Assessing the impacts of drought on UK wheat production
| dc.contributor.advisor | Knox, Jerry W. | |
| dc.contributor.advisor | Hess, Tim M. | |
| dc.contributor.author | Clarke, David | |
| dc.date.accessioned | 2017-08-16T10:58:44Z | |
| dc.date.available | 2017-08-16T10:58:44Z | |
| dc.date.issued | 2017-01 | |
| dc.description.abstract | Water limitations typically reduce UK wheat yields on average by 1-2 t ha- 1 , although this can be considerably more in extreme drought years. With the frequency and intensity of droughts expected to increase under a changing climate, an improved understanding of the impacts of drought and better systems for agricultural drought monitoring are required. Previous studies, however, have found no significant relationship between UK wheat yields and commonly employed drought severity indices (DSI). Using historical (1911-2015) daily weather data for Cambridge the Standardized Precipitation Index (SPI), the Standardized Precipitation and Evapotranspiration Index (SPEI), the Palmer Drought Severity Index (PDSI) and the Potential Soil Moisture Deficit (PSMD) were calculated on various time steps (e.g. 1-12 months for SPI and SPEI) to provide a drought record for the site. A wheat crop growth simulation model (Sirius) was then used to simulate the effects of the identified historic droughts on wheat yields. The use of the Sirius crop model removed the non-drought related yield losses (e.g. disease, pests, and lodging) present in national yield records. Using the Spearman’s Rho correlation coefficient (r) the simulated yield record was then correlated against the different DSIs. The droughts of 1921, 1976 and 2010 were found to be the most extreme in term of yield reduction. In addition, there were also two noticeable periods of successive yield loss in the early 1940s and between 2009 and 2013. All DSIs showed significant (p = 0.05) correlations on monthly time steps between April and August. The SPI, SPEI and PSMD showed a strong correlation to wheat yields (r = 0.64 to 0.66) on time steps incorporating the end of the ‘construction’ and the entirety of the ‘production’ phases for wheat growth. The PDSI showed the weakest correlation (r = 0.55), although it may be helpful in identifying yield-limiting droughts earlier in the year. The research has contributed new scientific insights and understanding of the impacts of historic droughts on wheat productivity, and demonstrated the application of DSIs in monitoring potentially yield-limiting droughts. The research also provides new evidence to support developments in UK food security and drought management for agriculture. | en_UK |
| dc.identifier.uri | http://dspace.lib.cranfield.ac.uk/handle/1826/12321 | |
| dc.publisher | Cranfield University | en_UK |
| dc.rights | © Cranfield University, 2017. All rights reserved. No part of this publication may be reproduced without the written permission of the copyright holder. | en_UK |
| dc.subject | Drought severity indices | en_UK |
| dc.subject | Sirius crop model | en_UK |
| dc.subject | Simulation | en_UK |
| dc.subject | Cereals | en_UK |
| dc.subject | Agricultural drought | en_UK |
| dc.title | Assessing the impacts of drought on UK wheat production | en_UK |
| dc.type | Thesis or dissertation | en_UK |
| dc.type.qualificationlevel | Masters | en_UK |
| dc.type.qualificationname | MRes | en_UK |