elham fakhimi; Hossein Naderi
Abstract
Floristic studies are fundamental for the applied sciences such as rangeland management and conservation. Rangelands of Sadrabad with an area of 40000 hectares is jocated in South West of Yazd province that it remarkable habitat for the floristic studies. In this study the floristic list of the region ...
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Floristic studies are fundamental for the applied sciences such as rangeland management and conservation. Rangelands of Sadrabad with an area of 40000 hectares is jocated in South West of Yazd province that it remarkable habitat for the floristic studies. In this study the floristic list of the region is presented and their life forms and endangered species are distingushed Plants were sampled following the common method in the regional taxonomic studies and their families, genera, and species were determined using indispensable references. The life form of plant species was determined using Raunkier’s method. The results showed that 235 plant species belonging to 39 families and 169 genera exist in this area. Hemicryptophytes, Therophytes, Chamaephytes, Geophytes and Phanerophytes included 36.45, 25.65, 23.47 , 7.82 and 6.55% of the total species, respectively. Furthermore, the endangered species of the region were identified on the basis of IUCN criteria and Red Data Book of Iran. Accordingly, 43endangered species were identified, of which 34 were in lower risk (LR) class, , 7 species were in vulnerable (VU) class, and 2 were put in data deficient (DD) class.
hamide afkhami; azam habibi pour; mohammad reza ekhtesasi
Abstract
Evaporation is considered one of the key climatic variables, especially in arid regions and evaporation losses is one of the important issues in irrigation and water resources management in these areas. Therefore, it is important being aware of the amount of evaporation and its modeling, as one of the ...
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Evaporation is considered one of the key climatic variables, especially in arid regions and evaporation losses is one of the important issues in irrigation and water resources management in these areas. Therefore, it is important being aware of the amount of evaporation and its modeling, as one of the most important hydrological variables in agricultural research and water and soil conservation. In recent decades, artificial intelligence techniques have proven high capability and flexibility to estimate and predict nonlinear phenomena. In this study, three important data mining techniques including Artificial Neural Network, Active Neuro-Fuzzy Inference System and Regression Decision Tree were used for predicting evaporation. For this purpose, 8 climatic variables (Minimum average temperature, average maximum temperature, average temperature, sunshine hours, wind speed, wind direction, relative humidity and evaporation averages) were employed in this study. The results showed three models are able to predict evaporation for 12 months after. Finally among the used models, ANN showed better performance with coefficient efficiency of 0.97 and RMSE of 5.1and ME of 0.48. Also, The results showed that there is not significant difference in simulation results to predict the evaporation between two scenario, original data and normalized data.
