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Estimating nonpoint source pollution: An application of a sequential entropy filter
Author(s) -
Kaplan Jonathan D.,
Howitt Richard E.
Publication year - 2002
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/2000wr000088
Subject(s) - estimator , nonpoint source pollution , entropy (arrow of time) , bayes' theorem , computer science , mathematics , environmental science , econometrics , bayesian probability , statistics , pollution , ecology , biology , physics , quantum mechanics
This paper develops a sequential entropy filter for disaggregating nonpoint sources from ambient data. A numerical simulation based on sediment loading is provided to illustrate the ability of the sequential entropy filter to recover the underlying parameters and optimally disaggregate ambient sediment load among nonpoint sources. In the process we show the equivalence of this sequential entropy filter with Bayes' theorem and, given this equivalence, argue that the sequential entropy filter is more applicable than traditional Bayesian estimators are when the parameter distributions are unknown or when the sample is undersized, which is typically the case when dealing with natural resource data.