Abstract.
Two types of time scales – 10-day intervals (D) and phenological phases (P) – were applied to environmental variables for the development of statistical regression models relating to the southwest pampa region of Argentina, with the aim of detecting the effects of weather on wheat yields for the period 1977–1999. The parameters were grouped as meteorological and processed variables and indices. The processed variables used were total soil water availability (SWA) and the ratio of actual evapotranspiration to potential evapotranspiration (α), obtained from a water-balance model in which the moisture anomaly index (Z) and the Palmer drought severity index (PDSI) were calculated according to Palmer’s model. For these parameters it was possible to establish the times of year and the phenological phases with the best correlation to grain yield. The regression equation for meteorological variables on a 10-day scale provides one of the best fits. Using mixed parameters, the two models, D and P, give rise to a standard error of estimate of approximately 200 kg ha–1. Truncated models perform better on a P scale than on a D scale. The use of phenological stages improved yield assessment, particularly for those years with extreme meteorological conditions. The optimum models were tested and root-mean-square errors (RMSE) of 440 kg ha–1 and 470 kg ha–1 were obtained for P and D scales respectively.
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References
Akinremi OO, McGinn SM (1995) Usage of soil moisture models in agronomic research. In: Symposium on modeling and measurement of soil water content, Ottawa, Ontario. pp 285–295
Castañeda ME, Barros VR (1994) Las tendencias de la precipitación en el cono Sur de América al este de los Andes. Meteorologica 19:23–32
Draper NR, Smith H (1981) Applied regression analysis, 2nd edn. Wiley, New York
Gallo Candolo E (2001) Zona semiarida. In: Cuaderno de actualización 63. Consorcio Regional de Experimentación Agrícola (CREA), Buenos Aires, pp 139–142
Hatfield JL (1990) Agroclimatology of semiarid lands. Adv Soil Sci 13:9–26
Hoffmann JAJ, Nuñez SE, Vargas WM (1997) Temperature, humidity and precipitation variations in Argentina and the adjacent sub-antartic region during the present century. Meteorol Z NF 6:3–11
Landau S, Mitchell RAC, Barnett V, Colls JJ, Craigon J, Moore KL, Payne RW (1998) Testing winter wheat simulation models prediction against observed UK grain yields. Agric For Meteorol 89:85–99
Landau S, Mitchell RAC, Barnett V, Colls JJ, Craigon J, Moore KL, Payne RW (2000) A parsimonious, multiple-regression model of wheat yield response to environment. Agric For Meteorol 101:151–166
Magrin G, Diaz R, Rebella C, Santo C del, Rodríguez R (1991) Simulación del crecimiento y desarrollo de trigo en Argentina y la necesidad de información meteorológica de entrada. Anales, Congremet VI, Buenos Aires, Argentina, pp 49–50
Miralles DJ, Slafer GA (2001) Desarrollo, crecimiento y determinación de las componentes del rendimiento de trigo. In: Cuaderno de actualización 63. Consorcio Regional de Experimentación Agrícola (CREA), Buenos Aires, pp 8–17
Palmer WC (1965) Meteorological drought. Research paper 45. US Department of Commerce, Weather Bureau
Paoloni JD, Vazquez R (1984) Necesidades teóricas de agua de los cereales de invierno y probabilidad de ocurrencia de las precipitaciones como base para el balance hídrico. An Edafol Agrobiol 43:1545–1556
Roberto ZE, Casagrande G, Viglizzo E (1994) Lluvias en la Pampa Central, tendencias y variaciones del siglo. Publicación 2. Cambio Climático y Agricultura Sustentable en la Region Pampeana, Centro Regional de La Pampa-San Luis
Scian B, Donnari M (1995) El índice de anomalía de humedad z y su relación con el rendimiento de trigo en Bordenave, Buenos Aires, Argentina. Agriscientia, 12:47–51
Sierra EM, Brynsztein S (1990) Wheat yield variability in the S.E. of the province of Buenos Aires. Agric For Meteorol 49:281–290
Storch H von, Zwiers W (1999) Statistical analysis in climate research, 1st edn. Cambridge University Press, Cambridge
Travasso MI, Dellecolle R, Baldy Ch (1994) Principales factores agroclimáticos determinantes del rendimiento del trigo en el sur bonaerense. RIA 25:33–40
Acknowledgements.
This work was funded by the Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET) through grant PID-454/98. The author would like to express her thanks to Ing. E. Campi and Ing. S. Venanzi from the Instituto Nacional de Tecnología Agropecuaria (INTA) for their technical collaboration and assistance with the data. Special thanks go to the undergraduate students Ms. M. Bouza and Ms. R. Zuain (UNS). This research was carried out in accordance with and under the terms of the current laws of Argentina.
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Scian, B.V. Environmental variables for modeling wheat yields in the southwest pampa region of Argentina. Int J Biometeorol 48, 206–212 (2004). https://doi.org/10.1007/s00484-004-0198-2
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DOI: https://doi.org/10.1007/s00484-004-0198-2