Abstract
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° 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.
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•GDV is found in low permeable HSU with surficial groundwater circulation.•GDV classes got validated with an ecohydrological index from botanical in situ data.•Differences in in situ ...vitality exist between Quercus species in GDV and non-GDV.
Groundwater dependent ecosystems (GDEs) are biodiversity hotspots and provide important ecosystem services. This study presents a novel multi-instrument concept for the local identification of groundwater dependent vegetation (GDV) in the Mediterranean. The concept integrates high-resolution Sentinel-2 remote sensing data with available geodata and requires in situ vegetation data for validation and calibration. The approach combines five criteria to identify GDV: 1) high vitality, and wetness during dry period, 2) low seasonal changes in vitality and leaf area, 3) low interannual changes in vitality, 4) high topographic potential of water accumulation and low water table depth, 5) high potential inflow dependency. Iso Cluster Unsupervised Classification (ICUC) was applied to identify GDV in the study area (Campania, Italy). Botanical field mapping was utilized for validating the remote sensing approach, as it exhibited significant differences between GDV and Non-GDV in terms of ecohydrological indicator values, leaf anatomy and phreatophyte coverage. According to a new simple ecohydrological rule set that considers phreatophyte cover and mean moisture value of non-phreatophyte species, 9% of vegetation plots are considered GDV and 33% likely GDV. 80% of all GDV derived from classification occur in hydrostratigraphic units (HSU) that are characterized by surficial groundwater circulation and low permeability. The overall accuracy of classifying likelihoods is 62.7%. For 14.6% of the plots, non-GDVs were classified as GDVs (false positives), and only one GDV plot has been classified falsely as non-GDV (false negative). Local results on GDV locations can be overlayed with aquifer use or aquifer reaction to climate change in order to identify GDV under threat and implement sustainable managements of groundwater resources.
Groundwater-dependent vegetation (GDV) is essential for maintaining ecosystem functions and services, providing critical habitat for species, and sustaining human livelihoods. However, climate and ...land-use change are threatening GDV, highlighting the need for harmonised, global mapping of the distribution and extent of GDV. This need is particularly crucial in vulnerable biodiversity hotspots such as the Mediterranean biome. This study presents a novel multicriteria index to identify areas in the Mediterranean biome that provide suitable environmental conditions to support potentially groundwater-dependent vegetation (pGDV) where vegetation behaviour is also indicative of groundwater use. Global datasets targeting 1) groundwater vegetation interaction; 2) soil water holding capacity; 3) topographical landscape wetness potential; 4) land use land cover and 5) hydraulic conductivity of rocks have been combined for the first time in an easy-to-use index. Layer weightings from Analytical Hierarchy Process and Random Forest showed limited applicability on biome scale, but an unweighted overlay of eleven thematic layers produced plausible results. The final pGDV map indicates that 31 % of the natural vegetation in the Mediterranean biome likely depend on groundwater. Moreover, moderate to good agreement was found compared to actual GDV locations in Campania, Italy (91 % with at least moderate potential) and California, USA (87 % with at least moderate potential). The results provide valuable information for identifying regions with a substantial presence of pGDV in the Mediterranean biome and can be used for decision making, e.g. to prioritise field surveys and high-resolution remote sensing for GDV mapping. It can therefore support effective groundwater resource management and the conservation of biodiversity hotspots.
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•Potentially groundwater-dependent vegetation (pGDV) was derived for the Mediterranean biome.•The novel pGDV index integrates globally-available remote sensing and geodata.•Vegetation surveys and regional pGDV maps show moderate to good agreement with the pGDV index.•31 % of the naturally vegetated areas in the Mediterranean likely depend on groundwater.•The pGDV index supports the local identification of actual GDV and biodiversity conservation.
