Snowmelt-Driven Streamflow Prediction Using Machine Learning Techniques (LSTM, NARX, GPR, and SVR)
Published 2020 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Snowmelt-Driven Streamflow Prediction Using Machine Learning Techniques (LSTM, NARX, GPR, and SVR)
Authors
Keywords
-
Journal
Water
Volume 12, Issue 6, Pages 1734
Publisher
MDPI AG
Online
2020-06-19
DOI
10.3390/w12061734
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Trend analysis of climatic variables and their relation to snow cover and water availability in the Central Himalayas: a case study of Langtang Basin, Nepal
- (2020) Samit Thapa et al. THEORETICAL AND APPLIED CLIMATOLOGY
- Comparison of Long Short Term Memory Networks and the Hydrological Model in Runoff Simulation
- (2020) Hongxiang Fan et al. Water
- A Nonlinear Autoregressive Modeling Approach for Forecasting Groundwater Level Fluctuation in Urban Aquifers
- (2020) Abdullah A. Alsumaiei Water
- Modelling Snowmelt in Ungauged Catchments
- (2019) Carolina Massmann Water
- Application of Long Short-Term Memory (LSTM) Neural Network for Flood Forecasting
- (2019) Le et al. Water
- Near Real-Time Measurement of Snow Water Equivalent in the Nepal Himalayas
- (2019) James D. Kirkham et al. Frontiers in Earth Science
- Implications of observation-enhanced energy-balance snowmelt simulations for runoff modeling of Alpine catchments
- (2019) N. Griessinger et al. ADVANCES IN WATER RESOURCES
- Depthwise separable convolution architectures for plant disease classification
- (2019) Kamal KC et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Auto-Regressive Neural-Network Models for Long Lead-Time Forecasting of Daily Flow
- (2018) Mohammad Ebrahim Banihabib et al. WATER RESOURCES MANAGEMENT
- Operational River Discharge Forecasting with Support Vector Regression Technique Applied to Alpine Catchments: Results, Advantages, Limits and Lesson Learned
- (2017) Ludovica De Gregorio et al. WATER RESOURCES MANAGEMENT
- The Use of NARX Neural Networks to Forecast Daily Groundwater Levels
- (2017) Sandra M. Guzman et al. WATER RESOURCES MANAGEMENT
- Improving daily streamflow forecasts in mountainous Upper Euphrates basin by multi-layer perceptron model with satellite snow products
- (2016) Gökçen Uysal et al. JOURNAL OF HYDROLOGY
- Unraveling the hydrology of a Himalayan catchment through integration of high resolution in situ data and remote sensing with an advanced simulation model
- (2015) S. Ragettli et al. ADVANCES IN WATER RESOURCES
- A robust combination approach for short-term wind speed forecasting and analysis – Combination of the ARIMA (Autoregressive Integrated Moving Average), ELM (Extreme Learning Machine), SVM (Support Vector Machine) and LSSVM (Least Square SVM) forecasts using a GPR (Gaussian Process Regression) model
- (2015) Jianzhou Wang et al. ENERGY
- Seasonal River Discharge Forecasting Using Support Vector Regression: A Case Study in the Italian Alps
- (2015) Mattia Callegari et al. Water
- Estimation of discharge from Langtang River basin, Rasuwa, Nepal, using a glacio-hydrological model
- (2014) Niraj S. Pradhananga et al. ANNALS OF GLACIOLOGY
- Evaluation of distributed hydrologic impacts of temperature-index and energy-based snow models
- (2013) Mukesh Kumar et al. ADVANCES IN WATER RESOURCES
- Runoff conditions in the upper Danube basin under an ensemble of climate change scenarios
- (2012) Harald Kling et al. JOURNAL OF HYDROLOGY
- Methods used for the development of neural networks for the prediction of water resource variables in river systems: Current status and future directions
- (2010) Holger R. Maier et al. ENVIRONMENTAL MODELLING & SOFTWARE
- Large-scale monitoring of snow cover and runoff simulation in Himalayan river basins using remote sensing
- (2008) W.W. Immerzeel et al. REMOTE SENSING OF ENVIRONMENT
Add your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload NowCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now