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1.
Analysis of methods to estimate spring flows in a karst aquifer 总被引：2，自引：0，他引：2
Sepúlveda N 《Ground water》2009,47(3):337-349
Hydraulically and statistically based methods were analyzed to identify the most reliable method to predict spring flows in a karst aquifer. Measured water levels at nearby observation wells, measured spring pool altitudes, and the distance between observation wells and the spring pool were the parameters used to match measured spring flows. Measured spring flows at six Upper Floridan aquifer springs in central Florida were used to assess the reliability of these methods to predict spring flows. Hydraulically based methods involved the application of the Theis, Hantush-Jacob, and Darcy-Weisbach equations, whereas the statistically based methods were the multiple linear regressions and the technology of artificial neural networks (ANNs). Root mean square errors between measured and predicted spring flows using the Darcy-Weisbach method ranged between 5% and 15% of the measured flows, lower than the 7% to 27% range for the Theis or Hantush-Jacob methods. Flows at all springs were estimated to be turbulent based on the Reynolds number derived from the Darcy-Weisbach equation for conduit flow. The multiple linear regression and the Darcy-Weisbach methods had similar spring flow prediction capabilities. The ANNs provided the lowest residuals between measured and predicted spring flows, ranging from 1.6% to 5.3% of the measured flows. The model prediction efficiency criteria also indicated that the ANNs were the most accurate method predicting spring flows in a karst aquifer. 相似文献
2.
This paper evaluates the feasibility of using an artificial neural network (ANN) methodology for estimating the groundwater levels in some piezometers placed in an aquifer in north‐western Iran. This aquifer is multilayer and has a high groundwater level in urban areas. Spatiotemporal groundwater level simulation in a multilayer aquifer is regarded as difficult in hydrogeology due to the complexity of the different aquifer materials. In the present research the performance of different neural networks for groundwater level forecasting is examined in order to identify an optimal ANN architecture that can simulate the piezometers water levels. Six different types of network architectures and training algorithms are investigated and compared in terms of model prediction efficiency and accuracy. The results of different experiments show that accurate predictions can be achieved with a standard feedforward neural network trained usung the Levenberg–Marquardt algorithm. The structure and spatial regressions of the ANN parameters (weights and biases) are then used for spatiotemporal model presentation. The efficiency of the spatio‐temporal ANN (STANN) model is compared with two hybrid neural‐geostatistics (NG) and multivariate time series‐geostatistics (TSG) models. It is found in this study that the ANNs provide the most accurate predictions in comparison with the other models. Based on the nonlinear intrinsic ANN approach, the developed STANN model gives acceptable results for the Tabriz multilayer aquifer. Copyright © 2008 John Wiley & Sons, Ltd. 相似文献
3.
《Advances in water resources》2005,28(9):899-909
Functional networks were recently introduced as an extension of artificial neural networks (ANNs). Unlike ANNs, they estimate unknown neuron functions from given functional families during the training process. Here, we applied two types of functional network models, separable and associativity functional networks, to forecast river flows for different lead-times. We compared them with a conventional artificial neural network model, an ARMA model and a simple baseline model in three catchments. Results show that functional networks are flexible and comparable in performance to artificial neural networks. In addition, they are easier and quicker to train and so are useful tools as an alternative to artificial neural networks. These results were obtained with only the simplest structures of functional networks and it is possible that a more detailed study with more complex forms of the model will improve even further on these results. Thus we recommend that the use of functional networks in discharge time series modelling and forecasting should be further investigated. 相似文献
4.
Advances over the past 40 years have resulted in a clear understanding of how dissolution processes in carbonate rocks enhance aquifer permeability. Laboratory experiments on dissolution rates of calcite and dolomite have established that there is a precipitous drop in dissolution rates as chemical equilibrium is approached. These results have been incorporated into numerical models, simulating the effects of dissolution over time and showing that it occurs along the entire length of pathways through carbonate aquifers. The pathways become enlarged and integrated over time, forming self‐organized networks of channels that typically have apertures in the millimeter to centimeter range. The networks discharge at point‐located springs. Recharge type is an important factor in determining channel size and distribution, resulting in a range of aquifer types, and this is well demonstrated by examples from England. Most carbonate aquifers have a large number of small channels, but in some cases large channels (i.e., enterable caves) can also develop. Rapid velocities found in ground water tracer tests, the high incidence of large‐magnitude springs, and frequent microbial contamination of wells all support the model of self‐organized channel development. A large majority of carbonate aquifers have such channel networks, where ground water velocities often exceed 100 m/d. 相似文献
5.
ABSTRACTThe application of artificial neural networks (ANNs) has been widely used recently in streamflow forecasting because of their ?exible mathematical structure. However, several researchers have indicated that using ANNs in streamflow forecasting often produces a timing lag between observed and simulated time series. In addition, ANNs under- or overestimate a number of peak flows. In this paper, we proposed three data-processing techniques to improve ANN prediction and deal with its weaknesses. The Wilson-Hilferty transformation (WH) and two methods of baseflow separation (one parameter digital filter, OPDF, and recursive digital filter, RDF) were coupled with ANNs to build three hybrid models: ANN-WH, ANN-OPDF and ANN-RDF. The network behaviour was quantitatively evaluated by examining the differences between model output and observed variables. The results show that even following the guidelines of the Wilson-Hilferty transformation, which significantly reduces the effect of local variations, it was found that the ANN-WH model has shown no significant improvement of peak flow estimation or of timing error. However, combining baseflow with streamflow and rainfall provides important information to ANN models concerning the flow process operating in the aquifer and the watershed systems. The model produced excellent performance in terms of various statistical indices where timing error was totally eradicated and peak flow estimation significantly improved.
Editor D. Koutsoyiannis; Associate editor Y. Gyasi-Agyei 相似文献
6.
The purpose of this research is to include expert knowledge as one part of the modelling system and therefore offer the chance to create a productive interaction system between expert, mathematical model (MMO8) and artificial neural networks (ANNs). In the present project, the first objective is to determine some parameters by the MMO8 model, introduced as ANN input parameters to forecast spring outflow. The second objective is first to investigate the effect of temporal information by taking current and past data sets and then to forecast spring outflow. The good results obtained reveal the merit of the ANNs–MMO8 combination, and specifically multilayer perceptron (MLP) models. This methodology, for a network with lower, lag and number hidden layer, consistently produced better performance. Copyright © 2003 John Wiley & Sons, Ltd. 相似文献
7.
Data‐driven techniques based on machine learning algorithms are becoming popular in hydrological modelling, in particular for forecasting. Artificial neural networks (ANNs) are often the first choice. The so‐called instance‐based learning (IBL) has received relatively little attention, and the present paper explores the applicability of these methods in the field of hydrological forecasting. Their performance is compared with that of ANNs, M5 model trees and conceptual hydrological models. Four short‐term flow forecasting problems were solved for two catchments. Results showed that the IBL methods often produce better results than ANNs and M5 model trees, especially if used with the Gaussian kernel function. The study showed that IBL is an effective data‐driven method that can be successfully used in hydrological forecasting. Copyright © 2007 John Wiley & Sons, Ltd. 相似文献
8.
Most surface water bodies (i.e., streams, lakes, etc.) are connected to the groundwater system to some degree so that changes to surface water bodies (either diversions or importations) can change flows in aquifer systems, and pumping from an aquifer can reduce discharge to, or induce additional recharge from streams, springs, and lakes. The timescales of these interactions are often very long (decades), making sustainable management of these systems difficult if relying only on observations of system responses. Instead, management scenarios are often analyzed based on numerical modeling. In this paper we propose a framework and metrics that can be used to relate the Theis concepts of capture to sustainable measures of stream‐aquifer systems. We introduce four concepts: Sustainable Capture Fractions, Sustainable Capture Thresholds, Capture Efficiency, and Sustainable Groundwater Storage that can be used as the basis for developing metrics for sustainable management of stream‐aquifer systems. We demonstrate their utility on a hypothetical stream‐aquifer system where pumping captures both streamflow and discharge to phreatophytes at different amounts based on pumping location. In particular, Capture Efficiency (CE) can be easily understood by both scientists and non‐scientist alike, and readily identifies vulnerabilities to sustainable stream‐aquifer management when its value exceeds 100%. 相似文献
9.
Artificial neural networks (ANNs) were developed for accurately predicting potentiometric surface elevations (monitoring well water level elevations) in a semiconfined glacial sand and gravel aquifer under variable state, pumping extraction, and climate conditions. ANNs "learn" the system behavior of interest by processing representative data patterns through a mathematical structure analogous to the human brain. In this study, the ANNs used the initial water level measurements, production well extractions, and climate conditions to predict the final water level elevations 30 d into the future at two monitoring wells. A sensitivity analysis was conducted with the ANNs that quantified the importance of the various input predictor variables on final water level elevations. Unlike traditional physical-based models, ANNs do not require explicit characterization of the physical system and related physical data. Accordingly, ANN predictions were made on the basis of more easily quantifiable, measured variables, rather than physical model input parameters and conditions. This study demonstrates that ANNs can provide both excellent prediction capability and valuable sensitivity analyses, which can result in more appropriate ground water management strategies. 相似文献
10.
Automatic identification of noisy seismic events is still a problem. The process involves the analysis of complex relationships between data from different sources. Moreover, there are disturbing factors such as poor signal-to-noise ratio, the presence of accidental bursts of man-made noise, and changes in the amplitude and phase of the waves as they travel through the medium. The amount of observed data increases rapidly, so it is imperative to develop suitable and effective methods for processing and analyzing the influx of big data. Artificial neural networks (ANNs) show promise as a disruptive technology that will accelerate and improve analysis of seismic signals. ANNs are easy to apply, and the results often outperform alternative methods. This paper gives an overview of the highs and lows of neural networks, discusses the possibility of routine processing of seismic signals using ANNs, and presents examples of some interesting applications. It is hoped that researchers who read the article will actively use this technique, because ANNs could become more robust and flexible for solving complex problems that currently cannot be solved by the standard approach. 相似文献
11.
Antonella Amoruso Luca Crescentini Marco Petitta Sergio Rusi Marco Tallini 《水文研究》2011,25(11):1754-1764
The Mw = 6·3 L'Aquila earthquake on 6 April 2009 produced a mainshock that caused significant changes in the hydrogeology of the Gran Sasso carbonate fractured aquifer: (i) the sudden disappearance at the time of the mainshock of some springs located exactly along the surface trace of the Paganica normal fault (PF); (ii) an immediate increase in the discharge of the Gran Sasso highway tunnel drainages and of other springs and (iii) a progressive increase of the water table elevation at the boundary of the Gran Sasso aquifer during the following months. Using the data collected since the 1990s that include aftershock monitoring as well as data regarding spring discharge, water table elevations, turbidity and rainfall events, a conceptual model of the earthquake's consequences on the Gran Sasso aquifer is proposed herein. In this model that excludes the contribution of seasonal recharge, the short‐term hydrologic effects registered immediately after the mainshock are determined to have been caused by a pore pressure increase related to aquifer deformation. Mid‐term effects observed in the months following the mainshock suggest that there was a change in groundwater hydrodynamics. Supplementary groundwater that flows towards aquifer boundaries and springs in discharge areas reflects a possible increase in hydraulic conductivity in the recharge area, nearby the earthquake fault zone. This increase can be attributed to fracture clearing and/or dilatancy. Simulations by numerical modelling, related to pore pressure and permeability changes with time, show results in accordance with observed field data, supporting the conceptual model and confirming the processes that influenced the answer of the Gran Sasso aquifer to the L'Aquila earthquake. Copyright © 2010 John Wiley & Sons, Ltd. 相似文献
12.
《水文科学杂志》2013,58(1):192-205
Abstract Considering the geological conditions of the southwest of Boroujerd and northwest of Doroud, Iran, karst development is analysed with respect to the hydrodynamic behaviour of the main draining springs of the units and the karstic aquifers are classified as either those developed in Cretaceous limestone or those developed in Oligomiocene limestone. For this purpose, the yields of the main karstic springs of the region—Absardeh and Zoorabad (Cretaceous karstic limestone aquifer), Kalamsooz and Azizabad (Oligomiocene karstic limestone aquifer)—were measured and analysed. Analysis of the recession curve is used for hydrodynamical analysis and to construct the conceptual model for estimation of karst development in the selected aquifers. Based on the results, the dynamic storage capacity of the saturated zone in Cretaceous limestone is evaluated as low to medium and that in Oligomiocene limestone as medium to high. The dynamic storage capacity of the unsaturated zone in Cretaceous limestone is evaluated as high and that in Oligomiocene limestone as low to medium. Moreover, the contribution of quickflow in karstic aquifers developed in the Cretaceous limestone drained by the Absardeh and Zoorabad springs is 23.5 and 82.2%, respectively, and that for the Kalamsooz and Azizabad springs (Oligomiocene limestone) is 5.7 and 22.5%, respectively. Flow in the Cretaceous limestone aquifer drained by the Zoorabad Spring is of concentrated type and the main flow occurs in the well-developed karstic conduits. The main flow in the Oligomiocene limestone aquifer, drained by the Kalamsooz Spring, occurs in a network of joints and fractures and the contribution of concentrated flow is very low. The transmissivity of the saturated zone in the karstic aquifer drained by the Zoorabad and Absardeh springs is medium to high and that for the Kalamsooz and Azizabad springs is found to be low. 相似文献
13.
J. Farlin T. Gallé M. Bayerle D. Pittois C. Braun H. El Khabbaz M. Elsner P. Maloszewski 《Ground water》2013,51(2):276-285
Neighboring springs draining fractured‐rock aquifers can display large differences in water quality and flow regime, depending on local variations of the connectivity and the aperture size distribution of the fracture network. Consequently, because homogeneous equivalent parameters cannot be assumed a priori for the entire regional aquifer, the vulnerability to pollution of such springs has to be studied on a case by case basis. In this paper, a simple lumped‐parameter model usually applied to estimate the mean transit time of water (or tracer) is presented. The original exponential piston‐flow model was modified to take land‐use distribution into account and applied to predict the evolution of atrazine concentration in a series of springs draining a fractured sandstone aquifer in Luxembourg, where despite a nationwide ban in 2005, atrazine concentrations still had not begun to decrease in 2009. This persistence could be explained by exponentially distributed residence times in the aquifer, demonstrating that in some real world cases, models based on the groundwater residence time distribution can be a powerful tool for trend reversal assessments as recommended for instance by current European Union guidelines. 相似文献
14.
Artificial neural networks (ANNs) were developed to accurately predict highly time-variable specific conductance values in an unconfined coastal aquifer. Conductance values in the fresh water lens aquifer change in response to vertical displacements of the brackish zone and fresh water-salt water interface, which are caused by variable pumping and climate conditions. Unlike physical-based models, which require hydrologic parameter inputs, such as horizontal and vertical hydraulic conductivities, porosity, and fluid densities, ANNs can "learn" system behavior from easily measurable variables. In this study, the ANN input predictor variables were initial conductance, total precipitation, mean daily temperature, and total pumping extraction. The ANNs were used to predict salinity (specific conductance) at a single monitoring well located near a high-capacity municipal-supply well over time periods ranging from 30 d to several years. Model accuracy was compared against both measured/interpolated values and predictions were made with linear regression, and in general, excellent prediction accuracy was achieved. For example, although the average percent change of conductance over 90-d periods was 39%, the absolute mean prediction error achieved with the ANN was only 1.1%. The ANNs were also used to conduct a sensitivity analysis that quantified the importance of each of the four predictor variables on final conductance values, providing valuable insights into the dynamics of the system. The results demonstrate that the ANN technology can serve as a powerful and accurate prediction and management tool, minimizing degradation of ground water quality to the extent possible by identifying appropriate pumping policies under variable and/or changing climate conditions. 相似文献
15.
James C. Adamski 《水文研究》2000,14(5):849-866
Geochemical data indicate that the Springfield Plateau aquifer, a carbonate aquifer of the Ozark Plateaus Province in central USA, has two distinct hydrochemical zones. Within each hydrochemical zone, water from springs is geochemically and isotopically different than water from wells. Geochemical data indicate that spring water generally interacts less with the surrounding rock and has a shorter residence time, probably as a result of flowing along discrete fractures and solution openings, than water from wells. Water type throughout most of the aquifer was calcium bicarbonate, indicating that carbonate‐rock dissolution is the primary geochemical process occurring in the aquifer. Concentrations of calcium, bicarbonate, dissolved oxygen and tritium indicate that most ground water in the aquifer recharged rapidly and is relatively young (less than 40 years). In general, field‐measured properties, concentrations of many chemical constituents, and calcite saturation indices were greater in samples from the northern part of the aquifer (hydrochemical zone A) than in samples from the southern part of the aquifer (hydrochemical zone B). Factors affecting differences in the geochemical composition of ground water between the two zones are difficult to identify, but could be related to differences in chert content and possibly primary porosity, solubility of the limestone, and amount and type of cementation between zone A than in zone B. In addition, specific conductance, pH, alkalinity, concentrations of many chemical constituents and calcite saturation indices were greater in samples from wells than in samples from springs in each hydrochemical zone. In contrast, concentrations of dissolved oxygen, nitrite plus nitrate, and chloride generally were greater in samples from springs than in samples from wells. Water from springs generally flows rapidly through large conduits with minimum water–rock interactions. Water from wells flow through small fractures, which restrict flow and increase water–rock interactions. As a result, springs tend to be more susceptible to surface contamination than wells. The results of this study have important implications for the geochemical and hydrogeological processes of similar carbonate aquifers in other geographical locations. Copyright © 2000 John Wiley & Sons, Ltd. 相似文献
16.
Hydrogeological information for the territories of the Republic of Estonia, Leningrad province, and northern Pskov province of the Russian Federation is generalized. A unified groundwater flow model was developed for the Lomonosov-Voronkovskii aquifer, including its Estonian part is developed. The methodological approaches for solving transboundary problems as applied to groundwater are determined. The results of studying transboundary hydrodynamic interaction in Lomonosov-Voronkovskii aquifer in the Russian-Estonian boundary area are given. The direction of undisturbed groundwater flow is determined, and changes caused by the exploitation of the aquifer are assessed. 相似文献
17.
Interpretation of spring recession curves 总被引：4，自引：0，他引：4
Recession curves contain information on storage properties and different types of media such as porous, fractured, cracked lithologies and karst. Recession curve analysis provides a function that quantitatively describes the temporal discharge decay and expresses the drained volume between specific time limits (Hall 1968). This analysis also allows estimating the hydrological significance of the discharge function parameters and the hydrological properties of the aquifer. In this study, we analyze data from perennial springs in the Judean Mountains and from others in the Galilee Mountains, northern Israel. All the springs drain perched carbonate aquifers. Eight of the studied springs discharge from a karst dolomite sequence, whereas one flows out from a fractured, slumped block of chalk. We show that all the recession curves can be well fitted by a function that consists of two exponential terms with exponential coefficients alpha1 and alpha2. These coefficients are approximately constant for each spring, reflecting the hydraulic conductivity of different media through which the ground water flows to the spring. The highest coefficient represents the fast flow, probably through cracks, or quickflow, whereas the lower one reflects the slow flow through the porous medium, or baseflow. The comparison of recession curves from different springs and different years leads to the conclusion that the main factors that affect the recession curve exponential coefficients are the aquifer lithology and the geometry of the water conduits therein. In normal years of rainy winter and dry summer, alpha1 is constant in time. However, when the dry period is longer than usual because of a dry winter, alpha1 slightly decreases with time. 相似文献
18.
Changes in effective stress due to water pressure variations modify the intrinsic hydrodynamic properties of aquifers and aquitards. Overexploited groundwater systems, such as basins with heavy pumping, are subject to nonrecoverable modifications. This results in loss of permeability, porosity, and specific storage due to system consolidation. This paper presents (1) the analytical development of model functions relating effective stress to hydrodynamic parameters for aquifers and aquitards constituted of unconsolidated granular sediments, and (2) a modeling approach for the analysis of aquifer systems affected by effective stress variations, taking into account the aforementioned dependency. The stress‐dependent functions were fit to laboratory data, and used in the suggested modeling approach. Based on only few unknowns, this approach is computationally simple, efficiently captures the hydromechanical processes that are active in regional aquifer systems under stress, and readily provides an estimate of their consolidation. 相似文献
19.
The regional study of hydrodynamic characteristics of karstic aquifers is challenging because of the great variety of lithology and the structural complexity found in carbonate formations. In order to improve this situation, a combined approach of time series and stochastic analyses was adopted to assess the hydrodynamic behaviour of the karstic aquifers. To achieve this, daily flow rates of 20 springs were taken from the 11 most significant aquifer units of the Basque Country. The results demonstrate the presence of memory effects, which modulated the input rainfall for short‐, medium‐ and long‐term storage capacity, resulting in hydrodynamic properties such as system memory, response time and mean delay between input and output. They reflect the storage and the manner in which these are filled and emptied, thus indicating the karstification of the aquifer. Likewise, the hydrodynamic and hydraulic classification obtained from the stochastic analysis provides a complementary approach to characterize the hydraulic behaviour of the studied karstic aquifers. The discussed examples indicate that this approach provides an excellent method to research hydrological karst systems. It is also shown that the use of hydrologic time series, alone, does not lead to a satisfactory classification of the hydrodynamic characteristics. Therefore, the general approach to hydrological regionalization in karst areas should take into account the structural complexity, heterogeneity of the lithology and the degree of karstification. Only in this case will the regionalization be physically founded, leading to a regional understanding of the hydrodynamic characteristics and flow conditions in a karst aquifer. Copyright © 2009 John Wiley & Sons, Ltd. 相似文献
20.
Groundwater discharge from the Riverine Plains of the southern Murray‐Darling Basin is a major process contributing salt to the Murray River in Australia. In this study, data from an irrigated 60 000 ha catchment in the Riverine Plains were analysed to understand groundwater discharge into deeply incised drains, the process dominating salt mobilization from the catchment. We applied three integrated methodologies: classification and regression trees (CART), conceptual modelling and artificial neural networks (ANNs) to a comprehensive, spatially lumped, monthly data set from July 1975 to December 2004. Using CART analysis, it was shown that rainfall was the most important variable consistently explaining the salt load patterns at the catchment outlet. Using the conceptual model representing spatially lumped groundwater discharge into deeply incised drains, we demonstrated that salt mobilization from the study catchment can be well represented by a rainfall contribution, influenced by the hydraulic head in the deep regional aquifer and potential evapotranspiration. Using ANNs, it was confirmed that rainfall had a much higher impact on salt loads at the catchment outlet than irrigation water use. All these results demonstrate that under conditions similar to those experienced from 1975 to 2004, it is rainfall rather than irrigation water use that governs salt mobilization from the study catchment. Management of salt mobilization from irrigated catchments has traditionally focussed on the improvement of irrigation practices but it could be equally important to further understand the scope for management to control groundwater discharge in these irrigation areas. Copyright © 2010 John Wiley & Sons, Ltd. 相似文献