Urban waterlogging will harm economic development and people’s life safety; however, the waterlogging risk zoning map provides the necessary decision support for the management of urban waterlogging, urban development and urban planning. This paper proposes an urban waterlogging risk assessment method that combines multi-criteria decision analysis (MCDA) with a geographic information system (GIS). The framework of urban waterlogging risk assessment includes four main elements: hazard, exposure, vulnerability, and emergency response and recovery capability. Therefore, we selected the urban area of Changchun City, Jilin Province as the study area. The Analytic Hierarchy Process (AHP) is a generally accepted MCDA method, it is used to calculate the weight and generate a result map of hazards, exposure, vulnerability, and emergency responses and recovery capability. Based to the principle of natural disaster risk formation, a total of 18 parameters, including spatial data and attribute data, were collected in this study. The model results are compared with the recorded waterlogging points, and the results show that the model is more reliable.

Tianchi volcano is a dormant active volcano with a risk of re-eruption. Volcanic soil and volcanic ash samples were collected around the volcano and the concentrations of 21 metals (major and trace elements) were determined. The spatial distribution of the metals was obtained by inverse distance weight (IDW) interpolation. The metals’ sources were identified and their pollution levels were assessed to determine their potential ecological and human health risks. The metal concentrations were higher around Tianchi and at the north to the west of the study area. According to the geo-accumulation index (I_geo), enrichment factor (EF) and contamination factor (CF) calculations, Zn pollution was high in the study area. Pearson’s correlation analysis and principal component analysis showed that with the exception of Fe, Mn and As, the metals that were investigated (Al, K, Ca, Na, Mg, Ti, Cu, Pb, Zn, Cr, Ni, Ba, Ga, Li, Co, Cd, Sn, Sr) were mostly naturally derived. A small proportion of Li, Pb and Zn may have come from vehicle traffic. There is no potential ecological risk and non-carcinogenic risk because of the low concentrations of the metals; however, it is necessary to pay attention to the carcinogenic risk of Cr and As in children.

The impacts of earthquakes and secondary disasters on ecosystems and the environment are attracting increasing global attention. Development of uncertainty reasoning models offers a chance to research these complex correlations. The primary aim of this research was to construct a disaster chain hazard assessment model that combines a Bayesian Network model and the ArcGIS program software for Changbai Mountain, China, an active volcano with a spate of reported earthquakes, collapses, and landslide events. Furthermore, the probability obtained by the Bayesian Networks was used to determine the disaster chain probability and hazard intensity of the earthquake events, while ArcGIS was used to produce the disaster chain hazard map. The performance of the Bayesian Network model was measured by error rate and scoring rules. The confirmation of the outcomes of the disaster chain hazard assessment model shows that the model demonstrated good predictive performance on the basis of the area under the curve, which was 0.7929. From visual inspection of the produced earthquake disaster chain hazard map, highly hazardous zones are located within a 15 km radius from the Tianchi center, while the northern and the western parts of the studied area are characterized mainly by “very low” to “low” hazard values.

The aim of this project was to produce an earthquake–landslide debris flow disaster chain susceptibility map for the Changbai Mountain region, China, by applying data-driven model series and parallel model and Bayesian Networks model. The accuracy of these two models was then compared. Parameters related to the occurrence of landslide and debris flow disasters, including earthquake intensity, rainfall, elevation, slope, slope aspect, lithology, distance to rivers, distance to faults, land use, and the normalized difference vegetation index (NDVI), were chosen and applied in these two models. Disaster chain susceptibility zones created using the two models were then contrasted and verified using the occurrence of past disasters obtained from remote sensing interpretations and field investigations. Both disaster chain susceptibility maps showed that the high susceptibility zones are situated within a 10 km radius around the Tianchi volcano, whereas the northern and southwestern sections of the study area comprise primarily very low or low susceptibility zones. The two models produced similar and compatible results as indicated by the outcomes of basic linear correlation and cross-correlation analyses. The verification results of the ROC curves were found to be 0.7727 and 0.8062 for the series and parallel model and BN model, respectively. These results indicate that the two models can be used as a preliminary base for further research activities aimed at providing hazard management tools, forecasting services, and early warning systems.

Clean groundwater resources are vital to human health. To evaluate groundwater quality in the Songnen Plain (Jilin), a field investigation sampling test, multivariate statistical analysis, and spatial analysis were conducted based on a geographic information system. The main substances exceeding the standard were screened out, and the main controlling factors affecting groundwater quality were discussed. The research result showed that nine components exceeded groundwater standards by approximately 10%: Al, total hardness (TH), total dissolved solids (TDS), Mn, As, NO₃⁻, Fe, F⁻, and BaP. The over-standard of TDS and TH in groundwater are mainly distributed in the geological environment conditions and unreasonable exploitation and utilization of groundwater in this area. The results of the multi-index evaluation showed that the most important factors affecting groundwater quality were general chemical indices, followed by inorganic toxicology and heavy metals. Controlling the overexploitation of water resources, controlling agricultural activities and sewage discharge, and implementing water conservation systems are the main pathways to improve water quality in the study area. The research results can provide a reference for groundwater pollution control and water resource protection in the Songnen Plain (Jilin).

This study quantitatively assesses the resilience of the urban transport system in Changchun under extreme climatic conditions, focusing on the impacts of natural disasters such as snowstorms, strong winds and extreme low temperatures on the transport system. The vulnerability, exposure, and emergency recovery capacity of the transport system in Changchun were analyzed by constructing a comprehensive assessment framework combining multi-criteria decision analysis (MCDM) and geographic information system (GIS). Based on the meteorological and traffic data of Changchun City in the past 10 years, key indicators such as traffic network density, emergency resource distribution, traffic flow, and extreme weather frequency were selected in this study. The weights were calculated by the improved hierarchical analysis method (AHP) and entropy weighting method, and finally the traffic resilience of Changchun city was quantitatively analyzed. The results show that there are significant spatial differences in the toughness of the transport system in Changchun, of which 38.6% of the areas have very low toughness and are concentrated in the urban fringe and urban–rural areas; 25.3% of the areas are at a medium level of toughness; and 5.4% of the areas show high toughness and are mainly located in the city center and important transport hubs. This study proposes transport resilience enhancement strategies for different areas of Changchun, with special recommendations for strengthening infrastructure development, optimizing traffic management and emergency response capacity in low resilience areas. The results of this study provide a scientific basis for Changchun to cope with future extreme climate challenges, and a reference framework for other cities with similar climatic conditions.