Detecting Climate Driven Changes in Chlorophyll-a in Deep Subalpine Lakes Using Long Term Satellite Data

Abstract

Climate change has increased the temperature and altered the mixing regime of high-value lakes in the subalpine region of Northern Italy. Remote sensing of chlorophyll-a can help provide a time series to allow an assessment of the ecological implications of this. Non-parametric multiplicative regression (NPMR) was used to visualize and understand the changes that have occurred between 2003–2018 in Lakes Garda, Como, Iseo, and Maggiore. In all four deep subalpine lakes, there has been a disruption from a traditional pattern of a significant spring chlorophyll-a peak followed by a clear water phase and summer/autumn peaks. This was replaced after 2010–2012, with lower spring peaks and a tendency for annual maxima to occur in summer. There was a tendency for this switch to be interspersed by a two-year period of low chlorophyll-a. Variables that were significant in NPMR included time, air temperature, total phosphorus, winter temperature, and winter values for the North Atlantic Oscillation. The change from spring to summer chlorophyll-a maxima, relatively sudden in an ecological context, could be interpreted as a regime shift. The cause was probably cascading effects from increased winter temperatures, reduced winter mixing, and altered nutrient dynamics. Future trends will depend on climate change and inter-decadal climate drivers.

Evaluation of Macrophyte Community Dynamics (2015–2020) in Southern Lake Garda (Italy) from Sentinel-2 Data

“…Rrs products were then used as input for the BOMBER bio-optical model (Bio-Optical Model-Based tool for Estimating water quality and bottom properties from Remote sensing images) [58] for estimating the substrate coverage. BOMBER parameterization was based on the in situ inherent optical proprieties (IOP) of the water column and reflectances of bottom substrate collected in Lake Garda and previously used and validated in different work [54,[59][60][61]. The BOMBER code was applied in shallow water mode for each pixel included in the predefined mask of 3.97 km 2 (Figure 1), defining the shallow waters of Sirmione Peninsula reaching a maximum depth of 10 m. This mask was created to avoid areas too close to the coast that might contain mixed pixels (water-land interface).…”

Zonation of Subalpine Lakes Based on Remotely Sensed Water Quality Parameters

“…For this scope, the ESA Sentinel-3 A and B OLCI images have been processed since 2019 to map CHL-a and TSM concentrations, offering a daily revisit time and spatial resolution of 300m (Free et al, 2021). Imagery from Thermal Infrared Sensor TIRS on board NASA Landsat 8 satellite has also been used to monitor LSWT, providing a higher spatial resolution of 30m with 16 days revisit time.…”

“…The processing of images is based on free and opensource algorithms (Luciani et al, 2021), validated for the specific application to inland aquatic environments (Soomets et al, 2020, Free et al, 2021 and applied within the free software SNAP distributed by ESA (Zuhlke et al, 2015). Sentinel-3 imagery is processed through the Case 2 Regional Coast Colour C2RCC (Brockmann et al, 2016) that, based on a neural network, performs radiometric and atmospheric correction, and automatically retrieves CHL-a and TSM concentrations.…”

Shorter blooms expected with longer warm periods under climate change: an example from a shallow meso-eutrophic Mediterranean lake

“…Recent projections have indicated that lakes are predicted to get warmer for longer periods, with heatwaves potentially extending across multiple seasons (Woolway et al, 2021). Climate has been found to alter the seasonal pattern of phytoplankton in several ways, for example, through altering the physical environment with warmer winters reducing the incidence of stratification overturn and thereby altering nutrient cycling (Rogora et al, 2018;Free et al, 2021a). Whereas in high latitude lakes an increase in the length of growing season of phytoplankton has been attributed to an increasing proportion of rain relative to snow resulting in earlier delivery of nutrient loads to lakes (Maeda et al, 2019).…”