Abstract
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).
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
