Evaluation of a Penman-Monteith approach to provide a “standard” leaf wetness duration estimate

Leaf wetness duration (LWD) is a key parameter for disease-warning systems since the risk of outbreaks of many plant diseases is directly proportional to this environmental variable. However, LWD is not widely measured so several methods have been developed to estimate it from weather data. Methods based on the physical principals of dew deposition and dew or rain evaporation have shown good portability and sufficiently accurate results for operational use. In this study, a Penman-Monteith approach to modeling LWD on a wetness sensor located in a weather station was investigated. This study was undertaken because recent observations revealed that an LWD sensor located about 30 cm above a turf surface provided useful estimates of LWD in various nearby crops, therefore modeling such a sensor and location may be a simpler “standard” alternative to modeling LWD in a crop canopy.

LWD was measured over turfgrass at different heights (30, 110, 190 cm from the ground) and at the top of three different crops: coffee, corn, and grape, using painted flat-plate sensors. At the same times and places, automatic weather stations measured air temperature, RH, wind speed, and net radiation at 190 cm above turf. A Penman-Monteith approach was able to estimate sensor LWD over turfgrass with good accuracy and precision, using an aerodynamic resistance based on the wind speed to estimate wetness duration at 110 and 30 cm. The model overestimated LWD by 3.3% at 190 cm (R2 = 0.92), 1.5% at 110 cm (R2 = 0.87), and 5.7% at 30 cm (R2 = 0.89). When modeled LWD for a 30 cm sensor over turf was correlated with crop LWD, good agreement was observed, with an overestimation of 7.8% and a coefficient of determination of 0.88 for all three crops combined.

The requirement for an estimation of net radiation (Rn) is a disadvantage for operational physical models, since this variable is seldom measured directly. The effect of different estimates of Rn on the accuracy and precision of LWD estimates from our model was tested. Four different available methods to estimate Rn were used, based on combinations of incoming solar radiation, air temperature, RH, cloud cover and cloud height. When these estimates were used in place of measured Rn in the Penman-Monteith model there was no significant degradation in the accuracy of the LWD estimates, while the precision of the estimates (R2 –values) varied between 0.85 – 0.92, depending on the complexity of the Rn models.

We conclude that a Penman-Monteith model for a fixed sensor size, albedo and exposure over turf may be a very useful “standard” tool to estimate LWD for use in plant disease management schemes.