Inclusive Multiple Model Using Hybrid Artificial Neural Networks for Predicting Evaporation

Predicting evaporation is essential for managing water resources in basins. Improvement of the prediction accuracy is essential to identify adequate inputs on evaporation. In this study, artificial neural network (ANN) is coupled with several evolutionary algorithms, i.e., capuchin search algorithm (CSA), firefly algorithm (FFA), sine cosine algorithm (SCA), and genetic algorithm (GA) for robust training to predict daily evaporation of seven synoptic stations with different climates. The inclusive multiple model (IMM) is then used to predict evaporation based on established hybrid ANN models. The adjusting model parameters of the current study is a major challenge. Also, another challenge is the selection of the best inputs to the models. The IMM model had significantly improved the root mean square error (RMSE) and Nash Sutcliffe efficiency (NSE) values of all the proposed models. The results for all stations indicated that the IMM model and ANN-CSA could outperform other models. The RMSE of the IMM was 18, 21, 22, 30, and 43% lower than those of the ANN-CSA, ANN-SCA, ANN-FFA, ANN-GA, and ANN models in the Sharekord station. The MAE of the IMM was 0.112 mm/day, while it was 0.189 mm/day, 0.267 mm/day, 0.267 mm/day, 0.389 mm/day, 0.456 mm/day, and 0.512 mm/day for the ANN-CSA, ANN-SCA, and ANN-FFA, ANN-GA, and ANN models, respectively, in the Tehran station. The current study proved that the inclusive multiple models based on improved ANN models considering the fuzzy reasoning had the high ability to predict evaporation.

Dynamic Changes in Anthocyanin Accumulation and Cellular Antioxidant Activities in Two Varieties of Grape Berries during Fruit Maturation under Different Climates

As popularly consumed fruit berries, grapes are widely planted and processed into products, such as raisins and wine. In order to identify the influences of different climatic conditions on grape coloring and quality formation, we selected two common varieties of grape berries, ‘Red Globe’ and ‘Xin Yu’, for investigation. Grapes were separately grown in different climates, such as a temperate continental arid climate and a temperate continental desert climate, in Urumqi and Turpan, China, for five developmental stages. As measured, the average daily temperature and light intensity were lower in Urumqi. Urumqi grape berries had a lower brightness value (L*) and a higher red-green value (a*) when compared to Turpan’s. A RT-qPCR analysis revealed higher transcriptions of key genes related to anthocyanin biosynthesis in Urumqi grape berries, which was consistent with the more abundant phenolic substances, especially anthocyanins. The maximum antioxidant activity in vitro and cellular antioxidant activity of grape berries were also observed in Urumqi grape berries. These findings enclosed the influence of climate on anthocyanin accumulation and the antioxidant capacity of grapes, which might enlarge our knowledge on the quality formation of grape berries and might also be helpful for cultivating grapes with higher nutritional value.

A Study to Explore the Dew Condensation Potential of Cars

The metal surfaces of a car exhibit favorable properties for the passive condensation of atmospheric water. Under certain nocturnal climatic conditions (high relative humidity, weak windspeed, and total nebulosity), dew is often observed on cars, and it is appropriate to ask the question of using a vehicle as a standard condenser for estimating the dew yield. In order to see whether cars can be used as reference dew condensers, we report a detailed study of radiative cooling and dew formation on cars in the presence of radiating obstacles and for various windspeeds. Measurements of temperature and condensed dew mass on different car parts (rooftop, front and back hoods, windshield, lateral and back windows, inside and outside air) are compared with the same data obtained on a horizontal, thermally isolated planar film. The paper concludes that heat transfer coefficients, evaluated from temperature and dew yield measurements, are found nearly independent of windspeed and tilt angles. Moreover, this work describes the relation between cooling and dew condensation with the presence or not of thermal isolation. This dependence varies with the surface tilt angle according to the angular dependence of the atmosphere radiation. This work also confirms that cars can be used to estimate the dew yields in a given site. A visual observation scale h = Kn, with h the dew yield (mm) and n = 0, 1 2, 3 an index, which depends whether dew forms or not on rooftop, windshield, and lateral windows, is successfully tested with 8 different cars in 5 sites with three different climates, using K = (0.067 ± 0.0036) mm.day−1.

Combination of Models to Generate the First PAR Maps for Spain

This work addresses the development of a PAR model in the entire territory of mainland Spain. Thus, a specific model is developed for each location of the study field. The new PAR model consists of a combination of the estimates of two previous models that had unequal performances in different climates. In fact, one of them showed better results with Mediterranean climate, whereas the other obtained better results under oceanic climate. Interestingly, the new PAR model showed similar performance when validated at seven stations in mainland Spain with Mediterranean or oceanic climate. Furthermore, all validation slopes ranged from 0.99 to 1.00; the intercepts were less than 3.70 μmol m−2 s−1; the R2 were greater than 0.988, while MBE was closer to zero percent than −0.39%; and RMSE were less than 6.21%. The estimates of the PAR model introduced in this work were then used to develop PAR maps over mainland Spain that represent daily PAR averages of each month and a full year at all locations in the study field.