Development of priority setting process for the small stream restoration projects using multi criteria decision analysis

Abstract

This study performed a flood risk assessment using one of the multi criteria decision-making methods to identify the small stream basins with high risk of flooding and to determine the optimal small stream restoration measures by priority ranking for flood risk. The 12 representative factors for the flood risk assessment were carefully selected and constructed for the three main aspects, such as pressure factors, state factors and response factors including the government capacities under the pressure-state-response classification system for identifying the 212 small stream watersheds.The entropy weight coefficient method helps to reduce subjective judgments as well as calculate effective weighting coefficients. To evaluate the practical applications of the proposed method, the results from the preference ranking organization method for enrichment evaluation (PROMETHEE) with six preference functions are compared with the official priority ranking of flood risk assessment for the Small Stream Watershed Restoration Projects which is determined by the weighted method.Also, guidelines for the community-based restoration projects such as prevention or preparedness, sustainable development and resilient recovering have been suggested based on the three predicted priority ranking groups. It is expected that the flood risk assessment ranking ensured by full verification can help to establish optimal regional restoration plans against flooding disasters with respect to causes and characteristics of past flash flood.

Meta-Analysis and Visualization of the Literature on Early Identification of Flash Floods

“…At present, there are various sensitivity analysis methods (as shown in Figure 16), which can be generally divided into four categories: experience driven, data driven, mechanism driven, and intelligence driven. (1) Experience-driven model: It forms its own experience and understanding of the early identification of flash flood disasters based on the qualitative technology and expert knowledge, and puts forward the weight of the contribution of various factors to the occurrence of flash flood disaster, but it is limited in its range of application and low in accuracy due to its inherent subjectivity [108]. (2) Data-based flash flood object-oriented model: It relies on the analysis data to identify the relationship between independent flash flood-related variables and flash floods, mines and quantifies the correlation between flash floods and various single factors by statistical analysis methods related to spatial analysis or mathematical regression, such as information quantity, evidence weight, cluster analysis, etc., and predicts the risk of flash flood disaster through the comprehensive analysis of multiple factors.…”

“…Experience-driven model: It forms its own experience and understanding of the early identification of flash flood disasters based on the qualitative technology and expert knowledge, and puts forward the weight of the contribution of various factors to the occurrence of flash flood disaster, but it is limited in its range of application and low in accuracy due to its inherent subjectivity[108]. (2) Data-based flash flood object-oriented model: It relies on the analysis data to identify the relationship between independent flash flood-related variables and flash floods, mines and quantifies the correlation between flash floods and various single factors by statistical analysis methods related to spatial analysis or mathematical regression, such as information quantity, evidence weight, cluster analysis, etc., and predicts the risk of flash flood disaster through the comprehensive analysis of multiple factors.The data used in the data-driven model include not only maps, remote sensing images, digital databases, and other data, but also hydrological statistical data obtained or derived, as well as spatial data of basin geographical features such as geology, soil, and land utilization, all of which can be integrated into a GIS environment for sensitivity analysis and mapping[109].…”

Initial allocation of flood drainage rights based on a PSR model and entropy-based matter-element theory in the Sunan Canal, China

“…be reduced by introducing the entropy method to address the issues of order, degree and utility [42]. The steps to determine the weights were as follows [43,44].…”