Modelling Soil Degradation in Libya

Abstract

Soil degradation is considered one of the most important factors limiting agricultural development in Libya, however little effort has been taken to identify the distribution of soil degradation occurrence and type for the country. While the soil degradation for the primary agriculture regions (PAR) has been previously determined as thirty-three percent (33%), the degradation for the rest of the country was still unknown. For this reason, polygons representing soil and climate characteristics, landscape feature and soil degradation from the PAR were converted to raster using ArcGIS (at a resolution of 1000 m²) resulting in 850 points which were then exported as a table for modelling purposes. The data set was subjected to logistic regression to model the binomial outcome of soil degradation occurrence (occurrence, no occurrence). A multinomial logistic regression was used to relate predictor variables to the type of soil degradation since there was more than two outcome options (salinization, water erosion, and wind erosion). Finally, the prediction models were used to determine the remainder of the country’s degradation occurrence and type. Results indicated that slope, texture and wind speed are the most important variables for soil degradation occurrence and type in PAR. When these models are applied to the reminder of the country, they show that salinization was the primary type of soil degradation (30 %), with water erosion and wind erosion causing 10 % and 15 % of soil degradation, respectively. The intention is for these models to assist stakeholders in identifying areas where agriculture is most likely to be successful, while also applicable to countries with similar climate and soils in North Africa.

Keywords: Agriculture, GIS, Libya, Logistic regression, Soil degradation.