Full text: The 3rd ISPRS Workshop on Dynamic and Multi-Dimensional GIS & the 10th Annual Conference of CPGIS on Geoinformatics

1SPRS, Vol.34, Part 2W2, “Dynamic and Multi-Dimensional GIS”, Bangkok, May 23-25, 2001 
applied to the planning of water pollution control in the Lake 
Erhai Basin, China. This project was supported by the United 
Nations Environment Programme (UNEP) (Huang et al., 1996) 
OVERVIEW OF THE STUDY AREA 
The study area, Lake Erhai Basin, which covers an area of about 
2,565 km 2 , is located in the southwest of China (Figure 1). The 
lake is known as a “bright pearl” with unique sightseeing 
resources. It is a freshwater lake with a surface area of 250-257 
km 2 , an average depth of 10.2 m. There are 117 rivers flowing 
into the lake, and only Xier River out of the lake. The lake plays a 
crucial role in local economic development, with its resources 
available for water supply, agricultural irrigation, fishery, tourism, 
and navigation. Economic activities in the basin includes 
agricultural and industrial production, net-cage fish culture, 
forestry, tourism, and lime/brick production. Currently, the major 
environmental problems in the lake basin are: (i) deterioration of 
lake water quality and increased soil erosion due to decline of 
lake water level; (ii) nonpoint source pollution from crop farming, 
livestock husbandry, and fish culture; (iii) water contamination in 
Xier River due to industrial wastewater discharge; and (iv) 
deforestation in the lake basin coupled with increased soil 
erosion, leading to accelerated sedimentation process in the 
lake. 
SYSTEM DESCRIPTION 
Interactive Relationships 
Based on the consideration of many socio-economic, 
environmental concerns and the requirement of system 
modeling, system activities in watershed were divided into 
several components, including agriculture, industry, in-lake net- 
cage fish culture, tourism, forest, stone excavation, in-lake 
navigation, in-lake fishing, lime/brick production, and water 
supply. They are related to each other and have direct or indirect 
impacts on the system’s environmental and economic objectives. 
For example, agricultural production needs water for irrigation, 
and generates nonpoint source pollutants due to 
manure/fertilizer applications. Water pollution results from 
nonpoint source losses of sediment, nitrogen and phosphorus 
from farm lands due to land erosion and washing away of 
unused nutrients from fertilizers and manure; and irrigation water 
allocation is related to farming activities, pipe flows, and 
economic returns. High nitrogen and phosphorus concentrations 
can lead to eutrophication of water. This should be controlled 
under allowable levels corresponding to the objective of lake 
water quality (Haith, 1984). 
Figure 2 shows interactive relationships among various system 
activities and pollution concerns. It is indicated that most of the 
activities are not only related to each other but also responsible 
to a number of pollution problems. Any change in one activity 
may lead to a series of consequences to the others, as well as 
the related environmental problems. The problems are also 
interrelated to each other. For example, point/nonpoint source 
pollution may affect biodiversity, and solid/hazardous waste 
generation may contribute to point/nonpoint source pollution. 
Between the activities and the problems, there exist potential 
abatement measures such as pollution control projects, and 
environmental management initiatives. For decisions related to 
these actions, careful systems analysis would be needed. 
Figure 2 Interactive relationships between human activities and resulting 
pollution problems 
Dynamic Feature 
For the planning horizon, social, economic, legislative, and 
resources conditions will vary with time. Reflection of these 
temporal variations would be important for generating effective 
and realistic planning alternatives. Thus, employment of dynamic 
optimization and systems dynamics methods for the study 
problem is desired. Due to possibility of continuous changes in 
system components along with time, it was suggested this study 
should lead to a "real-time" decision support system. This means 
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