Introduction

Sinkholes are depressions in the ground which have no natural external surface drainage. They may be occurred in karstic landforms through dissolution process with accompanying of other karstic features (Parise, 2019). Jafari and Mohammadi (2018), stated that understanding geographical condion and causative factors and related processes are vital in sinkhole hazard zonation in Kabudrahang and Famenin plain. North of Alamut at border of Gilan and Mazandaran provinces is one of the areas that dominantly sinkholes have been taken place. More than 200 dissolution based sinkhole have been observed and mapped in this area (Armani and Taromi, 2022). In this study an attempt was made to map sinkholes in this area by understanding environmental condition, role of causative factors, data integration and modeling in a GIS.





Methodology

The study field is located in North of Razmian, bordrs of Qazvin, Gilan and Mazandaran provinces. The study area is limited to latitudes between 36° 35΄ and 36° 42΄ North, and longitudes between 50° 15΄ and 50° 30΄ East. First, the required geographic data, such as a map indicating areas of hope to have access to shallow karst water, climate zones, mean temperature classes map, surface flow concentration, geology map including lithology and geological lineaments density maps at scale 1:100000 were prepared. Since areas of hope to have access to shallow karst water are potentially vulnerable to collapse of overburden materials over such areas, therefore this spatial data was used as a basis for detail investigation and identification of sinkholes. For doing this, the data layers were integrated by using of decision making critera.

Then, cross operation was applied to the data layers called climate zones and zones with same mean temperature. The same operation also was applied to data layers named lineaments density and flow accumulation classes. These operaton led to have two maps and attribute tables. By overlaying the two output maps, a new map having information on possible combinations of all causative factors was produced. At the next step, proper weights (1 to 5) were given to the possible combination forms, based on characteristics and role of causative factors in dissolving carbonate rocks and creation of sinkholes, by using two dimentional tables in a GIS. The map representing potentials for sinkhole occurrence was created by classifying the final weight map. Consequently the generated map representing potentials for occurrence of sinkholes or susceptible areas for sinkhole occurrence was refined and precceised via considering information of areas of hope to have access shallow karst water resources. Accuracy of results then were assessed by cheking spatial overlaps and coincidence of geographic locations of more than 240 observed sinkholes and sinkhole vulnerability map and sink map generated through proccessing of digital elevaton model (DEM). Since results of model for mapping areas of hope to have access to shallow karst water is underestimated due to sensivity to vegetation cover, so a buffer around ground truths are used for accuracy assessment.



Results and Discussion



There are many sinkholes in the study area. More than 240 of them have been studied during a intensive field work. Most of sinkholes in Northwest of Alamut are Karrens and caves in type and variety, which have been formed through solution processes in bedrocks. About 28 sinkholes have been reported by Soldo et al., 2020, in Feiz_Abad plain, Abarkuh, that are taken place by means of the same processe. Although solution process in soluble materials like carbonate rocks is a main factor for generating such geomorphological features at highlands, but lowering groundwater level in plains plays a main role for land subsidene and also collapsing Earth materials ending to sinkholes. There are some methods like radar interferometery and direct field measurments that have been developed for recognition and characterizing occurred land subsidence and sinkholes, while there is no well known method for identifying and mappig points that are potentially vulnerable to sinkhole incidence. The method which has been developed for mapping areas of hope to have access to shallow karst water, in Azarshahr, by Jalali et, al 2009 and the same method applied by Armani et al., 2022, to North of Qazwin province, might be the most proper method and basis for seeking areas potentially vulnerable to sinkhole hazard. Therefore the areas of hope to have access to shallow kaerst water, provided by Armani et al., for this study area, were searched for allocating areas that are vulnerable for sinkhole occurrences, by applying above_mentioned methodology. as a result of application of this method, spatial distribution of potentials areas that are vulnerable to sinkhole occurrence were identified.

The model used by Jalali et al., (2009) al. and Armani and Jalali, (2022) for mapping areas of hope to have access to shallow karst water excludes dense vegetation covers, so the final result becomes underestimated. Since the study area relatively have good vegetation cover, therefore the area and number of identified sinkholes were identified less than they are. In the other words if vegetation cover was not a limiting factor in the model, high regression would be expected between observed sinkholes and output of the model. Anyhow more than 66% of susceptible areas to sinkhole occurrence are coincide with areas less than 200 meter DEM-derived sinks buffers and about 40% of those susceptible areas are fallen in buffers less than 200 meter to observed sinkholes.



Conclusion

Preparing sinkhole hazard map by making use of remotely snsensed data and relational modeling in Alamut area is bearable and cost effective from time and cost points of vies. Therefore one may provide sinkhole hazard and their spatial distribution maps by indirect mapping procedure. Since sinkhole are generally being formed in soluble materials, like carbonate rocks, so some susceptible parts of this rocks that have been marked as areas of hope to have access to shallow karst water, could be selected as a reliable bassis for further spatial data achievement about sinkholes and their characteristics.