Climatic gradients along the windward slopes of Mount Kenya and their implication for crop risks. Part 2: crop sensitivity

Abstract

Mount Kenya is an equatorial mountain whose climatic setting is fairly simple (two rainy seasons in March-May, the Long Rains, and October-December, the Short Rains) though concealing significant spatial variations related to elevation and aspect (part I, Camberlin et al., 2014). This part II is dedicated to the sensitivity of sorghum yields to climate variability in space and time, with a focus on the intra-seasonal characteristics of the rainy seasons. To that aim we use the crop model SARRA-H calibrated for the region and fed with rainfall, temperature, wind speed, humidity and solar radiation data over the period 1973-2001 at three stations located on the eastern slopes of Mount Kenya. The crop model is run independently for the two rainy seasons. Four groups of simulations are conducted by varying the initialization date of the simulation, the sowing dates and the type of soil, in order to test sorghum sensitivity to water availability. Evidence is found that potential sorghum yields are dominantly controlled by variations in seasonal rainfall amounts: mean yields are higher at higher and wetter locations, and are higher during the wettest rainy season and years. However, beyond this apparent simplicity, more complex aspects emerge of the crop-climate relationships. First, the yield-elevation relationship is altered at high elevation due to lower temperature. Second, despite a strong link with the seasonal rainfall amounts, we evidence an underlying role of some intra-seasonal rainfall characteristics such as the number of rainy days (itself mainly determined by the rainy season duration) or the occurrence of long dry spells. Third, unseasonal rains occurring after the end of the rainy season, especially after the Short Rains, play a role in final crop yield. Fourth, variations of climate variables such as solar radiation by modulating the potential evapotranspiration concur to yield variations at the wettest locations.

Understanding the Role of User Needs and Perceptions Related to Sub-Seasonal and Seasonal Forecasts on Farmers' Decisions in Kenya: A Systematic Review

“…It is interesting that seasonal forecasts have been found to show skill and usefulness in Meru (Recha et al, 2012). Similar to Laikipia and Machakos, farmers' perceptions have led to utilization of onset dates in planning planting times and choices of seeds to plant by farmers in Meru County (Philippon et al, 2016). Another perception influencing decisions in Meru regards farmers' combining forecasts and other agricultural and market information in managing climate risks (Percy, 2013).…”

Reconstitution de séries de pluies quotidiennes en Afrique de l’est : application aux caractéristiques des saisons des pluies

“…On peut citer pour exemple, les hydrologues pour qui les précipitations quotidiennes sont nécessaires en entrée des modèles de pluie-débit (Obled et al, 2009), les climatologues qui les utilisent dans l'étude des sécheresses (Usman et Reason, 2004 ;Gitau, 2011 ;Gitau et al, 2012). C'est aussi le cas en agronomie où les pluies représentent la variable d'entrée majeure dans les modèles de croissance de plantes (Baron et al, 2005 ;Traoré et al, 2011) et les modèles statistiques empiriques (Schlenker et Lobell, 2010) dont l'objectif est la compréhension et la prévision de l'évolution des rendements céréaliers par exemple (Ramarohetra et al, 2012 ;Philippon et al, 2015a). Si les jeux de données globaux en points de grille fournissent des séries complètes, leurs résolutions spatiales et temporelles (au mieux 0,5° en latitude et longitude et au pas de temps mensuel pour les données du Climatic Research Unit par exemple) les rendent inadéquats pour analyser les caractéristiques intrasaisonnières des pluies en zone de forts gradients climatiques.…”