Impact of the North Atlantic Oscillation on streamflow in Western Iran

The Middle East region, where arid and semi‐arid regions occupy most of the land, is extremely vulnerable to any natural or anthropogenic reductions in available water resources. Much of the observed interannual‐decadal variability in Middle Eastern streamflow is physically linked to a large‐scale atmospheric circulation patterns such as the North Atlantic Oscillation (NAO). In this work, the relationship between the NAO index and the seasonal and annual streamflows in the west of Iran was statistically examined during the last four decades. The correlations were constructed for two scenarios (with and without time lag). The associations between the annual and seasonal streamflows and the simultaneous NAO index were found to be poor and insignificant. The possibility of streamflow forecasting was also explored, and the results of lag correlations revealed that streamflow responses at the NAO signal with two and three seasons delays. The highest Spearman correlation coefficient of 0.379 was found between the spring NAO index and the autumn streamflow series at Taghsimab station, indicating that roughly 14% of the variance in the streamflow series is associated with NAO forcing. Copyright © 2013 John Wiley & Sons, Ltd.     

Spatial distribution and temporal variation of reference evapotranspiration in arid and semi‐arid regions of Iran

Analysis of spatial and temporal variations of reference evapotranspiration (ET_o) is important in arid and semi‐arid regions where water resources are limited. The main aim of this study was to analyse the spatial distribution and the annual, seasonal and monthly trends of the Penman–Monteith ET_o for 21 stations in the arid and semi‐arid regions of Iran. Three statistical tests the Mann‐Kendall, Sen's slope estimator and linear regression were used for the analysis. The analysis revealed that ET_o increased from January to July and deceased from July to December at almost all stations. Additionally, higher annual ET_o values were found in the southeast of the study region and lower values in the northwest of the region. Although the results showed both positive and negative trends in annual ET_o series, ET_o generally increased, significantly so in six (～30%) of the stations. Analysis of the impacts of meteorological variables on the temporal trends of ET_o indicated that the increasing trend of ET_o was most likely due to a significant increase in minimum air temperature, while decreasing trend of ET_o was mainly caused by a significant decrease in wind speed. At the sites where increasing ET_o trends were statistically significant, the rate of increase varied from (+)8·36 mm/year at Mashhad station to (+)31·68 mm/year at Iranshahr station. On average, an increasing trend of (+)4·42 mm/year was obtained for the whole study area during the last four decades. Seasonal and monthly ET_o have also tended to increase at the majority of the stations. The greatest numbers of significant trends were observed in winter on the seasonal time‐scale and in September on the monthly time‐scale. Copyright © 2011 John Wiley & Sons, Ltd.     

Daily soil temperature modeling using neuro-fuzzy approach

Soil temperature is an important meteorological parameter which influences a number of processes in agriculture, hydrology, and environment. However, soil temperature records are not routinely available from meteorological stations. This work aimed to estimate daily soil temperature using the coactive neuro-fuzzy inference system (CANFIS) in arid and semiarid regions. For this purpose, daily soil temperatures were recorded at six depths of 5, 10, 20, 30, 50, and 100 cm below the surface at two synoptic stations in Iran. According to correlation analysis, mean, maximum, and minimum air temperatures, relative humidity, sunshine hours, and solar radiation were selected as the inputs of the CANFIS models. It was concluded that, in most cases, the best soil temperature estimates with a CANFIS model can be provided with the Takagi–Sugeno–Kang (TSK) fuzzy model and the Gaussian membership function. Comparison of the models’ performances at arid and semiarid locations showed that the CANFIS models’ performances in arid site were slightly better than those in semiarid site. Overall, the obtained results indicated the capabilities of the CANFIS model in estimating soil temperature in arid and semiarid regions.     

Observed changes in relative humidity and dew point temperature in coastal regions of Iran

The analysis of trends in hydroclimatic parameters and assessment of their statistical significance have recently received a great concern to clarify whether or not there is an obvious climate change. In the current study, parametric linear regression and nonparametric Mann?CKendall tests were applied for detecting annual and seasonal trends in the relative humidity (RH) and dew point temperature (T _dew) time series at ten coastal weather stations in Iran during 1966?C2005. The serial structure of the data was considered, and the significant serial correlations were eliminated using the trend-free pre-whitening method. The results showed that annual RH increased by 1.03 and 0.28?%/decade at the northern and southern coastal regions of the country, respectively, while annual T _dew increased by 0.29 and 0.15°C per decade at the northern and southern regions, respectively. The significant trends were frequent in the T _dew series, but they were observed only at 2 out of the 50 RH series. The results showed that the difference between the results of the parametric and nonparametric tests was small, although the parametric test detected larger significant trends in the RH and T _dew time series. Furthermore, the differences between the results of the trend tests were not related to the normality of the statistical distribution.     

Evaluation of Tailings from a Porphyry Copper Mine based on Joint Simulation of Contaminants

Natural Resources Research - Tailings from porphyry copper mines contain environmentally harmful amounts of elements such as copper, molybdenum, lead and cobalt. Geostatistical simulation of...     

Local vs. cross station simulation of suspended sediment load in successive hydrometric stations: heuristic modeling approach

The present paper aims at modeling suspended sediment load (SSL) using heuristic data driven methodologies, e.g. Gene Expression Programming (GEP) and Support Vector Machine (SVM) in three successive hydrometric stations of Housatonic River in U.S. The simulations were carried out through local and cross-station data management scenarios to investigate the interrelations between the SSL values of upstream/downstream stations. The available scenarios were applied to predict SSL values using GEP to obtain the best models. Then, the best models were predicted by SVM approach and the obtained results were compared with those of GEP. The comparison of the results revealed that the SVM technique is more capable than the GEP for modeling the SSL through the both local and cross-station data management strategies. Besides, local application seems to be better than cross-station application for modeling SSL. Nevertheless, the cross-station application demonstrated to be a valid methodology for simulating SSL, which would be of interest for the stations with lack of observational data. Also, the prediction capability of conventional Sediment Rating Curve (SRC) method was compared with those of GEP and SVM techniques. The obtained results revealed the superiority of GEP and SVM-based models over the traditional SRC technique in the studied stations.     

Time trend and change point of reference evapotranspiration over Iran

Identifying changes in reference evapotranspiration (ET_o) can help in future planning of crop water requirements and water resources for high water-use efficiency. This study analyzes the ET_o trends on a seasonal and annual timescale by applying various statistical tools to data from 41 Iranian weather stations during the period between 1966 and 2005. The Mann–Kendall test after removal of significant serial correlation was used to determine the statistical significance of the trends, and the change point in the ET_o time series was determined using the cumulative sum technique. The results showed that (1) the significant increasing trends of annual ET_o were observed at seven stations which are located in different parts of Iran, (2) the stations located at the southeast, northeast, and northwest corners of Iran experienced the highest positive change of annual ET_o, and (3) the changes in seasonal ET_o were most pronounced in the winter season, both in terms of trend magnitude and the number of stations with significant trends.     

Temporal trends and spatial characteristics of drought and rainfall in arid and semiarid regions of Iran

Drought, a normal recurrent event in arid and semiarid lands such as Iran, is typically of a temporary nature usually leaving little permanent aftermath. In the current study, the rainfall and drought severity time series were analyzed at 10 stations in the eastern half of Iran for the period 1966–2005. The drought severity was computed using the Standardized Precipitation Index (SPI) for a 12‐month timescale. The trend analyses of the data were also performed using the Kendall and Spearman tests. The results of this study showed that the rainfall and drought severity data had high variations to average values in the study period, and these variations increased with increasing aridity towards the south of the study area. The negative serial correlations found in the seasonal and annual rainfall time series were mostly insignificant. The trend tests detected a significant decreasing trend in the spring rainfall series of Birjand station at the rate of 8.56 mm per season per decade and a significant increasing trend in the summer rainfall series of Torbateheydarieh station at the rate of 0.14 mm per season per decade, whereas the rest of the trends were insignificant. Furthermore, the 12‐month values of the standardized precipitation index decreased at all the stations except Zabol during the past four decades. During the study period, all of the stations experienced at least one extreme drought which mainly occurred in the winter season. Copyright © 2011 John Wiley & Sons, Ltd.     

Petrography,geochemistry and geodynamic environment of potassic alkaline rocks in Eslamy peninsula,northwest of Iran

Eslamy peninsula, 360 km² in area, is located in the eastern coast of Urmieh lake in the northwest of Iran. This peninsula is a complex stratovolcano with a collapsed center, which is elevated due to later intrusions of sub-volcanic masses with trachytic to microsyenitic composition. The composite cone consists of a sequence of leucite tephrite, tephrite, leucite basanite, basanite and related pyroclastic rocks. Magmatic activities in the Eslamy peninsula begin with potassic alkaline to ultrapotassic and basic, silica-undersaturated shoshonitic rocks and they are followed by intrusions of lamprophyric dykes and end with acidic magmatism including trachytic, microsyenitic, syenitic and phonolitic domes. The original magma of the Eslamy peninsula rocks has a potassic alkaline nature (Roman type) rich in LREE and LILE and depleted of HREE. These characteristics suggest that the origin of magma can be from deep mantle with a garnet lherzolite composition, a low partial melting rate which has been contaminated by crustal materials in its way up. Fractional crystallization of olivine, diopsidic clinopyroxene and leucite played an important role in the evolution of magmas. Scrutinizing the geodynamic environment of Eslamy peninsula rocks in discrimination diagrams indicates that these rocks must have been formed in a post-collision magmatic arc setting.     

Streamflow drought severity analysis by percent of normal index (PNI) in northwest Iran

The streamflow drought is the most important type of drought due to the high dependence of many activities on surface water resources. The streamflow drought severity was identified by the percent of normal index (PNI) in the western basins of the Lake Urmia located in northwest Iran. The streamflow records were obtained from 14 hydrometric stations for the period October 1975–September 2009. The temporal trends of the streamflow drought severity were detected by the parametric Student’s t test and the nonparametric Mann–Kendall and Sen’s tests. The worst streamflow droughts at almost all the stations occurred in 1999–2000 and 2000–2001. The streamflow drought severity based on the PNI increased during the last 34 years. The results also indicated that the temporal dependency of time series had a dominant role in detecting trend by the parametric Student’s t test.