Urban flood risk differentiation under land use scenario simulation

Influence of rainfall pattern and infiltration capacity on the spatial and temporal inundation characteristics of urban waterlogging

The rapid development of the city leads to the continuous updating of the land use allocation ratio, particularly during the flood season, which will exacerbate the significant changes in the spatial and temporal patterns of urban flooding, increasing the difficulty of urban flood forecasting and early warning. In this study, the spatial and temporal evolution of flooding in a high-density urban area was analyzed based on the Mike Flood model, and the influence mechanisms of different rainfall peak locations and infiltration rate scenarios on the spatial and temporal characteristics of urban waterlogging were explored. The results revealed that under the same return period, the larger the rainfall peak coefficient, the larger the peak value of inundation volume and inundation area. When the rainfall peak coefficient is small, the higher the return period is, and the larger the peak lag time of the inundation volume is, in which P = 50a, r = 0.2, the peak lag time of the inundation volume reached 32 min and 45 min for the inundation depths H > 0.03 m and H > 0.15 m, respectively. There are also significant differences in the peak lag time of waterlogging inundation volume for different inundation depths. The greater the inundation depth, the longer the peak lag time of the inundation volume, and the higher the return period, the more significant the effect of lag time prolongation. It is worth noting that the increase in infiltration rate may lead to an advance in the peak time of inundation volume and inundation area, and the peak time of the inundation area is overall more obvious than that of inundation volume. The effect of infiltration rate on the peak time of inundation volume for larger inundation depths was relatively large; the peak times of inundation volume and inundation area were advanced by 4-6 min and 4-8 min for H > 0.03 m and H > 0.15 m, respectively, after the increase in infiltration rate, and the higher the rainfall return period, the longer the advance time. The spatial and temporal characteristics of waterlogging under different peak rainfall locations and infiltration capacities obtained in this study can help provide a new perspective for temporal forecasting and warning of urban waterlogging.

The application of integrating comprehensive evaluation and clustering algorithms weighted by maximal information coefficient for urban flood susceptibility

Different sub-regions of Zhengzhou city have various levels of sensitivity to flood due to the impact of urbanization. Thus, an accurate flood sensitivities assessment is a key tool for flood prevention and urban planning and development. To successfully link the urban flood sensitivity assessment with the real flood situation, a method combining clustering algorithm with comprehensive evaluation is presented. The proposed method is not affected by the classification standard of sensitivities levels and has a small and undemanding demand for flood data. First, Maximal Information Coefficient between conditional factors and flood is employed to determine the weight. Then, the different results are obtained by three clustering algorithms. Finally, a four-layer evaluation structure weighted by analytic hierarchy process is established to select the best flood susceptibility map. A case study in the Zhengzhou city, China shows that the positive scale amplification strategy is relatively best and the flood sensitivity of sub-regions in Zhengzhou city should be divided into four levels obtained by K-Means clustering. Hence, it supplies the valuable insights for the urban planning and flood mitigation.

Coupling of soil methane emissions at different depths under typical coastal wetland vegetation types

As an important source of atmospheric methane, methane emissions from coastal wetlands are affected by many factors. However, the methane emission process and interrelated coupling mechanisms in coastal wetland soils of a variety of environments remain unclear owing to complex interactions between intensified anthropogenic activities and climate change in recent years. In this study, we investigated methane cycling processes and the response mechanisms of environmental and microbial factors in soils at different depths under four typical coastal wetland vegetation types of the Yellow River Delta, China, using laboratory culture and molecular biology techniques. Our results show that methane generation pathways differed among the different soil layers, and that the methane emission process has a special response to soil N compounds (NO3-, NH4+). We found that nitrogen can indirectly affect methane emission by impacting key physicochemical properties (pH, oxidation reduction potential, etc.) and some functional communities (mcrA, ANME-2d, sulfate-reducing bacteria (SRB), narG, nosZII). Methane production processes in shallow soils compete closely with sulfate reduction processes, while methane emissions facilitated in deeper soils due to denitrification processes. We believe that our results provide a reference for future research and wetland management practices that seek to mitigate the global greenhouse effect and climate change.