Sensitivity of Vegetation Growth to Precipitation in a Typical Afforestation Area in the Loess Plateau: Plant-Water Coupled Modelling

Dandan Wu, Xianhong Xie, Juxiu Tong, Shanshan Meng and Yibing Wang

Ecological Modelling, 2020, vol. 430, issue C

Abstract: Vegetation dynamics are generally restricted by climate and the related soil-water state; however, the responses of vegetation growth to precipitation conditions following afforestation at a watershed scale remain unclear. In this study, we selected a typical small watershed in a semi-humid-arid transition climate zone, the Loess Plateau in China, where several afforestation programs have been implemented. We employed a plant-water coupled model to investigate the sensitivity of vegetation growth to precipitation input and to identify the effect of drought on vegetation growth during juvenile and mature stages. The model presents a favourable performance in simulating the water balance and vegetation dynamics during 2000‒2015. The model and remote sensing retrieved leaf area index (LAI) produce consistent trends regarding vegetation growth. Vegetation growth is not considerably restricted by the current precipitation conditions (semi-humid); however, the growth rate may be quite sensitive to low precipitation input (semi-arid conditions), particularly in the juvenile stage following afforestation. Moreover, vegetation growth is limited by the occurrence of drought in this area. Drought events impose a lag effect on the LAI, and there may be a longer lag effect in the juvenile stage than in the mature sage. The findings from this study provide comprehensive insights into analysing vegetation responses to precipitation, with considerable implications for the implementation of ecological restoration programs in China.

Keywords: Loess Plateau; Vegetation Growth; Drought; Leaf Area Index; SWAT Model; Afforestation (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:430:y:2020:i:c:s0304380020302003

DOI: 10.1016/j.ecolmodel.2020.109128

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