MoisturEC: A New R Program for Moisture Content Estimation from Electrical Conductivity Data

Noninvasive geophysical estimation of soil moisture has potential to improve understanding of flow in the unsaturated zone for problems involving agricultural management, aquifer recharge, and optimization of landfill design and operations. In principle, several geophysical techniques (e.g., electrical resistivity, electromagnetic induction, and nuclear magnetic resonance) offer insight into soil moisture, but data‐analysis tools are needed to “translate” geophysical results into estimates of soil moisture, consistent with (1) the uncertainty of this translation and (2) direct measurements of moisture. Although geostatistical frameworks exist for this purpose, straightforward and user‐friendly tools are required to fully capitalize on the potential of geophysical information for soil‐moisture estimation. Here, we present MoisturEC, a simple R program with a graphical user interface to convert measurements or images of electrical conductivity (EC) to soil moisture. Input includes EC values, point moisture estimates, and definition of either Archie parameters (based on experimental or literature values) or empirical data of moisture vs. EC. The program produces two‐ and three‐dimensional images of moisture based on available EC and direct measurements of moisture, interpolating between measurement locations using a Tikhonov regularization approach.     

Vertically Integrated Hydraulic Conductivity: A New Parameter for Groundwater-Surface Water Analysis

Numerical modeling of groundwater-surface water interactions provides vital information necessary for determining the extent of nutrient transport, quantifying water budgets, and delineating zones of ecological support. The hydrologic data that drive these models are often collected at disparate scales and subsequently incorporated into numerical models through upscaling techniques such as piecewise constancy or geostatistical methods. However, these techniques either use basic interpolation methods, which often simplifies the system of interest, or utilize complex statistical methods that are computationally expensive, time consuming, and generate complex subsurface configurations. We propose a bulk parameter termed “vertically integrated hydraulic conductivity” (K_V), and defined as the depth-integrated resistance to fluid flow sensed at the groundwater-surface water interface, as an alternative to hydraulic conductivity when investigating vertical fluxes across the groundwater-surface water interface. This bulk parameter replaces complex subsurface configurations in situations dominated by vertical fluxes and where heterogeneity is not of primary importance. To demonstrate the utility of K_V, we extracted synthetic temperature time series data from a forward numerical model under a variety of scenarios and used those data to quantify vertical fluxes using the amplitude ratio method. These quantified vertical fluxes and the applied hydraulic head gradient were subsequently input into Darcy's Law and used to quantify K_V. This K_V was then directly compared to the equivalent hydraulic conductivity (K_T) assuming an infinitely extending layer. Vertically integrated hydraulic conductivity allows for more accurate and robust flow modeling across the groundwater-surface water interface in instances where complex heterogeneities are not of primary concern.     

Sampling Strategies for Estimation of Parameters Related to Ground Water Quality

Multiple theoretical sampling designs are studied to determine whether sampling designs can be identified that will provide for characterization of ground water quality in rural regions of developing nations. Sampling design in this work includes assessing sampling frequency, analytical methods, length of sampling period, and requirements of sampling personnel. The results answer a set of questions regarding whether using innovative sampling designs can allow hydrogeologists to take advantage of a range of characterization technologies, sampling strategies, and available personnel to develop high-value, water-quality data sets. Monte Carlo studies are used to assess different sampling strategies in the estimation of three parameters related to a hypothetical chemical observed in a ground water well: mean concentration (MeanC), maximum concentration (MaxC), and total mass load (TML). Five different scenarios are simulated. These scenarios are then subsampled using multiple simulated sampling instruments, time periods (ranging from 1 to 10 years), and sampling frequencies (ranging from weekly to semiannually to parameter dependent). Results are analyzed via the statistics of the resulting estimates, including mean square error, bias, bias squared, and precision. Results suggest that developing a sampling strategy based on what may be considered lower quality instruments can represent a powerful field research approach for estimating select parameters when applied at high frequency. This result suggests the potential utility of using a combination of lower quality instrument and local populations to obtain high frequency data sets in regions where regular monitoring by technicians is not practical.     

A New System for Ground Water Monitoring

This paper describes a new system for ground water monitoring, "the BAT System," which includes the following functions: (a) sampling of ground water in most types of soils, (b) measurement of pore water pressure, and (c) in situ measurement of hydraulic conductivity. The system can also be used for tracer tests. The system utilizes a permanently installed filter tip attached to a steel or PVC pipe. Installation is normally performed by pushing the tip down to the desired depth. The filter tip can also be buried beneath a landfill. The primary feature of the new system is that the filter tip contains a self-sealing quick coupling unit, which makes it possible to temporarily connect the filter tip to adapters for various functions, e.g. water sampling and for measurement of pore pressure and hydraulic conductivity. The new technique makes sampling of both pressurized water and gas possible. Samples are obtained directly in hermetically sealed, pre-sterilized sample cylinders. Sampling of ground water and measurement of pore pressure can be repeated over a long period of time with undiminished accuracy. This technique is also well-adapted for taking water samples from different strata in a soil profile, in both the saturated and unsaturated zones. Actual installations range from 0.5 to 60m depth.     

综合治理太湖污染的一种方法：为环境目的而挖泥

The eutrophication of Lake Taihu is becoming more serious day by day and more urgent to be comprehensively harnessed. The lake sludge is considered as a important polluting factor. To control the internal pollution source of Lake Taihu and restore its water ecological environment, this paper put forward an idea of the dredging for environmental purposes. It was on the basis of the research on the sludge storage and physical/chemical characteristics. The technical keys are sludge-dredging depth, time, method and sludge treatment. The requirements and scheme for the environmental dredging work in Lake Taihu were also analyzed in detail.     

A New Method for the Estimation of Avalanche Distance Exceeded Probabilities

A crucial point in any methodology for avalanche hazard assessment is the evaluation of avalanche distance exceeded probability, i.e., the annual probability that any assigned location along a given path is reached or exceeded by an avalanche. Typically this problem is faced by estimating the snow volume in the starting zone that is likely to accumulate an average every T years by statistical analysis of snowfall record, and then using this volume as input to an appropriately calibrated avalanche dynamics model to determine the runout distancesfor this design event. This methodology identifies the areas that canbe affected by an avalanche for the considered value of the return period (i.e. the average interval of time for a certain event to repeat itself), ¯T. However, it does not allow us to evaluate the actual avalanche encounter probability for any given point in the runout zone. In the present work this probability is computed by numerical integration of the expression P(x) = ∫₀ ^∞ P^*(V)f(V) dV, where f is the probabilitydensity function (PDF) of the avalanche release volume V, and P^* is the probability of the point x being reached or passed by an avalanche if the release volume is V; this latter probability is calculated by avalanche dynamics simulations. The procedure is implemented using a one-dimensional hydraulic-continuum avalanche dynamic model, calibrated on data from different Italian Alpine ranges, and is applied to a real world hazard mapping problem.     

Determination of Hydraulic Conductivity from Grain‐Size Distribution for Different Depositional Environments

Over 400 unlithified sediment samples were collected from four different depositional environments in global locations and the grain‐size distribution, porosity, and hydraulic conductivity were measured using standard methods. The measured hydraulic conductivity values were then compared to values calculated using 20 different empirical equations (e.g., Hazen, Carman‐Kozeny) commonly used to estimate hydraulic conductivity from grain‐size distribution. It was found that most of the hydraulic conductivity values estimated from the empirical equations correlated very poorly to the measured hydraulic conductivity values with errors ranging to over 500%. To improve the empirical estimation methodology, the samples were grouped by depositional environment and subdivided into subgroups based on lithology and mud percentage. The empirical methods were then analyzed to assess which methods best estimated the measured values. Modifications of the empirical equations, including changes to special coefficients and addition of offsets, were made to produce modified equations that considerably improve the hydraulic conductivity estimates from grain size data for beach, dune, offshore marine, and river sediments. Estimated hydraulic conductivity errors were reduced to 6 to 7.1 m/day for the beach subgroups, 3.4 to 7.1 m/day for dune subgroups, and 2.2 to 11 m/day for offshore sediments subgroups. Improvements were made for river environments, but still produced high errors between 13 and 23 m/day.     

A New Parameter Estimation Method for Solute Transport in a Column

To study contaminant transport in groundwater, an essential requirement is robust and accurate estimation of the transport parameters such as dispersion coefficient. The commonly used inverse error function method (IEFM) may cause unacceptable errors in dispersion coefficient estimation using the breakthrough curves (BTCs) data. We prove that the random error in the measured concentrations, which might be described by a normal distribution, would no longer follow the normal distribution after the IEFM transformation. In this study, we proposed a new method using the weighted least squares method (WLSM) to estimate the dispersion coefficient and velocity of groundwater. The weights were calculated based on the slope of the observed BTCs. We tested the new method against other methods such as genetic algorithm and CXTFIT program and found great agreement. This new method acknowledged different characteristics of solute transport at early, intermediate, and late time stages and divided BTCs into three sections for analysis. The developed method was applied to interpret three column tracer experiments by introducing continuous, constant‐concentration of sodium chloride (NaCl) into columns filled with sand, gravel, and sand‐gravel media. This study showed that IEFM performed well only when the observed data points were located in the linear (intermediate time) section of BTCs; it performed poorly when data points were in the early and late time stages. The new WLSM method, however, performed well for data points scattering over the entire BTCs and appeared promising in parameter estimation for solute transport in a column.     

A Simple Field Method for Assessing Near‐Surface Saturated Hydraulic Conductivity

This technical note describes an effective and inexpensive field technique for measuring the saturated hydraulic conductivity of both undisturbed cores and repacked soil samples. The method requires no specialized equipment; everything that is required can be obtained in a hardware store. The method is a straightforward field implementation of the widely used falling‐head laboratory analysis directly derived from Darcy's law. As such, it sidesteps the need for empirical assumptions about soil texture and the relationship between saturated and unsaturated flow components which many permeameter‐based methods rely upon. The method is shown to produce results that are consistent with K values obtained elsewhere in the same homogeneous sand formation. Furthermore, the proposed method is useful for measuring hydraulic conductivity in drill cuttings obtained from direct push or auguring drill techniques, which cannot be done with any other field method. The range of hydraulic conductivity values that this test is appropriate for is on the order of 1E ? 7 m/s to 1E ? 3 m/s.     

A Physically Based Approach for Estimating Hydraulic Conductivity from HPT Pressure and Flowrate

The hydraulic profiling tool (HPT) is widely used to generate profiles of relative permeability vs. depth. In this work, prior numerical modeling results are used to develop a relationship between probe advance rate V (cm/s), probe diameter D (cm), water injection rate Q (mL/min), corrected pressure P_c (psi), and hydraulic conductivity K (feet/d) ((1)) where E is an empirically derived hydraulic efficiency factor. The relationship is validated by 23 HPT profiles that, after averaging K vertically, were similar to slug test results in adjoining monitoring wells. The best fit value of E for these profiles was 2.02. This equation provides a physically based approach for generating hydraulic conductivity profiles with HPT tooling.