Hydrogeochemical assessment of surface and groundwater resources of Korba coalfield,Central India: environmental implications

The present study assesses the impact of coal mining on surface and groundwater resources of Korba Coalfield, Central India. Accordingly, water samples collected from various sources are analyzed for major ions, trace elements, and other mine effluent parameters. Results show that the groundwater samples are slightly acidic, whereas river water and mine water samples are mildly alkaline. Elevated concentrations of Ca²⁺, Na⁺, HCO₃ ^?, and SO₄ ^2? alongside the molar ratios (Ca²⁺+Mg²⁺)/(SO₄ ^2?+HCO₃ ^?) <1 and Na⁺/Cl^? >1 suggest that silicate weathering (water-rock interaction) coupled with ion exchange are dominant solute acquisition processes controlling the chemistry of groundwater in the study area. The overall hydrogeochemistry of the area is dominated by two major hydrogeochemical facies (i.e., Ca–Cl–SO₄ and Ca–HCO₃). Analysis of groundwater and river water quality index (GRWQI) elucidates that majority (82%) of samples are of “excellent” to “good” category, and the remaining 12% are of “poor” quality. Similarly, the effluent water quality index (EWQI) indicates that 6 out of 8 samples belong to excellent quality. Concentration of trace element constituents such as As, Zn, Cu, Cr, and Cd is found to be well within the stipulated limits for potable use, except for Fe, Mn, and Pb. Suitability of water samples for irrigation purpose, established using standard tools like Wilcox and USSL diagrams, reveal “excellent to permissible” category for majority of the samples. The present study also substantiates the effectiveness of the measures implemented for the treatment of mine effluent water.     

An automated 3D modeling of topological indoor navigation network

Indoor navigation is important for various applications such as disaster management, building modeling, safety analysis etc. In the last decade, indoor environment has been a focus of wide research that includes development of indoor data acquisition techniques, 3D data modeling and indoor navigation. In this research, an automated method for 3D modeling of indoor navigation network has been presented. 3D indoor navigation modeling requires a valid 3D model that can be represented as a cell complex: a model without any gap or intersection such that two cells (e.g. room, corridor) perfectly touch each other. This research investigates an automated method for 3D modeling of indoor navigation network using a geometrical model of indoor building environment. In order to reduce time and cost of surveying process, Trimble LaserAce 1000 laser rangefinder was used to acquire indoor building data which led to the acquisition of an inaccurate geometry of building. The connection between surveying benchmarks was established using Delaunay triangulation. Dijkstra algorithm was used to find shortest path in between building floors. The modeling results were evaluated against an accurate geometry of indoor building environment which was acquired using highly-accurate Trimble M3 total station. This research intends to investigate and propose a novel method of topological navigation network modeling with a less accurate geometrical model to overcome the need of required an accurate geometrical model. To control the uncertainty of the calibration and of the reconstruction of the building from the measurements, interval analysis and homotopy continuation will be investigated in the near future.     

Holocene tectono-geomorphic evolution of Haryana plains,Western Ganga plain,India

Haryana plain is the drainage divide between the Ganga plain in the east and the Indus plain in the west. Being a part of the Himalayan foreland, its geomorphology, sedimentation processes, and tectonism are broadly controlled by the Himalayan tectonics. Soil and geomorphological mapping in Haryana plain bring out geomorphic features such as paleochannels, various active drainage patterns, and landforms such as old fluvial plains, floodplains, piedmonts, pediments, terminal fans, and eolian plains. Based on the degree of soil development, and Optical stimulated luminescence (OSL) ages, the soil-geomorphic units were grouped into six members (QIMS-I to VI) (Quaternary Indus Morphostratigraphic Sequence) of a morphostratigraphic sequence: QIMS-VI 9.86–5.38 Ka, QIMS-V 5.38–4.45 Ka, QIMS-IV 4.45–3.60 Ka, QIMS-III 3.60–2.91 Ka, QIMS-II <?2.91–1.52 Ka, and QIMS-I <?1.52 Ka. OSL chronology of different geomorphic features suggests six episodes of tectono-geomorphic evolution in the region since 10 Ka. Neotectonic features such as nine faults, two lineaments, and five fault-bounded tectonic blocks have been identified. Independent tilting and sagging of the blocks in response to neotectonics have resulted in modification of landforms, depositional processes, and hydro-geomorphology of the region. Major rivers like the Yamuna, the Ghaggar, and the Sutlej show different episodes of shifting of their courses. Lineament controlled few extinct channels have been recorded between 20 and 25 m depth below the surface in the ground-penetrating radar (GPR) profiles. These buried channels are aligned along the paleo-course of the Lost Saraswati River interpreted from the existing literature and hence are considered as the course of the lost river. Seven terminal fans have been formed on the downthrown blocks of the associated faults. The Markanda Terminal Fan, the first of such features described, is indeed a splay terminal fan and was formed by a splay distributary system of the Markanda River. Association of three terminal fans of different ages with the Karnal fault indicates the segment-wise development of the fault from west to east. Also, comparison with other such studies in the Ganga plain to further east suggests that the terminal fans formed by streams with distributary drainage pattern occur only in semiarid regions as in the present area and thus are indicators of semiarid climate/paleoclimate. Though the whole region is tectonically active, the region between the Rohtak fault and Hisar fault is most active at present signified by the concentration of earthquake epicenters.     

Role of unbalanced slab resistive force in the 2004 off Sumatra mega-earthquake (<Emphasis Type="Italic">M</Emphasis><Subscript>w</Subscript> > 9.0) event

Present study addresses the role of major plate-driving forces, particularly the slab pull and slab resistive forces, for the generation of 26 December 2004 M _w > 9.0 off Sumatra megathrust earthquake. Major controls on the plate-driving forces are normally visualized through age, speed, and average dip of the slab during subduction. Wide variation in age, plate obliquity, stress obliquity, subduction rate, dip angle, and flexing depth of the subducting oceanic lithosphere between Andaman and Sumatra thus allowed us for quantitative evaluation of the slab pull (F _SP) and slab resistive (F _SR) forces in three well-defined sectors (I, II and III). Computed values of these forces in the three sectors: (1) F _SP = 1.29 × 10¹³ N/m, F _SR = 1.41 × 10¹³ N/m; sector I, (2) F _SP = 2.10 × 10¹³ N/m, F _SR = 1.13 × 10¹³ N/m; sector II, and (3) F _SP = 2.08 × 10¹³ N/m, F _SR = 2.72 × 10¹³ N/m; sector III clearly suggest a spatial variation of stress regime in the subducting oceanic lithosphere. Excess F _SR in sectors I and III are interpreted as the causative forces behind the triggering of major seismic energy bursts near Sumatra and Andaman on 26 December 2004. A gap of minimum seismic energy burst near Great Nicobar possibly was controlled by the excess of F _SP in sector II. This study further advocates that the cyclic stress, resulted from unbalanced component of slab resistive force, had a definite control on the occurrence of 2004 off Sumatra megathrust earthquake around the flexing zone of the subducting lithosphere.     

Probabilistic seismic hazard assessment for some parts of the Indo-Gangetic plains,India

Natural Hazards - Indo-Gangetic plains are seismically most vulnerable due to the proximity of adjacent great Himalayan earthquakes and thick alluvium deposits of the Ganga River system. As the...     

Hybrid attenuation model for estimation of peak ground accelerations in the Kutch region, India

The Kutch region of Gujarat in India is the locale of one of the most devastating earthquake of magnitude (M _w) 7.7, which occurred on January 26, 2001. Though, the region is considered as seismically active region, very few strong motion records are available in this region. First part of this paper uses available data of strong motion earthquakes recorded in this region between 2006 and 2008 years to prepare attenuation relation. The developed attenuation relation is further used to prepare synthetic strong motion records of large magnitude earthquakes using semiempirical simulation technique. Semiempirical simulation technique uses attenuation relation to simulate strong ground motion records of any target earthquake. The database of peak ground acceleration obtained from simulated records is used together with database of peak ground acceleration obtained from observed record to develop following hybrid attenuation model of wide applicability in the Kutch region: $$ \begin{aligned} \ln \left( {\text{PGA}} \right) & = - 2.56 + 1.17 \, M_{\text{w}} - \, 0.015R - 0.0001\ln \left( {E + 15} \right) \\ &\quad 3.0 \le M_{\text{w}} \le 8.2;\quad 12 \le R \le 120;\quad {\text{std}} . {\text{ dev}}.(\sigma ): \pm 0.5 \\ \end{aligned} $$ ln ( PGA ) = ? 2.56 + 1.17 M w ? 0.015 R ? 0.0001 ln ( E + 15 ) 3.0 ≤ M w ≤ 8.2 ; 12 ≤ R ≤ 120 ; std . dev . ( σ ) : ± 0.5 In the above equation, PGA is maximum horizontal ground acceleration in gal, M _w is moment magnitude of earthquake, R is hypocentral distance, and E is epicentral distance in km. The standard deviation of residual of error in this relation is 0.5. This relation is compared with other available relations in this region, and it is seen that developed relation gives minimum root mean square error in comparison with observed and calculated peak ground acceleration from same data set. The applicability of developed relation is further checked by testing it with the observed peak ground acceleration from earthquakes of magnitude (M _w), 3.6, 4.0, 4.4, and 7.7, respectively, which are not included in the database used for regression analysis. The comparison demonstrates the efficacy of developed hybrid attenuation model for calculating peak ground acceleration values in the Kutch region.