Speaker
Description
Mediterranean agricultural systems are progressively facing escalating challenges due to the multifaceted impacts of climate change, which threaten the sustainability and productivity of key crops, notably olive cultivation, within arid and semi-arid zones. The Marrakesh region classified climatically as semi-arid according to the Köppen–Geiger classification system, exemplifies an area of heightened vulnerability to the projected intensification of global warming and its attendant environmental stressors. Empirical climate data collected over recent decades indicate a marked and continuous increase in thermal stress, manifested through rising temperatures and extended periods of heat exposure, which collectively jeopardize the phenological development, physiological stability, and yield potential of olive groves.
In response to these emerging threats, this research implements a comprehensive and integrated agroclimatic modelling framework designed to simulate future climate trajectories and quantify their effects on the agroecological suitability of olive cultivation within the region. By employing advanced modelling techniques that summarise climatological, agronomic, and ecological variables, the study aims to assess shifts in key climatic parameters critical to olive growth, such as temperature extremes and precipitation patterns, over the extended temporal horizon leading up to the year 2100. This holistic approach facilitates a nuanced evaluation of the resilience capacity of local olive production systems and informs adaptive management strategies that can enhance sustainability under changing climatic conditions.
The methodological approach adopted in this study centers on the deployment of ARIMA (AutoRegressive Integrated Moving Average) models, a well-established class of time series forecasting techniques, to rigorously analyze historical climate data spanning the period from 2000 to 2024. This timeframe was selected to capture recent climatic variability and trends relevant to the study region. The modelling process focuses on four critical climatic parameters that significantly influence olive cultivation dynamics: minimum temperature, mean temperature, maximum temperature, and total annual precipitation. These variables were chosen due to their direct impacts on phenological phases, water availability, and overall plant stress responses.
To ensure data quality and consistency, comprehensive meteorological time series were sourced from the NASA POWER database, which provides high-resolution, satellite-derived climate data aligned with the stringent data quality and format standards set forth by the World Meteorological Organization (WMO). This adherence guarantees comparability and reliability of the input datasets for subsequent modelling.
The ARIMA models were meticulously calibrated for each climatic variable, incorporating autoregressive, differencing, and moving average components tailored to capture the inherent temporal dependencies and non-stationarities within the data. The parameterization process included rigorous diagnostic checks and validation steps, such as autocorrelation function (ACF) and partial autocorrelation function (PACF) analyses, residual diagnostics, and out-of-sample testing, to optimize model fit and predictive accuracy.
Using these calibrated models, climate projections were extended from 2026 through to the end of the 21st century (2100), thereby generating multiple plausible scenario trajectories that reflect potential future climate evolution under current trends. These scenario-based projections allow for a nuanced understanding of the range and uncertainty inherent in long-term climate forecasts, providing essential insights for adaptive planning in olive cultivation within the Marrakesh semi-arid context.
This study represents the first structured application of ARIMA modelling to local climate forecasting in support of Moroccan olive cultivation. The resulting projections serve as the foundation for a quantitative, evidence-based framework to guide adaptation strategies in production systems. This includes redefining cropping calendars, optimizing irrigation management, and informing breeding programmes aimed at selecting climate-resilient olive varieties. The proposed methodological approach is not only robust but also transferable to other Mediterranean regions confronting comparable agroclimatic pressures, thereby contributing meaningfully to broader global initiatives focused on agricultural adaptation to climate change.
