Abstract
Assessing the potential of non-point source pollution to assist in the planning of Best Management Practice (BMP) is significant for improving pollution prevention and control in a river basin. In many cases, however, the grid-based modelling analysis is prohibitively laborious and hindered because of insufficient information. This paper presents a new and fast methodology for catchment land-use identification and waste load estimation by properly integrating the skills of remote sensing (RS), geographic information system (GIS), global positioning system (GPS), and the Generalized Watershed Loading Functions (GWLF) model. In this analysis, eight types of land-use patterns in the watershed area of the Kao-Ping River Basin were classified with the aid of SPOT satellite images, Erdas Imagine image processing system, and ArcView GIS system. Hydrologic and geographical features were obtained or derived by the Digital Elevation Model (DEM) and GIS technique simultaneously. The GWLF model was used to estimate the waste loads of non-point sources in terms of the total phosphorus (TP) and total nitrogen (TN). It shows that the variations of TN and TP loadings are closely related to the amount of rainfall over seasons. Final managerial policy can be made with respect to the identified three impact levels of nutrient loadings in the Kao-Ping River Basin, southern Taiwan, which could eventually perform as part of the Total Maximum Daily Load (TMDL) study in this region.
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