INTRODUCTION - Integrating GIS, Remote Sensing, and Mathematical Modelling for Surface Water Quality Management - page 2

1.1. BACKGROUND
Many developing countries including the Nile Basin Countries face threats to the security of their
water resources. Fulfilling the increasing needs for water supply, irrigation and hydropower results in
water scarcity, a serious decline in water quality and growing environmental and social concerns. With
the consequences due to floods and droughts aggravated by climate change, the need for sustainable
management of available water resources becomes a key issue for the future development of these
countries.
The surface water quality of lakes, reservoirs, rivers and drainage channels can vary in space and time
according to natural morphological, hydrological, chemical, biological and sedimentation processes.
Pollution of natural bodies of surface water is widespread because of human activities, such as
disposal of sewage and industrial wastes, land clearance, deforestation, use of pesticides, mining, and
hydroelectric developments. However, clean water is essential to human survival as well as to aquatic
life. Much surface water is used for irrigation, with lesser amounts for municipal, industrial, and
recreational purposes: only 6% of all inland water is used for domestic consumption. An estimated
75% of the population of developing nations lacks adequate sanitary facilities, and solid waste is
commonly dumped into the nearest body of flowing water. Pathogens such as bacteria, viruses and
parasites make these waste materials among the world's most dangerous environmental pollutants:
water-borne diseases are estimated to cause about 25,000 deaths daily worldwide (World Bank, 2000
(World Bank 2000)).
Pollution sources affecting surface water bodies and contributing to the increasing deterioration of
water quality in general fall into two categories: point sources and non-point sources (NPS). The point
sources include discrete flows of polluted water that enter a stream through a pipe or channel, for
example, the effluent from a sewage treatment plant. Point sources are often associated with industries
or municipalities. Non-point sources are diffuse contributions that occur over a wide area and are
usually associated with land uses such as agricultural cultivation, livestock grazing and forest
management practices. These sources generally enter streams as overland flow (i.e. urban runoff),
groundwater flow, or flow from small tributaries (McCutcheon, 1990). Abatement efforts to address
non-point sources include the identification and implementation of improved land use practices in
rural areas involving, for example, agricultural, forestry and road construction activities (Brooks et al.,
1997).
In order to manage surface water quality for better protection and remediation, rather than focusing
just on water quality of a lake or stream and point or non-point sources of pollution separately, all
activities in the surrounding area are examined for their possible effects on the water body. In other
words, for better assessment of the problems related to surface water quality, there should be a broad
scope of study based on a watershed or an integrated catchment approach (Haith and Tubbs, 2003).
Following the integrated watershed management approach in terms of water quality, the availability of
data in different forms and for different levels of users, whether the decision makers and planners or
the technical engineers involved in the field, is an issue of great importance. An essential tool, which
can be used by water quality researchers and managers in developing management plans for rivers,
streams and lakes, is the mathematical modelling of water quality. Integrating different computer
technologies and tools, such as GIS and the fast growing technology of remote sensing (as a powerful
source of data acquisition), with water quality models, gives an even more powerful and efficient
management tool, especially when dealing with complicated surface networks in watersheds. Not only
does a GIS enable the user to collect, store, manipulate, analyse, and display spatially referenced data,
it also provides an interactive environment to construct models and makes the models easier to use
(Goodchild, 1996).
Remote sensing techniques have also shown through different studies good potential for monitoring,
mapping and estimating a number of water quality parameters. The reason that these techniques are
not yet used widely and efficiently at their full potential can partly be explained by poor information
facilities and a poor infrastructure for acquisition, processing, archiving and distributing remote
sensing data. It is expected that improvements in these facilities will lead to a considerable increase in