, we...
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Trend analysis and forecasting of streamflow using random forest in the Punarbhaba River basin
Streamflow rate changes due to damming are hydro-ecologically sensitive in present and future times. Very less studies have done an investigation of...
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A Multi-model Framework for Streamflow Forecasting Based on Stochastic Models: an Application to the State Of Ceará, Brazil
Reliable long-term (decadal scale) streamflow prediction would provide significant planning information for water resources management, particularly...
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Coupling ANFIS with ant colony optimization (ACO) algorithm for 1-, 2-, and 3-days ahead forecasting of daily streamflow, a case study in Poland
Finding an efficient and reliable streamflow forecasting model has always been an important challenge for managers and planners of freshwater...
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Machine Learning Algorithms with Hydro-Meteorological Data for Monthly Streamflow Forecasting of Kurau River, Malaysia
Monthly streamflow forecasting is crucial in water resources management to assess the possible future streamflow patterns. It becomes vital where...
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Robust streamflow forecasting: a Student’s t-mixture vector autoregressive model
Accurate streamflow forecasting is one of the main challenges in the management of reservoirs, where autoregressive models have been commonly used....
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Interpretable and explainable hybrid model for daily streamflow prediction based on multi-factor drivers
Streamflow time series data typically exhibit nonlinear and nonstationary characteristics that complicate precise estimation. Recently,...
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An assessment of multi-layer perceptron networks for streamflow forecasting in large-scale interconnected hydrosystems
This work analyzes the use of artificial neural networks in the short-term streamflow forecasting for large interconnected hydropower systems. The...
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Bias Correction of Regional Climate Models for Streamflow Forecasting
Climate change is recognised as a serious phenomenon affecting socio-economic agricultural development activities around the globe. Regional climate...
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A new interpretable streamflow prediction approach based on SWAT-BiLSTM and SHAP
Streamflow is a crucial variable for assessing the available water resources for both human and environmental use. Accurate streamflow prediction...
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Application of novel artificial bee colony optimized ANN and data preprocessing techniques for monthly streamflow estimation
Streamflow estimation is important in hydrology, especially in drought and flood-prone areas. Accurate estimation of streamflow values is crucial for...
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Multi-phase hybrid bidirectional deep learning model integrated with Markov chain Monte Carlo bivariate copulas function for streamflow prediction
In recent years, deep learning (DL) approaches have been proven effective in addressing high nonlinear relationships within complex systems. Although...
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Improved monthly streamflow prediction using integrated multivariate adaptive regression spline with K-means clustering: implementation of reanalyzed remote sensing data
This study investigates monthly streamflow modeling at Kale and Durucasu stations in the Black Sea Region of Turkey using remote sensing data. The...
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Physically based vs. data-driven models for streamflow and reservoir volume prediction at a data-scarce semi-arid basin
Physically based or data-driven models can be used for understanding basinwide hydrological processes and creating predictions for future conditions....
