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Showing 8 results for Mann-Kendall

R Sabohi, S Soltani,
Volume 12, Issue 46 (1-2009)
Abstract

Climate change has important effects on earth environment and human life. Therefor, investigation and study of climate change is very essential. This study investigated rainfall, temperature, relative humidity and wind variability by analyzing data for annual and monthly climatic factors collected at 13 synoptic stations (industrial cities of Iran) by using Mann-Kendall test. The results of monthly rainfall trends showed that most of synoptic stations have significant positive and negative trends in winter and spring months. About 23% and 1.7% of stations have significant negative and positive trends, respectively, in annual trend of this factor. The results of monthly number of rainy days showed the major number of significant trends occurs in spring. In autumn (September, October and November) like as summer most of the stations have no significant trends. Analyzing the annual number of rainy days trends also showed that 4 stations have significant positive trends and 2 stations negative trends. Trend of greatest daily precipitation is low throughout the year, so there is not any significant trend in winter. Annual investigations confirm the seasonal investigations. The major number of significant trends in monthly mean maximum temperature occurs in summer but there are not any significant trends in winter and March. The trend of mean minimum temperature is approximately high in all of the seasons and the major number of significant trends occurs in summer and autumn and then in spring and ultimately in winter. In annual investigation, most of the stations showed positive trends and only Oroomieh station has negative trends. Trend of mean temperature is high except for winter. Most of the stations showed positive trend, indicating increasing trends in this factor. Annual studies vertify the positive trends and about 63% of stations have significant positive trends.
S. Dodangeh, S. Soltani, A. Sarhadi,
Volume 15, Issue 58 (3-2012)
Abstract

This study performs trend analysis of hydroclimatic varibles and their possible effects on the water resources variability. Nonparametric Mann-Kendall and spearman tests were used to investigate trend analysis of mean annual and 24-hr maximum rainfall, flood and low flow parameters of 23 hydrometery and 18 synoptic stations in Sefid-Roud basin. The results showed that mean annual and 24-hr rainfall parameters are decreasing in few stations while most of stations representing negative trend for low flow and flood time series. Applying Sequential Mann-Kendall test revelad that this negative trend is started from 1965 to 1970 for rainfall parameters and from 1970 to1980 for flow (low flow and flood) parameters. Results show that climate change has probability affected variability of climatic variables, while changing of land use may have aslo affeteced extreme flow trends during recent decads. Therefor it can be noted that combination of climate chanege effects and human activities on water recources have affected the negative trend of hydroclimatics variables.
S. Dodangeh, J. Abedi Koupai, S. A. Gohari,
Volume 16, Issue 59 (4-2012)
Abstract

Due to the important role of climatic parameters such as radiation, temperature, precipitation and evaporation rate in water resources management, this study employed time series modeling to forecast climatic parameters. After normality test of the parameters, nonparametric Mann-Kendall test was used in order to do trend analysis of data at P-value<0.05. Relative humidity and evaporation (with significant trend, -0.348 and -0.42 cm, respectively), as well as air temperature, wind speed, and sunshine were selected for time series modeling. Considering the Autocorrelation function (ACF) and Partial Autocorrelation function (PACF) and trend of data, appropriate models were fitted. The significance of the parameters of the selected models was examined by SE and t statistics, and both stationarity and invertibility conditions of Autoregressive (AR) and Moving average (MA) were also tested. Then, model calibration was carried out using Kolmogorov-Smirnov, Anderson- Darling and Rayan-Joiner. The selected ARIMA models are ARIMA(0,0,11)*(0,0,1), ARIMA(2,0,4)*(1,1,0), ARIMA(4,0,0)*(0,1,1), ARIMA (1,0,1)*(0,1,1), ARIMA (1,0,0)*(0,1,1) for relative humidity, evaporation, air temperature, wind speed and sunshine, respectively. The fitted models were then used to forecast the parameters. Finally, trend analysis of forecasted data was done in order to investigate the climate change. This study emphasizes efficiency of time series modeling in water resources studies in order to forecast climatic parameters.
A. Khanamani, E. Dodangeh, F. Soleymani , H. Karimzadeh, S. Soltani,
Volume 18, Issue 67 (6-2014)
Abstract

Underground water resources considered as a major source of fresh water. Increasing need to water in Iran, causing to immensely utilization and ground water balance disorder, so that state of ground water in many of area is negative.The purpose of this study is to investigate the trend of changes in some of the characteristics of groundwater during the period 1374 to 1387 is Segzi plain. For this purpose, data gathered from the Organization of regional water and homogenous test with Tom test (Run-test) at 95% confidence level was performed on the data. The independence of data evaluated by time series auto correlated functions (ACF), to do this, the amount of auto correlated data computed in different time delays and finally Mann- Kendall test used to evaluate the trend of time series properties in groundwater. The results of Run-Test showed that all of used series in this study were homogenous (P value< 0.05). The result of trend analysis test for region’s wells showed a significant increase in chlorine in underground water resources (P value< 0.05). Calcium has an increasing Trend too about 3 units. Results also showed that all used series in this study are random and Mann- Kendall trend analysis test can be an appropriate for trend evaluating in data series. As regard to irregular utilization of underground water resources by increasing depth of water level, amount of different salts such as chlorine and sodium increased, that causing to surface source degradation like soil and plant cover in agricultural area.
M. Khodagholi, R. Saboohi, Z. Eskandari,
Volume 18, Issue 67 (6-2014)
Abstract

The geographical location of Isfahan province has led the province to be at risk of drought. One of the ways to mitigate drought is evaluation and monitoring of drought based on indices that can determine its intensity and permanence in each region. In this research, for drought and trend analysis standard precipitation index and Mann-Kendall test were used, respectively. Also, monthly precipitation time series of Isfahan province was applied to forecast drought from 1970 to 2009. For this purpose, Box and Jenkins modeling approach (1976) was used which has three main steps, namely model identification, parameter estimation, goodness of fit test or time independency and normal test of residual. The results showed that most of the stations in Isfahan province were faced with severe drought in the year 2000 and this situation was repeated one more time in 2008. Also, the results brought forth multiplicative models in all the stations. ARIMA (1,0,0) (0,1,1) showed the highest correlations between control and forecast data in Isfahan, Meime and Ardestan stations, and the model ARIMA (0,0,1) (0,1,1) displayed the highest correlation between control and forecasted data in Naein, Freydoonshahr, Khansar and Natanz. These models were selected as the best models through which the amount of precipitation was predicted till 2015. The trend of forecast data across Isfahan province showed that in most months the trend is not significant.
F. Banan Ferdosi, Y. Dinpashoh,
Volume 22, Issue 3 (11-2018)
Abstract

In this study, in order to analyze the trends of annual precipitation, the information from 21 synoptic meteorological stations located in the Urmia Lake basin in a 30-year time period (1986-2015) was used. For this purpose, the Sequential Mann-Kendall test was used. The date of sudden change (if exist) in the precipitation time series of each station was identified. Significance of the trend in each of the time series and its direction (decrease or increase) in each of the stations were tested at 0.05 level. The results showed that 10 out of the 21 stations had a significant decreasing trend. Three stations (Sarab, Bostanabad and Sardasht) had significant increasing trends. Precipitation trends of eight stations were insignificant. Also, the study of sudden breaking points in the annual rainfall time series of the selected stations revealed that about 57.143 percent of the stations (12 stations) showed a significant sudden change in their annual rainfall series. In other words, more than half of the selected stations exhibited a   sudden change in their time series. The date of the sudden change of precipitation in eight stations (namely, Bonab, Sarab, Urmia, Oshnavieh, Kahrizi, Miyandoab, Bokan and Saghez) belonged to the middle part of the time series (i.e. 1996-2005). The sudden change date  of t hree stations (namely, Sardasht, Nagade and Tekab) belonged to the first decade of time series (i.e. 1986-1995) and only the sudden change date of  one station (namely, Maragheh) belonged to the last decade of time series (i.e. 2006-2015).

F. Negahban Khajeh, Y. Dinpashoh,
Volume 23, Issue 2 (9-2019)
Abstract

Studying the trends of water table in any region especially in arid and semi-arid regions is an important issue. This study focuses on assessing groundwater table changes in Tabriz plain. For this purpose, non-parametric Mann-Kendall test is used. In studing groundwater level the information of 14 pizometric wells in the period of 1991-2013 was used. Significant levels of 1, 5 and 10% were used for the trend test. Slope of trend lines is estimated using the sen's estimator method. The homogeneity of trends were tested using the Van Belle and Hughes method. The results showed that groundwater level in the most of pizometric wells have decreasing trend, That was significante in 1% sifnificance level. According to the research, trend of groundwater level was negative in all of the stations in April and maximum negative trend was belong to Dizaj Leily Khany station (Z= -6/47) that was significante in 1% sifnificance level. Also the minimum negative trend was belong to Ana Khaton station (Z= -0/322). The minimum groundwater level was -1.45 in Said-Abad station.

S. Jahanbakhsh Asl, B. Sari Saraf, T. Raziei, A. Parandeh Khouzani,
Volume 23, Issue 4 (12-2019)
Abstract

In this study, the temporal and spatial variation of snow depth over the mountainous region of Zagros, in the western Iran, for the period 1979–2010 was investigated for the cold season when the probability of snow occurrences was high. For this purpose, daily gridded snow depth data relative to Era-Interim/land were retrieved from the European Centre for Medium-Range Weather Forecasts (ECMWF) and used for spatiotemporal analysis of snow in the region. Furthermore, monthly maximum, minimum and mean air temperature relative to the weather stations distributed over the region were also used to investigate the relationship between snow depth and air temperature variability in the region. In each grid point, the rate of temporal changes in the snow depth was estimated using the Sen’s slope estimator, while the modified Mann-Kendall Test was applied to assess if the change identified was statistically significant. The results showed that in almost all of the studied months, especially February and March, the snow depth was significantly reduced in the region, which was statistically significant at 5% significant level. Unlike the observed statistically significant decreasing trend in the depth snow in the region, a significant increase in the maximum, minimum and average temperature was observed for all the studied months and the stations. The result suggested that the observed decrease in the snow depth in the region was related to the increasing trend in the temperature during the study period, which could be attributed to the global warming and climate change.


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