Assessing spatiotemporal risks of nonpoint source pollution via soil erosion: a coastal case in the Yellow River Delta, China.

Nonpoint source pollution (NPSP) has always been the dominant threat to regional waters. Based on empirical models of the revised universal soil loss equation and the phosphorus index, an NPSP risk assessment model denoted as SL-NPSRI was developed. The surface soil pollutant loss was estimated by simulating the rain-runoff topographic process, and the influence of path attenuation was quantified. A case study in the Yellow River Delta and corresponding field surveys of soil pollutants and water quality showed that the established model can be applied to evaluate the spatial heterogeneity of NPSP. NPSP usually occurs during high-intensity rainfall periods and in larger estuaries. Summer rainfall increased pollutant transport into the sea from late July to mid-August and caused estuarine dilution. Higher NPSP risks often correspond to coastal areas with lower vegetation coverage, higher soil erodibility, and higher soil pollutant concentrations. Agricultural NPSP originating from cropland significantly increase the pollutant fluxes. Therefore, area-specific land use management and vegetation coverage improvement, and temporal-specific strategies can be explored for NPSP control during source-transport hydrological processes. This research provides a novel insight for coastal NPSP simulations by comprehensively analyzing the soil erosion process and its associated pollutant loss effects, which can be useful for targeted spatiotemporal solutions.

[Estimation of Agricultural Non-point Source TN and TP Export Coefficients Based on Soil Loss].

Taking the Yellow River Delta as a typical research area, we constructed a coastal agricultural TN and TP non-point source pollution estimating model by analyzing the relationship between the surface soil pollutant loss risks and the monitored pollutant flux into the sea. On this basis, TN and TP non-point source export coefficients of paddy fields, irrigated land, and dry land were calculated, and the verification showed that the estimated export coefficients were acceptable. In the study area, the TN and TP export coefficients into the sea of arable land were 18.33 kg·(hm2·a)-1 and 1.02 kg·(hm2·a)-1, respectively. The agricultural non-point source pollution loads of arable land were relatively high in summer. The sub-basins with larger agricultural non-point source pollution loads were mainly located in the control areas of the Zhimai River, Guangli River, and Xiaodao River. The administrative regions with larger total agricultural TN and TP loads were mainly in the northern Huanghekou Town and Yong'an Town, and areas with larger loads per unit area were in the southwest. Therefore, it is necessary to pay more attention to the temporal effects of agricultural non-point source pollution, simultaneously coordinate the social and economic development, and formulate comprehensive agricultural non-point source pollution prevention and control strategies from the perspective of sub-basins and administrative units. This will allow us to improve the offshore pollution status from the perspective of land and sea coordination.

Using soil erosion to locate nonpoint source pollution risks in coastal zones: A case study in the Yellow River Delta, China.

Soil erosion contributes greatly to nonpoint source pollution (NSP). We built a coastal NSP risk calculation method (CNSPRI) based on the Revised Universal Soil Loss Equation (RUSLE) and geospatial methods. In studies on the formation and transport of coastal NSP, we analysed the pollution impacts on the sea by dividing subbasins into the sea and monitoring the pollutant flux. In this paper, a case study in the Yellow River Delta showed that the CNSPRI could better predict the total nitrogen (TN) and total phosphorus (TP) NSP risks. The value of the soil erodibility factor (K) was 0.0377 t h·MJ-1·mm-1, indicating higher soil erodibility levels, and presented an increased trend from the west to the east coast. The NSP risk also showed an increased trend from west to east, and the worst status was found near the Guangli River of the south-eastern region. The contributions of the seven influencing factors to CNSPRI presented an order of vegetation cover > rainfall erosivity > soil content > soil erodibility > flow > flow path > slope. The different roles of source and sink landscapes influenced the pollutant outputs on a subbasin scale. Arable land and saline-alkali land were the two land-use types with the greatest NSP risks. Therefore, in coastal zones, to reduce NSP output risks, we should pay more attention to the spatial distribution of vegetation cover, increase its interception effect on soil loss, and prioritize the improvement of saline-alkali land to reduce the amount of bare land.