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Hydrogeology Journal

, Volume 15, Issue 1, pp 19–28 | Cite as

Remote sensing and GIS based determination of groundwater dependent ecosystems in the Western Cape, South Africa

  • Zahn Münch
  • Julian Conrad
Paper

Abstract

Finding the location of groundwater dependent ecosystems (GDEs) is important in determining the extent of restrictions that need to be placed upon the abstraction of groundwater. Remote sensing was combined with geographical information system (GIS) modelling to produce a GDE probability rating map for the Sandveld region, South Africa. Landsat TM imagery identified the areas indicating the probable presence of GDEs and GIS assisted in their delineation. Three GIS models were generated: a GIS model predicting landscape wetness potential (LWP model) based on terrain morphological features; the LWP model was modified to highlight groundwater generated landscape wetness potential (the resulting GglWP model); and a groundwater elevation model was interpolated, combining groundwater level measurements in boreholes in the region with digital elevation model data. Biomass indicators generated from Landsat were classified and combined with the GIS models, followed by field verification of riverine and wetland GDEs. The LWP model provided the most accurate results of the three models tested for GDEs in this region.

Keywords

Remote sensing Geographical information systems Groundwater dependent ecosystems Groundwater management Sandveld region 

Résumé

Dans le cadre de la délimitation géographique des restrictions sur les prélèvements en eau souterraine, la localisation des écosystèmes dépendant des eaux souterraines (EDES, ou GDE) a son importance. La télédétection a été combinée à une modélisation sous SIG (Système d’Information Géographique) afin de produire une carte de probabilité de présence des EDES sur la région de Sandveld, en Afrique du Sud. Les images Landsat TM ont identifié les secteurs indicateurs de présence de EDES, et les SIG ont contribué à leur délimitation. Trois modèles SIG ont été créés: un premier modèle prédisant le potentiel d’humidité des terrains d’après la morphologie locale (modèle LWP); ce modèle a été modifié dans le but de souligner le potentiel d’humidité généré par les eaux souterraines (modèle résultant GglWP); enfin, un modèle piézométrique a été interpolé par combinaison des levés piézométriques dans les forages du secteur et des données du modèle numérique de terrain. Les indicateurs de biomasse issus des données Landsat ont été classés et combinés aux modèles SIG, puis les EDES de zones humides et de cours d’eau ont été vérifiés sur le terrain. Sur les trois modèles testés pour ce secteur, le modèle LWP a donné les résultats les plus probants.

Resumen

Definir la localización de los ecosistemas dependientes de las aguas subterráneas (GDEs) es importante para determinar la extensión de las restricciones que hay que tomar en la extracción de aguas subterráneas. La teledetección se ha combinado con la modelación utilizando Sistemas de Información Geográfica (GIS), para producir un mapa de valoración de probabilidades para la región Sandveld, en Sudáfrica. Las imágenes Landsat TM identificaron las áreas con presencia de GDEs y el GIS ayudó en su delineación. Se generaron tres modelos GIS: un Modelo GIS para predecir los paisajes húmedos potenciales (LWP model) basado en las características morfológicas del terreno; el modelo LWP fue modificado para destacar los paisajes húmedos potenciales producidos por las aguas subterráneas (dando lugar al modelo GgIWP); y se interpoló un modelo de niveles de aguas subterráneas, combinando medidas de niveles de agua subterránea en sondeos en la región con datos de un modelo digital de niveles. Los indicadores de biomasa generados mediante Landsat fueron clasificados y combinados con los modelos GIS, seguidos por verificaciones de campo en GDEs de rivera y humedales. El model LWP proporciona los resultados más precisos de los tres modelos probados por GDEs en esta región.

Notes

Acknowledgements

The following people and organisations are thanked for contributing to this work: Barry Low and Uschi Pond, COASTEC (Coastal and Environmental Consultants) for botanical field mapping, Department of Water Affairs and Forestry for funding, Roger Parsons, Parsons and Associates Specialist Groundwater Consultants CC for technical input and Water Research Commission for funding.

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Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  1. 1.GEOSS-Geohydrological and Spatial Solutions International (Pty) LtdStellenboschSouth Africa

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