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Research article · 2025 · Full text

International Journal of Geography Geology and Environment

Assessment of groundwater dependent ecosystems and their vulnerability in the Kalahari Basin

Facundo GómezFlorencia Sánchez

Volume 7(12) · Pages 153–155 · DOI: 10.22271/27067483.2025.v7.i12b.665 ↗

Research areasGroundwater and Watershed AnalysisAquatic Ecosystems and BiodiversityWater Quality and Resources Studies

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Abstract

Author-written

8-4Groundwater dependent ecosystems (GDEs) across the Kalahari Basin face mounting pressure from abstraction, yet baseline data on their extent and vulnerability remain scarce. This research mapped and classified GDEs across a 34,000 km² transect in the central Kalahari of Botswana and assessed their sensitivity to projected water table decline. Three GDE categories were identified—riparian woodland, phreatophyte savanna, and seasonal wetland—using Landsat-8 NDVI time series, geological mapping, and piezometric monitoring from 26 boreholes (January 2019 to July 2023). Water table depths ranged from 1.4 m beneath wetlands to 12.8 m under phreatophyte savanna during the dry season. Consistent deepening averaged 0.43 m/year across all types. NDVI analysis showed vegetation vigour declines of 24-34% over five years. A composite vulnerability index classified 41% of mapped GDEs as highly vulnerable. Scenario modelling projected that continued abstraction would push water tables beyond root-zone access for 62% of riparian woodlands within 15 years.

Summary

Source-checked

Plain-language reading of the full paper, prepared with AI and checked against the text. Each point links to the authors' own words.

  1. Why it matters

    • In arid regions, groundwater dependent ecosystems (GDEs) are critical for sustaining biodiversity, providing grazing, and regulating the microclimate when surface water is unavailable. View evidence ↗

      Why it matters

      In arid regions, groundwater dependent ecosystems (GDEs) are critical for sustaining biodiversity, providing grazing, and regulating the microclimate when surface water is unavailable.

      In the paper's own words

      “in water-scarce environments, vegetation communities are tightly coupled to water table position [1]. These groundwater dependent ecosystems sustain biodiversity, provide grazing, and regulate microclimate where surface water is absent most of the year [2].”

      Page 1

      Found in: Introduction

      Read it in the full textOpen PDF at page 1 ↗
    • Water abstraction for mining, cattle ranching, and municipal use has increased since the 1990s, while policies have generally overlooked the water requirements of terrestrial ecosystems. View evidence ↗

      Why it matters

      Water abstraction for mining, cattle ranching, and municipal use has increased since the 1990s, while policies have generally overlooked the water requirements of terrestrial ecosystems.

      In the paper's own words

      “Since the 1990s, abstraction has risen sharply, driven by mining, cattle ranches, and growing municipal demand [4]. But environmental allocation policies have largely ignored terrestrial ecosystem water needs.”

      Page 1

      Found in: Introduction

      Read it in the full textOpen PDF at page 1 ↗
    • Comprehensive mapping of GDEs in southern Africa has been scarce, with previous efforts limited to localized areas like the Okavango Delta fringe. View evidence ↗

      Why it matters

      Comprehensive mapping of GDEs in southern Africa has been scarce, with previous efforts limited to localized areas like the Okavango Delta fringe.

      In the paper's own words

      “In southern Africa, however, GDE mapping has been limited to localised assessments around the Okavango Delta fringe [7].”

      Page 1

      Found in: Introduction

      Read it in the full textOpen PDF at page 1 ↗
  2. The question

    • The study aimed to map GDEs across a 34,000 km² area in central Botswana, measure water table trends, and evaluate their vulnerability to future water level declines. View evidence ↗

      The question

      The study aimed to map GDEs across a 34,000 km² area in central Botswana, measure water table trends, and evaluate their vulnerability to future water level declines.

      In the paper's own words

      “This research set out to map GDEs across a 34,000 km² transect in central Botswana, quantify water table trends, and assess vulnerability to projected future drawdown [9].”

      Page 1

      Found in: Introduction

      Read it in the full textOpen PDF at page 1 ↗
  3. What they did

    • The researchers monitored 26 boreholes monthly from January 2019 to July 2023 across a 34,000 km² transect in central Botswana. View evidence ↗

      What they did

      The researchers monitored 26 boreholes monthly from January 2019 to July 2023 across a 34,000 km² transect in central Botswana.

      In the paper's own words

      “The transect covered roughly 34,000 km² in central Botswana. Piezometric data from 26 monitoring boreholes were recorded monthly from January 2019 to July 2023.”

      Page 2

      Found in: Material and Methods Material

      Read it in the full textOpen PDF at page 2 ↗
    • GDEs were mapped by calculating annual NDVI from Landsat-8 imagery, identifying pixels with dry-season NDVI above 0.25 over five years, and verifying these with geological maps and borehole data. View evidence ↗

      What they did

      GDEs were mapped by calculating annual NDVI from Landsat-8 imagery, identifying pixels with dry-season NDVI above 0.25 over five years, and verifying these with geological maps and borehole data.

      In the paper's own words

      “GDE mapping followed three steps: NDVI computation from Landsat-8 bands averaged into annual composites; flagging pixels with dry-season NDVI above 0.25 across all five years as probable GDE candidates; and cross-referencing with borehole data and geological maps.”

      Page 2

      Found in: Material and Methods Material

      Read it in the full textOpen PDF at page 2 ↗
    • The study classified GDEs into three distinct categories: riparian woodland, phreatophyte savanna, and seasonal wetland. View evidence ↗

      What they did

      The study classified GDEs into three distinct categories: riparian woodland, phreatophyte savanna, and seasonal wetland.

      In the paper's own words

      “Three GDE categories were identified—riparian woodland, phreatophyte savanna, and seasonal wetland”

      Page 1

      Found in: Material and Methods Material

      Read it in the full textOpen PDF at page 1 ↗
    • Vulnerability was measured using a GDE Vulnerability Index (GVI) that combined water table decline rates, the ratio of water table depth to root reach, and rainfall dependence. View evidence ↗

      What they did

      Vulnerability was measured using a GDE Vulnerability Index (GVI) that combined water table decline rates, the ratio of water table depth to root reach, and rainfall dependence.

      In the paper's own words

      “Vulnerability was quantified using a composite GDE Vulnerability Index (GVI) combining three sub-indices: water table decline rate normalised against rooting depth (WTR), the ratio of dry-season water table depth to estimated maximum root reach (RDR), and a rainfall dependence factor (RDF).”

      Page 1

      Found in: Model Description and Parameterisation

      Read it in the full textOpen PDF at page 1 ↗
  4. What they found

    • The study mapped 6,780 km² of GDEs, which represents approximately 20% of the total research area. View evidence ↗

      What they found

      The study mapped 6,780 km² of GDEs, which represents approximately 20% of the total research area.

      In the paper's own words

      “A total of 6,780 km² of GDEs were mapped (roughly 20% of the research area).”

      Page 2

      Found in: Material and Methods Material

      Read it in the full textOpen PDF at page 2 ↗
    • Seasonal wetlands were the most vulnerable ecosystem type, with a GVI of 0.72 and the most significant vegetation vigour decline (33.9% NDVI loss). View evidence ↗

      What they found

      Seasonal wetlands were the most vulnerable ecosystem type, with a GVI of 0.72 and the most significant vegetation vigour decline (33.9% NDVI loss).

      In the paper's own words

      “Seasonal wetlands showed the highest vulnerability (GVI = 0.72) and steepest NDVI decline (33.9%) [14].”

      Page 2

      Found in: Material and Methods Material

      Read it in the full textOpen PDF at page 2 ↗
    • Using the composite vulnerability index, 41% of the mapped GDEs were categorized as highly vulnerable. View evidence ↗

      What they found

      Using the composite vulnerability index, 41% of the mapped GDEs were categorized as highly vulnerable.

      In the paper's own words

      “A composite vulnerability index classified 41% of mapped GDEs as highly vulnerable.”

      Page 1

      Found in: Material and Methods Material

      Read it in the full textOpen PDF at page 1 ↗
    • Under the most conservative abstraction scenario (Scenario A), 38.4% of riparian woodlands and 67.2% of wetlands are projected to lose groundwater access by 2038. View evidence ↗

      What they found

      Under the most conservative abstraction scenario (Scenario A), 38.4% of riparian woodlands and 67.2% of wetlands are projected to lose groundwater access by 2038.

      In the paper's own words

      “Under Scenario A, 38.4% of riparian woodland and 67.2% of wetland area would exceed root-zone thresholds by 2038.”

      Page 2

      Found in: Material and Methods Material

      Read it in the full textOpen PDF at page 2 ↗
    • Under the most aggressive abstraction scenario (Scenario C), the projected loss of groundwater access increases to 84.7% for riparian woodlands and 97.1% for wetlands. View evidence ↗

      What they found

      Under the most aggressive abstraction scenario (Scenario C), the projected loss of groundwater access increases to 84.7% for riparian woodlands and 97.1% for wetlands.

      In the paper's own words

      “Under Scenario C, these rose to 84.7% and 97.1% [15].”

      Page 2

      Found in: Material and Methods Material

      Read it in the full textOpen PDF at page 2 ↗
  5. What it means

    • The authors recommend integrating GDE water requirements into allocation frameworks by using sentinel boreholes to set monitoring triggers and adaptive limits on water abstraction. View evidence ↗

      What it means

      The authors recommend integrating GDE water requirements into allocation frameworks by using sentinel boreholes to set monitoring triggers and adaptive limits on water abstraction.

      In the paper's own words

      “Integrating GDE needs into allocation frameworks would require monitoring trigger levels at sentinel boreholes coupled with adaptive abstraction limits.”

      Page 2

      Found in: Discussion

      Read it in the full textOpen PDF at page 2 ↗
    • The authors state that future research needs to improve the accuracy of root-depth measurements and include climate projections in the vulnerability model. View evidence ↗

      What it means

      The authors state that future research needs to improve the accuracy of root-depth measurements and include climate projections in the vulnerability model.

      In the paper's own words

      “Future work should refine root-depth measurements and incorporate climate projections into the vulnerability framework [21].”

      Page 3

      Found in: Conclusion

      Read it in the full textOpen PDF at page 3 ↗

Visual summary

2 visuals

Illustrations explain the paper; charts are replotted from the paper's own table values.

AI-generated illustration
AI-generated conceptual illustration (Kalahari Basin groundwater dependent vegetation). It explains the idea and does not show study data.↗ Enlarge
GVI Model Components
AI-generated conceptual illustration (Kalahari Basin groundwater dependent vegetation). It explains the idea and does not show study data.

AI-generated conceptual illustration (Kalahari Basin groundwater dependent vegetation). It explains the idea and does not show study data.

Open full-size image ↗

GVI Model Components

AI-generated conceptual illustration (Kalahari Basin groundwater dependent vegetation). It explains the idea and does not show study data.

View source evidence ↗
Replotted from source data
Replotted from Table 2 (page 2) of the original paper. Every bar is the paper's own table value.↗ Enlarge
Scenario A (%) and Scenario B (%) and more: Riparian vs Phreatophyte vs Wetland
Replotted from Table 2 (page 2) of the original paper. Every bar is the paper's own table value.

Replotted from Table 2 (page 2) of the original paper. Every bar is the paper's own table value.

Open full-size image ↗

Scenario A (%) and Scenario B (%) and more: Riparian vs Phreatophyte vs Wetland

Replotted from Table 2 (page 2) of the original paper. Every bar is the paper's own table value.

View source evidence ↗

Figures & tables

From the original paper
Projected GDE area exceeding root-zone access thresholdTable 2Page 2GDE characteristics and water table trends across threeTable 1Page 2Water table depth trends for three GDE types in the centralFigure 1Page 2Mean annual NDVI trends for three GDE types (2019-2023)Figure 2Page 2
FULL TEXT Original article · reflowed for reading

Introduction

Long before hydrologists began drilling monitoring boreholes in the Kalahari, the San people navigated this landscape by reading the distribution of trees that betrayed shallow groundwater beneath the sand. That indigenous knowledge rested on an ecological reality modern science has been slow to formalise: in water-scarce environments, vegetation communities are tightly coupled to water table position [1] . These groundwater dependent ecosystems sustain biodiversity, provide grazing, and regulate microclimate where surface water is absent most of the year [2] . The Kalahari Basin extends across roughly 2.5 million km² of southern Africa. Beneath the sand, the Stampriet artesian aquifer supports scattered but ecologically significant vegetation [3] . Since the 1990s, abstraction has risen sharply, driven by mining, cattle ranches, and growing municipal demand [4] . But environmental allocation policies have largely ignored terrestrial ecosystem water needs. Eamus et al. [5] proposed a GDE classification system, and Murray et al. [6] mapped GDEs across Australia using remote sensing and hydrogeological inference. In southern Africa, however, GDE mapping has been limited to localised assessments around the Okavango Delta fringe [7] . Hatton and Evans [8] demonstrated that phreatophytic vegetation responds non-linearly to water table drawdown, with sharp die-back thresholds. This research set out to map GDEs across a 34,000 km² transect in central Botswana, quantify water table trends, and assess vulnerability to projected future drawdown [9] .

Model Description and Parameterisation

Vulnerability was quantified using a composite GDE Vulnerability Index (GVI) combining three sub-indices: water table decline rate normalised against rooting depth (WTR), the ratio of dry-season water table depth to estimated maximum root reach (RDR), and a rainfall dependence factor (RDF). Each was scaled from 0 to 1 and weighted equally. The model was parameterised using measured piezometric data, published root-depth profiles for Kalahari woody species [10] , and rainfall-NDVI lag correlations. GVI thresholds: <0.33 (low), 0.33-0.66 (moderate), >0.66 (high vulnerability).

Scenario Development

Three abstraction scenarios were defined for the 15-year projection period (2024-2038). Scenario A assumed continuation of 2023 rates. Scenario B assumed 3.2% annual increase consistent with national projections. Scenario C assumed 6.1% annual increase reflecting accelerated mining and urbanisation. Water table trajectories were estimated by extrapolating measured decline rates adjusted for projected volumes using Stampriet aquifer transmissivity values [11] .

Material and Methods Material

The research was coordinated from the National Geological Institute of Bariloche, Río Negro, Argentina. The transect covered roughly 34,000 km² in central Botswana. Piezometric data from 26 monitoring boreholes were recorded monthly from January 2019 to July 2023. Landsat-8 OLI imagery (paths 173-174, rows 76-77) yielded 108 cloud-free composites after atmospheric correction [12] . Methods GDE mapping followed three steps: NDVI computation from Landsat-8 bands averaged into annual composites; flagging pixels with dry-season NDVI above 0.25 across all five years as probable GDE candidates; and crossreferencing with borehole data and geological maps. Each confirmed GDE was classified as riparian woodland, phreatophyte savanna, or seasonal wetland based on NDVI amplitude, drainage proximity, and field verification at 38 ground-truth points [13] . Vulnerability was computed using the GVI model. A total of 6,780 km² of GDEs were mapped (roughly 20% of the research area). Seasonal wetlands showed the highest vulnerability (GVI = 0.72) and steepest NDVI decline (33.9%) [14] . Under Scenario C, these rose to 84.7% and 97.1% [15] . Seasonal wetlands showed the steepest NDVI decline (0.62 to 0.41, 34% reduction). This vegetation stress preceded visible canopy loss, suggesting NDVI monitoring can serve as an early warning indicator [16] .

Results

Results

Discussion

These results provide the first spatially explicit evidence that Kalahari GDEs are undergoing measurable degradation linked to declining water tables. The average drawdown of 0.43 m/year exceeds the natural recharge rate (0.5-3.0 mm/year) [17] , confirming unsustainable abstraction patterns. The high wetland vulnerability (GVI = 0.72) and rapid 34% NDVI decline suggest limited buffering capacity against even moderate drawdown, contrasting with deeper-rooted phreatophyte species like Boscia albitrunca that tolerate several metres of lowering [18] . Even the most conservative scenario projects loss of groundwater access for a third of riparian woodlands and two-thirds of wetlands within 15 years. These projections carry uncertainties around future rainfall but the direction is consistent across all scenarios [19] . Botswana's current Water Act doesn't explicitly recognise ecological water requirements for terrestrial GDEs [20] . Integrating GDE needs into allocation frameworks would require monitoring trigger levels at sentinel boreholes coupled with adaptive abstraction limits.

Conclusion

This research mapped 6,780 km² of GDEs across the central Kalahari and documented declining water tables and vegetation vigour across all categories. Seasonal wetlands were most vulnerable (GVI = 0.72, 34% NDVI decline). Scenario modelling indicated 62-97% of GDE area could lose groundwater access within 15 years. These findings underscore the need for explicit ecological water requirements in Kalahari groundwater policy. NDVI-based early warning systems at sentinel sites could provide costeffective management triggers. Future work should refine root-depth measurements and incorporate climate projections into the vulnerability framework [21] .

Acknowledgement

Acknowledgements Funding SourcesThis research was supported by internal institutional research funding. Institutional SupportThe authors thank the National Geological Institute of Bariloche for analytical and computational support. Contributions Not Qualifying for AuthorshipStaff from the Botswana Department of Water Affairs assisted with borehole access and data provision.

Figures and tables from the paper

Table 2. Projected GDE area exceeding root-zone access threshold
GDE TypeScenario A (%)Scenario B (%)Scenario C (%)
Riparian38.462.184.7
Phreatophyte21.641.367.8
Wetland67.286.497.1

Table text extracted from the original PDF; superscript letters are shown inline. The original table image is below.

View original table image
Projected GDE area exceeding root-zone access threshold↗ Enlarge
Table 2
Projected GDE area exceeding root-zone access threshold

Projected GDE area exceeding root-zone access threshold

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Original paper tableSource PDF · page 2 ↗
Table 1. GDE characteristics and water table trends across three
GDE characteristics and water table trends across three↗ Enlarge
Table 1
GDE characteristics and water table trends across three

GDE characteristics and water table trends across three

Open full-size image ↗
Original paper figureSource PDF · page 2 ↗
Figure 1. Water table depth trends for three GDE types in the central
Water table depth trends for three GDE types in the central↗ Enlarge
Figure 1
Water table depth trends for three GDE types in the central

Water table depth trends for three GDE types in the central

Open full-size image ↗
Original paper figureSource PDF · page 2 ↗
Figure 2. Mean annual NDVI trends for three GDE types (2019-2023)
Mean annual NDVI trends for three GDE types (2019-2023)↗ Enlarge
Figure 2
Mean annual NDVI trends for three GDE types (2019-2023)

Mean annual NDVI trends for three GDE types (2019-2023)

Open full-size image ↗
Original paper figureSource PDF · page 2 ↗

References

18 in the original paper
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