Response of sediments and phosphorus to catchment characteristics and human activities under different rainfall patterns with Bayesian Networks

• Published in: Journal of hydrology (Amsterdam) 2020-05, Vol.584, p.124695, Article 124695
• Main Authors: Jin, Guangqiu, Xu, Jing, Mo, Yuming, Tang, Hongwu, Wei, Tong, Wang, You-Gan, Li, Ling
• Format: Article
• Language: English
• Subjects: Bayesian Network; Human activity; Rainfall pattern; Suspended sediment; Total phosphorus
• ISSN: 0022-1694; 1879-2707
• DOI: 10.1016/j.jhydrol.2020.124695

[Display omitted] •Heavy rainfall increases the contribution of sediment to total phosphorus.•Human activities contributed more to water pollution in the Huaihe River Basin.•With heavy antecedent rainfall, farmland was the most significant pollution source. The rainfall patterns play an important role in determining the response of Suspended Sediment (SS) and Total Phosphorus (TP) to influence factors, which is complex and needs to be better understood. The Bayesian Network (BN), with each variable depending on only its immediate parent variables, can help to describe the complex processes involved. In this study, BNs were developed to assess the impacts of catchment characteristics and human activities on SS and TP loads under different rainfall patterns in the Huaihe River Basin (HRB). The results showed that SS made significant contributions to TP in rivers which increased with the rainfall intensity. Catchment characteristics (sub-catchment area, slope and soil erosion area) affected the SS and TP loads; however the influence of human activities (sewage outfalls and land use) was more significant. With the rainfall intensity rising, farmland switched from a “sink” to a “source” of nutrients. When the antecedent three-day-average rainfall intensity was high but the current one was low, the farmland became the most significant source of SS and TP. The urbanization had significant positive effects on SS (ranging from 10.9% to 15.1%) and TP (ranging from 8.3% to 10.5%), which was insensitive to rainfall patterns as a result of the high proportions of impervious surface coverage in the urban area. These results improve our understanding of influence factors on river water quality and will contribute to effective water environment management for rivers.