Image analysis of seafloor photographs for estimation of deep-sea minerals

Factors such as non-uniform illumination of seafloor photographs and partial burial of polymetallic nodules and crusts under sediments have prevented the development of a fully automatic system for evaluating the distribution characteristics of these minerals, necessitating the involvement of a user input. A method has been developed whereby spectral signatures of different features are identified using a software ‘trained’ by a user, and the images are digitized for coverage estimation of nodules and crusts. Analysis of >20,000 seafloor photographs was carried out along five camera transects covering a total distance of 450 km at 5,100–5,300 m water depth in the Central Indian Ocean. The good positive correlation (R² > 0.98) recorded between visual and computed estimates shows that both methods of estimation are highly reliable. The digitally computed estimates were ∼10% higher than the visual estimates of the same photographs; the latter have a conservative operator error, implying that computed estimates would more accurately predict a relatively high resource potential. The fact that nodules were present in grab samples from some locations where photographs had nil nodule coverage emphasises that nodules may not always be exposed on the seafloor and that buried nodules will also have to be accounted for during resource evaluation. When coupled with accurate positioning/depth data and grab sampling, photographic estimates can provide detailed information on the spatial distribution of mineral deposits, the associated substrates, and the topographic features that control their occurrences. Such information is critical for resource modelling, the selection of mine sites, the designing of mining systems and the planning of mining operations.     

Characterizing wetland dynamics: a post-classification change detection analysis of the East Kolkata Wetlands using open source satellite data

The East Kolkata Wetlands is a unique resource recovery system. The Ramsar Convention recognized it as a ‘Wetland of International Importance’ in August 2002. However, the long-term resource exploitation and land use changes in the dynamic ecosystem have resulted in non-linear environmental responses. This is an attempt using open source remote sensing datasets to capture the spatio-temporal transformation of the wetland resulting from various anthropogenic activities. Landsat MSS and TM imageries of 1973, 1980, 1989, 2001 and 2010 were classified using Maximum Likelihood Classifier to monitor the wetland change; however, to study wetland dynamics, the post-classification wetland change detection maps have been generated for two temporal phases, i.e. 1973–1989 and 1989–2010. This study finds that the area under wetlands has reduced comprehensively in the past 40 years due to the conversion of wetlands into various other uses such as urban expansion of the Kolkata metropolitan city.     

A cascade approach to continuous rainfall data generation at point locations

High-resolution temporal rainfall data sequences serve as inputs for a range of applications in planning, design and management of small (especially urban) water resources systems, including continuous flow simulation and evaluation of alternate policies for environmental impact assessment. However, such data are often not available, since their measurements are costly and time-consuming. One alternative to obtain high-resolution data is to try to derive them from available low-resolution information through a disaggregation procedure. This study evaluates a random cascade approach for generation of high-resolution rainfall data at a point location. The approach is based on the concept of scaling in rainfall, or, relating the properties associated with the rainfall process at one temporal scale to a finer-resolution scale. The procedure involves two steps: (1) identification of the presence of scaling behavior in the rainfall process; and (2) generation of synthetic data possessing same/similar scaling properties of the observed rainfall data. The scaling identification is made using a statistical moment scaling function, and the log–Poisson distribution is assumed to generate the synthetic rainfall data. The effectiveness of the approach is tested on the rainfall data observed at the Sydney Observatory Hill, Sydney, Australia. Rainfall data corresponding to four different successively doubled resolutions (daily, 12, 6, and 3 h) are studied, and disaggregation of data is attempted only between these successively doubled resolutions. The results indicate the presence of multi-scaling behavior in the rainfall data. The synthetic data generated using the log–Poisson distribution are found to exhibit scaling behaviors that match very well with that for the observed data. However, the results also indicate that fitting the scaling function alone does not necessarily mean reproducing the broader attributes that characterize the data. This observation clearly points out the extreme caution needed in the application of the existing methods for identification of scaling in rainfall, especially since such methods are also prevalent in studies of the emerging satellite observations and thus in the broader spectrum of hydrologic modeling.     

Dissociation constants of protonated cysteine species in seawater media

The dissociation constants (pK₁, pK₂ and pK₃) for cysteine have been measured in seawater as a function of temperature (5 to 45 °C) and salinity (S = 5 to 35). The seawater values were lower than the values in NaCl at the same ionic strength. In an attempt to understand these differences, we have made measurements of the constants in Na–Mg–Cl solutions at 25 °C. The measured values have been compared to those calculated from the Pitzer ionic interaction model. The lower values of pK₃ in the Na–Mg–Cl solutions have been attributed to the formation of Mg²⁺ complexes with Cys²⁻ anions

Mg²⁺ + Cys²⁻ = MgCys

The stability constants have been fitted to

after corrections are made for the interaction of Mg²⁺ with H⁺.The pK₁ seawater measurements indicate that H₃Cys⁺ interacts with SO₄²⁻. The Pitzer parameters β⁰(H₃CysSO₄), β¹(H₃CysSO₄) and C(H₃CysSO₄) have been determined for this interaction. The formation of CaCys as well as MgCys are needed to account for the values of pK₂ and pK₃ in seawater.The consideration of the formation of MgCys and CaCys in seawater yields model calculated values of pK₁, pK₂ and pK₃ that agree with the measured values to within the experimental error of the measurements. This study shows that it is important to consider all of the ionic interactions in natural waters when examining the dissociation of organic acids.     

The gravitational instability of flow through porous medium for some systems of astrophysical interest

The gravitational instability of flow through porous medium for some hydrodynamical and hydromagnetical systems of astrophysical interest is investigated. The effects of rotation, magnetic field, viscosity and finite electrical conductivity are studied for the gravitational instability through porous medium. The effect of suspended particles on the instability is also considered. It is found that Jean's criterion remains unchanged in the presence of porosity, viscosity, finite conductivity, rotation, magnetic field and suspended particles in the medium.     

Environment and Deep-Sea Mining: A Perspective

Abstract

As the quest for deep-sea mineral resources is gaining momentum, environment and ocean mining have become important aspects of study. Because many of these deposits occur in international waters, the concern for environmental conservation in view of the effects of deep-sea mining is resulting in these effects being studied in different oceans, and efforts to develop regulations governing this exploitation are also underway at national and international levels. The impact assessment of deep-sea mining needs to encompass a variety of subjects, including environmental, socioeconomic, technological, and legal aspects. At the same time, effects of in situ environmental conditions on mining activities also need to be considered for effecient performance by the mining system. Differences in the degree of impact have been noticed during the mining simulation experiments by different investigating agencies. Therefore, interparameter comparisons, standardization of methods, and improvement in mining design are important considerations for proper utilization of resources, conservation of environment, and cost efficiency of the mining operations.     

Soil chemical changes resulting from irrigating with petrochemical effluents

Irrigating food crops with treated wastewater is a popular management option in India. This study evaluated the impacts of land application of treated petrochemical effluent on soil chemical properties. Soil samples were collected from different depths from sites irrigated with petrochemical effluent for 2?years and from control sites. The effluent collected was analysed for different physic?Cchemical properties and its impact on Lagenaria siceraria (Bottle gourd) growth. 100% concentrated effluent was used for the study and compared with the control. It was observed that application of effluent significantly increased the major cations and anions in the field. On the basis of the study, it may be suggested that treated petrochemical effluent can be used as an alternate source for irrigating crops as it increases the nutrient content of the soil. The overall application indicates a lavishing growth of L. siceraria crop in petrochemical irrigated soil than control sites. This study provides information for better understanding of changes in soil properties due to land application of petrochemical effluent. These changes must be considered in developing possible criteria for preserving delicate ecosystems.     

Suggestion for the search of H2CC in cool cosmic objects

The transition 1₁₁ ? 1₁₀ at 4.829 GHz of formaldehyde (H₂CO) was the first one showing the anomalous absorption, i.e., the absorption against the cosmic microwave background. Anomalous absorption is an unusual phenomena. Structure of H₂CC is very similar to that of H₂CO and H₂CS. Both H₂CO and H₂CS have already been identified in a number of cosmic objects. Though H₂CC is not yet identified in the cosmic objects, we propose that H₂CC may be identified in cool cosmic objects through its transition 1₁₁ ? 1₁₀ at 4.85 GHz in anomalous absorption.     

Bootstrap based artificial neural network (BANN) analysis for hierarchical prediction of monthly runoff in Upper Damodar Valley Catchment

Estimation of runoff is a prerequisite for many applications involving conservation and management of water resources. This study is undertaken in the Upper Damodar Valley Catchment (UDVC) having a drainage area of 17513.08 km² for prediction of monthly runoff. Thirty one microwatersheds and 15 sub-watersheds were selected from a total of 716 microwatersheds in the catchment area for this study. The feasibility of using different soil attributes (particle size distribution, organic matter content and apparent density), topographic attributes (primary, secondary and compound), geomorphologic attributes (basin, relief and network indices) and vegetation attribute as Normalized Difference Vegetation Index (NDVI), on prediction of monthly runoff were explored in this study. Principal Component Analysis (PCA) was applied to minimize the data redundancy of the input variables. Ten significant input variables namely; watershed length (km), elongation ratio, bifurcation ratio, area ratio, coarse sand (%), fine sand (%), elevation (m), slope (°), profile curvature (rad/m) and NDVI were selected. The selected input variables were added in hierarchy with monthly rainfall (mm) as inputs for prediction of monthly runoff (mm) using Bootstrap based artificial neural networks (BANN). The performance of the models was tested using Spearman’s correlation coefficient (r), coefficient of efficiency (COE), Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). Best performance was observed for model with monthly rainfall, slope, coarse sand, bifurcation ratio and Normalized Difference Vegetation Index (NDVI) as inputs (r = 0.925 and COE = 0.839). Increase in number of input variables did not necessarily yield better performances of the BANN models. Selection of relevant inputs and their combinations were found to be key elements in determining the performance of BANN models. Annual runoff map was generated for all the microwatersheds utilizing the weights of the best performing BANN model. This study reveals that the specific combinations of soil, topography, geomorphology and vegetation inputs can be utilized for better prediction of monthly runoff.