AIMC Topic: Rivers

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Comparative analysis of machine learning methods for prediction of chlorophyll-a in a river with different hydrology characteristics: A case study in Fuchun River, China.

Journal of environmental management Jun 11, 2024
Eutrophication is a serious threat to water quality and human health, and chlorophyll-a (Chla) is a key indicator to represent eutrophication in rivers or lakes. Understanding the spatial-temporal distribution of Chla and its accurate prediction are ...
Eutrophication China Machine Learning Chlorophyll A Hydrology Environmental Monitoring Rivers Water Quality Chlorophyll
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Ensemble machine learning using hydrometeorological information to improve modeling of quality parameter of raw water supplying treatment plants.

Journal of environmental management Jun 5, 2024
Source and raw water quality may deteriorate due to rainfall and river flow events that occur in watersheds. The effects on raw water quality are normally detected in drinking water treatment plants (DWTPs) with a time-lag after these events in the w...
Rivers Models, Theoretical Water Quality Machine Learning Water Purification
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Research on runoff process vectorization and integration of deep learning algorithms for flood forecasting.

Journal of environmental management Jun 4, 2024
Accurate multi-step ahead flood forecasting is crucial for flood prevention and mitigation efforts as well as optimizing water resource management. In this study, we propose a Runoff Process Vectorization (RPV) method and integrate it with three Deep...
Algorithms Models, Theoretical Rivers Forecasting Floods Deep Learning
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Long-term water demand forecasting using artificial intelligence models in the Tuojiang River basin, China.

PloS one May 22, 2024
Accurate forecasts of water demand are a crucial factor in the strategic planning and judicious use of finite water resources within a region, underpinning sustainable socio-economic development. This study aims to compare the applicability of variou...
Neural Networks, Computer China Rivers Models, Theoretical Artificial Intelligence Algorithms Water Supply Forecasting
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Machine learning approaches to debris flow susceptibility analyses in the Yunnan section of the Nujiang River Basin.

PeerJ May 20, 2024
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.
Machine Learning China Support Vector Machine Algorithms Environmental Monitoring Rivers
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A hybrid deep learning approach to predict hourly riverine nitrate concentrations using routine monitored data.

Journal of environmental management May 10, 2024
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 ...
New Hampshire Nitrates Neural Networks, Computer Environmental Monitoring Rivers Deep Learning Water Pollutants, Chemical
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Interpretable baseflow segmentation and prediction based on numerical experiments and deep learning.

Journal of environmental management May 10, 2024
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...
Neural Networks, Computer Deep Learning Models, Theoretical Rivers Climate
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Integrated machine learning reveals aquatic biological integrity patterns in semi-arid watersheds.

Journal of environmental management May 9, 2024
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...
Environmental Monitoring Phytoplankton Rivers Machine Learning Algorithms
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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 May 6, 2024
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 ...
Water Movements Hydrology Models, Theoretical Rivers Machine Learning China Humans
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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 May 6, 2024
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 ...
Rivers Geologic Sediments Environmental Monitoring Ethiopia Hydrology Neural Networks, Computer Models, Theoretical
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