Prioritizing sub-watersheds based on soil-erosion potential by integrating RUSLE and game-theory algorithms

Abstract

Determining areas that are experiencing severe soil erosion and prioritizing these areas for management and conservation planning is a critical contemporary need. The purpose of this research is to use two different approaches - the experimental model of the global soil loss equation (RUSLE) and three game theory algorithms (Fallback, Borda and Condorcet) - to prioritize areas with high erosion in Talar watershed, Iran. Five factors were employed to operationalize the RUSLE model – rainfall erosivity (R), soil erodibility (K), slope length (LS), cover (C), and support practice factor (P). The average of each factor in each sub-watershed provided inputs for the game-theory algorithms. The results indicated that the average soil loss in the entire watershed is 29 t ha−1 yr−1. The RUSLE model revealed that sub-watersheds 9, 11, 12, and 13 have the highest erosion rates in the study area. The three game-theory algorithms agreed that sub-watersheds 1, 2, 3, 4 and 5 possessed the highest erosion potential in the region. Anthropogenic activities like deforestation, farming, and tillage relative to certain slope directions and the development of rainfed agriculture are the main reasons for high soil loss rates in the study area. The conclusions drawn in this study can be helpful for prioritizing areas prone to critical levels of erosion and can help to determine appropriate erosion prevention and loss mitigation methods in other watersheds.