Quantifying uncertainties associated with depth duration frequency curves

Uncertainty in depth–duration–frequency (DDF) curves is usually disregarded in the view of difficulties associated in assigning a value to it. In central Iran, precipitation duration is often long and characterized with low intensity leading to a considerable uncertainty in the parameters of the probabilistic distributions describing rainfall depth. In this paper, the daily rainfall depths from 4 stations in the Zayanderood basin, Iran, were analysed, and a generalized extreme value distribution was fitted to the maximum yearly rainfall for durations of 1, 2, 3, 4 and 5 days. DDF curves were described as a function of rainfall duration (D) and return period (T). Uncertainties of the rainfall depth in the DDF curves were estimated with the bootstrap sampling method and were described by a normal probability density function. Standard deviations were modeled as a function of rainfall duration and rainfall depth using 10⁴ bootstrap samples for all the durations and return periods considered for each rainfall station.     

Hydrochemical and isotopic investigation of groundwater of Al-Batin alluvial fan aquifer,Southern Iraq

Major ions and important trace elements in addition to δ¹⁸O and δ²H were analysed for 43 groundwater samples sampled from the Al-Batin alluvial fan aquifer, South Iraq. The most dominant ions (with respect to molarity) were: Na⁺ > Cl^? > SO₄ ^2? > Ca²⁺ > Mg²⁺ > NO₃ ^? > HCO₃ ^?, with total dissolved solids (TDS) averaging 7855 mg/L. High concentrations were found for the trace elements U, Mo, V, B, Sr, and Cr. This study suggests a hydraulic connection exists near the fan apex between the uppermost part of the Al-Batin aquifer and the underlying Dammam aquifer by means of the Abu-Jir fault system. Except for the effects of extensive irrigation, fertilizer use, and poorly maintained sewers, the groundwater chemistry is mainly controlled by geological processes such as dissolution of evaporites and the enrichment of dissolved ions as a result of the high evaporation and low recharge rate. Furthermore, it is shown that the Kuwaiti fuel–oil burning during Gulf War in 1991 contributed to the enrichment of V and Mo in the studied aquifer. The spatial distribution of most ions appears to generally increase from the south-west towards the north-east, in the direction of groundwater flow. The stable isotopes show heavier values in groundwater with a gradually increasing trend in the direction of groundwater flow due to the decreasing depth to groundwater and thus increasing of evaporation from both groundwater or irrigation return water. Additionally, the stable isotope signature suggests that rainfall from sources in the Arabian Gulf and the Arabian Sea is the major source of recharge for the Al-Batin aquifer. Except for two samples of groundwater, all samples were not suitable for potable use according to the WHO standards. Most of the groundwater is suitable for some agricultural purpose and for livestock water supply. Apart from the high salinity, boron represents the most critical element in the groundwater with respect to agricultural purposes.     

Evaluation of dynamic regression and artificial neural networks models for real-time hydrological drought forecasting

In this study, application of a class of stochastic dynamic models and a class of artificial intelligence model is reported for the forecasting of real-time hydrological droughts in the Black River basin in the USA. For this purpose, the Standardized Hydrological Drought Index (SHDI) was adopted in different time scales to represent the hydrological drought index. Six probability distribution functions (PDF) were fitted to the discharge time series to obtain the best fit for SHDI calculation. Then, a dynamic linear spatio-temporal model (DLSTM) and artificial neural network (ANN) were used to forecast SHDI. Although results indicated that both models were able to forecast SHDI in different time scales, the DLSTM was far superior in longer lead times. The DLSTM could forecast SHDI up to 6 months ahead while ANN was only capable of forecasting SHDI up to 2 months ahead appropriately. For short lead times (1–6 months), the DLSTM has performed nearly perfect in test phase and CE oscillates between 0.97 and 0.86 while for ANN modeling, CE is between 0.72 and 0.07. However, the performance of DLSTM and ANN reduced considerably in medium lead times (7–12 months). Overall, the DLSTM is a powerful tool for appropriately forecasting SHDI at short time scales; a major advantage required for drought early warning systems.     

Spatial variability of rainfall trends in Iran

The main objective of this paper is to analyze the spatial variability of rainfall trends using the spatial variability methods of rainfall trend patterns in Iran. The study represents a method on the effectiveness of spatial variability for predicting rainfall trend patterns variations. In rainfall trend analysis and spatial variability methods, seven techniques were used: Mann–Kendall test, Sen’s slope method, geostatistical tools as a global polynomial interpolation and the spatial autocorrelation (Global Moran’s I), high/low clustering (Getis-Ord General G), precipitation concentration index, generate spatial weights matrix tool, and activation functions of semiliner, sigmoid, bipolar sigmoid, and hyperbolic tangent in the artificial neural network technique .For the spatial variability of monthly rainfall trends, trend tests were used in 140 stations of spatial variability of rainfall trends in the 1975–2014 period. We analyzed the long and short scale spatial variability of rainfall series in Iran. Spatial variability distribution of rainfall series was depicted using geostatistical methods (ordinary kriging). Relative nugget effect (RNE) predicted from variograms which showed weak, moderate, and strong spatial variability for seasonal and annual rainfall series. Moreover, the rainfall trends at each station were examined using the trend tests at a significance level of 0.05. The results show that temporal and spatial trend patterns are different in Iran and the monthly rainfall had a downward (decreasing) trend in most stations, and the trend was statistically significant for most of the series (73.5% of the stations demonstrated a decreasing trend with 0.5 significance level). Rainfall downward trends are generally temporal-spatial patterns in Iran. The monthly variations of rainfall decreased significantly throughout eastern and central Iran, but they increased in the west and north of Iran during the studied interval. The variability patterns of monthly rainfall were statistically significant and spatially random. Activation functions in the artificial neural network models, in annual time scale, had spatially dispersed distribution with other clustering patterns. The results of this study confirm that variability of rainfall revealing diverse patterns over Iran should be controlled mainly by trend patterns in the west and north parts and by random and dispersed patterns in the central, southern, and eastern parts.     

An Analytical Study of the Diurnal Variations of Wind in a Semi-geostrophic Ekman Boundary Layer Model

A time-dependent semi-geostrophic Ekman boundary-layer model based on the geostrophic momentum approximation is used to study the diurnal wind variation in the planetary boundary layer (PBL) and the evolution of the low-level nocturnal jet (LLJ). The coefficient of eddy viscosity varies periodically with time, varies linearly with height in the surface layer and is constant above the surface layer. The influence of horizontal advection of momentum on the diurnal wind variation in the PBL, the development of inertial oscillations (IOs) and the formation of the LLJ are examined.In comparison with the Ekman solutions, the diurnal wind variation in semi-geostrophic Ekman boundary-layer dynamics has the following features: (1) the phase angle of the diurnal wind wave shifts with height, the rate of shifting is increased in anticyclonic regions and decreased in cyclonic regions, (2) the time of occurrence of the low-level maximum wind speed is later in anticyclonic regions and earlier in cyclonic regions, (3) the height of occurrence of the maximum wind speed is higher in the anticyclonic and lower in cyclonic regions, (4) the wind speed maximum and the amplitude of the diurnal wind variation are larger in anticyclonic and smaller in cyclonic regions, (5) the period of IOs is larger in anticyclonic regions and smaller in cyclonic regions, (6) anticyclonic vorticity is conducive to the generation of LLJ in the PBL. These features are interpreted by means of the physical properties of semi-geostrophic Ekman boundary-layer dynamics and inertial oscillation dynamics.     

Variation of Rhenium Contents in Molybdenites from the Sar Cheshmeh Porphyry Cu‐Mo Deposit in Iran

This paper presents the results of a study on the variation of Re in the Sar Cheshmeh porphyry copper‐molybdenum deposit in Iran. The Re content was determined in monomineralic molybdenite separates from veinlets and from molybdenum milled floatation concentrates. Mineralogical data and chemical analyses indicate two generations of veinlet molybdenites in the Sar Cheshmeh deposit. The first generation (molybdenite I), which contains low Re, is found as intergrowth with quartz in silicified rocks with low total sulfide content, and the second generation (molybdenite II), which contains high Re, is found in veinlets with low quartz content. There is a positive correlation between the elevation of molybdenite deposition and Re content. Decrease in the temperature and pH of the hydrothermal fluids are effective for the accumulation Re in molybdenite. X‐ray diffraction study of 14 molybdenite samples indicate that the molybdenites are of the 2H polytype.