[HTML][HTML] Sources of hydrological model uncertainties and advances in their analysis
Water | Free Full-Text | Review: Sources of Hydrological Model Uncertainties and Advances
in Their Analysis Next Article in Journal Assessing the Influence of Compounding Factors to …
in Their Analysis Next Article in Journal Assessing the Influence of Compounding Factors to …
[HTML][HTML] Advancing measurements and representations of subsurface heterogeneity and dynamic processes: towards 4D hydrogeology
Essentially all hydrogeological processes are strongly influenced by the subsurface spatial
heterogeneity and the temporal variation of environmental conditions, hydraulic properties …
heterogeneity and the temporal variation of environmental conditions, hydraulic properties …
[HTML][HTML] Polynomial chaos expansion for sensitivity analysis of model output with dependent inputs
In this paper, we discuss the sensitivity analysis of model response when the uncertain
model inputs are not independent of one other. In this case, two different kinds of sensitivity …
model inputs are not independent of one other. In this case, two different kinds of sensitivity …
On uncertainty quantification in hydrogeology and hydrogeophysics
Recent advances in sensor technologies, field methodologies, numerical modeling, and
inversion approaches have contributed to unprecedented imaging of hydrogeological …
inversion approaches have contributed to unprecedented imaging of hydrogeological …
Innovative approach for estimating evapotranspiration and gross primary productivity by integrating land data assimilation, machine learning, and multi-source …
The integration of data assimilation (DA) and machine learning (ML) methods helps to
incorporate multi-source observations into physical models, enabling more accurate …
incorporate multi-source observations into physical models, enabling more accurate …
Groundwater contamination source identification and high-dimensional parameter inversion using residual dense convolutional neural network
X Xia, S Jiang, N Zhou, J Cui, X Li - Journal of Hydrology, 2023 - Elsevier
Data assimilation for high-dimensional parameter joint inversion of multiple time-varying
source strength and hydraulic conductivity fields can be computationally intensive as a large …
source strength and hydraulic conductivity fields can be computationally intensive as a large …
An efficient Bayesian inversion method for seepage parameters using a data-driven error model and an ensemble of surrogates considering the interactions between …
H Yu, X Wang, B Ren, T Zeng, M Lv, C Wang - Journal of Hydrology, 2022 - Elsevier
The Bayesian method has been increasingly applied to the inversion of seepage
parameters owing to its superiority of considering the uncertainty in the inversion process …
parameters owing to its superiority of considering the uncertainty in the inversion process …
Quantifying model structural error: Efficient B ayesian calibration of a regional groundwater flow model using surrogates and a data‐driven error model
Groundwater model structural error is ubiquitous, due to simplification and/or
misrepresentation of real aquifer systems. During model calibration, the basic …
misrepresentation of real aquifer systems. During model calibration, the basic …
Evaluation of Gaussian process regression kernel functions for improving groundwater prediction
Systematic model error is caused by the unreasonable simplification of real groundwater
system, which damages the reliability of groundwater model prediction. Gaussian process …
system, which damages the reliability of groundwater model prediction. Gaussian process …
Bayesian Calibration of Using CO2 Sensors to Assess Ventilation Conditions and Associated COVID-19 Airborne Aerosol Transmission Risk in Schools
Ventilation rate plays a significant role in preventing the airborne transmission of diseases in
indoor spaces. Classrooms are a considerable challenge during the COVID-19 pandemic …
indoor spaces. Classrooms are a considerable challenge during the COVID-19 pandemic …