ORIGINAL RESEARCH article
Front. Water
Sec. Water and Artificial Intelligence
Volume 7 - 2025 | doi: 10.3389/frwa.2025.1622980
Quantifying Hydrological Connectivity in Inland Arid Regions Using Transfer Entropy and Multi-Source Data
Provisionally accepted- Xinjiang University of Finance and Economics, Ürümqi, China
Select one of your emails
You have multiple emails registered with Frontiers:
Notify me on publication
Please enter your email address:
If you already have an account, please login
You don't have a Frontiers account ? You can register here
Hydrological modeling in inland arid regions faces persistent challenges due to the strong spatiotemporal variability of water fluxes and limited availability of highquality meteorological data. Existing studies often rely on single-source interpolated inputs and conventional evaluation metrics, which constrain the understanding of internal interactions within hydrological subsystems. To address this gap, we employ a multi-source data framework combined with an information-theoretic approach to assess hydrological process connectivity and causal relationships in the Ebinur Basin of northwestern China. We applied the Variable Infiltration Capacity (VIC) model, enhanced with glacier dynamics, using three station-interpolated datasets and one satellite-based reanalysis product. Transfer entropy was utilized to capture directional dependencies between hydrological variables across seasonal and temporal scales.Results indicate that satellite-based and interpolated datasets produce contrasting spatial and seasonal patterns of water fluxes. Evapotranspiration and runoff dominate in summer and autumn, while snow water equivalent exhibits weak causal coupling.Transfer entropy provided more detailed insights than traditional correlation methods, particularly in identifying information flow between runoff and soil moisture. These findings highlight the importance of integrating information-theoretic diagnostics and multi-source data for improving hydrological understanding and prediction in datascarce, environmentally sensitive arid basins.
Keywords: transfer entropy, Hydrological connectivity, VIC model, Satellite reanalysis, Arid regions, Multi-source data
Received: 05 May 2025; Accepted: 08 Aug 2025.
Copyright: © 2025 Bao. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Qingling Bao, Xinjiang University of Finance and Economics, Ürümqi, China
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.