Abstract
The occurrence and extent of intense harmful algal blooms (HABs) have increased in inland waters during recent decades. Standard monitor networks, based on infrequent sampling from a few fixed observation stations, are not providing enough information on the extent and intensity of the blooms. Remote sensing has great potential to provide the spatial and temporal coverage needed. Several sensors have been designed to study water properties (AVHRR, SeaBAM, and SeaWIFS), but most lack adequate spatial resolution for monitoring algal blooms in small and medium-sized lakes. Over the last decade, satellite data with 250-m spatial resolution have become available with MODIS. In the present study, three models inspired by published approaches (Kahru, Gitelson, and Floating Algae Index (FAI)) and a new approach named APPEL (APProach by ELimination) were adapted to the specific conditions of southern Quebec and used to estimate chlorophyll-a concentration (Chl-a) using MODIS data. Calibration and validation were provided from in situ Chl-a measured in four lakes over 9 years (2000–2008) and concurrent MODIS imagery. MODIS bands 3 to 7, originally at 500-m spatial resolution, were downscaled to 250 m. The APPEL, FAI, and Kahru models yielded satisfactory results and enabled estimation of Chl-a for heavy blooming conditions (Chl-a > 50 mg∙m−3), with coefficients of determination reaching 0.95, 0.94, and 0.93, respectively. The model inspired from Gitelson did not provide good estimations compared to the others (R2 = 0.77). However, the performance of all models decreased when Chl-a was below 50 mg∙m−3.
Highlights
Sustainable management of water resources became a real interest for the international community a few decades ago
The y-axis corresponds to the spectral index of the downscaled image, and the x-axis to the spectral index of the original image (500-m spatial resolution) re-sampled to 250 m using a method that does not enhance the resolution of the image but divides the surface of each pixel into four
Our aim in this study was to assess the performance of three existing models: Kahru, Floating Algae Index (FAI) and a model inspired from Gitelson, as well as a novel approach named APPEL for the estimation of Chl-a in southern Quebec inland waters as an indicator of water quality
Summary
Sustainable management of water resources became a real interest for the international community a few decades ago. Canada holds 9% of the renewable supply of freshwater for 0.5% of the worldwide population [1], this precious resource needs to be managed responsibly. Evidence that a lot of countries currently suffer from water penury cannot be denied [2]. The origin of the penury is attributed in part to the deterioration of water quality caused by the development of Harmful Algal. The increasing development of such HABs reflects the advanced state of aquatic ecosystem eutrophication caused by urban, agricultural, and industrial developments. Cyanobacterial populations are extremely difficult to control except through the long-term reduction of nutrient inputs from the watershed and from internal sources
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