Groundwater-level prediction using multiple linear regression and artificial neural network techniques: a comparative assessment

The potential of multiple linear regression (MLR) and artificial neural network (ANN) techniques in predicting transient water levels over a groundwater basin were compared. MLR and ANN modeling was carried out at 17 sites in Japan, considering all significant inputs: rainfall, ambient temperature, river stage, 11 seasonal dummy variables, and influential lags of rainfall, ambient temperature, river stage and groundwater level. Seventeen site-specific ANN models were developed, using multi-layer feed-forward neural networks trained with Levenberg-Marquardt backpropagation algorithms. The performance of the models was evaluated using statistical and graphical indicators. Comparison of the goodness-of-fit statistics of the MLR models with those of the ANN models indicated that there is better agreement between the ANN-predicted groundwater levels and the observed groundwater levels at all the sites, compared to the MLR. This finding was supported by the graphical indicators and the residual analysis. Thus, it is concluded that the ANN technique is superior to the MLR technique in predicting spatio-temporal distribution of groundwater levels in a basin. However, considering the practical advantages of the MLR technique, it is recommended as an alternative and cost-effective groundwater modeling tool.     

Non-point source pollution in Indian agriculture: Estimation of nitrogen losses from rice crop using remote sensing and GIS

The paper presents a detailed understanding of nitrogenous fertilizer use in Indian agriculture and estimation of seasonal nitrogen loosses from rice crop in Indo-Gangetic plain region, the ‘food bowl’ of the Indian sub-continent. An integrated methodology was developed for quantification of different forms of nitrogen losses from rice crop using remote sensing derived inputs, field data of fertilizer application, collateral data of soil and rainfall and nitrogen loss coefficients derived from published nitrogen dynamics studies. The spatial patterns of nitrogen losses in autumn or ‘kharif’ and spring or ‘rabi’ season rice at 1 × 1 km grid were generated using image processing and GIS. The nitrogen losses through leaching in form of urea-N, ammonium-N (NH₄-N) and nitrate-N (NO₃-N) are dominant over ammonia volatilization loss. The study results indicate that nitrogen loss through leaching in kharif and rabi rice is of the order of 34.9% and 39.8% of the applied nitrogenous fertilizer in the Indo-Gangetic plain region. This study provides a significant insight to the role of nitrogenous fertilizer as a major non-point source pollutant from agriculture.     

Dependence of normal albedo of lunar regions on wavelength

Normal albedos of thirteen lunar regions are determined at five wavelengths between 4000 and 8000 Å. The deduced values agree with those of the previous investigators except those given by Gehrelset al. (1964) and Van Diggelen (1965). They increase monotonically with the wavelength. At the shortest wavelength, a slight enhancement is detected for most of the regions observed.     

Controlling factors of the δ 11B-pH proxy and its research direction

Significant boron isotope fractionation occurs in nature (?70 ‰ to +75 ‰) due to the high geochemical reactivity of boron and the large relative mass difference between ¹⁰B and ¹¹B. Since the 1990s, reconstruction of ancient seawater pH using the isotopic composition of boron in bio-carbonates (δ ¹¹B_carb), and then calculation of the past pCO₂ have become important issues for the international isotope geochemistry community, and are called the δ ¹¹B-pH proxy. Although many achievements have been made by this proxy, various aspects of boron systematics require rigorous evaluation. Based on the previous researches, mechanism of boron isotope fractionation, variation of boron isotope (δ ¹¹B) in nature (especially in bio-carbonates) and controlling factors of the δ ¹¹B-pH proxy, such as the dissociation constant of B(OH)₃ in seawater (pK_a), the δ ¹¹B of seawater (δ ¹¹B_SW), the boron isotopic fractionation factor between B(OH) ₄ ^? and B(OH)₃ (α _4–3), and the incorporated species of boron into bio-carbonates, are reviewed in detail and the research directions of this proxy are proposed. Generally, the controversy about pK_a, δ ¹¹B_sw, and α _4–3 is relatively less, but whether boron incorporated into bio-carbonates only in the form of B(OH) ₄ ^? remains doubtful. In the future, it is required that the physicochemical processes that control boron incorporation into carbonates be rigorously characterized and that the related chemical and isotopic fractionation be quantified. It is also necessary and important to establish a “best-fit empirically equation” between δ ¹¹B_carb and pH of seawater based on the precipitation experiments of inorganic or culture experiments of corals or foraminifera. In addition, extended application of the δ ¹¹B-pH proxy to the earlier part of the Phanerozoic relying on the Brachiopods is worthy of studying. Like other geochemical indicators, there are limiting factors of δ ¹¹B; however, it remains a very powerful tool in the reconstruction of past seawater pH at present.     

Evaluation of significant sources influencing the variation of physico-chemical parameters in Port Blair Bay,South Andaman,India by using multivariate statistics

Port Blair is the capital city of Andaman & Nicobar Islands, the union territory of India. More than 50% of the population of these islands lives around Port Blair Bay. Therefore the anthropogenic effects in the bay water were studied for monitoring purpose from seven stations. Physico-chemical parameters of seawater were analyzed in samples collected once in every 3 months for 2 years from seven sampling stations located in Port Blair Bay, South Andaman Island to evaluate the spatial and tidal variation. Cluster analysis and factor analysis were applied to the experimental data in an attempt to understand the sources of variation of physico-chemical parameters. In cluster analysis, the stations Junglighat Bay and Phoenix Bay having high anthropogenic influence formed a separate group. The factors obtained from factor analysis indicated that the parameters responsible for physico-chemical variations are mainly related to land run-off, sewage outfall and tidal flow.     

Space Weather: Physics,Effects and Predictability

The time varying conditions in the near-Earth space environment that may affect space-borne or ground-based technological systems and may endanger human health or life are referred to as space weather. Space weather effects arise from the dynamic and highly variable conditions in the geospace environment starting from explosive events on the Sun (solar flares), Coronal Mass Ejections near the Sun in the interplanetary medium, and various energetic effects in the magnetosphere–ionosphere–atmosphere system. As the utilization of space has become part of our everyday lives, and as our lives have become increasingly dependent on technological systems vulnerable to the space weather influences, the understanding and prediction of hazards posed by these active solar events have grown in importance. In this paper, we review the processes of the Sun–Earth interactions, the dynamic conditions within the magnetosphere, and the predictability of space weather effects on radio waves, satellites and ground-based technological systems today.     

Fields as a framework for integrating GIS and environmental process models. Part 1: Representing spatial continuity

Linking a GIS to a spatially distributed, physically-based environmental model offers many advantages. However, the implementation of such linkages is generally problematic. Many problems arise because the relationship between the reality being represented by the mathematical model and the data model used to organize the spatial data in the GIS has not been rigorously defined. In particular, while many environmental models are based on theories that assume continuity and incorporate physical fields as independent variables, current GISs can only represent continuous phenomena in a variety of discrete data models. This paper outlines a strategy in which field variables are used to enable modellers to work directly with the spatial data as spatially continuous phenomena. This allows the manner in which the spatial data has been discretized and the ways in which it can be manipulated to be treated independently from the conceptual modelling of physical processes. Modellers can express their spatial data needs as representations of reality, rather than as elements of a GIS database, and a GIS-independent language for model development may result. By providing a formal linkage between the various models of spatial phenomena, a mechanism is created for the explicit expression of transformation rules between the different spatial data models stored and manipulated by a GIS.     

Studying the Deep Structure of Elbrus Volcano by Microseismic Sounding

This paper presents results from a study of the deep structure of the Elbrus edifice and adjacent areas using geophysical techniques. We confirmed the existence of a shallow magma chamber, derived a more accurate location of the chamber in the host rocks and its characteristic dimensions, and compared new results with known studies. More accurate estimates have been obtained for the temperature at the top of the magma chamber and new evidence is adduced concerning the deep structure of the fluid magmatic systems in the Elbrus volcanic area.     

Occurrence and Distribution of Organic Contaminants in the Aquatic System in Berlin.Part II: Substituted Phenols in Berlin Surface Water

In a surface water screening, 30 representative surface water samples collected from rivers, canals, and lakes in Berlin were investigated for the presence of 22 substituted phenols. The phenols selected include the 11 phenols considered as “priority pollutants” by the US Environmental Protection Agency (US-EPA). Surface water samples were extracted applying solid-phase extraction with styrenedivinylbenzene adsorbent. The recoveries, determined in spiking experiments, were between 80 % and 103 %. After derivatization with N-(tert-butyldimethylsilyl)-N-methyl-trifluoroacetamide (MTBSTFA) the samples were analyzed by capillary gas chromatography-mass spectrometry (GC-MS). Phenol, cresols, 2-ethylphenol, 2-chlorophenol, 4-chloro-3-methylphenol, pentachlorophenol, 2-nitrophenol, and 4-nitrophenol were detected in the surface water samples at concentrations between 0.02 μg/L and 7.8 μg/L, respectively. The distribution of these residues in the Berlin surface waters showed that the phenolic residues, with the exception of pentachlorophenol and 2-ethylphenol, do not originate primarily from municipal sewage treatment plants discharges. Some of the phenols are formed naturally or occur as ubiquitous anthropogenic contaminants in the aquatic system.