In recent years, urban flooding has become an increasingly serious problem, posing a serious threat to socio-economic development and personal safety. In this paper, we consider the Dongfeng Canal area in Zhengzhou City as an example and build a 1D/2D coupled urban flood model using the InfoWorks ICM. This study area uses six scenarios with rainfall return periods of 5 a, 20 a, and 50 a, corresponding to rainfall ephemeris of 1 h and 2 h to assess the flood risk. The results of the study show that (1) The flood depth, inundation duration, and extent of inundation in the study area vary with the return period and rainfall history. Generally, most of the water accumulation is concentrated in the low-lying areas adjacent to the river and near the roadbed. (2) As the rainfall recurrence period and rainfall duration increase, the proportion of overflow at the nodes becomes more pronounced and the overload from the pipe network flows mainly to the overload. (3) The high-risk areas under the different scenarios are mainly distributed on both sides of the river, and most of the low-risk areas transform into medium- and high-risk areas as the rainfall recurrence period and rainfall duration increase. This study analyses the flood risk situation under different scenarios, as well as the elements and areas that should be monitored in case of flooding, with the aim of providing a reference for flood prevention and control in the study area and formulating corresponding countermeasures. It also serves as a reference for flood risk analysis in other areas with similar situations.

Determination of heavy metal (HM) contamination, ecological risks, and sources in river sediments are important to preventing and controlling environmental pollution. This study investigated the spatial distribution, potential ecological risks, and biological toxicity of five heavy metals in river sediments of Huanghua City in the water diversion area from the Yellow River, China. GIS, redundancy analysis (RDA), and the positive matrix factorization (PMF) model were used to accurately quantify the pollution sources and the spatial distribution of pollution sources. The results revealed that Cu had the highest degree of natural pollution, and the source mainly comes from traffic. Residential land (RL), population density (PD), GDP, and industrial construction (IC) make high contributions to traffic pollution; the highest level of potential ecological risk was Hg, and the source mainly comes from industrial wastewater discharges. IC makes a high contribution to industrial wastewater discharges pollution; the highest effect of bio-toxic risk was As, and the source mainly comes from farmland drainage water. Agricultural production potential (APP) and water area (WA) make high contributions to farmland drainage water pollution; Zn might be of natural origin, and woodlands (WLs) make high contribution to natural origin. This result provided a new idea for the system control of sediment heavy metal pollution in Huanghua City.

The assessment of river health holds paramount significance in diagnosing the conditions of river water environments, and its research serves as a crucial foundation for the functional management and restoration of rivers. We discuss the concept and assessment criteria of health in areas characterized by significant human activity. Utilizing the “over the riverbank” and “under the riverbank” quantification criteria as the framework, a comprehensive river health assessment index system is developed, encompassing seven aspects (riparian zone condition, pollution discharge condition, human–water interaction, physical structure, water environment, water ecology, and socio-economic service function) and 35 indicators. This study introduces the River Health Index (RHI), specifically tailored for regions with significant human activity, facilitating the quantitative assessment of river health status and precise calculation of the River Health Index in these areas. The research employs the RHI to assess the health condition of the Cangzhou section of the Qingliang River in China. The results indicate that the Qingliang River is in a suboptimal state of health, with the key limiting factors being the aspects of “water environment” and “water ecology”. The research demonstrates that the proposed river health assessment system for areas with significant human activity effectively reflects the objective reality of the Qingliang River, exhibiting a high level of reliability and applicability.