Integration of water quality modeling, remote sensing, and GIS

Water quality modeling has been developed for more than three quarters of a century, but is limited to the study of trends instead of making accurate short-term forecasts. A major barrier to water quality forecasting is the l ack of an efficient system for water quality monitoring. Traditional water quality sampling is time-consuming, expensive, and can only be taken for sm all sizes. Remote sensing provides a new technique to monitor water quality repetitively for a large area. The objective of this research is to use re motely sensed data in a water quality model - QUAL2E in a case study of the Te-Chi Reservoir in Taiwan. The water quality variables developed from the simulations are displayed in map form. The developed forecasting system is designed to predict water quality variables using remote sensing data as a n input to initialize and update water quality conditions.