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Speleology in Kazakhstan

Shakalov on 04 Jul, 2018
Hello everyone!   I pleased to invite you to the official site of Central Asian Karstic-Speleological commission ("Kaspeko")   There, we regularly publish reports about our expeditions, articles and reports on speleotopics, lecture course for instructors, photos etc. ...

Speleology in Kazakhstan

Shakalov on 04 Jul, 2018
Hello everyone!   I pleased to invite you to the official site of Central Asian Karstic-Speleological commission ("Kaspeko")   There, we regularly publish reports about our expeditions, articles and reports on speleotopics, lecture course for instructors, photos etc. ...

Speleology in Kazakhstan

Shakalov on 11 Jul, 2012
Hello everyone!   I pleased to invite you to the official site of Central Asian Karstic-Speleological commission ("Kaspeko")   There, we regularly publish reports about our expeditions, articles and reports on speleotopics, lecture course for instructors, photos etc. ...

New publications on hypogene speleogenesis

Klimchouk on 26 Mar, 2012
Dear Colleagues, This is to draw your attention to several recent publications added to KarstBase, relevant to hypogenic karst/speleogenesis: Corrosion of limestone tablets in sulfidic ground-water: measurements and speleogenetic implications Galdenzi,

The deepest terrestrial animal

Klimchouk on 23 Feb, 2012
A recent publication of Spanish researchers describes the biology of Krubera Cave, including the deepest terrestrial animal ever found: Jordana, Rafael; Baquero, Enrique; Reboleira, Sofía and Sendra, Alberto. ...

Caves - landscapes without light

akop on 05 Feb, 2012
Exhibition dedicated to caves is taking place in the Vienna Natural History Museum   The exhibition at the Natural History Museum presents the surprising variety of caves and cave formations such as stalactites and various crystals. ...

Did you know?

That subsurface flow is see subsurface runoff.?

Checkout all 2699 terms in the KarstBase Glossary of Karst and Cave Terms

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KarstBase a bibliography database in karst and cave science.

Featured articles from Cave & Karst Science Journals
Chemistry and Karst, White, William B.
Engineering challenges in Karst, Stevanović, Zoran; Milanović, Petar
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Featured articles from other Geoscience Journals
Geochemical and mineralogical fingerprints to distinguish the exploited ferruginous mineralisations of Grotta della Monaca (Calabria, Italy), Dimuccio, L.A.; Rodrigues, N.; Larocca, F.; Pratas, J.; Amado, A.M.; Batista de Carvalho, L.A.
Karst environment, Culver D.C.
Mushroom Speleothems: Stromatolites That Formed in the Absence of Phototrophs, Bontognali, Tomaso R.R.; D’Angeli Ilenia M.; Tisato, Nicola; Vasconcelos, Crisogono; Bernasconi, Stefano M.; Gonzales, Esteban R. G.; De Waele, Jo
Calculating flux to predict future cave radon concentrations, Rowberry, Matt; Marti, Xavi; Frontera, Carlos; Van De Wiel, Marco; Briestensky, Milos
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Laboratoire de Génie de l'Environnement Industriel (Ecole des Mines d’Alès) et Hydrosciences Montpellier (Université Montpellier 2)
2014, p. 1-202
Caractérisation et modélisation hydrodynamique des karsts par réseaux de neurones. Application à l’hydrosystème du Lez
Abstract:
Improving knowledge of karst hydrodynamics represents a global challenge for water resources because karst aquifers provide approximately 25% of the world population in fresh water. Nevertheless, complexity, anisotropy, heterogeneity, non-linearity and possible non-stationarity of these aquifers make them underexploited objects due to the difficulty to characterize their morphology and hydrodynamics. In this context, the systemic paradigm proposes others methods by studying these hydrosystems through input-output (rainfall-runoff) relations.

The approach proposed in this thesis is to use information from field measurement and from systemic analyses to constrain neural network models. The goal is to make these models interpretable in terms of hydrodynamic processes by making model functioning to be similar to natural system in order to obtain a good representation and extract knowledge from model parameters.

This work covers the association of information available on the hydrosystem with correlation and spectral analyses to develop a temporal multiresolution decomposition of variables and to constrain neural network models. A new method for variable selection, adapted to represent long term hydrodynamics of the system, has been proposed. These constrained models show very good results and allow, through their parameters, to study the temporal contribution of inputs variables to the output.

Modeling nonlinear and non-stationary hydrosystems with neural network has been improved by a novel implementation of data assimilation. More precisely, when non-stationarity is attributed to the catchment, data assimilation is used to modify the model parameters. When the inputs are non-stationary, data assimilation can be used to modify the inputs.

The modification of inputs opens considerable scope to: i) fill gaps or homogenizing time series, ii) estimate effective rainfall.

Finally, these various analyses and modeling methods, mainly developed on the karst hydrosystem Lez, can improve the knowledge of the rainfall-runoff relationship at different time scales. These methodological tools thus offer perspectives of better management of the aquifer in terms of floods and resources. The advantage of these analyses and modeling tools is that they can be applicable to other systems.