Assessing uncertainty propagation in hybrid models for daily streamflow simulation based on arbitrary polynomial chaos expansion
Accurate streamflow prediction is of significant importance in watershed management and
has been attracting a lot of research interest. Hybrid hydrological models that employ …
has been attracting a lot of research interest. Hybrid hydrological models that employ …
Toward an efficient uncertainty quantification of streamflow predictions using sparse polynomial chaos expansion
Reliable hydrologic models are essential for planning, designing, and management of water
resources. However, predictions by hydrological models are prone to errors due to a variety …
resources. However, predictions by hydrological models are prone to errors due to a variety …
A polynomial chaos ensemble hydrologic prediction system for efficient parameter inference and robust uncertainty assessment
This paper presents a polynomial chaos ensemble hydrologic prediction system (PCEHPS)
for an efficient and robust uncertainty assessment of model parameters and predictions, in …
for an efficient and robust uncertainty assessment of model parameters and predictions, in …
Parametric uncertainty assessment in hydrological modeling using the generalized polynomial chaos expansion
J Hu, S Chen, A Behrangi, H Yuan - Journal of Hydrology, 2019 - Elsevier
An integrated framework is proposed for parametric uncertainty analysis in hydrological
modeling using a generalized polynomial chaos expansion (PCE) approach. PCE …
modeling using a generalized polynomial chaos expansion (PCE) approach. PCE …
Propagation of parameter uncertainty in SWAT: A probabilistic forecasting method based on polynomial chaos expansion and machine learning
Abstract Soil and Water Assessment Tool (SWAT) is one of the most widely used semi-
distributed hydrological models. Assessment of the uncertainties in SWAT outputs is a …
distributed hydrological models. Assessment of the uncertainties in SWAT outputs is a …
Uncertainty analysis for hydrological models with interdependent parameters: an improved polynomial chaos expansion approach
The use of polynomial chaos expansion (PCE) has gained a lot of attention due to its ability
to efficiently estimate the effects of parameter uncertainty on model outputs. The traditional …
to efficiently estimate the effects of parameter uncertainty on model outputs. The traditional …
Towards robust quantification and reduction of uncertainty in hydrologic predictions: Integration of particle Markov chain Monte Carlo and factorial polynomial chaos …
The particle filtering techniques have been receiving increasing attention from the
hydrologic community due to its ability to properly estimate model parameters and states of …
hydrologic community due to its ability to properly estimate model parameters and states of …
Development of clustered polynomial chaos expansion model for stochastic hydrological prediction
This study introduced a clustered polynomial chaos expansion (CPCE) model to reveal
random propagation and dynamic sensitivity of uncertainty parameters in hydrologic …
random propagation and dynamic sensitivity of uncertainty parameters in hydrologic …
Simulation–optimization framework for multi-season hybrid stochastic models
A novel simulation–optimization framework is proposed that enables the automation of the
hybrid stochastic modeling process for synthetic generation of multi-season streamflows …
hybrid stochastic modeling process for synthetic generation of multi-season streamflows …
Multi-model ensemble hydrologic prediction and uncertainties analysis
S Jiang, L Ren, X Yang, M Ma… - Proceedings of the …, 2014 - piahs.copernicus.org
Modelling uncertainties (ie input errors, parameter uncertainties and model structural errors)
inevitably exist in hydrological prediction. A lot of recent attention has focused on these, of …
inevitably exist in hydrological prediction. A lot of recent attention has focused on these, of …