Gosford City Council Historical Water Quality Review & Analysis

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FUTURE DIRECTIONS FOR WATER QUALITY / ENVIRONMENTAL HEALTH MONITORING 4-10 The selection of appropriate methods for analysing the physical, chemical or biological analytes will be dependent on the objectives of the monitoring programme, available budget, laboratory resources, speed on analysis, matrix type and contamination potential. The choice of an appropriate method is based on four primary considerations-: • The range of concentrations of the analytes that need to be detected (detection limits are method specific); • The accuracy and precision required (all results are only estimates, higher accuracy and precision increases the costs); • The period between sampling and analysis (some analysis may be required on-site); and • Familiarity with a particular method when more than one suitable method is available. Laboratory analyses also need to consider a range of issues including-: • Data management ( data storage and reporting); • Quality assurance/control; and • OH&S ( identification of hazards, risk minimisation plans, education). 4.3.6 Data Analysis and interpretation A number of common statistical methods are used for the analysis of water quality data. A methodology for undertaking data analysis is shown in Figure 4.9. Figure 4.9 Framework for Data Analysis (ANZECC/ARMCANZ, 2000) D:\R.N0754.002.01.DOC 7/11/03 16:11
FUTURE DIRECTIONS FOR WATER QUALITY / ENVIRONMENTAL HEALTH MONITORING 4-11 The data initially needs to be summarised from the laboratory into a form that is suitable for analysis, and preliminary checks made for erroneous, missing or below detection data. Suitable approaches for dealing with these types of data will need to be considered. The checked data is then reduced and summarised using a combination of commonly used statistical tools, including graphs, tables, statistical measures (e.g. mean, standard deviation). The objective of the summarised data is to present essential information contained in the data set concisely, and to assist in clearly identifying outliers. Advances in computer software have enabled highly sophisticated graphics to be readily accessible. A number of more advanced statistical methods are then typically used to assess data relationships. Methods including transformations, checking distributional assumptions, trend detection and smoothing can be undertaken. It is then important to subject the data to a process of statistical inference to assist with determining characteristics of the data set, enabling testing of hypothesis and comparison of the data with water quality guideline or trigger values. The relationship between pairs of water quality variables can be evaluated using correlation and regression analysis. Following the data analysis, the results should be summarised concisely, and compared with the monitoring programme objectives to determine if the original questions are answered by the results. 4.3.7 Reporting The reporting of data from the water quality monitoring requires careful consideration of the end user to ensure that the technical nature of the topic is presented to the intended audience in an appropriate format. • Executive summary – summarises technical findings for managers; • Introduction – Outlining study objectives, study location and review of previous/related studies; • Methodology – Outline of study design, sampling and analysis methods; • Results – Summarised results; • Discussion – Data interpretation and implications for management; • Conclusions • Recommendations • References • Appendices – laboratory reports, data tables The report findings can be disseminated in a number of ways depending on the intended audience. Methods for disseminating the data include publications, meetings, internet web pages, film and video presentations, and media reporting. D:\R.N0754.002.01.DOC 7/11/03 16:11
Page 1 and 2: Gosford City Council Historical Wat
Page 3 and 4: CONTENTS I CONTENTS Contents List o
Page 5 and 6: LIST OF FIGURES III 4.4 Outcomes fr
Page 7 and 8: LIST OF TABLES V Table 3.23 Water Q
Page 9 and 10: INTRODUCTION 1-2 locations in Brisb
Page 11 and 12: INTRODUCTION 1-4 aquatic ecosystems
Page 13 and 14: INTRODUCTION 1-6 Default trigger va
Page 15 and 16: GWQ: A DATA MANAGEMENT AND ASSESSME
Page 23 and 24: RESULTS OF WATER QUALITY DATA ANALY
Page 43 and 44: FUTURE DIRECTIONS FOR WATER QUALITY
Page 51: FUTURE DIRECTIONS FOR WATER QUALITY
Page 67 and 68: MHL DATASONDE RESULTS: AVOCA LAGOON
Page 69: MHL DATASONDE RESULTS: KOOLEWONG C-

Gosford City Council Historical Water Quality Review & Analysis

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