Assessment of Land Subsidence Induced by Groundwater Level Decline and Land. Use Changes in the Mahidasht Plain, Kermanshah

Land subsidence has become a critical geomorphological hazard in many arid and semi-arid regions of Iran, where intensive groundwater extraction and rapid land-use transitions have accelerated ground deformation. This study examines the spatial–temporal dynamics of subsidence in the Mahidasht Plain of Kermanshah Province by integrating SBAS-InSAR time-series analysis, long-term piezometric records, and multi-temporal Landsat-based land-use classifications. Thirty Sentinel-1 SLC images (2022–2024) were processed using SNAP and SARscape to derive vertical displacement rates, while groundwater-level variations from 21 piezometric wells (2001–2023) were interpolated using the Inverse Distance Weighting (IDW) method. Land-use maps for 2001 and 2023 were generated through artificial neural network classification to evaluate the impact of agricultural transformation on subsidence patterns. Results indicate substantial deformation, ranging from +22 mm of uplift to −40 mm of annual subsidence, with the most severe rates concentrated in the eastern and northern sectors of the plain. These hotspots coincide with significant groundwater decline (up to −26.98 m) and extensive conversion of rain-fed agriculture to irrigated farming. The spatial overlap among subsidence zones, declining water tables, and intensified land-use changes confirms the dominant influence of anthropogenic pressures on ground deformation. In contrast, central and western areas exhibit lower deformation rates due to more stable groundwater conditions and limited land-use alteration. Overall, the findings reveal an escalating subsidence crisis driven primarily by unsustainable groundwater exploitation and agricultural expansion. If current trends continue, they may threaten soil stability, water quality, infrastructure integrity, and regional food security. This study underscores the urgent need for sustainable groundwater management, reduction of high-water-demand crops, and stricter land-use regulations to mitigate future risks effectively.
Introduction
Land subsidence has become an increasingly critical geomorphological hazard in many arid and semi‑arid regions of Iran, where rapid agricultural intensification, groundwater over‑extraction, and climate‑driven water scarcity have accelerated ground deformation. The Mahidasht Plain in Kermanshah Province is one of the regions most severely affected by this phenomenon. Subsidence in such environments typically results from the compaction of unconsolidated sediments, triggered primarily by declining groundwater levels and exacerbated by land‑use changes, particularly the conversion of rain‑fed agriculture to irrigated farming. Given the region’s semi‑arid climate and its heavy reliance on groundwater for irrigation, understanding the interplay between hydrological changes and land‑surface response is critical for sustainable planning. Given the growing pressure on groundwater resources and the rapid transformation of agricultural practices in Mahidasht, a comprehensive assessment of subsidence dynamics is essential. This study integrates radar interferometry, hydrogeological observations, and multi‑temporal land‑use analysis to evaluate the spatial‑temporal patterns of subsidence and identify the dominant drivers influencing ground deformation in the region.
Materials and Methods
A multi‑source analytical framework was employed, combining SBAS‑InSAR time‑series analysis, piezometric data interpretation, and long‑term land‑use change assessment. Thirty Sentinel‑1 SLC images acquired between January 2022 and July 2024 were processed using SNAP and SARscape to derive vertical displacement rates. Interferograms were generated using small baseline pairs, followed by Goldstein filtering, phase unwrapping, and geocoding. Ground control points were selected in stable zones to enhance phase correction accuracy. The IDW interpolation was performed with a power parameter of 2, and cross‑validation was used to assess the accuracy of the groundwater‑level maps. Additionally, the land‑use classification achieved an overall accuracy exceeding 85% based on field‑collected ground truth points. Hydrogeological data from 21 piezometric wells (2001–2023) were analyzed using the IDW interpolation method to map groundwater‑level variations. Land‑use maps for 2001 and 2023 were produced using an artificial neural network classifier applied to Landsat imagery, supported by field‑based ground control points. The integration of these datasets enabled a detailed evaluation of the relationship between subsidence, groundwater decline, and land‑use transitions.
Results and Discussion
The SBAS‑InSAR analysis revealed significant vertical deformation across the Mahidasht Plain, with displacement ranging from +22 mm uplift to −40 mm annual subsidence. The most severe subsidence occurred in the eastern and northern sectors, where groundwater extraction is most intensive. Piezometric data indicated a maximum groundwater decline of −26.98 m over the study period, with steep hydraulic gradients surrounding high‑extraction well clusters. These zones correspond closely with subsidence hotspots, demonstrating a strong spatial correlation between aquifer depletion and ground settlement. Land‑use analysis showed substantial expansion of irrigated agriculture between 2001 and 2023, replacing large areas of rain‑fed croplands. This transition significantly increased groundwater demand, accelerating aquifer compaction and subsidence. The growth of barren lands further reduced soil moisture retention and increased susceptibility to erosion, contributing to weakened soil structure. The spatial overlap between subsidence zones and areas with high irrigation density was quantified, revealing that regions with more than 50% irrigated crop cover experienced subsidence rates nearly double those with lower irrigation intensity. Moreover, the temporal analysis indicates an acceleration of subsidence after 2020, coinciding with a period of reduced rainfall. In contrast, central and western areas exhibited lower subsidence rates due to more stable groundwater conditions and limited land‑use alteration.
     Comparisons with previous studies in other Iranian plains such as Kermanshah, Harris, and Shahr‑e Kord confirm that subsidence in Mahidasht is both more intense and spatially distinct. While many regions exhibit central subsidence patterns, Mahidasht shows maximum deformation along its eastern and northern margins, indicating a shift in subsidence dynamics driven by localized human pressures. The combined evidence highlights that anthropogenic factors particularly groundwater over‑extraction and agricultural intensification are the primary drivers of subsidence in the region. The findings also reveal that continued land‑use transitions, especially the conversion of rain‑fed to irrigated farming, have amplified environmental stress, reduced soil stability, and increased vulnerability to long‑term degradation. These changes have broader implications for water quality, agricultural productivity, and the resilience of rural communities.
Conclusion
This study demonstrates that the Mahidasht Plain is experiencing a rapidly intensifying subsidence crisis driven primarily by unsustainable groundwater exploitation and extensive land‑use transformation. Maximum annual subsidence reached 40 mm, with the most affected areas corresponding to zones of severe groundwater decline and widespread conversion of rain‑fed to irrigated agriculture. Continued trends pose serious risks to soil stability, water quality, agricultural productivity, and infrastructure integrity. Effective mitigation requires strict groundwater management, reduction of high‑water‑demand crops, and regulatory control over land‑use practices. Integrating these findings into local water‑resource management plans for instance, through managed aquifer recharge and promoting drought‑resistant crops could substantially reduce future impacts. The study also emphasises the need for continuous satellite‑based monitoring to track deformation trends and inform adaptive management strategies. The findings provide a scientific foundation for regional planning and highlight the urgent need for sustainable resource management to prevent irreversible environmental degradation.