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Exploration of the statistical relationships between rainfall indices and cotton yields in northern Cameroon, to strengthen the resilience of farmers to climate change

Titre :	Exploration of the statistical relationships between rainfall indices and cotton yields in northern Cameroon, to strengthen the resilience of farmers to climate change Ajouter au panier
Auteur(s) :	Clara Knops, Auteur (et co-auteur) Jean-Stéphane Bailly, Tuteur Jérémy Lavarenne, Responsable de stage Agroparistech (Montpellier; FRA), Etablissement de soutenance Université de Montpellier (Montpellier; FRA), Etablissement de soutenance Institut Agro Montpellier (Montpellier; FRA), Etablissement de soutenance
Type de document :	Mémoire
Filière :	M. : EA -- Eau et agriculture
Sujets :	Pluviométrie ; Coton ; Rendement des cultures ; Cameroun ; Indicateurs biologiques ; Changement climatique Prévision de rendement
Résumé :	This thesis investigates the statistical relationships between rainfall indices and cotton yields in northern Cameroon, a region heavily dependent on cotton and vulnerable to climate change due to its high rainfall variability. Daily rainfall data from the NoCORA rainfall dataset was interpolated using Ordinary Kriging to calculate yearly rainfall indices maps for a total of 25 indices. Cotton yield data on two different geographical levels was additionally provided by SODECOTON. Applying simple and multiple linear regression, the impact of the rainfall indices on cotton yields were analyzed. The onset and cessation day of the rainy season as well as the season length, dry days, dry spell consecutive 10 and 15, seasonal rainfall amount, rain days, wet days 20 and 30, as well as heavy [...] This thesis investigates the statistical relationships between rainfall indices and cotton yields in northern Cameroon, a region heavily dependent on cotton and vulnerable to climate change due to its high rainfall variability. Daily rainfall data from the NoCORA rainfall dataset was interpolated using Ordinary Kriging to calculate yearly rainfall indices maps for a total of 25 indices. Cotton yield data on two different geographical levels was additionally provided by SODECOTON. Applying simple and multiple linear regression, the impact of the rainfall indices on cotton yields were analyzed. The onset and cessation day of the rainy season as well as the season length, dry days, dry spell consecutive 10 and 15, seasonal rainfall amount, rain days, wet days 20 and 30, as well as heavy rain days were found to be the indices with the strongest, statistically significant relationships. Our findings will allow further research into the topic, serving for prediction-analysis using climate projection data.
Date de publication :	2024
Format :	2 pdf (56, 22 p.)
Note(s) :	Stage de fin d'étude du master "Sciences de l'eau" parcours Eau et Agriculture Promo du stage : 2023-2024
Langue(s) :	Anglais
Organisme d'accueil :	UMR TETIS, CIRAD
Lien vers la notice :	https://infodoc.agroparistech.fr/index.php?lvl=notice_display&id=225791

Exemplaires (2)

Localisation	Emplacement	Pôle	Section	Cote	Support	Disponibilité
Montpellier	Serveur		Eau et Agriculture	MEM-M2-2024-KNOP-E A	Numérique	Diffusable Exclu du prêt
Montpellier	Serveur		Eau et Agriculture	MEM-M2-2024-KNOP-E B	Numérique	Diffusable Exclu du prêt