An Easy Method for Interpretation of Gravity Anomalies Due to Vertical Finite Lines

A new method is introduced to determine the top and bottom depth of a vertical line using gravity anomalies. For this, gravity at a distance x from the origin and horizontal derivative at that point are utilized. A numerical value is obtained dividing the gravity at point x by horizontal derivative. Then a new equation is obtained dividing the theoretical gravity equation by the derivative equation. In that equation, assigning various values to the depth and length of vertical line, several new numerical values are obtained. Among these values, a curve is obtained for the one that is closest to the first value from attending the depth and length values. The intersection point of these curves obtained by repeating this procedure several times for different points x yield the real depth and length values of the line. The method is tested on two synthetics and field examples. Successful results are obtained in both applications.     

Investigation on the efficiency of a silicone antifouling coating in controlling the adhesion and germination of <Emphasis Type="Italic">Ulva prolifera</Emphasis> micro-propagules on rafts

Prevention of annual “green tides” caused by blooms of the green macroalga Ulva prolifera, which have occurred in the Yellow Sea since 2007, has received much attention. Increasing evidence indicates that micro-propagules on the rafts used for Porphyra yezoensis aquaculture along the coastline of Jiangsu Province in China, were the primary source of these green tides. In this study, we investigated the effectiveness of a silicone antifouling coating for preventing the adhesion and germination of U. prolifera micro-propagules on bamboo and nylon ropes, which have been used in rafts for P. yezoensis aquaculture. Our results demonstrated that a coating of silicone (Sylgard 184) containing 1.0 wt.% sodium benzoate (NaB) could reduce the adhesion rate to <5% and completely inhibited the growth of U. prolifera propagules on the coated surfaces. Coating bamboo and nylon ropes with NaB-incorporated silicone thus proved a potentially effective method for controlling the initial biomass accumulation of U. prolifera.     

Pyrite morphology and episodic euxinia of the Ediacaran Doushantuo Formation in South China

The Ediacaran Doushantuo Formation with well-preserved fossil record in South China provides a rare window for our understanding of biological evolution,global carbon cycle,and oceanic redox states.Prominent negativeδ~(13)C anomalies(i.e.,the Shuram excursion)in Ediacaran successions worldwide fundamentally challenge the traditional models of isotopic mass balance.Additionally,conflicting opinions of both oxic and anoxic conditions have been proposed for the deep waters during this period.Here,we present a detailed study of pyrite morphology and carbonate carbon isotope data documented from drill core samples at Songtao County,northeastern Guizhou.Framboid aggregates are the dominant pyrite form in black shale and they can transfer to euhedral crystals through continuous growth of the constituent microcrystals.A positive correlation between microcrystal sizes(d)and framboid diameters(D)is observed,while the different D/d ratios of framboids in argillaceous dolostone and black shale reflect different substrate availability.Electron microprobe analyses reveal no consistent compositional patterns between framboidal and euhedral pyrites.Framboid size distributions of the investigated drill core,in combination with previously published redox data from the intra-shelf Jiulongwan section,shelf margin Zhongling section,and lower slope Wuhe section,suggest that three episodes of marine euxinia have been established throughout the deposition of the Doushantuo Formation.The time lag between the uppermost euxinic interval and the Shuram excursion may arise from the depression of sulfate reduction maintained by other oxidants.     

Detection of ionospheric scintillation effects using LMD–DFA

The performance and measurement accuracy of global navigation satellite system (GNSS) receivers is greatly affected by ionospheric scintillations. Rapid amplitude and phase variations in the received GPS signal, known as ionospheric scintillation, affects the tracking of signals by GNSS receivers. Hence, there is a need to investigate the monitoring of various activities of the ionosphere and to develop a novel approach for mitigation of ionospheric scintillation effects. A method based on Local Mean Decomposition (LMD)–Detrended Fluctuation Analysis (DFA) has been proposed. The GNSS data recorded at Koneru Lakshmaiah (K L) University, Guntur, India were considered for analysis. The carrier to noise ratio (C/N₀) of GNSS satellite vehicles were decomposed into several product functions (PF) using LMD to extract the intrinsic features in the signal. Scintillation noise was removed by the DFA algorithm by selecting a suitable threshold. It was observed that the performance of the proposed LMD–DFA was better than that of empirical mode decomposition (EMD)–DFA.     

Support vector machines and feed-forward neural networks for spatial modeling of groundwater qualitative parameters

The present study attempts to model the spatial variability of three groundwater qualitative parameters in Guilan Province, northern Iran, using artificial neural networks (ANNs) and support vector machines (SVMs). Data collected from 140 observation wells for the years 2002–2014 were used. Five variables, X and Y coordinates of the observation well, distance of the observation well from the shoreline, areal average 6-month rainfall depth, and groundwater level at the day of water quality sampling, were considered as primary input variables. In addition, nine qualitative variables were also considered as auxiliary input variables. Electrical conductivity (EC), sodium concentration (Na⁺), and sulfate concentration (SO₄ ^2?) of the groundwater in the region were estimated using ANNs and SVMs with different input combinations. The results showed that both ANNs and SVMs work well when the only primary input variable is the well location. The ANN yielded an RMSE of 1.03 mEq/l for SO₄ ^2?, 1.05 mEq/l for Na⁺, and 203.17 μS/cm for EC, using the X and Y coordinates of the observation wells in the study area. In the case of SVM, these values were, respectively, 0.87, 0.87, and 176.68. Considering the auxiliary input variables (pH, EC, and the concentrations of Na⁺, K⁺, Ca²⁺, Mg²⁺, Cl^?, SO₄ ^2?, and HCO₃ ^?) resulted in a significant decrease in the RMSE of both ANNs (0.22, 0.30, and 33.04) and SVMs (0.26, 0.34, and 36.23). Comparing these RMSE values with those of cokriging interpolation technique (0.59, 0.98, and 177.59) indicated that ANNs and SVMs produced more accurate estimates of the three qualitative parameters. The relative importance of auxiliary input variables was also determined using Gamma test. The output uncertainty of ANNs and SVMs were determined using p-factor and d-factor. The results showed that SVMs have less uncertainty than ANNs.     

Field spectroscopy and radiative transfer modelling to assess impacts of petroleum pollution on biophysical and biochemical parameters of the Amazon rainforest

Biophysical and biochemical plant foliage parameters play a key role in assessing vegetation health. Those plant parameters determine the spectral reflectance and transmittance properties of vegetation; therefore, hyperspectral remote sensing, particularly imaging spectroscopy, can provide estimates of leaf and canopy chemical properties. Based on the relationship between spectral response and biochemical/biophysical properties of the leaves and canopies, the PROSPECT radiative transfer model simulates the interaction of light with leaves. In this study, more than 1100 leaf samples from the Amazon forest of Ecuador were collected at several study sites, some of which are affected by petroleum pollution, and across the vertical profile of the forest. For every sample, field spectroscopy at leaf level was conducted with a spectroradiometer. The goal of this study was to assess leaf optical properties of polluted and unpolluted rainforest canopies across the vertical profile and identify vegetation stress expressed in changes of biophysical and biochemical properties of vegetation. An ANOVA followed by Holme’s multiple comparisons of means and a principal component analysis showed that photosynthetic pigments, chlorophyll and carotenoids have significantly lower levels across the vertical profile of the forest, particularly in sites affected by petroleum pollution. On the other hand, foliar water content showed significantly higher levels in the polluted site. Those findings are symptoms of vegetation stress caused by reduced photosynthetic activity and consequently decreased transpiration and water-use efficiency of the plants. Cross-comparison between SPAD-502 chlorophyll content meter index and chlorophyll content showed strong positive correlation coefficients (r = 0.71 and r ² = 0.51) which suggests that using the SPAD-502 chlorophyll index itself is sensitive enough to detect vegetation stress in a multispecies tropical forest. Therefore, the SPAD-502 can be used to assess chlorophyll content of vegetation across polluted and non-polluted sites at different canopy layers. The results presented in this paper contribute to the very limited literature on field spectroscopy and radiative transfer models applied to the vertical profile of the Amazon forest.     

Impact of 3D Var GSI-ENKF hybrid data assimilation system

The hybrid two-way coupled 3DEnsVar assimilation system was tested with the NCMRWF global data assimilation forecasting system. At present, this system consists of T574L64 deterministic model and the grid-point statistical interpolation analysis scheme. In this experiment, the analysis system is modified with a two-way coupling with an 80 member Ensemble Kalman Filter of T254L64 resolution and runs are carried out in parallel to the operational system for the Indian summer monsoon season (June–September) for the year 2015 to study its impact. Both the assimilation systems are based on NCEP GFS system. It is found that hybrid assimilation marginally improved the quality of the forecasts of all variables over the deterministic 3D Var system, in terms of statistical skill scores and also in terms of circulation features. The impact of the hybrid system in prediction of extreme rainfall and cyclone track is discussed.     

Characteristics of winter mass balance of Glacier No.1 at the headwaters of the Urumqi River,Tianshan Mountains

This study analyzes the response of glacier to climate change during the past 49 years in Urumqi River source region, the Tianshan Mountains of China. The temporal and spatial variations of winter mass balance (bn-w) at different time scales were analyzed to identify their response to climate change during 1988–2006 (The observation of winter mass balance observation began in 1988) on the Glacier No.1 at the headwaters of the Urumqi River, Tianshan Mountains, China. The winter accumulation shows a significantly decreasing trend. The results show that the cumulative values on Glacier No.1 is 2,202 mm water equivalent during 1988–2006 and the mean values is 116 mm a⁻¹. Furthermore, the trend analysis of the winter mass balance indicates a rapid decrease since 1990, and the mean mass balance is only 79 mm a⁻¹ during 1997–2006. Winter mass balance correlates well negatively with the total evaporation from September to April (r = −0.68, α = 0.01), and positively with the total precipitation from September to April (r = 0.74, α = 0.01). However, winter mass balance shows a weak correlation with mean minimum air temperature during September to April (r = −0.35), and runoff on September (r = −0.13).