Development of a Land Subsidence Forecasting Model Using Small Baseline Subset—Differential Synthetic Aperture Radar Interferometry and Particle Swarm Optimization—Random Forest (Case Study: Tehran-Karaj-Shahriyar Aquifer,Iran)

Doklady Earth Sciences - Land subsidence, as a dangerous environmental issue, causes serious damages to farms and urban infrastructure. In this regards, this research was conducted with aimed to...     

Variability of Airborne Dust Fallout and Associated Trace Metals around Industrial Sites in Esfahan,Iran

The seasonal and spatial variability of airborne dust deposits and associated trace metals such as Pb, Co, Ni, Cd, Mn in 15 sites surrounding a heavily industrialized region in south Esfahan (central Iran) are investigated. Total deposit rates (TDR) of dusts and trace metals are analyzed, contamination factor (CF) and pollution load index (PLI) are also calculated. Furthermore, correlation and cluster analysis are performed to identify the source of the pollution. The highest dust-TDR (15.97 g m⁻² per season), the highest concentration of trace metals, CF and PLI are recorded in summer because of the lack of precipitation, high temperature, and drought conditions in this season. Pb and Cd show the highest CF values. In the towns near the two major steel mills in the region (i.e., Esfahan Steel Company and Mobarekeh Steel Complex), the CF values for Pb and Cd are about 13 and 12, respectively (i.e., 13 and 12 times higher than the pre-industrial values, respectively). The spatial distribution maps of the dust deposit rate, dust-borne trace metals, and the obtained PLI of the trace metals in the study area reveal that the two major industries in the region are the main sources of dust and trace metal distribution.     

Modeling the impact of groundwater harvesting on the hydro-salinity of a saline catchment in southeastern Australia

Recharge to a saline, unconfined shallow-water-table aquifer is normally considered as an irrecoverable loss of water, but such thinking could be reviewed empirically. The use of an appropriate groundwater harvesting system does not only provide an opportunity to recover this lost water, but can also help in catchment salinity management and improvement. Agricultural-based land-drainage systems such as those that use serial biological concentration (SBC) of salts, provide examples of such harvesting methods. The impact of groundwater harvesting has been assessed on the hydro-salinity of a saline catchment in southeastern Australia through modeling. For both the below average rainfall and very wet years, the “do nothing” scenario resulted in increasing salinization in the catchment. However, after introducing a SBC system, groundwater salinity showed a decreasing trend while hydraulic heads tended to stabilize around the depth of subsurface collector wells. However, for a successful groundwater harvesting system, proper understanding of the groundwater flows and salt mobilization associated with a catchment is necessary. The outcomes of this modelling study have the potential to address similar issues (salinization) and/or needs (water harvesting) existing elsewhere in the world, particularly in semi-arid regions.

A supervised committee machine artificial intelligent for improving DRASTIC method to assess groundwater contamination risk: a case study from Tabriz plain aquifer,Iran

Vulnerability maps are designed to show areas of greatest potential for groundwater contamination on the basis of hydrogeological conditions and human impacts. The objective of this research is (1) to assess the groundwater vulnerability using DRASTIC method and (2) to improve the DRASTIC method for evaluation of groundwater contamination risk using AI methods, such as ANN, SFL, MFL, NF and SCMAI approaches. This optimization method is illustrated using a case study. For this purpose, DRASTIC model is developed using seven parameters. For validating the contamination risk assessment, a total of 243 groundwater samples were collected from different aquifer types of the study area to analyze \( {\text{NO}}_{ 3}^{ - } \) concentration. To develop AI and CMAI models, 243 data points are divided in two sets; training and validation based on cross validation approach. The calculated vulnerability indices from the DRASTIC method are corrected by the \( {\text{NO}}_{3}^{ - } \) data used in the training step. The input data of the AI models include seven parameters of DRASTIC method. However, the output is the corrected vulnerability index using \( {\text{NO}}_{3}^{ - } \) concentration data from the study area, which is called groundwater contamination risk. In other words, there is some target value (known output) which is estimated by some formula from DRASTIC vulnerability and \( {\text{NO}}_{3}^{ - } \) concentration values. After model training, the AI models are verified by the second \( {\text{NO}}_{3}^{ - } \) concentration dataset. The results revealed that NF and SFL produced acceptable performance while ANN and MFL had poor prediction. A supervised committee machine artificial intelligent (SCMAI), which combines the results of individual AI models using a supervised artificial neural network, was developed for better prediction of vulnerability. The performance of SCMAI was also compared to those of the simple averaging and weighted averaging committee machine intelligent (CMI) methods. As a result, the SCMAI model produced reliable estimates of groundwater contamination risk.     

Providing interoperability for air quality in-situ sensors observations using GML technology

Geographic information provides the basis for many types of decisions ranging from simple path finding, to the sustainable management of environmental conditions. Producing such information is a time consuming and costly endeavor. Data sharing on the web is an avenue to increase the efficiency of the practices. This paper scientifically examines the new emerging technologies namely, internet, geographic markup language (GML), and observation and measurement models, to construct an interoperable repository for air quality sensors measurements. The paper also elaborates on the design and implementation of a web-based air quality information system (AQIS) for the city of Tehran. In-situ sensors measure ozone (C₃), carbon monoxide (CO), sulfur dioxide (SC₂), nitrogen dioxide (NC₂) and particulate matters (PM) in polluted metropolitans. Providing real-time air quality information can improve the decisions of the pertinent environmental organizations. Using GML for encoding sensors observations makes it possible to build an interoperable repository that is independent of platforms and vendors. Providing query possibilities based on monitoring stations, sensor names (pollutants), date and time intervals, and spatial query on the AQIS interfaces are the major functions of this system. Although standardized, it was concluded that the use of GML as data format increases the size of GML document. In addition, the developed system provides no map based results for the clients. Therefore, it is required to be improved by adding more GIS functions.     

Multivariate statistics and hydrogeochemical modeling for source identification of major elements and heavy metals in the groundwater of Qareh-Ziaeddin plain,NW Iran

The present study aims to evaluate the possible source of major and some minor elements and heavy metals in the groundwater of Qareh-Ziaeddin plain, NW Iran with respect to chemical elements, saturation index, and multivariate statistics including correlation coefficient, cluster analysis, and factor analysis. Groundwater samples were collected in Jun 2016 and measured with respect to EC, pH, major and some minor elements and heavy metals including Fe, Mn, Zn, Cr, Pb, Cd, Al, and As. Among all the measured parameters, some of the samples exceed the World Health Organization (WHO) guideline value for EC, Na, Mg, HCO₃, SO₄, Cl, NO₃, F, As, Zn, and Pb. The results of correlation analysis show that weathering and dissolution of minerals especially evaporites and silicates, water-rock interaction, and cation exchange are dominant occurred processes in the groundwater of the study area. Also, denitrification process is occurred in the groundwater system. Cluster analysis categorizes the samples into three distinct groups which are different based on their EC and dependent variables, e.g., Na, Ca, Cl, SO₄ and pH, Pb, Cd, and As. It can be found that volcanic, evaporite, and clay formations have the least impact on the chemistry of the cluster 1 samples while clay and evaporite formations have the highest impact on the cluster 3 and also calcareous formations on cluster 2. Factor analysis shows that five factors, with total variance of 83%, are effective in the release of heavy metals and groundwater chemistry which are mostly geogenic.     

The evaluation of borehole imaging result comparing with cores in Sarvak fractured and non-fractured reservoir

Core samples are still today considered as the standard measurement against all other measurements which must be compared. Core analysis usually focuses on the worse portion of the reservoir due to the fact that core recovery has rarely been well in a highly fractured zone; hence, permeability measured from core sample is often not representative. Core analysis is a common method to identify small-scale fractures of the well and permeability and porosity; however, there are some limitations in the core procedure such as it is highly expensive and unidirectional and has a low recovery coefficient in fractured zone. In contrast, there tends to be a mistrust and even a suspicion of those logging instruments that make measurements which threaten to replicate or even replace the “sacred core.” Thus, image logs are more useful to study the subsurface fractures in these such cases and the logs which come closest to achieving this are the high-resolution micro resistivity (OBMI) and acoustic geological imaging (UBI). The core and OBMI-UBI result was matched in order to verify the log measurements. Furthermore, FMI data were integrated with other open-hole logs to derive a permeability curve. As demonstrated in the case studies, it is believed that the permeability in the basement could be reasonably evaluated using this method. As a result, this exercise has proven to be very valuable, not only for demonstrating the value of the log data, but also it has also highlighted some significant limitations of the core in water-based mud and oil-based mud systems.     

Exploring Placer Gold Deposits through Integrated Geophysical and Geochemical Techniques at the Confluence of the Indus and Kabul Rivers, NW Pakistan

Analysis of the anomalous magnetic mineral intensities and geochemistry for placer gold deposits are presented for those of the Attock area at the confluence of the Indus and Kabul rivers in northwestern Pakistan. Two grids covering an area of 10x18 m2 and 8x10 m2 were analyzed using a G-858 Cesium Vapor Magnetometer. The anomalous zones obtained were plotted on contour maps, 2D and 3D magnetic intensity maps. Based on the magnetic anomalies, grid-1 of the study area was sampled at three different anomalous zones for geochemical analysis. These zones contain gold concentrations, ranging from 2.11 ppm to 6.109 ppm with an average of 4.01 ppm. Increase in gold concentration in the subsurface within the anomalous zones indicates that magnetometer survey followed by a geochemical analysis can potentially narrow down the gold-bearing anomalous zones.     

Mineralogical and geochemical study of bentonite deposits of Garhi Chandan area,District Nowshera,Khyber Pakhtunkhwa,Pakistan

The Pliocene-Pleistocene Ghari Chandan Formation consists of lacustrine-fluvio-deltaic deposits exposed in the Attock-Cherat Range. Three beds of bentonite deposits occur in the upper part of the formation. An average thickness of each layer ranges from 0.4 to 1 m with a total strike length of ~5 Km. Montmorillonite and saponite clay minerals with admixtures of quartz, feldspar, muscovite, biotite, and hornblende were identified in these samples. Compositionally these beds are similar and comprised of dioctahedral smectite. The differential thermal analyses of bentonite reveals high thermal stability of the deposits. Detailed mineralogical and geochemical investigations suggest that the Garhi Chandan deposit is a mixture of calcic and sodic bentonite derived from andesitic and trachyandesitic source rock. Heavy metal concentration reduces the overall adsorbing capacity of the deposit.     

Water consumption of a six-year-old river red gum plantation in the Southern Zagros Mountains, Iran

Water is the most important limiting factor in the development of arid environments; therefore, optimization of water use is a necessity in desert reclamation projects. Evapotranspiration of a 6-year-old river red gum (Eucalyptus camaldulensis Dehnh.) plantation, located in a sedimentation basin of an artificial recharge of the Gareh Bygone Plain groundwater system in Iran’s southern Zagros Mountains, was studied during a 7-month period. A neutron moisture probe was used to monitor soil water changes in the root zone. Soil water depletion following rapid drainage for blocks receiving relatively high, medium and low volumes of floodwater were 809.6, 312.4, and 203.1 mm, respectively, for a 150-day period. Soil water potential during most of the study period was below -1.5 MPa. This study proves that river red gum in not a suitable species for desertification control where water conservation is of vital importance. Flood irrigation of trees on 8 Aug. 1991 provided the opportunity to throw doubt upon the claim of summer dormancy of river red gum.