Flood Risk Analysis and Flood Potential Losses Assessment

The heavy floods in the Taihu Basin showed increasing trend in recent years. In this work, a typical area in the northern Taihu Basin was selected for flood risk analysis and potential flood losses assessment. Human activities have strong impact on the study area’s flood situation (as affected by the polders built, deforestation, population increase, urbanization, etc.), and have made water level higher, flood duration shorter, and flood peaks sharper. Five years of different flood return periods [(1970), 5 (1962), 10 (1987), 20 (1954), 50 (1991)] were used to calculate the potential flood risk area and its losses. The potential flood risk map, economic losses, and flood-impacted population were also calculated. The study’s main conclusions are: 1) Human activities have strongly changed the natural flood situation in the study area, increasing runoff and flooding; 2) The flood risk area is closely related with the precipitation center; 3) Polder construction has successfully protected land from flood, shortened the flood duration, and elevated water level in rivers outside the polders; 4) Economic and social development have caused flood losses to increase in recent years.

Rapid assessment of flood loss based on neural network ensemble

Considering the defects of low accuracy and slow speed existing in traditional flood loss assessment, firstly, the technical route of flood loss assessment was presented based on the neural network ensemble. Secondly, through the study of certain country of Poyang Lake district, the flood loss assessment indicators of the test area were analyzed and extracted by utilizing analytic hierarchy process (AHP), and the weights of the impact factors were assigned. Subsequently, the approaches to generate individuals and conclusions of neural network ensemble model were also investigated. In the platform of C# language and neural network library under AForge.NET open source, a flood loss assessment program which could rapidly build neural network ensemble models was developed. Finally, the proposed method was tested and verified. The comparison results between the assessment results of the proposed method and the actual statistical flood loss proved the feasibility of this method, thus a new approach for flood loss assessment was provided.

A High Precision Comprehensive Evaluation Method for Flood Disaster Loss Based on Improved Genetic Programming

Precise comprehensive evaluation of flood disaster loss is significant for the prevention and mitigation of flood disasters. Here, one of the difficulties involved is how to establish a model capable of describing the complex relation between the input and output data of the system of flood disaster loss. Genetic programming (GP) solves problems by using ideas from genetic algorithm and generates computer programs automatically. In this study a new method named the evaluation of the grade of flood disaster loss (EGFD) on the basis of improved genetic programming (IGP) is presented (IGP-EGFD). The flood disaster area and the direct economic loss are taken as the evaluation indexes of flood disaster loss. Obviously that the larger the evaluation index value, the larger the corresponding value of the grade of flood disaster loss is. Consequently the IGP code is designed to make the value of the grade of flood disaster be an increasing function of the index value. The result of the application of the IGP-EGFD model to Henan Province shows that a good function expression can be obtained within a bigger searched function space; and the model is of high precision and considerable practical significance. Thus, IGP-EGFD can be widely used in automatic modeling and other evaluation systems.