GIS-based evaluation of diagnostic areas in landslide susceptibility analysis of Bahluieț River Basin (Moldavian Plateau, NE Romania). Are Neolithic sites in danger?

Abstract

The aim of this study is to compare the predictive strenghtness of different diagnostic areas in determining landslide susceptibility using frequency ratio (FR), statistical index (SI), and analytic hierarchy process (AHP) models in a catchment from the northeastern part of Romania. Scarps (point), landslide areas (polygon), and middle of the landslide (point) have been tested and checked in regards to their performance. The three statistical models have been employed to assess the landslide susceptibility using eleven conditioning factors (slope angle, elevation, curvature, lithology, precipitations, land use, topographic wetness index (TWI), landforms, aspect, plan curvature and distance to river). The three models were validated using the receiver operating characteristic (ROC) curves and the seed cell area index (SCAI) methods. The predictive capability of each model was established from the area under the curve (AUC), for FR, SI and AHP; the values are 0.75, 0.81 and 0.78 (using polygon as diagnostic area), respectively. Among the three methods used, SI had a better predictability. When it comes to the predictability values regarding the diagnostic areas, the landslide area (polygon) proves to have the highest values. This results from the entire surface of the landslide being taken into account when validating the data. Approximately 70% of the Neolithic sites are located in areas with high and very high susceptibility to landslides, meaning that they are in danger of being destroyed in the future. The final susceptibility maps are useful in hazard mitigation, risk reduction, a sustainable land use planning, evaluation of cultural heritage integrity, and to highlight the most endangered sites that are likely to be destroyed in the future.

Is Overgrazing Really Influencing Soil Erosion?

“…Therefore, the specific objectives of this study are (1) spatially predict the gully erosion in the Bahluieț river basin; (2) employing two statistical models, FR and IV; (3) to evaluate the final susceptibility maps performance by using ROC curves; (4) to analyse the final susceptibility maps with and without the overgrazing as a conditioning factor; (5) to determine the number of Neolithic sites located in areas with high and very high susceptibility to gully erosion; and (6) to investigate the final susceptibility maps in the framework of big infrastructure projects (A8 motorway). Europe's cultural heritage is in danger from natural hazards [34] and anthropic interventions [35]; the cultural heritage from the northeastern part of Romania is no exception [19,[36][37][38][39]. However, significant efforts are made every year in order to highlight the importance of Neolithic sites in establishing the Romanian identity and to promote them from a tourism point of view [40].…”

“…The lithological setting of the area is characterised by non-cohesive deposits of Bessarabian age (an alternation of marls, clays with intrusions of sand, and oolithic limestone); the fine granulation of these lithological deposits led to the triggering and developing of geomorphological processes, The lithological setting of the area is characterised by non-cohesive deposits of Bessarabian age (an alternation of marls, clays with intrusions of sand, and oolithic limestone); the fine granulation of these lithological deposits led to the triggering and developing of geomorphological processes, especially gullying ( Figure 3). More details regarding the geomorphic characteristics of this area can be found in the literature [35][36][37][38][39]. Cucuteni culture is one of the most representative prehistoric cultures from Eastern Europe and is part of the well-known Cucuteni-Ariușd-Trypillia Cultural Complex (approximately 350,000 km 2 ).…”

“…Many gullies are initiated by the unconsolidated deposits of the landslides; therefore, there are higher chances of gully triggering around landslides. Out of the total number of 677 gullies, 457 gullies intersect with a landslide (there is a total of 764 landsides) [39]. In order to realize the final susceptibility maps, a set of ten environmental factors were used; namely, elevation, precipitations, slope angle, curvature, lithology, drainage density, topographic wetness index, landforms, aspect, and distance from rivers.…”

“…Europe's cultural heritage is in danger from natural hazards [34] and anthropic interventions [35]; the cultural heritage from the northeastern part of Romania is no exception [19,[36][37][38][39]. However, significant efforts are made every year in order to highlight the importance of Neolithic sites in establishing the Romanian identity and to promote them from a tourism point of view [40].…”

Optimizing an Adaptive Neuro-Fuzzy Inference System for Spatial Prediction of Landslide Susceptibility Using Four State-of-the-art Metaheuristic Techniques

“…Many scholars have employed statistical-based methods for landslide susceptibility assessment [9][10][11]. Fayez, et al [12] successfully implemented the FR model for landslide susceptibility assessment in India.…”