Analytical hierarchical process of soil erosion risk assessment in Ondo State, Nigeria

Abstract

Soil erosion risk assessment and landuse planning strategics have become increasingly more data-intensive, sophisticated and highly complex involving myriads of quantitative and qualitative techniques. One of the methods that can help in synchronizing all these diverse data sets within a decision making framework is the analytical hierarchical process (AHP) developed by Satty. AHP provides a better technique for the comparison of factors based on decision matrices. It also provides structured methods for the incorporation of experts’ opinions in the ranking of factors. This study examines the use of the AHP in modelling soil erosion risk using Universal Soil Loss Equation (USLE). Rainfall data, landuse/landcover, digital elevation data, soil erosivity index, supporting practices and expert opinions were integrated using AHP to identify areas with varying degrees of erosion risk potential. A pairwise comparison of the four factors identified by experts and supported by the USLE model was performed by means of Saaty's square it is a reciprocal matrix with unit rank whose eigenvector solution gives the priority or the relative importance, or dominance, of the elements on a ratio scale. The inputs to the matrix were derived from field survey and expert opinions on the relative dominance of the elements within each pair by using a nine-point scale. The approach retains the quantitative conceptual elements of the USLE methodology while allowing for a qualitative assessment and ranking of pertinent factors of soil erosion at micro level. The study shows that hilly areas with high rainfall particularly in the urban areas have the highest erosion risk potential while the natural forest areas have the least. It therefore shows the utility of AHP in coupling existing models with expert opinions as well as some subjective indicators in decision making. The method was capable of ranking ecosystems in terms of environmental conditions and suggesting cumulative impacts across a large region.