Prediction of water inflow to mechanized tunnels during tunnel-boring-machine advance using numerical simulation

An accurate estimate of the groundwater inflow to a tunnel is one of the most challenging but essential tasks in tunnel design and construction. Most of the numerical or analytical solutions that have been developed ignore tunnel seepage conditions, material properties and hydraulic-head changes along the tunnel route during the excavation process, leading to inaccurate prediction of inflow rates. A method is introduced that uses MODFLOW code of GMS software to predict inflow rate as the tunnel boring machine (TBM) gradually advances. In this method, the tunnel boundary condition is conceptualized and defined using Drain package, which is simulated by dividing the drilling process into a series of successive intervals based on the tunnel excavation rates. In addition, the drain elevations are specified as the respective tunnel elevations, and the conductance parameters are assigned to intervals, depending on the TBM type and the tunnel seepage condition. The Qomroud water conveyance tunnel, located in Lorestan province of Iran, is 36 km in length. Since the Qomroud tunnel involved groundwater inrush during excavating, it is considered as a good case study to evaluate the presented method. The groundwater inflow to this tunnel during the TBM advance is simulated using the proposed method and the predicted rates are compared with observed rates. The results show that the presented method can satisfactorily predict the inflow rates as the TBM advances.     

Petrography and geochemistry of the Proterozoic sandstones of Somanpalli Group from Pomburna area,Eastern Belt of Pranhita–Godavari Valley,central India: Implications for provenance,weathering and tectonic setting

In this paper, we, for the first time, report geochemistry of sandstone from Somanpalli Group from Pomburna area in the Eastern Belt of Pranhita–Godavari (PG) Valley, central India and studied to infer their provenance, intensity of paleo-weathering and depositional tectonic setting. Petrographic study of sandstones show QFL modal composition of arenite. Chemical results show high \(\hbox {SiO}_{2}\) and CIA but lower \(\hbox {Al}_{2}\hbox {O}_{3}, \hbox {TiO}_{2}\), Rb, Sr, \(\hbox {K}_{2}\hbox {O}\) indicating mixed sources. Major elements chemistry parameters such as, \(\hbox {K}_{2}\hbox {O/Al}_{2}\hbox {O}_{3}\) ratio and positive correlation of Rb with \(\hbox {K}_{2}\hbox {O}\), reflects a warm and humid climate for study area. The tectonic discrimination plots (\(\hbox {SiO}_{2}/20\)–\(\hbox {K}_{2}\hbox {O} + \hbox {Na}_{2}\hbox {O}\)–\(\hbox {TiO}_{2} + \hbox {Fe}_{2}\hbox {O}_{3} + \hbox {MgO};\,\hbox {K}_{2}\hbox {O}/\hbox {Na}_{2}\hbox {O}\) vs. \(\hbox {SiO}_{2}\); Th–Sc–Zr/20) indicate dominantly passive margin and slight active tectonic setting. Concentrations of Zr, Nb, Y, and Th are higher compared to the UCC values and the trends in Th/Cr, Th/Co, La/Sc and Cr/Zr ratios support a felsic and mafic source for these sandstones and deposition in passive margin basin. Chondrite normalized REE pattern reflects LREE depletion, negative Eu anomaly and flat HREE similar to UCC, felsic components. ICV value (0.95) also supports tectonically quiescent passive margin settings. CIA values (74) indicate high degree of chemical weathering and warm and humid paleoclimatic condition.     

The age of the Nodular Limestone Formation (Late Cretaceous), Narmada Basin,central India

The age of the marine Nodular Limestone Formation of the Bagh Group is refined at Substage level through ammonoid and inoceramid index taxa. The study is based on the fresh collections from three well-defined successive intervals (Lower Karondia, Upper Karondia and Chirakhan members) of this formation having excellent exposures in different localities of the Narmada Basin, central India. The first record of the widely distributed Turonian ammonoid genera Spathites Kummel and Decker and Collignoniceras Breistroffer from the Nodular Limestone Formation constrained its age exclusively to Turonian. The Early Turonian species Spathites (Jeanrogericeras) aff. revelieranus (Courtiller) and Mytiloides labiatus (Sclotheim) occur in the lower part, while the Middle Turonian marker Collignoniceras cf. carolinum (d’Obrbigny) and Inoceramus hobetsensis (Nagao and Matsumoto) occurs in the upper part of the Karondia Member. The record of the index species Inoceramus teshioensis (Nagao and Matsumoto) in association with Placenticeras mintoi Vredenburg from Chirakhan Member allows a definite Late Turonian age. The present contribution is an attempt to resolve the controversies in the age of the Nodular Limestone Formation and also demarcation of the three divisions (Early, Middle and Late) of the Turonian Stage in the Narmada Basin, central India.     

Reliability of reanalyses products in simulating precipitation and temperature characteristics over India

Various reanalyses have been utilized in numerous climate related researches around the globe, however, there exists considerable biasedness in these products, especially in precipitation and temperature data. The ability of these reanalysis products to simulate the precipitation and temperature patterns is observed to be satisfactory at global scale, while it differs significantly at regional scale, especially over regions of high spatio-temporal heterogeneity such as India. Therefore, it is essential to evaluate the applicability and robustness of reanalyses in climate related research. The annual and seasonal variability in spatio-temporal patterns and trends of precipitation and temperature data, with respect to the IMD gridded data over 34 yrs, are evaluated for six global reanalyses namely, NCEP/NCAR Reanalysis (NCEP R1), NCEP-DOE AMIP-2 Reanalysis (NCEP R2), Climate Forecast System Reanalysis (CFSR), ECMWF Interim Reanalysis (ERA-Interim), Modern Era Retrospective Analysis for Research and Application Land only model (MERRA-Land) and JMA 55-year Reanalysis (JRA-55). The ability of the reanalyses was tested based on several factors such as statistical and categorical indices, spells and trends, for annual and seasonal daily values. Several regional and seasonal differences were observed, particularly over high rainfall regions such as Western Ghats and northeastern India. MERRA-Land is found to give the best results for precipitation over India, which is attributed to the updated forcing data using gauge-based precipitation observations. Similarly, ERA-Interim and JRA-55 exhibit better performance for temperature than other datasets. All reanalyses failed to correctly reproduce the trends in IMD data, for both precipitation and temperature. These observations will provide a better perception on the reliability and applicability of reanalyses for climate and hydrological studies over India.     

Classify-normalize-classify

Changing atmospheric conditions often result in a data distribution shift in remote sensing images for different dates and locations making it difficult to discriminate between various classes of interest. To alleviate this data shift issue, we introduce a novel supervised classification framework, called Classify-Normalize-Classify (CNC). The proposed scheme uses a two classifier approach where the first classifier performs a rough segmentation of the class of interest (COI) in the input image. Then, the median signal of the estimated COI regions is subtracted from all image pixels values to normalize them. Finally, the second classifier is applied to the normalized image to produce the refined COI segmentation. The proposed methodology was tested to detect deforestation using bitemporal Landsat 8 OLI images over the Amazon rainforest. The CNC framework compared favorably to benchmark masks of the PRODES program and state-of-the-art classifiers run on surface reflectance images provided by USGS.     

Air pollution forecasting from sky images with shallow and deep classifiers

Air pollution is one of the most important problems in the new era. Detecting the level of air pollution from an image taken by a camera can be informative for the people who are not aware of exact air pollution level be declared daily by some organizations like municipalities. In this paper, we propose a method to predict the level of the air pollution of a location by taking an image by a camera of a smart phone then processing it. We collected an image dataset from city of Tehran. Afterward, we proposed two methods for estimation of level of air pollution. In the first method, the images are preprocessed and then Gabor transform is used to extract features from the images. At the end, two shallow classification methods are employed to model and predict the level of air pollution. In the second proposed method, a Convolutional Neural Network(CNN) is designed to receive a sky image as an input and result a level of air pollution. Some experiments have been done to evaluate the proposed method. The results show that the proposed 9 method has an acceptable accuracy in detection of the air pollution level. Our deep classifier achieved accuracy about 59.38% which is 10 about 6% higher than traditional combination of feature extraction and classification methods.     

A fine-granularity scheduling algorithm for parallel XDraw viewshed analysis

Viewshed analysis is widely used in many terrain applications such as siting problem, path planning problem, and etc. But viewshed computation is very time-consuming, in particular for applications with large-scale terrain data. Parallel computing as a mainstream technique with the tremendous potential has been introduced to enhance the computation performance of viewshed analysis. This paper presents a revised parallel viewshed computation approach based on the existing serial XDraw algorithm in a distributed parallel computing environment. A layered data-dependent model for processing data dependency in the XDraw algorithm is built to explore scheduling strategy so that a fine-granularity scheduling strategy on the process-level and thread-level parallel computing model can be accepted to improve the efficiency of the viewshed computation. And a parallel computing algorithm, XDraw-L, is designed and implemented taken into account this scheduling strategy. The experimental results demonstrate a distinct improvement of computation performance of the XDraw-L algorithm in this paper compared with the coarse-partition algorithm, like XDraw-E which is presented by Song et al. (Earth Sci Inf 10(5):511–523, 2016), and XDraw-B that is the basic algorithm of serial XDraw. Our fine-granularity scheduling algorithm can greatly improve the scheduling performance of the grid cells between the layers within a triangle region.     

Modeling the Population Effects of Hypoxia on Atlantic Croaker (<Emphasis Type="Italic">Micropogonias undulatus</Emphasis>) in the Northwestern Gulf of Mexico: Part 1—Model Description and Idealized Hypoxia

We developed a spatially explicit, individual-based model to analyze how hypoxia effects on reproduction, growth, and mortality of Atlantic croaker in the northwestern Gulf of Mexico lead to population-level responses. The model follows the hourly growth, mortality, reproduction, and movement of individuals on a 300 × 800 spatial grid of 1-km² cells for 140 years. Chlorophyll-a concentration, water temperature, and dissolved oxygen (DO) were specified daily for each grid cell and repeated for each year of the simulation. A bioenergetics model was used to represent growth, mortality was assumed stage- and age-dependent, and the movement behavior of juveniles and adults was modeled based on temperature and avoidance of low DO. Hypoxia effects were imposed using exposure effect submodels that converted time-varying exposures to low DO to reduced hourly growth, increased hourly mortality, and reduced annual fecundity. Results showed that 100 years of either mild or intermediate hypoxia produced small reductions in population abundance, while repeated severe hypoxia caused a 19% reduction in long-term population abundance. Relatively few individuals were exposed to low DO each hour, but many individuals experienced some exposure. The response was dominated by a 5% average reduction in annual fecundity of individuals. Under conditions of random sequences of mild, intermediate, and severe hypoxia years occurring in proportion to their historical frequency, the model predicted a 10% decrease in the long-term population abundance of croaker. A companion paper substitutes hourly DO values from a three-dimensional water quality model for the idealized hypoxia and results in a more realistic population reduction of about 25%.     

Formation Mechanism of Mud Bank Along the Southwest Coast of India

Mud bank formation during the southwest monsoon along the southwest coast of India remains an enigma to the researchers and coastal community in spite of several earlier studies. The present study attempts to unravel the mystery through a high-frequency, season-long time-series observation at Alappuzha, located at the southern part of the west coast of India, a region of frequent occurrence of mud bank. Using 7-month-long weekly time-series observation, we identified strong winds and high waves associated with onset of the southwest monsoon and subsequent three episodic atmospheric low-pressure events (LPEs).With the help of in situ time-series data, we show that the strong winds and high waves associated with southwest monsoon pre-conditions the near shore bottom sediment to bring it into suspension. The high amplitude waves associated with the southwest monsoon, while propagating from the deep water to shallow water region, interact with the bottom initiating bottom-sediment movement and its suspension due to wave refraction and shoaling. The sporadic occurrence of the atmospheric LPEs enhances the process of suspension of bottom sediment in the near shore region leading to the formation of fluid mud. Simulations with a cohesive sediment transport model yielded realistic estimates of sediment transport, in the presence of an onshore current, a pre-requisite for transporting the fluid mud toward the coast. The prevailing onshore upwelling current during the southwest monsoon provides the favorable pre-requisite conditions for transporting the fluid mud through depression channel network towards the coast. Once sufficient quantity and thickness of fluid mud is accumulated in the near shore region, it acts as a wave damper for subsequent high monsoon waves, as indicated by the time-series wave data, leading to the formation of tranquil mud bank region. Depression channel networks extending from the shelf to the coast off Alappuzha, Kochi, Ponnani, Beypore, and Ullal were found in the bathymetric charts, thus explaining why mud banks occur only at few locations in spite of the prevalence of similar monsoon conditions.     

Increase in Dissolved Silica of Rivers Due to a Volcanic Eruption in an Estuarine Bay (Sorsogon Bay,Philippines)

Mount Bulusan, the Philippines’ fourth most active volcano, erupted in February 21, 2011, sending volcanic ash and pyroclastic materials to its surrounding rivers. The waters drained into the estuary of harmful algal blooms plagued Sorsogon Bay. We aim to determine the impact of the 2011 volcanic eruption and the preceding volcanic ash emissions to the dissolved silica concentration of rivers draining the flanks of Mt. Bulusan and its possible implications to the phytoplankton assemblage of the bay. Six river water sampling periods from August 2010 to October 2012 overlapped with Mt. Bulusan’s active phase of volcanism. Our data shows that mean river silica from pre-eruption levels of ~?500 μM increased by more than 200% during and post-eruption. Highest Si concentration of 2270 μM was measured from Cadacan River in August 2011. Here, we argue that the sustained general increase of dissolved silica is due to the silica-containing materials from Mt. Bulusan’s eruption and that their concentration in river waters is also a function of watershed lithology and precipitation. Increase in dissolved silica and other nutrients caused a shift to diatom domination and, possibly, termination of Pyrodinium bahamense var. compressum blooms. Silica load increase in embayments is a natural process that controls the dominance of algae. Our study also highlights the importance of Philippine rivers to the global ocean silica budget as a function of high precipitation, tectonics in general, and volcanism in particular.