Journal Article

FZJ-2019-00356

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Towards a computationally efficient free-surface groundwater flow boundary condition for large-scale hydrological modelling

Rahman, M. (Corresponding author) ; Rosolem, R. ; Kollet, S.FZJ* ; Wagener, T.

2019
Elsevier Science Amsterdam [u.a.]

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Please use a persistent id in citations: http://hdl.handle.net/2128/23135  doi:10.1016/j.advwatres.2018.11.015

Abstract: Shallow groundwater is a critical component of the terrestrial water cycle. It sustains baseflow in rivers, supplies root zones with soil moisture during dry periods, and directly influences the land-atmosphere exchange processes. Nonetheless, the integration of groundwater into large-scale hydrological models remains challenging. The most detailed way of representing groundwater dynamics is to incorporate three-dimensional, variably saturated flow processes in the subsurface representation of hydrological models. However, such detailed modelling is still a challenge for global hydrological applications, mainly due to its high computational demand. In this study, a free-surface boundary condition called the Groundwater Flow Boundary (GFB) is developed to represent groundwater dynamics in a more computationally-efficient manner than the full three-dimensional models do. We evaluate GFB using two synthetic test cases, namely an infiltration experiment and a tilted-v catchment, which focus on groundwater recharge and discharge processes, respectively. The simulation results from GFB are compared with a three-dimensional groundwater flow model and with an over-simplified approach using a free-drainage lower boundary condition to assess the impact of our assumptions on model results. We demonstrate that GFB is computationally more efficient compared to the three-dimensional model with limited loss in model performance when simulating infiltration and runoff dynamics.

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Contributing Institute(s):

1. Agrosphäre (IBG-3)

Research Program(s):

1. 255 - Terrestrial Systems: From Observation to Prediction (POF3-255) (POF3-255)

Appears in the scientific report 2019

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Database coverage:
; ; Clarivate Analytics Master Journal List ; Current Contents - Engineering, Computing and Technology ; Ebsco Academic Search ; IF < 5 ; JCR ; Nationallizenz ; SCOPUS ; Science Citation Index ; Science Citation Index Expanded ; Web of Science Core Collection

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