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An Introduction to Reservoir Water Quality Data Collection and Analysis
An Introduction to Reservoir Water Quality Data Collection and Analysis
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This publication provides introductory technical guidance for civil engineers, environmental engineers and other professional engineers and scientists interested in the collection and analysis of environmental data for reservoirs. Here is what is discussed: 1. PURPOSE 2. OVERVIEW 3. FIELD DATA COLLECTION PRINCIPLES 4. SAMPLING DESIGNS 5. FIELD SAMPLING AND ANALYSIS 6. LABORATORY ANALYSIS 7. DATABASE MANAGEMENT SYSTEMS 8. SELECTION CRITERIA 9. DATA PRESENTATION METHODS 10. SUMMARY TABLES 11. PRE…
  • Leidėjas:
  • Metai: 2017
  • Puslapiai: 52
  • ISBN-10: 1549598120
  • ISBN-13: 9781549598128
  • Formatas: 21.6 x 28 x 0.3 cm, minkšti viršeliai
  • Kalba: Anglų

An Introduction to Reservoir Water Quality Data Collection and Analysis (el. knyga) (skaityta knyga) | knygos.lt

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This publication provides introductory technical guidance for civil engineers, environmental engineers and other professional engineers and scientists interested in the collection and analysis of environmental data for reservoirs. Here is what is discussed: 1. PURPOSE 2. OVERVIEW 3. FIELD DATA COLLECTION PRINCIPLES 4. SAMPLING DESIGNS 5. FIELD SAMPLING AND ANALYSIS 6. LABORATORY ANALYSIS 7. DATABASE MANAGEMENT SYSTEMS 8. SELECTION CRITERIA 9. DATA PRESENTATION METHODS 10. SUMMARY TABLES 11. PRESENTATIONS 12. QUALITY ASSURANCE 13. STATISTICAL ANALYSIS.

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  • Autorius: J Paul Guyer
  • Leidėjas:
  • Metai: 2017
  • Puslapiai: 52
  • ISBN-10: 1549598120
  • ISBN-13: 9781549598128
  • Formatas: 21.6 x 28 x 0.3 cm, minkšti viršeliai
  • Kalba: Anglų

This publication provides introductory technical guidance for civil engineers, environmental engineers and other professional engineers and scientists interested in the collection and analysis of environmental data for reservoirs. Here is what is discussed: 1. PURPOSE 2. OVERVIEW 3. FIELD DATA COLLECTION PRINCIPLES 4. SAMPLING DESIGNS 5. FIELD SAMPLING AND ANALYSIS 6. LABORATORY ANALYSIS 7. DATABASE MANAGEMENT SYSTEMS 8. SELECTION CRITERIA 9. DATA PRESENTATION METHODS 10. SUMMARY TABLES 11. PRESENTATIONS 12. QUALITY ASSURANCE 13. STATISTICAL ANALYSIS.

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