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.
One of the recent concerns of reservoir eutrophication issues focuses on a fast assessment of the non-point sources pollution impact. It frequently requires an initial evaluation of the land use pattern and the reservoir assimilative capacity. This information is useful for estimating the non-point source loads, assessing the proper uses of natural resources in the watershed, and generating the essential control strategies when required. To achieve this goal, the state-of-the-art 3S information technologies, which properly integrates the skills of geographic information system (GIS), global positioning system (GPS) and remote sensing (RS), is viewed as an integrated means for reservoir land use assessment and watershed management. Substantial efforts in this study are placed upon identifying seven types of land use patterns in the watershed of the Tseng-Wen Reservoir in Southern Taiwan, which would directly assist in the required estimation of non-point sources pollution impact. With the aid of SPOT satellite images, Erdas Imagine ® image processing system, and ArcView ® GIS, the numerical model based on the export coefficient method yields an estimation of non-point source loads on a yearly basis with respect to four target constituents. These constituents of interest consist of total phosphorus (TP), total nitrogen (TN), biochemical oxygen demand (BOD), and total suspended solid (TSS). The analysis of assimilative capacity of the Tseng-Wen Reservoir based on various types of numerical models is also included for the evaluation of the eutrophication issue. Advanced management strategies with regard to the proper use of assimilative capacity of the Tseng-Wen Reservoir and the land resources in the watershed are then discussed in terms of three classified impact levels of non-point sources in the watershed. The methodology is proved practical, promising, and effective for assessing the eutrophication issue in the reservoir watershed within a short period of time.
Emission inventory data is one of the major inputs for all air quality simulation models. Emission inventory data for the prediction of ground-level ozone concentration, grouped as point, area, mobile and biogenic sources, are a composite of all reported and estimated pollutant emission information from many organizations. Before applying air quality simulation model, the emission inventory data generally require additional processing for meeting spatial, temporal, and speciation requirements using advanced information technologies. In this study, SMOKE was setup to update the essential emission processing. The emission processing work was performed to prepare emission input for U.S. EPA's Models-3/CMAQ. The fundamental anthropogenic emission inventory commonly used in Taiwan is the TEDS 4.2 software package. However, without the proper inclusion of accurate estimation of biogenic emission, the estimation of ground-level ozone concentration may not be meaningful. With the aid of SPOT satellite image, biogenic gas emission modeling analysis can be achieved to fit in BEIS-2 in SMOKE. Improved utilization of land use identification data, based on SPOT outputs and emission factors, may be influential in support of the modeling work. During this practice, land use was identified via an integrated assessment based on both geographical information system and remote sensing technologies; and emission factors were adapted from a series of existing database in the literature. The research findings clearly indicate that the majority of biogenic VOCs emissions occurred in the mountains and farmland actually exhibit fewer impacts on ground-level ozone concentration in populated areas than the anthropogenic emissions in South Taiwan. This implies fast economic growth ends up with sustainability issue due to overwhelming anthropogenic emissions.
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