جستجوی مقالات مرتبط با کلیدواژه « روند زمانی » در نشریات گروه « آب و خاک »

Evaluation of the changes in river water quality plays key role in sustainable management of surface water resources. This study evaluates the river water quality of Sofi Chai River using the water quality index (WQI) from 1972 to 2016. Shannon's Entropy Method and Analytical Hierarchy Process (AHP) have been used to determine the relative weight of water quality parameters and then these parameters have been compared with the weights provided by the World Health Organization (WHO). Qualitative parameters of Electrical Conductivity (EC), acidity (pH), Total Dissolved Solids (TDS), calcium (Ca2+), bicarbonate (HCO3-), sulfate (SO42-), chloride (Cl-), magnesium (Mg2+) and sodium (Na+) have been used to evaluate the water quality of Soufi Chai River. The results of this study show TDS and EC in AHP and sodium, chlorine and sulfate in the Entropy Method are the most effective parameters on the water quality of Soufi Chai River. The average of Water Quality Indicator calculated by the weighting methods such as entropy, AHP and standard weighting of the WHO during the period of 1972 and 2016 are 13, 38 and 16, accordingly, which indicates that the water quality of Soufi Chai River is excellent.

Article abstract:Evapotranspiration (ET) is the largest water consumer in arid and semi- arid regions. Therefore, acquiring the knowledge of the factors and processes leading to ET is of utmost importance in decision – making water resources management. In this study, the long time trend in mean monthly temperature, rainfall and ET was investigated to this end, all synoptic stations were categorized according to the De Martonne climate classification method. As we were mostly concerned with the semi- arid region of the Land of Iran, only 14 stations with at least 30 years of data were selected for this purpose. The least squares error, the Man – Kendall, and the Vald-Volfoyts methods were used in analyzing the data. The FAO-Penman-Monteith equation was used in the reference crop ET estimation. It was observed that 24% of the stations showed positive and 14% showed negative trends, and the remaining stations did not follow any trend. As for the rainfall, no meaningful trend was detected in this parameter. Of the applied statistical methods, the least squares and error the Mann-Kendall methods showed closer similarities than the other procedures. In conclusion, it is certain that some regions shall experience higher temperatures, thus ET, in the coming years

A number of researches have indicated a gradual increase in mean temperature throughout the world. Yet, there are some reports on the reduction of annual mean temperature. In this research we investigated a long-term trend of annual mean temperature in 34 synoptic stations in Iran (2 stations in cold and humid climates 14 in humid and moderate climates, 11 in Steppe climate and 7 in desert climate - following Kopen climatic division) with a minimum statistical record of 30 years by applying the minimum square-error and Man-Kendall methods (Wald-Wolfowitz method had a different result). The results confirmed a positive trend in 59% stations, while 41 % of the stations were negative for the whole time-horizon of data. Considering the significance level, 3 zones of positive, negative, and no trends for annual mean temperature were detected in Iran. However, it was hard to define a specific spatial theme for such a division. By taking another approach, we proceeded with a shared statistical time period of 1968-1998 for all stations. In this case, 68% of the stations showed a positive trend, while the remaining 32% was negative. There were some shifts in direction from one trend to another in some of the stations in the study, yet no well-defined spatial structure was reported. In contrast, at 5% level of significance, 44, 15 and 41 percentages of the stations demonstrated positive, negative, and no trend for annual mean temperature, respectively. In general the behavior was different for different climates and no specific pattern was found. So, despite the fact that some stations did not show significant trends, one may hypothesize that more regions in future will experience higher temperature values and their positive trends would be a clue for future warming.