Replication Data for: Association of catchment characteristics to Budyko hydrologic model’s uncertainty in humid catchments

DOI

Accurate quantification of precipitation partitioning into evapotranspiration and runoff is important for global water balance estimation and water resources management. The Budyko framework is a simple and robust solution to parameterize precipitation partitioning for studying catchment-level water and energy fluxes. However, substantial variations between the observed and Budyko-predicted evaporative indices have been observed. Many studies have attributed the scatter around the Budyko curve to catchment characteristics (e.g., vegetation and soil properties), which are not directly accounted for in the Budyko framework. However, modified Budyko-type equations that consider catchment characteristics are not transferable between regions and the interannual catchment behaviours still fail to follow the adjusted Budyko trajectories. To explore if the pronounced Budyko scatter in humid catchments has a systematic pattern caused by measurable catchment properties, this dataset comprehensively investigated the relationship between Budyko scatter and multiple catchment biophysical features from both spatial and temporal perspectives.

Identifier
DOI https://doi.org/10.17026/PT/XIF2OA
Metadata Access https://phys-techsciences.datastations.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.17026/PT/XIF2OA
Provenance
Creator L. Zhang
Publisher DANS Data Station Physical and Technical Sciences
Contributor Koelen, M Th; Lilin Zhang; Michael Marshall; Anton Vrieling; Andy Nelson
Publication Year 2024
Rights CC BY 4.0; info:eu-repo/semantics/openAccess; http://creativecommons.org/licenses/by/4.0
OpenAccess true
Contact Koelen, M Th (Faculty of Geo-Information Science and Earth Observation)
Representation
Resource Type Dataset
Format text/tab-separated-values; text/plain
Size 60264; 6966; 4985; 4981; 4972; 4983; 3861; 154
Version 1.0
Discipline Earth and Environmental Science; Environmental Research; Geosciences; Natural Sciences