Table 3. Merits and Demerits of Selected Water Quality Indices Shweta Tyagi et al. Water Quality Assessment in Terms of Water Quality Index. American Journal.

Slides:



Advertisements
Similar presentations
Benthic Assessments One benthic ecologists concerns and suggestions Fred Nichols USGS, retired.
Advertisements

Framework for the Ecological Assessment of Impacted Sediments at Mining Sites in Region 7 By Jason Gunter (R7 Life Scientist) and.
INTRODUCTION TO MODELING
Exploring uncertainty in cost effectiveness analysis NICE International and HITAP copyright © 2013 Francis Ruiz NICE International (acknowledgements to:
Chapter 1 Introduction to Modeling DECISION MODELING WITH MICROSOFT EXCEL Copyright 2001 Prentice Hall Publishers and Ardith E. Baker.
Lec 12: Rapid Bioassessment Protocols (RBP’s)
Measuring and Monitoring Program Outcomes
Bioassessment and biomonitoring: some general principles.
Developing the Research Question
Tomas Pivoras - EMS experience1 Environmental management systems – experience from Lithuania Tomas Pivoras Kaunas University of Technology.
An increase of population and growth in economic development is causing adverse reactions with the surrounding environment of many areas. This population.
Parameterising Bayesian Networks: A Case Study in Ecological Risk Assessment Carmel A. Pollino Water Studies Centre Monash University Owen Woodberry, Ann.
Biostatistics Frank H. Osborne, Ph. D. Professor.
Lecture ERS 482/682 (Fall 2002) TMDL Assessment ERS 482/682 Small Watershed Hydrology.
Neural Networks (NN) Ahmad Rawashdieh Sa’ad Haddad.
Urban Planning Applications of GIS GIS can be applied to many types of problem. Among these are representatives of both raster and vector data base structures,
The Application of the CCME WQI as a Screening Tool to Evaluate the Suitability of Waters for Aquaculture Aquatic Toxicity Workshop October 24 th – October.
Stratification and Adjustment
ANCOVA Lecture 9 Andrew Ainsworth. What is ANCOVA?
Material Flow Analysis
Day 7 Model Evaluation. Elements of Model evaluation l Goodness of fit l Prediction Error l Bias l Outliers and patterns in residuals.
DSS Modeling Current trends – Multidimensional analysis (modeling) A modeling method that involves data analysis in several dimensions – Influence diagram.
BASIC STATISTICAL METHODS FOR QUALITY ASSURANCE(QA) AND QUALITY CONTROL (QC) SCHEMES IN WATER LABORATORIES Presented by: A. MANOHARAN Scientist Central.
Background and Some General Considerations. The Basic Dilemma in Risk Communication The risks that kill people and the risks that alarm them are completely.
ARROW: system for the evaluation of the status of waters in the Czech Republic Jiří Jarkovský 1) Institute of Biostatistics and Analyses, Masaryk University,
Lecture 07 Dr. MUMTAZ AHMED MTH 161: Introduction To Statistics.
Correlational Research Chapter Fifteen Bring Schraw et al.
Geo597 Geostatistics Ch9 Random Function Models.
The Use of Source Apportionment for Air Quality Management and Health Assessments Philip K. Hopke Clarkson University Center for Air Resources Engineering.
Handbook on Residential Property Price Indices Chapter 5: Methods Jan de Haan UNECE/ILO Meeting, May 2010.
Lecture 5 Model Evaluation. Elements of Model evaluation l Goodness of fit l Prediction Error l Bias l Outliers and patterns in residuals.
International Network Network of Basin OrganizationsInternationalOffice for Water PARIS Paper of Mr. Jean-François DONZIER Paper of Mr. Jean-François DONZIER.
BPS - 5th Ed. Chapter 221 Two Categorical Variables: The Chi-Square Test.
Environment Environnement Canada Rob Kent, Chris Lochner, Janine Murray, Connie Gaudet Water Quality Monitoring and Surveillance Water Science and Technology.
Chapter 13 Repeated-Measures and Two-Factor Analysis of Variance
 Definition  Unweighted and Weighted Index Numbers ( Simple Index Numbers, Laspeyre’s, Paasche’s Index, Fisher’s “Ideal” Index)  CPI ( Consumer Price.
Report Card Scoring Several options under consideration for scoring and aggregating data.
Lesson Overview Lesson Overview What Is Science? Lesson Overview 1.1 What Is Science?
RISK DUE TO AIR POLLUTANTS
Unit 11: Evaluating Epidemiologic Literature. Unit 11 Learning Objectives: 1. Recognize uniform guidelines used in preparing manuscripts for publication.
Additional site characterization questions 2) which determinants make the food system vulnerable (to disruption)? 3) which determinants are most sensitive.
Watersheds and Wetlands CHAPTER 1. Lesson 1.5 Factors That Affect Wetlands and Watersheds Human Activities Watershed Quality Health of U.S. Watersheds.
PROBLEM SOLVING. STEPS IN PROBLEM SOLVING  Problem Definition.  Problem Analysis.  Generating possible Solutions.  Analyzing the Solutions.  Evaluation:
United Nations Statistics Division Overview of handbook on rapid estimates Expert Group Meeting on Short-Term Economic Statistics in Western Asia
B ENCHMARK : SC.912.L By: Kassandra Fallon P. 5.
and Statistics, 2016, Vol. 4, No. 1, 1-8. doi: /ajams-4-1-1
A Hierarchical Model for Object-Oriented Design Quality Assessment
Table 2. Changes in body composition, energy and water intake
Table 1. Advantages and Disadvantages of Traditional DM/ML Methods
Measures of Central Tendency
MODELING THE CURRENT AND FUTURE DISTRIBUTIONS OF
Water Quality Acquisition Systems in Australia
WATER QUALITY Vol 3: Biological Characteristics
Quantifying Indicator Uncertainty
Table 1. General Characteristics of the Study Subjects
© The Author(s) Published by Science and Education Publishing.
Statistical Data Analysis
Table 1. Descriptive statistics
© The Author(s) Published by Science and Education Publishing.
Summing up and next steps
National Sanitation Foundation Water Quality Index (NSFWQI) WQI Value
© The Author(s) Published by Science and Education Publishing.
Rating of Water Quality
Table 2. Showing mean and SD along with t- critical ratio
Table 1. Descriptive Statistics
Table 6. The effect of porosity on pore velocity
Table 4. University Minnesota Model
Category Quantity Secondary school 3 Student participant
© The Author(s) Published by Science and Education Publishing.
© The Author(s) Published by Science and Education Publishing.
Presentation transcript:

Table 3. Merits and Demerits of Selected Water Quality Indices Shweta Tyagi et al. Water Quality Assessment in Terms of Water Quality Index. American Journal of Water Resources, 2013, Vol. 1, No. 3, doi: /ajwr © The Author(s) Published by Science and Education Publishing. National Sanitation Foundation (NSF) WQI MeritsDemeritsReferences 1. Summarizes data in a single index value in an objective, rapid and reproducible manner. 2. Evaluation between areas and identifying changes in water quality. 3. Index value relate to a potential water use. 4. Facilitates communication with lay person. 1. Represents general water quality, it does not represent specific use of the water. 2. Loss of data during data handling. 3. Lack of dealing with uncertainty and subjectivity present in complex environmental issues. [49,50] Canadian Council of Ministers of the Environment (CCME) WQI 1. Represent measurements of a variety of variables in a single number. 2. Flexibility in the selection of input parameters and objectives. 3. Adaptability to different legal requirements and different water uses. 4. Statistical simplification of complex multivariate data. 5. Clear and intelligible diagnostic for managers and the general public. 6. Suitable tool for water quality evaluation in a specific location 7. Easy to calculate 8. Tolerance to missing data 9. Suitable for analysis of data coming from automated sampling. 10. Combine various measurements in a variety of different measurement units in a single metric. 1. Loss of information on single variables. 2. Loss of information about the objectives specific to each location and particular water use. 3. Sensitivity of the results to the formulation of the index. 4. Loss of information on interactions between variables. 5. Lack of portability of the index to different ecosystem types. 6. Easy to manipulate (biased). 7. The same importance is given to all variables. 8. No combination with other indicators or biological data 9. Only partial diagnostic of the water quality. 10. F 1 not working appropriately when too few variables are considered or when too much covariance exists among them. [51,52] Oregon WQI 1. Un-weighted harmonic square mean formula used to combine sub-indices allows the most impacted parameter to impart the greatest influence on the water quality index. 2. Method acknowledges that different water quality parameters will pose differing significance to overall water quality at different times and locations. 3. Formula is sensitive to changing conditions and to significant impacts on water quality. 1. Does not consider changes in toxics concentrations, habitat or biology. 2. To make inferences of water quality conditions outside of the actual ambient network site locations is not possible. 3. Cannot determine the water quality for specific uses nor can it be used to provide definitive information about water quality without considering all appropriate physical, chemical and biological data. 4. Cannot evaluate all health hazards (toxics, bacteria, metals, etc.). [43,53] Weight Arithmetic WQI 1. Incorporate data from multiple water quality parameters into a mathematical equation that rates the health of water body with number. 2. Less number of parameters required in comparison to all water quality parameters for particular use. 3. Useful for communication of overall water quality information to the concerned citizens and policy makers. 4. Reflects the composite influence of different parameters i.e. important for the assessment and management of water quality. 5. Describes the suitability of both surface and groundwater sources for human consumption. 1. WQI may not carry enough information about the real quality situation of the water. 2. Many uses of water quality data cannot be met with an index. 3. The eclipsing or over-emphasizing of a single bad parameter value 4. A single number cannot tell the whole story of water quality; there are many other water quality parameters that are not included in the index. 5. WQI based on some very important parameters can provide a simple indicator of water quality. [6,54]