Assessing Anthropogenic Impacts on Chemical and Biochemical Oxygen Demand in Different Spatial Scales with Bayesian Networks

Abstract

In order to protect the water environment in seriously polluted basins, the impacts of anthropogenic activities (sewage outfalls and land use) on water quality should be assessed. The Bayesian network (BN) provides a convenient way to model these complex processes. In this study, anthropogenic impacts on chemical oxygen demand (COD) and biochemical oxygen demand (BOD) were evaluated in the Huaihe River basin (HRB) considering dry and wet seasons and different spatial scales. The results showed that anthropogenic activities had the most significant impacts on COD and BOD at the catchment scale. In dry seasons, sewage outfalls played an important role in organic pollution. Farmland became the most important source in wet seasons although it had a “sink” process in dry seasons. Intensive human activities in urban made significant contributions to increased COD levels. Grassland had a negative relationship with organic pollution, especially in dry seasons. Therefore, governments should implement strategies to control organic matters transported from urban and farmland regions. Increasing the efficiency of wastewater treatments and the percentage of grassland in the riparian zone could improve water quality. These results can enhance understanding of anthropogenic impacts on water quality and contribute to efficient management for river basins.