Mourot F, Westerhoff RS, Macdonald N, Cameron SG. 2019. Better spatial characterisation of evapotranspiration and rainfall recharge estimates to groundwater using remote sensing multispectral techniques at lysimeter sites. Lower Hutt (NZ): GNS Science. 82 p. (GNS Science report; 2019/17). doi:10.21420/Z3NQ-CE33
Regional councils have the responsibility to set up allocation limits to protect and ensure the sustainable use of their freshwater resources. An important part of allocation limit setting consists in assessing the amount of recharge to groundwater. Improvement of recharge models and assessments of sustainable allocation limits will become more important in the context of climate change, where more variable rainfall inputs are expected in the future.
This study, commissioned by Envirolink for Hawke’s Bay and Bay of Plenty regional councils, aims to use two novel techniques, unmanned aerial vehicle (UAV) and satellite multispectral imagery interpretations, to enable better rainfall recharge estimates to groundwater through better estimates of actual evapotranspiration.
Therefore, UAV and satellite data have been acquired and processed in six surveys, three each at two sites, i.e., in the Hawke’s Bay (Substation site) and the Bay of Plenty (Collins Lane site). The aim of these surveys was to explore the two novel techniques for their ability to improve spatial representation of evapotranspiration and recharge estimates near rainfall recharge lysimeters, i.e., to refine the understanding of how rainfall recharge, measured at lysimeter sites or modelled at a coarse resolution, can be better spatially represented over these aquifer recharge areas.
This study showed that inclusion of spatially detailed evapotranspiration data obtained from the UAV multispectral data can lead to significant improvements in recharge estimates. For this purpose, low resolution (10 m x 10 m) satellite data is used as a ‘spatial interpolator’ for the high resolution (0.1 m x 0.1 m) UAV data in combination with rainfall recharge time series measured at lysimeters and local hydrogeological information.
The study also found that UAV and satellite imagery data could be used to refine soil type mapping, to incorporate human-made features into recharge models, and optimise the location of new lysimeter sites. The use of cloud-computing services in data processing can significantly reduce the computational burden of using such high-resolution data and would be highly recommended for the development of dynamic recharge models.
This study has demonstrated proof of concept for improved parametrisation of rainfall recharge in regional numerical groundwater models (e.g., Heretaunga Plains Groundwater Flow model in Hawke’s Bay and the Kaituna, Makatu and Pongakawa Water Management Area groundwater flow model in Bay of Plenty), which will ultimately benefit management of water resources through improved understanding and reduced uncertainty.