State and Parameter Estimation in Three-Dimensional Subsurface Contaminant Transport Modeling using Kalman Filter Coupled with Monte Carlo Sampling

Assumaning, Godwin Appiah; Chang, Shan

doi:10.3808/jei.201400280

Cited by 14 publications

(5 citation statements)

References 12 publications

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“…Over the past decades, numerical efforts were made in dealing with uncertainties in water quality management, such as Monte Carlo simulation, Bayesian statistics, and stochastic programming (Assumaning and Chang 2014;Ahmadi et al 2015). Bayesian analysis is effective in evaluating the probabilistic risk of water quality management through estimating unknown parameters in terms of posterior joint distributions, which incorporate the information of prior distributions (e.g., existing expert knowledge and experiences) and observed data (Qian et al 2005;Malve and Qian 2006;Chen et al 2012).…”

Section: Introductionmentioning

confidence: 99%

A Bayesian-based two-stage inexact optimization method for supporting stream water quality management in the Three Gorges Reservoir region

Guo

et al. 2016

Environ Sci Pollut Res

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In this study, a Bayesian-based two-stage inexact optimization (BTIO) method is developed for supporting water quality management through coupling Bayesian analysis with interval two-stage stochastic programming (ITSP). The BTIO method is capable of addressing uncertainties caused by insufficient inputs in water quality model as well as uncertainties expressed as probabilistic distributions and interval numbers. The BTIO method is applied to a real case of water quality management for the Xiangxi River basin in the Three Gorges Reservoir region to seek optimal water quality management schemes under various uncertainties. Interval solutions for production patterns under a range of probabilistic water quality constraints have been generated. Results obtained demonstrate compromises between the system benefit and the system failure risk due to inherent uncertainties that exist in various system components. Moreover, information about pollutant emission is accomplished, which would help managers to adjust production patterns of regional industry and local policies considering interactions of water quality requirement, economic benefit, and industry structure.

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Section: Introductionmentioning

confidence: 99%

A Bayesian-based two-stage inexact optimization method for supporting stream water quality management in the Three Gorges Reservoir region

Guo

et al. 2016

Environ Sci Pollut Res

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“…Hydrological models have widely been used for analyzing water balance, forecasting long-range streamflow, predicting real-time flood, and investigating climate-change impact in watershed management because of the increasing availability of digital elevation models (DEMs), geographical information system (GIS), remote sensing (RS), and terrain analysis tools over a broad range of scales (Vincendon et al, 2010;Assumaning and Chang, 2014;Zhang et al, 2014). However, hydrological models often encounter substantial uncertainties with respect to the input data, initial and boundary conditions, model structure, and parameters due to insufficient of observation data, difference in spatiotemporal scale between the model and measurements and simplification of physical processes within the model (Salamon and Feyen, 2009;Jordan et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Development of an inexact-variance hydrological modeling system for analyzing interactive effects of multiple uncertain parameters

Wang

Zhang

et al. 2015

Journal of Hydrology

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“…Understanding the ongoing climatic changes is very important for human subsistence and sustainable development of the economy and society (Jordan et al, 2014;Jozsa et al, 2014;Shi et al, 2014;Wang et al, 2015b). Recent studies suggested that the change in climate extremes is particularly notable (Alexander et al, 2006;Assumaning and Chang, 2014). From a global perspective, changes in climate extremes have led to many serious consequences due to their direct and indirect effects on the physical, chemical and biological processes of other components of the Earth system.…”

Section: Introductionmentioning

confidence: 99%

Observed changes in temperature extremes for the Beijing–Tianjin–Hebei region of China

Yao

Huang

Wang

et al. 2017

Meteorological Applications

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As one of the most significant threats facing the world, climate change has already been manifested everywhere in the form of frequent extreme climate events (e.g. heat waves, floods, droughts and wildfires) and has caused serious impacts on all aspects of the living environment. Due to the regional variability of global climate change, understanding the ongoing climatic changes at a local scale is very important for decision makers and resource managers to develop appropriate mitigation and adaptation strategies against the changing climate. In this study, recent changes in extreme temperature indices (including frost days, summer days, icy days, tropical nights, growing season length, cool nights and warm nights, cool days and warm days, and daily temperature range) over the Beijing-Tianjin-Hebei (BTH) region of China were investigated in the context of global warming. The results indicate that the historical trends of these extreme temperature indices are statistically significant in Huailai, Beijing, Leting and Shijiazhuang while no significant trends are reported in Chengde, Tianjin and Cangzhou−Potou. By comparing results between coastal and inland stations, it is found that the changes in temperature extremes in inland stations are less significant than the changes in coastal stations. The results also suggest that the indices based on minimum temperature show decreasing trends while those for maximum temperature present increasing trends. Furthermore, mutation tests were performed for all indices in order to understand when the changes were initiated. An apparent mutation point (mostly in the 1980s) is detected for most of the analysed temperature indices. This may be caused by the wide implementation of the reform and opening policy in the early 1980s to boost economic development in the BTH region.

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State and Parameter Estimation in Three-Dimensional Subsurface Contaminant Transport Modeling using Kalman Filter Coupled with Monte Carlo Sampling

Abstract: CT. Accurate con f mathematical m ic models do no atially and temp contaminant pred ed with Monte C oise to reflect re de the filter at ev te Carlo sampling ter coupled with M n Absolute Error e Carlo sampling n filter coupled w n Absolute Error ter to the observat Kalman filter, pa

Cited by 14 publications

References 12 publications

A Bayesian-based two-stage inexact optimization method for supporting stream water quality management in the Three Gorges Reservoir region

A Bayesian-based two-stage inexact optimization method for supporting stream water quality management in the Three Gorges Reservoir region

Development of an inexact-variance hydrological modeling system for analyzing interactive effects of multiple uncertain parameters

Observed changes in temperature extremes for the Beijing–Tianjin–Hebei region of China

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