Assessing uncertainty propagation in hybrid models for daily streamflow simulation based on arbitrary polynomial chaos expansion
出版年份 2021 全文链接
标题
Assessing uncertainty propagation in hybrid models for daily streamflow simulation based on arbitrary polynomial chaos expansion
作者
关键词
Hydrological model, Hybrid modeling, MIKE SHE, Machine-learning, Parameter uncertainty, aPCE
出版物
ADVANCES IN WATER RESOURCES
Volume 160, Issue -, Pages 104110
出版商
Elsevier BV
发表日期
2021-12-23
DOI
10.1016/j.advwatres.2021.104110
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- A hybrid ensemble modelling framework for the prediction of breakup ice jams on Northern Canadian Rivers
- (2021) Michael De Coste et al. COLD REGIONS SCIENCE AND TECHNOLOGY
- Uncertainty Analysis for Hydrological Models With Interdependent Parameters: An Improved Polynomial Chaos Expansion Approach
- (2021) Maysara Ghaith et al. WATER RESOURCES RESEARCH
- Hydrological response to climate and land use changes in the dry–warm valley of the upper yangtze river
- (2021) Congcong Li et al. Engineering
- Quantifying the Uncertainties in Data-Driven Models for Reservoir Inflow Prediction
- (2020) Xiaoli Zhang et al. WATER RESOURCES MANAGEMENT
- Application of arbitrary polynomial chaos (aPC) expansion for global sensitivity analysis of mineral dissolution and precipitation modeling under geologic carbon storage conditions
- (2020) Liwei Zhang et al. COMPUTATIONAL GEOSCIENCES
- Machine learning assisted hybrid models can improve streamflow simulation in diverse catchments across the conterminous US
- (2020) Goutam Konapala et al. Environmental Research Letters
- Propagation of parameter uncertainty in SWAT: A probabilistic forecasting method based on polynomial chaos expansion and machine learning
- (2020) Maysara Ghaith et al. JOURNAL OF HYDROLOGY
- Arbitrary polynomial chaos expansion method for uncertainty quantification and global sensitivity analysis in structural dynamics
- (2020) Hua-Ping Wan et al. MECHANICAL SYSTEMS AND SIGNAL PROCESSING
- Improving the Robustness of Beach Water Quality Modeling using an Ensemble Machine Learning Approach
- (2020) Leizhi Wang et al. SCIENCE OF THE TOTAL ENVIRONMENT
- Influent Forecasting for Wastewater Treatment Plants in North America
- (2019) Gavin Boyd et al. Sustainability
- Data-driven polynomial chaos expansions: A weighted least-square approximation
- (2019) Ling Guo et al. JOURNAL OF COMPUTATIONAL PHYSICS
- A Monte Carlo simulation approach for effective assessment of flyrock based on intelligent system of neural network
- (2019) Jian Zhou et al. ENGINEERING WITH COMPUTERS
- Polynomial chaos expansion and response surface method for nonlinear modelling of reference evapotranspiration
- (2019) Behrooz Keshtegar et al. HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES
- A random forest model for inflow prediction at wastewater treatment plants
- (2019) Pengxiao Zhou et al. STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
- On the number of Monte Carlo runs in comparative probabilistic LCA
- (2019) Reinout Heijungs INTERNATIONAL JOURNAL OF LIFE CYCLE ASSESSMENT
- Hybrid Hydrological Data-Driven Approach for Daily Streamflow Forecasting
- (2019) Maysara Ghaith et al. JOURNAL OF HYDROLOGIC ENGINEERING
- River flow modelling: comparison of performance and evaluation of uncertainty using data-driven models and conceptual hydrological model
- (2018) Zhenghao Zhang et al. STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
- Efficient kNN Classification With Different Numbers of Nearest Neighbors
- (2018) Shichao Zhang et al. IEEE Transactions on Neural Networks and Learning Systems
- Uncertainty analysis of hydrological modeling in a tropical area using different algorithms
- (2018) Ammar Rafiei Emam et al. Frontiers of Earth Science
- Long-term streamflow forecasting using SWAT through the integration of the random forests precipitation generator: case study of Danjiangkou Reservoir
- (2017) Zhongmin Liang et al. HYDROLOGY RESEARCH
- Long-term streamflow forecasting using SWAT through the integration of the random forests precipitation generator: case study of Danjiangkou Reservoir
- (2017) Zhongmin Liang et al. Hydrology Research
- A comparative study of artificial neural network (MLP, RBF) and support vector machine models for river flow prediction
- (2016) Mohammad Ali Ghorbani et al. Environmental Earth Sciences
- Parameter uncertainty and temporal dynamics of sensitivity for hydrologic models: A hybrid sequential data assimilation and probabilistic collocation method
- (2016) Y.R. Fan et al. ENVIRONMENTAL MODELLING & SOFTWARE
- CEREF: A hybrid data-driven model for forecasting annual streamflow from a socio-hydrological system
- (2016) Hongbo Zhang et al. JOURNAL OF HYDROLOGY
- A hybrid approach to monthly streamflow forecasting: Integrating hydrological model outputs into a Bayesian artificial neural network
- (2016) Greer B. Humphrey et al. JOURNAL OF HYDROLOGY
- Modeling of effluent quality parameters in a submerged membrane bioreactor with simultaneous upward and downward aeration treating municipal wastewater using hybrid models
- (2015) Majid Bagheri et al. Desalination and Water Treatment
- Dynamic coupling of support vector machine and K-nearest neighbour for downscaling daily rainfall
- (2015) Manjula Devak et al. JOURNAL OF HYDROLOGY
- Global sensitivity analysis in hydrological modeling: Review of concepts, methods, theoretical framework, and applications
- (2015) Xiaomeng Song et al. JOURNAL OF HYDROLOGY
- Applications of hybrid wavelet–Artificial Intelligence models in hydrology: A review
- (2014) Vahid Nourani et al. JOURNAL OF HYDROLOGY
- Quantitatively analyze the impact of land use/land cover change on annual runoff decrease
- (2014) Jianzhu Li et al. NATURAL HAZARDS
- A Comprehensive Land-Use/Hydrological Modeling System for Scenario Simulations in the Elbow River Watershed, Alberta, Canada
- (2013) Gayan Nishad Wijesekara et al. ENVIRONMENTAL MANAGEMENT
- Monte Carlo Simulation Models Evolving in Replicated Runs: A Methodology to Choose the Optimal Experimental Sample Size
- (2012) Lucia Cassettari et al. MATHEMATICAL PROBLEMS IN ENGINEERING
- Data-driven uncertainty quantification using the arbitrary polynomial chaos expansion
- (2012) S. Oladyshkin et al. RELIABILITY ENGINEERING & SYSTEM SAFETY
- Data-driven models for monthly streamflow time series prediction
- (2010) C.L. Wu et al. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
- Comparing Sigmoid Transfer Functions for Neural Network Multistep Ahead Streamflow Forecasting
- (2010) H. Yonaba et al. JOURNAL OF HYDROLOGIC ENGINEERING
- A hybrid neural network and ARIMA model for water quality time series prediction
- (2009) Durdu Ömer Faruk ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
- A Surrogate Ensemble Study of Climate Reconstruction Methods: Stochasticity and Robustness
- (2008) Bo Christiansen et al. JOURNAL OF CLIMATE
- Evaluation of the MIKE SHE Model for Application in the Loess Plateau, China1
- (2008) Zhiqiang Zhang et al. JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION
Create your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create NowAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started