Brackish karstic springs model: application to Almiros spring in Crete

A mathematical model is proposed to simulate brackish karstic springs. Rainfall data constitutes model input information while output information is the discharge and the chloride concentration of the water versus time. The model was constructed by considering the mass and mechanical energy balance on the hydrodynamic analog, which includes three reservoirs outflowing in a tube that lies adjacent to the spring. Two reservoirs emulate the karstic system, and the third one emulates the sea. The discharge of the spring is given by the sum of the discharge of the reservoirs, and the chloride concentration by the solution of the mixing problem between the fresh and the salty water, which exists in the tube leading to the spring. The model is applied to the spring of Almiros at Heraklion, Crete, Greece. The agreement between model values and field measurements is very good for depletion periods and satisfactory for recharge periods.     

Prediction of flow rate of karstic springs using support vector machines

Complex void space structure and flow patterns in karstic aquifers render behaviour prediction of karstic springs difficult. Four support vector regression-based models are proposed to predict flow rates from two adjacent karstic springs in Greece (Mai Vryssi and Pera Vryssi). Having no accurate estimates of the groundwater flow pattern, we used four kernels: linear, polynomial, Gaussian radial basis function and exponential radial basis function (ERBF). The data used for training and testing included daily and mean monthly precipitation, and spring flow rates. The support vector machine (SVM) performance depends on hyper-parameters, which were optimized using a grid search approach. Model performance was evaluated using root mean square error and correlation coefficient. Polynomial kernel performed better for Mai Vryssi and the ERBF for Pera Vryssi. All models except one performed better for Pera Vryssi. Our models performed better than generalized regression neural network, radial basis function neural network and ARIMA models.     

Estimating ground water recharge using flow models of perched karstic aquifers

The fraction of rain that is annually recharged to ground water is a function of the transient quantities of precipitation (wet vs. dry years) as well as other meteorological and geologic factors, and thus it is very difficult to estimate. In this study, we have used long records (20 to 30 years) of precipitation and spring discharge to reconstruct the transient character of yearly recharge. These data sets were used to calibrate numerical ground water flow models on the less than 3 km(2) scale for four separate perched karstic aquifers in the Judean and Samarian Mountains of Israel. The stratification and karstic character of the local carbonate rock aquifers cause ground water to flow through discrete dissolution channels and to discharge at isolated springs. An innovative, dual-porosity approach was used where a finite-difference solution simulates flow in the rock matrix, while the karstic channels are simulated using computationally simple drains. Perched conditions are also simulated innovatively using MODFLOW by treating the bottom unsaturated layer as if it is saturated, but by assuming zero pressure head throughout the "unsaturated" layer. Best fitting between measured and computed spring hydrograph data has allowed us to develop a set of empirical functions relating measured precipitation to recharge to the aquifer. The generic methodology presented gives insight into the suspected changes in aquifer recharge rates between particularly wet or dry years.     

Stable isotope‐based mean catchment altitudes of springs in the Lebanon Mountains

Stable isotopes of water are known to provide information on mean altitudes of spring recharge areas, which is an important parameter for groundwater resources management especially in karstic environments. Very often, a lack of precipitation input data limits the possibility for an appropriate estimation of mean catchment altitudes. In the Jeita spring catchment, Lebanon, a characterization of precipitation input was possible with samples collected at six stations at varying altitudes (88 amount‐weighted monthly samples). A local meteoric water line for the Jeita spring catchment was characterized as δ²H = 6.04 * δ¹⁸O + 8.45 (R ² = .92) for a 2‐year observation period between October 2012 and September 2014. Integral samples from the snow layer were collected at 22 sites at altitudes ranging from 1,000 to 2,300 m above sea level at the end of February 2012 and February 2013, when snow height reached a maximum of more than 6 m at the highest peak in the catchment. Water samples were continuously collected from six springs (Jeita, Kashkoush, Labbane, Assal, Afqa, and Rouaiss). Jeita spring water samples were collected additionally in daily time steps during the snowmelt season in 2012. Mean isotope values of the sampled springs range from ?6.8‰ to ?8.2‰, and from ?33‰ to ?44‰, for δ¹⁸O and δ²H, respectively. The stable isotope data show that input variability (space and time, snow cover, and rainfall) has direct impacts on mean altitude estimates of spring catchments. A more profound interpretation of spring response to rainfall for six local springs in the Lebanon Mountains was possible in comparison to four earlier described springs collected in the Anti‐Lebanon Mountains in Syria.     

Stream Temperature Modeling and Fiber Optic Temperature Sensing to Characterize Groundwater Discharge

The Ngongotaha Stream was used as a case study to assess the applicability of fiber optic distributed temperature sensing (FODTS) to identify the location of springs and quantify their discharge. Thirteen springs were identified, mostly located within a 115 m reach, five discharged from the right bank and eight from the left bank. To quantify groundwater discharge, a new approach was developed in which the one-dimensional transient heat transport model was fitted to the FODTS measurements, where the main calibration parameters of interest were the unknown spring discharges. The spatial disposition of the groundwater discharge estimation problem was constrained by two sources of information; first, the stream gains ∼500 L/s as determined by streamflow gauging. Second, the temperature profiles of the left and right banks provide the spatial disposition of springs and their relative discharges. FODTS was used to measure stream temperature near the left and right banks, which created two temperature datasets. A weighted average of the two datasets was then calculated, where the weights reflected the degree of mixing between the right and left banks downstream of a spring. The new approach in this study marks a departure from previous studies, in which the general approach was to use the steady-state thermal mixing model (Selker et al. 2006a; Westhoff et al. 2007; Briggs et al. 2012) to infer groundwater discharge, which is then used as an input into a transient model of the general form of equation to simulate stream temperature (Westhoff et al. 2007).     

Simulation of spring flows from a karst aquifer with an artificial neural network

In China, 9·5% of the landmass is karst terrain and of that 47,000 km² is located in semiarid regions. In these regions the karst aquifers feed many large karst springs within basins of thousands of square kilometres. Spring discharges reflect the fluctuation of ground water level and variability of ground water storage in the basins. However, karst aquifers are highly heterogeneous and monitoring data are sparse in these regions. Therefore, for sustainable utilization and conservation of karst ground water it is necessary to simulate the spring flows to acquire better understanding of karst hydrological processes. The purpose of this study is to develop a parsimonious model that accurately simulates spring discharges using an artificial neural network (ANN) model. The karst spring aquifer was treated as a non‐linear input/output system to simulate the response of karst spring flow to precipitation and applied the model to the Niangziguan Springs, located in the east of Shanxi Province, China and a representative of karst springs in a semiarid area. Moreover, the ANN model was compared with a previous time‐lag linear model and it was found that the ANN model performed better. Copyright © 2007 John Wiley & Sons, Ltd.     

Etiology of Salinity and Water Origin,the Main Dilemma of Badab Sourt,a Unique Travertine Spring

Badab Sourt travertine‐depositing springs in the north of Iran, naturally create a unique surreal landscape containing a range of stepped travertine terraces, similarly found only in a few other places on earth. This site comprises of three travertine saline springs with different values of salinity and discharge (SP₁, SP₂, and SP₃) and one non‐travertine fresh karstic spring (SP₄) within a distance of about 300 m. The etiology behind this salinity and the water origin are the main research's dilemma that were investigated using geological, hydrochemical, and stable isotopic techniques. Based on the topography and isotopic results, the carbonate formations in northern (Khoshyeilagh and Mobarak) and southern (Cretaceous limestone) parts of the springs potentially provide the initial hydraulic gradient for deep circulation of the water and CO₂. However, geological studies indicate that the hydraulic connectivity of the Cretaceous formation to the travertine springs is interrupted by impermeable geological formations. Based on the proposed conceptual hydrogeological model and mass balance calculations, the SP₄ spring is locally recharged from the nearby karstic area of Khoshyeilagh formation through shallow, short and steep groundwater flow circulation that is completely different from the travertine springs. The travertine spring (SP₁) is recharged from more distant areas having higher altitudes on Mobarak and Khoshyeilagh limestone and circulate more deeply before emerging on the surface. The SP₂ and SP₃ springs can derive from the mixing of the saline water (SP₁) and fresh water (SP₄). The dissolution of interlayers of halite in Shemshak formation is concluded as the main source of salinity. This is the first research article in detail to survey hydrogeology of the travertine springs in Iran.     

Lotic communities of two small temporary karstic stream systems (East Westphalia, Germany) along a longitudinal gradient of hydrological intermittency

The spatial and temporal discharge regime and its effects on benthic communities were studied in two small temporary karstic stream systems of the Paderborner Hochfläche (East Westphalia, Germany). Both streams are characterized by very small perennial springbrook sections. Benthic invertebrates were sampled three times at 12 sites and discharge was measured monthly from March to September 2000. The spatial extension of streamflow was observed regularly to evaluate the duration of drought. Both streams showed a longitudinal gradient of hydrological intermittency from very small perennial reaches with low intermittency to an extremely harsh hydrological situation. The benthic communities displayed a decreasing species richness at increasing intermittency. The different hydrological stream sections were colonized by different lotic communities, characterized by typical species of temporary streams and by several typical species of springs. Particularly the perennial springs and springbrooks are very important for the species richness in these karstic stream systems.     

Conceptualization of Karstic Aquifer with Multiple Outlets Using a Dual Porosity Model

In this study, two conceptual models, the classic reservoir (CR) model and exchange reservoirs model embedded by dual porosity approach (DPR) are developed for simulation of karst aquifer functioning drained by multiple outlets. The performances of two developed models are demonstrated at a less developed karstic aquifer with three spring outlets located in Zagros Mountain in the south‐west of Iran using 22‐years of daily data. During the surface recharge, a production function based on water mass balance is implemented for computing the time series of surface recharge to the karst formations. The efficiency of both models has been assessed for simulation of daily spring discharge during the recession and also surface recharge periods. Results indicate that both CR and DPR models are capable of simulating the ordinates of spring hydrographs which drainage less developed karstic aquifer. However, the goodness of fit criteria indicates outperformance of DPR model for simulation of total hydrograph ordinates. In addition, the DPR model is capable of quantifying hydraulic properties of two hydrologically connected overlapping continua conduits network and fissure matrix which lays important foundations for the mining operation and water resource management whereas homogeneous model representations of the karstic subsurface (e.g., the CR) do not work accurately in the karstic environment.     

Modelling tidal signals enhanced by a submarine spring in a coastal confined aquifer extending under the sea

Submarine springs discharge offshore groundwater from confined aquifers extending under the sea. The effects of these springs on the propagation of tidal oscillations in coastal confined aquifers are not known. This paper presents an approximate analytical solution of tidal head fluctuations in a confined aquifer with one submarine spring. The aquifer is assumed to extend in all directions infinitely. The spring is represented by a permeable round column on the seabed, which penetrates completely the impermeable layer overlying the confined aquifer. The error of the approximate solution is negligible if the distance from the spring to the coastline is much greater than the radius of the permeable column representing the spring. Through a hypothetical example, we demonstrate that it is possible to identify the spring’s location using tidal signals observed from inland wells. Tidal groundwater head fluctuations from three inland observation wells at least are needed to determine the 5 model parameters, including the location (2 parameters), the radius of the permeable column representing the spring, the diffusivity of the aquifer, and the tidal loading efficiency of the system.     

Using periodic hydrologic and geochemical sampling with limited continuous monitoring to characterize remote karst aquifers in the Kaweah River Basin,California, USA

Hydrogeologic field work in remote settings is often challenging: assessing spring behaviour and aquifer characteristics can be expensive in both time commitment and resources needed to assess these systems. In this study, we document the hydrology and geochemistry of 47 perennial karst springs in the Kaweah River, a mountain river basin in the Sierra Nevada, California. After preliminary hydrogeochemical characterization and grouping, selected springs were continuously monitored to further assess aquifer characteristics in each group. Later, in areas without previous dye‐tracing work, traces were conducted to establish connections between large sinking streams and springs. The springs have a wide range of inter‐spring and intra‐spring variability in discharge and geochemistry. We assessed this variability by performing statistical comparisons with spring chemistry and principal components analysis of all measured variables. Results show that springs can be divided into two distinct groups: high elevation springs of the Mineral King Valley and lower elevation springs throughout the rest of the basin. Continuous discharge, temperature and specific conductivity data from four springs (two from each group) were then used to characterize the hydrograph recession behaviour of springs in each group. Both groups showed statistically similar baseflow recession slopes, suggesting that both groups contain baseflow storage compartments with similar hydrogeologic properties. The biggest difference between each group is the variability in amount of water remaining in the aquifer during baseflow conditions. High elevation springs have lower baseflow discharges, relative to peak flow, than lower elevation springs, despite the fact that more precipitation falls at higher elevation. This is likely caused by differences in the amount of soil and epikarst storage, which are related to recent geomorphic events: high elevation aquifers were glaciated as recent as 41 thousand years ago (kya), while there is no evidence that low elevation aquifers were glaciated. As a result, lower elevations have developed thicker soils, weathered bedrock and epikarst. Copyright © 2016 John Wiley & Sons, Ltd.     

Linear and nonlinear input/output models for karstic springflow and flood prediction at different time scales

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 Pyrénées 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).     

Feed forward neural network and interpolation function models to predict the soil and subsurface sediments distribution in Bam,Iran

An application of the artificial neural network (ANN) approach for predicting mean grain size using electric resistivity data from Bam city is presented. A feed forward back propagation network was developed employing 45 sets of input data. The input variables in the ANN model are the electrical resistivity, water table as a Boolean value and depth; the output is the mean grain size. To demonstrate the authenticity of this approach, the network predictions are compared with those from interpolation methods and the same data. This comparison shows that the ANN approach performs better results. The predicted and observed mean grain size values were compared and show high correlation coefficients. The ANN approach maps show a high degree of correlation with well data based grain size maps and can therefore be used conservatively to better understand the influence of input parameters on sedimentological predictions.     

Modelling discharge from a coastal watershed in southeast Sweden using an integrated framework

The field hydrology model DRAINMOD integrated with Arc Hydro in geographical information system (GIS) framework (Arc Hydro–DRAINMOD) was used to simulate the hydrological response of a coastal watershed in southeast Sweden. Arc Hydro–DRAINMOD uses a distributed approach to route water from each field edge to the watershed outlet. In the framework the Arc Hydro data model was used to describe the stream network in the watershed and to connect the individual simulated DRAINMOD‐field outflow time series from each plot using Arc Hydro schema‐links features, which were summed at Arc Hydro schema‐nodes features along the stream network to generate the stream network flow. Hydrology data collected during six periods between 2003 and 2008 were used to test Arc Hydro–DRAINMOD and its performance was evaluated by considering uncertainties in model inputs using generalized likelihood uncertainty estimation (GLUE). The GLUE estimates obtained (uncertainty bands 5% and 95%) agreed satisfactorily with measured monthly discharges. The percentage of time in which the observed discharges were bracketed by the uncertainty bands was 88% in calibration periods and 75% in validation periods. Although monthly time step simulations showed good agreement with observed discharges during the two main discharge events in spring, the contradictory daily time step results indicate that the watershed response simulations on a daily basis need to be improved. The uncertainty analysis showed that in periods of higher discharge, such as spring periods, the uncertainty in prediction was higher. It is important to note that these uncertainty estimations using the GLUE procedure include the uncertainties in measured discharge values, model inputs, boundary conditions and model structures. It was estimated that stream baseflow represented 42% of the total watershed discharge, but further research is needed to confirm this. These results show that the new Arc Hydro–DRAINMOD framework is applicable for predicting discharge from artificially drained watersheds in southeast Sweden. Copyright © 2010 John Wiley & Sons, Ltd.     

Simple procedure to simulate karstic aquifers

A procedure to simulate karstic aquifers is presented. It is based on a simulation of spring discharge using precipitation and, where necessary, temperature as input data. The karstic aquifer system is considered to be divided into three zones: the surface zone, the unsaturated zone (UZ) and the saturated zone (SZ). Each of these is described by a transfer function that determines the water supplied from the overlying zone. Water loss through evapotranspiration is calculated empirically and subtracted from the total precipitation in order to obtain the effective infiltration into the UZ. The transfer function characterizing the UZ can be expressed as a convolution function. The UZ acts as a buffer, delaying effective infiltration into the SZ. Water discharge from the SZ is described by the recession function of the spring, and this becomes the transfer function that characterizes the emergence of water from the SZ. The model permits the simulation of the influence of pumped abstractions from the system by a simple modification of the transfer functions involved. Copyright © 2007 John Wiley & Sons, Ltd.     

Turbidity dynamics in karstic systems. Example of Ribaa and Bittit springs in the Middle Atlas (Morocco)

Abstract

The identification of the turbidity mechanisms in two karstic springs (Ribaa and Bittit) located in the Middle Atlas Plateau in Morocco was performed by means of correlation and spectral analyses applied to time series of rainfall, flow rates, and turbidity. Time series analyses of rainfall and discharges revealed high inertia and storage capacities of the karstic systems. However, the occurrence of turbidity in the springs proved independent of discharges. A causal relationship between rainfall and the occurrence of turbidity in the form of waves was established. Accordingly, turbidity was assumed to be related to the hydrodynamic conditions prevailing in the karst. Turbulent quickflows in the karst transmissive conduits, following heavy rainfall, are thought to provoke the resuspension of solid particles deposited in the conduits, as well as their transport towards outlets. An external origin has also been contemplated, concerning infiltration waters may be loaded with suspended matters washed from the watershed.     

Natural responses of Neoproterozoic dynamic karst springs to rainfall events,São Miguel Watershed,Minas Gerais,Brazil

Karst aquifers consist of complex networks of conduits in which groundwater flows and recharge/discharge processes are generally more dynamic than in other types of aquifers. Due to their intrinsic heterogeneity and anisotropy, monitoring, quantifying, and analysing natural responses of karst springs is an efficient tool. Unlike Cenozoic and Mesozoic rocks, in Neoproterozoic karst systems, groundwater circulates and stores generally in dissolution features known as tertiary porosity, as the rock's primary porosity is recrystallized, considered negligible. This article studies the hydrodynamics of a karst portion of the São Miguel River basin, southwest of the state of Minas Gerais, Brazil. The region is predominantly composed of Neoproterozoic carbonate rocks, dating from about 570 to 540 million years ago. During a hydrological year (2019–2020), three karst springs (S1, S2, and S3) were daily monitored through their natural responses (variations of electrical conductivity, EC, temperature, T, and discharge, Q) to rainfall episodes. The data were interpreted based on the analysis of spring hydrographs, time series, recession curves (seasonal and intra-annual), and statistics of EC, T, and Q variations. The results show the three springs generally exhibit quick flow, typically karstic, in the case of hydrosystems with a well-structured and functional underground drainage network. The time series indicate the hydrosystem drained by S1 presents slower circulation and a lower degree of linearity, resulting from the higher sinuosity of the system, while the hydrosystems of S2 and S3 have similar behaviours, of quick water circulations immediately after a rainy episode. The degrees of karstification classify S1 and S2 as complex and extensive karst systems consisting of several subsystems, and S3 as a system in which the conduit network is more developed at the upper epiphreatic zone than near the outlet.     

Introducing the recharge–discharge relationship to evaluate the recharge coefficient of karstic aquifers: thematic and indexing approaches

ABSTRACT

Karst aquifers and springs are important with respect to their potential for supplying drinking water in regions suffering from water scarcity in Iran. Accordingly, it is essential to determine the recharge potential of the catchment and the regions with higher obtainability potential. This study provides a road map for the Sheshpeer catchment in southern Iran. A recharge potential (RP) map was produced from which a recharge index (RI) was computed for several selected springs in the catchment. Furthermore, the unit discharge (q) – defined as the average annual discharge for a given catchment area and unit rainfall depth for each spring – was calculated. The plot of q versus RI for the springs showed a linear positive relationship between the two variables (R ² = 0.9). Applying the trend equation of this plot to the whole Sheshpeer karstic catchment reveals that its long-term recharge coefficient is 0.74.     

Variation of karst spring discharge in the recent five decades as an indicator of global climate change: A case study at Shanxi,northern China

As one of the largest international scientific pro- grams in geoscience and environmental science, global change studies were initiated in the early 1980s[1,2]. Noticeable achievements have been made in the stud- ies using indicators such as loess, marine sediment, permafrost, vermicular red earth, and even magmatic activity[2―6]. In recent years, the importance of ground- water as a new type of global change indicators has caused wide attention[7]. Stochastic, isotopic and hy- drochemical st…