Scientific evaluation of flood resource utilization potential is an important prerequisite for carrying out flood resource utilization in the basin and alleviating the contradiction between supply and demand of water resources. To evaluate the potential of flood resource utilization in different sections of the Xizhijiang River Basin, the SWAT model was constructed to simulate the natural runoff process of Xizhijiang River Basin, and the flood resources of the basin were quantified by combining the limit analysis theory. The potential of flood resources utilization in the upper, middle and lower reaches of the basin was evaluated, and the feasibility of flood resources utilization in Xizhijiang River Basin was discussed based on the water quality conditions. The results show that the SWAT model has good applicability in runoff simulation of Xizhijiang River Basin; The inter-annual distribution of flood resources is uneven, and there are great differences in inter-annual flood resources utilization potentiality. The utilization condition of flood resources in the lower reaches is better than that in the upper reaches, while the utilization rate of flood resources in the lower reaches is lower. The average annual current and theoretical utilization potential of flood resources in the lower reaches are 3.48×10⁸m³ and 7.97×10⁸m³, respectively. The water quality indexes of the main stream of Xizhijiang River Basin are not lower than the class Ⅲ standard, and the utilization of flood resources in Xizhijiang River is feasible. This study can provide support for the optimal allocation of flood resources in Xizhijiang River Basin, and it has an important reference value for achievement of high quality development of the basin.

In order to analyze the Nitrogen pollution status and changes in the Yihe River Basin, a SWAT model was established, and the model was calibrated based on the monitoring data of Linyi Station. Its temporal and spatial distribution characteristics were analyzed and the key pollution sources were identified. The results show that the SWAT model has good applicability in the simulation research of runoff and pollution in the Yihe River Basin; The pollution is mainly concentrated in the flood season from July to September, and the ammonia nitrogen and total nitrogen load account for 73.34% and 81.58% of the whole year; The sub-basin in the southwest and close to the water system in the northeast are the main source area of pollution; The main sources of pollution in the basin are sewage discharge, agricultural fertilization and soil loss. Taking Nitrogen fertilizer reduction, returning farmland to forest and comprehensive management measures for the changes can effectively reduce the discharge of pollution load.

Support Vector Machine (SVM) has advantages in small sample simulation prediction, but there is subjectivity in the selection of penalty factor C and kernel function parameter γ in SVM. Therefore, the Harris Hawks Optimization (HHO) algorithm was used to optimize C and γ in the SVM. And then the HHO-SVM mode was established to predict water quality in the Xiyuan tunnel section of Lake Dianchi Caohai. The results show that the prediction accuracy of the water quality prediction model based on HHO-SVM is higher than that of the SVM based on genetic algorithm (GASVM) and the SVM based on whale optimization algorithm (WOA-SVM). It is proved that the HHO is feasible to optimize the parameters in SVM, and HHO-SVM can be used in water quality prediction.

Aiming at the problem that the traditional water quality prediction method is difficult to capture the spatial and temporal characteristics of the sample, this paper proposes to establish a CNN-EA-ConvLSTM based water quality prediction model. The convolutional neural network (CNN) was used to reduce the dimensionality of the data and extract the sample features. Then the hidden information among samples was explored by the external attention mechanism. The convolutional long and short-term memory network (ConvLSTM) was further used to capture the spatial characteristics of the data. To achieve optimal results of the model, a genetic algorithm was used to optimize the parameters of the model. The water quality test data of Qinghai Province was used as a sample to simulate and validate the model. The results show that the mean absolute error (M_MAE) of the model is 0.063, the root mean square error (R_RMSE) is 0.012, and the mean absolute percentage error is 2.6%, which are respectively reduced by 18% and 24%, 14% and 25%, 16% and 21% compared with the CNN-EA model and CNN-LSTM model. Therefore, the model can effectively obtain the spatial and temporal characteristics of water quality, attenuate the influence of different samples, and achieve the ideal prediction effect.

In the case that hydrological data only include rainfall station data and measured water level data of river monitoring section, it is always a major challenge to improve the accuracy of flood forecasting in small and medium-sized basins. In this paper, flood automatic coding was realized according to data characteristics, and historical floods were classified by using decision tree model, thus the candidate flood groups and eliminated flood groups were obtained and the calculation efficiency was improved. On this basis, a flood forecasting model was established based on the similarity measurement of spatio-temporal hydrological data. Taking the hydrological data of Dafenshui Basin in Jiangxi Province as an example, a case analysis of hydrological data was carried out, and four floods were randomly selected for verification. The results show that the qualification rate of flood peak water level is 100%, and the qualification rate of flood peak time is 75%, the accuracy is high, which has important theoretical value and practical significance in hydrological data research.

Regarding the impact of the construction of the Guotan Hub of the Tanghe Navigation Project on the flood control safety of the river channel, the design flood of Guotan Hub was calculated through measured flood data of hydrological stations and linear interpolation method. According to the measured cross sections and thalwegs over the years, the river channel scouring and silting evolution and evolution trend prediction were analyzed. The water surface profile of a river was calculated using the energy equation of a constant non-uniform gradient flow equation. The second-order RungeKutta method of a two-dimensional model was used to simulate the impact of construction projects on the flow field during river flood discharge. The results indicate that the Guotan Hub of the Tanghe Navigation Project has a relatively small impact on river flooding so that solved the technical problem of flood impact assessment for Guotan Shipping Hub, which provided reference for relevant departments.

Aiming at the problem of campus waterlogging in Hefei City, this paper constructs a 1D-2D coupled model based on Mike Flood. Firstly, GIS was used to obtain the distribution information of the five types of land surface in the study area by analyzing satellite images, and to automatically divide the catchment areas. Secondly, combined with the measured elevations by using the RTK device, the 3 m×3 m high-precision DEM data of the study area were obtained. A 1D pipeline model and a 2D surface model in the study area were constructed using Mike Urban and Mike 21 respectively, and the two models were coupled on Mike Flood. At the same time, a flowmeter, a liquid level meter and a rain gauge were installed in the campus. The model was calibrated by two measured rainfall events according to R² and E_NSE. Finally, the Chicago rainfall pattern was used to design rainfall scenarios for the 5, 10, 30 and 50 years of recurrence periods, and the severity, inundation range and inundation depth of nodes and pipelines in different rainfall processes were simulated. The simulation results show that main causes for the waterlogging in the campus are due to unreasonable sub-catchment designs, which resulted in limited absorption of rain peak runoff and serious overload of the pipe network.

In view of the frequent occurrence and serious loss of urban waterlogging disasters in recent years, this paper focuses on the current situation of engineering of waterlogging drainage, and takes Lu'an City, Anhui Province, which experienced waterlogging disasters in 2016 and 2020 as the research object. Considering the connection relationship between drainage network and drainage channel systematically, the study analyzes and determines the engineering weakness that cause urban waterlogging from the aspects of the standard of drainage network corresponding to the location of water logging points, the relationship between ground elevation and the design water level of the corresponding receiving rainwater river, the drainage capacity of the river, and the operation conditions of the drainage pumping station, based on the tracking of rainwater discharge process of pipe network-inland river-outland river. The results show that the elevation of water logging point in the old urban area of Lu'an City has the condition of flowing into the river by gravity, and the drainage channel and drainage pumping station can meet the drainage requirements. The main engineering reason for the occurrence of waterlogging is that most drainage network have low standards and can not drain rainwater into the river in time. On this basis, it is further considered that the implementation of the drainage network rectification in the old urban area is difficult and long cycle. In order to minimize the risk of waterlogging before rectification, it is proposed to reduce the operation water level of the drainage pumping station at the estuary of the outland river, so as to improve the ability of urban drainage and disaster reduction.

In order to study the impact of the dam break of the Huiling tailings pond in Guangxi on the downstream region, a three-dimensional model of the tailings pond region conforming to the actual terrain was established with the help of GOCAD and Rhino software. In addition, PFC3D discrete element simulation software was used to simulate the state of dam break when the tailings pond runs to the final accumulation elevation +490 m, and the possible submerged range of tailings discharge and the area affected by tailings debris flow were analyzed. The results show that the evolution rate of tailings debris flow increases rapidly to the maximum value in a short time after dam break, and then decreases gradually. The farther away from the dam site, the faster the reduction of tailings debris flow evolution rate is. When the evolution time of dam break is 1 100 s, the furthest evolution distance of tailings is 1 215 m at the foot of tailings dam, the maximum width of the drainage body is 853 m, and the maximum depth is about 30 m. In the process, many sensitive points are submerged. The research provides decision-making information for early warning, personnel evacuation and flood relief of tailings pond accident.

In view of the case that the high wave wall changes from inclined to vertical near the dam slope and crest, numerical simulation and physical model tests were used to mutually verify the calculation of wave run-up. The working conditions of different wave elements and water depth in front of the dam were analyzed to study the impact of high wave walls on wave run-up in the reservoir. The results show that when the same wave factor is applied to different reservoir depths, the wave run-up shows an inverted parabolic trend with the reservoir depth; The maximum wave run-up occurs at the intersection of the vertical section of the wave wall and the slope section; When the water depth in front of the wall is higher than the intersection of the vertical section and the slope section, the wave run-up calculated by the standard method is larger compared with the results of mathematical and physical models. The finding can provide a reference for the refined design of the top elevation of high wave walls considering the impact of wave run-up in the design of earth-rockfill dam.