Where does all the water go? Partitioning water transmission losses in a data-sparse, multi-channel and low-gradient dryland river system using modelling and remote sensing

Ben Jarihani; J R Larsen; J N Callow; T R McVicar; K Johansen

doi:10.1016/j.jhydrol.2015.08.030

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Where does all the water go? Partitioning water transmission losses in a data-sparse, multi-channel and low-gradient dryland river system using modelling and remote sensing

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Where does all the water go? Partitioning water transmission losses in a data-sparse, multi-channel and low-gradient dryland river system using modelling and remote sensing

Ben Jarihani, J R Larsen, J N Callow, T R McVicar and K Johansen

Journal of Hydrology, Vol.529(Part 3), pp.1511-1529

2015

DOI: https://doi.org/10.1016/j.jhydrol.2015.08.030

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Abstract

transmission losses

hydrodynamic modelling

remote sensing

water balance

low gradient river systems

Drylands cover approximately one-third of the Earth's surface, are home to nearly 40% of the Earth's population and are characterised by limited water resources and ephemeral river systems with an extremely variable flow regime and high transmission losses. These losses include actual evaporation, infiltration to the soil and groundwater and residual (terminal) water remaining after flood events. These critical components of the water balance of dryland river systems remain largely unknown due to the scarcity of observational data and the difficulty in accurately accounting for the flow distribution in such large multi-channel floodplain systems. While hydrodynamic models can test hypotheses concerning the water balance of infrequent flood events, the scarcity of flow measurement data inhibits model calibration, constrains model accuracy and therefore utility. This paper provides a novel approach to this problem by combining modelling, remotely-sensed data, and limited field measurements, to investigate the partitioning of flood transmissions losses based on seven flood events between February 2006 and April 2012 along a 180. km reach of the Diamantina River in the Lake Eyre Basin, Australia. Transmission losses were found to be high, on average 46% of total inflow within 180. km reach segment or 7. GL/km (range: 4-10. GL/km). However, in 180. km reach, transmission losses vary non-linearly with flood discharge, with smaller flows resulting in higher losses (up to 68%), which diminish in higher flows (down to 24%) and in general there is a minor increase in losses with distance downstream. Partitioning these total losses into the major components shows that actual evaporation was the most significant component (21.6% of total inflow), followed by infiltration (13.2%) and terminal water storage (11.2%). Lateral inflow can be up to 200% of upstream inflow (mean. =. 86%) and is therefore a critical parameter in the water balance and transmission loss calculations. This study shows that it is possible to constrain the water balance using hydrodynamic models in dryland river systems using remote sensing and simple field measurements to address the otherwise scarce availability of data. The results of this study also enable a better understanding of the water resources available for ecosystems in these unique multi-channel and large floodplain rivers. The combined modelling/remote sensing approach of this study can be applied elsewhere in the world to better understand the water balances and water transmission losses, important drivers of ecohydrological processes in dryland environments. © 2015 Elsevier B.V.

Details

Title: Where does all the water go? Partitioning water transmission losses in a data-sparse, multi-channel and low-gradient dryland river system using modelling and remote sensing
Authors: Ben Jarihani (Author) - University of Queensland
J R Larsen (Author) - University of Queensland
J N Callow (Author) - University of Western Australia
T R McVicar (Author) - CSIRO Land and Water
K Johansen (Author) - University of Queensland
Publication details: Journal of Hydrology, Vol.529(Part 3), pp.1511-1529
Publisher: Elsevier BV
Date published: 2015
DOI: 10.1016/j.jhydrol.2015.08.030
ISSN: 0022-1694; 0022-1694
Copyright note: Copyright © 2015. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
Organisation Unit: University of the Sunshine Coast, Queensland; School of Science, Technology and Engineering; Sustainability Research Cluster
Language: English
Record Identifier: 99449162502621
Output Type: Journal article
Research Statement: false