Evaluation of efficiency of landslide hazard zoning models of Kurdistan dam watershed

During the last two decades, Landslide susceptibility mapping is very important for landslide hazard assessment and has become an effective method (Zhao et al. 2016 and 2015). So that now the results of landslides prepared for landslide management and mitigation are widely used in the world. Ildoromi et al. (2017) by examining the effective factors and landslide hazard zoning using surface density model, hierarchical analysis (AHP) and logistic regression in Ashvand watershed showed that regression logistic and AHP models are suitable models of land hazard zoning Slips are in the area. Bravo et al. (2019) in assessing landslides using sensitivity models and comparing them in the western continent, India, by measuring the cameras had that landslides in the region under the influence of a set of conditions and factors such as altitude, slope, lithology, And geomorphology occurs, etc. In addition to external factors, precipitation, tectonics and human activity are also very effective on the frequency of landslides. The purpose of this study is to evaluate the statistical models of landslide hazard zoning in the watershed of Kurdistan Dam.

Kurdistan Dam watershed with an area of 120.15 Km2 is located in the northeast of Saqez city.
In this study, after determining the study area, 9 landslides occurred, location and landslide distribution map were prepared. In the next step, the factors affecting the landslide occurrence in the region, including geology, precipitation, land use, distance from the river, distance from the fault, slope, altitude were identified and then a map of these factors was prepared to prepare their information provinces. Then, by scoring the effective factors, and using each of the statistical models of information value, surface density, frequency ratio and LNRF, the final landslide hazard zoning map by 10.2 software, Arc / map and Arc / GIS10 3. Prepared in the Kurdistan Dam watershed. Also, in order to evaluate the accuracy and comparative comparison for landslide hazard prediction in the basin in the models, three criteria, landslide index, accuracy of predicted results and compression ratio have been used and the most suitable model for the watershed has been introduced and selected .

Based on the computational results using evaluation indicators and comparison of landslide hazard assessment models in the watershed of Kurdistan Dam, it is inferred that in the information value model, the value of Li index is 72.32, in level 30 density, LNRF 81.65 and At a frequency ratio of 49.4%, the basin is in the high hazard category. The results of the total quality of Qs in the models also show that LNRF models have presented the frequency ratio, surface density and correct information value or seismic hazard segregation in the watershed of Kurdistan Dam with differences. So that information value and LNRF models with values of 2.41 and 2.89, respectively, have better and more accurate performance in landslide hazard zoning of the basin than frequency ratio models with value of 0.304 and surface density with 1.11. The results of compaction of density ratio values show that LNRF models and information value in the separation between hazard categories with density ratio index, respectively, have the highest desirability and accuracy compared to frequency ratio models and surface density in terms of methods used in the basin. In general, the results of P index study show that among the models used in this study, information value models with a P value of 0.81 and in the LNRF of 0.89 are appropriate models in accordance with the study area. And surface density and frequency ratio models are less accurate.

Currently, few studies have been conducted on the use of comparative methods in relation to landslide assessment and zoning and increasing the accuracy of landslide hazard maps. In this study, using statistical models of frequency ratio, information value, surface density and LNRF, final landslide hazard zoning maps in Kurdistan dam basin were prepared and the accuracy of the models, with landslide index, accuracy of predicted results and ratio Compression was assessed. The results of field studies and analysis of basin zoning maps show that statistical models show that a significant percentage of the basin area is in the high hazard category.The results of evaluation and comparison of landslide hazard assessment models using indicators show the upward trend of all models and especially the upward trend of compression ratio index indicates better separation of hazard classes in information value models and LNRF compared to surface density models and The ratio is abundant. One of the reasons is the adaptation of geological, geomorphological and climatic characteristics of Kurdistan dam basin with effective factors in statistical models of information value and LNRF compared to surface density models and frequency ratio. In general, the results of P index study show that among the models used in this study, information value models with a P value of 0.81 and in the LNRF of 0.89 are appropriate models in accordance with the study area. Due to the complex and nonlinear behavior of the variables involved in landslides in the study area, it is recommended to use geomorphometric indicators such as the effect of curvature, cross-curvature, surface curvature and Gaussian and tectonic curvature to complete the results of these studies.dunes. The stability model was involving the input and output of energy and material in the barchan system that eventually is formed a flow structure. This structure is representing the stability and equilibrium of barchan system in time. Also, the obtained results from investigation of steady state index show the barchan dunes, with annual displacement rate more than 12 meters, have the maximum number and highest rates of displacement, and have the lowest steady state. Thus this group is demanding the more attention and planning requirements for stabilization of quicksand and environmental management of mobile barchan dunes.