JWSS - Journal of Water and Soil Science

Modeling of Kaboodval Dam using Plaxis software has been used for the Mouher-Columb behavior model. The effect of two continuities of embankment and watering operations on the meeting was considered. The body structure of the dam was increased from the side of the faces to the middle sections, and the maximum seating was recorded at 25-25 and at about 2200 mm. By examining at different intervals, the largest meeting was in the range of 180 to 185. That is, the level of the embankment was found to be critical in these numbers. Most concerns were regarding the middle of the dam, which had a weaker position. According to the analysis of different parts of Kaboudvall Dam, the materials forming the right wing of the dam in the middle and left wings of the dam were better. In the case of the 19th Module, besides the Mouher-Columb model, the dam could be modeled with hardening and hardening models. Here, the hardening model created a better fit. The hardening model, as it could get more data from the soil, is likely to better model the behavior of the soil dams. Due to the fact that, during the construction, the first sessions usually occur, the hardening model can have a better performance.

Land subsidence as a hydrogeomorphology event is currently occurring dangerously in many plains of the country due to uncontrolled groundwater extraction from water bearing layers, and accordingly monitoring and studying this phenomenon seems to be necessary. In this study, land subsidence rate of the Najafabad aquifer was determined through the Differential Radar Interferometry (DInSAR) processing of the ASAR and PALSAR radar data and the results were validated by comparying with the differential leveling and groundwater level drowdown data. Processing of the ASAR sensor data estimates the land subsidence in the Najafabad plain at an average annual subsidence rate of 6.7 cm and a total of 41 cm during 6 years period and processing of the PALSAR data suggests an annual rate of 7.7 cm and total subsidence of 30 cm during 4 years period. Most of the occured displacements are related to the Tiranchi, Koushk, Ghahderijan, Goldasht and Falavarjan cities. The simultaneous groundwater level data with acquisition date of the radar satellite images between 2002 and 2014 shows a drawdown ranging from 0.5 to 46.5 meters in the south and east to north of the Najafabad city consistent with the estimated land subsidence areas.The DInSAR processing of the PALSAR data has led to a more accurate results with higher spatial resolution. Results of the radar data processing can be employed for the hazard zonation directly utilized for management and planning of control and preventive measures.

In the future, the risk of land subsidence due to water resources shortage crisis and improper water resources management will become more and more dangerous. It is necessary to assess and identify areas susceptible to subsidence risk and take necessary actions to reduce risks related to land subsidence. In this study, first, the risk of land subsidence was identified and evaluated using a radar interferometry method called LiCSBAS. Then, the spatial relationship between the occurrence of land subsidence hazard and effective factors such as ground elevation, slope, slope aspect, lithology, land use, groundwater decline, distance from rivers, distance from faults, topographic moisture index, and arc curvature was investigated using the random forest (RF) model. In the end, the land subsidence hazard sensitivity map was prepared after calibrating the random forest algorithm. The analysis of LiCSBAS interferometric time series data from 2015 to 2022 showed that the center of the Marvdasht-Kharameh plain and adjacent agricultural areas are continuously subsiding and the mean deformation rate map showed a subsidence rate of 11.6 centimeters per year. The results of determining the spatial relationship between subsidence occurrence and effective factors confirmed the positive impact of distance from rivers, urban and agricultural land uses, depth of bedrock (aquifer thickness), groundwater decline, and alluvial and fine-grained formations on this phenomenon. Also, the results of subsidence modeling using the random forest algorithm showed that factors such as bedrock depth, groundwater decline, land use, and geology have the greatest impact on the potential for subsidence occurrence in the study area. Also, based on the results, about 3 to 4 percent of the areas are in the very high and extremely high-risk classes of land subsidence, especially in the center and suburbs of Mervdasht. Therefore, water resources management and control and developing a systematic program to reduce subsidence risk and aquifer recharge conservation in Merudasht-Kharameh Plain is essential.