Zohreh Maryanaji; Abozar Ramezani
Abstract
1- Introduction Natural hazards cause enormous damages every year. Among the natural hazards, floods, earthquakes, and droughts have special importance in financial and human losses. Meanwhile, according to the available statistics and information, floods in some parts of the world, especially in Asia ...
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1- Introduction Natural hazards cause enormous damages every year. Among the natural hazards, floods, earthquakes, and droughts have special importance in financial and human losses. Meanwhile, according to the available statistics and information, floods in some parts of the world, especially in Asia and Oceania, have the highest damage. Iran is one of the arid and semi-arid regions of the world with particular climatic conditions. Inappropriate spatiotemporal distribution of rainfall in such regions has caused devastating floods. In this study, flood vulnerable areas are identified by determining the effective parameters of flood using Shannon entropy model. The results of this study can be used in flood zoning and forecasting and planning and management of water resources in the region. 2- Materials & Methods In multi-criteria decision-making problems having and knowing the relative weights of the existing indicators is a significant step in the problem-solving process. (Relations 1 to 6). (1) Aij= (2) (3) (4) Ej= i=1,2…,m (5) wj=dj/∑dj (6) wj= Entropy method is one of the multi-criteria decision-making methods for calculating the weight of criteria. This method requires a criterion-option matrix. The steps of Shannon entropy method consist of five steps of the decision matrix, normalization of the decision matrix, calculation of the entropy of each index, the calculation of deviation, and calculation of weight value Wj. In the Shannon method using the experience and knowledge of experts appropriate factors are determined and weighed. After collecting the questionnaire data and considering the geography of the study area, the scores of each factor are adjusted. 3- Results & Discussion Natural parameters of flood occurrence in Hamadan province include: climate, snowmelt, slope, soil type, Gravilius coefficient, and vegetation. Due to the climatic characteristics of the province, most of the province's rainfall is due to the Mediterranean systems. In winter, the rains are in the form of snow, and in the early spring the melting of snows is accompanied by spring rains which most of the time causes the rivers to overflow. Due to the severe destruction of vegetation in the province, the potential of the region in flooding has been increased. In general, it can be said that the occurrence of floods in any region is due to the confrontation and alignment of human and natural factors. This study only examines the natural causes of flood. The study of the effect of each parameter in the occurrence of floods based on the data-expert method showed that the six factors studied in these studies do not have the same effect on reducing or increasing floods in the basins. 4- Conclusion Based on scoring the natural factors that cause floods, according to the intensity of their impact, the flood-prone areas of the province have been identified. Based on the combined data model and Shannon entropy, the highest weighting was given to the maximum 24-hour precipitation. Vegetation factors, snow melting time, basin slope, soil type and Gravilius coefficient were identified as the most effective natural factors in causing floods in Hamadan province, respectively. Based on the final weights, a hazard map was drawn using the GIS. According to the hazard map, the very high risk regions are located in the central and southern parts of the province. Also, the northern areas including the cities of Razan, Kaboudar Ahang and Dargazin are located in high risk area. Using the results of this study, it is possible to identify the approximate time of flood occurrence and flood-prone areas in Hamedan province.
Mojgan Entezari; Tahere Jalilian
Volume 6, Issue 18 , June 2019, , Pages 19-38
Abstract
IntroductionLandslide as a natural hazard is very dangerous especially in mountainous areas. It results in loss of human life and property around the world. In spite of the progress in identifying, measuring, predicting, and landslide warning systems, the damage caused by landslides is still increasing ...
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IntroductionLandslide as a natural hazard is very dangerous especially in mountainous areas. It results in loss of human life and property around the world. In spite of the progress in identifying, measuring, predicting, and landslide warning systems, the damage caused by landslides is still increasing worldwide. Therefore, given the importance of the problem, the most important managerial goals include favorable sustainable development in watershed and urban management, and the prediction and controlling of landslide with the aim of reducing its dangers. Indeed, many landslide damages are caused due to not observing correct principles of residential development, dam construction, and construction of roads and facilities. Consequently, the identification of the areas prone to landslide has a great importance for executive organizations. Indeed, the mentioned organizations knowing the location of these areas, they should certainly prevent structure construction in these areas as much as possible. In addition, if it is necessary, they should consider required technical tips and arrangements with more precision. According to the cost of performance, prioritizing the sub basins is very important. Decision making methods is an effective tool to deal with issues that may be created and in this context it has a lot of use. In recent years, attention to the ranking methods in environmental studies have been increased, especially in natural hazards risk management. In this paper, considering the importance and efficiency of the non-ranked ELECTRE-1 method and its non-compensatory nature, we tried to apply this method in the prioritization of landslide risk assessment in six sub-watersheds at Kermanshah province based on the factors and indicators affecting a landslide. The main objectives of the current research were: (1) identifying the main factors affecting the landslides occurrence in the study area, (2) prioritization of the watersheds based on the risk of landslide occurrences, and (3) introducing critical watersheds regarding landslide occurrence.MethodologyThis method, like other decision-making models, is applicable to choosing the best option among others. And like the TOPSIS model, it prioritizes or ranks options by various criteria. In the ELECTRE-1 method, the weight of the criteria should also be calculated for each option.Landslide risk assessment options for the study period are Mahidshat basin, Deira, Kanekabod, Tajrakbadre, Kangir basin, and Chika basin.In general, there are various indicators for assessing the factors affecting the occurrence of landslides in the basins. According to the survey of location of the study area, of various factors affecting the occurrence of landslide, lithological factors, elevation, slope, slope direction, fault density, drainage density, congestion, land use, temperature, precipitation, and slip density were selected as effective factors.-ELECTREmodelFor the first time, it was developed by Roy (1968) in a situation where real criteria and limited privileged relationships were given. Due to the complexity and high volume of computations, the algorithm of the model was programmed in EXCEL software and the values of each step were obtained. Discussion and Conclusion In this research, a multi-criteria decision-making technique was used to map areas susceptible to landslide. To do so, the factors affecting the slope sensitivity to landslide were collected. Then, to apply ELECTERE I technique to rank the sensitivity of the selected sub watersheds to the landslide, the following steps were consecutively taken. 1) The Performance matrix was created to determine the weights of the criteria. 2) The Normalization and Non-normalization matrices were formed. 3) The Harmonious and Inharmonious matrices along with the Coordinated and Uncoordinated effective matrices were obtained. 4) The final Dominance matrix was calculated. The results suggested that among the selected sub watersheds, Mahidasht Rezevand basin ranked the first having the highest vulnerability to landslide occurrence. BadraTjrk and Chika basins respectively ranked the second and the third. Deira and Kanekabod basins shared the forth rank. Finally, Kangir basin was the least likely basin to suffer from landslide incident. The susceptibility maps of the studied basins together with field surveys confirmed the proper application of ELECTRE method for ranking the sub watersheds based on landside risk. Fig 2 indicates that over 36 percent of the landslides have occurred in the high risk area. The proposed method and findings of this study are invaluable for practitioners and future academic studies.
