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Advances in Meteorology
Volume 2016 (2016), Article ID 1891465, 11 pages
http://dx.doi.org/10.1155/2016/1891465
Research Article

Information Analysis of Catchment Hydrologic Patterns across Temporal Scales

Institute of Hydrology and Water Resources, Tsinghua University, Beijing 100084, China

Received 18 September 2015; Revised 9 December 2015; Accepted 29 December 2015

Academic Editor: Vijay P. Singh

Copyright © 2016 Baoxiang Pan and Zhentao Cong. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Catchment hydrologic cycle takes on different patterns across temporal scales. The interim between event-scale hydrologic process and mean annual water-energy correlation pattern requires further examination to justify self-consistent understanding. In this paper, the temporal scale transition revealed by observation and simulation was evaluated in an information theoretical framework named Aleatory Epistemic Uncertainty Estimation. The Aleatory Uncertainty refers to posterior uncertainty of runoff given the input variables’ observations. The Epistemic Uncertainty refers to the posterior uncertainty increase due to the imperfect observation decoding in models. Daily hydrometeorological observations in 24 catchments were aggregated from 10 days to 1 year before implementing the information analysis. Estimations of information contents and flows of hydrologic terms across temporal scales were related with the catchments’ seasonality type. It also showed that information distilled by the monthly and annual water balance models applied here did not correspond to that provided by observations around temporal scale from two months to half a year. This calls for a better understanding of seasonal hydrologic mechanism.