Groundwater-dependent ecosystems at risk - global hotspot analysis and implications

Many land-based ecosystems are dependent on groundwater and could be threatened by human groundwater abstraction. One key challenge for the description of associated impacts is the initial localisation of groundwater-dependent ecosystems (GDEs). This usually requires a mixture of extensive site-specific data collection and the use of geospatial datasets and remote sensing techniques. To date, no study has succeeded in identifying different types of GDEs in parallel worldwide. The main objective of this work is to perform a global screening analysis to identify GDE potentials rather than GDE locations. In addition, potential risks to GDEs from groundwater abstraction shall be identified. We defined nine key indicators that capture GDE potentials and associated risks on a global grid of 0.5 & DEG; spatial resolution. Groundwater-dependent streams, wetlands and vegetation were covered, and a GDE index was formulated incorporating the following three aspects: the extent of groundwater use per GDE type, GDE diversity and GDE presence by land cover. The results show that GDE potentials are widely distributed across the globe, but with different distribution patterns depending on the type of ecosystem. The highest overall potential for GDEs is found in tropical regions, followed by arid and temperate climates. The GDE potentials were validated against regional studies, which showed a trend of increasing matching characteristics towards higher GDE potentials, but also inconsistencies upon closer analysis. Thus, the results can be used as first-order estimates only, which would need to be explored in the context of more site-specific analyses. Identified risks to GDEs from groundwater abstraction are more geographically limited and concentrated in the US and Mexico, the Iberian Peninsula and the Maghreb, as well as Central, South and East Asia. The derived findings on GDEs and associated risks can be useful for prioritising future research and can be integrated into sustainability-related tools such as the water footprint.