Aboveground biomass determines canopy rainfall interception loss in Semiarid Grassland Communities

Yang Luo, Quan Yang, Junjie Zhou, Chunxia Jian, Zhifei Chen, Peifeng Xiong, Jairo A. Palta, Bingcheng Xu

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Canopy rainfall interception is one key hydrological process, affecting rainwater redistribution and effectiveness in semiarid regions. Canopy rainfall interception loss is jointly influenced by meteorology, vegetation and topography. The canopy water storage capacity (S), rainfall interception depth (Im) and ratio (I%) and vegetation characteristics, together with topographic factors of three grassland communities (dominated by Bothriochloa ischaemum, Lespedeza davurica and Artemisia gmelinii, respectively) were investigated on the Loess Plateau of China during the main growing season (June to September). Results showed that Im ranged from 0.55 to 0.89 mm and I% ranged from 6.14% to 12.1%, with the maximum values occurring in August for three communities, and A. gmelinii community had the largest Im (0.89 mm) and I% (12.1%). The Im and I% were positively correlated with aboveground biomass (AGB), coverage (Cov), leaf area index (LAI), community-weighted mean height (CWMH) and altitude (Alt), but negatively correlated with slope degree and rainfall intensity (RI). Hierarchical partitioning analysis (HPA) showed that AGB had the highest contribution for Im (20.3%), while Alt had the highest contribution for I% (18.2%). The regression models based on forward selection could effectively predict the values of Im (R2 = 0.802, RMSE = 0.049) and I% (R2 = 0.546, RMSE = 1.434). Topographic factors (altitude, slope degree and aspect) indirectly influenced both Im and I% by modulating vegetation characteristics (AGB, Cov, etc.). All these indicated that aboveground biomass mainly determines grassland community rainfall interception loss in the semiarid Loess Plateau.

Original languageEnglish
Article numbere2677
Number of pages11
JournalEcohydrology
Volume17
Issue number6
Early online date28 May 2024
DOIs
Publication statusPublished - Sept 2024

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