Distribution Of Hydrological Losses For Varying Rainfall And Antecedent Wetness Conditions

Hydrological loss is a vital component in many hydrological models, which are usedin forecasting floods and evaluating water resources for both surface and subsurface flows. Due to the complex and random nature of the rainfall runoff process, hydrological losses are not yet fully understood. Consequently, practitioners often use representative values of the losses for design applications such as rainfall-runoff modelling which has led to inaccurate quantification of water quantities in the resulting applications. The existing hydrological loss models must be revisited and modellers should be encouraged to utilise other available data sets. This study is based on three unregulated catchments situated in Mt. Lofty Ranges of South Australia (SA). The paper focuses on conceptual models for: initial loss (IL), continuing loss (CL) and proportional loss (PL) with rainfall characteristics (total rainfall (TR) and storm duration (D)), and antecedent wetness (AW) conditions. The paper introduces two methods that can be implemented to estimate IL as a function of TR, D and AW. The IL distribution patterns and parameters for the study catchments are determined using multivariate analysis and descriptive statistics. The possibility of generalising the methods and the limitations of this are also discussed. This study will yield improvements to existing loss models and will encourage practitioners to utilise multiple data sets to estimate losses, instead of using hypothetical or representative values to generalise real situations.

Spatial portability of numerical models of leaf wetness duration based on empirical approaches

Leaf wetness duration (LWD) models based on empirical approaches offer practical advantages over physically based models in agricultural applications, but their spatial portability is questionable because they may be biased to the climatic conditions under which they were developed. In our study, spatial portability of three LWD models with empirical characteristics - a RH threshold model, a decision tree model with wind speed correction, and a fuzzy logic model - was evaluated using weather data collected in Brazil, Canada, Costa Rica, Italy and the USA. The fuzzy logic model was more accurate than the other models in estimating LWD measured by painted leaf wetness sensors. The fraction of correct estimates for the fuzzy logic model was greater (0.87) than for the other models (0.85-0.86) across 28 sites where painted sensors were installed, and the degree of agreement k statistic between the model and painted sensors was greater for the fuzzy logic model (0.71) than that for the other models (0.64-0.66). Values of the k statistic for the fuzzy logic model were also less variable across sites than those of the other models. When model estimates were compared with measurements from unpainted leaf wetness sensors, the fuzzy logic model had less mean absolute error (2.5 h day(-1)) than other models (2.6-2.7 h day(-1)) after the model was calibrated for the unpainted sensors. The results suggest that the fuzzy logic model has greater spatial portability than the other models evaluated and merits further validation in comparison with physical models under a wider range of climate conditions. (C) 2010 Elsevier B.V. All rights reserved.

Suitability of relative humidity as an estimator of leaf wetness duration

Leaf wetness duration (LWD) is a key parameter in agricultural meteorology since it is related to epidemiology of many important crops, controlling pathogen infection and development rates. Because LWD is not widely measured, several methods have been developed to estimate it from weather data. 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, but their complexity is a disadvantage for operational use. Alternatively, empirical models have been used despite their limitations. The simplest empirical models use only relative humidity data. The objective of this study was to evaluate the performance of three RH-based empirical models to estimate LWD in four regions around the world that have different climate conditions. Hourly LWD, air temperature, and relative humidity data were obtained from Ames, IA (USA), Elora, Ontario (Canada), Florence, Toscany (Italy), and Piracicaba, Sao Paulo State (Brazil). These data were used to evaluate the performance of the following empirical LWD estimation models: constant RH threshold (RH >= 90%); dew point depression (DPD); and extended RH threshold (EXT_RH). Different performance of the models was observed in the four locations. In Ames, Elora and Piracicaba, the RH >= 90% and DPD models underestimated LWD, whereas in Florence these methods overestimated LWD, especially for shorter wet periods. When the EXT_RH model was used, LWD was overestimated for all locations, with a significant increase in the errors. In general, the RH >= 90% model performed best, presenting the highest general fraction of correct estimates (F(C)), between 0.87 and 0.92, and the lowest false alarm ratio (F(AR)), between 0.02 and 0.31. The use of specific thresholds for each location improved accuracy of the RH model substantially, even when independent data were used; MAE ranged from 1.23 to 1.89 h, which is very similar to errors obtained with published physical models for LWD estimation. Based on these results, we concluded that, if calibrated locally, LWD can be estimated with acceptable accuracy by RH above a specific threshold, and that the EXT_RH method was unsuitable for estimating LWD at the locations used in this study. (C) 2007 Elsevier B.V. All rights reserved.

Estimating hourly net radiation for leaf wetness duration using the Penman-Monteith equation

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 R-2 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 1.5h, which is sufficient for use in plant disease management schemes.

The Infection of Soybean Leaves by Phakopsora pachyrhizi during Conditions of Discontinuous Wetness

The ability of Phakopsora pachyrhizi to cause infection under conditions of discontinuous wetness was investigated. In in vitro experiments, droplets of a uredospore suspension were deposited onto the surface of polystyrene. After an initial wetting period of either 1, 2 or 4 h, the drops were dried for different time intervals and then the wetness was restored for 11, 10 or 8 h. Germination and appressorium formation were evaluated. In in vivo experiments, soybean plants were inoculated with a uredospore suspension. Leaf wetness was interrupted for 1, 3 or 6 h after initial wetting periods of 1, 2 or 4 h. Then, the wetting was re-established for 11, 10 or 8 h, respectively. Rust severity was evaluated 14 days after inoculation. The germination of the spores and the formation of the appressoria on the soybean leaves after different periods of wetness were also quantified in vivo by scanning electron microscopy. P. pachyrhizi showed a high infective capacity during short periods of time. An interruption of wetness after 1 h caused average reductions in germination from 56 to 75% and in appressorium formation from 84 to 96%. Rust severity was lower in all of the in vivo treatments with discontinuous wetness when compared to the control plants. Rust severity was zero when the interruption of wetness occurred 4 h after the initial wetting. Wetting interruptions after 1 and 2 h reduced the average rust severity by 83 and 77%, respectively. The germination of the uredospores on the soybean leaves occurred after 2 h of wetness, with a maximum germination appearing after 4 h of wetness. Wetness interruption affected mainly the spores that had initiated the germination.

Prepenetration Stages of Guignardia psidii in Guava: Effects of Temperature, Wetness Duration and Fruit Age

This study examined the effects of temperature and wetness duration in vitro and in vivo as well as the effects of fruit age on germination and appressoria formation by conidia of Guignardia psidii, the causal agent of black spot disease in guava fruit. The temperatures tested for in vitro and in vivo experiments were 10, 15, 20, 25, 30, 35 and 40 degrees C. The wetness periods studied were 6, 12, 24, 36 and 48 h in vitro and 6, 12 and 24 h in vivo. Fruit 10, 35, 60, 85 and 110-days old were inoculated and maintained at 25 degrees C, with a wetness period of 24 h. Temperature and wetness duration affected the variables evaluated in vitro and in vivo. All variables reached their maximum values at between 25 and 30 degrees C with a wetness duration of 24 h in vivo and 48 h in vitro. These conditions resulted in 31.3% conidia germination, 33.6% appressoria formation and 32.5% appressoria melanization in vitro, and 50.4% conidia germination and 9.5% appressoria formation in vivo. Fruit age also influenced these factors. As fruit age increased, conidia germination and appressoria formation gradually increased. Conidia germination and appressoria formation were 10.8% and 2.3%, respectively, in 10-day-old fruits. In 110-day-old fruits, conidia germination and appressoria formation were 42.5% and 23.2% respectively.

Modelling the progress of Asiatic citrus canker on Tahiti lime in relation to temperature and leaf wetness

The combined effect of temperature (15A degrees C, 20A degrees C, 25A degrees C, 30A degrees C, 35A degrees C, 40A degrees C and 42A degrees C) and leaf wetness duration (0, 4, 8 12, 16, 20 and 24 h) on infection and development of Asiatic citrus canker (Xanthomonas citri subsp. citri) on Tahiti lime plant was examined in growth chambers. No disease developed at 42A degrees C and zero hours of leaf wetness. Periods of leaf wetness as short as 4 h were sufficient for citrus canker infection. However, a longer leaf duration wetness (24 h) did not result in much increase in the incidence of citrus canker, but led to twice the number of lesions and four times the disease severity. Temperature was the greatest factor influencing disease development. At optimum temperatures (25-35A degrees C), there was 100% disease incidence. Maximum disease development was observed at 30-35A degrees C, with up to a 12-fold increase in lesion density, a 10-fold increase in lesion size and a 60-fold increase in disease severity.

Spatial heterogeneity of leaf wetness duration in apple trees and its influence on performance of a warning system for sooty blotch and flyspeck

To determine the effect of sensor placement on the performance of a disease-warning system for sooty blotch and flyspeck (SBFS), we measured leaf wetness duration (LWD) at 12 canopy positions in apple trees, then simulated operation of the disease-warning system using LWD measurements from different parts of the canopy. LWD sensors were placed in four trees within one Iowa orchard during two growing seasons, and in one tree in each of four orchards during a single growing season. The LWD measurements revealed substantial heterogeneity among sensor locations. In all data sets, the upper, eastern portion of the canopy had the longest mean daily LWD, and was the first site to form dew and the last to dry. The lower, western portion of the canopy averaged about 3 It less LWD per day than the top of the canopy, and was the last zone where dew formed and the first to dry off. On about 25% of nights when dew occurred in the top of the canopy, no dew formed in the lower, western canopy. Intracanopy variability of LWD was more pronounced when dew was the sole source of wetness than on days when rainfall occurred. Daily LWD in the upper, eastern portion of the canopy was slightly less than reference measurements made at a 0.7-m height over turfgrass located near the orchard. When LWD measurements from several canopy positions were input to the SBFS warning system, timing of occurrence of a fungicide-spray threshold varied by as much as 30 days among canopy positions. Under Iowa conditions, placement of an LWD sensor at an unobstructed site over turfgrass was a fairly accurate surrogate for the wettest part of the canopy. Therefore, such an extra-canopy LWD sensor might be substituted for a within-canopy sensor to enhance operational reliability of the SBFS warning system.

Enamel Wetness Effects on Bond Strength Using Different Adhesive Systems

Objective: To evaluate, through the application of different dentin bonding systems, the influence of wetness on shear bond strength in enamel. Methods: This study evaluated three etch-and-rinse adhesive systems (Scotchbond MP [used with and without primer]; Singlebond; and Prime&Bond 2.1) and two self-etching adhesive systems (Clearfil SE Bond; and Xeno IV). Flat bovine enamel surfaces were either air-dried for 30 seconds or blotted with absorbent paper after acid-etching for the conventional bonding agents or before the application of self-etching bonding agents. The resin composite EsthetX was bonded to flat surfaces that had been treated with one of the adhesives, following the manufacturer`s instructions. After being stored in water at 37 degrees C for one week, bonded specimens were broken in shear. Data were evaluated with two-way analysis of variance (ANOVA) and Student-Newman-Keuls tests (alpha=0.05). For comparing each condition individually, regardless of the adhesive or wetness condition, a one-way ANOVA and a Student-Newman-Keuls test (alpha=0.05) were applied. Results: The two-way ANOVA showed significant differences among adhesive systems. An interaction effect was also observed (p < 0.05), but wetness did not influence shear bond strength (p=0.98). The one-way ANOVA showed that the all-in-one adhesive was the only material influenced by the presence of water at the enamel`s surface. Conclusion: The all-in-one adhesive behaved differently depending on whether the enamel surface was dry or wet.

Effect of soil wetness on air composition and nitrous oxide emission in a loam soil

Selostus: Maan märkyyden vaikutus ilman koostumukseen ja dityppioksidiemissioon hiuemaassa

Effect of temperature, leaf wetness, and rainfall on the production of Guignardia citricarpa ascospores and on back spot severity on sweet orange

The black spot of citrus (Citrus sp.) is caused by Guignardia citricarpa with ascospore production depending on temperature, leaf wetness, and rainfall. The number of ascospores produced was monitored using a spore trap and climatic factors were recorded using an automated meteorological station of 'Natal' and 'Valencia' sweet orange (Citrus sinensis) orchards in Mogi Guaçu in the state of São Paulo, Brazil, from November 2000 to March 2001. The fruits were bagged to prevent infection and the bags removed from different sets of fruit for one week during each of the 18 weeks of the season in both orchards. Ascospores were produced during the entire experimental period, from spring through summer, primarily after rain events. In both orchards, ascospore production reached a peak in January and February. Ascospore production was related to leaf wetness only in the Natal orange orchard but was not related to total rainfall or temperature in either orchard. Disease was most severe on fruit exposed the 7th, 8th, and 13th weeks after beginning the experiment in both cultivars as well as after the 16th week for 'Natal'. There was a strong relationship between disease severity and total rainfall for both orchards and a weak correlation between temperature and severity in the 'Natal' block only. There was no relationship between severity and leaf wetness or ascospore numbers.

Effect of temperature, wetness duration and cultivar on the development of anthracnose in guava fruits

The development of a large number of postharvest diseases is closely associated with fruit ripeness. Environmental conditions may affect both the pathogen development and the fruit ripening rate. The aim of this study was to determine the most favorable temperature and wetness duration to the development of anthracnose in guava fruits. Cultivars 'Kumagai' (white pulp) and 'Pedro Sato' (red pulp) were inoculated with a conidial suspension of Colletotrichum gloeosporioides and C. acutatum and incubated at constant temperature ranging from 10 to 35ºC and wetness duration of 6 and 24 hours. Disease severity and incidence were evaluated at every two days during 12 days. No infection occurred at 10 and 35ºC, regardless of the wetness duration. The optimum conditions for fruit infection were 26 and 27ºC for 'Kumagai' and 25 and 26ºC for 'Pedro Sato', adopting 24 hours of wetness. In general, the disease development in 'Kumagai' cultivar was more affected by the wetness period, compared to 'Pedro Sato'. Disease severity for 'Kumagai' fruits was maximal between 25 and 30ºC , depending on the Colletotrichum species. Regarding 'Pedro Sato', the mean diameter of lesions was greater in fruits stored at 20, 25 and 30ºC , compared to 'Kumagai' cultivar, depending on the wetness period and the species. The incubation period (between 6 and 7 days) and the latent period (between 8 and 10 days) were minimal at 30ºC. The data generated in this study will be useful either for the development of a disease warning system or for the increase in the shelf life of guavas in the postharvest.

Influence of temperature and leaf wetness duration in the severity of Cercospora leaf spot of beet

ABSTRACT In the present study, the influence of temperature (15, 20, 25, 30 and 35°C) and leaf wetness period (6, 12, 24 and 48 hours) on the severity of Cercospora leaf spot of beet, caused by Cercospora beticola, was studied under controlled conditions. Lesion density was influenced by temperature and leaf wetness duration (P<0.05). Data were subjected to nonlinear regression analysis. The generalized beta function was used for fitting the disease severity and temperature data, while a logistic function was chosen to represent the effect of leaf wetness on the severity of Cercospora leaf spot. The response surface resultant of the product of the two functions was expressed as ES = 0.0001105 * (((x-8)2.294387) * ((36-x)0.955017)) * (0.39219/(1+25.93072 * exp (-0.16704*y))), where: ES represents the estimated severity value (0.1); x, the temperature (ºC) and y, the leaf wetness duration (hours). This model should be validated under field conditions to assess its use as a computational forecast system for Cercospora leaf spot of beet.