Upper layer circulation,hydrography, and biological response of the Andaman waters during winter monsoon based on in situ and satellite observations

Upper layer circulation, hydrography, and biological response of Andaman waters during winter monsoon are assessed based on the observations carried out onboard FORV Sagar Sampada during January 2009 and November–December 2011. Cool and dry air carried by the moderate winds (6 m/s) from north and northeast indicates the influence of northeast monsoon (NEM) in the area during the observation time. The characteristics of physical parameters and the water mass indicate that the southeastern side is dominated by the less saline water from South China Sea intruded through the Malacca Strait, whereas the northeast is influenced by the freshwater from Ayeyarwady-Salween river system. The western side of the Andaman and Nicobar Islands exhibits similar properties of Bay of Bengal (BoB) water as evidenced in the T-S relation. Circulation pattern is uniform for the upper 88 m and is found to be more geostrophic rather than wind driven. Magnitude of the current velocity varies between 100 and 900 mm/s in November–December 2011 with strong current (900 mm/s) near Katchal and Nancowry islands and 100 and 1000 mm/s in January 2009 recording strong current (1000 mm/s) near the Little Nicobar Island. The Andaman waters are observed as less productive during the season based on the satellite-derived surface chl-a (0.1–0.4 mg/m³) and column-integrated primary productivity (PP) (100–275 mgC/m²/d).     

Leaky Aquifer Models to Simulate the Well Flow in Fractured Aquifers with Linear Interporosity Flow

Following Hemker and Maas (1987) the models of two or three leaky aquifers are applied to simulate the flow to vertical wells operating in the fractured or dual porosity aquifers. The software WellTest (WT) (Székely 2015) is used for calculating the drawdown and discharge rate variation. The comparative analysis with the independent analytical solutions by Boulton and Streltsova-Adams (1978), Warren and Root (1963), Kazemi et al. (1969) concluded with acceptable agreement between the WT simulation and the alternate calculation methods. The selected field tests have been conducted in fractured limestone aquifers. The pumping test west of Copenhagen shows an example of fractured aquifer with considerable negative skin effect at the well face. The flowing well Wafra W1 in Kuwait operates in the two-zone aquifer exhibiting sufficient vertical recharge via leakage beyond a circular domain of estimated radius of 2460 m.     

A New Approach for Border Detection of the Dumluca (Turkey) Iron Ore Area: Wavelet Cellular Neural Networks

Anomaly analysis is used for various geophysics applications such as determination of geophysical structure's location and border detections. Besides the classical geophysical techniques, artificial intelligence based image processing algorithms have been found attractive for geophysical anomaly analysis. Recently, cellular neural networks (CNN) have been applied to geophysical data and satisfactory results are reported. CNN provides fast and parallel computational capability for geophysical image processing applications due to its filtering structure. The behavior of CNN is defined by two template matrices that are adjusted by a properly supervised learning algorithm. After training stage for geophysical data, Bouguer anomaly maps can be processed and analyzed sequentially. In this paper, CNN learning and processing capability have been improved, combining Wavelet functions and backpropagation learning algorithms. The new architecture is denoted as Wavelet-Cellular Neural networks (Wave-CNN) and it is employed to analyze Bouguer anomaly maps which are important to extract useful information in geophysics. At first, Wave-CNN performance is tested on synthetic geophysical data, which are created by a computer environment. Then, Bouguer anomaly maps of the Dumluca iron ore field have been analyzed and results are reported in comparison to real drilling results.     

Results of surface ozone monitoring in the atmosphere over Ulan-Ude

Presented are the results of surface ozone monitoring in the atmosphere over Ulan-Ude during the period from 2000 to 2012. Revealed are seasonal and diurnal variations of surface ozone. The analysis of the seasonal variability of surface ozone concentration indicates the presence of the clearly pronounced maximum in spring-summer period. A statistical model of forecasting single concentrations of the surface ozone is considered using the multiple regression analysis. Temperature, relative humidity, wind direction, wind speed, turbulence factor, temperature gradient, velocity of vertical flow, and concentrations of minor gas admixtures such as nitrogen oxides are used as predictors. Analyzed are statistical relationships, where observed ozone values are presented in the form of the regression function of the most significant predictors.     

Erratum to: Climate change projections over India by a downscaling approach using PRECIS

The author “Bhaski Bhaskaran” and his affiliation “Fujitsu Laboratory of Europe, Middlesex, UK” should be replaced by “Balakrishnan Bhaskaran”, “Fujitsu Laboratories of Europe Limited, Hayes Park, Middlesex, UK”, respectively.The corrected name and affiliation are shown in this erratum.     

Crop Residue Discrimination Using Ground-Based Hyperspectral Data

Crop residue has become an increasingly important factor in agriculture management. It assists in the reduction of soil erosion and is an important source of soil organic carbon (soil carbon sequestration). In recent past, remote sensing, especially narrowband, data have been explored for crop residue assessment. In this context, a study was carried out to identify different narrow-bands and evaluate the performance of SWIR region based spectral indices for crop residue discrimination. Ground based hyperspectral data collected for wheat crop residue was analyzed using Stepwise Discriminant Analysis (SDA) technique to select significant bands for discrimination. Out of the seven best bands selected to discriminate between matured crop, straw heap, combine-harvested field with stubbles and soil, four bands were from SWIR (1980, 2030, 2200, 2440 nm) region. Six spectral indices were computed, namely CAI, LCA, SINDRI, NDSVI, NDI5 and hSINDRI for crop residue discrimination. LCA and CAI showed to be best (F?>?115) in discriminating above classes, while LCA and SINDRI were best (F?>?100) among all indices in discriminating crop residue under different harvesting methods. Comparison of different spectral resolution (from 1 nm to 150 nm) showed that for crop residue discrimination a resolution of 100 nm at 2100–2300 m region would be sufficient to discriminate crop residue from other co-existing classes.     

Modification of a Parametrization of Shallow Convection in the Grey Zone Using a Mesoscale Model

In current operational numerical weather prediction models, the effect of shallow convection is parametrized. The grey zone of shallow convection is found between the horizontal resolutions of mesoscale numerical models (2–3 km) and large-eddy simulations (10–100 m or finer). At these horizontal scales the shallow convection is to some extent explicitly resolved by the model. The shallow-convection parametrization is still needed, but has to be regulated according to the model horizontal resolution. Here the behaviour of the non-hydrostatic mesoscale numerical weather prediction model Application of Research to Operations at Mesoscale is examined in the grey zone and a new scale-adaptive surface closure of its shallow-convection parametrization, dependent on horizontal resolution, is defined based on large-eddy simulation. The new closure is tested on a series of numerical experiments and validated on a 15-day-long real case period. Its impact on the development of deep convection is examined in detail. The idealized simulations show promising results, as the mean profiles of the subgrid and resolved turbulence change in the desired way. Based on the real case tests our modification has a low impact on model performance, but is part of a set of upgrades of the current parametrization that is aimed to treat the shallow convection grey zone.     

Filtration and Clogging Behavior of Geotextiles with Roorkee Soils

Geotextile filters are rapidly replacing graded granular filters as the standard of practice in geotechnical design. The objective of the present study is to predict the behavior of the geotextile filter for the locally (Roorkee—India) available soils using three different geotextiles (two nonwoven and one woven). Nonwoven geotextiles are commonly used in filtration applications. This paper evaluates the long-term performance of two needle-punched nonwoven geotextiles and one woven geotextile. Filtration tests on soil–geotextile filter systems were conducted in the laboratory in order to evaluate the filtration and clogging behavior. Laboratory test program, include evaluation of performance of two different nonwoven and one woven geotextile filters in combination with locally available Solani River Sand and Clayey Soil. The paper describes the concept and details of the Fine Fraction Filtration (F³) test and presents data on three different geotextiles, which were evaluated using three different soil types. It is deduced that in all filtration applications, the non-woven geotextile would perform better than the woven geotextile.     

Extracting water-related features using reflectance data and principal component analysis of Landsat images

This study aimed to map water features using a Landsat image rather than traditional land cover. We involved the original bands, spectral indices and principal components (PCs) of a principal component analysis (PCA) as input data, and performed random forest (RF) and support vector machine (SVM) classification with water, saturated soil and non-water categories. The aim was to compare the efficiency of the results based on various input data. Original bands provided 93% overall accuracy (OA) and bands 4–5–7 were the most informative in this analysis. Except for MNDWI (modified normalized differenced water index, with 98% OA), the performance of all water indices was between 60 and 70% (OA). The PCA-based approach conducted on the original bands resulted in the most accurate identification of all classes (with only 1% error in the case of water bodies). We therefore show that both water bodies and saturated soils can be identified successfully using this approach.