The WRF model performance for the simulation of heavy precipitating events over Ahmedabad during August 2006

The summer monsoon season of the year 2006 was highlighted by an unprecedented number of monsoon lows over the central and the western parts of India, particularly giving widespread rainfall over Gujarat and Rajasthan. Ahmedabad had received 540.2mm of rainfall in the month of August 2006 against the climatological mean of 219.8mm. The two spells of very heavy rainfall of 108.4mm and 97.7mm were recorded on 8 and 12 August 2006 respectively. Due to meteorological complexities involved in replicating the rainfall occurrences over a region, the Weather Research and Forecast (WRF-ARW version) modeling system with two different cumulus schemes in a nested configuration is chosen for simulating these events. The spatial distributions of large-scale circulation and moisture fields have been simulated reasonably well in this model, though there are some spatial biases in the simulated rainfall pattern. The rainfall amount over Ahmedabad has been underestimated by both the cumulus parameterization schemes. The quantitative validation of the simulated rainfall is done by calculating the categorical skill scores like frequency bias, threat scores (TS) and equitable threat scores (ETS). In this case the KF scheme has outperformed the GD scheme for the low precipitation threshold.     

Doline probability map using logistic regression and GIS technology in the central Ebro Basin (Spain)

In the surroundings of Zaragoza, karstification processes are especially intense in covered karst areas where fluvial terraces lie directly on Tertiary evaporites. Since the beginning of Quaternary, these processes have lead to the development of collapse and subsidence dolines with a wide range of sizes, which have significant economic impacts. To reduce economic impact and increase safety, a regional analysis of this phenomenon is needed for spatial management. Therefore, a probability map of dolines was developed using logistic regression and geographic information system (GIS) techniques. This paper covers the selection of input data, manipulation of data using the GIS technology, and the use of logistic regression to generate a doline probability map. The primary variable in the doline development in this area is geomorphology, represented by the location of endorheic areas and different terrace levels. Secondary variables are the presence of irrigation and the water table gradient.     

Suitability analysis for sand and gravel extraction site location in the context of a sustainable development in the surroundings of Zaragoza (Spain)

Zaragoza city is located in the central Ebro Basin, in the Iberian Peninsula. The fluvial terraces formed by the Ebro River present a valuable resource of sand and gravel deposits. However, taking advantage of these available resources implies conflicts with other land use interests like urban and industrial development as well as agricultural use, which has also traditionally occupied the alluvial terraces. These deposits represent a substantial groundwater resource that should be preserved for future generations. The development of spatial decision support systems (SDSS) has greatly assisted efforts for solving land-use conflicts. These systems combine the benefits of geographic information systems (GIS) and decision support methodologies and are therefore suitable to manage sustainable development of urban areas. In this contribution, an extraction suitability map taking into consideration a variety of environmental criteria is created with the help of a SDSS. The method used is the analytical hierarchy process which is integrated in ArcGIS. Areas most suitable to sand and gravel extraction are located in the high terraces, and in those terraces covered by pediments where the thickness of resource is relatively high. These areas are far from valuable natural areas, outside areas most vulnerable to groundwater contamination, and beneath soils with poor irrigation characteristics.     

Application of precise 142Nd/144Nd analysis of small samples to inclusions in diamonds (Finsch,South Africa) and Hadean Zircons (Jack Hills,Western Australia)

¹⁴⁶Sm–¹⁴²Nd and ¹⁴⁷Sm–¹⁴³Nd systematics were investigated in garnet inclusions in diamonds from Finsch (S. Africa) and Hadean zircons from Jack Hills (W. Australia) to assess the potential of these systems as recorders of early Earth evolution. The study of Finsch inclusions was conducted on a composite sample of 50 peridotitic pyropes with a Nd model age of 3.3 Ga. Analysis of the Jack Hills zircons was performed on 790 grains with ion microprobe ²⁰⁷Pb/²⁰⁶Pb spot ages from 3.95 to 4.19 Ga. Finsch pyropes yield 100 × ?¹⁴²Nd = ? 6 ± 12 ppm, ?¹⁴³Nd = ? 32.5, and ¹⁴⁷Sm/¹⁴⁴Nd = 0.1150. These results do not confirm previous claims for a 30 ppm ¹⁴²Nd excess in South African cratonic mantle. The lack of a ¹⁴²Nd anomaly in these inclusions suggests that isotopic heterogeneities created by early mantle differentiation were remixed at a very fine scale prior to isolation of the South African lithosphere. Alternatively, this result may indicate that only a fraction of the mantle experienced depletion during the first 400 Myr of its history. Analysis of the Jack Hills zircon composite yielded 100 × ?¹⁴²Nd = 8 ± 10 ppm, ?¹⁴³Nd = 45 ± 1, and ¹⁴⁷Sm/¹⁴⁴Nd = 0.5891. Back-calculation of this present-day ?¹⁴³Nd yields an unrealistic estimate for the initial ?¹⁴³Nd of ? 160 ?-units, clearly indicating post-crystallization disturbance of the ¹⁴⁷Sm–¹⁴³Nd system. Examination of ^146,147Sm–^142,143Nd data reveals that the Nd budget of the Jack Hills sample is dominated by non-radiogenic Nd, possibly contained in recrystallized zircon rims or secondary subsurface minerals. This secondary material is characterized by highly discordant U–Pb ages. Although the mass fraction of altered zircon is unlikely to exceed 5–10% of total sample, its high LREE content precludes a reliable evaluation of ¹⁴⁶Sm–¹⁴²Nd systematics in Jack Hills zircons.     

Evidence for crustal degassing of CF4 and SF6 in Mojave Desert groundwaters

Dissolved tetrafluoromethane (CF₄) and sulfur hexafluoride (SF₆) concentrations were measured in groundwater samples from the Eastern Morongo Basin (EMB) and Mojave River Basin (MRB) located in the southern Mojave Desert, California. Both CF₄ and SF₆ are supersaturated with respect to equilibrium with the preindustrial atmosphere at the recharge temperatures and elevations of the Mojave Desert. These observations provide the first in situ evidence for a flux of CF₄ from the lithosphere. A gradual basin-wide enhancement in dissolved CF₄ and SF₆ concentrations with groundwater age is consistent with release of these gases during weathering of the surrounding granitic alluvium. Dissolved CF₄ and SF₆ concentrations in these groundwaters also contain a deeper crustal component associated with a lithospheric flux entering the EMB and MRB through the underlying basement. The crustal flux of CF₄, but not of SF₆, is enhanced in the vicinity of local active fault systems due to release of crustal fluids during episodic fracture events driven by local tectonic activity. When fluxes of CF₄ and SF₆ into Mojave Desert groundwaters are extrapolated to the global scale they are consistent, within large uncertainties, with the fluxes required to sustain the preindustrial atmospheric abundances of CF₄ and SF₆.     

Geochemistry, petrology and ages of the lunar meteorites Kalahari 008 and 009: New constraints on early lunar evolution

Kalahari 008 and 009 are two lunar meteorites that were found close to each other in Botswana. Kalahari 008 is a typical lunar anorthositic breccia; Kalahari 009 a monomict breccia with basaltic composition and mineralogy. Based on minor and trace elements Kalahari 009 is classified as VLT (very-low-Ti) mare basalt with extremely low contents of incompatible elements, including the REE. The Lu-Hf data define an age of 4286 ± 95 Ma indicating that Kalahari 009 is one of the oldest known basalt samples from the Moon. It provides evidence for lunar basalt volcanism prior to 4.1 Ga (pre-Nectarian) and may represent the first sample from a cryptomare. The very radiogenic initial ¹⁷⁶Hf/¹⁷⁷Hf (εHf = +12.9 ± 4.6), the low REE, Th and Ti concentrations indicate that Kalahari 009 formed from re-melting of mantle material that had undergone strong incompatible trace element depletion early in lunar history. This unusually depleted composition points toward a hitherto unsampled basalt source region for the lunar interior that may represent a new depleted endmember source for low-Ti mare basalt volcanism. Apparently, the Moon became chemically very heterogeneous at an early stage in its history and different cumulate sources are responsible for the diverse mare basalt types.Evidence that Kalahari 008 and 009 may be paired includes the similar fayalite content of their olivine, the identical initial Hf isotope composition, the exceptionally low exposure ages of both rocks and the fact that they were found close to each other. Since cryptomaria are covered by highland ejecta, it is possible that these rocks are from the boundary area, where basalt deposits are covered by highland ejecta. The concentrations of cosmogenic radionuclides and trapped noble gases are unusually low in both rocks, although Kalahari 008 contains slightly higher concentrations. A likely reason for this difference is that Kalahari 008 is a polymict breccia containing a briefly exposed regolith, while Kalahari 009 is a monomict brecciated rock that may never have been at the surface of the Moon.Altogether, the compositions of Kalahari 008 and 009 permit new insight into early lunar evolution, as both meteorites sample lunar reservoirs hitherto unsampled by spacecraft missions. The very low Th and REE content of Kalahari 009 as well as the depletion in Sm and the lack of a KREEP-like signature in Kalahari 008 point to a possible source far from the influence of the Procellarum-KREEP Terrane, possibly the lunar farside.     

Exurbia from the bottom-up: Confronting empirical challenges to characterizing a complex system

We describe empirical results from a multi-disciplinary project that support modeling complex processes of land-use and land-cover change in exurban parts of Southeastern Michigan. Based on two different conceptual models, one describing the evolution of urban form as a consequence of residential preferences and the other describing land-cover changes in an exurban township as a consequence of residential preferences, local policies, and a diversity of development types, we describe a variety of empirical data collected to support the mechanisms that we encoded in computational agent-based models. We used multiple methods, including social surveys, remote sensing, and statistical analysis of spatial data, to collect data that could be used to validate the structure of our models, calibrate their specific parameters, and evaluate their output. The data were used to investigate this system in the context of several themes from complexity science, including have (a) macro-level patterns; (b) autonomous decision making entities (i.e., agents); (c) heterogeneity among those entities; (d) social and spatial interactions that operate across multiple scales and (e) nonlinear feedback mechanisms. The results point to the importance of collecting data on agents and their interactions when producing agent-based models, the general validity of our conceptual models, and some changes that we needed to make to these models following data analysis. The calibrated models have been and are being used to evaluate landscape dynamics and the effects of various policy interventions on urban land-cover patterns.     

Planktonic foraminifers in the southern Bering Sea: Changes in composition and productivity during the Late Pleistocene-Holocene

Taxonomic composition and distribution of planktonic foraminifers are studied in section of Core GC-11 that penetrated through Upper Quaternary sediments of the Bowers Ridge western slope, the southern Bering Sea. As is shown, structure of foraminiferal assemblage and productivity have varied substantially during the last 32000 calendar years in response to changes in surface water temperatures and water mass circulation in the northern part of the Pacific, the Bering Sea included. The productivity was maximal during deglaciation epoch, being notably lower in the Holocene and minimal at the glaciation time.     

Geochemistry and mineralogy of arsenic in (natural) anaerobic groundwaters

Here new data from field bioremediation experiments and geochemical modeling are reported to illustrate the principal geochemical behavior of As in anaerobic groundwaters. In the field bioremediation experiments, groundwater in Holocene alluvial aquifers in Bangladesh was amended with labile water-soluble organic C (molasses) and MgSO₄ to stimulate metabolism of indigenous SO₄-reducing bacteria (SRB). In the USA, the groundwater was contaminated by Zn, Cd and SO₄, and contained <10 μg/L As under oxidized conditions, and a mixture of sucrose and methanol were injected to stimulate SRB metabolism. In Bangladesh, groundwater was under moderately reducing conditions and contained ∼10 mg/L Fe and ∼100 μg/L As. In the USA experiment, groundwater rapidly became anaerobic, and dissolved Fe and As increased dramatically (As > 1000 μg/L) under geochemical conditions consistent with bacterial Fe-reducing conditions. With time, groundwater became more reducing and biogenic SO₄ reduction began, and Cd and Zn were virtually completely removed due to precipitation of sphalerite (ZnS) and other metal sulfide mineral(s). Following precipitation of chalcophile elements Zn and Cd, the concentrations of Fe and As both began to decrease in groundwater, presumably due to formation of As-bearing FeS/FeS₂. By the end of the six-month experiment, dissolved As had returned to below background levels. In the initial Bangladesh experiment, As decreased to virtually zero once biogenic SO₄ reduction commenced but increased to pre-experiment level once SO₄ reduction ended. In the ongoing experiment, both SO₄ and Fe(II) were amended to groundwater to evaluate if FeS/FeS₂ formation causes longer-lived As removal. Because As-bearing pyrite is the common product of SRB metabolism in Holocene alluvial aquifers in both the USA and Southeast Asia, it was endeavored to derive thermodynamic data for arsenian pyrite to better predict geochemical processes in naturally reducing groundwaters. Including the new data for arsenian pyrite into Geochemist’s Workbench, its stability field completely dominates in reducing Eh–pH space and “displaces” other As-sulfides (orpiment, realgar) that have been implied to be important in previous modeling exercises and reported in rare field conditions.     

Spatial Variability of Rock Depth in Bangalore Using Geostatistical, Neural Network and Support Vector Machine Models

Geospatial technology is increasing in demand for many applications in geosciences. Spatial variability of the bed/hard rock is vital for many applications in geotechnical and earthquake engineering problems such as design of deep foundations, site amplification, ground response studies, liquefaction, microzonation etc. In this paper, reduced level of rock at Bangalore, India is arrived from the 652 boreholes data in the area covering 220 km². In the context of prediction of reduced level of rock in the subsurface of Bangalore and to study the spatial variability of the rock depth, Geostatistical model based on Ordinary Kriging technique, Artificial Neural Network (ANN) and Support Vector Machine (SVM) models have been developed. In Ordinary Kriging, the knowledge of the semi-variogram of the reduced level of rock from 652 points in Bangalore is used to predict the reduced level of rock at any point in the subsurface of the Bangalore, where field measurements are not available. A new type of cross-validation analysis developed proves the robustness of the Ordinary Kriging model. ANN model based on multi layer perceptrons (MLPs) that are trained with Levenberg–Marquardt backpropagation algorithm has been adopted to train the model with 90% of the data available. The SVM is a novel type of learning machine based on statistical learning theory, uses regression technique by introducing loss function has been used to predict the reduced level of rock from a large set of data. In this study, a comparative study of three numerical models to predict reduced level of rock has been presented and discussed.