Water Quality Modeling : A Guide to Effective Practice

This report serves as a guide to the utility and relevance of water quality prediction modeling. It draws upon examples from recent World Bank water resources and wastewater management projects. The goal of the guide is to provide a broad-based und...

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Bibliographic Details
Main Author: Palmer, Mervin D.
Language:English
en_US
Published: Washington, DC: World Bank 2013
Subjects:
BOD
Online Access:http://documents.worldbank.org/curated/en/2001/05/1121241/water-quality-modeling-guide-effective-practice
http://hdl.handle.net/10986/13914
Description
Summary:This report serves as a guide to the utility and relevance of water quality prediction modeling. It draws upon examples from recent World Bank water resources and wastewater management projects. The goal of the guide is to provide a broad-based understanding of the water quality prediction process and to evaluate the relative merits and cost-effectiveness of using water quality models under field conditions. The guide build on and revises the chapter on water quality modeling prepared for the World Bank's "Pollution Prevention and Abatement Handbook, 1998 (report no. 19128)." The guide comprises five sections. Chapter 1 provides a general overview of the use of water quality models, including the objectives of water quality modeling, the approach to water quality prediction, the costs of modeling processes, and the general components of typical water quality models. Chapter 2 discusses the most common water quality parameters that are modeled, the receiving water processes, quality assurance and control for the water quality data and model predictions, and the required model resources. Chapter 3 describes generic components of water quality models. Some prediction models are then discussed, with detailed summaries of these models presented in an Appendix. Chapter 4 summarizes the present uses of water quality models and recent Bank development projects that used water quality models. Chapter 5 discusses the model data requirements and prediction issues.