نشریه جغرافیا و مخاطرات محیطی
پیاپی 44 (زمستان 1401)

One of the dangers in many areas in recent years is subsidence. Landslides are less harmful than other hazards and its adverse consequences will directly affect human, industrial, agricultural, and civil development. The importance of paying attention to this issue is that the most harmful side effects are irreparable. Scientometric research have provided a comprehensive understanding of global research on the subject. Data were obtained from the Scopus Scientific Database (1965-2022). Most of the scientific research on land subsidence has been on the United States and China. The most important aggravating factors for the occurrence of hazards include the exploitation of groundwater and mineral extraction, which has been emphasized in most studies. On the other hand, the use of scientific technologies over the past years has become more widespread in landslide research. Now it is used more to predict the risk. Most research on the risk of land subsidence has focused on the use of methods and models, but its impacts on different aspects of human life have not been considered. The results of this research can help reduce and manage the negative consequences of land subsidence.

Global climate changes and population growth have increased the need to exploit underground water resources. The phenomenon of land subsidence as a result of groundwater extraction and water depletion is one of the environmental hazards that threatens societies all over the world. In this research, for the first time, Sentinel-1 radar satellite images were used by the SNAP2StaMPS to automate the process of processing and analyzing the subsidence in Marand Plain. In recent years, the uneven development of agricultural lands and the excessive extraction of underground water in the Marand plain in East Azerbaijan province have caused landslides on the surface of this plain. In this study, an automatic interferometric processing algorithm between SNAP and StaMPS was used to determine the displacement rate in the direction of the satellite line of sight. The results of the PSI interferometry technique were performed on 133 images of the Sentinel-1 satellite in the descending orbit of the Sentinel-1 satellite. Based on the obtained results, the annual land displacement rate for Marand plain in 2016, 2017, 2018, 2019, and 2020 was -13.7, -12, -2.15, -12.3 and -13.1 cm respectively. In order to validate the results, the amount of subsidence resulting from the interferometric processing was compared with the amount of groundwater level drop in the study area, using the unit hydrograph analysis method. The results showed that the amount of water level drop and the results of hydrograph analysis of observation wells in the region are consistent with the results of time series maps obtained from interferometry. Therefore, the automatic method presented in this study can be used for monitoring land subsidence.

One of the dangers facing Iran’s plains is subsidence. Land subsidence due to various reasons, such as over-harvesting of underground water sources and climate changes, has caused many problems in agricultural lands, roads, and power and energy transmission lines. Therefore, it is important to deal with the causes and influencing factors to control the risks. Ardabil plain is also one of the areas prone to subsidence due to climate changes and the decrease of underground water in recent years. The aim of the present research is the zoning subsidence risk in this plain. First, the factors influencing subsidence in the Ardabil plain (slope, land use, lithology, distance from the fault, distance from the waterway, drop in water level, distance from the city and the village) were identified. Then the layers of data were applied in the geographic information system. In the next stage, the weighting of the investigated factors was done using ANP method and in the Super Decision software, and the final analysis and modeling were done using the MABAC method as one of the multi-criteria decision making methods. Finally, the resulting map was classified into five categories from very low risk to very high risk. The results showed that such factors as water level drop, distance from the river and lithology have the highest weighting factor. Moreover, 244.29 and 370.59 square kilometers, respectively, of the area of this plain, are in very dangerous and dangerous classes. Finally, due to the high potential of Ardabil plain in terms of subsidence, protective and management measures should be taken into consideration by relevant authorities and institutions.

Land subsidence is one of the most important environmental problems that affects agriculture and urban infrastructure. In order to plan for mitigating the damages caused by land subsidence, it is necessary to identify high-risk and prone areas for this phenomenon specially in different plains of Iran. The main purpose of this research was zoning the land subsidence in Kashan aquifer using Dempster-Schafer, Weight of Evidence, Shannon Entropy, and Frequency Ratio. To conduct this research, 14 factors affecting the occurrence of subsidence including elevation, slope, slope direction, surface curvature, distance from stream, distance from fault, distance from road, lithology, land use, longitudinal and transverse curvature, water table changes, distance from mining and well density in aquifer surface were used. Then, determining 108 subsidence positions and 108 non-subsidence positions at the aquifer level, these points were randomly classified as 30% and 70% as validation data and test data, respectively. To evaluate each of the models, the ROC curve was used. The results showed that among the used methods based on the ROC curve and the amount of AUC, the Frequency Ratio method (training: 0.84 and validation: 0.89) performed best and is introduced as the best method for predicting areas with subsidence sensitivity in studied area. Shannon Entropy, Dempster-Schafer and Weight of Evidence were also ranked next, respectively. The results of this study can be used by provincial managers to reduce the damage caused by land subsidence and to determine areas with subsidence sensitivity.

Land subsidence is one of the most important geomorphic hazards that has a slow motion but destructive effects in the long run. For the spatial analysis of the amount of displacement, the data on changes of the ground surface from Sentinel A1 for a period of 3 years (2017-2020) through the radar interferometric method and SNAP software were used. Field observations were also made to evaluate the research results. The results showed that the rate of land subsidence has increased from 2017 to 2020, from 2.6 cm in 2017 to 7.8 cm in 2020. Moreover, the groundwater hydrograph in the central plain of Ghaen has significantly decreased, so that the rate of water level drop in the plain level has been about 1.30 meters during 5 years (from 2014 to March 2020), i.e, about 26 cm per year. In addition, the analysis of spatial autocorrelation and Moran index (0.984) confirmed the clustering of subsidence event under the influence of water level changes in the study area. The correlation results also showed that there was a small correlation between the factor “changes in water level” and “land subsidence rate” (p = -0.138), which is an indirect relationship, i.e., the higher the groundwater abstraction (or the lower the water level), the higher the amount of subsidence. But due to the level of significance (sig = 0.585) this relationship is not significant.

The occurrence of land subsidence phenomenon and its potential hazards in the plains of Iran due to the water crisis and drought period has grown significantly in recent years. In this study, the zoning of land subsidence hazard in the Hashtgerd plain was discussed and 19 criteria were selected as factors that influence the subsidence. The mentioned layers were prepared in GIS, weighted based on the best-worst method (BWM) and integrated using the Weighted Overlay Index (WOI). The results of BWM method showed that groundwater abstraction (0.219), the type of geological formation (0.157), the decrease of groundwater level (0.079), and groundwater depth (0.078) are important factors on the potential of subsidence hazard in the study area. Moreover, in order to evaluate the results of this model, the ROC curve was used, which has an accuracy of 90%. The results showed that land subsidence hazard of 10.66% of the study area was in very low category, 38.51% in low category, 31.49% in medium category, 11.66% in high category and 7.69% is in the very high category. According to the results, there are areas with a high probability of subsidence in the central part of Hashtgerd Plain, which requires continuous evaluation, controling, and monitoring of the criteria that affect the situation.

Among the risks facing the plains in Iran is subsidence, which causes many problems in agricultural lands, roads, power, and energy transmission lines. In recent years, Sarab plain has faced a sharp drop in the level of underground water, which has caused this area to be exposed to the risk of subsidence. Therefore, the purpose of this research is to investigate and analyze the most important factors involved in creating the risk of subsidence in Sarab plain and to identify the susceptible surfaces that are likely to be involved in subsidence in the future, using the multi-criteria MARCOS and CODAS algorithms. According to the results of subsidence risk zoning, water depth, land use, and slope, respectively, with weight coefficients of 0.194, 0.171, and 0.159, are the most important factors involved in creating the risk of subsidence in the studied area. The output of the MARCOS method showed that, respectively, 167.50 and 276.09 square kilometers of the area of Sarab Plain, and results of applying the CODAS method, showed that 187.13 and 279.03 square kilometers of the area are in the high-risk and critical category. In addition, the map extracted from the MARCOS and CODAS algorithms with the depth of the water level of the wells, respectively, have correlation coefficient values of 0.77 and 0.81. A correlation can be seen between the output of both methods with the water level map. It seems that the results of this study can be of great help to organizational managers and land and soil resource planners for protecting and managing water resources and natural hazards and preventing land degradation.

Land subsidence induced by soil consolidation is one of the natural hazards that occur gradually. This phenomenon has reached its critical state in most regions of Iran. Factors affecting subsidence are groundwater level depletion, land cover, soil type, elevation, slops gradient, rock bed depth, etc. The causes of subsidence should be investigated so that decisions could be based on the real characteristics of the region. Decrease in groundwater level is one of the most important factors that influences subsidence but due to the complexity of the relationship between subsidence and other factors, a direct linear relationship between groundwater level and subsidence cannot be considered. The study aimed to investigate the relationship between subsidence and groundwater changes through relationship between the two parameters in the period 2014 to 2018 in Isfahan. In this regard, the time series of radar interferometry and the time series of water levels of piezometric wells in the Isfahan were studied. The results show that in 12% of the wells, no correlation exists, in 9%, poor positive ignorable correlation, in 12%, fair positive correlation, in 48%, significant positive correlation, in 6%, poor negative ignorable correlation, in 4% fair negative correlation and in 9% there is a strong and negative significant correlation between the subsidence rate and the groundwater level. Correlation values show the complexity of the relationship between subsidence and water level depletion. Therefore, the relationship between subsidence and its causative factors requires more detailed studies and comprehensive models.

Due to the uncontrolled abstraction of groundwater resources in the last half century, the water level of groundwater aquifers in most plains of Iran has decreased sharply. Sharp drop in groundwater levels is the main cause of land subsidence in Iran. Land subsidence has the potential to cause a major human catastrophe, and if it happens, it will expose agricultural lands, urban fabric, vital arteries, and many other environmental aspects to extreme vulnerability. This study evaluated the vulnerability of urban fabric in District 18 of Tehran regarding the influence of land subsidence. The spatial study was carried out by implementing an analytical model in three steps. In the first step, the indicators of vulnerability of urban tissue affected by land subsidence were identified and classifiedbased based on three criteria of physical and demographic, access and proximity to high risk centers. In the second step, using a questionnaire and expert’s ideas, the priorities of urban tissue vulnerability in relation to land subsidence were identified and based on the network analysis process, the weight of each criterion was determined. In the third step, the weight obtained from the ANP model was applied to the spatial layers of the region in ArcGIS software. The results of model implementation showed that a high percentage of District 18 have features such as worn texture, buildings with low structural strength, very low building quality, high population and construction density and are prone to high vulnerability. Moreover, Zone 1 with 96%, Zone 2 with 88.5%, Zone 3 with 90.4%, Zone 4 with 85%, and Zone 5 with 92.3% have high vulnerability. About 90% of the total buildings constructed in District 18 of Tehran are affected by land subsidence in a highly vulnerable area.

The risk of subsidence in recent years has posed serious challenges to many cities, including cities in arid and semi-arid regions of Iran. Hamedan is one of the cities that are exposed to this risk and for this reason, this study evaluated the subsidence in the city. The data included Sentinel 1 radar images, Landsat satellite images, 30 m SRTM digital model and groundwater data. Tools also included ArcGIS, GMT, and ENVI. In the first stage, land use maps of the region for the period 1991-2020 were prepared and analyzed. In the second stage, the situation of groundwater depletion in the study area was explored, and in the third stage, using radar images and SBAS time series method, the amount of subsidence in the area over a three-year period (2017 to 2020) was calculated. The results showed that the urban area and suburbs of Hamedan annually experience one meter drop in water resources and 0.7 Square kilometers of physical development. Moreover, the subsidence rate of this area during the three-year period was between 6 to 98 mm. According to the final map, the rate in western areas of Hamadan was between 60 to 98 mm, in central areas was between 30 to 60 mm, and in a big part the city subsidence is 6 to 30 mm from its eastern regions. Considering that the highest rate of physical development of Hamedan city in recent years has been in the western suburbs of the city, it can be said that the physical development along with the decline of groundwater resources are the main factors of subsidence in this city.