@article{fdi:010085256,
  title = {{A} systematic national stocktake of crop models in {M}orocco},
  author = {{E}pule, {T}. {E}. and {C}hehbouni, {A}bdelghani and {C}hfadi, {T}. and {O}ngoma, {V}. and {E}r-{R}aki, {S}. and {K}habba, {S}. and {E}tongo, {D}. and {M}artinez-{C}ruz, {A}. {L}. and {M}olua, {E}. {L}. and {A}chli, {S}. and {S}alih, {W}. and {C}huwah, {C}. and {J}emo, {M}. and {C}hairi, {I}.},
  editor = {},
  language = {{ENG}},
  abstract = {{A}griculture is an important sector of the {M}oroccan economy, employing a huge portion of the {M}oroccan population and contributing about 14 - 20% to the country's {GDP}. {U}nfortunately, agricultural production in {M}orocco is impacted by climatic, non-climatic, biophysical, and non-biophysical stressors. {R}esearchers have employed various crop models to understand how different crops respond to different environmental conditions such as temperature, precipitation, soil properties, fertilization, and irrigation. {U}nfortunately, there are no studies that provide a summary and a holistic perspective of the most frequently used models and their calibration inputs in {M}orocco. {T}his 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. {T}his 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. {T}he results show that most of the authors are affiliated with {M}oroccan universities/organizations while wheat is the most studied crop. {I}n addition, the {AQUACROP} and the regression-based models are the most used crop models. {A}dditionally, most of the models are calibrated in order of importance with variables such as temperature, precipitation, soil properties, irrigation, and fertilizers. {O}n 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. {I}t is still unclear how process-based models will integrate socio-economic indicators. {T}his work has implications for future research as it provides a holistic picture of the key models that are currently used and their calibration. {T}his 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 {M}orocco, and {N}orth {A}frica. {T}hese results underscore the leading role in research funding offered by the government of {M}orocco and other organizations such as {UM}6{P} and {OCP} {A}frica in research valorization in {M}orocco and {A}frica.},
  keywords = {{A}griculture ; {W}heat ; {C}rop {M}odels ; {P}eer reviewed ; grey literature ; {M}orocco ; {MAROC}},
  booktitle = {},
  journal = {{E}cological {M}odelling},
  volume = {470},
  numero = {},
  pages = {110036 [17 p.]},
  ISSN = {0304-3800},
  year = {2022},
  DOI = {10.1016/j.ecolmodel.2022.110036},
  URL = {https://www.documentation.ird.fr/hor/fdi:010085256},
}