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      Hindcasting water clarity from Landsat satellite images of unmonitored shallow lakes in the Waikato region, New Zealand

      Hicks, Brendan J.; Stichbury, Glen; Brabyn, Lars; Allan, Mathew Grant; Ashraf, Muhammad Salman
      DOI
       10.1007/s10661-013-3098-2
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      Hicks, B. J., Stichbury, G. A., Brabyn, L. K., Allan, M. G., & Ashraf, S. (2013). Hindcasting water clarity from Landsat satellite images of unmonitored shallow lakes in the Waikato region, New Zealand. Environmental Monitoring and Assessment, first published online February 2013.
      Permanent Research Commons link: https://hdl.handle.net/10289/7274
      Abstract
      Cost-effective monitoring is necessary for all investigations of lake ecosystem responses to perturbations and long-term change. Satellite imagery offers the opportunity to extend low-cost monitoring and to examine spatial and temporal variability in water clarity data. We have developed automated procedures using Landsat imagery to estimate total suspended sediments (TSS), turbidity (TURB) in nephlometric turbidity units (NTU) and Secchi disc transparency (SDT) in 34 shallow lakes in the Waikato region, New Zealand, over a 10-year time span. Fifty-three Landsat 7 Enhanced Thematic Mapper Plus images captured between January 2000 and March 2009 were used for the analysis, six of which were captured within 24 h of physical in situ measurements for each of 10 shallow lakes. This gave 32-36 usable data points for the regressions between surface reflectance signatures and in situ measurements, which yielded r (2) values ranging from 0.67 to 0.94 for the three water clarity variables. Using these regressions, a series of Arc Macro Language scripts were developed to automate image preparation and water clarity analysis. Minimum and maximum in situ measurements corresponding to the six images were 2 and 344 mg/L for TSS, 75 and 275 NTU for TURB, and 0.05 and 3.04 m for SDT. Remotely sensed water clarity estimates showed good agreement with temporal patterns and trends in monitored lakes and we have extended water clarity datasets to previously unmonitored lakes. High spatial variability of TSS and water clarity within some lakes was apparent, highlighting the importance of localised inputs and processes affecting lake clarity. Moreover, remote sensing can give a whole lake view of water quality, which is very difficult to achieve by in situ point measurements.
      Date
      2013
      Type
      Journal Article
      Publisher
      Springer
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      • Science and Engineering Papers [3124]
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