Estimation Of Reference Crop Evapotranspiration Using Fuzzy State Models

Daily evapotranspiration (ET) rates are needed for irrigation scheduling. Owing to the difficulty of obtaining accurate field measurements, ET rates are commonly estimated from weather parameters. A few empirical or semi–empirical methods have been developed for assessing daily reference crop ET, which is converted to actual crop ET using crop coefficients. The FAO Penman–Monteith method, which is now accepted as the standard method for the computation of daily reference ET, is sophisticated. It requires several input parameters, some of which have no actual measurements but are estimated from measured weather parameters. In this study, we examined the suitability of fuzzy logic for estimating daily reference ET with simpler and fewer parameters. Two fuzzy evapotranspiration models, using two or three input parameters, were developed and applied to estimate grass ET. Independent weather parameters from sites representing arid and humid climates were used to test the models. The fuzzy estimated ET values were compared with direct ET measurements from grass–covered weighing lysimeters, and with ET estimations obtained using the FAO Penman–Monteith and the Hargreaves–Samani equations. The estimated ET values from a fuzzy model using three input parameters (Syx = 0.54 mm, r2 = 0.90) were found to be comparable to ET values estimated with the FAO Penman–Monteith equation (Syx = 0.50 mm, r2 = 0.91) and were more accurate than those obtained by the Hargreaves–Samani equation (Syx = 0.66 mm, r2 = 0.53). These results show that fuzzy evapotranspiration models with simpler and fewer input parameters can yield accurate estimation of ET

Optimization Of Fuzzy Evapotranspiration Model Through Neural Training With Input–Output Examples

In a previous study, we demonstrated that fuzzy evapotranspiration (ET) models can achieve accurate estimation of daily ET comparable to the FAO Penman–Monteith equation, and showed the advantages of the fuzzy approach over other methods. The estimation accuracy of the fuzzy models, however, depended on the shape of the membership functions and the control rules built by trial–and–error methods. This paper shows how the trial and error drawback is eliminated with the application of a fuzzy–neural system, which combines the advantages of fuzzy logic (FL) and artificial neural networks (ANN). The strategy consisted of fusing the FL and ANN on a conceptual and structural basis. The neural component provided supervised learning capabilities for optimizing the membership functions and extracting fuzzy rules from a set of input–output examples selected to cover the data hyperspace of the sites evaluated. The model input parameters were solar irradiance, relative humidity, wind speed, and air temperature difference. The optimized model was applied to estimate reference ET using independent climatic data from the sites, and the estimates were compared with direct ET measurements from grass–covered lysimeters and estimations with the FAO Penman–Monteith equation. The model–estimated ET vs. lysimeter–measured ET gave a coefficient of determination (r2) value of 0.88 and a standard error of the estimate (Syx) of 0.48 mm d–1. For the same set of independent data, the FAO Penman–Monteith–estimated ET vs. lysimeter–measured ET gave an r2 value of 0.85 and an Syx value of 0.56 mm d–1. These results show that the optimized fuzzy–neural–model is reasonably accurate, and is comparable to the FAO Penman–Monteith equation. This approach can provide an easy and efficient means of tuning fuzzy ET models

Ocean Chlorophyll Studies from a U-2 Aircraft Platform

Chlorophyll gradient maps of large ocean areas were generated from U-2 ocean color scanner data obtained over test sites in the Pacific and Atlantic Oceans. The delineation of oceanic features using the upward radiant intensity relies on an analysis method which presupposes that radiation backscattered from the atmosphere and ocean surface can be properly modeled using a measurement made at 778 nm. An estimation of the chlorophyll concentration was performed by properly ratioing radiances measured at 472 nm and 548 nm after removing the atmospheric effects. The correlation between the remotely sensed data and in-situ surface chlorophyll measurements was validated in two sets of data. The results show that the correlation between the in-situ measured chlorophyll and the derived quantity is a negative exponential function and the correlation coefficient was calculated to be -0.965

Electron mean free path from angle-dependent photoelectron spectroscopy of aerosol particles

We propose angle-resolved photoelectron spectroscopy of aerosol particles as an alternative way to determine the electron mean free path of low energy electrons in solid and liquid materials. The mean free path is obtained from fits of simulated photoemission images to experimental ones over a broad range of different aerosol particle sizes. The principal advantage of the aerosol approach is twofold. Firstly, aerosol photoemission studies can be performed for many different materials, including liquids. Secondly, the size-dependent anisotropy of the photoelectrons can be exploited in addition to size-dependent changes in their kinetic energy. These finite size effects depend in different ways on the mean free path and thus provide more information on the mean free path than corresponding liquid jet, thin film, or bulk data. The present contribution is a proof of principle employing a simple model for the photoemission of electrons and preliminary experimental data for potassium chloride aerosol particles

Calculation of Turbulent Subsonic Diffuser Flows Using the NPARC Navier-Stokes Code

Axisymmetric subsonic diffuser flows were calculated with the NPARC Navier-Stokes code in order to determine the effects various code features have on the flow solutions. The code features examined in this work were turbulence models and boundary conditions. Four turbulence models available in NPARC were used: the Baldwin-Lomax algebraic model, the Baldwin-Barth one-equation model, and the Chien kappa-epsilon and Wilcox kappa-omega two-equation models. The three boundary conditions examined were the free boundary, the mass flux boundary and the subsonic outflow with variable static pressure. In addition to boundary condition type, the geometry downstream of the diffuser was varied to see if upstream influences were present. The NPARC results are compared with experimental data and recommendations are given for using NPARC to compute similar flows

Determinants of Performance in Smallholder Farmer Groups in Uganda

The performance of farmer groups is critical for the success of the farmer-led Agricultural Extension approach currently used in Uganda. This study examines factors affecting performance of farmer groups accessing agricultural extension and advisory services from the National Agricultural Advisory Services in Eastern Uganda. The study collected data 200 members of 19 farmer groups in Eastern Uganda. Performance of farmer groups was the dependent variable, which was perceived to be influenced by individual members’ objectives, participation culture, power distance, structure of task, perceived equity, reward allocation and participation in group activities. Farmer group performance had a statistically significant positive relationship with power distance and perceived equity. Group participation culture and structure of tasks had a statistically negative relationship with group performance. Members tended to deflect group losses to factors beyond the seasonality of group activities, quality of farm inputs, and poor training delivered by advisory service providers. The advisory service providers and farmer group members need to use the political and social capital possessed by the local leadership, groups and community members for enhancing support and collective participation of the community in farmer groups. Since farmer groups are a sub-set of wider community, this empirical study brings into perspective the role of community culture in influencing performance of farmer groups in smallholder farming communities

The use of DiazaConTM to limit fertility in grey squirrels

Mayle, B., Ferryman, M., Peace, A., Yoder, C.A., Miller, L.A., Cowan, D

Nicarbazin OvoControl G Bait Reduces Hatchability of Eggs Laid by Resident Canada Geese in Oregon

Expanding populations of resident Canada geese (Branta canadensis) are resulting in increased conflicts with humans. Nonlethal and humane means are needed for managing Canada goose flocks at a variety of sites, including golf courses, industrial parks, government sites, and city parks. Decreased egg production and hatching are side effects of nicarbazin, a veterinary drug used to treat coccidiosis in chickens. Capitalizing on these effects, we developed nicarbazin as a reproductive inhibitor for Canada geese and conducted a field efficacy study. We recruited study sites in 2002 and 2003. Following laboratory testing, we conducted a field efficacy trial of nicarbazin for reducing the hatchability of Canada goose eggs in spring 2004 in Oregon, USA. The study began in February 2004 at 10 sites in Oregon, with 2 control and 3 treated sites on each side of the Cascades. We fed bait daily to resident Canada geese for approximately 6 weeks. We located and monitored nests until hatching or ≥5 days beyond the expected hatching date to determine hatchability. We completed data collection in May 2004. Geese consumed 8,000 kg of bait, with 5,100 kg of OvoControl G* (Innolytics, LLC, Rancho Santa Fe, CA) 2,500-ppm nicarbazin bait consumed among 6 treated sites and 2,900 kg of untreated bait consumed among 4 control sites. We monitored 63 nests at treated sites and 46 nests at control sites to determine hatching success of eggs. There was a 62% reduction in the percentage of nests with 100% hatchability at treated sites as compared to controls. There was a 93% increase in the percentage of nests at treated sites with 0% hatchability as compared to nests with no eggs hatching at control sites. Hatchability from treated sites versus control sites was reduced 36%(F=5.72, P=0.0622). We submitted results from this study to support Environmental Protection Agency registration of nicarbazin as a reproductive inhibitor for use in Canada geese. We have shown that treatment of resident Canada geese with OvoControl G 2,500-ppm nicarbazin bait by licensed, trained applicators immediately prior to and during the breeding season can reduce hatchability of eggs laid by treated geese, thereby reducing recruitment of goslings into problem resident Canada goose populations. ( JOURNAL OF WILDLIFE MANAGEMENT 71(1):135–143; 2007