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You searched for: Journal name Advances in water resources Remove constraint Journal name: Advances in water resources Subject term Monte Carlo method Remove constraint Subject term: Monte Carlo method
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1. Assessing uncertainty propagation in hybrid models for daily streamflow simulation based on arbitrary polynomial chaos expansion

Author:
Pengxiao Zhou; Congcong Li; Zhong Li; Yanpeng Cai
Source:
Advances in water resources 2022 v.160 pp. 104110
ISSN:
0309-1708
Subject:
Monte Carlo method; artificial intelligence; hybrids; hydrologic models; parameter uncertainty; prediction; stream flow; water; watershed management
Abstract:
... Accurate streamflow prediction is of significant importance in watershed management and has been attracting a lot of research interest. Hybrid hydrological models that employ advantages of physically-based models (PBMs) and data-driven models (DDMs) emerge recently as reliable tools for analyzing hydrological processes. Both PBMs and DDMs have uncertain parameters that could affect the hybrid mode ...
DOI:
10.1016/j.advwatres.2021.104110

2. Statistical analysis and modeling of particle trajectories in 2-D fractured porous media

Author:
Ranit Monga; Oliver Brenner; Daniel W. Meyer; Patrick Jenny
Source:
Advances in water resources 2022 v.161 pp. 104106
ISSN:
0309-1708
Subject:
Monte Carlo method; evolution; macrodispersion; models; solutes; stochastic processes; water
Abstract:
... Solute transport observed in subsurface formations shows complex behavior, particularly in the presence of fractures. In this work, we focus on formations with fractures that are smaller compared to the domain of interest and which are distributed in a heterogeneous matrix at densities below the percolation threshold. We developed a simplified Lagrangian approach to characterize and predict advect ...
DOI:
10.1016/j.advwatres.2021.104106

3. Probabilistic Godunov-type hydrodynamic modelling under multiple uncertainties: robust wavelet-based formulations

Author:
James Shaw; Georges Kesserwani; Per Pettersson
Source:
Advances in water resources 2020 v.137 pp. 103526
ISSN:
0309-1708
Subject:
Monte Carlo method; computer software; deterministic models; friction; hydrologic models; probability distribution; roughness; topography; uncertainty; water resources; wavelet
Abstract:
... Intrusive stochastic Galerkin methods propagate uncertainties in a single model run, eliminating repeated sampling required by conventional Monte Carlo methods. However, an intrusive formulation has yet to be developed for probabilistic hydrodynamic modelling incorporating robust wetting-and-drying and stable friction integration under joint uncertainties in topography, roughness, and inflow. Robu ...
DOI:
10.1016/j.advwatres.2020.103526

4. Updating urban design floods for changes in central tendency and variability using regression

Author:
Jory S. Hecht; Richard M. Vogel
Source:
Advances in water resources 2020 v.136 pp. 103484
ISSN:
0309-1708
Subject:
Monte Carlo method; case studies; floods; infrastructure; least squares; models; statistical inference; water resources
Abstract:
... Ordinary least squares (OLS) regression offers a decision-oriented approach for modeling trends in annual peak flows. We introduce a two-stage OLS approach for nonstationary flood frequency analysis that (i) models changes in their central tendency (median) in response to environmental perturbations with one regression and then (ii) examines changes in the coefficient of variation (Cv) by running ...
DOI:
10.1016/j.advwatres.2019.103484

5. Crossover from anomalous to Fickean behavior in infiltration and reaction in fractal porous media

Author:
Fábio D.A. Aarão Reis
Source:
Advances in water resources 2019 v.134 pp. 103428
ISSN:
0309-1708
Subject:
Monte Carlo method; chemical equilibrium; diffusivity; geological eons; geometry; models; porous media; rocks; water resources; weathering
Abstract:
... When the solution in a porous medium is in chemical equilibrium with mineral grains and an external surface is put in contact with water, the infiltration of unsaturated solution may be accompanied by mineral reactions that change the morphology of that medium. Here we study the evolution of this infiltration process considering that the initial porous media are fractal and that the reactions form ...
DOI:
10.1016/j.advwatres.2019.103428

6. Hydraulic conductivity and porosity heterogeneity controls on environmental performance metrics: Implications in probabilistic risk analysis

Author:
Arianna Libera; Christopher V. Henri; Felipe P.J. de Barros
Source:
Advances in water resources 2019 v.127 pp. 1-12
ISSN:
0309-1708
Subject:
Monte Carlo method; aquifers; environmental performance; hydraulic conductivity; neoplasms; porosity; probabilistic risk assessment; risk; solutes; solvents; subsurface flow; uncertainty
Abstract:
... Heterogeneities in natural porous formations, mainly manifested through the hydraulic conductivity (K) and, to a lesser degree, the porosity (ϕ), largely control subsurface flow and solute transport. The influence of the heterogeneous structure of K on transport processes has been widely studied, whereas less attention is dedicated to the joint heterogeneity of conductivity and porosity fields. Ou ...
DOI:
10.1016/j.advwatres.2019.03.002

7. Characterizing the impact of model error in hydrologic time series recovery inverse problems

Author:
Scott K. Hansen; Jiachuan He; Velimir V. Vesselinov
Source:
Advances in water resources 2018 v.111 pp. 372-380
ISSN:
0309-1708
Subject:
Monte Carlo method; hydrologic data; hydrologic models; time series analysis; water resources
Abstract:
... Hydrologic models are commonly over-smoothed relative to reality, owing to computational limitations and to the difficulty of obtaining accurate high-resolution information. When used in an inversion context, such models may introduce systematic biases which cannot be encapsulated by an unbiased “observation noise” term of the type assumed by standard regularization theory and typical Bayesian for ...
DOI:
10.1016/j.advwatres.2017.09.030

8. Efficient uncertainty quantification in fully-integrated surface and subsurface hydrologic simulations

Author:
K.L. Miller; S.J. Berg; J.H. Davison; E.A. Sudicky; P.A. Forsyth
Source:
Advances in water resources 2018 v.111 pp. 381-394
ISSN:
0309-1708
Subject:
Monte Carlo method; algorithms; basins; computers; covariance; cumulative distribution; hydrologic models; probability distribution; sampling; steady flow; subsurface flow; transient flow; uncertainty; water resources; watersheds
Abstract:
... Although high performance computers and advanced numerical methods have made the application of fully-integrated surface and subsurface flow and transport models such as HydroGeoSphere common place, run times for large complex basin models can still be on the order of days to weeks, thus, limiting the usefulness of traditional workhorse algorithms for uncertainty quantification (UQ) such as Latin ...
DOI:
10.1016/j.advwatres.2017.10.023

9. Integrating transient behavior as a new dimension to WHPA delineation

Author:
Rodriguez-Pretelin Abelardo; Wolfgang Nowak
Source:
Advances in water resources 2018 v.119 pp. 178-187
ISSN:
0309-1708
Subject:
Monte Carlo method; covariance; groundwater extraction; groundwater flow; groundwater recharge; hydraulic conductivity; land use; risk; risk reduction; transient flow; uncertainty; water resources; watersheds
Abstract:
... The protection of groundwater abstraction is primarily based on the delineation of “time-of-travel capture zones” known as Well Head Protection Areas (WHPAs). Their delineation is subject to several uncertainties: the scarcity of hydrogeological data due to limited budgets for exploration and additional uncertainty from time-varying flow conditions. While the former has lead to the use of probabil ...
DOI:
10.1016/j.advwatres.2018.07.005

10. An efficient Bayesian data-worth analysis using a multilevel Monte Carlo method

Author:
Dan Lu; Daniel Ricciuto; Katherine Evans
Source:
Advances in water resources 2018 v.113 pp. 223-235
ISSN:
0309-1708
Subject:
Monte Carlo method; cost effectiveness; data collection; hydrologic models; mass flow; prediction; simulation models; subsurface flow; uncertainty; water resources; wells
Abstract:
... Improving the understanding of subsurface systems and thus reducing prediction uncertainty requires collection of data. As the collection of subsurface data is costly, it is important that the data collection scheme is cost-effective. Design of a cost-effective data collection scheme, i.e., data-worth analysis, requires quantifying model parameter, prediction, and both current and potential data u ...
DOI:
10.1016/j.advwatres.2018.01.024

11. Bayesian model selection in hydrogeophysics: Application to conceptual subsurface models of the South Oyster Bacterial Transport Site, Virginia, USA

Author:
Carlotta Brunetti; Niklas Linde; Jasper A. Vrugt
Source:
Advances in water resources 2017 v.102 pp. 127-141
ISSN:
0309-1708
Subject:
Bayesian theory; Monte Carlo method; geophysics; ground-penetrating radar; models; porosity; water resources; Virginia
Abstract:
... Geophysical data can help to discriminate among multiple competing subsurface hypotheses (conceptual models). Here, we explore the merits of Bayesian model selection in hydrogeophysics using crosshole ground-penetrating radar data from the South Oyster Bacterial Transport Site in Virginia, USA. Implementation of Bayesian model selection requires computation of the marginal likelihood of the measur ...
DOI:
10.1016/j.advwatres.2017.02.006

12. Gaussian process modelling for uncertainty quantification in convectively-enhanced dissolution processes in porous media

Author:
D. Crevillén-García; R.D. Wilkinson; A.A. Shah; H. Power
Source:
Advances in water resources 2017 v.99 pp. 1-14
ISSN:
0309-1708
Subject:
Monte Carlo method; aquifers; carbon sequestration; convection; equations; groundwater flow; mathematical models; porous media; uncertainty; uncertainty analysis
Abstract:
... Numerical groundwater flow and dissolution models of physico-chemical processes in deep aquifers are usually subject to uncertainty in one or more of the model input parameters. This uncertainty is propagated through the equations and needs to be quantified and characterised in order to rely on the model outputs. In this paper we present a Gaussian process emulation method as a tool for performing ...
DOI:
10.1016/j.advwatres.2016.11.006

13. Nested sparse grid collocation method with delay and transformation for subsurface flow and transport problems

Author:
Qinzhuo Liao; Dongxiao Zhang; Hamdi Tchelepi
Source:
Advances in water resources 2017 v.104 pp. 158-173
ISSN:
0309-1708
Subject:
Monte Carlo method; mathematical models; subsurface flow; uncertainty; water resources
Abstract:
... In numerical modeling of subsurface flow and transport problems, formation properties may not be deterministically characterized, which leads to uncertainty in simulation results. In this study, we propose a sparse grid collocation method, which adopts nested quadrature rules with delay and transformation to quantify the uncertainty of model solutions. We show that the nested Kronrod–Patterson–Her ...
DOI:
10.1016/j.advwatres.2017.03.020

14. Relating recent random walk models with classical perturbation theory for dispersion predictions in the heterogeneous porous subsurface

Author:
Daniel W. Meyer
Source:
Advances in water resources 2017 v.105 pp. 227-232
ISSN:
0309-1708
Subject:
Monte Carlo method; mathematical theory; models; prediction; water resources
Abstract:
... Recently developed stochastic macro-dispersion models enable computationally inexpensive flow and transport predictions for highly heterogeneous formations with statistically non-stationary conductivity and flow statistics. So far, the random processes at the heart of these models have been calibrated numerically based on velocity statistics from Monte Carlo simulation studies. In this work, we pr ...
DOI:
10.1016/j.advwatres.2017.04.017

15. Seasonality in cholera dynamics: A rainfall-driven model explains the wide range of patterns in endemic areas

Author:
Theo Baracchini; Aaron A. King; Menno J. Bouma; Xavier Rodó; Enrico Bertuzzo; Mercedes Pascual
Source:
Advances in water resources 2017 v.108 pp. 357-366
ISSN:
0309-1708
Subject:
Markov chain; Monte Carlo method; cholera; climate change; climatic factors; data collection; health policy; hydrology; models; monsoon season; mortality; planning; rain; seasonal variation; temperature; water reservoirs
Abstract:
... Seasonal patterns in cholera dynamics exhibit pronounced variability across geographical regions, showing single or multiple peaks at different times of the year. Although multiple hypotheses related to local climate variables have been proposed, an understanding of this seasonal variation remains incomplete. The historical Bengal region, which encompasses the full range of cholera’s seasonality o ...
DOI:
10.1016/j.advwatres.2016.11.012

16. An efficient stochastic approach for flow in porous media via sparse polynomial chaos expansion constructed by feature selection

Author:
Jin Meng; Heng Li
Source:
Advances in water resources 2017 v.105 pp. 13-28
ISSN:
0309-1708
Subject:
Monte Carlo method; algorithms; porous media; probability distribution; uncertainty; water resources
Abstract:
... An efficient method for uncertainty quantification for flow in porous media is studied in this paper, where response surface of sparse polynomial chaos expansion (PCE) is constructed with the aid of feature selection method. The number of basis functions in PCE grows exponentially as the random dimensionality increases, which makes the computational cost unaffordable in high-dimensional problems. ...
DOI:
10.1016/j.advwatres.2017.04.019

17. A proposed Fast algorithm to construct the system matrices for a reduced-order groundwater model

Author:
Timothy T. Ushijima; William W-G. Yeh
Source:
Advances in water resources 2017 v.102 pp. 68-83
ISSN:
0309-1708
Subject:
Monte Carlo method; algorithms; hydrologic models; peroxidase; water resources
Abstract:
... Past research has demonstrated that a reduced-order model (ROM) can be two-to-three orders of magnitude smaller than the original model and run considerably faster with acceptable error. A standard method to construct the system matrices for a ROM is Proper Orthogonal Decomposition (POD), which projects the system matrices from the full model space onto a subspace whose range spans the full model ...
DOI:
10.1016/j.advwatres.2017.01.010

18. Assessing the joint impact of DNAPL source-zone behavior and degradation products on the probabilistic characterization of human health risk

Author:
Christopher V. Henri; Daniel Fernàndez-Garcia; Felipe P.J. de Barros
Source:
Advances in water resources 2016 v.88 pp. 124-138
ISSN:
0309-1708
Subject:
Monte Carlo method; anthropogenic activities; aquifers; dense nonaqueous phase liquids; ganglia; groundwater; human health; porous media; probability distribution; risk; risk management; screening; solubility; solvents; tetrachloroethylene; toxicity; uncertainty
Abstract:
... The release of industrial contaminants into the subsurface has led to a rapid degradation of groundwater resources. Contamination caused by Dense Non-Aqueous Phase Liquids (DNAPLs) is particularly severe owing to their limited solubility, slow dissolution and in many cases high toxicity. A greater insight into how the DNAPL source zone behavior and the contaminant release towards the aquifer impac ...
DOI:
10.1016/j.advwatres.2015.12.012

19. Calibrating Lattice Boltzmann flow simulations and estimating uncertainty in the permeability of complex porous media

Author:
Aleksandra Hosa; Andrew Curtis; Rachel Wood
Source:
Advances in water resources 2016 v.94 pp. 60-74
ISSN:
0309-1708
Subject:
Markov chain; Monte Carlo method; computers; models; permeability; porosity; porous media; prediction; sandstone; uncertainty; water resources
Abstract:
... A common way to simulate fluid flow in porous media is to use Lattice Boltzmann (LB) methods. Permeability predictions from such flow simulations are controlled by parameters whose settings must be calibrated in order to produce realistic modelling results. Herein we focus on the simplest and most commonly used implementation of the LB method: the single-relaxation-time BGK model. A key parameter ...
DOI:
10.1016/j.advwatres.2016.04.020

20. Comments on ‘‘Operations optimization of multireservoir systems using storage moments equations” by M. Mahootchi, K. Ponnambalam, H.R. Tizhoosh [Adv. Water Resour. 33 (2010) 1150–1163]

Author:
Ata Joodavi
Source:
Advances in water resources 2016 v.98 pp. 211-212
ISSN:
0309-1708
Subject:
Monte Carlo method; equations; models; water resources
Abstract:
... In a paper published in this journal, Mahootchi et al. (2010) presented a stochastic optimization modeling technique to solve multireservoir optimization problems. The authors provide expressions for estimating the means and variances of the storage state variable. In this comment we show that the derived expression for estimating the second moments of the storage variable contains a serious mista ...
DOI:
10.1016/j.advwatres.2016.11.004