Information Analysis of Catchment Hydrologic Patterns across Temporal Scales

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.

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