Association of catchment characteristics to Budyko hydrologic model’s uncertainty in humid catchments

Lilin Zhang*, M. Marshall, A. Vrieling, A. Nelson

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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Abstract

Accurate quantification of precipitation partitioning into evapotranspiration and runoff is important for global water balance estimation and water resources managements. The Budyko framework is a simple yet robust solution to parameterize precipitation partitioning and has been widely applied 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 property), 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 study comprehensively investigated the relationship between Budyko scatter and multiple catchment biophysical features from both spatial and temporal perspectives. Results reveal that for humid catchments, topography and seasonal cumulative moisture surplus can explain the spatial distributions of Budyko scatter with r higher than 0.65, whereas soil properties and vegetation indices explained little of the variance (r≤0.30). Temporally, the interannual variability of Budyko scatter was negatively correlated with annual average vegetation indices, particularly for catchments with relatively low vegetation cover. Overall, this study provides valuable insights to the interpretation of Budyko framework and offers possible solutions to improve its performance to predict the spatio-temporal variability of water balances.
Original languageEnglish
Title of host publicationRemote Sensing for Agriculture, Ecosystems, and Hydrology XXV
EditorsChristopher M. Neale, Antonino Maltese
PublisherSPIE
Number of pages12
Volume12727
ISBN (Electronic)9781510666832
DOIs
Publication statusPublished - 17 Oct 2023
EventSPIE Remote Sensing 2023 - Amsterdam, Netherlands
Duration: 3 Sept 20236 Sept 2023
https://spie.org/conferences-and-exhibitions/sensors-and-imaging/programme/conferences/remote-sensing

Conference

ConferenceSPIE Remote Sensing 2023
Country/TerritoryNetherlands
CityAmsterdam
Period3/09/236/09/23
Internet address

Keywords

  • 2023 OA procedure

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