Estimating hourly net radiation for leaf wetness duration using the Penman-Monteith equation |
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| Authors: | P C Sentelhas T J Gillespie |
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| Institution: | Agrometeorology Group, Department of Exact Sciences, ESALQ, University of S?o Paulo, Piracicaba, SP, Brazil
Agrometeorology Group, Department of Land Resource Science, Ontario Agricultural College, University of Guelph, Guelph, ON, Canada
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| Abstract: | Summary Leaf wetness duration (LWD) is related to plant disease occurrence and is therefore a key parameter in agrometeorology. As
LWD is seldom measured at standard weather stations, it must be estimated in order to ensure the effectiveness of warning
systems and the scheduling of chemical disease control. Among the models used to estimate LWD, those that use physical principles
of dew formation and dew and/or rain evaporation have shown good portability and sufficiently accurate results for operational
use. However, the requirement of net radiation (Rn) is a disadvantage foroperational physical models, since this variable
is usually not measured over crops or even at standard weather stations. With the objective of proposing a solution for this
problem, this study has evaluated the ability of four models to estimate hourly Rn and their impact on LWD estimates using
a Penman-Monteith approach. A field experiment was carried out in Elora, Ontario, Canada, with measurements of LWD, Rn and
other meteorological variables over mowed turfgrass for a 58 day period during the growing season of 2003. Four models for
estimating hourly Rn based on different combinations of incoming solar radiation (Rg), airtemperature (T), relative humidity
(RH), cloud cover (CC) and cloud height (CH), were evaluated. Measured and estimated hourly Rn values were applied in a Penman-Monteith
model to estimate LWD. Correlating measured and estimated Rn, we observed that all models performed well in terms of estimating
hourly Rn. However, when cloud data were used the models overestimated positive Rn and underestimated negative Rn. When only
Rg and T were used to estimate hourly Rn, the model underestimated positive Rn and no tendency was observed for negative Rn.
The best performance was obtained with Model I, which presented, in general, the smallest mean absolute error (MAE) and the
highest C-index. When measured LWD was compared to the Penman-Monteith LWD, calculated with measured and estimated Rn, few
differences were observed. Both precision and accuracy were high, with the slopes of the relationships ranging from 0.96 to
1.02 and R2 from 0.85 to 0.92, resulting in C-indices between 0.87 and 0.93. The LWD mean absolute errors associated with Rn estimates
were between 1.0 and 1.5 h, which is sufficient for use in plant disease management schemes.
Authors’ addresses: Paulo C. Sentelhas, Agrometeorology Group, Department of Exact Sciences, ESALQ, University of S?o Paulo,
P.O. Box 9, 13418-900, Piracicaba, SP, Brazil; Terry J. Gillespie, Agrometeorology Group, Department of Land Resource Science,
Ontario Agricultural College, University of Guelph, NIG-2W1, Guelph, ON, Canada. |
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