A COMPARATIVE STUDY OF THE BIVARIATE STATISTICAL METHODS AND THE ANALYTICAL HIERARCHICAL PROCESS FOR THE ASSESSMENT OF MASS MOVEMENT SUSCEPTIBILITY. A CASE STUDY: THE LM-116 ROAD – PERU

Abstract

It has been long observed that the Peruvian Central Highway (PE-22) and the LM-116 road are among the roads most affected by mass movements (MM) in Peru, frequently exposed to the occurrence of rockfalls, debris flow and landslides; both roads represent an important connection alternative between Lima with towns, cities and mining centers located in the Central Mountain Range of the Andes. In this research, firstly, a point density analysis was performed using Geographic Information Systems (GIS) considering the road network of all of Peru (composed of 144,499 km) and the inventory of geological hazards (GEOCATMIN) prepared by the Geological, Mining and Metallurgical Institute of Peru INGEMMET (2000-2018). Subsequently, the evaluation of the mass movement susceptibility on the LM-116 road has been carried out using free access data reported by Peruvian institutions (INGEMMET, MTC, MINAM) from which it was possible to elaborate thematic maps, including the most relevant factors in the occurrence of mass movements, like a slope, lithology, geomorphology, land use, drainage density, and the distance from tectonic structures. Finally, for the mass movement susceptibility analysis, three methods have been considered: the Analytic Hierarchical Process (AHP), the Statistical Index (Wi) and the Weights of Evidence (WoE). The results were validated using the area under the curve criteria (AUC). Both bivariate statistical methods (Wi and WoE) presented a prediction rate above 78%, with a higher rate for the WoE method. On the other hand, the semi-quantitative method (AHP) obtained values in the order of 69%. Therefore, it is concluded that the maps elaborated with the statistical methods presented a better approximation concerning the database of geological hazards reported by GEOCATMIN.

Keywords

• Mass movement susceptibility
• linear projects
• Weights of Evidence
• statistical indeks