Evaluation of Rainfall Networks Using Entropy - by P F Krstanovic

asim99 · (This post was last modified: 04-07-2013, 11:38 PM by usman.)

Evaluation of Rainfall Networks Using Entropy: I. Theoretical Development

This paper, the first in a series of two, develops an entropy-based approach for evaluating
rainfall networks. Space and time dependencies between raingages are examined by autocovariance
and cross-covariance matrices. Multivariate distributions, associated with different dependencies, are
obtained using the principle of maximum entropy (POME). Formulas for entropy (uncertainty in data
of one raingage), joint entropy (uncertainty in data of two or more raingages) and transinformation
(common information content among two or more raingages) are derived for each distribution, based
on normal data. The decision whether to keep or eliminate a raingage depends entirely on reduction
or gain of information at that raingage. The lines of equal information (isoinformation contours are
defined by considering two raingages (bivariate case) and many raingages (multivariate case).

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asim99 · 04-07-2013, 08:05 PM

Evaluation of Rainfall Networks Using Entropy: II. Application

This paper, the second in the series, applies the entropy approach to space and time evaluation
of rainfall networks in Louisiana. The evaluation is made for five sampling intervals: daily, 2-day,
weekly, monthly, and yearly, and for two separate seasons. In each case, the best combination of raingages
is suggested and the lines of equal information (isoinformation contours) are constructed showing the
areas of greater or less information transfer. The isoinformation lines are especially suitable in decisions
concerning the expansion of the existing network or deleting the unnecessary raingages.

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arshiakh · 04-08-2013, 06:26 PM

Evaluation of rainfall networks using entropy: I. Theoretical development

This paper, the first in a series of two, develops an entropy-based approach for evaluating rainfall networks. Space and time dependencies between raingages are examined by autocovariance and cross-covariance matrices. Multivariate distributions, associated with different dependencies, are obtained using the principle of maximum entropy (POME). Formulas for entropy (uncertainty in data of one raingage), joint entropy (uncertainty in data of two or more raingages) and transinformation (common information content among two or more raingages) are derived for each distribution, based on normal data. The decision whether to keep or eliminate a raingage depends entirely on reduction or gain of information at that raingage. The lines of equal information (isoinformation contours) are defined by considering two raingages (bivariate case) and many raingages (multivariate case).

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arshiakh · 04-08-2013, 06:29 PM

Evaluation of rainfall networks using entropy: II. Application

This paper, the second in the series, applies the entropy approach to space and time evaluation of rainfall networks in Louisiana. The evaluation is made for five sampling intervals: daily, 2-day, weekly, monthly, and yearly, and for two separate seasons. In each case, the best combination of raingages is suggested and the lines of equal information (isoinformation contours) are constructed showing the areas of greater or less information transfer. The isoinformation lines are especially suitable in decisions concerning the expansion of the existing network or deleting the unnecessary raingages.

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