Correlation of vertical electrical sounding and electrical borehole log data for groundwater exploration

We have correlated the longitudinal unit conductance CL obtained from interpreted vertical electrical sounding data with the formation resistivity R_t and the formation resistivity factor F, obtained by carrying out electrical borehole logging. Interpreted geophysical data of eleven soundings and two electrical borehole log records are used for the analysis. The geophysical data used were acquired in a sedimentary basin. The study area is called Lower Maner Basin located in the province of Andhra Pradesh, India. Vertical electrical soundings were carried out using a Schlumberger configuration with half current electrode separation varying from 600–1000 m. For logging the two boreholes, a Widco logger‐model 3200 PLS was used. True formation resistivity R_t was calculated from a resistivity log. Formation resistivity factor F was also calculated at various depths using R_t values. An appreciable inverse relation exists between the correlated parameters. The borehole resistivity R_t and the formation resistivity factor F decrease with the increase in the longitudinal unit conductance CL. We have shown the use of such a relation in computing borehole resistivity R_t and formation resistivity factor F at sites that posses only vertical electrical sounding data, with a fair degree of accuracy. Validation of the correlation is satisfactory. Scope for updating the correlation is discussed. Significance and applications of the relation for exploration of groundwater, namely to update the vertical electrical sounding data interpretation by translating the vertical electrical sounding data into electrical borehole log parameters, to facilitate correlations studies and to estimate the porosity (φ), permeability (K) and water saturation S_w of water bearing zones are discussed.     

Estimating time parameters of overland flow on impervious surfaces by the particle tracking method

Abstract

Travel time and time of concentration T_c are important time parameters in hydrological designs. Although T_c is the time for the runoff to travel to the outlet from the most remote part of the catchment, most researchers have used an indirect method such as hydrograph analysis to estimate T_c. A quasi two-dimensional diffusion wave model with particle tracking for overland flow was developed to determine the travel time, and validated for runoff discharges, velocities, and depths. Travel times for 85%, 95% and 100% of particles arrival at the outlet of impervious surfaces (i.e. T_t85, T_t95, and T_t100) were determined for 530 model runs. The correlations between these travel times and T_c estimated from hydrograph analysis showed a significant agreement between T_c and T_t85. All the travel times showed nonlinear relationships with the input variables (plot length, slope, roughness coefficient, and effective rainfall intensity) but showed linear relationships with each other.

Editor D. Koutsoyiannis; Associate editor S. Grimaldi     

Sensitivity analysis of a no-crossflow model for the transient flowmeter test

 Logarithmic sensitivities and plausible relative errors are studied in a simple no-crossflow model of a transient flowmeter test (TFMT). This model is identical to the model of a constant-rate pumping test conducted on a fully penetrating well with wellbore storage, surrounded by a thick skin zone, and situated in a homogeneous confined aquifer. The sensitivities of wellbore drawdown and wellface flowrate to aquifer and skin parameters are independent of the pumping rate. However, the plausible relative errors in the aquifer and skin parameters estimated from drawdown and wellface flowrate data can be proportionally decreased by increasing the pumping rate. The plausible relative errors vary by many orders of magnitude from the beginning of the TFMT. The practically important flowrate and drawdown measurements in this test, for which the plausible relative errors vary by less than one order of magnitude from the minimum plausible relative errors, can begin approximately when the dimensionless wellface flowrate exceeds q _D =q/Q≈0.4. During most of this stage of the test, the plausible relative errors in aquifer hydraulic conductivity (K _a ) are generally an order of magnitude smaller than those in aquifer specific storativity. The plausible relative errors in the skin hydraulic conductivity (K _s ) are generally larger than the plausible relative errors in the aquifer specific storativity when the thick skin is normal (K _s >K _a ) and smaller when the thick skin is damaged (K _s <K _a ). The specific storativity of the skin zone would be so biased that one should not even attempt to estimate it from the TFMT. We acknowledge Wiebe H. van der Molen for recommending the De Hoog algorithm and sharing his code. This research was partially supported by the US Geological Survey, USGS Agreement #1434-HQ-96-GR-02689 and North Carolina Water Resources Research Institute, WRRI Project #70165.     

Prediction of rainfall‐induced shallow landslides in the Loess Plateau,Yan'an,China, using the TRIGRS model

In this work, a transient rainfall infiltration and grid‐based regional slope‐stability model (TRIGRS) was implemented in a case study of Yan'an City, Northwest China. In this area, widespread shallow landslides were triggered by the 12 July 2013 exceptional rainstorm event. A high‐resolution DEM, soil parameters from in‐situ and laboratory measurements, water table depths, the maximum depth of precipitation infiltration and rain‐gauge‐corrected precipitation of the event, were used as inputs in the TRIGRS model. Shallow landslides triggered on the same day were used to evaluate the modeling results. The summarized results are as follows: (i) The characteristics and distribution of thirty‐five shallow landslides triggered by the 12 July 2013 rainfall event were identified in the study area and all were classified as shallow landslides with the maximum depth, area and volume less than 3 m, 200 m² and 1000 m³, respectively, (ii) Four intermediate factor of safety (F_S) maps were generated using the TRIGRS model to represent the scenarios 6, 12, 18 and 24 hours after the storm event. The area with F_S < 1 increased with the rainfall duration. The percentage of the area with F_S < 1 was 0.2%, 3.3%, 3.8% and 5.1% for the four stages, respectively. Twenty‐four hours after the rainstorm, TRIGRS predicted that 1255 grid cells failed, which is consistent with the field data. (iii) TRIGRS generated more satisfactory results at a given precipitation threshold than SINMAP, which is ideal for landslide hazard zoning for land‐use planning at the regional scale. Comparison results showed that TRIGRS is more useful for landslide prediction for a certain precipitation threshold, also in the regional scale. (iv) Analysis of the responses of loess slope prone to slope failure after different precipitation scenarios revealed that loess slopes are particularly sensitive to extended periods of heavy precipitation. Copyright © 2016 John Wiley & Sons, Ltd.     

Moho depth of the European Plate from teleseismic receiver functions

Crustal structure and the Moho depth are exceptionally well known beneath Europe. The first digital, high-resolution map of the Moho depth for the whole European Plate was compiled in 2007 and recently published in Geophysical Journal International. In the past few years, considerable developments have taken place in the receiver function techniques. Different receiver function techniques provide new, independent information, in particular on the S-wave velocity distribution in the crust and on the Moho depth. This gives an opportunity to compare the Moho depth from the Moho depth map of the European Plate (H _MM) and the Moho depth from receiver function studies (H _RF). Herein, we also compile and analyze the uncertainty of the crustal thickness determinations data obtained with receiver function analysis. The uncertainty is found to be ±2 km for 20-km-thick crust and about ±4 km for 60-km-thick crust. Comparison of the Moho depths shows an approximately linear trend between H _RF and H _MM. For the Moho depth of 30–40 km, the values are approximately equal, while for thin crust, H _RF is about 5 km shallower than H _MM, and for thick crust, it is about 5 km deeper than H _MM. Possible reasons for this, the observed discrepancy between the Moho depths H_MM and H_RF, are discussed.     

Passive and active control of three‐dimensional buildings

The majority of the recent research effort on structural control considers two‐dimensional plane structures. However, not all buildings can be modelled as plane structures, thus limiting the capability of the proposed procedures only to regular and symmetrical structures. A new procedure is developed in this paper to analyse three‐dimensional buildings utilizing passive and active control devices. In the building model, the floors are assumed rigid in their own plane resulting in three degrees of freedom at each floor. Two types of active control devices utilizing an active tuned mass damper and an active bracing system are considered. The effect of passive mass dampers and active control force in the equations of motion is incorporated by using the Hamilton's principle. The passive parameters of the dampers as well as the controller gain is then optimized using a genetic based optimizer where the H₂, H_∞ and L₁ norms are taken as the objective functions. Copyright © 2000 John Wiley & Sons, Ltd.     

Depth of detection of buried resistive targets with some electrode arrays in electrical prospecting

Assuming the minimum detectable anomaly to be 10%, depths of detection of a 2D vertical resistive sheet of thickness t are found to be 4.0t, 3.0t, 4.0t and 4.0t with Wenner, two-electrode, three-electrode and dipole-dipole (β-Wenner) arrays, respectively, when the array spread is in-line. On the other hand, the depths of detection obtained with a broadside spread of the arrays right over the sheet are much less and are correspondingly 2.5t, 2.0t, 2.5t and 2.5t. An increase in the depth extent W of the sheet from 10t to 20t does not increase its depth of detection with the arrays. The depths of detection of an infinitely resistive horizontal cylinder of radius R are respectively 1.5R, 1.8R, 2.0R and 2.0R with the above-listed arrays when the array spread is in-line. With broadside spread of any of the arrays, the depth of detection is seen to be 2.5R. In the case of a spherical target of radius R, the detection depths of any of the arrays are found to be small and to vary between 0.8R and 1.1R. Comparatively, the detection depths of resistive targets are much lower than those of conductive targets of the same size and shape, with any electrode array. Among all the arrays studied, the two-electrode array performs worst in the detection of resistive targets while it performs best in detecting conducting targets of limited lateral extent. In the case of a spherical target, either resistive or conductive, there is no distinct change in its detection depth with array.     

Application of wavelet‐based multi‐model Kalman filters to real‐time flood forecasting

This paper presents the application of a multimodel method using a wavelet‐based Kalman filter (WKF) bank to simultaneously estimate decomposed state variables and unknown parameters for real‐time flood forecasting. Applying the Haar wavelet transform alters the state vector and input vector of the state space. In this way, an overall detail plus approximation describes each new state vector and input vector, which allows the WKF to simultaneously estimate and decompose state variables. The wavelet‐based multimodel Kalman filter (WMKF) is a multimodel Kalman filter (MKF), in which the Kalman filter has been substituted for a WKF. The WMKF then obtains M estimated state vectors. Next, the M state‐estimates, each of which is weighted by its possibility that is also determined on‐line, are combined to form an optimal estimate. Validations conducted for the Wu‐Tu watershed, a small watershed in Taiwan, have demonstrated that the method is effective because of the decomposition of wavelet transform, the adaptation of the time‐varying Kalman filter and the characteristics of the multimodel method. Validation results also reveal that the resulting method enhances the accuracy of the runoff prediction of the rainfall–runoff process in the Wu‐Tu watershed. Copyright © 2004 John Wiley & Sons, Ltd.     

Dehydration of clastic sediments in subduction zones: Theoretical study using thermodynamic data of minerals

Pseudosections for two sediments and one basalt calculated in the system K₂O–Na₂O–CaO–MgO–FeO–Fe₂O₃–Al₂O₃–TiO₂–SiO₂–H₂O for the P–T range 10 to 35 kbar, 300 to 900°C give useful insights into the amount of H₂O released from oceanic crust in subduction zones. In cold subduction zones (20 kbar–300°C to 35 kbar–500°C) hydrous minerals storing 3 to 4 wt% H₂O are still present in metasediments at depths of 120 km. In the same environment, metabasite releases 1 wt% H₂O in the depth range 100 to 120 km, but 4.5 wt% H₂O is transported to greater depths. In hot subduction zones (300°C hotter than the cold subduction zone at 100 km depth), dehydration events of metasediments in the depth range 50 to 80 km correspond to the breakdown of chlorite and paragonite. In the calculations no further water is released at greater depths because the modal content of phengite, the only hydrous mineral phase at these depths, remains almost constant. For the same P–T path, metabasite shows continuous dehydration between 40 and 80 km releasing almost 3 wt% H₂O. At 120 km depth less than 0.4 wt% of H₂O remains. In an average modern subduction zone (～6°C/km) most dehydration of sediments occurs at depths of 70 to 100 km and that of basalts at depths of 80 to 120 km. Only 1.3 wt% H₂O in metasediments and 1.6 wt% H₂O in metabasalt has the potential to be subducted to depths greater than 120 km. The dehydration behavior of sediments concurs with the generally held idea that subduction zone fluids are most effectively transported to great depths by cold subduction. In hot subduction zones, such as those characteristic of early Earth, most H₂O carried by oceanic crust is liberated at depths less than 120 km and, thus, would not contribute to island‐arc magmatism.     

S-wave envelope broadening characteristics of microearthquakes in the Canary Islands

This study analyzes the S-wave envelope broadening characteristics of 290 earthquakes recorded by 14 stations of the Spanish National Seismograph Network in the Canary Islands region. The S-wave peak delay time (t _p ) and envelope duration (t _q ) parameters are evaluated phenomenologically to infer the strength of velocity inhomogeneities of the medium along each seismic ray path. Crustal (0?≤?h?≤?18 km) and upper mantle (18?<?h?≤?80 km) events are analyzed separately. Results in the frequency range 1 to 12 Hz for hypocentral distances from 30 to 600 km show that both t _p and t _q increase according to a power of hypocentral distance and they are independent of frequency. The spatial distribution of the peak delay time reveals weak strength of heterogeneity in most of the region at shallow depths. Relatively strong inhomogeneous zones are generated under the island of Tenerife and Gran Canaria at depths of 11–22 km.     

Removal of Hydrogen Sulfide by Physico‐Biological Filter Using Mixed Rice Husk Silica and Dried Activated Sludge

This study investigated the effectiveness of a new packing material, namely mixed rice husk silica with dried activated sludge for removing H₂S. Dried sewage sludge was collected from Putrajaya sewage treatment plant in Malaysia. Rice husk silica was prepared at temperature of 800°C, after acid leaching and mixed with dried sewage sludge to be utilized in a polyvinyl chloride filter. The system was operated under variable conditions of two parameters, different inlet gas concentration and different inlet flow rate. H₂S was passed through the filter with one liter of the packing material. More than 99.96% removal efficiency (RE) with empty bed residence time (EBRT) of 90–45 s and 300 ppm inlet concentration was observed. However, the RE decreased to 96.87% with the EBRT of 30 s. The maximum elimination capacity (EC) of 52.32 g/m³/h was obtained with the RE of 96.87% and H₂S mass loading rate of 54 g/m³/h, while at the RE of 99.96%, maximum EC was 26.99 g/m³/h with the H₂S mass‐loading rate of 27 g/m³/h. A strong significant correlation between increasing of H₂S mass loading rate and pressure drop was also detected (p < 0.01). Maximum pressure drop was 3.0 mm H₂O after 53 days of operating time, the EBRT of 30 s, and 54 g/m³/h of H₂S loading rate. These observations suggest that the mixture of rice husk silica with dried activated sludge is a suitable physico‐biological filter for H₂S removal.     

Control algorithm for estimating future responses of active variable stiffness structure

A control algorithm has been developed for controlling Active Variable Stiffness (AVS) structures. This algorithm analyses information of an observed seismic excitation, estimates the future structural responses and determines how to alter the structure stiffness. An objective structure is assumed to possess N on-off elements whose states are controlled by the proposed algorithm. That is, at a given moment t_k, (1) seismic excitation information is expressed by an Auto Regressive (AR) model as the identification model; (2) future excitation information is predicted using the AR model; (3) future responses due to predicted excitation are estimated; (4) based on the initial condition at t_k, the responses of 2^N possible structural states from t_k, to t_k+L are calculated; (5) the state which minimizes the input energy during t_L is selected; and (6) immediately after t_k, on-off elements are set up and subjected to the selected states. The effectiveness of the induced algorithm is confirmed by numerical experiments on a model of a three-storey building under sine and seismic excitations.     

Anisotropy and temporal variations in the fast azimuth of the fast shear wave beneath southern Kamchatka during 1993–2002

Parameters of split shear waves from local earthquakes in the area of the PET IRIS station (town of Petropavlovsk-Kamchatski) were measured over the period 1993–2002 for the study of anisotropic properties of rocks in the subduction zone and variations in the fast azimuth of the fast shear wave (?). The dominating fast shear wave polarization directions were oriented in 1993–2002 along N90°E ± 20° in agreement with the direction of the Pacific plate motion. The normalized shear wave delay times δt _SS increase to a depth of 150 km. The values of δt _SS are largest (up to 20 ms/km) for earthquakes at depths of 50–60 and 90–150 km and smallest (up to 6 ms/km) for earthquakes at depths greater than 200 km. The fast azimuths for events with H < 80 km are described in terms of a horizontal transversely isotropic (HTI) model of the medium, with the axis oriented northward. Temporal variations in the fast azimuths with an amplitude of up to 90° and a predominant period of about 400–600 days are observed for events at depths of 80–120 km. The anisotropy of rocks is described by effective models of the orthorhombic and HTI symmetries. The predominant fast shear wave fast azimuths from events at depths of 120–310 km vary with time: the polarization axis was oriented to the north in 1993–1995, to the north and east in 1996–1998, to the east in 1999–2000, and to the northeast and southeast in 2001–2002. The anisotropy of rocks can be described in terms of the HTI model with the symmetry axis subparallel to the focal zone dip.     

Modeling non-stationary extreme waves using a point process approach and wavelets

In the present paper a statistical model for extreme value analysis is developed, considering seasonality. The model is applied to significant wave height data from the N. Aegean Sea. To build this model, a non-stationary point process is used, which incorporates apart from a time varying threshold and harmonic functions with a period of one year, a component μ _w(t) estimated through the wavelet transform. The wavelet transform has a dual role in the present study. It detects the significant “periodicities” of the signal by means of the wavelet global and scale-averaged power spectra and then is used to reconstruct the part of the time series, μ _w(t), represented by these significant features. A number of candidate models, which incorporate μ _w(t) in their location and scale parameters are tried. To avoid overparameterisation, an automatic model selection procedure based on the Akaike information criterion is carried out. The best obtained model is graphically evaluated by means of diagnostic plots. Finally, “aggregated” return levels with return periods of 20, 50 and 100 years, as well as time-dependent quantiles are estimated, combining the results of the wavelet analysis and the Poisson process model, identifying a significant reduction in return level estimation uncertainty, compared to more simple non-stationary models.     

An approach to estimation problems containing uncertain parameters

We consider how to treat a finite-dimensional linear inverse problem when the form of the forward problem is known exactly, but is dependent upon some parameters whose exact value is uncertain and which enter the forward problem multiplicatively. We show one way to proceed when the uncertainty is treatable in a statistical manner. Predicting the secular variation ∂_tB(t) produced by a particular fluid flow V at the core-mantle boundary (when magnetic diffusion is ignored) is one such example, because the results depend on the main magnetic field B(t) originating in the core which is improperly known because of contamination by the crustal magnetic field. This infinite-dimensional inverse problem is often solved by projection on to a finite-dimensional basis, and the resulting parameters found by a maximum likelihood technique. If the main field is contaminated with errors from a Gaussian distribution, this paper describes how the maximum likelihood solution can take this into account, and we show the probability density function that must be maximised in this case. We give an example of the effects for a simple model system, and suggest possible areas of application.     

Robust data assimilation in hydrological modeling – A comparison of Kalman and H-infinity filters

Hydrological model and observation errors are often non-Gaussian and/or biased, and the statistical properties of the errors are often unknown or not fully known. Thus, determining the true error covariance matrices is a challenge for data assimilation approaches such as the most widely used Kalman filter (KF) and its extensions, which assume Gaussian error nature and need fully known error statistics. This paper introduces H-infinite filter (HF) to hydrological modeling and compares HF with KF under various model and observation error conditions. HF is basically a robust version of KF. When model performance is not well known, or changes unpredictably, HF may be preferred over KF. HF is especially suitable for the cases where the estimation performance in the worst error case needs to be guaranteed. Through the application of HF to a hypothetical hydrologic model, this paper shows that HF is less sensitive to the uncertainty in the initial condition, corrects system bias more effectively, and converges to true state faster after interruptions than KF. In particular, HF performs better in dealing with instant human inputs (irrigation is used as an example), which are characterized by non-stationary, non-Gaussian and not fully known errors. However HF design can be more difficult than KF design due to the sensitivity of HF performance to design parameters (weights for model and observation error terms). Through sensitivity analysis, this paper shows the existence of a certain range of those parameters, in which the “best” value of the parameters is located. The tuning of HF design parameters, which can be based on users’ prior knowledge on the nature of model and observation errors, is critical for the implementation of HF.     

Recharge,upflux and water table response for shallow water table conditions in southwest Florida

A disproportionate increase or decrease in water table in response to minor water input or drainage is observed in shallow water table conditions inside drainage lysimeters. This increase happens because the capillary fringe of the shallow water table reaches up to or near the surface (Wieringermeer effect). The correlations between water table level changes and rainfall, seepage irrigation, drip irrigation, and drainage were analysed. Correlations with rainfall, seepage irrigation, and drainage were high (R² ranged from 0·46 to 0·97). Drip irrigation had low correlations due to the low rates of application (R² ranged from 0·26 to 0·44). Conventional methods of calculating recharge, such as multiplying the specific yield with the water table fluctuations, cannot be used for Wieringermeer effect situations. A method using water balance data and soil moisture at different depths in the lysimeters was developed to estimate recharge and upflux. The recharge results were used to develop the apparent specific yield S_ya, which could be used to calculate consequent recharge events from water table fluctuation data. Combining the water table fluctuation relationships developed with the S_ya value will allow the prediction of recharge from rainfall and irrigation events without the need for soil moisture equipment. Copyright © 2005 John Wiley & Sons, Ltd.     

Fluid inclusion evidence for rapid formation of the vapor-dominated zone at Sulphur Springs, Valles caldera, New Mexico, USA

Microthermometric measurements were obtained for 618 fluid inclusions in hydrothermal quartz, fluorite and calcite and magmatic quartz phenocrysts in intracaldera tuffs from the VC-2A core hole in order to study evolutionary processes of the Sulphur Springs hydrothermal system in the Valles caldera. Relatively high T_h values in samples from shallow depths indicate erosion of about 200 m of caldera fill since deposition of hydrothermal minerals at shallow depths in the Sulphur Springs hydrothermal system, accompanied by a descent in the water table of the liquid-dominated reservoir. For samples collected below the current water level of the well, the minimum values of homogenization temperature (T_h) fit the present thermal profile, whereas minimum T_h values of samples from above the water level are several tens of degrees higher than the present thermal profile and fit a paleo-thermal profile following the boiling point curve for pure water, as adjusted to 92 °C at 20 m below the present land surface. This is attributed to development of an evolving vapor zone that formed subsequent to a sudden drop in the water table of the liquid-dominated reservoir. We suggest that these events were caused by the drainage of an intracaldera lake when the southwestern wall of the caldera was breached about 0.5 Ma. This model indicates that vapor zones above major liquid-dominated geothermal reservoirs can be formed due to dramatic changes in geohydrology and not just from simple boiling.     

Simulating low flows over a heterogeneous landscape in southeastern Poland

This paper presents a scheme describing low flow formation processes in areas with different environmental conditions, including the impact of the selection and explanatory power of predictors for a probabilistic model based on the Logit model. The research was carried out using 29 daily streamflow gauges located in the Lublin region of southeastern Poland for the hydrological period 1976–2018. Analysis resulted in two distinct low flow schemes. In the lowland rivers, low flows occur during the warm season and are related to evaporation exceeding precipitation. In the upland rivers, hydrogeological factors related to water levels in the local Cretaceous aquifers determine the occurrence of low flows. This differentiation affects the quality of the predictive models. For lowland rivers, models based on the climatic water balance with a monthly shift have a better fit, while these models used for upland rivers are characterized by an approximately 10% decrease in accuracy. For upland rivers, the combined C_tH_t models without shifts produce the best model fit. The generalized precision of the Logit models is around 80%–90%.