بیشینه شتاب زمین

Soil erosion is a natural geomorphic process. An increasing number of studies show that changes in the rate of erosion and sediment yield in watershed are often strongly correlated with seismicity. Peak ground acceleration is equal to the maximum acceleration of the ground that occurred during the shaking of the earthquake in a place. Therefore, the purpose of this study is to investigate the relationship between soil erosion and seismic activities and erosion control factors, how high erosion zones are related to the Peak ground acceleration and other factors, and to compare the efficiency of two fuzzy logic and entropy models in erosion zoning.

Talar drainage basin is located on both sides of Qaimshahr-Tehran axis. In terms of geographic coordinates, it is located between ˚52 '35 "22 to˚53 '23 "34 east longitude and ˚35 '44 "23 to ˚36 '19 "1 north latitude. For this purpose, important indices such as erosivity, erodibility, slope-length, cover management have been calculated in the RUSLE equation. Then, the zoning map of the peak ground acceleration has been used as the erosion control factor using the seismic hazard analysis method obtained in the study (Ashtari et al., 2023).

Fuzzy logic and entropy:

For the purpose of zoning, all the layers produced in the previous step were placed as base layers in fuzzy logic and entropy models. Linear function was used to quantify all layers in fuzzy logic. In order to combine the layers, the fuzzy gamma operator was used. In the entropy model, based on the map of erosion levels from specialized studies of the Talar drainage basin, the number of sample sites in each of the erosion zones is as follows: The areas of surface erosion are (16), lateral stream erosion (10), groove erosion (9), gully erosion (8), rock and rock mass erosion (6) and badland erosion (1). The steps of the entropy method are as follows: forming the decision matrix, Ej function and determining the value of entropy, calculating the degree of deviation of criteria dj, determining the weight of each criterion Wij, regional erosion risk model Hi.

Rainfall erosivity factor: This factor expresses the kinetic energy of rain when the drops hit the soil particles, and in other words, it is the intensity of precipitation and erosion resulting from the impact of rain drops on the ground during rainfall. The highest and lowest amount of this factor is respectively in the northern side of the sub-basin 3 with (369-457-8) and in the southern side of the sub-basin 1 with (13.9-102).Erodibility factor: It is in accordance with the average sensitivity factor of formations to erosion of sub-basin 1 (6.09), sub-basin 2 (6.39), sub-basin 3 (7.6). Due to the extent and variety of geological formations, there is a high potential for erosion in all 3sub-basins.length - slope: which is also known as the topography factor, is a function of the height in the basin. The lowest amount of this factor is in the areas of valleys and river streams (>6) and the highest amount corresponds to slopes and heights (>23).cover management: Vegetation factor represents the amount of vegetation waste in different uses. The lower the amount of c, the more vegetation in the area. The highest coefficient c (0.5-0.6) is in sub-basin 1, which indicates the decrease of vegetationand the potential for erosion, and the lowest c (0.2-0.3) in sub-basin 3, which indicates the richness of land uses from forest vegetation.Peak ground acceleration factor: The highest amount of ground acceleration is near the active faults in the region. Due to the structure of the faults, which have an east-west trend, in all 3 sub-basins there are areas of maximum ground acceleration during each event. The highest areas of ground acceleration levels (0.5-0.6) are sub-basin 1 and the lowest are sub-basin 3, which is due to the structure of active faults such as Firuzukuh fault, IRQ112 and IRQ357.

The highest area is in the very low class (839 km2 and 39.9 %) and the lowest area is in the low class (162.9 km2 and 7.7 %). The largest expansion of the mentioned areas is located in sub-basin 1. The distribution of high and very high-risk areas especially in sub-basin 2 and the low coverage of these areas in sub-basin 1 do not match with the relative contribution of high sediment production in sub-basin 1 based on studies.Erosion zonation map by entropy methodThe results of the entropy model showed that the erodibility factor was 20.62%, the peak ground acceleration factor was 20.20%, the cover management was 20%, the erosivity factor was 19.60%, and the slope-length factor was 19.58% in the occurrence of erosion in the region. The area of very high risk with 13.5% of the area of the basin includes erosional facies containing surface, groove, gully and lateral stream. In general, it can be said that the highest erosion risk zones are not related to the highest weighting of the layers, but the placement of a set of factors influencing the occurrence of erosion, which shows the highest amount of erosion.

The peak ground acceleration has a direct impact on the control of sediment yield and erosion processes. The placement of a small part of the IRQ112 fault has caused the extent of ground acceleration levels (0.5-0.6) to be less in sub-basin 3 and more in sub-basin 1 due to the placement of 3 faults, Firuzukuh, IRQ112 and IRQ357. The placement of erodible formations in the ranges of peak ground acceleration has caused the process of sediment production and erosion to accelerate. The coordination of the erosion occurrence zones with the ground acceleration levels is due to the regionality of the entropy model in contrast to the fuzzy model.

One of the main issues in drainage watersheds is erosion and sediment yield. Lack of proper management in this field can be environmental hazards and even a threat to human life. The purpose of this study is fingerprinting the sources of sediment yield in sub-basins 1 and 2 of Talar drainage basin in Mazandaran province.140 soil samples in first approach and 80 samples in second approach collected respectively sub-basin 1 (77) and (47), sub-basin 2 (63) and (33) of lithological units and range of peak ground acceleration and 20 drape sediment samples at the outlet sub-basins and 28 geochemical elements measured as tracers in the samples. Using the Kruskal-Wallis test and discriminant function analysis, the composite fingerprints was determined. The largest relative contribution of sediment yield based on the Bayesian un-mixing model is in the first approach (sub-basin 1 unit sandstone and conglomerate with 59.1%, sub-basin 2 unit marl and shale with 47.2%), in the second approach (sub-basin 1 unit the range of peak ground acceleration at the level (0.51-0.6) g with 50.3%, and sub basin 2 units channel bank with 64.6%). The results of this study showed that the range of peak ground acceleration have a direct effect on control of sediment yield and erosion processes. Also, division of lithological groups as sources sediment yield based on range of peak ground acceleration, which have a great impact on sediment yield, as a new approach, can be of great help in understanding sediment yield processes.

Considering devastating events like the 2003 Bam earthquake (M_w~6.6), it is essential to develop up-to-date earthquake hazard maps to design structures in this area. In this study, a seismic catalog including historical and instrumental events was compiled and then 21 seismic sources were identified in Kerman province and its surrounding. Seismicity parameters were estimated for all 21 source zones and an attenuation relationship was selected to obtain local site effect-based seismic hazard maps. Finally, seismic hazard maps, which is one of the basic requirements of seismic design and seismic regulations, were presented in form of the peak ground acceleration (PGA) measures for the return period of 475 and 2475 years, and the high risk areas in Kerman Province were introduced. To investigate the depth of events on Iranian plateau, according to the studies conducted in this study, it is suggested to use only the data obtained from local seismic networks. The results were presented as seismic hazard maps for the parameters of maximum intensity of horizontal ground acceleration, taking into account construction effects with a probability of 2% and 10% over 50 years for all parts of Kerman province to provide all design needs according to 2800 regulations. Using the obtained maps, the earthquake parameter in the Iranian Seismic Code (Code 2800) can be updated. Results showed that, as expected, two areas in Kerman province are with the highest accelerations: The first is the Kuhbanan-Golbaf-Bam fault systems with a northwest-southeast trend and the second is the northeast termination of Zagros toward Makran. Both of these ranges are seismic and of great importance in seismic surveys. These areas include Kuhbanan-Golbaf-Bam fault systems and Jiroft-Kahnooj.

In this research, the prediction of Peak Ground Acceleration (PGA) is investigated through training the Adaptive Neuro Fuzzy Inference System (ANFIS) network using data partitioned into inlier and outlier groups. The partitioning procedure is based on an automated method which uses K Nearest Neighbor (KNN) search and Local Linear Model Tree (LOLIMOT) methods. The mentioned proved to enhance the prediction procedure at least 36 percent with respect to normal training mode with no data partitioning. Hereafter, a PGA catalogue reported by the Iranian ground acceleration network with 1571 records was used and the trained network was used for predicting the PGA map around the Mormori, 2014 earthquake epicenter. We used spatial information of the epicenter and the site, earthquake magnitude, Vs30, depth of the hypocenters and the epicentral distance foe the sites. The resulted map adapts well to the official report of the mentioned earthquake for the PGA analysis published by the International Institute of Earthquake Engineering and Seismology (IIEES). Finally, it is concluded that using machine learning algorithms could be beneficial in the cases where adequate data-sets are not provided by the seismological networks specifically in the concept of the strong ground motion analysis.

WARED system is Internet-based software that automatically receives the seismic information from Iran seismic center (ISC) every 10 seconds. The information is processed in a few seconds and damage assessment maps of various parts of the city (such as buildings, hospitals, bridges, etc.) become available, in layered format, to rescue groups through system site. WARED system based on the population exposed to each Peak Ground Acceleration (PGA) level, it estimates the losses from earthquakes in residential areas. This system was implemented in the municipality of Mashhad (North East of Iran) in January 2014. Principles of information processing in this system depend on three main factors including the magnitude and location of earthquakes, the properties of the rocks and sediment the earthquake waves travel through, and the technical characteristics of the buildings (strength, age, type, and geotechnical conditions of soil, etc.). Therefore PGA is used as the most important parameter to assess the damages and fatality occurred. Primary purpose of WARED system is rapid dissemination of earthquake impact assessments for decision-making purposes. This is motivated by the idea that an estimated range of damage and number of deaths will aid in decisions regarding humanitarian response.

Khark Island is located in the southern margin of the Zagros folded belt in the northeast of the Arabian plate. This study is focused on active geological characteristics of the area understudy, where there is defined 11 seismogenic zones. The seismicity parameters are assessed for these zones based on seismicity characteristics, as well as the return period of the earthquakes. Using the reliable attenuation relationships, the seismic hazard zoning maps are developed in which the PGA of 0.36 is found for the 475 years return period.