GIS and SDM-Based Methodology for Resource Optimisation: Feasibility Study for Citrus in Mediterranean Area

Abstract

South Italy is characterised by a semi-arid climate with scarce rain and high evaporative demand. Since climate change could worsen this condition, the need to optimise water resources in this area is crucial. In citrus cultivation, which involves one of the most important crops bred in Southern Italy, and more generally in Mediterranean regions, deficit irrigation strategies are implemented in order to cope with limited resource availability. On this basis, knowledge on how the territorial distribution of citrus would change in relation to these strategies represents valuable information for stakeholders. Therefore, the objective of this study was to determine the probability of the presence of citrus in Sicily based on changes in the percentage of water deficit in order to identify and analyse change in the surface area as well as the location of the crop. The methodology was based on the application of species distribution models (SDM) and Geographic Information Systems (GIS) to the case study of the province of Syracuse in Sicily. Different geostatistical and machine learning models were applied based on bioclimatic variables measured over three decades, a Digital Terrain Model and irrigation. Assessment of the outcomes was carried out using classification evaluation metrics. The analysis of the outcomes showed that uncorrelated predictor layers mainly included water input that most affected the probability of the presence of citrus fruits. Moreover, GIS analyses showed that deficit irrigation strategies would generate an overall reduction of cultivation surfaces in the territory (e.g., for the Random Forest model the surface reduction was equal to 41.15%) and a decrease of citrus presence in southern areas of the considered territory. In this area, climate conditions are less favourable in terms of temperature and precipitation; thus, these analyses provide useful information for decision support tools in agriculture and land use policy.

Keywords

• VisTrails:SAHM software
• citrus
• spatial distribution
• probability of presence
• Mediterranean climate
• predictor layers