Please use this identifier to cite or link to this item: https://hdl.handle.net/11681/35053
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dc.contributor.authorJohansen, Richard A.-
dc.contributor.authorReif, Molly K.-
dc.contributor.authorEmery, Erich B.-
dc.contributor.authorNowosad, Jakub.-
dc.contributor.authorBeck, Richard A.-
dc.contributor.authorXu, Min.-
dc.contributor.authorLiu, Hongxing.-
dc.date.accessioned2020-01-06T15:18:36Z-
dc.date.available2020-01-06T15:18:36Z-
dc.date.issued2019-12-
dc.identifier.govdocERDC/EL TR-19-20-
dc.identifier.urihttps://hdl.handle.net/11681/35053-
dc.identifier.urihttp://dx.doi.org/10.21079/11681/35053-
dc.descriptionTechnical Report-
dc.description.abstractSatellite monitoring of cyanobacterial harmful algal blooms in small freshwater lakes and reservoirs remains challenging. This is partly due to the configurations and resolutions of commonly utilized satellite imagers, which are traditionally designed for large terrestrial applications. The purpose of this report is to provide an efficient methodology for the detection and quantification of harmful algal bloom indicators via remote sensing imagery utilizing the newly developed open-source R package waterquality. To accomplish this goal, this report uses Harsha Lake as a case study to demonstrate the use of water quality proxies (chlorophyll-a, phycocyanin, and turbidity) for the evaluation of inland lake and reservoir water quality. This package and associated manuscript were designed to assist researchers and water managers by establishing a flexible and user-friendly workflow to improve water quality monitoring.en_US
dc.description.sponsorshipAquatic Nuisance Species Research Program (U.S.)en_US
dc.description.tableofcontentsAbstract .................................................................................................................................... ii Figures and Tables .................................................................................................................. iv Preface ...................................................................................................................................... v 1 Introduction ...................................................................................................................... 1 1.1 Background ........................................................................................................ 1 1.2 Objective............................................................................................................. 3 1.3 Approach ............................................................................................................ 4 2 Data and Methods ........................................................................................................... 5 2.1 Imagery acquisition ........................................................................................... 5 2.2 Study area and surface measurements .......................................................... 5 2.3 Atmospheric correction and image pre-processing ......................................... 6 3 Image Analysis Using waterquality .............................................................................. 12 3.1 Water quality algorithms ................................................................................ 12 3.2 Water quality index calculation function ........................................................15 3.3 Algorithm evaluation and model validation ................................................... 17 4 Results ............................................................................................................................. 19 4.1 Chlorophyll....................................................................................................... 20 4.2 Blue-green algae/Phycocyanin (BGA/PC) ...................................................... 21 4.3 Turbidity ............................................................................................................ 21 5 Conclusions .................................................................................................................... 24 References ............................................................................................................................. 26 Appendix: Water Quality Algorithms, Workflow, and Computation ................................ 30 Acronyms and Abbreviations ............................................................................................... 45 Report Documentation Page-
dc.format.extent54 pages / 2.074 Mb-
dc.format.mediumPDF-
dc.language.isoen_USen_US
dc.publisherEnvironmental Laboratory (U.S.)en_US
dc.publisherEngineer Research and Development Center (U.S.)-
dc.relation.ispartofseriesTechnical Report (Engineer Research and Development Center (U.S.)) ; no. ERDC/EL TR-19-20-
dc.rightsApproved for Public Release; Distribution is Unlimited-
dc.sourceThis Digital Resource was created in Microsoft Word and Adobe Acrobat-
dc.subjectAlgal blooms--Monitoringen_US
dc.subjectEnvironmental managementen_US
dc.subjectRemote-sensing imagesen_US
dc.subjectReservoirs--Water qualityen_US
dc.subjectWater quality managementen_US
dc.titlewaterquality : an open-source R package for the detection and quantification of cyanobacterial harmful algal blooms and water qualityen_US
dc.typeReporten_US
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