Abstract
Development of any area often leads to more intensive land use and increase in the generation of pollutants. Modeling these changes is critical to evaluate emerging changes in land use and their effect on stream water quality. The objective of this study was to assess the impact of spatial patterns in land use and population density on the water quality of streams, in case of data scarcity, in the Chugoku district of Japan. The study employed artificial neural network (ANN) technique to assess the relationship between the total phosphorous (TP) in river water and the land use in 21 river basins in the district, and the model was able to reasonably estimate the TP in the stream water. Uncertainty analysis of ANN estimates was performed using the Monte Carlo framework, and the results indicated that the ANN model predictions are statistically similar to the characteristics of the measured TP values. It was observed that any reduction in forested area or increase in agricultural land in the watersheds may cause the increase of TP concentration in the stream. Therefore, appropriate watershed management practices should be followed before making any land use change in the Chugoku district.