Climate, groundwater extraction, and surface water flows have complex nonlinear relationships with groundwater level in agricultural regions. To better understand the relative importance of each ...driver and predict groundwater level change, we develop a new ensemble modeling framework based on spectral analysis, machine learning, and uncertainty analysis, as an alternative to complex and computationally expensive physical models. We apply and evaluate this new approach in the context of two aquifer systems supporting agricultural production in the United States: the High Plains aquifer (HPA) and the Mississippi River Valley alluvial aquifer (MRVA). We select input data sets by using a combination of mutual information, genetic algorithms, and lag analysis, and then use the selected data sets in a Multilayer Perceptron network architecture to simulate seasonal groundwater level change. As expected, model results suggest that irrigation demand has the highest influence on groundwater level change for a majority of the wells. The subset of groundwater observations not used in model training or cross‐validation correlates strongly (R > 0.8) with model results for 88 and 83% of the wells in the HPA and MRVA, respectively. In both aquifer systems, the error in the modeled cumulative groundwater level change during testing (2003–2012) was less than 2 m over a majority of the area. We conclude that our modeling framework can serve as an alternative approach to simulating groundwater level change and water availability, especially in regions where subsurface properties are unknown.
Key Points
Groundwater level change can be modeled with high accuracy using machine learning methods
Model framework does not require subsurface parameters and simulates comparable groundwater levels to numerical models of physical flow
Seasonal irrigation demand has the highest relevance to groundwater level change compared to climate and streamflow inputs for most wells
Soil organic carbon plays an important role in the stability and fertility of soil and is influenced by different management practice. We quantified active and passive carbon pools from total soil ...organic carbon (TOC) in seven different land use systems of northeast India. TOC was highest (2.75%) in natural forest and lowest in grassland (1.31%) and it decreased with increasing depth in different pools of lability. Very Labile Carbon (VLC) fraction ranged from 36.11 to 42.74% of TOC across different land use system. Active carbon (AC) pool was highest in Wet Rice Cultivation (61.64%) and lowest (58.71%) in natural forest. Higher AC pools (VLC and less labile) in most land use systems barring natural forests suggest that the land use systems in the region are vulnerable to land use change and must adopt suitable management practice to harness carbon sequestration.
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•A twostep relatively green method adopted to synthesize nanocomposite materials.•RGO/MnFe2O4/Polyaniline nanocomposite synthesized using the method.•Analytical method of detection ...with detection limit 0.015 μM developed.•Mechanism of interaction between the nano composite and nitrite explained.•Method has been applied in real sample analysis.
In the present investigation fibrous nanocomposite of reduced graphene oxide, manganese ferrite and polyaniline (RGO/MnFe2O4/Polyaniline) has been synthesized through a facile two-step greener approach by a solvent less thermolysis synthesis procedure. Long-chain amine is used as the solvent, reducing agent and surface functionalizing agent. Morphology and chemical functionalities of the nanocomposites are characterized using microscopic and spectroscopic measurements. Modified electrode is fabricated using the nanocomposite material and the electrochemical property of nitrite has been investigated using cyclic voltammetry measurements, an analytical method of detection of nitrite is developed using the modified electrode based on differential pulse voltammetry. Under optimum conditions, RGO/MnFe2O4/PANI fibrous nanocomposite based modified electrode have shown the linear dynamic range from 0.05 to 12000 μM with a detection limit of 0.015 μM for the detection of nitrite. The nanocomposite modified electrode showed good anti-interference ability against various common metal ions and some organic interfering agents. The nanocomposite modified electrodeis applied to determine the nitrite level in tap water. The indicative performance of the RGO/MnFe2O4/PANI fibrous nanocomposite modified electrode widens the scope of applications of RGO/MnFe2O4/PANI fibrous nanocomposite materials for on-site monitoring of nitrite.
An in situ modified Hummers method (without the use of any surfactants) has been used for the deposition of bismuth (Bi) nanoparticles onto the surface of reduced graphene oxide (RGO) sheets. The ...as-synthesized nanocomposites were characterized by X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, Raman spectroscopy, transmission electron microscopy (TEM), thermogravimetry (TG) and differential scanning calorimetry (DSC). The morphology of the RGO/Bi nanocomposites provides a better choice as an electrode material for detection of heavy metal ions due to its better functional properties over the Bi film electrode. Trace analysis of heavy metal ions like Cd+2, Pb+2, Cu+2 and Zn+2 in water is carried out by stripping voltammetric analysis using RGO/Bi nanocomposite as an electrode material. The sensitivity and detection limit of the electrode were quantitatively estimated from the analysis. The three sigma detection limits at different deposition potential for Cd2+, Pb2+, Zn2+ and Cu2+ were obtained as 2.8, 0.55, 17 and 26μgL−1, respectively. Copper detection using Bi-film electrode was a major challenge, which has been resolved using the RGO/Bi nanocomposite electrode.
► RGO/Bi nanocomposite synthesized by modified Hummers method without surfactant. ► Reduction of GO and formation of Bi nanoparticles are accomplished simultaneously. ► Trace analysis of heavy ions with composite as electrode by stripping voltammetry. ► Detection limit for Cd2+, Pb2+, Zn2+, Cu2+ were 2.8, 0.55, 17 and 26μgL−1. ► Copper detection using Bi-film electrode resolved using these composites.
Corrosion inhibition effect of
Justicia gendarussa extract (JGPE) on mild steel in 1
M HCl medium has been investigated by weight loss and electrochemical techniques. Inhibition efficiency of 93% was ...achieved with 150
ppm JGPE at 25
°C. The polarization studies showed that JGPE acts as mixed-type inhibitor. The Nyquist plots showed that on increasing JGPE concentration, increases charge transfer resistance and decreases double layer capacitance. JGPE obeys the Langmuir adsorption isotherm. AFM and ESCA confirmed the adsorption of JGPE on mild steel surface. Finally, JGPE inhibition efficiency was discussed in terms of adsorption and protective film formation.
ABSTRACT
The results of the evolutionary modelling of subdwarf B stars are presented. For the first time, we explore the core and near-core mixing in subdwarf B stars using new algorithms available ...in the mesa code: the predictive mixing scheme and the convective pre-mixing scheme. We show how both methods handle problems related to the determination of the convective boundary and the discrepancy between the core masses obtained from asteroseismology and evolutionary models, and long-standing problems related to the core-helium-burning phase, such as the splitting of the convective core and the occurrence of breathing pulses. We find that the convective pre-mixing scheme is the preferable algorithm. The masses of the convective core in the case of the predictive mixing and the combined convective and semiconvective regions in the case of the convective pre-mixing scheme are higher than in the models with only the Ledoux criterion, but they are still lower than the seismic-derived values. Both algorithms are promising and alternative methods of studying models of subdwarf B stars.
Semantic Sensor Web Sheth, A.; Henson, C.; Sahoo, S.S.
IEEE internet computing,
07/2008, Letnik:
12, Številka:
4
Journal Article
Recenzirano
Sensors are distributed across the globe leading to an avalanche of data about our environment. It is possible today to utilize networks of sensors to detect and identify a multitude of observations, ...from simple phenomena to complex events and situations. The lack of integration and communication between these networks, however, often isolates important data streams and intensifies the existing problem of too much data and not enough knowledge. With a view to addressing this problem, the semantic sensor Web (SSW) proposes that sensor data be annotated with semantic metadata that will both increase interoperability and provide contextual information essential for situational knowledge.
In the present paper, we construct the analytical exact solutions of some nonlinear evolution equations in mathematical physics, namely the time fractional KdV–Zakharov–Kuznetsov (KdV–ZK) and ...space–time fractional modified KdV–Zakharov–Kuznetsov (mKdV–ZK) equations by using improved fractional sub equation method. As a result, new types of exact analytical solutions are obtained. The obtained results are shown graphically. Here the fractional derivative is described in the Jumarie’s modified Riemann–Liouville sense.
In this paper, a new variety of solitary wave patterns to the time-fractional seventh-order Kaup–Kupershmidt equation is studied. This model is important because of its nonlinear effects on the ...propagation of different water waves. For this study, we have considered the beta-fractional derivative form of the model. To derive the required exact solutions, we have used two analytical methods, specifically the new Kudryashov (nK) and modified Khater (mK) methods. Different types of wave patterns are produced from the solutions for distinct fractional and unidentified parameter values. These solutions include bright, two-soliton propagation, combined bright-dark, w-shaped pattern, combined dark-bright, m-shape wave, l-shaped bright wave, w-shaped periodic, u-shaped wave-form, and grey-type w-shaped periodic wave solutions. These dynamics of different wave natures are analyzed thoroughly by the graphical depiction of the solutions. Additionally, the characteristics of water waves and their many application areas can benefit greatly from these solutions such as surface waves in deep water, the dynamics of liquid-vapour interfaces, and many more. These solutions help us to understand how nonlinearity can affect the system during wave propagation. The novel aspect of this work is that the investigated model of the beta fractional form has never been solved before.