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EN
Having doubts about the adequacy of reliability level of satellite-derived precipitation products, along with their application in large number of hydrological models, has led to many studies on evaluating the efficiency of such data. In this study, two new procedures were proposed to compute reliability and certainty degrees of PERSIANN and TRMM 3B42RT data sets, and six traditional indicators were used to evaluate their validation. In addition, the cumulative density function (cdf) of the above-mentioned data sets was compared with the ground-based observations in 23 synoptic stations in Fars, Iran. The Kolmogorov–Smirnov test was performed using the data sets at 5% significance level which led to the result of null hypothesis that was not being rejected, suggesting that the satellite-derived daily precipitation data (SDDPD) and ground based observations are drawn from the same distribution. Results indicated that TRMM and PERSIANN follow quite similar probability pattern of ground-based observations in arid and semiarid climate, respectively. However, data probability pattern of TRMM cannot be considered similar to ground-based observations in arid region, neither can PERSIANN in semiarid climate. Among common cross-validating attributes, the values of ME and BIAS, in addition to RMSE and MAE, led to the conclusion that in PERSIANN, the rainfall daily rates are almost underestimated while TRMM overestimates the values mainly in semiarid regions. Moreover, the PERSIANN was found to be significantly correlated with IDM (De Martonne aridity Index), and the values of underestimation increased with growth of the index. The reliability values of SDDPD over the study area, for both TRMM and PERSIANN, show the reverse trend with increasing IDM in almost all acceptable error intervals. Along with effects of climate conditions, the reliability degrees of PERSIANN seem quite more consistent at different acceptable error intervals in comparison with the corresponding values of TRMM. In addition to validity and reliability, the error entropy of SDDPD, as an index for uncertainty degree, increases as the IDM rises, which is theoretically corresponds with reliability concept. However, in comparison with PERSIANN, TRMM data set, overall, has higher degree of uncertainty. In addition, to evaluate effect of daily rainfall intensity on the uncertainty degree of SDDPD, the uncertainty degree slightly increases as daily rainfall intensifies to about 15 mm/day. But for higher daily rainfall intensities, on the other hand, the uncertainty degree seems to gradually decline as the daily rainfall increases.
EN
Lemon verbena is cultivated mainly due to the lemon-like aroma emitted from its leaves that are utilized for most purposes. The chemical composition of the essential oil of lemon verbena was analyzed by GC/MS in July at pre flowering, in September at full flowering and in end of October at post flowering period. The in vitro antimicrobial activity of the essential oil, extracted from Lippia citriodora was tested against laboratory control strains belonging to the American Type Culture Collection (Maryland, USA) four Gram (+) and Gram (-) bacteria using the disc diffusion test. Antioxidant activity of the sample was determined by 1,1-diphenil-2- -picrly-hydrazil (DPPH) assay. Well-known antioxidant compounds such as ascorbic acid and α-tocopherol were used as standard. Results showed, among different harvest periods high fresh and dry herbage and dry leaf yields per plant were obtained from full flowering stage. Harvest periods were found to have a significant effect on the content of essential oil and the highest amounts of limonene, neral and geranial and measured as 31.15, 11.92 and 15.53%, respectively at full flowering stage. In all samples, the main constituents were limonene, neral and geranial constituting 46.03%–58.59% of the total essential oil yield depend on development stages. Lemon verbena essential oil was found to have antibacterial activity especially against Gram (+) microorganisms. In DPPH system, the moderate radical scavenging activity was exhibited. Therefore, L. citriodora has potential to be used as a natural antioxidant and antimicrobial agent in food processing.
EN
Salinity stress is a serious problem in urban landscape of arid and semi arid regions. To overcome the adverse impact of salinity, the application of organic matter and plant nutrients in the growth media for improving the plant growth is essential. An experiment was conducted in order to determine the response of Salvia splendens to salinity levels and also the role of humic acid in the salt stress alleviation. In the current experiment, five salinity levels (0, 20, 40, 60, and 80 mM NaCl) and three humic acid (0, 100, 500 and 1000 mg/l) treatments were prepared. The effects of these treatments were investigated on some growth parameters, physiological characteristics and also biochemical compounds. The results indicated that the growth parameters decreased in saline-treated than control plants. Different salinity levels significantly affected relative water content, evaporation rate and also electrolyte leakage. Salinity caused the increase in proline, malondialdehyde, sugar content, DPPH, total phenol content and decrease in chlorophyll, compare to the control plants. Application of humic acid on Salvia splendens decreased the leaf area and plant height compared to the control plants. Thus, regarding the growth parameters, it is probable that the effect of humic acid on the biochemical compounds is similar to salinity effect. The findings suggest that sage is an ornamental plant sensitive to salinity and humic acid (in the studied levels) could not alleviate the negative effects of salt stress on this plant.
EN
Ain Sefra is one of the Algerian cities that had been experienced several devastating floods during the past 100 years. The purpose of this study is to simulate runoff in the semi-arid region of Ain Sefra watershed through the employing of the Hydrologic Engineering Center – Hydrologic Modelling System (HEC-HMS). In this paper, the frequency storm is used for the meteorological model, the Soil Conservation Service – curve number (SCS-CN) is selected to calculate the loss rate and Soil Conservation Service unit hydrograph method have been applied to simulate the runoff rate. After calibration and validation, the simulated peak discharges were very close with observed values. The Nash–Sutcliffe efficiency coefficient was 0.95, indicates that the hydrological modeling results are satisfactory and accepted for simulation of rainfall-runoff. The peak discharges obtained for the 10, 50, 100 and 1000 year storms are respectively 425.8, 750.5, 904.3 and 1328.3 m3∙s–1.
PL
Ain Sefra jest jednym z algierskich miast, które doświadczyły kilku niszczących powodzi w ciągu minionych 100 lat. Celem badań prezentowanych w pracy było symulowanie odpływu w regionie o klimacie półsuchym w zlewni Ain Sefra z wykorzystaniem systemu modelowania hydrologicznego HEC-HMS. W pracy użyto częstotliwości opadów nawalnych do konstruowania modelu meteorologicznego, liczbę krzywych Służby Ochrony Gleb USA – ang. Soil Consevation Service (SCS-CN) wybrano do obliczenia tempa strat, a metodę jednostkowego hydrogramu Służby Ochrony Gleb USA użyto do symulowania szybkości odpływu. Po przeprowadzeniu kalibracji i walidacji modelu symulowane maksymalne odpływy były bardzo bliskie wartościom obserwowanym. Współczynnik wydajności Nasha–Sutcliffa równy 0,95 wskazuje, że wyniki modelowania hydrologicznego są zadowalające i mogą być przyjęte do symulowania relacji opad–odpływ. Uzyskane maksymalne odpływy dla 10-, 50-, 100- i 1000-letnich opadów nawalnych wynoszą odpowiednio 425,8, 750,5, 904,3 i 1328,3 m3∙s–1.
EN
The study aimed to determine agronomic characteristics and essential oil components of different basil ecotypes in semi-arid climatic conditions of South Eastern Anatolia, Diyarbakir, Turkey. Two-year harvest data about fresh and dry herb yield, dry leaf yield, essential oil content and its components from the plants of year 2015 and 2016 was analyzed in this study. Essential oil components were detected by gas chromatography/ mass spectrometry (GC/MS). The resulting outcomes demonstrated that both ecotypes and harvests had important effects on fresh and dry herb, dry leaf yield and essential oil contents of sweet basil. The highest dry leaf yield was noted from green leafy ecotypes and from second harvest stage. Twenty-three constituents were detected in the essential oil of O. basilicum ecotypes. The main components of basil essential oil were linalool, methyl chavicol, neral, geranial and methyl cinnamate that differed according to ecotypes and harvests during experimental years 2015 and 2016. Purple leafy basil ecotypes were determined as linalool rich, while greenish leaf ecotypes were abundant in methyl chavicol. Silbe – green ecotype contains higher neral and geranial levels than the other ecotypes. It was concluded that basil plant could be grown successfully and harvested two or more times to prefer for maximum dry leaf yield and essential oil contents under semi-arid climatic conditions.
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