Skip to main content
SLU publication database (SLUpub)
Research article - Peer-reviewed, 2022

A systematic national stocktake of crop models in Morocco

Epule, Terence Epule; Chehbouni, Abdelghani; Chfadi, Tarik; Ongoma, Victor; Er-Raki, Salah; Khabba, Said; Etongo, Daniel; Martinez-Cruz, Adan L.; Molua, Ernest Lytia; Achli, Soumia; Salih, Wiam; Chuwah, Clifford; Jemo, Martin; Chairi, Ikram


Agriculture is an important sector of the Moroccan economy, employing a huge portion of the Moroccan population and contributing about 14 - 20% to the country's GDP. Unfortunately, agricultural production in Morocco is impacted by climatic, non-climatic, biophysical, and non-biophysical stressors. Researchers have employed various crop models to understand how different crops respond to different environmental conditions such as temperature, precipitation, soil properties, fertilization, and irrigation. Unfortunately, there are no studies that provide a summary and a holistic perspective of the most frequently used models and their calibration inputs in Morocco. This work, therefore, seeks to fill these knowledge gaps by providing a summary of the most calibrated crop models, their calibration input data, the most frequently studied crops, how the studies are published (peerreview or grey literature), and the affiliations of the lead authors. This is achieved through a systematic review of the primary peer review and grey literature. A total of 68 relevant peer review and grey literature papers were considered. The results show that most of the authors are affiliated with Moroccan universities/organizations while wheat is the most studied crop. In addition, the AQUACROP and the regression-based models are the most used crop models. Additionally, most of the models are calibrated in order of importance with variables such as temperature, precipitation, soil properties, irrigation, and fertilizers. On the other hand, there is an observed increase in the use of non-climatic indicators such as poverty, farm income, and literacy levels to fit empirical models. It is still unclear how process-based models will integrate socio-economic indicators. This work has implications for future research as it provides a holistic picture of the key models that are currently used and their calibration. This information can be used by other projects to select methods to use, and crops to study based on the available data when working on crop models in Morocco, and North Africa. These results underscore the leading role in research funding offered by the government of Morocco and other organizations such as UM6P and OCP Africa in research valorization in Morocco and Africa.


Agriculture; Wheat; Crop Models; Peer reviewed; grey literature; Morocco

Published in

Ecological Modelling
2022, Volume: 470, article number: 110036

    Associated SLU-program


    Sustainable Development Goals

    SDG1 No poverty
    SDG8 Decent work and economic growth

    UKÄ Subject classification

    Agricultural Science

    Publication identifier


    Permanent link to this page (URI)