Journal of Natural Disasters,2016,Vol 25,No. 01
【Abstract】 Flood and waterlogging disasters occur frequently in midstream of the Huaihe River. This paper analyzed the severity of closed floods and the encounter of the inner and outer flood in the study area. The analytical method adopted is statistical analysis based on the combination of semi-quantitative and semi-qualitative ways. Data for analysis include precipitation of the study area and flow rate and water level of the Huaihe River in 1951–2010. The analytical results showed that there were six serious flood years, which were arranged according to the severity of the closed flood from minor to major: 1956, 1968, 2007, 1991, 2003 and 1954. The sequence will provide some reference to the selection of the typical flood years in the flood control potential analysis of the flood detention areas.
Science of Surveying and Mapping,2016,Vol 41,No. 10
【Abstract】 For the problem of flood caused by rainstorm in urban areas and the requirements of emergency surveying and mapping support services for flood disasters being able to be rapidly and scientifically analyzed, a method of analyzing rainstorm flood inundation calculation based on water retention was put forward. The soil conservation service (SCS) model to calculate the regional rainfall runoff was researched to calculate and analyze regional water retention, combining with regional drainage capacity, river, lake, reservoir storage ability and the environment water; on this basis, the analysis of submerged water depth and submerged area calculation was realized using digital elevation model (DEM) data and flood inundation analysis method. It was verified by using the real case of the study area and the results showed that this method had the characteristics of scientific, timeliness and simple operability, which could meet the requirements of emergency surveying and mapping support services and could quickly provide the decision-making basis for relevant departments of flood disaster analysis.
Science of Surveying and Mapping,2017,Vol 42,No. 02
【Abstract】 Since traditional urban storm waterlogging simulation based on two-dimensional GIS cannot show the dynamic evolution of the flood disaster in three-dimensional plot, the method of rainstorm waterlogging disaster simulation based on 3D GIS was proposed. This method integrated techniques of meticulous modeling and stretching modeling, through the regional DEM construction, road surface modeling, building modeling, terrain matching to build urban three-dimensional model of the study area. The D8 algorithm was improved to carry out the catchment division, and the method of runoff coefficient was applied to carry out runoff calculation. The results showed that this method could effectively achieve the calculation of rainstorm waterlogging depth, water depth range as well as the waterlogging depth, the affected houses, the affected roads visualization in the three-dimensional scene.
Science of Surveying and Mapping,2016,Vol 41,No. 10
【Abstract】 Normally, traditional GIS uses non-source flood or source flood in fulfilling the dam-break flood process simulation. These methods ignore the physics and dynamics factors in the process of flood routing, so the simulation results of timeliness and reliability are poor, and also the effect of expression is relatively simple. Aiming at this problem, the 3D dynamic visualization and analysis of dam-break flood routing was realized combining with the smooth particle hydrodynamics (SPH) method and GIS technology in this paper. The particle data modeling and spatio-temporal modeling technology were researched based on the huge amounts of multidimensional spatio-temporal sequence of fluid particles generated by smooth particle hydrodynamics. Finally, the 3D dynamic visualization and analysis of dam-break flood routing were realized in the independent development of the system, and the application effect was good.
Acta Meteorologica Sinica,2017,Vol 75,No. 04
【Abstract】 Based on the DEM terrain data of Zhanghe reservoir in Jingmen City on Hubei Province with a spatial resolution 90 m × 90 m, twenty flood processes selected from 2012–2015 (sixteen of which were used for simulation and four were used for verification), the operational forecast of WRF model over triple-nesting domains with spatial resolutions of 3 km × 3 km, 9 km × 9 km and 27 km × 27 km in Central China was combined with results of the lumped Xin’anjiang model and the semi-distributed hydrological model, i.e. the Topmodel, in the present study for experimental prediction of flood. Results of comparative experiments were analyzed and major conclusions are given below. In the case when spatial and temporal distribution of precipitation was uniform in the basin, the lumped Xin’anjiang model could accurately forecast the peak flow and peak time; when the spatial-temporal distribution of precipitation became uneven, the forecasting error also increased. The Topmodel based on the DEM data could reflect the difference in flood forecast for precipitation with different spatial and temporal distributions. The results showed that the outputs of WRF at the 3 km × 3 km and 9 km × 9 km domains were close to each other for flood forecasting and both were better than the output at the 27 km × 27 km domain based on the deterministic coefficient and relative error of peak forecast. However, the result of 27 km × 27 km domain was good at forecasting the peak time of flood. Further analysis also found that the WRF at the three spatial resolutions could not realistically forecast the spatial and temporal distributions of precipitation, but the WRF forecast could still be accurate when the forecast error of temporal distribution offset the error of spatial distribution. Therefore, the model forecast of precipitation with high spatial and temporal resolution may not be able to yield more accurate flood forecasting results. The optimal spatial and temporal resolution for the coupled hydrological model and numerical weather forecast model needs to be determined by numerous experimental studies.
Design of economic losses evaluation information system of rainstorm waterlogging disasters in cities: evidence from Longhua New District in Shenzhen City
Journal of Natural Disasters,2017,Vol 26,No. 05
【Abstract】 An economic losses evaluation information system of rainstorm waterlogging disasters in cities is introduced. The system integrates multiple subjects such as meteorology, disaster, information science, and economics science. As a man-machine interactive system, it includes basic function, information query, data management, economic lossesevaluation, assessment report generation, user rights management and system management function modules. This system is made as the way of ‘WYSIWYG’. Direct economic losses and indirect economic losses are calculated by input-output model. Combined with the weather true information, this system can report the real-time direct and indirect economic losses of rainstorm waterlogging disasters, automatically generate defense countermeasure reports in typical waterlogged points, and provide the spatial distribution of disasters and economic loss. Finally, the system is conducive to improving the ability of disaster emergency management of government departments and reducing the economic losses from the disaster eventually.
Geomatics and Information Science of Wuhan University,2019,Vol 44,No. 01
【Abstract】 Urban waterlogging is a typical kind of urban natural disasters, which affects the quality of residents’ life. This paper takes a series of waterlogging points produced by urban rainstorm as the research objects. Comprehensively considering the influence of urban waterlogging on the work and life of residents, it screens out 21 kinds of data related to the influence degree. At the same time, based on the principle of deep learning, it constructs a stacked autoencoder neural network model. With the influence degrees of urban waterlogging points obtained by analytic hierarchy process method, the relationship between the 21 types of data and the influence degree of waterlogging points is analyzed, which will be applied to the quantitative analysis of the influence of urban waterlogging points. The experimental results show that the proposed model in this paper can describe the relationship between the spatial data and the influence degree accurately. In addition, this model can effectively predict the influence degree of potential waterlogging points, which is not only beneficial to the formulation of the urban waterlogging prevention scheme but also provides a reference for the design of urban drainage pipe network.
Journal of Natural Disasters,2019,Vol 28,No. 04
【Abstract】 There are frequent disasters in the downtown of Tianjin. It is proposed to use engineering and non-engineering methods to mitigate urban shackles. As for engineering measures, we should accelerate the construction of “sponge city” and “ecological rehabilitation and patchwork urbanism” to transform the open space from small, medium, and large scale, build urban water storage and seepage space to contain the drainage from the source, and slow down urban runoff. We should construct a perfect drainage pipe network and delimit reasonable drainage zones, improve urban drainage standards and set up one-way drainage outlets, build river gates and drainage pumping stations, and achieve rapid drainage during heavy rainfall. With respect to non-engineering measures, we should use big data and Internet technologies to build urban waterlogging prediction and service platforms, increase the forecast level of urban water accumulation points and the level of public participation, and realize the participation of all people in the city during heavy rainfall. The management also quickly controls the inflowing water points. Finally, we should rely on the construction of smart cities, strengthen the construction of a comprehensive disaster prevention platform and construct an emergency disaster prevention platform in the city by the intelligent control of various drainage facilities and departments. At the same time, we should enhance the exchange of data among different departments and draft the emergency strategies timely. In these ways, we can finally mitigate the waterlogging in the city.