Pre-and post-dam river water temperature alteration prediction using advanced machine learning models
Dams significantly impact river hydrology by changing the timing, size, and frequency of low
and high flows, resulting in a hydrologic regime that differs significantly from the natural flow …
and high flows, resulting in a hydrologic regime that differs significantly from the natural flow …
River water temperature forecasting using a deep learning method
Accurate water temperature forecasting is essential for understanding thermal regimes of
rivers in the context of climate change and anthropogenic disturbances, such as dam …
rivers in the context of climate change and anthropogenic disturbances, such as dam …
River/stream water temperature forecasting using artificial intelligence models: a systematic review
S Zhu, AP Piotrowski - Acta Geophysica, 2020 - Springer
Water temperature is one of the most important indicators of aquatic system, and accurate
forecasting of water temperature is crucial for rivers. It is a complex process to accurately …
forecasting of water temperature is crucial for rivers. It is a complex process to accurately …
[HTML][HTML] Machine-learning methods for stream water temperature prediction
M Feigl, K Lebiedzinski, M Herrnegger… - Hydrology and Earth …, 2021 - hess.copernicus.org
Water temperature in rivers is a crucial environmental factor with the ability to alter hydro-
ecological as well as socio-economic conditions within a catchment. The development of …
ecological as well as socio-economic conditions within a catchment. The development of …
Modelling daily water temperature from air temperature for the Missouri River
The bio-chemical and physical characteristics of a river are directly affected by water
temperature, which thereby affects the overall health of aquatic ecosystems. It is a complex …
temperature, which thereby affects the overall health of aquatic ecosystems. It is a complex …
Assessing the performance of a suite of machine learning models for daily river water temperature prediction
In this study, different versions of feedforward neural network (FFNN), Gaussian process
regression (GPR), and decision tree (DT) models were developed to estimate daily river …
regression (GPR), and decision tree (DT) models were developed to estimate daily river …
River water temperature prediction using hybrid machine learning coupled signal decomposition: EWT versus MODWT
Accurate prediction of water temperature (T w) will greatly help in improving our
understanding of the overall thermal regime fluctuation, and it can help in making sound …
understanding of the overall thermal regime fluctuation, and it can help in making sound …
[HTML][HTML] Water temperature prediction using improved deep learning methods through reptile search algorithm and weighted mean of vectors optimizer
Precise estimation of water temperature plays a key role in environmental impact
assessment, aquatic ecosystems' management and water resources planning and …
assessment, aquatic ecosystems' management and water resources planning and …
Exploring the exceptional performance of a deep learning stream temperature model and the value of streamflow data
Stream water temperature (T s) is a variable of critical importance for aquatic ecosystem
health. T s is strongly affected by groundwater-surface water interactions which can be …
health. T s is strongly affected by groundwater-surface water interactions which can be …
Genetic-algorithm-optimized sequential model for water temperature prediction
Advances in establishing real-time river water quality monitoring networks combined with
novel artificial intelligence techniques for more accurate forecasting is at the forefront of …
novel artificial intelligence techniques for more accurate forecasting is at the forefront of …