جستجوی مقالات مرتبط با کلیدواژه "من-کندال" در نشریات گروه "محیط زیست"

Land use/land cover (LULC) change, strongly affects surface water characteristics, especially in urban watersheds. The aim of this study was to determine LULC in the Samian Watershed and assessing its relationship with water quality parameters. In this study, LULC maps was obtained by ENVI software in four periods (1992 to 2016). Then, 9 water quality parameters at five river gauge stations were selected for further analysis. The Mann-Kendall test was performed to examine the trends in water quality parameters and Pearson test was used to assess the correlation between quality parameters and land uses. According to the results, rangeland decreased by 9.75%, irrigated agriculture increased by 8.45%, residential increased by 1.42% and rainfed agriculture increased by 3.29% compared to the first period. Average of TDS and EC in the study periods in Samian and Gilandeh stations, has been increased. The correlation analysis using Pearson test between quality data and LULC also shows that the EC, Ca, Cl, SO4, Mg and Na pameters of had a significant relationship with increasing residential, irrigated and rainfed land uses.

The study of snow cover changes, as one of the sources of water supply is very important. The purpose of this study is to investigate the trend of snow cover changes in Tehran province using MODIS sensor images of Terra satellite and Aqua satellite (since 2003) until the end of 2018 and compare the performance of MODIS sensor in these two satellites. The trend of snow cover satellite images changes was determined by ETM analyzer of TerrSET software, their significance was determined by non-parametric methods of Mann-Kendall significance test. Then, the satellite images were validated by analyzing the data trend of synoptic stations in Tehran province using regression methods. Also, the trend of snow cover changes obtained from Terra satellite was compared with the trend of snow cover changes obtained from Aqua satellite by Kappa index. And the time series of these two satellites were compared by the correlation coefficient of Linear Modeling analysis. According to the results, changes in total days with monthly, annual and seasonal snow cover (autumn and winter) have a significant decreasing trend in a scattered manner in most parts of Tehran province. Seasonal trend analysis (STA) showed a delay in the start of days with snow cover and its shift from late January to late March. The correlation coefficient of MODIS sensor time series between two satellites in most parts of Tehran province was 99% and showed high similarity. Validation results showed that the trend of snow cover satellite images changes is 85% similar to the trend of synoptic stations snow cover data changes in Tehran province.

The climate of an area over a long period is called the climate. Climate identification and classification have long been of interest to meteorologists. Researchers have classified the earth into homogeneous climatic zones using different methods and climatic variables such as rainfall and temperature. They have used the results of climate zoning to assess water scarcity and water resources on a small and large scale to anticipate practical measures to control drought in vulnerable areas. The purpose of this study is to update and analyze the Spatio-temporal analysis of Iran's climatic classification based on the Domarten index and the Mann-Kendall test. Because in studies based on climate classification maps, up-to-date maps can better help understand the study area.

For this study, data related to temperature and precipitation variables were extracted monthly from 153 synoptic stations from 1995-2019 from the Meteorological Organization of Iran. First, the data of average annual temperature and total annual precipitation were obtained from monthly data and then, using isothermal and isothermal maps, were obtained using the kriging model. The final climate zoning map was prepared using the De-Martonne index based on rainfall and temperature. The non-parametric Mann-Kendall test was also used to evaluate the significance or non-significance of the De-Martonne climate index and determine the trend.

The results showed that based on the Kriging model, R2 and RMSE for precipitation data were 0.58 and 167.51 mm, respectively, and for the data were 0.83 and 2.23 ° C, respectively. This indicates better performance of the model for temperature data. This is related to the high variance of precipitation data in the country. Iran's climatic zoning based on the De-Martonne index showed six main climatic types in Iran. Most of the area of Iran is an arid climate and then a semi-arid climate. The study results showed that arid climate is 76.40%, the semi-arid climate is 19.65%, and other climates make up less than 4% of the area of Iran. Also, the area of arid and semi-arid climates with an area of 96.05% of the area of Iran has increased compared to previous research, which may be due to reduced rainfall and increased temperature. Also, the results of the Mann-Kendall test showed that Khorramdareh, Miyaneh, Ramsar, Boroujerd, Piranshahr, Tabriz, and Bijar stations have a significant upward trend (wetting trend), and Dezful, Malayer, Sabzevar, Bandar Anzali, Tehran (Mehrabad), Tehran (Shemiran), Qazvin and Dushan Tappeh stations have a significant downward trend (drying trend) at the level of 5%.

This study showed that Iran has six climatic regions, including; The climate is arid, semi-arid, Mediterranean, semi-humid, humid, and very humid. Also, comparing the results with the results of research done by other researchers in the past showed that the area of arid and semi-arid climates in the study period has increased compared to previous periods. Also, 14% of stations with a downtrend (8 stations) have a significant downtrend, and 7% of stations with an uptrend (7 stations) have a significant uptrend at 95%.

In this study, in order to investigate the trend of precipitation changes in Khuzestan Province, the data used were daily, monthly and annual data of precipitation of selected synoptic stations for a statistical period of 30 years (1987-2016). To study the trend of precipitation changes, precipitation-related indices defined by the ETCCDMI expert group were estimated using RClimDex software. Then, the ascending and descending trend of changes in precipitation limit values ​​was investigated using Mann-Kendall non-parametric test method. The age slope estimator method was also used to determine the rate of precipitation change. The results showed that all precipitation-related indicators (except for the number of days with more than 25 mm and very wet days) had significant changes at the level of 5%. In terms of stations, Dezful station with 26.41% had the highest rainfall and Shushtar station with 3.64% had the lowest rainfall. Behbahan station also had a 14.87% increase in rainfall.

One of the impacts of climate change is alteration in water cycles in the different parts of the world. Since the impacts can influence economy and importantly, human health, it is necessary to study effective parameters of human readiness against economic issues, water shortages and so forth in the future. Thus, the present research is conducted to study the process of hydro-climatic changes of Kan River basin. The research examined a 30-year period of 1985-2014 using Mann-Kendall test and linear regression. According to the research results, precipitation and discharge decreased slightly; whereas, evapotranspiration (evaporation and transpiration) followed an ascending trend. In addition, studying the changes within three prospective periods 2030, 2060, and 2090 through GISS-AOM of general circulation model series indicated that evapotranspiration maintains an ascending trend; while, precipitation declines despite volatility in particular periods. Moreover, the average temperature of the area, which is directly related to evapotranspiration, decreases to the mid21st century, and then increases comparing to global mean temperature.