The spatial distribution of heavy metals in rivers is affected by human activities and the natural environment, posing a risk to human health related to heavy metal pollution. In order to study the characteristics, health risk levels, and influencing factors of heavy metal distribution and pollution in the lower reaches of the Qianhe River, 19 surface sediments and 20 water samples were collected, and the contents of As, Cd, Cr, Cu, Mn, Ni, Pb, and Zn were measured by inductively coupled plasma mass spectrometry(ICP-MS). Using the DEM, air temperature, precipitation and other 11 factors as independent variables, the spatial differentiation of heavy metal pollution in sediments were explored based on geo-detector and geo-weighted regression model. The results showed that the eight heavy metal contents in the lower reaches of the Qianhe River did not exceed the "Surface Water Environmental Quality Standards" Ⅱ for water-like bodies, in which the variation coefficient of Pb element was 3.11, and the high content areas were mainly concentrated around Dongling Smelting Company and Fengxiang Railway Station. The average Rc value of adult carcinogens in water bodies was 7.72 E-06, showing a low risk level, and the children's carcinogens average Rc value was 1.17 E-04, showing a strong risk degree. The non-carcinogen risks for adults and children were both tolerable. The total high R value for children was mainly concentrated around Fengxiang Railway Station, posing a high risk. Sedimentation of heavy metals, except As and Mn, exceeded the soil background value in Shaanxi Province. The average content of Cd element was 1.12 mg·kg-1, which was 12 times the soil background value in Shaanxi Province. The pollution of Cd, Zn, and Pb was high, and distributed mainly in Changqing Village, Nanwan Village and Niujiatan Village, Gaozhuang, and Dongling Smelting Company. PLIzone of heavy metals in the sediments in the study area was 1.71, which was light pollution. DEM, temperature and precipitation were the main natural factors influencing the spatial pattern of heavy metal pollution load index(PLI) in sediments, and their nonlinear interactions were enhanced, which may play a role in the spread of heavy metals in sediments. This research can provide a scientific basis for urban planning and human health risks prevention in the Qianhe River.
Keywords: Qianhe River; geographic detector; geographical weighted regression(GWR); heavy metals; risk assessment; spatial distribution.