Bayesian geological and geophysical data fusion for the construction and uncertainty quantification of 3D geological models

Traditional approaches to develop 3D geological models employ a mix of quantitative and qualitative scientific techniques,which do not fully provide quantification of uncertainty in the constructed models and fail to optimally weight geological field observations against constraints from geophysical data.Here,using the Bayesian Obsidian software package,we develop a methodology to fuse lithostratigraphic field observations with aeromagnetic and gravity data to build a 3D model in a small(13.5 km×13.5 km)region of the Gascoyne Province,Western Australia.Our approach is validated by comparing 3D model results to independently-constrained geological maps and cross-sections produced by the Geological Survey of Western Australia.By fusing geological field data with aeromagnetic and gravity surveys,we show that 89%of the modelled region has>95%certainty for a particular geological unit for the given model and data.The boundaries between geological units are characterized by narrow regions with<95%certainty,which are typically 400-1000 m wide at the Earth's surface and 500-2000 m wide at depth.Beyond~4 km depth,the model requires geophysical survey data with longer wavelengths(e.g.,active seismic)to constrain the deeper subsurface.Although Obsidian was originally built for sedimentary basin problems,there is reasonable applicability to deformed terranes such as the Gascoyne Province.Ultimately,modification of the Bayesian engine to incorporate structural data will aid in developing more robust 3D models.Nevertheless,our results show that surface geological observations fused with geophysical survey data can yield reasonable 3D geological models with narrow uncertainty regions at the surface and shallow subsurface,which will be especially valuable for mineral exploration and the development of 3D geological models under cover.     

GPS-derived precipitable water vapour and its comparison with MODIS data for Almora, Central Himalaya, India

The present study is an attempt to analyse the precipitable water vapour (PWV) derived from Global Positioning System (GPS) and observed meteorological data over Almora, Central Himalayan Region. The PWV values derived using GPS study is compared with the corresponding moderate resolution imaging spectro-radiometer (MODIS) data. The statistical analysis reveals a positive correlation between both methods. Moderate resolution imaging spectroradiometer near-infrared (MODIS NIR) clear column water vapour product shows a higher correlation (R ² = 90–93 %) with GPS-derived precipitable water vapour on annual scale as compared to the seasonal scale (R ² = 62–87 %). MODIS is found to be overestimating in NIR clear column where the magnitude of bias and RMSE show systematic changes from season to season. Monsoon is an important phenomenon in the Indian weather context and holds significant importance in Central Himalayan ecosystem. The monthly and seasonal variation in precipitable water vapour is related with monsoon onset in the region. Diurnal variations in precipitable water vapour are studied with other meteorological data over Almora during dry and wet season. The precipitable water vapour had minimum value in the morning, increases in the afternoon to evening and again decreases to the midnight in both the dry and wet seasons. These results suggest that diurnal variation of water vapour is caused by the transport of water vapour by thermally induced local circulation.     

Assessment of environmental flow requirements

Flow is considered to be the master variable for a river because the fluvial processes and health of its ecosystem critically depend upon flow. Increasing water withdrawals from many rivers of the world are leading to severe degradation in river ecosystems. Water is allocated for environmental needs so that a river can perform its natural functions. This article discusses the concept of environmental flow, methods to assess it, and issues in implementation. Copyright © 2012 John Wiley & Sons, Ltd.     

Tectonic and magmatic evolution of the eastern Karakoram,India

Abstract

The Shyok suture zone separates the Ladakh terrane to the SW from the Karakoram terrane to the NE. Six tectonic units have been distinguished. From south to north these are; 1. Saltoro formation; 2. Shyok volcanites; 3. Saltoro molasse; 4. Ophiolitic melange; 5. Tirit granitoids; 6. Karakoram terrane including the Karakoram batholith. Albian—Aptian Orbitolina-bearing lime-stones and turbidites of the Saltoro formation tectonically overlie high-Mg-tholeiites similar to the tectonically overlying Shyok volcanites. The high-Mg tholeiitic basalts and calcalkaline andesites of the Shyok volcanites show an active margin signature. The Saltoro molasse is an apron-like, moderately folded association of redgreen shales and sandstones that are interbedded with ~ 50 m porphyritic andesite. Desiccation cracks and rain-drop imprints indicate deposition in a subaerial fluvial environment. Rudist fragments from a polygenic conglomerate of the Saltoro molasse document a post-Middle Cretaceous age. The calcalkaline andesites of the Shyok volcanites are intruded by the Tirit granitoids, which are located immediately south of the Ophiolitic melange and belong to a weakly deformed trondhjemite-tonalite-granodiorite-granite suite. These granitoids are subalkaline, I-type and were emplaced in a volcanic arc setting. The subalkaline to calcalkaline granitoids of the Karakoram batholith are I-and S-type granitoid. The I-type granitoids represent a typical calcalkaline magmatism of a subduction zone environment whereas the S-type granitoids are crustderived, anatectic peraluminous granites. New data suggest that the volcano-plutonic and sedimentary successions of the Shyok suture zone exposed in northern Ladakh are equivalent to the successions exposed along the Northern suture in Kohistan. It is likely that the o istan and Ladakh blocks evolved as one single tectonic domain uring the Cretaceous-Palaeogene. Subsequently, collision, suturing and accretion of the Indian plate along the Indus suture (50–60 Ma) together with tectonic activity along the Nanga Parbataramosh divided Kohistan and Ladakh into two arealy distinct magmatic arc terranes. The activity and a dextral offset along the Karakoram fault (Holocene-Recent) disrupted the original tectonic relationships. © 1999 Éditions scientifiques et médicales Elsevier SAS     

A review of the stratigraphy and geological setting of the Palaeoproterozoic Magondi Supergroup,Zimbabwe – Type locality for the Lomagundi carbon isotope excursion

The Palaeoproterozoic Magondi Supergroup lies unconformably on the Archaean granitoid-greenstone terrain of the Zimbabwe Craton and experienced deformation and metamorphism at 2.06–1.96 Ga to form the Magondi Mobile Belt. The Magondi Supergroup comprises three lithostratigraphic units. Volcano-sedimentary rift deposits (Deweras Group) are unconformably overlain by passive margin, back-arc, and foreland basin sedimentary successions, including shallow-marine sedimentary rocks (Lomagundi Group) in the east, and deeper-water shelf to continental slope deposits in the west (Piriwiri Group). Based on the upward-coarsening trend and presence of volcanic rocks at the top of the Piriwiri and Lomagundi groups, the Piriwiri Group is considered to be a distal, deeper-water time-equivalent of the Lomagundi Group. The Magondi Supergroup experienced low-grade metamorphism in the southeastern zone, but the grade increases to upper greenschist and amphibolite facies grade to the north along strike and, more dramatically, across strike to the west, reaching upper amphibolite to granulite facies in the Piriwiri Group.     

A decadal historical satellite data analysis for flood hazard evaluation: A case study of Bihar (North India)

Flood is one of the major recurrent natural disasters faced by the state of Bihar in north India. In the present study the authors assess the severity of flood hazard in Bihar, using 128 decadal historical satellite datasets acquired during different flood magnitudes during 1998 to 2010. The satellite‐based observations have been analysed in conjunction with the hydrological data, for assessing the frequency of inundation, severity of flood hazard and cropped land under flood hazard. This study assesses the spatial distribution of flooding and creation of systematic flood hazard database, which can be analysed from a spatial dimension in GIS. It is observed that about 24.56 lakh ha of the state's area and about 15.85 lakh ha of the cropped area are vulnerable to flood hazard. North Bihar is more vulnerable to flooding; 8 of the 10 areas identified as worst flood‐affected districts lie in this region.     

Rayleigh waves in an inhomogeneous medium

Summary Dispersion in Rayleigh waves is discussed for semi-infinite media with = ₁(1 ± cos s z) and = ₁(1 ± cosh s z), being the rigidity of the medium. A few workers tried with the above Fourier type of model but failed to find the dispersive nature. Because they neglected s due to the complexity of the calculation they arrived at a non dispersive frequency equation. This difficulty is removed in this paper and a dispersive frequency equation is obtained which shows both direct and inverse dispersion. The second model leads to non-convergent solution forz but shows many interesting results which are also discussed.     

On the interaction of mesoscale eddies and a tropical cyclone in the Bay of Bengal

Natural Hazards - Oceanic eddies span over a wide range of sizes and affect the thermodynamic properties of water column. By modifying the thermal structure of the upper ocean, these eddies...     

Comparison of TRMM and water district rain rates over New Mexico

This paper compares monthly and seasonal rain rates derived from the Version 5 (V5) and Version 6 (V6) TRMM Precipitation Radar (TPR, TSDIS reference 2A25), TRMM Microwave Imager (TMI, 2A12), TRMM Combined Instrument (TCI, 2B31), TRMM calibrated IR rain estimates (3B42) and TRMM merged gauge and satellite analysis (3B43) algorithms over New Mexico (NM) with rain gauge analyses provided by the New Mexico water districts (WD). The average rain rates over the NM region for 1998–2002 are 0.91mmd?1 for WD and 0.75, 1.38, 1.49, 1.27, and 1.07mmd?1 for V5 3B43, 3B42, TMI, PR and TCA; and 0.74, 1.38, 0.87 and 0.97 mm d?1 for V6 3B43, TMI, TPR and TCA, respectively. Comparison of V5 3B43 with WD rain rates and the daily TRMM mission index (TPR and TMI) suggests that the low bias of V5 3B43 for the wet months (summer to early fall) may be due to the non-inclusion of some rain events in the operational gauge analyses that are used in the production of V5 3B43. Correlation analyses show that the WD rain rates vary in phase, with higher correlation between neighboring WDs. High temporal correlations (>0.8) exist between WD and the combined algorithms (3B42, 3B43 and TCA for both V5 and V6) while satellite instrument algorithms (PR, TMI and TCI) are correlated best among themselves at the monthly scale. Paired t-tests of the monthly time series show that V5 3B42 and TMI are statistically different from the WD rain rates while no significant difference exists between WD and the other products. The agreements between the TRMM satellite and WD gauge estimates are best for the spring and fall and worst for winter and summer. The reduction in V6 TMI (?7.4%) and TPR (?31%) rain rates (compared to V5) results in better agreement between WD estimates and TMI in winter and TPR during summer.     

Probabilistic Assessment of Earthquake Recurrence in Northeast India and Adjoining Regions

Northeast India and adjoining regions (20°–32° N and 87°–100° E) are highly vulnerable to earthquake hazard in the Indian sub-continent, which fall under seismic zones V, IV and III in the seismic zoning map of India with magnitudes M exceeding 8, 7 and 6, respectively. It has experienced two devastating earthquakes, namely, the Shillong Plateau earthquake of June 12, 1897 (M _w 8.1) and the Assam earthquake of August 15, 1950 (M _w 8.5) that caused huge loss of lives and property in the Indian sub-continent. In the present study, the probabilities of the occurrences of earthquakes with magnitude M ≥ 7.0 during a specified interval of time has been estimated on the basis of three probabilistic models, namely, Weibull, Gamma and Lognormal, with the help of the earthquake catalogue spanning the period 1846 to 1995. The method of maximum likelihood has been used to estimate the earthquake hazard parameters. The logarithmic probability of likelihood function (ln L) is estimated and used to compare the suitability of models and it was found that the Gamma model fits best with the actual data. The sample mean interval of occurrence of such earthquakes is estimated as 7.82 years in the northeast India region and the expected mean values for Weibull, Gamma and Lognormal distributions are estimated as 7.837, 7.820 and 8.269 years, respectively. The estimated cumulative probability for an earthquake M ≥ 7.0 reaches 0.8 after about 15–16 (2010–2011) years and 0.9 after about 18–20 (2013–2015) years from the occurrence of the last earthquake (1995) in the region. The estimated conditional probability also reaches 0.8 to 0.9 after about 13–17 (2008–2012) years in the considered region for an earthquake M ≥ 7.0 when the elapsed time is zero years. However, the conditional probability reaches 0.8 to 0.9 after about 9–13 (2018–2022) years for earthquake M ≥ 7.0 when the elapsed time is 14 years (i.e. 2009).