Abstract

Taking advantage of the opportunity provided by the nationally funded Water Resources Integrated Planning and Investigation of China program (WRIPI), a model was established to estimate non-point source pollutant loads in a large-scale basin (ENPS-LSB) on the basis of hydrological processes and pollutant transport. The model made use of Environment for Visualizing Images software (ENVI) and Interactive Data Language (IDL) and took the characteristics of present-day China into account: a huge rural population scattered widely, marginal rural infrastructure and livestock cultivation based on scatter-feeding. The model was divided into two sections: one on dissolved and one on adsorbed pollutant loads. The dissolved loads were divided into four different types: those originating from agricultural fields, urban areas, rural residential areas, and livestock. The study was undertaken in the Yangtze River Basin. The results showed the chemical oxygen demand (COD), the total nitrogen (TN), the total phosphorous (TP), and the ammonia nitrogen (NH3–N) loads to be 2.6 × 106, 1.6 × 106, 9.3 × 105 and 3.1 × 105 tons, respectively, in the year 2000. The dissolved COD resulted mainly from rural residential areas and livestock; 76.8% of the dissolved TN and 86.4% of the dissolved TP produced were from agricultural fields. The Yangtze River Delta, the lower reaches of the Han River, and part of the Dongting Lake, Taihu Lake and Poyang Lake basins all had relatively high dissolved pollutant loads; adsorbed nitrogen and phosphorus loads were mainly observed in the middle and upper reaches of the Yangtze River Basin. Dissolved loads were most affected by human activity, whereas adsorbed loads were most affected by natural factors. The results showed that the model performed well on large scale, describing pollutant loads effectively. This makes it possible to properly consider not only point source pollutant discharge but also non-point source pollution in the Yangtze River Basin. Combining point source discharge investigation with the ENPS-LSB model could assist environmental management with controlling water pollution.

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