Abstract
Crop phenology is essential for evaluating crop production in the food insecure regions of West Africa. The aim of the paper is to study whether satellite observation of plant phenology are consistent with ground knowledge of crop cycles as expressed in agro-simulations. We used phenological variables from a MODIS Land Cover Dynamics (MCD12Q2) product and examined whether they reproduced the spatio-temporal variability of crop phenological stages in Southern Mali. Furthermore, a validated cereal crop growth model for this region, SARRA-H (System for Regional Analysis of Agro-Climatic Risks), provided precise agronomic information. Remotely-sensed green-up, maturity, senescence and dormancy MODIS dates were extracted for areas previously identified as crops and were compared with simulated leaf area indices (LAI) temporal profiles generated using the SARRA-H crop model, which considered the main cropping practices. We studied both spatial (eight sites throughout South Mali during 2007) and temporal (two sites from 2002 to 2008) differences between simulated crop cycles and determined how the differences were indicated in satellite-derived phenometrics. The spatial comparison of the phenological indicator observations and simulations showed mainly that (i) the satellite-derived start-of-season (SOS) was detected approximately 30 days before the model-derived SOS; and (ii) the satellite-derived end-of-season (EOS) was typically detected 40 days after the model-derived EOS. Studying the inter-annual difference, we verified that the mean bias was globally consistent for different climatic conditions. Therefore, the land cover dynamics derived from the MODIS time series can reproduce the spatial and temporal variability of different start-of-season and end-of-season crop species. In particular, we recommend simultaneously using start-of-season phenometrics with crop models for yield forecasting to complement commonly used climate data and provide a better estimate of vegetation phenological changes that integrate rainfall variability, land cover diversity, and the main farmer practices.
Highlights
Crop phenological dynamics should be essential for evaluating crop production [1], especially in the West African food-insecure regions
The leaf area indices (LAI) profiles simulated for each synoptic station as the annual SARRA-H crop model output exhibit a typical vegetation growth shape, except at the end of the growing season, where the LAI
- The choice of different soil types has a limited impact on LAI dynamics, except for EMAX
Summary
Crop phenological dynamics should be essential for evaluating crop production [1], especially in the West African food-insecure regions. With the ability to detect surface phenology objectively on a uniform timescale and global scale, time series composed of low- and medium-resolution satellite images have been used to study the phenological patterns that relate to climate variability and human actions (e.g., [5,6,7,8,9]). As vegetation phenology in arid and semiarid ecosystems is primarily controlled by water availability, a number of field studies have attempted to quantitatively link phenology to precipitation forcing. Zhang et al [3] examined how phenology changed with latitude, and how it was related to the timing of seasonal rainfall in Sahelian and Sudanese regions; they concluded that well-defined thresholds exist in cumulative rainfall for stimulating vegetation green-up in arid and semiarid regions of Africa
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