جستجوی مقالات مرتبط با کلیدواژه « تابش خورشیدی » در نشریات گروه « زمین شناسی »

Accurate estimation of reference evapotranspiration is essential in many studies such as water hydrological balance, design and management of irrigation systems, simulation of plant growth stages and yield, and planning and management of water resources. Accurate estimation of this parameter can lead to proper management and planning of water resources. The aim of this study was to estimate the values of reference evapotranspiration in synoptic stations of Kermanshah province during the statistical period of 2010-2020, evaluation of Hargreaves Samani and modified Hargreaves Samani methods and zoning of reference evapotranspiration in the province. The standard Penman Monteith-FAO method resulting from the water requirement system of plants was used to determine the reference evapotranspiration. The results showed that the highest and lowest annual reference evapotranspiration among the meteorological stations in the amount of 1770 and 1341 mm per year belonged to Qasr-e-Shirin and Sararood stations, respectively. The most important effective parameter in the higher reference evapotranspiration in Qasr-e-Shirin station was high temperature and wind speed compared to other stations. The results of zoning of reference evapotranspiration showed that the western regions of the province have a higher intensity than the eastern regions. Evaluation of Hargreaves Samani and modified Hargreaves Samani methods showed that the mean of R2, RMSE and NRMSE statistics in Hargreaves Samani method were 0.9, 0.78 mm day-1 and 0.19, respectively. The mean values of these statistics in the modified Hargreaves Samani method were 0.71, 2.59 mm day-1 and 0.65, respectively. Therefore, the application of Hargreaves Samani method to calculate the reference evapotranspiration in this province is recommended.

Solar radiation is one of the important parameters that affects on many soil and water processes such as evaporation, snow melting and plant growth. Considering the importance of the amount of radiation in the the application of solar energy and the many problems in recording this parameter and the success of intelligent models in predicting complex parameters, it is reasonable to use ANFIS and ANN models to predict the radiation parameter.
In this study, using a large database on a wide period which contained a set of meteorological and geographical data such as latitude, longitude, months of the year, the average temperature, the sunshine duration, relative humidity and the average of the monthly global solar irradiation, the performance of two techniques, artificial neural network and Active Neuro-Fuzzy Inference System, was investigated for the next 12 months in the Yazd station. Sensitivity analysis of different climate parameters such as maximum temperature, average temperature, sunshine hours, relative humidity, solar radiation and evaporation, showed that they were important factors in predicting of solar radiation. Then, the two models were analyzed with different combinations of data. After ensuring the performance of the two models in the testing phase and achieving the best results with the highest efficiency and lowest error rate in the prediction of solar radiation, only by entering the most effective climatic parameters of 2005, the solar radiation value of 2006 was forecasted, and the predicted values were compared with actual values. The results of this study showed that both methods have the ability to simulate the amount of solar radiation. High values ​of the correlation coefficient and low error, confirm the reliability of the results. According to the results, although the highest correlation coefficient was obtained using artificial neural network, the results of both models were satisfactory in two stages of testing and evaluation and are estimated to be close to each other. In total, artificial neural networks with a correlation coefficient of 0.91 and RMSE and MAE rates of 0.19 and 0.08, respectively, produced less error in predictions in comparison with fuzzy-neural networks. Also, the BIAS value is -0.30, which shows a small negative overstimation in the data. Finally, the composition of sunny hours, average temperature, maximum temperature as the optimal combination was identified. In addition, it was determined that sunny hours and average temperatures are the most effective parameters in prediction of solar radiation, while relative humidity has the least effect on it.

Summary: One of the most important steps to make use of any renewable energy is to perform an accurate estimation of solar energy. Incoming shortwave (300-4000 nm) solar radiation is an important component in evaluating environmental factors. In addition to local solar radiation، a detailed spatial and temporal information of Global Solar Radiation (GSR) is required in urban design and regional plans. Further، beside the atmospheric parameters، the variability of the elevation، the surface orientation and the obstructions due to elevations are a source of great local differences affecting the incoming solar radiation. For this reason، several models based on GIS techniques have been recently proposed and developed، which consider the local topography for retrieving global solar radiation on the Earth’s surface. Actual irradiation which is received at any time and location depends on many factors such as solar zenith angle، solar declination angle، atmospheric transmissivity (i. e. cloud amount، aerosol optical depth)، diffused radiation، slope orientation and local topography. The commonly used radiation models (e. g. Angstrom- Prescott model) do not consider diffused radiation، atmospheric transmissivity (turbidity) and topography of the study sites; as they are not usualy available for model estimation. Using the Arc GIS tool، Batless et al. (2008) estimated the global solar radiation on a monthly basis. They showed that summer month estimations are more accurate than winter times. For a region with a different topography، Martinez et al. (2009) employed satellite images (Meteosat) and Digital Terrain Model for estimation of GSR. Their results showed reasonable performance for the model estimates. Bosch et al. (2010) addressed the same problem. To evaluate the potential of solar energy for Oman، Gastli and Charabi (2010) used Arc GIS method in their work. They found that Oman had ahigh potential of solar energy which could be used as a sustainable source of renewable energy. Iran is located in an unique part of the world، which experiences significant variation in altitude and latitude. The altitude of the country، which has a complex totography، varies from -40 to 5670 m above sea level. These geographical factors cause a wide range of climate types and different amounts of solar irradiance at the surface. The majority of the radiation modeling in Iran has relied on straightforward and simple radiation models such as Angstrom and Angstrom-Prescott. The main constraint of these models was the regional estimates of GSR which were not easily possible from the local estimates. As the first attempt in Iran، this work aimed to consider the effect of complex topography and altitude on surface GSR. In this study، global solar radiation was produced for four central provinces of Iran using the Solar Analyst model implemented on Arc GIS 9. 3. The Solar Analyst uses input parameters such as the diffuse fraction (k) and the atmospheric transmissivity. These parameters are not usually available in radiation networks. In this work، the aforesaid parameters were obtained with use of global solar radiation data (as measured in radiation sites) and extraterrestrial radiation (determined by astronomical models). Monthly localsolar irradiation in the year 2007 was calculated from a digital terrain model (DTM) with spatial resolution of 300 m، diffuse fraction (k) and atmospheric transmissivity (τ) for the study sites. Results were accordingly compared against the measured GSR values. Evaluation of the annual regional global solar radiation showed that the southern and northern slopes received the maximum and minimum incoming solar radiation، respectively. It was found that the elevation differences have less effect on the incoming global solar radiation than other topographic variables such as slope، surface orientation and the obstructions.