Against the backdrop of global warming and rising sea levels coupled with increasing urbanization, flood risks for plain cities have intensified. This study takes Liaocheng City as its research object and constructs a regional flood risk assessment model based on a combination of subjective and objective multi-weight methods. The model sets weights according to different return periods from three perspectives: the severity of disaster-causing factors, the exposure of disaster-prone environments, and the vulnerability of disaster-bearing bodies. It also uses a subjective–objective combination of weights for the severity of disaster-causing factors, adopts CRITIC-entropy weights for the exposure of disaster-prone environments and vulnerability of disaster-bearing bodies, and adopts AHP subjective weights for the criterion layer. Based on GIS spatial analysis technology, the examination and zoning of flood disasters at a county scale were carried out. The results show that, unlike the existing weighting methods and machine learning methods, this multi-weight combination method can simultaneously avoid the subjectivity of the results and the uncertainty of parameters, thus enabling more accurate decision-making results to be obtained. The spatial distribution of the comprehensive risk is high in the central and western parts and relatively low in the south and north, while the area characterized by very high risk is concentrated in Dongchangfu District and Guanxian County. With the gradual increase in return periods, the overall spatial distribution of medium-to-very-high-risk areas in risk zoning gradually shrinks, and the spatial distribution of very-high-risk areas gradually moves south but maintains a stable distribution rule. Flood risk assessment is an important basic process for disaster prevention and mitigation in plain cities, and the results of this study can provide a reference for similar plain cities.

As the social economy is further developed, there have been increasingly severe ecological and environmental issues. For instance, rivers located in mountainous areas are often encountered with the issue of zero flow. The ecological base flow was put forward to ensure the continuous flow of rivers, to realize the minimum ecological function, and to meet the most fundamental requirements of sustaining the river ecosystem. Wulong River Basin in Yantai City of China was taken as example here. Based on the runoff data collected in the Tuanwang Hydrological Station from 1960 to 2016, the measured runoff data was restored to natural runoff sequence by adopting the item-by-item investigation method. The different ecological base flows of Wulong River were calculated by adopting the Tennant Method, the Q_p90 Method, the Texas Method, the Base Flow Ratio Method, the Tessman Method, and Wetted Perimeter Method. The research findings have shown that the Base Flow Ratio Method proves to be the optimal approach for calculating the ecological base flow of Wulong River. Based on the analysis of the assurance degree of ecological base flow, the period from April to June is the period with the lowest assurance degree of ecological base flow.

It is interesting to study the impact of urbanization on climate in the Taihu Lake Basin. This study employed the Weather Research and Forecasting (WRF) model to simulate the Taihu Lake Basin's urbanization effect on climate. The results show that as the area of urbanization increases, the downwind precipitation in the study area increases significantly. In addition, the urbanization of the land surface has a strong impact on the surface energy balance, which can not only strengthen the transportation of the sensible heat flux from the surface to the atmosphere but even affect the transportation of water vapor, resulting in a decrease in specific humidity at 2 m from the ground surface. The simulation results have important theoretical significance in understanding the impact of urbanization on regional climate.

Water resources play a key role in development. The research on water resources carrying capacity (WRCC) is helpful to judge the development status and provide suggestions for regional policy-making. In this study, the System Dynamics (SD) model and the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method are combined to calculate the change of WRCC of the Hangbu River basin from 2015 to 2035 under four development scenarios. The results show that WRCC of each scenario decreases first and then increases. The scenario that prioritizes water resources is the best for the Hangbu River Basin, under which the WRCC will increase to 0.631 in 2035, achieving a good level. This is different from other WRCC studies. Through analysis, the research method and the development level and focus of the study area may be the reasons for this difference. In addition, some suggestions were provided such as focusing on improving the efficiency of irrigation water use and looking at the long-term development of the region.