Application of the water table fluctuation method to characterize groundwater recharge in the Pampa plain,Argentina

Abstract

The water table fluctuation (WTF) method is based on accepting that rises of a water table are due to recharge water reaching the groundwater. To apply the method, an estimate of the specific yield of the zone of fluctuation of the groundwater level is required. In this paper, a method for estimation of the specific yield (S_y) is proposed; it consists of a graphical procedure which relates rises in groundwater level to the precipitation from which they originated. The method presents more reliable S_y values as the number of events measured increases. Eighteen years of daily measurements were analysed to obtain a S_y value of 0.09, which was used to apply the WTF method. The obtained recharge values show consistency with values calculated by other authors for the same region.

Editor D. Koutsoyiannis

Citation Varni, M., Comas, R., Weinzettel, P., and Dietrich, S., 2013. Application of water table fluctuation method to characterize the groundwater recharge in the Pampa plain, Argentina. Hydrological Sciences Journal, 58 (7), 1445–1455.     

Gaussianity of the cosmic microwave background: smooth goodness-of-fit tests applied to interferometric data

We adapt the smooth tests of goodness-of-fit developed by Rayner and Best to the study of the non-Gaussianity of interferometric observations of the cosmic microwave background (CMB). The interferometric measurements (visibilities) are transformed into signal-to-noise ratio eigenmodes, and then the method is applied directly in Fourier space. This transformation allows us to perform the analysis in different subsets of eigenmodes according to their signal-to-noise ratio level. The method can also deal with non-uniform or incomplete coverage of the UV plane. We explore here two possibilities: we analyse either the real and imaginary parts of the complex visibilities (Gaussianly distributed under the Gaussianity hypothesis) or their phases (uniformly distributed under the Gaussianity hypothesis). The power of the method in discriminating between Gaussian and non-Gaussian distributions is studied by using several kinds of non-Gaussian simulations. On the one hand, we introduce a certain degree of non-Gaussianity directly into the Fourier space using the Edgeworth expansion, and afterwards the desired correlation is introduced. On the other hand, we consider interferometric observations of a map with topological defects (cosmic strings). To these previous non-Gaussian simulations we add different noise levels and quantify the required signal-to-noise ratio necessary to achieve a detection of these non-Gaussian features. Finally, we have also studied the ability of the method to constrain the so-called non-linear coupling constant f _NL using χ² simulations. The whole method is illustrated here by application to simulated data from the Very Small Array interferometer.     

The discriminating power of wavelets to detect non-Gaussianity in the cosmic microwave background

We investigate the power of wavelets in detecting non-Gaussianity in the cosmic microwave background (CMB). We use a wavelet-based method on small simulated patches of the sky to discriminate between a pure inflationary model and inflationary models that also contain a contribution from cosmic strings. We show the importance of the choice of a good test statistic in order to optimize the discriminating power of the wavelet technique. In particular, we construct the Fisher discriminant function, which combines all the information available in the different wavelet scales. We also compare the performance of different decomposition schemes and wavelet bases. For our case, we find that the Mallat and a ` trous algorithms are superior to the 2D-tensor wavelets. Using this technique, the inflationary and strings models are clearly distinguished even in the presence of a superposed Gaussian component with twice the rms amplitude of the original cosmic string map.     

Shear and vorticity in inflationary Brans–Dicke cosmology with lambda-term

We find a solution for exponential inflation in Brans–Dicke cosmology endowed with a cosmological term, which includes time-varying shear and vorticity. We find that the scalar field and the scale factor increase exponentialy while shear, vorticity, energy density, cosmic pressure and the cosmological term decay exponentialy for negative beta, where beta is defined in the text.     

Air-Parcel Residence Times Within Forest Canopies

We present a theoretical model, based on a simple model of turbulent diffusion and first-order chemical kinetics, to determine air-parcel residence times and the out-of-canopy export of reactive gases emitted within forest canopies under neutral conditions. Theoretical predictions of the air-parcel residence time are compared to values derived from large-eddy simulation for a range of canopy architectures and turbulence levels under neutral stratification. Median air-parcel residence times range from a few sec in the upper canopy to approximately 30 min near the ground and the distribution of residence times is skewed towards longer times in the lower canopy. While the predicted probability density functions from the theoretical model and large-eddy simulation are in good agreement with each other, the theoretical model requires only information on canopy height and eddy diffusivities inside the canopy. The eddy-diffusivity model developed additionally requires the friction velocity at canopy top and a parametrized profile of the standard deviation of vertical velocity. The theoretical model of air-parcel residence times is extended to include first-order chemical reactions over a range of of Damköhler numbers (Da) characteristic of plant-emitted hydrocarbons. The resulting out-of-canopy export fractions range from near 1 for \(Da =10^{-3}\) to less than 0.3 at \(Da = 10\). These results highlight the necessity for dense and tall forests to include the impacts of air-parcel residence times when calculating the out-of-canopy export fraction for reactive trace gases.     

Modeling neutral-atmospheric electromagnetic delays in a “big data” world

If left unmodeled, the delay suffered by electromagnetic waves while crossing the neutral atmosphere negatively affects Global Navigation Satellite System positioning. The modeling of the delay has been carried out by means of empirical models formulated based on climatological information or using information extracted from numerical weather prediction (NWP) models. This paper explores the potential use of meteorological information of several types that will become available with the increasing number of sensors (e.g. a cell phone, or the thermometer of a nearby smart home) in cyberspace. How can we make use of these potentially huge data-sets, which may help to provide the best possible representation of the neutral atmosphere at any given time, as readily and as accurately as possible? This situation falls in the realm of Big Data. A few potential scenarios, a sequential improvement of Marini mapping function coefficients, a self-feeding NWP, and near real-time empirical model updates, are discussed in this paper. The pros and cons of each approach are discussed in comparison with what is done today. Experiments indicate that they have potential for a positive contribution.     

Delineating managed land for reporting national greenhouse gas emissions and removals to the United Nations framework convention on climate change

Land use and management activities have a substantial impact on carbon stocks and associated greenhouse gas emissions and removals. However, it is challenging to discriminate between anthropogenic and non-anthropogenic sources and sinks from land. To address this problem, the Intergovernmental Panel on Climate Change developed a managed land proxy to determine which lands are contributing anthropogenic greenhouse gas emissions and removals. Governments report all emissions and removals from managed land to the United Nations Framework Convention on Climate Change based on this proxy, and policy interventions to reduce emissions from land use are expected to focus on managed lands. Our objective was to review the use of the managed land proxy, and summarize the criteria that governments have applied to classify land as managed and unmanaged. We found that the large majority of governments are not reporting on their application of the managed land proxy. Among the governments that do provide information, most have assigned all area in specific land uses as managed, while designating all remaining lands as unmanaged. This designation as managed land is intuitive for croplands and settlements, which would not exist without management interventions, but a portion of forest land, grassland, and wetlands may not be managed in a country. Consequently, Brazil, Canada and the United States have taken the concept further and delineated managed and unmanaged forest land, grassland and wetlands, using additional criteria such as functional use of the land and accessibility of the land to anthropogenic activity. The managed land proxy is imperfect because reported emissions from any area can include non-anthropogenic sources, such as natural disturbances. However, the managed land proxy does make reporting of GHG emissions and removals from land use more tractable and comparable by excluding fluxes from areas that are not directly influenced by anthropogenic activity. Moreover, application of the managed land proxy can be improved by incorporating additional criteria that allow for further discrimination between managed and unmanaged land.     

Characterization of a landslide-triggered debris flow at a rainforest-covered mountain region in Brazil

Natural Hazards - Debris flows represent great hazard to humans due to their high destructive power. Understanding their hydrogeomorphic dynamics is fundamental in hazard assessment studies,...     

Modelling of the groundwater hydrological behaviour of the Langueyú creek basin by using N‐way multivariate methods

The groundwater hydrochemical behaviour of the Langueyú creek basin (Argentina) has been evaluated through a systematic survey, followed by application of hydrological and chemometric multivariate techniques. Ten physicochemical parameters were determined in groundwater samples collected from 26 wells during four sampling campaigns (June 2010; October 2010; February 2011 and June 2011), originating a tridimensional experimental dataset X . Univariate statistical and graphical hydrochemical tools (contour maps and Piper diagrams) applied to individual campaigns, allowed to reach some preliminary conclusions. However, a best visualization of the aquifer behaviour was achieved by applying Principal Component Analysis (MA‐PCA) and N‐way PCA procedures, Parallel Factor Analysis and Tucker3. Results were consistent with two‐term models, being Tucker3 [2 2 1] the most adequate, explaining a large amount of the dataset variance (50.7%) with a low complexity. The first Tucker3 [1 1 1] interaction (38.2% of variance) is related with (i) calcium/magnesium versus sodium/potassium ion exchange processes; (ii) an increase of ionic concentration and (iii) a decrease of nitrate pollution, all processes along the direction of the groundwater flow. The second [2 2 1] interaction (12.5% of variance), accounts for the predominant role played by conductivity, bicarbonate and magnesium in the dataset. The seasonal variations are closely related to concentration/dilution phenomena originated by the variations of the phreatic levels, although this point will require additional sampling to establish a definitive hydrochemical model. Copyright © 2013 John Wiley & Sons, Ltd.