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Machine learning approaches to debris flow susceptibility analyses in the Yunnan section of the Nujiang River Basin.

PeerJ
BACKGROUND: The Yunnan section of the Nujiang River (YNR) Basin in the alpine-valley area is one of the most critical areas of debris flow in China.

A hybrid deep learning approach to predict hourly riverine nitrate concentrations using routine monitored data.

Journal of environmental management
With high-frequency data of nitrate (NO-N) concentrations in waters becoming increasingly important for understanding of watershed system behaviors and ecosystem managements, the accurate and economic acquisition of high-frequency NO-N concentration ...

Interpretable baseflow segmentation and prediction based on numerical experiments and deep learning.

Journal of environmental management
Baseflow is a crucial water source in the inland river basins of high-cold mountainous region, playing a significant role in maintaining runoff stability. It is challenging to select the most suitable baseflow separation method in data-scarce high-co...

Integrated machine learning reveals aquatic biological integrity patterns in semi-arid watersheds.

Journal of environmental management
Semi-arid regions present unique challenges for maintaining aquatic biological integrity due to their complex evolutionary mechanisms. Uncovering the spatial patterns of aquatic biological integrity in these areas is a challenging research task, espe...

Enhancing physically-based hydrological modeling with an ensemble of machine-learning reservoir operation modules under heavy human regulation using easily accessible data.

Journal of environmental management
Dams and reservoirs have significantly altered river flow dynamics worldwide. Accurately representing reservoir operations in hydrological models is crucial yet challenging. Detailed reservoir operation data is often inaccessible, leading to relying ...

Predicting reservoir sedimentation using multilayer perceptron - Artificial neural network model with measured and forecasted hydrometeorological data in Gibe-III reservoir, Omo-Gibe River basin, Ethiopia.

Journal of environmental management
The estimation and prediction of the amount of sediment accumulated in reservoirs are imperative for sustainable reservoir sedimentation planning and management and to minimize reservoir storage capacity loss. The main objective of this study was to ...

Interpretable and explainable hybrid model for daily streamflow prediction based on multi-factor drivers.

Environmental science and pollution research international
Streamflow time series data typically exhibit nonlinear and nonstationary characteristics that complicate precise estimation. Recently, multifactorial machine learning (ML) models have been developed to enhance the performance of streamflow predictio...

Enhancing short-term streamflow prediction in the Haihe River Basin through integrated machine learning with Lasso.

Water science and technology : a journal of the International Association on Water Pollution Research
With the widespread application of machine learning in various fields, enhancing its accuracy in hydrological forecasting has become a focal point of interest for hydrologists. This study, set against the backdrop of the Haihe River Basin, focuses on...

Assessment of machine learning algorithms and new hybrid multi-criteria analysis for flood hazard and mapping.

Environmental science and pollution research international
Floods in Iran cause a lot of damage in different places every year. The 2019 floods of the Gorgan and Atrak rivers basins in the north of Iran were one of the most destructive events in this country. Therefore, investigating the flood hazard of thes...

Using an interpretable deep learning model for the prediction of riverine suspended sediment load.

Environmental science and pollution research international
The prediction of suspended sediment load (SSL) within riverine systems is critical to understanding the watershed's hydrology. Therefore, the novelty of our research is developing an interpretable (explainable) model based on deep learning (DL) and ...