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.
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).
