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The agroclimatic analysis at farm scale

Published online by Cambridge University Press:  01 March 2007

Simone Orlandini ,
Anna Dalla Marta  and
Marco Mancini
Simone Orlandini
Affiliation:
Department of Agronomy and Land Management, University of Florence, Piazzale delle Cascine 18, 50144 Florence, Italy Email: simone.orlandini@unifi.it
Anna Dalla Marta
Affiliation:
Department of Agronomy and Land Management, University of Florence, Piazzale delle Cascine 18, 50144 Florence, Italy Email: simone.orlandini@unifi.it
Marco Mancini
Affiliation:
Department of Agronomy and Land Management, University of Florence, Piazzale delle Cascine 18, 50144 Florence, Italy Email: simone.orlandini@unifi.it
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Abstract

Research was performed in Poggio Casciano Estate (Chianti area, central Italy) with the aim of defining a general approach to analyse the spatial variability of temperature at the microscale. Hourly data were collected from a network of 27 temperature stations covering an area of about 120 ha and determination coefficients r between station pairs on the basis of different geo-topographical factors were calculated. The data were analysed in order to investigate trends describing the spatial distribution of temperature inside the study area. The results pointed out a strong effect of some topographical condition on the distribution of thermal patterns, in particular altitude and the distance from valley bottoms. The results are discussed in order to formulate a general approach for the characterisation of climatic conditions at small scale.

Keywords

topoclimateair temperaturespatial variabilitytemporal variability
Type
Research Article
Information
Meteorological Applications , Volume 13 , Issue S1 , December 2006 , pp. 87 - 93
Copyright
Royal Meteorological Society

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References

Aggarwal, P. K. 1993 Agro-ecological zoning using crop simulation models: characterization of wheat environments of India. In: Vries, F. W. T. Penning de, Teng, P. S. & Metselaar, K. (eds.), Systems Approaches for Agricultural Development. Dordrecht, The Netherlands: Kluwer, pp. 97–109.Google Scholar
Camargo, M. & Hubbard, K. 1999 Spatial and temporal variability of daily weather variables in sub-humid and semi-arid areas of the united states high plains. Agric. Forest Meteorol. 93: 141–148.CrossRefGoogle Scholar
Carlson, R. E., Enz, J. W. & Baker, D. G. 1993 Quality and variability of long term climate data relative to agriculture. Agric. Forest Meteor. 69: 61–74.CrossRefGoogle Scholar
Caruso, C. & Quarta, F. 1999. Interpolation methods comparison. Comput. Math. Appl. 35 (12): 109–126.CrossRefGoogle Scholar
Chapman, S. C., Edmeadas, G. O. & Crossa, J. 1996 Pattern analysis of gains from selection for drought tolerance in tropical maize populations. In: Cooper, M. & Hammer, G. L. (eds.), Plant Adaptation and Crop Improvement. Wallingford, UK: CAB International, pp. 513–528.Google Scholar
Dalla Marta, A., Mancini, M. & Orlandini, S. 2003 Analysis of interpolation methods applied at different spatial scales. In: Proceedings of the Sixth European Conference ‘Applications of Meteorology’, Rome, Italy, 15–19 September 2003 (CD-ROM).Google Scholar
Godwin, R. J., Richards, T. E., Wood, G. A., Welsh, J. P. & Knight, S. M. 2003 An economic analysis of the potential for precision farming in UK cereal production. Biosyst. Eng. 84 (4): 533–545.CrossRefGoogle Scholar
Hammer, G. L., Kropff, M. J., Zincalir, T. R. & Porter, J. R. 2002 Future contributions of crop modeling—from heuristics and supporting decision making to understanding genetic regulation and aiding crop improvement. Eur. J. Agron. 18: 15–31.CrossRefGoogle Scholar
Harcum, J. B. & Loftis, J. C. 1987 Spatial interpolation of Penman evapotranspiration. Trans. Am. Soc. Agric. Eng. 30 (1): 129–136.CrossRefGoogle Scholar
Hoogenboom, G. 2000 Contribution of agrometeorology to the simulation of crop production and its applications. Agric. Forest Meteorol. 103: 137–157.CrossRefGoogle Scholar
Hopkins, J. S. 1979 The spatial variability of daily temperature and sunshine over uniform terrain. Meteorol. Mag. 106: 278–292.Google Scholar
Hubbard, K. G. 1994 Spatial variability of daily weather variables in the high plains of the USA. Agric. Forest Meteorol. 68: 29–41.CrossRefGoogle Scholar
Maracchi, G. 2003 Meteorologia e climatologia applicate. Florence, Italy: Editrice L’Universo.Google Scholar
Maracchi, G., Dunkel, Z. & Orlandini, S. 2002 European agrometeorological applications. In: Sivakumar, M. V. K. (ed.), Proceedings of the Inter-Regional Workshop ‘Improving Agrometeorological Bulletins’, Bridgetown, Barbados, 15–19 October 2001. Geneva, Switzerland: World Meteorological Organization, pp. 261–274.Google Scholar
Meinke, H. & Hammer, G. L. 1995 A peanut simulation model. II: Assessing regional production potential. Agron. J. 87: 1093–1099.CrossRefGoogle Scholar
Neményi, M., Mesterhàzi, P. A., Pecze, Z. S. & Stepan, Z. 2003 The role of GIS and GPS in precision farming. Comput. Electron. Agric. 40: 45–55.CrossRefGoogle Scholar
Orlandini, S., Moriondo, M. & Mancini, M. 2000 Bio-climatic characterisation of hilly area. In: Proceedings of the Third European Conference ‘Applied Climatology’, 16–20 October 2000, Pisa, Italy (CD ROM).Google Scholar
Qiyao, L., Baopu, F. & Jingming, Y. 1987 Methods calculating the spatial distribution of agroclimatic resources in mountainous areas and climatic effects of microtopography. Acta Meteorol. Sin. 2 (3): 380–393.Google Scholar
Semenov, M. A. & Porter, J. P. 1995. Climatic variability and the modelling of crop yields. Agric. Forest Meteorol. 73: 265–283.CrossRefGoogle Scholar
Shorter, R., Lawn, R. J. & Hammer, G. L. 1991 Improving genotypic adaptation in crops—-a role for breeders, physiologists and modellers. Exp. Agric. 27: 155–175.CrossRefGoogle Scholar
Soderstrom, M. & Magnusson, B. 1995. Assesment of local agroclimatological conditions. Agric. Forest Meteorol. 72: 243–260.CrossRefGoogle Scholar
Soltani, A., Khooie, F. R., Ghassemi-Golezani, K. & Moghaddam, M. 2000 Thresholds for chickpea leaf expansion and transpiration response to soil water deficit. Field Crops Res. 68: 205–210.CrossRefGoogle Scholar
Thornton, P. E., Running, S. W. & White, M. A. 1997 Generating surfaces of daily meteorological variables over large regions of complex terrain. J. Hydrol. 190: 214–251.CrossRefGoogle Scholar