Application of “panel-data” modeling to predict groundwater levels in the Neishaboor Plain, Iran

The aim of this research was to predict groundwater levels in the Neishaboor plain, Iran, using a ??panel-data?? model. Panel-data analysis endows regression analysis with both spatial and temporal dimensions. The spatial dimension pertains to a set of cross-sectional units of observation. The temporal dimension pertains to periodic observations of a set of variables characterizing these cross-sectional units over a particular time span. Firstly, the available observation wells in the Neishaboor plain were clustered according to their fluctuation behavior using the ??Ward?? method, which resulted in six areal zones. Then, for each cluster, an observation well was selected as its representative, and for each zone, values of monthly precipitation and temperature, as independent variables, were estimated by the inverse-distance method. Finally, the performance of different panel-data regression models such as fixed-effects and random-effects models were investigated. The results showed that the two-way fixed-effects model was superior. The performance indicators for this model (R ²?=?0.97, RMSE?=?0.05?m and ME?=?0.81?m) reveal the effectiveness of the method. In addition, the results were compared with the results of an artificial-neural-network (ANN) model, which demonstrated the superiority of the panel-data model over the ANN model.     

Storage-yield analysis of surface water reservoirs: the role of reliability constraints and operating policies

Stochastic optimization methods are used for optimal design and operation of surface water reservoir systems under uncertainty. Chance-constrained (CC) optimization with linear decision rules (LDRs) is an old approach for determining the minimum reservoir capacity required to meet a specific yield at a target level of reliability. However, this approach has been found to overestimate the reservoir capacity. In this paper, we propose the reason for this overestimation to be the fact that the reliability constraints considered in standard CC LDR models do not have the same meaning as in other models such as reservoir operation simulation models. The simulation models have fulfilled a target reliability level in an average sense (i.e., annually), whereas the standard CC LDR models have met the target reliability level every season of the year. Mixed integer nonlinear programs are presented to clarify the distinction between the two types of reliability constraints and demonstrate that the use of seasonal reliability constraints, rather than an average reliability constraint, leads to 80–150 % and 0–32 % excess capacity for SQ-type and S-type CC LDR models, respectively. Additionally, a modified CC LDR model with an average reliability constraint is proposed to overcome the reservoir capacity overestimation problem. In the second stage, we evaluate different operating policies and show that for the seasonal (average) reliability constraints, open-loop, S-type, standard operating policy, SQ-type, and general SQ-type policies compared to a model not using any operation rule lead to 190–460 % (200–550 %), 100–200 % (80–300 %), 0–90 % (0–60 %), 30–90 % (0–20 %), and 10–90 % (0–10 %) excess capacity, respectively.     

Global morphology of ionospheric sporadic E layer from the FormoSat-3/COSMIC GPS radio occultation experiment

Ionospheric sporadic-E (Es) activity and global morphology were studied using the 50 Hz signal-to-noise ratio amplitude and excess phase measurements from the FormoSat-3/Constellation Observing System for Meteorology, Ionosphere and Climate (FS3/COSMIC) GPS radio occultation (RO) observations. The results are presented for data collected during the last sunspot cycle from mid-2006 to the end of 2017. The FS3/COSMIC generally performed more than 1000 complete E-region GPS RO observations per day, which were used to retrieve normalized L1-band amplitude standard deviation (SDL1) and relative electron density (N_e) profiles successfully. More or less 31% of those observations were identified as Es events based on SDL1 and peak SDL1 altitude criteria. We found that the peak Es-event i values are approximately proportional to the logarithms of the corresponding peak N_e differences. Five major geographical zones were identified, in which the seasonal and diurnal Es occurrence patterns are markedly different. These five zones include the geomagnetic equatorial zone (??5°?<?magnetic latitude (ML)?<?5°), two extended geomagnetic mid-latitude zones (15°?<?ML?<?55°, and ??55°?<?ML < ??15°), and two auroral zones (70°?<?ML, and ML < ??70°). The Es climatology, namely its variations with each identified zone, altitude, season, and local time has been documented.     

Identifying complexity of annual precipitation variation in Iran during 1960–2010 based on information theory and discrete wavelet transform

The hydrologic process and dynamic system of precipitation is influenced by many physical factors which are excessively complex and variable. Present study used a wavelet transform based multiscale entropy (WME) and wavelet-based multiscale relative entropy (WMRE) approach in order to analyze and gage the complexity of the precipitation series and spatially classify the raingauges in Iran. For this end, historical annual precipitation data of 51 years (1960–2010) from 31 raingauges was decomposed using WT in which smooth Daubechies (db) mother wavelet (db5–db10), optimal level of decomposition and boundary extensions were considered. Next, entropy concept was applied for components obtained from WT to measure of dispersion, uncertainty, disorderliness and diversification in a multi-scale form. Spatial classification of raingauges was performed using WME and WMRE values as input data to SOM and k-means approaches. Three validity indices namely Davis Bouldin (DB), Silhouette coefficient (SC) and Dunn index were used to validate the proposed model’s efficiency. Based on results, it was observed that k-means approach had better performance in determining homogenous areas with SC = 0.337, DB = 0.769 and Dunn = 1.42. Finally, spatial structure of precipitation variation in latitude and longitude directions demonstrated that WME and WMRE values had a decreasing trend with latitude, however, it was seen that WME and WMRE had an increasing relationship with longitude in Iran.     

Origin of 1.8 Ga zircons in Post Eocene mafic dikes in the Roshtkhar area,NE Iran

The Roshtkhar area is located in the Khaf-Kashmar-Bardaskan volcano-plutonic belt to the northeastern Iran along the regional E–W trending Dorouneh Fault, northeastern of the Lut Block. There are several outcrops of subvolcanic rocks occurring mainly as dikes in the area, which intruded into Cenozoic intrusive rocks. We present U–Pb dating of zircons from a diabase dike and syenite rock using LA-ICP-MS that yielded an age of 1778 ± 10 Ma for the dike, indicating this Cenozoic dike has zircon xenocrysts inherited from deeper sources; and 38.0 ± 0.5 Ma, indicating an Late Eocene crystallization age for the syenite. Geochemically, the dikes typical of high-K calc-alkaline to shoshonitic magmas. Petrographic observations and major and trace element variations suggest that diabase melts underwent variable fractionation of clinopyroxene, olivine, and Fe-Ti oxides and minor crustal contamination during the differentiation process. Primitive mantle-normalized multi-element diagrams display enrichment in LILE, such as Rb, Ba, Th, U, and Sr compared to HFSE, as well as negative anomalies of Nb, Ta, P, and Ti, suggesting derivation from subduction-modified mantle. Chondrite-normalized REE plots show moderately LREE enriched patterns (<3.83 La_N/Yb_N <8.27), and no significant Eu anomalies. Geochemical modelling using Sm/Yb versus La/Yb and La/Sm ratios suggests a low-degree of batch melting (~1–3%) of a phlogopite-spinel peridotite source to generate the mafic dikes. The geochemical signatures suggest that the Roshtkhar mafic dikes cannot be related directly to subduction and likely resulted from melting of upper mantle in an extensional setting where the heat flow was provided from deeper levels. These dikes presumably derived the zircon xenocrysts from the assimilation of upper crust of Gondwanian basement. Processes responsible for partial melting of metasomatized lithospheric mantle and post-collision magmatism in NE Iran was triggered by heating due to asthenospheric upwelling in an extensional setting.     

Hydrothermal evolution of Darrehzar porphyry copper deposit,Iran: evidence from fluid inclusions

The Darrehzar porphyry Cu-Mo deposit is located in Southwestern Iran (～70 km southwest of Kerman City). The porphyries occur as Tertiary quartz-monzonite stocks and dikes, ranging in composition from microdiorite to diorite and granodiorite. The Darrehzar stock is highly altered, and even in the outermost part of the intrusion, it is not possible to find completely fresh rock. Surface weathering was developing ferrous Fe-rich lithologic units in leached zone and concentrated copper minerals in supergene zone. Unlike eastern areas which do not account for deep faults, the supergene zone is well developed in western areas with maximum of 118 m thickness. Hydrothermal alteration and mineralization at Darrehzar are centered on the stock and were broadly synchronous with its emplacement. Early hydrothermal alteration was dominantly potassic and propylitic, and was followed by later phyllic and argillic alteration. The hydrothermal system involved both magmatic and meteoric water and boiled extensively. Copper mineralization was accompanied by both potassic and phyllic alteration. Four main vein groups have been identified: (I) quartz?+?pyrite?±?molybdenite?±?anhydrite?±?K-feldspar?±?chalcopyrite?±?bornite?±?Cu and Fe oxidic minerals (peripheral); (II) quartz?+?chalcopyrite?+?pyrite?+?molybdenite; (III) quartz?+?pyrite?±?calcite?±?chalcopyrite?±?anhydrite (gypsum); and (IV) quartz or calcite, gypsum or ± pyrite. Based on abundance, nature, and phases number observed at room temperature, three types of fluid inclusions are typically observed in these veins: (1) vapor-rich, (2) liquid-rich, and (3) multi-phase. Early hydrothermal alteration was caused by high temperature, high salinity orthomagmatic fluid and produced a potassic assemblage. Phyllitic alteration was caused by high salinity and lower temperature orthomagmatic fluid. Magmatic and meteoric water mixture was developed in the peripheral part of the stock and caused propylitic alteration which is attributed to a liquid-rich, lower temperature.     

完整岩石在不同尺度上的屈服

对完整岩石力学机制的研究有助于更好地理解与屈服有关的应力-应变关系。屈服准则研究方法包括基于实验数据分析和基于微观力学的研究。屈服数学理论的研究目标是对应力和应变关系的理论描述和对弹塑性界限的识别。本文主要研究完整岩石在不同尺度上的屈服。从Weibull理论可知,岩石强度随尺度增大而减少,这已经通过单轴压缩强度（UCS）的Hoek-Brown方程得到证实。然而,围压能改变岩石强度及屈服。因此,本文利用直径为50mm和96mm的圆柱形砂岩样品在不同围压作用下的压缩实验来研究不同尺度下的岩石屈服,从实验中提取不同尺度下的屈服初始点并描述屈服面,最终给出简单数学形式的屈服准则。     

Global Ionosphere Maps of VTEC from GNSS,satellite altimetry,and formosat-3/COSMIC data

For space geodetic techniques, operating in microwave band, ionosphere is a dispersive medium; thus signals traveling through this medium are in the first approximation affected proportional to inverse of the square of their frequencies. This effect allows gaining information about the parameters of the ionosphere in terms of Total Electron Content (TEC) or the electron density (N _e ). TEC or electron density can then be expressed by means of spherical harmonic base functions to provide a Global Ionosphere Map (GIM). The classical input data for development of GIMs are obtained from dual-frequency observations carried out at Global Navigation Satellite Systems (GNSS) stations. However, GNSS stations are in-homogeneously distributed around the world, with large gaps particularly over the oceans; this fact reduces the precision of the GIM over these areas. On the other hand, dual-frequency satellite altimetry missions such as Jason-1 provide information about the ionosphere precisely above the oceans; and furthermore Low Earth Orbiting (LEO) satellites, such as Formosat-3/COSMIC (F/C) provide well-distributed information of ionosphere globally. This study investigates on global modeling of TEC through combining GNSS and satellite altimetry data with global TEC data derived from the occultation measurements of the F/C mission. The combined GIMs of vertical TEC (VTEC) show a maximum difference of 1.3–1.7 TEC units (TECU) with respect to the GNSS-only GIMs in the whole day. The root mean square error (RMS) maps of combined solution show a reduction of about 0.1 TECU in the whole day. This decrease of RMS can reach up to 0.5 TECU in areas where no or few GNSS observations are available, but high number of F/C measurement is carried out. This proves that the combined GIMs provide a more homogeneous global coverage and higher reliability than results of each single method. All comparisons and validations made within this study provide vital information regarding combination and integration of various observation techniques in the Global Geodetic Observing System of the International Association of Geodesy.     

A hydrochemical and dye- tracing investigation in the Posht-e-Naz Karstic Aquifer, Alburz Mountain, Northern Iran

A hydrochemical and tracer study (uranine injection) was conducted in Jurassic limestone of the Posht-e-Naz area in the Alborz belt to evaluate hydraulic relations between a large diameter (about 100 m) sinkhole and springs and aquifer parameters. A main goal of the project was to find out the source of turbidity of the Emarate drinking water supply spring (SP4) in rainy season. Springs discharge were measured and hydrochemical investigation were carried out. The uranine tracer was injected and eight springs, three wells and the Neka River were selected and totally 989 samples in 107 days were collected. Hydrochemical data demonstrated a relative connection between sinkhole (Sh1) and spring (SP4). The results of the tracing by sampling water indicated only a hydraulic connection between Sange- Nou spring (SP8) and injection point, while the charcoal packets analysis revealed tracer exits from spring numbers SP1, SP3, SP4, SP5, SP8, in wells W1 and W2, and in the Neka River. The concentration — time curves of charcoal packets for qualitative analysis and exit tracer for quantitative analysis is also assessed.     

A spatiotemporal Bayesian maximum entropy-based methodology for dealing with sparse data in revising groundwater quality monitoring networks: the Tehran region experience

Data inadequacy is a common problem in designing or updating groundwater monitoring systems. The developed methodologies for the optimal design of groundwater monitoring systems usually assume that there is a complete set of data obtained from existing monitoring wells and provide a revised configuration for the system by analyzing the current data. These methodologies are not usually applicable when the current groundwater quantity and quality data are highly sparse. In this paper, a new simulation–optimization approach based on Bayesian maximum entropy theory (BME) is proposed for revising spatial and temporal monitoring frequencies in a sparsely monitored aquifer. The BME is used to simulate the spatial and spatiotemporal variations of groundwater indicators, incorporating the space/time uncertainties due to insufficient data. Comparing the obtained estimations with observations, the best BME model was selected to be linked with an optimization model. The main goal of optimization was to find out the spatial and temporal sampling characteristics of the monitoring stations using the concepts of Entropy theory and a groundwater vulnerability index. The results show the BME estimations are less biased and more accurate than Ordinary Kriging in both spatial and spatiotemporal analysis. The improvements in the BME estimates are mostly related to incorporating hard (accurate) and soft (uncertain) data in the estimation process. The applicability and efficiency of the proposed methodology have been evaluated by applying it to the Tehran aquifer in Iran which is suffering from high groundwater table fluctuations and nitrate pollution. Based on the results, in addition to the existing monitoring wells, seven new monitoring stations have been proposed. Few stations which potentially can be removed or combined with other stations have been identified and a monthly sampling frequency has been suggested.