INTRODUCTION - Integrating GIS, Remote Sensing, and Mathematical Modelling for Surface Water Quality Management - page 9

1.7. PROBLEM STATEMENT
For better surface water quality management of complex irrigated watersheds, there is a need to
identify the different components of a watershed, the categories of land use, and the interaction
between various connected water bodies. Understanding the hydrodynamics of the water bodies and
the different forces affecting them, leads to a better understanding of the water quality problems
associated with these water bodies. This truly reflects the requirement for and the expectations made
of effective tools in water quality management. Using existing tools for the management of surface
water quality in a new and integrated way could be a better approach for finding appropriate solutions
for pollution problems. Water quality models, as one set of these tools, are considered key elements in
understanding water quality problems and are therefore main components in management and decision
support systems. Models describing the dynamics of the aquatic environment are becoming more
sophisticated in that they include better and detailed interpretation of water quality processes. In this
way they can produce a considerable amount of data, which can be difficult to appreciate; the problem
that often arises is how to present these data in their geographical context in the most efficient way.
This introduces a reassessment and integration of information technology tools designed to support the
management process, and raises the role of the integration of the modelling with GIS and remote
sensing.
The advances made in water quality modeling using GIS, Remote Sensing and the importance of
management information systems (MIS) and decision support systems (DSS) in the management
process are increasingly being recognised. The research reported in this thesis makes use of the
integration of GIS capabilities and remote sensing facilities with water quality modeling to develop a
computational framework for a DSS concerning surface water quality management in complex
irrigated watersheds. The research also explores advances in these tools to solve particular water
quality problems. The main scope of the integration is to understand better the water quality of
different types of connected water bodies in irrigated watersheds. This integration provides a better
and clearer assessment of the water quality problems and helps in developing remedial management
actions for future protection of the environment.
1.8. RESEARCH OBJECTIVES
The general objective of this research work is to develop a practically applicable Surface Water
Quality Management Information System WQMIS (including the assessment, modelling and
management components) that is applied at a watershed scale. This system answers both planning and
technical questions of water quality managers, decision makers, and those of technical engineers
working on the sampling, monitoring, analysis and modelling of water quality parameters. This system
is developed as an integrated computational framework and decision support system for surface water
quality management in complex watersheds, and focuses on the flow of information regardless of the
user's level.
The proposed system comprises four main components:
The First component is a comprehensive surface water quality geo-database including different
watershed components, namely the catchment and lake systems. This data base is intended to be the
core of the developed information system. It includes all the categories and types of data that are used
as either inputs to the modelling components or outputs from models used for DSS. This geo-database
is also designed to be accessible by different levels of users based on the level of data needed and the
application. The geo-database incorporates all types of data needed for the development and operation
of water quality models. It includes, hydrographic survey data, GIS layers of the system under
investigation, spatially referenced water quality data, satellite images and processed images, spectral
water quality measurements,...etc.