A stream depletion field experiment

A field experiment was carried out to measure drawdowns in observation wells and stream depletion flows that occurred when water was abstracted from a well beside a stream. The field data is analyzed herein to determine the aquifer transmissivity, T, the aquifer storage coefficient, S, and a streambed leakage parameter, lambda, by comparing measurements with a solution obtained by Hunt (1999). The analysis uses early time drawdowns with a match-point method to determine T and S, and stream depletion measurements at later times are used to determine lambda. The final results are reasonably consistent for measurements taken in four observation wells. The advantages and disadvantages of this approach are discussed, and two alternative ways of estimating lambda are also discussed.     

Improving a regional model using reduced complexity and parameter estimation

The availability of powerful desktop computers and graphical user interfaces for ground water flow models makes possible the construction of ever more complex models. A proposed copper-zinc sulfide mine in northern Wisconsin offers a unique case in which the same hydrologic system has been modeled using a variety of techniques covering a wide range of sophistication and complexity. Early in the permitting process, simple numerical models were used to evaluate the necessary amount of water to be pumped from the mine, reductions in streamflow, and the drawdowns in the regional aquifer. More complex models have subsequently been used in an attempt to refine the predictions. Even after so much modeling effort, questions regarding the accuracy and reliability of the predictions remain. We have performed a new analysis of the proposed mine using the two-dimensional analytic element code GFLOW coupled with the nonlinear parameter estimation code UCODE. The new model is parsimonious, containing fewer than 10 parameters, and covers a region several times larger in areal extent than any of the previous models. The model demonstrates the suitability of analytic element codes for use with parameter estimation codes. The simplified model results are similar to the more complex models; predicted mine inflows and UCODE-derived 95% confidence intervals are consistent with the previous predictions. More important, the large areal extent of the model allowed us to examine hydrological features not included in the previous models, resulting in new insights about the effects that far-field boundary conditions can have on near-field model calibration and parameterization. In this case, the addition of surface water runoff into a lake in the headwaters of a stream while holding recharge constant moved a regional ground watershed divide and resulted in some of the added water being captured by the adjoining basin. Finally, a simple analytical solution was used to clarify the GFLOW model's prediction that, for a model that is properly calibrated for heads, regional drawdowns are relatively unaffected by the choice of aquifer properties, but that mine inflows are strongly affected. Paradoxically, by reducing model complexity, we have increased the understanding gained from the modeling effort.     

The influence of stochasticism on Indian summer monsoon rainfall and its impact on prediction

Output from a multi-millennial control simulation of the CSIRO Mark 2 coupled model has been used to investigate quantitatively the relation between the Indian summer monsoon rain and El Nino/Southern Oscillation events. A moving window correlation between these two features revealed marked interannual and multi-decadal variability with the correlation coefficient varying between ?0.8 and +0.2. This suggests that current observations showing a decline in this correlation are due to natural climatic variability. A scatter diagram of the anomalies of the Indian summer monsoon rainfall and NINO 3.4 surface temperature showed that in almost 40 % of the cases ENSO events were associated with rainfall anomalies opposite to those implied by the climatological correlation coefficient. Case studies and composites of global distributions of surface temperature and rainfall anomalies for El Nino (or La Nina) events highlight the opposite rainfall anomalies over India that can result from very similar ENSO surface temperature anomalies. Composite differences are used to demonstrate the unique sensitivity of Indian summer monsoon rainfall anomalies to ENSO events. The problem of predicting such anomalies is discussed in relation to the fact that time series of the monsoon rainfall, both observed and simulated, consist of white noise. Based on the scatter diagram it is concluded that in about 60 % of the cases seasonal or annual prediction of monsoon rainfall based on individual ENSO events will result in the correct outcome. Unfortunately, there is no way, a priori, of determining for a given ENSO event whether the correct or a rogue prediction will result. Analysis of the present model’s results suggest that this is an almost world-wide problem for seasonal predictions of rainfall.     

Performance characteristics of a new electronic snow water equivalent sensor in different climates

The US Army ERDC CRREL and the US Department of Agriculture Natural Resources Conservation Service developed a square electronic snow water equivalent (e‐SWE) sensor as an alternative to using fluid‐filled snow pillows to measure SWE. The sensors consist of a centre panel to measure SWE and eight outer panels to buffer edge stress concentrations. Seven 3 m square e‐SWE sensors were installed in five different climate zones. During the 2011–2012 winter, 1.8 and 1.2 m square e‐SWE sensors were installed and operated in Oregon. With the exception of New York State and Newfoundland, the e‐SWE sensors accurately measured SWE, with R² values between the sensor and manual SWE measurements of between 0.86 and 0.98. The e‐SWE sensor at Hogg Pass, Oregon, accurately measured SWE during the past 8 years of operations. In the thin, icy snow of New York during midwinter 2008–2009, the e‐SWE sensors overmeasured SWE because of edge stress concentrations associated with strong icy layers and a shallow snow cover. The New York e‐SWE sensors' measurement accuracy improved in spring 2009 and further improved during the 2011–2012 winter with operating experience. At Santiam Junction, measured SWE from the 1.8 and 1.2 m square e‐SWE sensors agreed well with the snow pillow, 3 m square e‐SWE sensor, and manual SWE measurements until February 2013, when dust and gravel blew onto the testing area resulting in anomalous measurements. © 2014 The Authors. Hydrological Processes published by John Wiley & Sons Ltd.     

Field Test of a Hybrid Finite‐Difference and Analytic Element Regional Model

Regional finite‐difference models often have cell sizes that are too large to sufficiently model well‐stream interactions. Here, a steady‐state hybrid model is applied whereby the upper layer or layers of a coarse MODFLOW model are replaced by the analytic element model GFLOW, which represents surface waters and wells as line and point sinks. The two models are coupled by transferring cell‐by‐cell leakage obtained from the original MODFLOW model to the bottom of the GFLOW model. A real‐world test of the hybrid model approach is applied on a subdomain of an existing model of the Lake Michigan Basin. The original (coarse) MODFLOW model consists of six layers, the top four of which are aggregated into GFLOW as a single layer, while the bottom two layers remain part of MODFLOW in the hybrid model. The hybrid model and a refined “benchmark” MODFLOW model simulate similar baseflows. The hybrid and benchmark models also simulate similar baseflow reductions due to nearby pumping when the well is located within the layers represented by GFLOW. However, the benchmark model requires refinement of the model grid in the local area of interest, while the hybrid approach uses a gridless top layer and is thus unaffected by grid discretization errors. The hybrid approach is well suited to facilitate cost‐effective retrofitting of existing coarse grid MODFLOW models commonly used for regional studies because it leverages the strengths of both finite‐difference and analytic element methods for predictions in mildly heterogeneous systems that can be simulated with steady‐state conditions.     

Scale-dependent hydraulic conductivity in anisotropic media from dimensional cross-over

A cross-over from 1D conduction to 3D conduction with increasing scale is shown to account for the kind of scale-dependent hydraulic conductivity sometimes observed in anisotropic systems. The cross-over is investigated in the context of the application of continuum percolation theory to a random fractal model. The dimensional cross-over is defined in terms of a comparison between the correlation length from percolation theory and the system dimensions.

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Résumé Le passage d’une conductivité 1D à une conductivité 3D, avec une échelle d’étude croissante, est étudié de manière à supputer les dépendances de la conducticité hydraulique aux échelles, parfois observées dans les systèmes anisotropiques. Ce passage est investigué dans le contexte d’une application de la théorie de la percolation continue à un modèle fractal probabiliste. Le passage dimensionnel est définit en terme de comparaison entre la longueur de corrélation issue de la théorie de la percolation, et les dimensions du système.

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Resumen Se muestra un cruce de conducción en 1D a conducción 3D con escala creciente para explicar el tipo de conductividad hidráulica dependiente de escala que se observa algunas veces en sistemas anisotrópicos. Se investiga el cruce en el contexto de la aplicación de la teoría de percolación continua a un modelo fractal aleatorio. El cruce dimensional se define en términos de una comparación entre la longitud de correlación de la teoría de percolación y las dimensiones del sistema.

     

Volatile C1-C7 organic compounds in surface sediments from Walvis Bay

C₁-C₇ volatile organic compounds were analyzed in three gravity cores taken from Walvis Bay shelf. The compounds detected included alkanes (methane, ethane, propane, i- and n-butane, and i- and n-pentane, and heptane), alkenes (2-methyl-2-butene, dimethylcyclopentenes, cyclohexene), oxygen containing compounds (2- and 3-methylfuran, 2,5-dimethylfuran, 2- and 3-methylbutanal and 3-pentanone), sulfur compounds (dimethylsulfide, thiophene, 2- and 3-methylthiophene) and aromatic compounds (benzene and toluene). In situ biological and low temperature chemical (less than 15°C) formation processes are proposed, possibly from marine terpene precursors. Subsequent to this work, these compounds were found to be widely distributed in surface gravity cores from other areas. Many of these compounds do not survive deeper burial. Furans, ketocompounds, and alkenes are generally not found in more than trace quantities in deeper (?10m subbottom) DSDP cores we have examined from other areas.     

Assessment of NMR Logging for Estimating Hydraulic Conductivity in Glacial Aquifers

Glacial aquifers are an important source of groundwater in the United States and require accurate characterization to make informed management decisions. One parameter that is crucial for understanding the movement of groundwater is hydraulic conductivity, K. Nuclear magnetic resonance (NMR) logging measures the NMR response associated with the water in geological materials. By utilizing an external magnetic field to manipulate the nuclear spins associated with ¹H, the time-varying decay of the nuclear magnetization is measured. This logging method could provide an effective way to estimate K at submeter vertical resolution, but the models that relate NMR measurements to K require calibration. At two field sites in a glacial aquifer in central Wisconsin, we collected a total of four NMR logs and obtained measurements of K in their immediate vicinity with a direct-push permeameter (DPP). Using a bootstrap algorithm to calibrate the Schlumberger-Doll Research (SDR) NMR-K model, we estimated K to within a factor of 5 of the DPP measurements. The lowest levels of accuracy occurred in the lower-K (K < 10⁻⁴ m/s) intervals. We also evaluated the applicability of prior SDR model calibrations. We found the NMR calibration parameters varied with K, suggesting the SDR model does not incorporate all the properties of the pore space that control K. Thus, the expected range of K in an aquifer may need to be considered during calibration of NMR-K models. This study is the first step toward establishing NMR logging as an effective method for estimating K in glacial aquifers.     

Evaluating a new landform evolution model: A case study using a proposed mine rehabilitation landform

Landform evolution models are powerful tools for determining long-term erosional stability and denudation rates spanning geological timescales. SIBERIA, CAESAR and CHILD are examples of these model. The newly developed State Space Soil Production and Assessment Model (SSSPAM) coupled soilscape-landform evolution model has the ability to assess overall erosion rates of catchment scale landforms either using short-term precipitation events, variable precipitation or time-averaged precipitation (annual average). In addition, SSSPAM has the capability of developing the subsurface soil profile through weathering and armouring. In SSSPAM, physical processes of pedogenesis such as erosion and armouring, diffusion, sediment deposition and weathering are modelled using a state space matrix approach. In this article we simulate the short-term evolution (100 years) of a proposed post-mining landform using both SIBERIA and SSSPAM and compare the erosion and sediment output results. For the short-term simulations SSSPAM's armouring capability was disabled. The models were then used to simulate the evolution of the catchment for 10,000 years. Results demonstrate that the short-term SSSPAM simulation results compare well with the results from the established landform evolution model SIBERIA. The long-term armouring disabled SSSPAM simulations produces simulated erosion rates comparable with SIBERIA simulations both of which are similar to upper limit of field measured denudation rates. The SSSPAM simulation using armouring demonstrated that armouring reduced the erosion rate of the catchment by a factor of 4 which is comparable with the lower limit of field measured denudation rates. This observation emphasizes the importance of armouring in long-term evolution of landforms. Soil profile cross-sections developed from the same results show that SSSPAM can also reproduce subsurface soil evolution and stratification and spatial variability of soil profile characteristics typically observed in the field.