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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. ...

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. ...

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That transpiration is the process by which water absorbed by plants, usually through the roots, is evaporated into the atmosphere from the plant surface [6].?

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Chemistry and Karst, White, William B.
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Your search for rainfall-runoff model (Keyword) returned 6 results for the whole karstbase:
Linear and nonlinear input/output models for karstic springflow and flood prediction at different time scales, 1999, Labat D. , Ababou R. , Mangin A. ,
Karstic formations function as three-dimensional (3D) hydrological basins, with both surface and subsurface flows through fissures, natural conduits, underground streams and reservoirs. The main characteristic of karstic formations is their significant 3D physical heterogeneity at all scales, from fine fissuration to large holes and conduits. This leads to dynamic and temporal variability, e.g, highly variable flow rates, due to several concurrent flow regimes with several distinct response times. The temporal hydrologic response of karstic basins is studied here from an input/output, systems analysis viewpoint. The hydraulic behaviour of the basins is approached via the relationship between hydrometeorological inputs and outputs. These processes are represented and modeled as random, self-correlated and cross-correlated, stationary time processes. More precisely, for each site-specific case presented here, the input process is the total rainfall on the basin and the output process is the discharge rate at the outlet of the basin (karstic spring). In the absence of other data, these time processes embody all the available information concerning a given karstic basin. In this paper, we first present a brief discussion of the physical structure of karstic systems. Then, we formulate linear and nonlinear models, i.e. functional relations between rainfall and runoff, and methods for identifying the kernel and coefficients of the functionals (deterministic vs. statistical; error minimisation vs. polynomial projection). These are based mostly on Volterra first order (linear) or second order (nonlinear) convolution. In addition, a new nonlinear threshold model is developed, based on the frequency distribution of interannual mean daily runoff. Finally, the different models and identification methods are applied to two karstic watersheds in the french Pyrenees mountains, using long sequences of rainfall and spring outflow data at two different sampling rates (daily and semi-hourly). The accuracy of nonlinear and linear rainfall-runoff models is tested at three time scales: long interannual scale (20 years of daily data), medium or seasonal scale (3 months of semi-hourly data), and short scale or 'flood scale' (2 days of semi-hourly data). The model predictions are analysed in terms of global statistical accuracy and in terms of accuracy with respect to high flow events (floods)

Rainfall-runoff relations for karstic springs. Part I: convolution and spectral analyses, 2000, Labat D. , Ababou R. , Mangin A. ,
Karstic basins contain large reserves of subsurface water. In this paper, three karstic systems located in the Pyrenees Mountains (Ariege, France) are studied. Long records of rainfall and discharge rates for these karstic springs are available, sampled at different rates: daily, hourly and half-hourly. This study aims at illustrating and assessing the capabilities and limitations of linear black-box methods for analysing rainfall-runoff type relationships and reconstructing runoffs from rainfall rate data using such systems. In this study, precipitation and discharge rates are considered as two autocorrelated and cross-correlated stochastic processes. A Linear and stationary rainfall-runoff model is adopted, which is used for identification and simulation purposes. Different versions are analysed, including a model based on a convolution integral between the precipitation rate P(tau) and a transfer function h(t - tau) which can be thought of as the unit impulse response of the system. It is shown that this linear stochastic model (i.e. the statistical version), although accurate in some respects, does not represent the hydraulic behaviour of the system very well during low flow episodes and floods. It is also shown that the use of Fourier analysis, alone, does not lead to a satisfactory reconstitution of observed runoff sequences. For these reasons, the use of non-linear random process input-output models based on Volterra integral series is proposed and discussed. (C) 2000 Elsevier Science B.V. All rights reserved

Composite transfer functions for karst aquifers, 2003, Icjukic V. , Jukic D. ,
Linear transfer functions have been extensively used in hydrological studies. Generally, we support this conclusion: rainfall-runoff models based on the convolution between rainfall rates and a nonparametric transfer function (NTF) are not successful at simulating karst spring discharges during long recession periods. The tails of identified transfer functions have irregular shapes and they are not accurate physical representation of the transport through a karst system. Irregularities are the result of unavoidable errors in input and output time series and simplifications made by considering the system as linear and time invariant. This paper deals with a new form of the transfer functions for karst aquifers, the so-called composite transfer function (CTF). The CTF simulates discharges by two transfer functions adapted for the quick flow and the slow flow hydrograph component modeling. NTF is responsible for the quick flow component. The slow flow component is modeled by a parametric transfer function that is an instantaneous unit hydrograph mathematically formulated and defined from a conceptual model. By using the CTF, the irregular shape of the tail of the identified transfer function can be avoided, and the simulation of long recession periods as well as the simulation of a complete hydrograph becomes more successful. The NTF, the Nash model, the Zoch model and other similar conceptual models can be considered separately as simplified forms of the CTF. The rainfall-runoff model based on the convolution between rainfall rates and the CTF was tested on the Jadro Spring in Croatia. The results of the application are compared with the results obtained by applying NTFs independently. (C) 2003 Elsevier Science B.V. All rights reserved

A nonlinear rainfall-runoff model using neural network technique: Example in fractured porous media, 2003, Lallahem S. , Mania J. ,
One of the more advanced approaches for simulating groundwater flow in karstic and fractured porous media is the combination of a linear and a nonlinear model. The paper presents an attempt to determine outflow influencing parameters in order to simulate aquifer outflow. Our approach in this study is to create a productive interaction system between expert, mathematical model, MERO,. and artificial neural networks (ANNs). The proposed method is especially suitable for the problem of large-scale and long-term simulation. In the present project, the first objective is to determine aquifer outflow influencing parameters by the use of MERO model, which gave a good results in a fissured and chalky media, and then introduce these parameters in neural network (NN). To determine outflow influencing parameters, we propose to test the NN under fourth different external input scenarios. The second objective is to investigate the effect of temporal information by taking current and past data sets. The good found results reveal the merit of ANNs-MERO combination and specifically multilayer perceptron (MLP) models. This methodology provided that the network with lower, lag and number hidden layer, consistently produced better performance. (C) 2003 Elsevier Science Ltd. All rights reserved

A DARCIAN MODEL FOR THE FLOW OF BIG SPRING AND THE HYDRAULIC HEAD IN THE OZARK AQUIFER, MISSOURI, USA, 2010, Criss R. E.
The complex discharge hydrograph for Big Spring, Missouri, can be described as the sum of two terms governed by Darcys Law. The dominant, long-term component is proportional to the regional hydraulic gradient, and constitutes about 80% of the average flow of 12.6 m3/s. Superimposed on this is a transient component with a time-constant of about 1.5 days that represents the Darcian response to sharp, rainfall-driven pulses on the head of the shallow groundwater system. This transient component delivers about 20% of the average total flow, but over short intervals can exceed the long-term component. However, the long-term component is so large that the ratio of record high flows to the average flow is only about 4x for Big Spring, and 1.5 to 4.5x for most other large Ozark springs; for comparison, this ratio is 10 to 3000x for most surface streams in Missouri. The strong correlation between the discharge of the large springs and the head in the Ozark aquifer permits the extension of the Darcian rainfall-runoff model to predict groundwater levels in wells.

Spring discharge records – a case study, 2013, Wicks, Carol M.

Spring discharge records integrate of all the processes and the reactions occurring within a karst basin. A brief summary of the use of discharge records as a means to constrain the internal structure of karst basins, as means to constrain rainfallrunoff models for karst basin, and as a means to determine the value of hydrodynamic parameters of karst basins is presented. Data collected from Devils Icebox, a karst basin spring in Missouri, USA, were used to assess these approaches to characterizing karst basins. For Devils Icebox, most of the discharge responses do not record information about the internal structure of the basin rather the responses record information about the recharge to the basin. A rainfall-runoff model failed to reproduce the data from which model parameters were derived and has little utility in a predictive mode. Use of conservation of mass equations as a means to derive hydrodynamic parameters is a useful approach, although critical data are lacking. More generally, karst hydrologists need quantitative tracer data and long-term, high-resolution temporal data of the input(s) to and the output(s) from karst basins.


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