气候变化领域集成服务门户

Central-southern Chile is characterized by a series of large lakes that originate in the Andes Mountains. This region is facing increasing anthropogenic impact, which threatens the oligotrophic status of these lakes. While monitoring programs are often based on a limited spatial and temporal coverage, remote sensing offers promising tools for large-scale observations improving our capacity to study comprehensively indicators of lake properties. Seasonal trends (long-term means) and intra-lake variation of surface water temperature (SWF), turbidity and chlorophyll a in Lake Panguipulli were studied through satellite imagery from Landsat 5 TM, 7 ETM+ and 8 OLI (1998-2018: SWT, turbidity), and Sentinel-2A/B MSI (2016-2017; chlorophyll). Remotely sensed data were validated against in situ data from monitoring database. Satellite-derived SWT (representing the surface skin layer of water, socalled skin temperature) showed good similarity with in situ (bulk) temperature (RRMSD 0.17. R-2 = 0.86), although was somewhat lower (RMSD of 2.77 degrees C ; MBD of -2.10 degrees C . Seasonal long-term means of turbidity from satellite imagery corresponded to those from in situ data, while satellite-derived predictions (based on OC2v2 algorithm) overestimated chlorophyll a levels slightly in summer-spring. SWT ranged from 8.0 degrees C in winter to 17.5 degrees C in summer. Mean turbidity (1.6 FNU) and chlorophyll a (1.1 mu g L-1) levels were at their lowest in summer. Spatial and seasonal patterns reflected the bathymetry and previously described mixing patterns of this monomictic lake: warming of shallow bays in spring extended to wider area along with summer stratification period, while mixing of the water column was reflected in spatially more homogenous SWT in fall-winter. Spatial heterogeneity in summer was confirmed by a clear separation of different lake areas based on SWT, turbidity and chlorophyll a using 3-D plot. Mapping of spatial and seasonal variation using satellite imagery allowed identifying lake areas with different characteristics, improving strategies for water resource management. (C) 2019 Elsevier B.V. All rights reserved.