Multi-temporal assessment of bio-physical parameters in lakes Garda and Trasimeno from MODIS and MERIS

Lake surface temperature (LST) reflects meteorological and climatological forcing more than any other physical lake parameter. LST is also strongly related to the mean temperature of the upper stratum which plays an important role in lake’s biology depending, among other factors, on the dynamics of phytoplankton and thence of chlorophyll-a concentrations (chl-a). Satellite remote sensing is a valuable tool to study these two bio-physical parameters by providing synoptically data at spatial/temporal resolutions not achievable with traditional techniques. In this study MODIS and MERIS data are used to assess LST and chl-a concentration in two important Italian lakes. Images data of Lake Garda in the time range from 2�� 4 to 2�� 9 and Images data of Lake Garda in the time range from 2�� 4 to 2�� 9 and mages data of Lake Garda in the time range from 2�� 4 to 2�� 9 and of Lake Trasimeno from 2�� 5 to 2�� 8 were used. The complexities of processes dealing with lacustrine ecosystems is reflected by the weak of correlation found between chl-a and LST in both lakes by using the entire dataset. However, by considering the time of the year with highest biological activity (i.e. from the end of spring to mid of summer) a positive correlation ( the end of spring to mid of summer) a positive correlation ( ) a positive correlation (r>� .5) was found between the two parameters in Lake Trasimeno. This behaviour was also observed in Lake Garda by considering LST and chl-a data from different areas. In particular the shallower south-east basin of Lake Garda was characterised by higher LST and chl-a concentrations.

[1]  M. Edwards,et al.  Impact of climate change on marine pelagic phenology and trophic mismatch , 2004, Nature.

[2]  Claudia Giardino,et al.  Imaging spectrometry of productive inland waters. Application to the lakes of Mantua , 2009 .

[3]  Dieter Gerten,et al.  Phytoplankton response to climate warming modified by trophic state , 2008 .

[4]  Ph. Quevauviller,et al.  The water framework directive : ecological and chemical status monitoring , 2008 .

[5]  Monika Winder,et al.  The annual cycles of phytoplankton biomass , 2010, Philosophical Transactions of the Royal Society B: Biological Sciences.

[6]  Daniel Odermatt,et al.  Chlorophyll retrieval with MERIS Case-2-Regional in perialpine lakes , 2010 .

[7]  I. Falconer Toxic cyanobacterial bloom problems in Australian waters: risks and impacts on human health , 2001 .

[8]  H. Gons,et al.  MERIS satellite chlorophyll mapping of oligotrophic and eutrophic waters in the Laurentian Great Lakes , 2008 .

[9]  Claudia Giardino,et al.  Application of Remote Sensing in Water Resource Management: The Case Study of Lake Trasimeno, Italy , 2010 .

[10]  Anatoly A. Gitelson,et al.  Remote chlorophyll-a retrieval in turbid, productive estuaries : Chesapeake Bay case study , 2007 .

[11]  M. Simona,et al.  Phytoplankton as an Indicator of the Water Quality of the Deep Lakes South of the Alps , 2006, Hydrobiologia.

[12]  Geoffrey A. Codd,et al.  HARMFUL CYANOBACTERIA From mass mortalities to management measures , 2005 .

[13]  D. Oesch,et al.  Lake surface water temperature retrieval using advanced very high resolution radiometer and Moderate Resolution Imaging Spectroradiometer data: Validation and feasibility study , 2005 .

[14]  M. Scheffer,et al.  Climatic warming causes regime shifts in lake food webs , 2001 .

[15]  I. Joint,et al.  Estimation of phytoplankton production from space: current status and future potential of satellite remote sensing. , 2000, Journal of experimental marine biology and ecology.

[16]  Janet W. Campbell,et al.  Comparison of algorithms for estimating ocean primary production from surface chlorophyll, temperature, and irradiance , 2002 .

[17]  J. Elliott,et al.  Testing the Sensitivity of Phytoplankton Communities to Changes in Water Temperature and Nutrient Load, in a Temperate Lake , 2006, Hydrobiologia.

[18]  Jan Köhler,et al.  Lake responses to reduced nutrient loading - an analysis of contemporary long-term data from 35 case studies , 2005 .

[19]  Martin Kernan,et al.  Freshwater ecosystem responses to climate change: the Euro-limpacs project , 2008 .

[20]  R. Tadonléké,et al.  Evidence of warming effects on phytoplankton productivity rates and their dependence on eutrophication status , 2010 .

[21]  Anu Reinart,et al.  Mapping surface temperature in large lakes with MODIS data , 2008 .

[22]  J. Gower,et al.  Validation of chlorophyll fluorescence derived from MERIS on the west coast of Canada , 2005 .

[23]  G. Chiaudani,et al.  Lake management in Italy: the implications of the Water Framework Directive , 2003 .

[24]  Richard D. Robarts,et al.  Microcystis Aeruginosa and Underwater Light Attenuation in a Hypertrophic Lake (Hartbeespoort Dam, South Africa) , 1984 .

[25]  Nico Salmaso,et al.  Long‐term phytoplankton community changes in a deep subalpine lake: responses to nutrient availability and climatic fluctuations , 2010 .

[26]  C. Stock,et al.  Phenology of phytoplankton blooms in the Nova Scotian Shelf–Gulf of Maine region: remote sensing and modeling analysis , 2010 .

[27]  R. Pingree,et al.  Spring and summer blooms of phytoplankton (SeaWiFS/MODIS) along a ferry line in the Bay of Biscay and western English Channel. , 2009 .

[28]  W. Greve Aquatic Plants and Animals , 2013 .

[29]  R. Wetzel Limnology: Lake and River Ecosystems , 1975 .

[30]  Kevin Winter,et al.  Remote sensing of cyanobacteria-dominant algal blooms and water quality parameters in Zeekoevlei, a small hypertrophic lake, using MERIS , 2010 .

[31]  Erik T. Crosman,et al.  MODIS-derived surface temperature of the Great Salt Lake , 2009 .

[32]  A. Nicklisch,et al.  Analysis and modelling of the interactive effects of temperature and light on phytoplankton growth and relevance for the spring bloom , 2007 .