Combining statistical machine learning models with ARIMA for water level forecasting: The case of the Red river
XH Nguyen - Advances in Water Resources, 2020 - Elsevier
Forecasting water level is an extremely important task as it allows to mitigate the effects of
floods, reduce and prevent disasters. Physically based models often give good results but …
floods, reduce and prevent disasters. Physically based models often give good results but …
Water level prediction through hybrid SARIMA and ANN models based on time series analysis: Red hills reservoir case study
Reservoir water level (RWL) prediction has become a challenging task due to spatio-
temporal changes in climatic conditions and complicated physical process. The Red Hills …
temporal changes in climatic conditions and complicated physical process. The Red Hills …
Water level forecasting using deep learning time-series analysis: A case study of red river of the north
The Red River of the North is vulnerable to floods, which have caused significant damage
and economic loss to inhabitants. A better capability in flood-event prediction is essential to …
and economic loss to inhabitants. A better capability in flood-event prediction is essential to …
Modeling of GRACE-derived groundwater information in the Colorado River Basin
Groundwater depletion has been one of the major challenges in recent years. Analysis of
groundwater levels can be beneficial for groundwater management. The National …
groundwater levels can be beneficial for groundwater management. The National …
ML-based streamflow prediction in the upper Colorado River Basin using climate variables time series data
Streamflow prediction plays a vital role in water resources planning in order to understand
the dramatic change of climatic and hydrologic variables over different time scales. In this …
the dramatic change of climatic and hydrologic variables over different time scales. In this …
Kabul river flow prediction using automated ARIMA forecasting: A machine learning approach
The water level in a river defines the nature of flow and is fundamental to flood analysis.
Extreme fluctuation in water levels in rivers, such as floods and droughts, are catastrophic in …
Extreme fluctuation in water levels in rivers, such as floods and droughts, are catastrophic in …
[HTML][HTML] Comparative Analysis of Convolutional Neural Network-Long Short-Term Memory, Sparrow Search Algorithm-Backpropagation Neural Network, and Particle …
L Zhen, A Bărbulescu - Water, 2024 - mdpi.com
Modeling and forecasting the river flow is essential for the management of water resources.
In this study, we conduct a comprehensive comparative analysis of different models built for …
In this study, we conduct a comprehensive comparative analysis of different models built for …
[HTML][HTML] Forecasting the River Water Discharge by Artificial Intelligence Methods
A Bărbulescu, L Zhen - Water, 2024 - mdpi.com
The management of water resources must be based on accurate models of the river
discharge in the context of the water flow alteration due to anthropic influences and climate …
discharge in the context of the water flow alteration due to anthropic influences and climate …
[PDF][PDF] Daily streamflow prediction for khazir river basin using ARIMA and ANN models
The present study used both Autoregressive Integrated Moving Average (ARIMA) and
Artificial Neural Network (ANN) models for Khazir river basin to simulate the daily flow at …
Artificial Neural Network (ANN) models for Khazir river basin to simulate the daily flow at …
Development of multidecomposition hybrid model for hydrological time series analysis
Accurate prediction of hydrological processes is key for optimal allocation of water
resources. In this study, two novel hybrid models are developed to improve the prediction …
resources. In this study, two novel hybrid models are developed to improve the prediction …