A copula model integrating atmospheric moisture demand and supply for vegetation vulnerability mapping

Abstract

Drought caused by various meteorological factors negatively affects vegetation. Constructing a joint probability distribution between vegetation and drought information may be appropriate to understand the vulnerability of vegetation to drought. In this study, a copula-based trivariate joint probability model is proposed to investigate the effects of various aspects of meteorological drought on vegetation (vegetation drought). Because drought can be caused by insufficient precipitation or excessive evapotranspiration, the meteorological drought risk for vegetation was divided into two aspects (atmospheric moisture supply and moisture demand). The vulnerability of vegetation drought was mapped when two aspects of meteorological drought occurred separately or simultaneously at high spatial resolution using remote sensing data. The results revealed that the response of vegetation was significantly different depending on the climatic stressors. Although the sensitivity of vegetation to each drought condition varied from region to region, it was found that vegetation was more vulnerable to drought caused by atmospheric moisture demand in most regions of Far East Asia. It has also been shown that drought conditions, which overlapped with insufficient precipitation and excessive evapotranspiration, can drive vegetation to a far more lethal level. Meanwhile, through comparison with the existing VTCI, the proposed Normalized Vegetation Temperature Condition Index (nVTCI) was found to be able to more rationally monitor vegetation drought in the Far East Asian region.

Keywords: Copula; Normalized VTCI; Remote sensing data; Vegetation drought; Vulnerability mapping.