A transfer entropy signature to capture hydrological similarity: a global-scale validation of a measure based on the interaction between streamflow and forcing time series

Understanding the primary controls of basin dynamics provides the fundamental basis for transferring hydrological information. When focusing on the rainfall-runoff transformation at high temporal resolutions, catchment similarity should reflect the stochastic nature and temporal sequencing of streamflow. This requires an integrated analysis of the entire hydrograph and its forcings, ensuring that the information embedded in the flow propagation and generation processes is fully captured for regionalization purposes.

In a previous study (Neri et al., 2022), we introduced a novel hydrological signature based on the concept of transfer entropy (TE). This signature quantifies the information flow between the complete time series of meteorological forcings and observed streamflow. The approach leverages these information flows to identify dominant hydrological processes and to characterize and classify basins, under the assumption that similar TE values identify similar catchments. In Neri et al. (2022), the proposed technique was applied to a densely gauged set of Austrian catchments, demonstrating the potential of transfer entropy as an additional instrument for assessing hydrological similarity and for quantifying the connection between different governing processes. Specifically, the method proved capable of distinguishing the predominant or partial roles of snowmelt and evapotranspiration in the region, assessing differences in catchment response times, and highlighting the role of high orographic precipitation in snow-dominated catchments.

In this new study, the proposed approach is tested across diverse large-sample datasets within the Caravan framework (Kratzert et al., 2023), at both national and global scales. The objective of the analysis is to determine whether the potential identified in the previous experiment is generalizable—and to what extent—to more extensive study areas. Furthermore, we investigate how the methodology can be adapted to better identify basin dynamics in regions characterized by significantly higher hydro-climatic variability. Specifically, we explore the use of various meteorological forcings and the application of transfer entropy across multiple time scales. The results, in terms of both indicator values and basin dynamics classification, are interpreted in detail against a set of geo-morphological and climatic catchment features, as well as a set of typical and consolidated streamflow signatures.

 

References

Kratzert, F., Nearing, G., Addor, N., Erickson, T., Gauch, M., Gilon, O., Gudmundsson, L., Hassidim, A., Klotz, D., Nevo, S., Shalev, G., & Matias, Y. (2023). Caravan—A global community dataset for large-sample hydrology. Scientific Data, 10(1), 61. https://doi.org/10.1038/s41597-023-01975-w

Neri, M., Coulibaly, P., & Toth, E. (2022). Similarity of catchment dynamics based on the interaction between streamflow and forcing time series: Use of a transfer entropy signature. Journal of Hydrology, 614, 128555. https://doi.org/10.1016/j.jhydrol.2022.128555