Modelling interannual variations in catchment evapotranspiration considering vegetation and climate seasonality using the Budyko framework

Abstract

AbstractThe Budyko framework is an efficient tool for investigating catchment water balance, focusing on the effects of seasonal changes in climate (S) and vegetation cover (M) on catchment evapotranspiration (ET). However, the effects of vegetation seasonality on ET remain largely unknown. The present study explored these effects by modelling interannual variations in ET considering vegetation and climate seasonality using the Budyko framework. Reconstructed 15‐day GIMMS NDVI3g timeseries data from 1982 to 2015 were used to estimate M and extract the relative duration of the vegetation growing season (GL) in the Yellow River Basin (YRB). To characterize S, seasonal variations in precipitation and potential ET were extracted using a Gaussian algorithm. Analysis of the observed datasets for 19 catchments revealed that interannual variation in the catchment parameter ϖ (in Fuh's equation) was significantly and positively correlated with M and GL. Conversely, ϖ was significantly but negatively correlated with S. Furthermore, stepwise linear regression was used to calibrate the empirical formula of ϖ for these three dimensionless parameters. Following validation, based on observations in the remaining 11 catchments, ϖ was integrated into Fuh's equation to accurately estimate annual ET. Over 79% subcatchments showed an upward trend (0.9 mm yr−1), whereas fewer than 21% subcatchments showed a downward trend (−0.5 mm yr−1) across YRB. In the central region of the middle reach, ET increased with increased M, prolonged GL, and decreased S, whereas in the source region of YRB, ET decreased with decreased M and shortened GL. Our study provides an alternative method to estimate interannual ET in ungauged catchments and offers a novel perspective to investigate hydrological responses to vegetation and climate seasonality in the long‐term.