Can groundwater storage in turn affect the cryospheric variables? A new perspective from nonlinear dynamic causality detection

Abstract

Despite that the supplying role of cryosphere (glaciers, permafrost, and snow) in groundwater storage (GWS) in Tibetan Plateau (TP) is well-known by comparing their long-term linear trends, the question whether GWS could in turn affect the variation of cryospheric variables remains controversial, since long-term trend analysis fails to distinguish the direction of their interplay. To find evidence of GWS causally affecting cryosphere, this research resorts to the causal inference community and investigates a novel causal interaction between GWS and cryosphere in TP: nonlinear dynamic causality (NDC), based on the Nonlinear Dynamic System (NDS) theory. The specific method applied is called Convergent Cross-mapping (CCM), which detects NDC between two targeted variables X and Y from both directions (X → Y, Y → X). Important findings are summarized as follows: (1) With CCM, NDCs with similar strengths are found from glaciers retreat, snowmelt, and permafrost thaw to GWS, respectively; (2) Also in the form of NDC, GWS is proven to reversely affect permafrost, but not to glacier and snow; (3) NDCs are also found between GWS and other hydrometeorological variables in TP, including lakes, soil moisture, precipitation, and temperature; (4) Some “nontraditional” NDCs from glaciers and lakes towards GWS are identified. Overall, using CCM, our new findings about NDC answer the controversial question of whether GWS could in turn affect cryosphere, completing previous conclusions about how GWS interplays with cryosphere in TP, and more importantly, this research would shed light on future causality detection in hydrology.