Land subsidence and collapsed pipes are considered among geomorphological hazards, causing significant damages annually in the form of direct and indirect costs. These hazards lead to notable changes in the landscape, land degradation, soil and water losses, and regional erosion and sedimentation. Consequently, the effective management of these hazards and the determination of relationships between their environmental factors for quantitative susceptibility assessment are of utmost importance. A trustworthy evaluation depends on the quality of available data and the selection of appropriate analytical and modeling methods. Given that no comprehensive study on land subsidence and collapsed pipes in Razavi Khorasan Province has been conducted so far and considering that the land degradation resulting from plain land subsidence and collapsed pipes are among the primary threatening hazards for the country and the province, particularly in recent years, the use of proper analytical and modeling methods for comprehensive and integrated management seems essential. This research was conducted using high-resolution satellite imagery in Razavi Khorasan Province. In this study, topographical and hydrological feature maps were prepared using a digital elevation model based on the boundaries of Razavi Khorasan Province. Physical and chemical tests were conducted on 624 soil samples collected throughout the province, and their raster maps were produced. Data pertaining to vegetation cover, land use maps, geology, and regional precipitation were also prepared and used as inputs for the models. The spatial locations of land subsidence and collapsed pipes across the province were identified in subsequent phases. Following this, using statistical and data mining methods, spatial modeling of the land subsidence and collapsed pipes was performed, and the best regional model for their evaluation was chosen. The AUC numerical value for both the support vector machine (SVM) and maximum entropy (ME) models ranges between 0.8 and 0.9, indicating an excellent evaluation of the models used in zoning the land subsidence. Ultimately, the ability to recognize the behavior and formation conditions of these hazards, to identify areas with greater susceptibility, to present a risk management model for land subsidence and collapsed pipes, and to distinguish critical and susceptible areas for land subsidence and collapsed pipes, along with their control methods, was provided. Notably, the SVM algorithm demonstrated superior efficacy in this study. The insights derived from identifying erosional structures of collapsed pipes and land subsidence and understanding their spatial interrelationships offer a robust foundation for devising timely and strategic management interventions in affected domains.

The primary objective of this research was to analyze the spatial pattern and interactions of dendritic rill channels and surface/subsurface channels (pipes)/collapsed pipes. To achieve this, photogrammetry drones were employed on over 70ha in the protected region of Takhtsoltan in Razavi Khorasan Province. This approach pinpointed areas impacted by erosions from subsurface channels (pipes)/collapsed pipes and dendritic rill channels and surfaces. Subsequent field visits documented 76 instances of subsurface channels (pipes)/collapsed pipes and 58 dendritic rill channels and surfaces, using orthophotos derived from the aerial drone images. In the analytical phase, topographical, hydrological, soil, and biological factors were examined as independent variables, whereas the types of erosion from subsurface channels (pipes)/collapsed pipes and dendritic rill channels were viewed as dependent variables. Spatial patterns of the subsurface channels (pipes)/collapsed pipes and dendritic rill channels were discerned using univariate functions. Further, bivariate functions were deployed to probe the interrelations, revealing that the distribution pattern of the study area's subsurface channels (pipes)/collapsed pipes is predominantly clustered, in contrast to the dispersed spatial pattern of the dendritic rill channels. This analysis also confirmed significant positive correlations between dendritic rill channel erosions and subsurface channels (pipes)/collapsed pipes. Ultimately, by identifying the erosional landforms of subsurface channels (pipes)/collapsed pipes and dendritic rill channels and understanding the spatial and processual relationships between them, a deeper insight into the natural processes inherent in their spatial structure was achieved, paving the way for devising suitable strategies for their timely management.