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This paper combines environmental science, inorganic chemistry, water quality monitoring and other disciplines to analyze and assess the heavy metals in the water bodies and sediments of the Fenghe River Basin (FRB) in Shaanxi Province, and reveal their sources. Water Quality Index (WQI), Nemero Index (Pn), Geological Accumulation Index (I-geo) and Potential Ecological Risk Index (RI) are used to assess heavy metals in water and sediments. Pearson correlation analysis (CA), hierarchical cluster analysis (HCA), principal component analysis (PCA) and positive matrix factorization (PMF) models are used to study the relationship and source of heavy metals. The results show that most of the residual heavy metals in the water are below the corresponding environmental quality standards for surface water. Most of the heavy metals in the sediment exceed the background value of the soil.The factors or sources of heavy metals in water and sediment are revealed in detail through PMF models. The main sources of pollution in the region are urban construction and transportation, electronics industry, machinery manufacturing and tourism. In water, the average contribution rates of these four sources to heavy metals were 36.8%, 11.7%, 9.4% and 42.0%, and in sediments were 8.0%, 29.2%, 23.9% and 38.9%. Therefore, these sectors should be given sufficient attention.

Reconstruction of historical land uses helps to understand patterns, drivers, and impacts of land-use change, and is essential for finding solutions to land-use sustainability. In order to analyze the relationship between land-use change and urban flooding, this study used the Classification and Regression Tree (CART) method to extract modern (2017) land-use data based on remote sensing images. Then, the Paleo-Land-Use Reconstruction (PLUR) program was used to reconstruct the land-use maps of Xi’an during the Ming (1582) and Qing (1766) dynasties by consulting and collecting records of land-use change in historical documents. Finally, the Flo-2D model was used to simulate urban flooding under different land-use scenarios. Over the past 435 years (1582–2017), the urban construction land area showed a trend of increasing, while the unused land area and water bodies were continuously decreasing. The increase in urban green space and buildings was 20.49% and 19.85% respectively, and the unused land area changed from 0.32 km2 to 0. Urban flooding in the modern land-use scenario is the most serious. In addition to the increase in impervious areas, the increase in building density and the decrease in water areas are also important factors that aggravate urban flooding. This study can provide a reference for future land-use planning and urban flooding control policy formulation and revision in the study area.

This paper combines environmental science, inorganic chemistry, water quality monitoring and other disciplines, and uses several representative evaluation methods (WQI, Pn, I-geo, RI) for heavy metals in water and sediments. A preliminary assessment and source analysis of heavy metals (Cd, Cr, Fe, Mn, Zn, Cr, Ti, Ni, Cu, As, Pb, Sr) in water and surface sediments of the Fenghe River Basin, Shannxi Province, China was carried out in this study. Results indicate that most of the heavy metals in water are below national water quality standards. Exceptions include Mn, which exceeds national tertiary standards and Cr, which exceeds national drinking water standards. Most heavy metals in the sediments exceed the environmental standard values except Ni. Water quality index (WQI) and Nemero index (Pn) showed the same trend in contamination levels of sampling sites. According to the Geological Accumulation Index method (I-geo) and the Potential Ecological Risk Index method (RI), high concentrations of Cd poses a high ecological risk in some sampling locations. Pearson Correlation Analysis (CA), Hierarchical Clustering Analysis (HCA), Principal Component Analysis (PCA) and Positive Matrix Factorization (PMF) models are used to explore the relationships and sources of heavy metals. In general, upstream sources are similar, and middle and lower reaches are easily clustered into a large category except for some specific sampling points. For example, metals in sampling site FHK mainly come from surrounding residents and farms and heavy metals attributes in sampling site SLQ relate to the fact that municipal sewage is collected and treated. The factors or sources of heavy metals in water and sediment are revealed in detail through PMF models. In the water, the average contribution rate of these four source factors for heavy metals is 36.8%, 11.7%, 9.4% and 42.0%, while the average proportion of these four factors for heavy metals in sediment is 8.0%, 29.2%, 23.9% and 38.9% respectively. Results show that the main sources of pollution in the region are urban construction and transportation, electronics industry, machinery manufacturing, tourism and agriculture. These sectors should therefore be given sufficient attention in the prevention and management of heavy metal pollution.