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Enviroscan Ukrainian Institute of Speleology and Karstology


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Community news

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. ...

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 snow cover; snowpack is the accumulated height of snow covering a given area [16].?

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.
See all featured articles
Featured articles from other Geoscience Journals
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
Microbial mediation of complex subterranean mineral structures, Tirato, Nicola; Torriano, Stefano F.F;, Monteux, Sylvain; Sauro, Francesco; De Waele, Jo; Lavagna, Maria Luisa; D’Angeli, Ilenia Maria; Chailloux, Daniel; Renda, Michel; Eglinton, Timothy I.; Bontognali, Tomaso Renzo Rezio
Evidence of a plate-wide tectonic pressure pulse provided by extensometric monitoring in the Balkan Mountains (Bulgaria), Briestensky, Milos; Rowberry, Matt; Stemberk, Josef; Stefanov, Petar; Vozar, Jozef; Sebela, Stanka; Petro, Lubomir; Bella, Pavel; Gaal, Ludovit; Ormukov, Cholponbek;
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Your search for modelling (Keyword) returned 156 results for the whole karstbase:
Showing 151 to 156 of 156
Deep 3D thermal modelling for the city of Berlin (Germany), 2013,
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Sippel Judith, Fuchs Sven, Cacace Mauro, Braatz Anna, Kastner Oliver, Huenges Ernst, Scheckwenderoth Magdalena

This study predicts the subsurface temperature distribution of Germany’s capital Berlin. For this purpose, a data-based lithosphere-scale 3D structural model is developed incorporating 21 individual geological units. This model shows a horizontal grid resolution of (500 9 500) m and provides the geometric base for two different approaches of 3D thermal simulations: (1) calculations of the steadystate purely conductive thermal field and (2) simulations of coupled fluid flow and heat transport. The results point out fundamentally different structural and thermal configurations for potential geothermal target units. The top of the Triassic Middle Buntsandstein strongly varies in depth (159–2,470 m below sea level) and predicted temperatures (15–95 _C), mostly because of the complex geometry of the underlying Permian Zechstein salt. The top of the sub-salt Sedimentary Rotliegend is rather flat (2,890–3,785 m below sea level) and reveals temperatures of 85–139 _C. The predicted 70 _C-isotherm is located at depths of about 1,500–2,200 m, cutting the Middle Buntsandstein over large parts of Berlin. The 110 _C-isotherm at 2,900–3,700 m depth widely crosscuts the Sedimentary Rotliegend. Groundwater flow results in subsurface cooling the extent of which is strongly controlled by the geometry and the distribution of the Tertiary Rupelian Clay. The cooling effect is strongest where this clay-rich aquitard is thinnest or missing, thus facilitating deep-reaching forced convective flow. The differences between the purely conductive and coupled models highlight the need for investigations of the complex interrelation of flow- and thermal fields to properly predict temperatures in sedimentary systems.


Deep 3D thermal modelling for the city of Berlin (Germany), 2013,
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Sippel Judith, Fuchs Sven, Cacace Mauro, Braatz Anna, Kastner Oliver, Huenges Ernst, Scheckwenderoth Magdalena

This study predicts the subsurface temperature distribution of Germany’s capital Berlin. For this purpose, a data-based lithosphere-scale 3D structural model is developed incorporating 21 individual geological units. This model shows a horizontal grid resolution of (500 9 500) m and provides the geometric base for two different approaches of 3D thermal simulations: (1) calculations of the steady state purely conductive thermal field and (2) simulations of coupled fluid flow and heat transport. The results point out fundamentally different structural and thermal configurations for potential geothermal target units. The top of the Triassic Middle Buntsandstein strongly varies in depth (159–2,470 m below sea level) and predicted temperatures (15–95 _C), mostly because of the complex geometry of the underlying Permian Zechstein salt. The top of the sub-salt Sedimentary Rotliegend is rather flat (2,890–3,785 m below sea level) and reveals temperatures of 85–139 _C. The predicted 70 _C-isotherm is located at depths of about 1,500–2,200 m, cutting the Middle Buntsandstein over large parts of Berlin. The 110 _C-isotherm at 2,900–3,700 m depth widely crosscuts the Sedimentary Rotliegend. Groundwater flow results in subsurface cooling the extent of which is strongly controlled by the geometry and the distribution of the Tertiary Rupelian Clay. The cooling effect is strongest where this clay-rich aquitard is thinnest or missing, thus facilitating deep-reaching forced convective flow. The differences between the purely conductive and coupled models highlight the need for investigations of the complex interrelation of flow- and thermal fields to properly predict temperatures in sedimentary systems.


‘Looping caves’ versus ‘water table caves’: The role of base-level changes and recharge variations in cave development, 2014,
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Gabrovšek Franci, Häuselmann Philipp, Audra Philippe

The vertical organisation of karst conduit networks has been the focus of speleogenetic studies for more than a century. The four state model of Ford and Ewers (1978), which still is considered as the most general, relates the geometry of caves to the frequency of permeable fissures. The model suggests that the ‘water table caves’ are common in areas with high fissure frequency, which is often the case in natural settings. However, in Alpine karst systems, water table caves aremore the exception than the rule. Alpine speleogenesis is influenced by high uplift, valley incision rates and irregular recharge. To study the potential role of these processes for speleogenesis in the dimensions of length and depth, we apply a simple mathematical model based on coupling of flow, dissolution and transport.We assume a master conduit draining thewater to the spring at a base level. Incision of the valley triggers evolution of deeper flow pathways,which are initially in a proto-conduit state. Themaster conduit evolves into a canyon following the valley incision,while the deep pathways evolve towards maturity and tend to capture the water fromthe master conduits. Two outcomes are possible: a) deep pathways evolve fast enough to capture all the recharge, leaving the master conduit dry; or b) the canyon reaches the level of deep pathways before these evolve to maturity. We introduce the Loop-to-Canyon Ratio (LCR), which predicts which of the two outcomes is more likely to occur in certain settings. Our model is extended to account for transient flow conditions. In the case of an undulating master conduit, floodwater is stored in troughs after the flood retreat. This water seeps through sub-vertical fractures (‘soutirages’) connecting the master conduitwith the deep pathways. Therefore, the loops evolve also during the dry season, and the LCR is considerably increased. Although themodel is based on several approximations, it leads to some important conclusions for vertical organisation of karst conduit networks and stresses the importance of base-level changes and transient recharge conditions. It therefore gives an explanation of speleogenesis that relies much more on the dynamic nature of water flow than on the static fracture density


Deep conduit flow in karst aquifers revisited, 2014,
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Kaufmann Georg, Gabrovšek Franci, Romanov Douchko

Caves formed in soluble rocks such as limestone, anhydrite, or gypsum are efficient drainage paths for water moving through the aquifer from the surface of the host rock towards a resurgence. The formation of caves is controlled by the physical solution through dissociation of the host rock by water or by the chemical solution through reactions of the host rock with water enriched with carbon dioxide. Caves as large underground voids are simply the end member of secondary porosity and conductivity characterizing the aquifer.

Caves and their relation to a present or past base level are found both close to a past or present water table (water-table caves) and extending far below a past or present water table (bathy-phreatic caves). One explanation for this different speleogenetic evolution is the structural control: Fractures and bedding partings are preferentially enlarged around more prominent faults, thus the fracture density in the host rock controls the speleogenetic evolution. This widely accepted explanation [e.g. Ford and Ewers, 1978] can be extended by adding other controls, e.g. a hydraulic control: As temperature generally increases with depth, density and viscosity of water change, and particularly the reduction of viscosity due to the increase in temperature enhances flow. This hypothesis was proposed by Worthington [2001, 2004] as a major controlling factor for the evolution of deep-bathyphreatic caves.

We compare the efficiency of structural and hydraulic control on the evolution of a cave passage by numerical means, adding a third control, the chemical control to address the change in solubility of the circulating water with depth. Our results show that the increase in flow through deep bathy-phreatic passages due to the decrease in viscosity is by far outweighted by effects such as the decrease in fracture width with depth due to lithostatic stress and the decrease in solubility with depth. Hence, the existence of deep bathy-phreatic cave passages is more likely to be controlled by the structural effect of prominent faults.


Characterisation and modelling of conduit restricted karst aquifers – Example of the Auja spring, Jordan Valley, 2014,
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Schmidta Sebastian, Geyera Tobias, Guttmanb Joseph, Mareic Amer, Riesd Fabian, Sauter Martin

The conduit system of mature karstified carbonate aquifers is typically characterised by a high hydraulic conductivity and does not impose a major flow constriction on catchment discharge. As a result, discharge at karst springs is usually flashy and displays pronounced peaks following recharge events. In contrast, some karst springs reported in literature display a discharge maximum, attributed to reaching the finite discharge capacity of the conduit system (flow threshold). This phenomenon also often leads to a non-standard recession behaviour, a so called “convex recession”, i.e. an increase in the recession coefficient during flow recession, which in turn might be used as an indicator for conduit restricted aquifers. The main objective of the study is the characterisation and modelling of those hydrogeologically challenging aquifers. The applied approach consists of a combination of hydrometric monitoring, a spring hydrograph recession and event analysis, as well as the setup and calibration of a non-linear reservoir model. It is demonstrated for the Auja spring, the largest freshwater spring in the Lower Jordan Valley. The semi-arid environment with its short but intensive precipitation events and an extended dry season leads to sharp input signals and undisturbed recession periods. The spring displays complex recession behaviour, exhibiting exponential (coefficient α) and linear (coefficient β) recession periods. Numerous different recession coefficients α were observed: ∼0.2 to 0.8 d−1 (presumably main conduit system), 0.004 d−1 (fractured matrix), 0.0009 d−1 (plateau caused by flow threshold being exceeded), plus many intermediate values. The reasons for this observed behaviour are the outflow threshold at 0.47 m3 s−1 and a variable conduit–matrix cross-flow in the aquifer. Despite system complexity, and hence the necessity of incorporating features such as a flow threshold, conduit–matrix cross-flow, and a spatially variable soil/epikarst field capacity, the developed reservoir model is regarded as relatively simplistic. As a number of required parameters were calculated from the hydrogeological analysis of the system, it requires only six calibration parameters and performs well for the highly variable flow conditions observed. Calculated groundwater recharge in this semi-arid environment displays high interannual variability. For example, during the 45-year simulation period, only five wet winter seasons account for 33% of the total cumulative groundwater recharge.


Calculating flux to predict future cave radon concentrations, 2016,
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Rowberry Matt, Marti Xavi, Frontera Carlos, Van De Wiel Marco, Briestensky Milos

Cave radon concentration measurements reflect the outcome of a perpetual competition which pitches flux against ventilation and radioactive decay. The mass balance equations used to model changes in radon concentration through time routinely treat flux as a constant. This mathematical simplification is acceptable as a first order approximation despite the fact that it sidesteps an intrinsic geological problem: the majority of radon entering a cavity is exhaled as a result of advection along crustal discontinuities whose motions are inhomogeneous in both time and space. In this paper the dynamic nature of flux is investigated and the results are used to predict cave radon concentration for successive iterations. The first part of our numerical modelling procedure focuses on calculating cave air flow velocity while the second part isolates flux in a mass balance equation to simulate real time dependence among the variables. It is then possible to use this information to deliver an expression for computing cave radon concentration for successive iterations. The dynamic variables in the numerical model are represented by the outer temperature, the inner temperature, and the radon concentration while the static variables are represented by the radioactive decay constant and a range of parameters related to geometry of the cavity. Input data were recorded at Driny Cave in the Little Carpathians Mountains of western Slovakia. Here the cave passages have developed along splays of the NE-SW striking Smolenice Fault and a series of transverse faults striking NW-SE. Independent experimental observations of fault slip are provided by three permanently installed mechanical extensometers. Our numerical modelling has revealed four important flux anomalies between January 2010 and August 2011. Each of these flux anomalies was preceded by conspicuous fault slip anomalies. The mathematical procedure outlined in this paper will help to improve our understanding of radon migration along crustal discontinuities and its subsequent exhalation into the atmosphere. Furthermore, as it is possible to supply the model with continuous data, future research will focus on establishing a series of underground monitoring sites with the aim of generating the first real time global radon flux maps.


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