A time-series analysis framework for the flood-wave method to estimate groundwater model parameters

Obergfell, Christophe; Bakker, Mark; Maas, Kees

A time-series analysis framework for the flood-wave method to estimate groundwater model parameters | La méthode de l’onde de crue appliquée dans le cadre d’analyses de séries de niveaux piézométriques dans le but d’estimer des paramètres de modèles d’écoulement d’eau souterraine Un marco de análisis de series de tiempo en el método de la onda de crecida para estimar los parámetros de un modelo de agua subterránea 用洪波法时间序列分析框架估算地下水 Uma abordagem por análise de series temporais para o método da onda de inundação ao estimar parâmetros de modelos de águas subterrâneas

2016

Obergfell, Christophe | Bakker, Mark | Maas, Kees

The flood-wave method is implemented within the framework of time-series analysis to estimate aquifer parameters for use in a groundwater model. The resulting extended flood-wave method is applicable to situations where groundwater fluctuations are affected significantly by time-varying precipitation and evaporation. Response functions for time-series analysis are generated with an analytic groundwater model describing stream–aquifer interaction. Analytical response functions play the same role as the well function in a pumping test, which is to translate observed head variations into groundwater model parameters by means of a parsimonious model equation. An important difference as compared to the traditional flood-wave method and pumping tests is that aquifer parameters are inferred from the combined effects of precipitation, evaporation, and stream stage fluctuations. Naturally occurring fluctuations are separated in contributions from different stresses. The proposed method is illustrated with data collected near a lowland river in the Netherlands. Special emphasis is put on the interpretation of the streambed resistance. The resistance of the streambed is the result of stream-line contraction instead of a semi-pervious streambed, which is concluded through comparison with the head loss calculated with an analytical two-dimensional cross-section model.

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