Hydro-pedotransfer functions: a roadmap for future development
Hydro-pedotransfer functions (PTFs) relate easy-to-measure and readily available soil
information to soil hydraulic properties (SHPs) for applications in a wide range of process …
information to soil hydraulic properties (SHPs) for applications in a wide range of process …
Modeling causes of death: an integrated approach using CODEm
Background Data on causes of death by age and sex are a critical input into health decision-
making. Priority setting in public health should be informed not only by the current …
making. Priority setting in public health should be informed not only by the current …
Grid search based multi-population particle swarm optimization algorithm for multimodal multi-objective optimization
In the multimodal multi-objective optimization problems (MMOPs), there may exist two or
multiple equivalent Pareto optimal sets (PS) with the same Pareto Front (PF). The difficulty of …
multiple equivalent Pareto optimal sets (PS) with the same Pareto Front (PF). The difficulty of …
A short exploration of structural noise
J Doherty, D Welter - Water Resources Research, 2010 - Wiley Online Library
“Structural noise” is a term often used to describe model‐to‐measurement misfit that cannot
be ascribed to measurement noise and therefore must be ascribed to the imperfect nature of …
be ascribed to measurement noise and therefore must be ascribed to the imperfect nature of …
Model selection on solid ground: Rigorous comparison of nine ways to evaluate B ayesian model evidence
Bayesian model selection or averaging objectively ranks a number of plausible, competing
conceptual models based on Bayes' theorem. It implicitly performs an optimal trade‐off …
conceptual models based on Bayes' theorem. It implicitly performs an optimal trade‐off …
Comparison of point forecast accuracy of model averaging methods in hydrologic applications
Multi-model averaging is currently receiving a surge of attention in the atmospheric,
hydrologic, and statistical literature to explicitly handle conceptual model uncertainty in the …
hydrologic, and statistical literature to explicitly handle conceptual model uncertainty in the …
A framework for propagation of uncertainty contributed by parameterization, input data, model structure, and calibration/validation data in watershed modeling
Failure to consider major sources of uncertainty may bias model predictions in simulating
watershed behavior. A framework entitled the Integrated Parameter Estimation and …
watershed behavior. A framework entitled the Integrated Parameter Estimation and …
Ensemble Bayesian model averaging using Markov chain Monte Carlo sampling
Bayesian model averaging (BMA) has recently been proposed as a statistical method to
calibrate forecast ensembles from numerical weather models. Successful implementation of …
calibrate forecast ensembles from numerical weather models. Successful implementation of …
Multiresponse multilayer vadose zone model calibration using Markov chain Monte Carlo simulation and field water retention data
In the past two decades significant progress has been made toward the application of
inverse modeling to estimate the water retention and hydraulic conductivity functions of the …
inverse modeling to estimate the water retention and hydraulic conductivity functions of the …
Comparing well and geophysical data for temperature monitoring within a Bayesian experimental design framework
Temperature logs are an important tool in the geothermal industry. Temperature
measurements from boreholes are used for exploration, system design, and monitoring. The …
measurements from boreholes are used for exploration, system design, and monitoring. The …