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 modelling of reference evapotranspiration using adjusted Blaney-Criddle equation in an arid environment

Abstract

The Blaney-Criddle (BC) temperature-based equation is used in areas where the complete weather data to estimate reference evapotranspiration (ET₀) by the Penman-Monteith FAO-56 (PMF-56) standard model is complex. In this study, the BC equation was first tested and calibrated against the ET₀ values computed by the PMF-56 method using data from 17 weather stations in arid regions of Iran. Then, geographical information systems (GIS)-based spatially-distributed maps of ET₀ were prepared by means of geographic/topographic factors derived from a digital elevation model (DEM) for all months, separately. The results indicate that the original BC equation overestimated PMF-56 ET₀ by 4% at the study sites. The BC equation produced closer ET₀ estimates to the PMF-56 method after it was calibrated. The error rate of <3% for the spatial modelling approach suggests that the developed ET₀ maps are reliable.

Editor D. Koutsoyiannis; Associate editor D. Yang

Citation Tabari, H., Hosseinzadeh Talaee, P., and Shifteh Some'e, B., 2013. Spatial modelling of reference evapotranspiration using adjusted Blaney-Criddle equation in an arid environment. Hydrological Sciences Journal, 58 (2), 408–420.     

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.     

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.     

Comparison of artificial neural network and multivariate linear regression methods for estimation of daily soil temperature in an arid region

Soil temperature (T _S) strongly influences a wide range of biotic and abiotic processes. As an alternative to direct measurement, indirect determination of T _S from meteorological parameters has been the focus of attention of environmental researchers. The main purpose of this study was to estimate daily T _S at six depths (5, 10, 20, 30, 50 and 100?cm) by using a multilayer perceptron (MLP) artificial neural network (ANN) model and a multivariate linear regression (MLR) method in an arid region of Iran. Mean daily meteorological parameters including air temperature (T _a), solar radiation (R _S), relative humidity (RH) and precipitation (P) were used as input data to the ANN and MLR models. The model results of the MLR model were compared to those of ANN. The accuracy of the predictions was evaluated by the correlation coefficient (r), the root mean-square error (RMSE) and the mean absolute error (MAE) between the measured and predicted T _S values. The results showed that the ANN method forecasts were superior to the corresponding values obtained by the MLR model. The regression analysis indicated that T _a, RH, R _S and P were reasonably correlated with T _S at various depths, but the most effective parameters influencing T _S at different depths were T _a and RH.     

Validation and calibration of solar radiation equations for estimating daily reference evapotranspiration at cool semi-arid and arid locations

ABSTRACT

In this work, the applicability of 12 solar radiation (R_S) estimation models and their impacts on daily reference evapotranspiration (ET_o) estimates using the Penman‐Monteith FAO-56 (PMF-56) method were tested under cool arid and semi-arid conditions in Iran. The results indicated that the average increase in accuracy of the ET_o estimates by the calibrated R_S models, quantified by the decrease in RMSE, was 2.8% and 6.4% for semi-arid and arid climates, respectively. Mean daily deviations in the estimated ET_o by the calibrated R_S equations in semi-arid climates varied from ?0.283?mm/d^-1 for the Glover‐McCulloch model to 0.080?mm/d for the El-Sebaii model, with an average of ?0.109?mm/d^-1, and in arid climates, they ranged from ?0.522?mm/d^-1 for the Samani model to 0.668?mm/d for the El-Sebaii model, with an average of 0.125?mm/d^-1.

Editor D. Koutsyiannis; Associate editor Not assigned     

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.     

Characterization of a biodegrading bacterium, <Emphasis Type="Italic">Bacillus subtilis</Emphasis>, isolated from oil-contaminated soil

Crude oil and its derivatives because of different events and accidents may cause pollution to the environment. A biological treatment is a novel technique that uses microorganisms to remove or neutralize pollutants from a contaminated site. Oil-contaminated soils were sampled, after isolating of soil bacteria, using quantitative and qualitative screening, biosurfactant-producing bacteria were identified and environmental factors on the growth of bacteria and biosurfactant were investigated. In this study, the Bacillus subtilis was identified as the best biosurfactant-producing strain which has the ability to grow in environments with high salinity and temperature and pH > 5. The produced biosurfactant from B. subtilis is stable to changes in temperature and salt concentration and pH (in the range of 5–12).The B. subtilis also showed that they are able to biodegrade aliphatic alkanes. The B. subtilis has necessary potential for bioremediation of oil pollution in the environment.