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1.
The main objective of this study is to investigate potential application of frequency ratio (FR), weights of evidence (WoE), and statistical index (SI) models for landslide susceptibility mapping in a part of Mazandaran Province, Iran. First, a landslide inventory map was constructed from various sources. The landslide inventory map was then randomly divided in a ratio of 70/30 for training and validation of the models, respectively. Second, 13 landslide conditioning factors including slope degree, slope aspect, altitude, plan curvature, stream power index, topographic wetness index, sediment transport index, topographic roughness index, lithology, distance from streams, faults, roads, and land use type were prepared, and the relationships between these factors and the landslide inventory map were extracted by using the mentioned models. Subsequently, the multi-class weighted factors were used to generate landslide susceptibility maps. Finally, the susceptibility maps were verified and compared using several methods including receiver operating characteristic curve with the areas under the curve (AUC), landslide density, and spatially agreed area analyses. The success rate curve showed that the AUC for FR, WoE, and SI models was 81.51, 79.43, and 81.27, respectively. The prediction rate curve demonstrated that the AUC achieved by the three models was 80.44, 77.94, and 79.55, respectively. Although the sensitivity analysis using the FR model revealed that the modeling process was sensitive to input factors, the accuracy results suggest that the three models used in this study can be effective approaches for landslide susceptibility mapping in Mazandaran Province, and the resultant susceptibility maps are trustworthy for hazard mitigation strategies.  相似文献   
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Abstract

A novel artificial intelligence approach of Bayesian Logistic Regression (BLR) and its ensembles [Random Subspace (RS), Adaboost (AB), Multiboost (MB) and Bagging] was introduced for landslide susceptibility mapping in a part of Kamyaran city in Kurdistan Province, Iran. A spatial database was generated which includes a total of 60 landslide locations and a set of conditioning factors tested by the Information Gain Ratio technique. Performance of these models was evaluated using the area under the ROC curve (AUROC) and statistical index-based methods. Results showed that the hybrid ensemble models could significantly improve the performance of the base classifier of BLR (AUROC?=?0.930). However, RS model (AUROC?=?0.975) had the highest performance in comparison to other landslide ensemble models, followed by Bagging (AUROC?=?0.972), MB (AUROC?=?0.970) and AB (AUROC?=?0.957) models, respectively.  相似文献   
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Globally, landslides cause hundreds of billions of dollars in damage and hundreds of thousands of deaths and injuries each year. A landslide susceptibility map describes areas where landslides are likely to occur in the future by correlating some of the principal factors that contribute to landslides with the past distribution of landslides. A case study is conducted in the mountainous northern Iran. In this study, a landslide susceptibility map of the study area was prepared using bivariate method with the help of the geographic information system. Area density (bivariate) method was used to weight landslide-influencing data layers. An overlay analysis is carried out by evaluating the layers obtained according to their weight and the landslide susceptibility map is produced. The study area was classified into five hazard classes: very low, low, moderate, high, and very high. The percentage distribution of landslide susceptibility degrees was calculated. It was found that about 26% of the study area is classified as very high and high hazard classes.  相似文献   
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Natural Hazards - The aim of this research is to investigate multi-criteria decision making [spatial multi-criteria evaluation (SMCE)], bivariate statistical methods [frequency ratio (FR), index of...  相似文献   
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The soil conditioner in processes of soil conservation is important especially in heavily eroded areas. Because in this study done in Educational and Research Forest Watershed of Tarbiat Modares University, north of Iran, the experiments created four treatments of control and different wood chips with rates of 0.5, 1, and 1.5 kg m?2, by rainfall simulation in rainfall intensity of 60 mm h?1, and plot scale of 1 m2 on changing ponding time, runoff coefficient, sediment concentration, and soil loss. The results showed that the average change ponding time in control treatment and wood chip treatments with rates of 0.5, 1, and 1.5 kg m?2 were 4.25, 7.48, 11.63, and 12.45 min. Also, the average change runoff coefficient in control treatment and wood chip treatments with rates of 0.5, 1, and 1.5 kg m?2 were 50.03, 26.27, 15.28, and 13.17 %. The results also indicated that the wood chips could decrease average soil loss with the rates of ?52.15, ?82.18, and ?89.35 % compared with control treatment for 0.5, 1, and 1.5 kg m?2 of wood chips, respectively. The one-way ANOVA results showed that the runoff coefficient, sediment concentration, and soil loss decreased with increasing wood chip amount, and the effect of conservation treatment was significant on study variables (R 2 = 0.99). But, the ponding time increased with increasing wood chip amount, and this effect was significant on study variables (R 2 = 0.99).  相似文献   
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Haraz River is one of the most important rivers in Iran, which has been faced with successive inappropriate land use changes and environmental degradation practices in recent decades. In this way, the impact of land use changes on stream flow generation, evaporation and hydrological processes of the Haraz basin has been studied. Land use maps for the years of 1988, 2000 and 2013 were prepared and assessed for any changes in land use using land change modeler and logistic regression methods. GEOMOD method was also used for accuracy tests of models. The calibration periods of 1988–2000, 1988–2013 and also Markov chain with hard prediction model were applied in order to predict the future land use for 2025. Besides, SWAT model was used to evaluate the watershed-scale impacts of land use change. Evaluating the calibration periods using GEOMOD method and some parameters showed a more accurate prediction for the period of 1988–2013 than the 1988–2000 period. Likewise, the results indicated that the rate of changes from 2013 to 2025 will be decreased in terms of forest and range lands (6751.05 and 168,09.01 ha, respectively) and will be increased in terms of residential areas, irrigated farming, gardens and bare lands up to 1567.2, 1405.68, 3039.38 and 174,05.55 ha, respectively. The assessment of model efficiency showed that the SWAT model has acceptable performance to simulate the flow discharge. Overall, the model outcomes indicated that land use changes lead to increase the average runoff in the study area. As a matter of fact, this issue has significant effects on water resources, economic and social situations, and hence, efficient strategies are needed for an integrated management in the Haraz basin.  相似文献   
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Nutrients are important building blocks for healthy aquatic ecosystems and are generally nontoxic; but they can change with alteration in environmental parameters. The main objective of this study was to consider the seasonal variability of NO 3 , PO 4 3– and total suspended solids (TSS) concentrations in water. The study sites, stream crossings (L30, L15) and river (R), are located in the hyrcanian forests, district 1 of Darabkola forest. The sampling was conducted in winter and spring. Water samples were taken into plastic bottles, labeled, and carried out to the laboratory for NO 3 , PO 4 3– and TSS analysis. T-test results showed that there was a seasonal change in nutrient concentrations (p < 0.05) except for NO 3 concentration at L30. Also, there was no significant seasonal change in TSS concentrations at all stations. Pearson correlation analysis did not reveal the same trend. Further analysis showed that the effect of road age on water quality parameters was statistically significant for PO 4 3– in spring and winter. Atmospheric precipitation plays vital role in nutrient loss and increasing concentration of suspended sediment. To prevent soil erosion from activities and discharge of wastes in the vicinity of river and stream an effective management should be planned and enforced.  相似文献   
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Forest soil is an important component of the natural environment, and is a primary medium for many biological activities. In this study, soil loss and displacement by excavator and bulldozer (heavy equipments) were measured on cut and fills slopes of forest roads located in Mazandaran province, lran. The volumes of soil losses were estimated by prismoidal analyses of cut and fill slopes deformation between two time treatments (under subgrading and two years later) in slope classes of 30-50% and 50-70%. Weights of soil losses were calculated by multiplying the volumes of soil losses (cm^3) to the general bulk density (1.3g/cm^3). Soil displaced area by heavy equipment was evaluated according to earth working width. Results indicated that heavy equipment has significant effect on deformation of cut slope gradient and fill slope length (p〈0.0001). During the two-year period, the cut (p〈0.0002) and fill (p〈0.0001) slope gradients were significantly deformed in different slope classes. The average soil loss by excavator and bulldozer were 160.35 t/ha·yr and 429.09 t/ha·yr, respectively. Moreover, the soil displaced area during the subgrading process by bulldozer was greater than excavator in both two slope classes (p〈0.05). Soil loss and displacement in forest roads can be rednced by applying powerful excavators in subgrading project, especially in steep terrains.  相似文献   
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Abstract

In this study, we introduced novel hybrid of evidence believe function (EBF) with logistic regression (EBF-LR) and logistic model tree (EBF-LMT) for landslide susceptibility modelling. Fourteen conditioning factors were selected, including slope aspect, elevation, slope angle, profile curvature, plan curvature, topographic wetness index (TWI), stream sediment transport index (STI), stream power index (SPI), distance to rivers, distance to faults, distance to roads, lithology, normalized difference vegetation index (NDVI), and land use. The importance of factors was assessed using correlation attribute evaluation method. Finally, the performance of three models was evaluated using the area under the curve (AUC). The validation process indicated that the EBF-LMT model acquired the highest AUC for the training (84.7%) and validation (76.5%) datasets, followed by EBF-LR and EBF models. Our result also confirmed that combination of a decision tree-logistic regression-based algorithm with a bivariate statistical model lead to enhance the prediction power of individual landslide models.  相似文献   
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