Rudraprayag in Garhwal Himalayan division is one of the most vulnerable districts to landslides in India. Heavy rainfall, steep slope and developmental activities are important factors for the occurrence of landslides...Rudraprayag in Garhwal Himalayan division is one of the most vulnerable districts to landslides in India. Heavy rainfall, steep slope and developmental activities are important factors for the occurrence of landslides in the district. Therefore, specific assessment of landslide susceptibility and its accuracy at regional level is essential for disaster management and proper land use planning. The article evaluates effectiveness of frequency ratio, fuzzy logic and logistic regression models for assessing landslide susceptibility in Rudraprayag district of Uttarakhand state, India. A landslide inventory map was prepared and verified by field data. Fourteen landslide parameters and generated inventory map were utilized to prepare landslide susceptibility maps through frequency ratio, fuzzy logic and logistic regression models. Landslide susceptibility maps generated through these models were classified into very high, high, medium, low and very low categories using natural breaks classification. Receiver operating characteristics(ROC) curve, spatially agreed area approach and seed cell area index(SCAI) method were used to validate the landslide models. Validation results revealed that fuzzy logic model was found to be more effective in assessing landslide susceptibility in the study area. The landslide susceptibility map generated through fuzzy logic model can be best utilized for landslide disaster management and effective land use planning.展开更多
An improvement was proposed for the statistical theory of breaking erttrainment depth and surface whitecap coverage of real sea waves in this study. The ratio of the kinetic and potential energy was estimated on a the...An improvement was proposed for the statistical theory of breaking erttrainment depth and surface whitecap coverage of real sea waves in this study. The ratio of the kinetic and potential energy was estimated on a theoretical level, and optimal constants were determined to improve the statistical theory model for wave breaking. We also performed a sensitivity test to the model constants. A comparison between the model and in situ observations indicated that the level of agreement was better than has been achieved in previous studies.展开更多
文摘Rudraprayag in Garhwal Himalayan division is one of the most vulnerable districts to landslides in India. Heavy rainfall, steep slope and developmental activities are important factors for the occurrence of landslides in the district. Therefore, specific assessment of landslide susceptibility and its accuracy at regional level is essential for disaster management and proper land use planning. The article evaluates effectiveness of frequency ratio, fuzzy logic and logistic regression models for assessing landslide susceptibility in Rudraprayag district of Uttarakhand state, India. A landslide inventory map was prepared and verified by field data. Fourteen landslide parameters and generated inventory map were utilized to prepare landslide susceptibility maps through frequency ratio, fuzzy logic and logistic regression models. Landslide susceptibility maps generated through these models were classified into very high, high, medium, low and very low categories using natural breaks classification. Receiver operating characteristics(ROC) curve, spatially agreed area approach and seed cell area index(SCAI) method were used to validate the landslide models. Validation results revealed that fuzzy logic model was found to be more effective in assessing landslide susceptibility in the study area. The landslide susceptibility map generated through fuzzy logic model can be best utilized for landslide disaster management and effective land use planning.
基金supported by the National High Technology Research and Development Program of China(Grant No.2013AA09A506)the National Natural Science Foundation of ChinaShandong Joint Fund for Marine Science Research Centers(Grant No. U1406404)+2 种基金the Youth Natural Foundation of Shandong Province(Grant No.ZR2015PD009)the Scientific and Technological Innovation Project Financially Supported by Qingdao National Laboratory for Marine Science and Technology(Grant No.2015ASKJ01)the Youth Science Foundation of China-Indonesia Maritime Cooperation Fund(Grant No. YZ0115005)
文摘An improvement was proposed for the statistical theory of breaking erttrainment depth and surface whitecap coverage of real sea waves in this study. The ratio of the kinetic and potential energy was estimated on a theoretical level, and optimal constants were determined to improve the statistical theory model for wave breaking. We also performed a sensitivity test to the model constants. A comparison between the model and in situ observations indicated that the level of agreement was better than has been achieved in previous studies.
