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How can remote sensing contribute in groundwater modeling?

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Abstract

Groundwater resources assessment, modeling and management are hampered considerably by a lack of data, especially in semi-arid and arid environments with a weak observation infrastructure. Usually, only a limited number of point measurements are available, while groundwater models need spatial and temporal distributions of input and calibration data. If such data are not available, models cannot play their proper role in decision support as they are notoriously underdetermined and uncertain. Recent developments in remote sensing have opened new sources for distributed spatial data. As the relevant entities such as water fluxes, heads or transmissivities cannot be observed directly by remote sensing, ways have to be found to link the observable quantities to input data required by the model. An overview of the possibilities for employing remote-sensing observations in groundwater modeling is given, supported by examples in Botswana and China. The main possibilities are: (1) use of remote-sensing data to create some of the spatially distributed input parameter sets for a model, and (2) constraining of models during calibration by spatially distributed data derived from remote sensing. In both, models can be improved conceptually and quantitatively.

Résumé

L’évaluation, la modélisation et la gestion des ressources d’eau souterraine sont considérablement entravées par un manque de données, particulièrement dans les régions semi-arides et arides possédant peu d’infrastructures d’observation. Généralement, seul un nombre limité de points de mesure sont disponibles, alors que les modèles hydrogéologiques demandent des distributions spatiales et temporelles de données d’entrée et de calibration. Si de telles données ne sont pas disponibles, les modèles ne peuvent pas jouer leur rôle d’appui à la décision puisqu’ils sont notoirement de mauvaise résolution et incertains. De récentes avancées en télédétection constituent de nouvelles sources pour les données spatialement distribuées. Comme les entités utiles telles que les flux et les niveaux d’eau ou les transmissivités ne peuvent pas être observées directement par télédétection, il convient de trouver des moyens de relier les quantités observables aux données d’entrée nécessaires aux modèles. A travers des exemples au Botswana et en Chine, un aperçu des possibilités d’utilisation des observations issues de la télédétection en modélisation hydrogéologique est présenté. Les principales possibilités sont: (1) l’utilisation de données de télédétection pour créer une partie des données d’entrée spatialement distribuées d’un modèle, et (2) la contrainte des modèles lors de la calibration avec des données spatialement distribuées dérivées de la télédétection. Dans les deux cas, les modèles peuvent être conceptuellement et quantitativement améliorés.

Resumen

La evaluación, modelizado, y gestión de recursos de agua subterránea, se dificulta considerablemente por la falta de datos, especialmente en ambientes áridos y semi-áridos donde existe una infraestructura débil de vigilancia. En esto ambientes normalmente solo se cuenta con un número limitado de mediciones puntuales mientras que los modelos de agua subterránea necesitan distribuciones temporales y espaciales de datos de entrada y calibración. Si estos datos no están disponibles los modelos no pueden jugar su rol apropiado en el apoyo de decisiones ya que en estas circunstancias son bastante inciertos e indeterminados. Los desarrollos recientes en sensores remotos han abierto nuevas fuentes para datos con distribución espacial. Debido a que las entidades relevantes tal como flujos de agua, presiones o transmisividades no pueden observarse directamente mediante sensores remotos, tienen que encontrarse maneras para vincular las cantidades observables a datos de entrada que requiere el modelo. Se proporciona una revisión de las posibilidades de utilizar observaciones de sensores remotos en los modelos de agua subterránea apoyándose en ejemplos de Bostwana y China. Las dos posibilidades son: (1) uso de datos de sensores remotos para crear algunos de los parámetros de entrada distribuidos espacialmente para un modelo, y (2) restricción de modelos durante la calibración mediante datos distribuidos espacialmente obtenidos de sensores remotos. Para ambas posibilidades los modelos pueden mejorarse conceptual y cuantitativamente.

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Acknowledgements

This work was financially supported by the Swiss National Science Foundation (SNF) under project no. 200021-105384. We are grateful for the valuable comments of the editor and of two anonymous reviewers.

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Authors and Affiliations

  1. Institute of Environmental Engineering, ETH Zurich, Zurich, Switzerland

    P. Brunner, H.-J. Hendricks Franssen, L. Kgotlhang & W. Kinzelbach

  2. Institute of Environment and Resources, Technical University of Denmark, Lyngby, Denmark

    P. Bauer-Gottwein

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  1. P. Brunner
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  2. H.-J. Hendricks Franssen
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Correspondence to W. Kinzelbach.

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Brunner, P., Hendricks Franssen, HJ., Kgotlhang, L. et al. How can remote sensing contribute in groundwater modeling?. Hydrogeol J 15, 5–18 (2007). https://doi.org/10.1007/s10040-006-0127-z

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