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Groundwater level thresholds for maintaining groundwater-dependent ecosystems in northwest China: Current developments and future challenges
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Abstract: Groundwater-Dependent Ecosystems (GDEs) in the arid region of northwest China are crucial for maintaining ecological balance and biodiversity. However, the ongoing decline in groundwater levels caused by excessive groundwater exploitation poses a potential threat to GDEs. This paper reviews the current developments and future challenges associated with defining groundwater level thresholds for maintaining GDEs in arid regions. It focuses on methods for identifying and investigating these thresholds, with particular attention to recent advances in northwest China. Additionally, this paper highlights the limitations and future challenges in determining these thresholds, including the complexities of ecological processes, groundwater systems, data availability, and methodological constraints. To address these issues, a multidisciplinary approach that incorporates new technologies, such as multi-source data fusion, machine learning models, and big data and cloud computing, will be essential. By overcoming these challenges and utilizing effective methods, appropriate groundwater level thresholds can be established to ensure the long-term sustainability of GDEs.
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Table 1. Methods for quantifying groundwater level thresholds to protect GDEs
Methods Explanations Pros/Cons Methods Based on Vegetation Indicators Species Diversity Analysis Determine groundwater thresholds by analyzing the changes in species diversity at different groundwater depths (e.g. Species richness, Shannon-Weiner index, and Simpson index) Provide direct information about the response of vegetation to groundwater changes.Indicate the overall health and functioning of the ecosystem.Cannot provide insights into the ecological and hydrological processes affecting vegetation responses to groundwater changes.Limited by data availability due to difficulty in obtaining data. Vegetation Cover Analysis Determine groundwater thresholds by analyzing the changes in vegetation cover at different groundwater depths Vegetation Growth Indicator Analysis Determine groundwater thresholds by analyzing the changes in plant growth indicators at different groundwater depths (e.g. height, biomass) Methods Based on Models Empirical Models Establish models based on historical data and expert experience to predict groundwater thresholds (Basic statistical analysis methods, e.g. linear correlations, stress gradients, ordination) Does not require complex models and a large number of parameters.Can use existing/ historical observation data for analysis.Uncertainties due to large data gaps may exist. Statistical Models Establish models based on statistical analysis methods to analyze the relationship between groundwater and vegetation, and determine groundwater thresholds (e.g. Functional linear model, Bayesian model, Gaussian regression model, forest gradient model) Can intuitively reflect the relationship between groundwater thresholds and the ecological environment.Can deal with missing data.Most models require large sample sizes.Cannot explain the physical mechanism.Limited by the data distribution and model assumptions. Mechanistic Models Establish models based on ecological hydrological processes to simulate the relationship between groundwater and vegetation and determine groundwater thresholds (e.g. MODFLOW) Can provide quantitative relationships between groundwater level and vegetation.Can explain the eco-hydrological processes influencing vegetation responses to groundwater changes.Require calibration with field data.Uncertainty due to simplifications and assumptions. Methods Based on Remote Sensing Remote Sensing Image Analysis Determine groundwater thresholds by analyzing vegetation cover and growth status at different groundwater depths using remote sensing images (e.g. NDVI method, NDVI-DTG method) Allow for large-scale analysis of vegetation.Time-series analysis: Can be used to time-series analysis of changes in vegetation.Limitations in spatial and temporal resolution, which can affect the accuracy of results.Can be affected by atmospheric conditions and topography, requiring careful processing and correction. Remote Sensing Inversion Models Establish models based on remote sensing data and ground-based measured data to invert groundwater depth and determine groundwater thresholds 
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Table 2. The suitable ranges of depth to groundwater and thresholds for maintaining healthy GDEs, NW China
Area GDEs Species and communities Suitable (m) Thresholds (m) Sources Middle and lower Tarim Rive Basin Desert riparian forests Mixed forest-shrub-herb: Populus euphratica, Tamarix spp., Phragmites australis 2–4 8 Li et al. 2013 2–4 6 Hao et al. 2010 Forest-shrub: Populus euphratica, Tamarix spp., Haloxylon ammodendron 4–8 8 Li et al. 2013 4–6 6 Hao et al. 2010 Herb: Phragmites australis 0.5–1 2 Li et al. 2013 Manaz River Valley (Junggar Basin) Desert riparian vegetation Shrub: Ulmus glaucescens Franch; Tamarix spp 1–4 5.5 Cheng et al. 2018 Herb: Phragmites australis 0.5–1.5 2.5 Cheng et al. 2018 Lower Heihe River Basin Desert riparian forests Forest-shrub: Populus euphratica, Tamarix spp. 2–4 4 Ding et al. 2017 Feng et al. 2012 Desert Terrestrial GDEs (Ejina oases) Shrub: Tamarix spp., Nitraria spp., Haloxylon ammodendron, Artemisia arenaria 2–5 5 Jin et al. 2010; Yu and Wang, 2012 Desert wetland(Juyan lake wetland) Salt marsh grassland: Phragmites australis, Agropyron cristatum, Tamarix ramosissima 1.5–2 2 Feng et al. 2012 Middle and lower Shiyanghe Rive Basin Desert riparian vegetation Shrubs: Nitraria spp., Tamarix spp., Reaumuria soongorica, Lycium ruthenicum 8.6–13.5 14 Liu et al. 2012 Desert Terrestrial GDEs (Minqin oases) Shrubs: Nitraria spp., Tamarix spp., Haloxylon ammodendron, Kalidium foliatum, Reaumuria soongorica, Artemisia arenaria 2.5–3.9 4 Cao et al. 2020 Desert wetland (Qingtuhu lake wetland) Herb-shrub ((Halophytic Marsh Grassland): Phragmites australis，Kalidium foliatum 0.5–2.0 2 Hu et al. 2021; Zhang, 2021 3 Liu et al. 2022 Shulehe River Basin Desert Terrestrial GDEs (Oases) Shrub-herb: Alhagi sparsifolia, Nitraria spp, Sophora alopecuroides, Phragmites australis 2–4 6 Ma et al. 2005; Ye et al. 2013 Desert wetland (Xihu lake, Dunhuang) Herb (Halophytic Marsh Grassland: About 0-5 km from lake): Agropyron cristatum, Phragmites australis 1.07–2.03 Chen et al. 2021 Shrub-herb (desert woodland: About 10–50 km from lake): Lycium ruthenicum, Phragmites australis, Populus euphratica, Tamarix ramosissima 2.78–5.42 Chen et al. 2021 Qaidam Basin Desert wetland (Spring and lake wetland) Salt marsh grassland: Phragmites australis, Agropyron cristatum, Kalidium foliatum, Nitraria spp. 0.3–0.9 1.1 Dang et al. 2019 Desert riparian vegetation Herb-shrub: Apocynum venetum, Nitraria spp., Tamarix ramosissim, Tamarix spp., Artemisia arenaria, Phragmites australis, Kalidium foliatum, Achnatherurn 1.4–3.5 5 Dang et al. 2019 Northern Ordos basin Desert wetland (Riparian and lake wetland) Shrub: Salix mongolica, Artemisia sphaero—cephala Krasch, Pulus simonii Carr. 1.5–3 5 Yang et al. 2006
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