Matches in SemOpenAlex for { <https://semopenalex.org/work/W2266976417> ?p ?o ?g. }
- W2266976417 endingPage "1264" @default.
- W2266976417 startingPage "1245" @default.
- W2266976417 abstract "Abstract This study expands the Box‐Hill discrimination function to design an optimal observation network to discriminate conceptual models and, in turn, identify a most favored model. The Box‐Hill discrimination function measures the expected decrease in Shannon entropy (for model identification) before and after the optimal design for one additional observation. This study modifies the discrimination function to account for multiple future observations that are assumed spatiotemporally independent and Gaussian‐distributed. Bayesian model averaging (BMA) is used to incorporate existing observation data and quantify future observation uncertainty arising from conceptual and parametric uncertainties in the discrimination function. In addition, the BMA method is adopted to predict future observation data in a statistical sense. The design goal is to find optimal locations and least data via maximizing the Box‐Hill discrimination function value subject to a posterior model probability threshold. The optimal observation network design is illustrated using a groundwater study in Baton Rouge, Louisiana, to collect additional groundwater heads from USGS wells. The sources of uncertainty creating multiple groundwater models are geological architecture, boundary condition, and fault permeability architecture. Impacts of considering homoscedastic and heteroscedastic future observation data and the sources of uncertainties on potential observation areas are analyzed. Results show that heteroscedasticity should be considered in the design procedure to account for various sources of future observation uncertainty. After the optimal design is obtained and the corresponding data are collected for model updating, total variances of head predictions can be significantly reduced by identifying a model with a superior posterior model probability." @default.
- W2266976417 created "2016-06-24" @default.
- W2266976417 creator A5060767149 @default.
- W2266976417 creator A5065051144 @default.
- W2266976417 date "2016-02-01" @default.
- W2266976417 modified "2023-10-15" @default.
- W2266976417 title "Optimal observation network design for conceptual model discrimination and uncertainty reduction" @default.
- W2266976417 cites W1481449975 @default.
- W2266976417 cites W1481860980 @default.
- W2266976417 cites W1483053213 @default.
- W2266976417 cites W1484878689 @default.
- W2266976417 cites W1488022545 @default.
- W2266976417 cites W1492717630 @default.
- W2266976417 cites W1531958500 @default.
- W2266976417 cites W1542922436 @default.
- W2266976417 cites W1544833062 @default.
- W2266976417 cites W1564996581 @default.
- W2266976417 cites W1592176596 @default.
- W2266976417 cites W1602410243 @default.
- W2266976417 cites W1603903339 @default.
- W2266976417 cites W1604615177 @default.
- W2266976417 cites W1605612495 @default.
- W2266976417 cites W1631618898 @default.
- W2266976417 cites W1637902018 @default.
- W2266976417 cites W1655071942 @default.
- W2266976417 cites W1657063761 @default.
- W2266976417 cites W1679242182 @default.
- W2266976417 cites W1713296299 @default.
- W2266976417 cites W1786226516 @default.
- W2266976417 cites W1822131053 @default.
- W2266976417 cites W1838767266 @default.
- W2266976417 cites W1881486198 @default.
- W2266976417 cites W1883026241 @default.
- W2266976417 cites W190093131 @default.
- W2266976417 cites W1908583432 @default.
- W2266976417 cites W1927341307 @default.
- W2266976417 cites W1932382878 @default.
- W2266976417 cites W1934590902 @default.
- W2266976417 cites W1947404099 @default.
- W2266976417 cites W1964812875 @default.
- W2266976417 cites W1965452118 @default.
- W2266976417 cites W1968703561 @default.
- W2266976417 cites W1973216219 @default.
- W2266976417 cites W1984138429 @default.
- W2266976417 cites W1985998030 @default.
- W2266976417 cites W1988584851 @default.
- W2266976417 cites W1990779154 @default.
- W2266976417 cites W1991921673 @default.
- W2266976417 cites W1994833963 @default.
- W2266976417 cites W1995875735 @default.
- W2266976417 cites W1997832228 @default.
- W2266976417 cites W1998829657 @default.
- W2266976417 cites W2000127926 @default.
- W2266976417 cites W2012603248 @default.
- W2266976417 cites W2012798851 @default.
- W2266976417 cites W2013740555 @default.
- W2266976417 cites W2014110860 @default.
- W2266976417 cites W2014579816 @default.
- W2266976417 cites W2016950925 @default.
- W2266976417 cites W2023699970 @default.
- W2266976417 cites W2024035570 @default.
- W2266976417 cites W2024208185 @default.
- W2266976417 cites W2024421907 @default.
- W2266976417 cites W2027372018 @default.
- W2266976417 cites W2028042973 @default.
- W2266976417 cites W2035035907 @default.
- W2266976417 cites W2035195574 @default.
- W2266976417 cites W2035331500 @default.
- W2266976417 cites W2036056913 @default.
- W2266976417 cites W2039216221 @default.
- W2266976417 cites W2043805260 @default.
- W2266976417 cites W2043976132 @default.
- W2266976417 cites W2045552356 @default.
- W2266976417 cites W2050017402 @default.
- W2266976417 cites W2057832688 @default.
- W2266976417 cites W2080319070 @default.
- W2266976417 cites W2083082288 @default.
- W2266976417 cites W2089707073 @default.
- W2266976417 cites W2089719636 @default.
- W2266976417 cites W2091396986 @default.
- W2266976417 cites W2094873228 @default.
- W2266976417 cites W2097128694 @default.
- W2266976417 cites W2103714425 @default.
- W2266976417 cites W2107211396 @default.
- W2266976417 cites W2112021406 @default.
- W2266976417 cites W2112036188 @default.
- W2266976417 cites W2114078686 @default.
- W2266976417 cites W2118103074 @default.
- W2266976417 cites W2122153187 @default.
- W2266976417 cites W2124156992 @default.
- W2266976417 cites W2124738823 @default.
- W2266976417 cites W2125420983 @default.
- W2266976417 cites W2126984495 @default.
- W2266976417 cites W2135555342 @default.
- W2266976417 cites W2138537392 @default.
- W2266976417 cites W2144960381 @default.
- W2266976417 cites W2146283576 @default.
- W2266976417 cites W2151285503 @default.