Modeling subsurface hydrology in floodplains
Date
03/2018Keywords
Metadata
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Abstract
Soil-moisture patterns in floodplains are highly dynamic, owing to the complex relationships between soil properties, climatic conditions at the surface, and the position of the water table. Given this complexity, along with climate change scenarios in many regions, there is a need for a model to investigate the implications of different conditions on water availability to riparian vegetation. We present a model, HaughFlow, which is able to predict coupled water movement in the vadose and phreatic zones of hydraulically connected floodplains. Model output was calibrated and evaluated at 6 sites in Australia to identify key patterns in subsurface hydrology. This study identifies the importance of the capillary fringe in vadose zone hydrology due to its water storage capacity and creation of conductive pathways. Following peaks in water table elevation, water can be stored in the capillary fringe for up to months (depending on the soil properties). This water can provide a critical resource for vegetation that is unable to access the water table. When water table peaks coincide with heavy rainfall events, the capillary fringe can support saturation of the entire soil profile. HaughFlow is used to investigate the water availability to riparian vegetation, producing daily output of water content in the soil over decadal time periods within different depth ranges. These outputs can be summarised to support scientific investigations of plant-water relations, as well as in management applications.
Citation
Evans , C M , Dritschel , D G & Singer , M B 2018 , ' Modeling subsurface hydrology in floodplains ' , Water Resources Research , vol. 54 , no. 3 , pp. 1428-1459 . https://doi.org/10.1002/2017WR020827
Publication
Water Resources Research
Status
Peer reviewed
ISSN
1944-7973Type
Journal article
Rights
Copyright © 2018. American Geophysical Union. All Rights Reserved. This work is made available online in accordance with the publisher’s policies. This is the final published version of the work, which was originally published at: https://doi.org/10.1002/2017WR020827
Description
Evans would also like to acknowledge the generous funding provided by the Natural Environment Research Council (NERC) and the University of St Andrews 600 Fund, without which this work would not have been possible. Singer was supported by funding from NSF EAR #700555. The data output files are hosted online by the NERC Environmental Information Data Centre [Evans et al., 2018].Collections
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