Estimation of sediment load and erosion of different geological units: A case study from a basin of north-eastern Iran

Erosion of geological units and sediment load in rivers can be considered as the serious problems in recent decades.Increasing sediment loads generate major hazards for water resources development,particularly in terms of loss of reservoir storage due to sedimentation and siltation of water distribution systems.In this paper,the performance of four sediment rating curve (SRC) development methods was evaluated for the Shirin Darreh River(SDR) basin (1750 km2),located in North Khorasan Province,Iran.Data of flow discharge (Q) and suspended sediment flux (SSF)(Q-SSF pairs,N=957)and daily flow discharge,recorded by the Regional Water Company of North Khorasan (RWCNK) at the Qaleh-Barbar (QB) gauging site during 1989-2018were used.The flow discharge classification method performed best by meeting the desired criteria of most statistical indices,including normalized root mean square error (NRMSE),mean bias error (MBE),mean absolute error (MAE),index of agreement (d),and coefficient of determination (R~2).Based on the optimized method,the rate of suspended sediment transportation at the study site was estimated about2.7×10~6 ton year~(-1).Erodibility of the exposed formations in the study area was estimated based on a factorial scoring model (FSM).Three indices,focused on the outcrop and erodibility,were calculated for the geological units at sub-basin and total scales.Marl deposits are the most extensive geological unit in the three sub-basins and the maximum formation outcrop ratio (FOR) and participation in erosion (PCE)were obtained for these rocks at total scale.In fact,marl unit can be regarded as the main source to supply the suspended sediments in the study basin.     

Using inverse modeling and hierarchical cluster analysis for hydrochemical characterization of springs and Talkhab River in Tang-Bijar oilfield,Iran

Hierarchical cluster analysis (HCA) and inverse modeling (PH REdox EQuilibrium (in C language) (PHREEQC)) were simultaneously useful approaches in interpreting surface water hydrochemistry within Talkhab River in the Tang-Bijar oilfield, Iran, where large uncertainties exist in the understanding of the water quality system. Q-mode HCA applied to the data revealed three major surface water associations distinguished on the basis of the major causes of variation in the hydrochemistry. The three water groups were classified as upstream waters (group 1: Ca–SO₄), intermediate waters (group 2: Ca–SO₄–Cl), and downstream waters (group 3: Na–Cl). Geochemical reaction models were constructed using PHREEQC to establish the reactions associated with the different mineral phases through inverse modeling. The hydrochemical compositions of the water groups and the mass balance calculations indicate that the dominant processes and reactions responsible for the hydrochemical evolution in the system are (1) dissolution of evaporites, (2) precipitation of carbonate minerals, (3) silicate weathering reactions, (4) limited mixing with saline water, and (5) ion exchange.     

Embedding eco-friendly and smart technology features in affordable housing for community happiness in Malaysia

GeoJournal - Two phases of study are involved in this research: first, the sales strategies for affordable houses embedded with eco-friendly and smart technology features; and second, the impact of...     

Composition and source identification of polycyclic aromatic hydrocarbons in mangrove sediments of Peninsular Malaysia: indication of anthropogenic input

This is a comprehensive study of the composition, origin and sources of specific polycyclic aromatic hydrocarbons (PAHs) in sediments of mangrove estuary in the western part of Peninsular Malaysia. Mangrove sediments were analyzed for 17 PAHs by gas chromatography–mass spectrometry. Total PAH concentrations in the sediments ranged from 20 to 112 ng/g on a dry-weight basis. High molecular weight PAHs were abundant in the sediments. Parent PAH ratios revealed that pyrogenic input has important contribution to the sedimentary PAHs. Ratios of alkylated PAHs indicate that the sedimentary PAHs were influenced by petrogenic PAHs, which implies that petrogenic input has contribution to the sedimentary PAHs but that it is not a major factor in distribution of PAHs within the estuary. Combustion-derived PAHs show a positive and very strong correlation with total PAHs (R ² = 0.926, p < 0.05). Total methylphenanthrenes show very weak correlation with total PAHs (R ² = 0.0928, p < 0.05). The PAH concentrations were found to increase with distance from the upstream of the estuary to the coastal area of the Straits of Malacca. For the assessment of sediment contamination using biological thresholds, none of the individual studied PAH compounds exceeded the values of the effect range low–effect range median guideline and the threshold effects level–probable effects level guideline. This study demonstrates that the sediments of the mangrove ecosystem facing the Straits of Malacca and Sumatra are influenced by anthropogenic PAH inputs as a result of human activities such as biomass burning, vehicle emissions and boating activities.     

Sources of sedimentary PAHs in tropical Asian waters: Differentiation between pyrogenic and petrogenic sources by alkyl homolog abundance

We collected surface sediment samples from 174 locations in India, Indonesia, Malaysia, Thailand, Vietnam, Cambodia, Laos, and the Philippines and analyzed them for polycyclic aromatic hydrocarbons (PAHs) and hopanes. PAHs were widely distributed in the sediments, with comparatively higher concentrations in urban areas (∑PAHs: ∼1000 to ∼100 000 ng/g-dry) than in rural areas (∼10 to ∼100 g-dry), indicating large sources of PAHs in urban areas. To distinguish petrogenic and pyrogenic sources of PAHs, we calculated the ratios of alkyl PAHs to parent PAHs: methylphenanthrenes to phenanthrene (MP/P), methylpyrenes + methylfluoranthenes to pyrene + fluoranthene (MPy/Py), and methylchrysenes + methylbenz[a]anthracenes to chrysene + benz[a]anthracene (MC/C). Analysis of source materials (crude oil, automobile exhaust, and coal and wood combustion products) gave thresholds of MP/P = 0.4, MPy/Py = 0.5, and MC/C = 1.0 for exclusive combustion origin. All the combustion product samples had the ratios of alkyl PAHs to parent PAHs below these threshold values. Contributions of petrogenic and pyrogenic sources to the sedimentary PAHs were uneven among the homologs: the phenanthrene series had a greater petrogenic contribution, whereas the chrysene series had a greater pyrogenic contribution. All the Indian sediments showed a strong pyrogenic signature with MP/P ≈ 0.5, MPy/Py ≈ 0.1, and MC/C ≈ 0.2, together with depletion of hopanes indicating intensive inputs of combustion products of coal and/or wood, probably due to the heavy dependence on these fuels as sources of energy. In contrast, sedimentary PAHs from all other tropical Asian cities were abundant in alkylated PAHs with MP/P ≈ 1-4, MPy/Py ≈ 0.3-1, and MC/C ≈ 0.2-1.0, suggesting a ubiquitous input of petrogenic PAHs. Petrogenic contributions to PAH homologs varied among the countries: largest in Malaysia whereas inferior in Laos. The higher abundance of alkylated PAHs together with constant hopane profiles suggests widespread inputs of automobile-derived petrogenic PAHs to Asian waters.     

Self-organised clustering for road extraction in classified imagery

The extraction of road networks from digital imagery is a fundamental image analysis operation. Common problems encountered in automated road extraction include high sensitivity to typical scene clutter in high-resolution imagery, and inefficiency to meaningfully exploit multispectral imagery (MSI). With a ground sample distance (GSD) of less than 2 m per pixel, roads can be broadly described as elongated regions. We propose an approach of elongated region-based analysis for 2D road extraction from high-resolution imagery, which is suitable for MSI, and is insensitive to conventional edge definition. A self-organising road map (SORM) algorithm is presented, inspired from a specialised variation of Kohonen's self-organising map (SOM) neural network algorithm. A spectrally classified high-resolution image is assumed to be the input for our analysis. Our approach proceeds by performing spatial cluster analysis as a mid-level processing technique. This allows us to improve tolerance to road clutter in high-resolution images, and to minimise the effect on road extraction of common classification errors. This approach is designed in consideration of the emerging trend towards high-resolution multispectral sensors. Preliminary results demonstrate robust road extraction ability due to the non-local approach, when presented with noisy input.     

Conjunctive use of surface water and groundwater via the bank infiltration method

The bank infiltration (BI) technique may be a viable option if the local climate, hydrological, and geological conditions are conducive. This study was specifically conducted to explore the possibility of using BI to source the polluted surface water in conjunction with groundwater. Three major factors were considered for evaluation: (1) investigation on the contribution of surface water through BI, (2) input of local groundwater, and (3) water quality characteristics of water supply. Initially, the geophysical method was employed to define the subsurface geology and hydrogeology, and isotope techniques were performed to identify the source of groundwater recharge and interaction between surface water and groundwater. The physicochemical and microbiological parameters of the local surface water bodies and groundwater were analyzed before and during water abstraction. Extracted water revealed a 5 %–98 % decrease in turbidity, as well as HCO₃ ⁺, SO₄ ^?, NO₃ ^?, Al, As, and Ca concentration reduction compared with those of Langat river water. However, water samples from test wells during pumping show high concentrations of Fe²⁺ and Mn²⁺. In addition, amounts of Escherichia coli, total coliform, and Giardia were significantly reduced (99.9 %). Pumping test results indicate that the two wells (DW1 and DW2) were able to sustain yields.     

Estimation of air-overpressure produced by blasting operation through a neuro-genetic technique

Blasting operations usually produce significant environmental problems which may cause severe damage to the nearby areas. Air-overpressure (AOp) is one of the most important environmental impacts of blasting operations which needs to be predicted and subsequently controlled to minimize the potential risk of damage. In order to solve AOp problem in Hulu Langat granite quarry site, Malaysia, three non-linear methods namely empirical, artificial neural network (ANN) and a hybrid model of genetic algorithm (GA)–ANN were developed in this study. To do this, 76 blasting operations were investigated and relevant blasting parameters were measured in the site. The most influential parameters on AOp namely maximum charge per delay and the distance from the blast-face were considered as model inputs or predictors. Using the five randomly selected datasets and considering the modeling procedure of each method, 15 models were constructed for all predictive techniques. Several performance indices including coefficient of determination (R ²), root mean square error and variance account for were utilized to check the performance capacity of the predictive methods. Considering these performance indices and using simple ranking method, the best models for AOp prediction were selected. It was found that the GA–ANN technique can provide higher performance capacity in predicting AOp compared to other predictive methods. This is due to the fact that the GA–ANN model can optimize the weights and biases of the network connection for training by ANN. In this study, GA–ANN is introduced as superior model for solving AOp problem in Hulu Langat site.     

A probabilistic model to improve reconciliation of estimated and actual grade in open-pit mining

Many of the open-pit mines suffer from the lack of reconciliation between estimated and actual grades. In a mining operation, grade reconciliation is the comparison between the values of the estimated grade calculated in exploration stage and the actual grade obtained from more reliable data such as blast holes?? samples. Many different factors affect the degree of reconciliation in a mining operation. In this paper, the factors related to estimated grade which affect the reconciliation process in the exploration stage of the orebody are investigated. These factors constitute the sources of uncertainty for the upcoming phases of the mining life. Among these parameters, the inherent variability, statistical uncertainty, and systematic uncertainty are the most important factors. In this work, these parameters are studied in further detail, and, accordingly, for each of these uncertainties, a correction factor is determined in the proposed model. The model was applied to the study of real data taken from an iron open-pit mine in Iran. The results of the case study indicated that the systematic uncertainty, inherent variability, and statistical uncertainty are, in order, the main sources of uncertainty on grade reconciliation process. Applying the correction factors to estimated grade values has increased the amount of grade reconciliation from 10%, at original condition, to 50%, at new condition, in the case study.     

Impacts of Methane on Carbon Dioxide Storage in Brine Formations

In the context of geological carbon sequestration (GCS), carbon dioxide (CO₂) is often injected into deep formations saturated with a brine that may contain dissolved light hydrocarbons, such as methane (CH₄). In this multicomponent multiphase displacement process, CO₂ competes with CH₄ in terms of dissolution, and CH₄ tends to exsolve from the aqueous into a gaseous phase. Because CH₄ has a lower viscosity than injected CO₂, CH₄ is swept up into a ‘bank’ of CH₄‐rich gas ahead of the CO₂ displacement front. On the one hand, this may provide a useful tracer signal of an approaching CO₂ front. On the other hand, the emergence of gaseous CH₄ is undesirable because it poses a leakage risk of a far more potent greenhouse gas than CO₂ if the cap rock is compromised. Open fractures or faults and wells could result in CH₄ contamination of overlying groundwater aquifers as well as surface emissions. We investigate this process through detailed numerical simulations for a large‐scale GCS pilot project (near Cranfield, Mississippi) for which a rich set of field data is available. An accurate cubic‐plus‐association equation‐of‐state is used to describe the non‐linear phase behavior of multiphase brine‐CH₄‐CO₂ mixtures, and breakthrough curves in two observation wells are used to constrain transport processes. Both field data and simulations indeed show the development of an extensive plume of CH₄‐rich (up to 90 mol%) gas as a consequence of CO₂ injection, with important implications for the risk assessment of future GCS projects.