Your search found 4 records
(Location: IWMI HQ Call no: 333.91 G592 MCV Record No: H044213)
(7.21 MB) (7.21MB)
2 Asseng, S.; Ewert, F.; Martre, P.; Rotter, R. P.; Lobell, D. B.; Cammarano, D.; Kimball, B. A.; Ottman, M. J.; Wall, G. W.; White, J. W.; Reynolds, M. P.; Alderman, P. D.; Prasad, P. V. V.; Aggarwal, Pramod Kumar; Anothai, J.; Basso, B.; Biernath, C.; Challinor, A. J.; De Sanctis, G.; Doltra, J.; Fereres, E.; Garcia-Vila, M.; Gayler, S.; Hoogenboom, G.; Hunt, L. A.; Izaurralde, R. C.; Jabloun, M.; Jones, C. D.; Kersebaum, K. C.; Koehler, A-K.; Muller, C.; Kumar, S. N.; Nendel, C.; O’Leary, G.; Olesen, J. E.; Palosuo, T.; Priesack, E.; Rezaei, E. E.; Ruane, A. C.; Semenov, M. A.; Shcherbak, I.; Stockle, C.; Stratonovitch, P.; Streck, T.; Supit, I; Tao, F.; Thorburn, P. J.; Waha, K.; Wang, E.; Wallach, D.; Wolf, J.; Zhao, Z.; Zhu, Y. 2015. Rising temperatures reduce global wheat production. Nature Climate Change, 5:143-147. [doi: https://doi.org/10.1038/nclimate2470]
(Location: IWMI HQ Call no: e-copy only Record No: H046906)
Crop models are essential tools for assessing the threat of climate change to local and global food production1. Present models used to predict wheat grain yield are highly uncertain when simulating how crops respond to temperature2. Here we systematically tested 30 different wheat crop models of the Agricultural Model Intercomparison and Improvement Project against field experiments in which growing season mean temperatures ranged from 15 °C to 32 °C, including experiments with artificial heating. Many models simulated yields well, but were less accurate at higher temperatures. The model ensemble median was consistently more accurate in simulating the crop temperature response than any single model, regardless of the input information used. Extrapolating the model ensemble temperature response indicates that warming is already slowing yield gains at a majority of wheat-growing locations. Global wheat production is estimated to fall by 6% for each °C of further temperature increase and become more variable over space and time.
(Location: IWMI HQ Call no: e-copy only Record No: H047487)
(0.43 MB)
This paper evaluates 30-year (2013–2042) projections of the selected climatic parameters in cotton/wheat agro-climatic zone of Pakistan. A statistical bias correction procedure was adopted to eliminate the systematic errors in output of three selected general circulationmodels (GCM) under A2 emission scenario. A transfer function was developed between the GCM outputs and the observed time series of the climatic parameters (base period: 1980–2004) and applied to GCM future projections. The predictions detected seasonal shifts in rainfall and increasing temperature trend which in combination can affect the crop water requirements (CWR) at different phonological stages of the two major crops (i.e. wheat and cotton). CROPWAT model is used to optimize the shifts in sowing dates as a climate change adaptation option. The results depict that with reference to the existing sowing patterns, early sowing of wheat and late sowing of cotton will favour decreased CWR of these crops.
4 Fragaszy, S.; Closas, Alvar. 2016. Cultivating the desert: irrigation expansion and groundwater abstraction in northern state, Sudan. Water Alternatives, 9(1):139-161.
(Location: IWMI HQ Call no: e-copy only Record No: H047657)
(1.03 MB)
This study examines the socioeconomic features that underpin the expansion of groundwater-dependent irrigation in Northern State, Sudan. Groundwater development in the region serves as an economic lifeline given the poor Nile-based irrigation infrastructure and future changes in Nile hydrology. Groundwater-dependent irrigation is found to be expanding in previously uncultivated regions increasingly distant from the Nile. The study finds these historically marginal lands are targeted for capital-intensive agricultural projects because landholding patterns in traditionally cultivated areas preclude new large developments and improved infrastructure has lowered farming costs in distant terraces. Private companies and large landholders have a history of successful agricultural ventures in Northern State and are reliant on easily accessible and reliable groundwater resources for these new farms.
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