Publications

Huang, X; Fang, NF; Shi, ZH; Zhu, TX; Wang, L (2019). Decoupling the effects of vegetation dynamics and climate variability on watershed hydrological characteristics on a monthly scale from subtropical China. AGRICULTURE ECOSYSTEMS & ENVIRONMENT, 279, 14-24.

Abstract
Hydrological characteristics are expected to be affected by climate variability and vegetation dynamics which are interconnected and coupled in most cases. Few studies have decoupled the effects of vegetation dynamics and climate variability on hydrological characteristics, a process that benefit both water resources management and agricultural water allocation. In this study, we used partial least squares-structural equation modeling (PLS-SEM) to decouple the effects of climate variability and vegetation on the temporal variations in hydrological characteristics on a monthly scale in the Upper Du watershed (8973 km(2)) in subtropical China. Monthly hydrometeorological and vegetation cover data were collected from 2000 to 2010. Moderate Resolution Imaging Spectroradiometer (MODIS) derived vegetation indices were used to represent the vegetation status of the watershed. The results showed that vegetation dynamics and climate variability account for up to 67% of the temporal variation in runoff, whereas the combined effects of vegetation, climate and runoff explain 62% of the variation in sediment. Climate variability both directly affects monthly hydrological characteristics and indirectly affects these characteristics through its effects on vegetation. Vegetation is negatively correlated with both runoff and sediment, and the net effect of vegetation on the sediment load (total effect = -0.20) is greater than its effect on runoff (total effect = -0.12). Our results indicate that the direct effect of vegetation on sediment (direct effect = -0.09) is smaller than the indirect effect (indirect effect = -0.11) of vegetation on sediment through its influence on runoff; thus, vegetation reduces both the sediment concentration and the sediment load mainly by reducing runoff. Compared to conventional multivariate statistical methodologies, PLS-SEM provides additional valuable information, including the direct and indirect impacts of climatic factors and vegetation on hydrological characteristics.

DOI:
10.1016/j.agee.2019.03.012

ISSN:
0167-8809