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Remote Sensing of Water Quality

Earth observation satellites capture comprehensive daily views of lake surface water globally. The colour of water recorded in these images allows the monitoring of water clarity, algal blooms and other important water quality attributes. Research under this theme addresses applied management requirements and fundamental processes related to climate change and freshwater ecology.

Chlorophyll a Spatial Distribution In The Rotorua (Te Arawa) Lakes

Understanding the spatial and temporal variability of ecosystems is a prerequisite for developing monitoring regimes to provide information on ecosystem attributes. Monitoring lakes, coastal oceans and rivers on effective spatial and temporal scales is particularly challenging, however, satellite images provide an opportunity to improve environmental monitoring of water quality.

Satellite images were used to analyse the spatial variability of chlorophyll a (Chl) concentrations in the Te Arawa lakes using two years data from the Multispectral Instrument (MSI) on the Sentinel-2 satellites. This analysis included optimisation of the C2RCC algorithm for atmospheric correction and water constituent retrieval using in situ data for the lakes to a prediction accuracy of r2 = 0.92. This is the first MSI-based inland water quality algorithm application for lakes in New Zealand, and represents an improvement in predictive capability compared with previous satellite observations.

Chlorophyll fields from cloud-free images between 2015 and 2019 were analysed and each pixel re-coded according to whether it was close to the median, upper or lower quartile of the lake’s Chl distribution in that image. Counting and contrasting the category assignment for each pixel revealed regions of the lakes which predominantly represent median, high or low Chl concentrations. These maps put existing environmental monitoring sites into the context of lake spatial variability and will help facilitate the improved placement of monitoring sites in order to maximise the representativeness physical environmental samples.

Samples from existing monitoring sites often contain systematic bias due to recurring spatial patters, remote sensing of water quality can assist by providing representative water quality estimates at a range of spatial scales.

Research lead: Moritz Lehmann

Left: Concentration of chlorophyll a in Lake Tarawera derived from a satellite image taken on 7 November 2019. The location of the sampling site of the Bay of Plenty water quality monitoring programme is marked with red concentric circles. Right:Map of Lake Tarawera identifying pixels whose Chl values are within 10% of the median, lower or upper quartile, respectively, in the majority of analysed images. Pixels shown as transparent have approximately equal assignments to median and quartile bins.

Water Colour

Remote sensing by satellite-borne sensors presents a significant opportunity to enhance the spatio-temporal coverage of environmental monitoring programmes for lakes, but the estimation of classic water quality attributes from inland water bodies has not reached operational status due to the difficulty of discerning the spectral signatures of optically active water constituents. Determination of water colour, as perceived by the human eye, does not require knowledge of inherent optical properties and therefore represents a generally applicable remotely-sensed water quality attribute. In this paper, we implemented a recent algorithm for the retrieval of colour parameters (hue angle, dominant wavelength) and derived a new correction for colour purity to account for the spectral bandpass of the Landsat 8 Operational Land Imager (OLI). We used this algorithm to calculate water colour on almost 45,000 observations over four years from 1486 lakes from a diverse range of optical water types in New Zealand. We show that the most prevalent lake colours are yellow-orange and blue, respectively, while green observations are comparatively rare. About 40% of the study lakes show transitions between colours at a range of time scales, including seasonal. A preliminary exploratory analysis suggests that both geo-physical and anthropogenic factors, such as catchment land use, provide environmental control of lake colour and are promising avenues for future analysis.

Research lead: Mortitz Lehmann