INTRODUCTION - Integrating GIS, Remote Sensing, and Mathematical Modelling for Surface Water Quality Management - page 8

quality parameters of great concern especially in studying eutrophication of shallow lakes such as total
suspended matter (TSM) and CHL-aorophyll-a (CHL-a).
Geographic Information Systems are becoming more useful in modelling water quality because they
can readily incorporate spatially varying data. There are many instances where GISs have been
incorporated into modelling efforts. Two basic ways that they have been used are: (1) as a method for
deriving input for external models, and (2) as a stand-alone data model. The coupling of GIS to a
water quality model is a marriage designed to address the problem of spatially simulating non-point
sources of pollutants at field, basin, region, and global scales. A GIS provides both the means of
organizing and manipulating spatial data and of creating visual displays of geo-referenced data.
Progress has been made in coupling GIS with water quality models on the basis of either a loose or
close coupling strategy.
In the design and development process of decision support systems for integrated water resources
management and planning, water quality issues are a major component that should be taken into
account. Water quality mathematical models are considered essential components of the computational
framework of such a DSS. Modelling, in the decision making process, provides the answers to
particular questions associated with environmental problems. Several studies have been carried out
both on building a standalone DSS for water quality management and on developing the appropriate
computational frameworks of DSS including water quality modelling tools. These water quality DSSs
depend on structured databases and computational frameworks. The computational frameworks
comprise water quality modeling tools of different properties and approaches, which depend on many
factors such as the particular water quality modeling problems, scale of application, parameters of
concern and management objectives.
Remotely sensed data and information derived from them have a wide range of application in
hydrology and water resources management (Shultz, 1988). Remote sensing and its associated image
processing technology provide access to spatial and temporal information at watershed or at regional
continental and global scales. Effective utilization of this large data volume is dependant upon the
existence of an efficient, geographic handling and processing system that will transform these data
into usable information. A Geographic Information System is a major tool for handling this spatial
data (Mattikalli and Engman, 2000).
Remotely sensed data can be best utilized if they are incorporated in a GIS that is designed to accept
large volumes of spatial data. Applications of GIS and remote sensing have mainly concentrated on
non-point sources (NPS) of pollutants. This is because remotely sensed data products such as land-
use/land cover could be directly utilized in NPS modelling.
Monitoring and assessing water in streams, reservoirs, lakes, estuaries and oceans are critical aspects
for managing and improving the quality of the environment. Classical techniques for measuring
indicators of water quality involve in situ measurements and/or the collection of water samples for
laboratory analysis. Although these technologies give accurate measurements for a point in time and
space, they are time consuming to implement, expensive, and do not give either the spatial or temporal
view of water quality for an individual water body or multiple water bodies across a landscape.
Remote sensing of indicators of water quality and its interpretation using GIS, offers the potential of
relatively inexpensive, frequent, and synoptic measurements using aircraft and/or satellites (Ritchie
and Schieb, 2000). Suspended sediment, CHL-aorophyll (algae), (humus), oil, and temperature are
water quality indicators that can change the spectral and thermal properties of surface water and are
the most readily measured indicators by remote sensing techniques. Substances (i.e. chemicals) that do
not change the optical and thermal conditions of surface waters can only be inferred by modelling
using other surrogate properties (i.e. suspended sediments, CHL-aorophylls), which may have
responded to an input or reduction of chemicals. Application of remote sensing in measuring
suspended sediments, CHL-aorophylls and temperature is widely used.