bluuebunny/crossref_metadata_2025 huggingface dataset:
Multi-level Parallelization of Ensemble Kalman Filter for Reservoir History Matching
Authors: Tavakoli Reza , Pencheva Gergina , Wheeler Mary F.
Published: February 2011

The ensemble Kalman filter (EnKF) has been successfully implemented to assimilate data in reservoir history matching problems. In the EnKF method, a suite of reservoir models (set of ensemble members) runs independently forward in time (forecast step), and is continuously updated as new data becomes available (analysis step). In this paper, an efficient implementation of the EnKF is presented in which three-level parallelization is employed.

The first level of parallelization is during the forecast step, where each ensemble member runs on a separate processor. This is very efficient for a large number of ensemble members, but without additional parallelization, the memory of a single processor constrains the size of the reservoir simulation. Therefore, a second level of parallelization which uses a parallel reservoir simulator for each realization is implemented. The analysis step requires collecting a state vector from each ensemble member. If this data is collected on a single processor, this poses an additional limitation on the size of the EnKF problem in terms of both memory and computation time. Therefore, we propose an algorithm in which a third level of parallelization is achieved for the analysis step. The main computational gain of parallelization of the analysis step comes from the fact that the matrix-vector multiplications can be parallelized efficiently.

The parallel EnKF algorithm is applied to a set of reservoir history matching problems. The effect of ensemble sizes on the history matching results is investigated. We present computational results that show the efficiency is greatly enhanced by moving from a serial to a parallel implementation of the EnKF. The initial testing of parallel EnKF has been done on the massively parallel machines Ranger and Lonestar, at the Texas Advanced Computing Center (TACC), and the cluster Bevo2, at the Institute for Computational Engineering and Sciences (ICES) at the University of Texas at Austin.
Uncertainty Quantification in History Matching of Channelized Reservoirs using Markov Chain Level Set Approaches
Authors: Xie Jiang , Efendiev Yalchin , Datta-Gupta Akhil
Published: February 2011

We present a method for history matching and uncertainty quantification for channelized reservoir models using Level Set Method and Markov Chain Monte Carlo. Our objective is to efficiently sample realizations of the channelized permeability fields conditioned to the production data and facies observation at the wells. In our approach, the channel field boundary is first described by a level set function, e.g., a signed distance function or any other indicator function. By solving the level set equation (motion in a prescribed direction), we are able to gradually move the channel boundaries and evolve the channelized reservoir properties. Our approach allows representing facies via a parameterization of the velocity field that deforms the interface. Thus facies can be parameterized in the space of smooth velocity fields. The dimension reduction can be achieved for covariance-based velocity fields by re-parameterizing with SVD techniques.

After parameterization, Markov Chain Monte Carlo method is utilized to perturb the coefficients of principal components of velocity field to update channel reservoir model matching production history. One advantage of this approach is that it is easy to condition the channel model to the facies observations at well locations by constraining the random velocity field to zero at well locations. To speed up the computation and improve the acceptance rate of the MCMC algorithm, we employ two stage methods where coarse-scale simulations are used to screen out the undesired proposals. The MCMC algorithms naturally provide multiple realizations of the permeability field conditioned to well and production data and thus, allow for uncertainty assessment in the forecasting. We demonstrate the effectiveness of the level set MCMC algorithm using both 2D and 3D examples involving waterflood history matching.
A Negative-Flash Tie-Simplex Approach for Multiphase Reservoir Simulation
Authors: Iranshahr Alireza , Voskov Denis , Tchelepi Hamdi A.
Published: February 2011

Enhanced Oil Recovery (EOR) processes usually involve complex phase behaviors between the injected fluid (e.g., steam, hydrocarbon, CO2, sour) and the in-situ rock-fluid system. Several fundamental questions remain regarding equation-of-state computations for mixtures than can form three, or more, phases at equilibrium. In addition, numerical and computational issues related to proper coupling of the thermodynamic phase-behavior with multi-component transport must be resolved in order to model the behaviors of large-scale EOR processes accurately and efficiently.

We describe a general negative-flash method for multi-component, thermal systems that can form three, or more, fluid phases. We prove that the new method is convergent to the unique solution. This negative-flash approach is integrated with reservoir flow simulation based on adaptive tie-simplex parameterization of the compositional space. We prove that the tie-simplexes change continuously as a function of pressure, temperature, and composition. The continuity of the parameterized space allows for interpolation in pressure and temperature using a limited number of tie-simplexes. This extended negative-flash approach accounts rigorously for tie-simplex degeneration across phase boundaries.

We study the behaviors of thermal-compositional reservoir displacement processes across a wide range of fluid mixtures, pressures, and temperatures. The focus is on the complex behaviors of the tie-triangles and tie-lines associated with three-phase, steam-injection problems in heterogeneous formations. The algorithms that capture the complex combinations of the appearance and disappearance of multiple phases are described in detail. The accuracy and computational efficiency of this negative-flash, tie-simplex based approach is demonstrated for several challenging compositional (CO2, sour-gas) and thermal-compositional (steam) models. The nonlinear behaviors are analyzed in terms of the particular displacement process, miscible/immiscible dynamics, number of components, and sensitivity to time step size.
An Adaptive Newton's Method for Reservoir Simulation
Authors: Lu Pengbo , Beckner Bret
Published: February 2011

In trying to speed up reservoir simulators, we have given significant attention to improving runtime performance and efficiency on various components of the simulator, i.e. linear solvers, flash calculations, time-step controls, with further performance gain from parallelization. This paper describes an enhanced version of Newton's method, the adaptive Newton's method, that reduces time spent in nonlinear loops of a reservoir simulator.

It is commonly observed that clusters of reservoir simulation cells are responsible for the convergence behavior within a Newton loop at a given timestep. In our investigations on field cases, the number of cells that had not converged, as defined by the magnitude of the residual and solution changes, would decease very rapidly as the Newton iteration progresses. In most cases, the number of unconverged cells was significantly less than 2% after just one or two Newton iterations.

An adaptive nonlinear method was developed to use the residual of the previous Newton iteration as a guide to select a subset of cells for subsequent Newton iterations. The subset of cells includes all the unconverged cells plus a collection of bordering cells. Using this adaptation, the matrix solved at Newton iterations after the first one is very much reduced, resulting in significant speedup. Several variations in the adaption were investigated, varying the size of the border, varying the timing of the application of adaption and including a residual smoothing step.

This adaptive Newton's method was applied to multiple field cases, with the numbers of simulation cells ranging from 14,000 to 900,000 cells. The use of the residual smoothing operator prevented material balance errors with minimal impact on the Newton convergence behavior and timestep sizes. Run times were reduced by 30~70 % in these field test cases with no negative effects on results.
A Simplified Model for Simulations of Alkaline-Surfactant-Polymer Floods
Authors: Delshad Mojdeh , Han Choongyong , Veedu Faiz Koyassan , Pope Gary A.
Published: February 2011

A common method of enhanced oil recovery is alkaline-surfactant-polymer (ASP) flooding where a solution of alkali, surfactant, and polymer is injected followed by a polymer drive. Many crude oils contain naphthenic acids that react with the alkali to form soap in-situ. With the proper selection of an injected surfactant that mixes with the soap in-situ, a sufficiently low interfacial tension can be achieved to mobilize the residual oil. However, ASP flooding is complex since it involves chemical reactions that depend on the oil composition, water composition, rock mineralogy, temperature, pH, etc.

Mechanistic simulations of ASP flooding typically involve a large number of reactions to calculate the consumption of alkali due to ion exchange reactions with the clay and micelles as well as other reactions with the minerals and brines. This approach is computationally intensive. After a full mechanistic model of ASP flooding was developed and validated, a simplified ASP model was implemented in a 3D chemical flooding reservoir simulator. In the simplified ASP model, the amount of soap is calculated using the total acid number of the crude oil. A phase behavior mixing rule model was developed to calculate the optimum salinity and solubilization ratio of the soap and surfactant mixtures. Other key mechanisms modeled are alkali consumption and surfactant adsorption as a function of alkali concentration.

Several ASP corefloods were successfully modeled using the simplified ASP model. Based on these results, 3D simulations of an ASP field pilot were performed. In this particular case, the results were comparable to those obtained from ASP flooding simulations using a more complete set of geochemical reactions. The simplified ASP flooding model is a more practical and convenient way to simulate field applications of ASP flooding for such cases.
Numerical Simulation of Fractured Carbonate Reservoirs with the M_1 Bimodal Pore System
Authors: Fung Larry S. , Middya Usuf , Dogru Ali H.
Published: February 2011

Recent petrophysical analyses of Arab D limestone identify the M_1 bimodal pore system as the most common and important member of a new set of petrophysical rock types, which uses a new pore system classification based on extensive studies of a large and comprehensive collection of mercury injection capillary pressure (MICP) data set from Ghawar Arab D. The role played by the pore system parameters describing the macropores (M) and the micropores (Type 1) within the M_1 system indicates the significant contrast in flow parameters and wettability which may have strong implication on the microscopic displacement efficiency of carbonate reservoirs dominated by these multimodal pore systems. We propose to study this system as a system consisting of multiple interacting continua. Numerically, such a system is a generalization of the classical dual porosity dual permeability system into the multiple porosity multiple permeability framework. Since the micropores have permeability which can be four orders of magnitude smaller than the macropores, it is reasonable to neglect the inter-grid flow for the microspore. However, the micropores and macropores connectivity is at the rock fabric and is expected to be substantial. Additionally, the reservoirs are also known to include fractures and super-K regions. Thus, the parallel reservoir simulator is for a general system of multiple interacting continua. The parallel numerical methods will be discussed. We performed numerical studies to examine the sensitivity of a bimodal pore system in both fractured and non-fractured scenarios and contrast these against the traditional simulation of the single-mode pore system. Simulation results and discussions of the effect of flow parameters and wettability contrasts of the bimodal system in both the non-fractured and fractured area of the reservoir will be presented.
Manure Application Technology in Reduced Tillage and Forage Systems: A Review
Authors: Maguire Rory O. , Kleinman Peter J. A. , Dell Curtis J. , Beegle Doug B. , Brandt Robin C. , McGrath Josh M. , Ketterings Quirine M.
Published: February 2011

Managing manure in reduced tillage and forage systems presents challenges, as incorporation by tillage is not compatible. Surface‐applied manure that is not quickly incorporated into soil provides inefficient delivery of manure nutrients to crops due to environmental losses through ammonia (NH3) volatilization and nutrient losses in runoff, and serves as a major source of nuisance odors. An array of technologies now exist to facilitate the incorporation of liquid manures into soil with restricted or minor soil disturbance, some of which are new: shallow disk injection; chisel injection; aeration infiltration; pressure injection. Surface banding of manure in forages decreases NH3 emissions relative to surface broadcasting, as the canopy can decrease wind speed over the manure, but greater reductions can be achieved with manure injection. Soil aeration is intended to hasten manure infiltration, but its benefits are not consistent and may be related to factors such as soil drainage characteristics. Work remains to be done on refining its method of use and timing relative to manure application, which may improve its effectiveness. Placing manure under the soil surface by injection offers much promise to improve N use efficiency through less NH3 volatilization, reduced odors and decreased nutrient losses in runoff, relative to surface application. We identified significant gaps in our knowledge as many of these technologies are relatively new, and this should help target future research efforts including environmental, agronomic, and economic assessments.
Field Olfactometry Assessment of Dairy Manure Land Application Methods
Authors: Brandt R. C. , Elliott H. A. , Adviento‐Borbe M. A. A. , Wheeler E. F. , Kleinman P. J. A. , Beegle D. B.
Published: February 2011

Surface application of manure in reduced tillage systems generates nuisance odors, but their management is hindered by a lack of standardized field quantification methods. An investigation was undertaken to evaluate odor emissions associated with various technologies that incorporate manure with minimal soil disturbance. Dairy manure slurry was applied by five methods in a 3.5‐m swath to grassland in 61‐m‐inside‐diameter rings. Nasal Ranger Field Olfactometer (NRO) instruments were used to collect dilutions‐to‐threshold (D/T) observations from the center of each ring using a panel of four odor assessors taking four readings each over a 10‐min period. The Best Estimate Threshold D/T (BET10) was calculated for each application method and an untreated control based on preapplication and <1 h, 2 to 4 h, and ∼24 h after spreading. Whole‐air samples were simultaneously collected for laboratory dynamic olfactometer evaluation using the triangular forced‐choice (TFC) method. The BET10 of NRO data composited for all measurement times showed D/T decreased in the following order (α = 0.05): surface broadcast > aeration infiltration > surface + chisel incorporation > direct ground injection ≈ shallow disk injection > control, which closely followed laboratory TFC odor panel results (r = 0.83). At 24 h, odor reduction benefits relative to broadcasting persisted for all methods except aeration infiltration, and odors associated with direct ground injection were not different from the untreated control. Shallow disk injection provided substantial odor reduction with familiar toolbar equipment that is well adapted to regional soil conditions and conservation tillage operations.
Phosphorus Runoff Losses from Subsurface‐Applied Poultry Litter on Coastal Plain Soils
Authors: Kibet Leonard C. , Allen Arthur L. , Kleinman Peter J. A. , Feyereisen Gary W. , Church Clinton , Saporito Lou S. , Way Thomas R.
Published: February 2011

The application of poultry litter to soils is a water quality concern on the Delmarva Peninsula, as runoff contributes P to the eutrophic Chesapeake Bay. This study compared a new subsurface applicator for poultry litter with conventional surface application and tillage incorporation of litter on a Coastal Plain soil under no‐till management. Monolith lysimeters (61 cm by 61 cm by 61 cm) were collected immediately after litter application and subjected to rainfall simulation (61 mm h−1, 1 h) 15 and 42 d later. In the first rainfall event, subsurface application of litter significantly lowered total P losses in runoff (1.90 kg ha−1) compared with surface application (4.78 kg ha−1). Losses of P with subsurface application were not significantly different from disked litter or an unamended control. By the second event, total P losses did not differ significantly between surface and subsurface litter treatments but were at least twofold greater than losses from the disked and control treatments. A rising water table in the second event likely mobilized dissolved forms of P in subsurface‐applied litter to the soil surface, enriching runoff water with P. Across both events, subsurface application of litter did not significantly decrease cumulative losses of P relative to surface‐applied litter, whereas disking the litter into the soil did. Results confirm the short‐term reduction of runoff P losses with subsurface litter application observed elsewhere but highlight the modifying effect of soil hydrology on this technology's ability to minimize P loss in runoff.
Modeling Concentration‐Dependent Sorption–Desorption Hysteresis of Atrazine in a Sandy Loam Soil
Authors: Anagu Ihuaku , Ingwersen Joachim , Drori Yaron , Chefetz Benny , Streck Thilo
Published: February 2011

Nonequilibrium sorption plays an active role in the transport of organic contaminants in soil. We applied a two‐stage, one‐rate model (2S1R) and a new, nonlinear variant (2S1RN) of this model to examine the effects of wastewater irrigation on the sorption kinetics of atrazine (2‐chloro‐4‐ethylamino‐6‐isopropylamino‐1,3,5‐triazine) in soil. The models were applied to previously published sorption–desorption data sets, which showed pronounced deviations between sorption curves and desorption curves (sorption–desorption hysteresis). Moreover, the slopes of the desorption curves decreased with decreasing concentration. Different treatments had been used, and two experimental time steps (2 and 14 d) were used. Treatments considered were lipid removal, fulvic and humic acid removal, and untreated soil. The 2S1R model was unable to reproduce the observed type of hysteresis, but the 2S1RN model, which assumes that the sorption–desorption process follows a power function relationship, was able to reproduce the observed type of hysteresis. Visually, applying the new model improved the model fits in all test cases. Statistically, as tested by an extra sum of squares analysis, the new model performed significantly better in 50% of all test cases. According to an example simulation, the choice of the sorption model has a considerable impact on the prediction of atrazine transport in soil.
An Investigation of the Kinetic Processes Influencing Mercury Emissions from Sand and Soil Samples of Varying Thickness
Authors: Quinones Jason L. , Carpi Anthony
Published: February 2011

Mercury flux from HgCl2–treated sand and untreated soil samples of varying thickness (0.5–15 mm) were measured in dark and light under a Teflon dynamic flux chamber. Mean emissions over a 5.5‐d sampling period showed an increase with depth for sand samples between 0.5 and 2 mm, but increasing depth above 2 mm had no effect. First‐order kinetic models showed strong goodness of fit to the data and explained a high degree of variability in the emissions profile of all sand samples (R2 = 0.70–0.98). Soil samples showed an initial emissions peak that was not correlated with depth, suggesting a very shallow process at work. However, longer‐term “baseline” emissions, measured as mean emissions between Days 4.5 and 5.5, did show a relationship with depth. First‐order kinetic models showed good fit for soil samples up to 4 mm thick (R2 = 0.66–0.91); however, thicker samples did not show a consistent fit to first‐ or second‐order kinetic models (1° R2 = 0.00–0.46; 2° R2 = 0.00–0.54). The data suggest that mercury emissions from soil samples may follow a multicomponent model for which more than one component is affected by incident radiation.
Denitrification in Alluvial Wetlands in an Urban Landscape
Authors: Harrison Melanie D. , Groffman Peter M. , Mayer Paul M. , Kaushal Sujay S. , Newcomer Tamara A.
Published: February 2011

Riparian wetlands have been shown to be effective “sinks” for nitrate N (NO3−), minimizing the downstream export of N to streams and coastal water bodies. However, the vast majority of riparian denitrification research has been in agricultural and forested watersheds, with relatively little work on riparian wetland function in urban watersheds. We investigated the variation and magnitude of denitrification in three constructed and two relict oxbow urban wetlands, and in two forested reference wetlands in the Baltimore metropolitan area. Denitrification rates in wetland sediments were measured with a 15N‐enriched NO3− “push–pull” groundwater tracer method during the summer and winter of 2008. Mean denitrification rates did not differ among the wetland types and ranged from 147 ± 29 μg N kg soil−1 d−1 in constructed stormwater wetlands to 100 ± 11 μg N kg soil−1 d−1 in relict oxbows to 106 ± 32 μg N kg soil−1 d−1 in forested reference wetlands. High denitrification rates were observed in both summer and winter, suggesting that these wetlands are sinks for NO3− year round. Comparison of denitrification rates with NO3− standing stocks in the wetland water column and stream NO3− loads indicated that mass removal of NO3− in urban wetland sediments by denitrification could be substantial. Our results suggest that urban wetlands have the potential to reduce NO3− in urban landscapes and should be considered as a means to manage N in urban watersheds.
Nitrification and Denitrification Gene Abundances in Swine Wastewater Anaerobic Lagoons
Authors: Ducey Thomas F. , Shriner Anthony D. , Hunt Patrick G.
Published: February 2011

Although anaerobic lagoons are used globally for livestock waste treatment, their detailed microbial cycling of N is only beginning to become understood. Within this cycling, nitrification can be performed by organisms that produce the enzyme ammonia monooxygenase. For denitrification, the reduction of nitrite to nitric oxide can be catalyzed by two forms of nitrite reductases, and N2O can be reduced by nitrous oxide reductase encoded by the gene nosZ. The objectives of this investigation were to (i) quantify the abundance of the amoA, nirK, nirS, and nosZ genes; (ii) evaluate the influence of environmental conditions on their abundances; and (iii) evaluate their abundance relative to denitrification enzyme activity (DEA). Samples were analyzed via real‐time quantitative polymerase chain reaction and collected from eight typical, commercial anaerobic, swine wastewater lagoons located in the Carolinas. The four genes assayed in this study were present in all eight lagoons. Their abundances relative to total bacterial populations were 0.04% (amoA), 1.33% (nirS), 5.29% (nirK), and 0.27% (nosZ). When compared with lagoon chemical characteristics, amoA and nirK correlated with several measured variables. Neither nirS nor nosZ correlated with any measured environmental variables. Although no gene measured in this study correlated with actual or potential DEA, nosZ copy numbers did correlate with the disparity between actual and potential DEA. Phylogenetic analysis of nosZ did not reveal any correlations to DEA rates. As with other investigations, analyses of these genes provide useful insight while revealing the underlying greater complexity of N cycling within swine waste lagoons.
Determining the Porosity and Saturated Hydraulic Conductivity of Binary Mixtures
Authors: Zhang Z. Fred , Ward Andy L. , Keller Janson M.
Published: February 2011

Gravel and coarse sand make up significant portions of some environmentally important sediments, but the hydraulic properties of the sediments are typically obtained in the laboratory using only the fine fraction (e.g., <2 mm or 4.75 mm). Researchers have found that the gravel content has a significant impact on the hydraulic properties of bulk soils. Therefore, laboratory experiments were conducted to measure the porosity and the saturated hydraulic conductivity of binary mixtures with different fractions of coarse and fine components. We proposed a mixing‐coefficient model to estimate the porosity and a power‐averaging method to determine the effective grain diameter of sediments. These were used to predict the saturated hydraulic conductivity of binary mixtures. The proposed methods could describe the porosity and saturated hydraulic conductivity of the binary mixtures for a range of gravel contents, and they were successfully applied to two data sets in the literature.
Temporal Downscaling of Soil Carbon Dioxide Efflux Measurements Based on Time‐Stable Spatial Patterns
Authors: Graf Alexander , Prolingheuer Nils , Schickling Anke , Schmidt Marius , Schneider Karl , Schüttemeyer Dirk , Herbst Michael , Huisman Johan A. , Weihermüller Lutz , Scharnagl Benedikt , Steenpass Christian , Harms Rainer , Vereecken Harry
Published: February 2011

Soil CO2 efflux at a field site is often computed as the average of successive chamber measurements at several points to overcome the effects of spatial variability and microclimatic disturbances. As a consequence, the resulting data set has a coarser resolution in space (one average per site) and time than the raw data set. The deviations between raw measurements and the field average may provide additional insights, however, if they can be decomposed into a time‐stable part, characterizing the spatial pattern of emission strengths, and a dynamic part, characterizing rapid changes in soil CO2 efflux. We evaluated data from several measurement campaigns in an agricultural landscape. First, we determined the persistence of spatial CO2 efflux patterns and found that ≥50% of spatial variance was stable for at least 1 d in all examined crop and field types. For fields where vegetation and gradients in soil properties determined the spatial variation in CO2 efflux, some correlation was still found after 10 d. In a next step, we removed the time‐stable patterns from the raw time series. The resulting estimate of instantaneous area‐average soil respiration closely resembled the conventional spatiotemporal field average on days without rapid changes in meteorologic conditions. On days with fluctuations of radiation and temperature, in contrast, soil respiration reacted on a time scale from instantaneous to about 1 h. Based on a discussion of potential mechanisms underlying these reactions for a wheat (Triticum aestivum L.) and a sugarbeet (Beta vulgaris L. ssp. vulgaris) stand, we suggest that the proposed downscaling methodology, in combination with existing decomposition techniques, may help to examine the short‐term dependence of heterotrophic and root respiration on radiation, temperature, and rain.
Determining the Effective Hydraulic Properties of a Highly Heterogeneous Soil Horizon
Authors: Samouëlian A. , Cousin I. , Dagès C. , Frison A. , Richard G.
Published: February 2011

In this study, we have attempted to determine the effective hydraulic properties of a highly heterogeneous soil horizon composed of two elementary pedological volumes (EPVs). Our upscaling approach was guided by the “scaleway” approach, in which the properties of a complex system can be estimated by multiple discrete upscaling steps. This approach was tested on a data set from laboratory measurements of hydraulic conductivity at the EPV scale, while an explicit three‐dimensional soil structure was considered at the horizon scale. We then formulated a decision tree to guide the choice of the appropriate upscaling method to determine the effective hydraulic conductivity at the horizon scale. In the case of low contrast between hydraulic conductivities at the EPV scale, the effective hydraulic conductivity at the horizon scale can be achieved by calculating the Wiener bounds, which requires only the proportion of the different EPVs. In the case of high contrast between hydraulic conductivities at the EPV scale, we recommend either calculating the Cardwell and Parson bounds, or performing a direct three‐dimensional numerical simulation to solve Richards' equation, which requires an explicit representation of the three‐dimensional structure of the soil horizon. The Cardwell and Parsons bounds remains a good and easily available approximation. Otherwise, more accurate estimation can be obtained by numerical simulation, although this is time consuming. A decision map is proposed to help choose the best method to estimate the effective hydraulic conductivity.
Simulation of Daily Nitrous Oxide Emissions from Managed Peat Soils
Authors: Stolk P. C. , Hendriks R. F. A. , Jacobs C. M. J. , Duyzer J. , Moors E. J. , van Groenigen J. W. , Kroon P. S. , Schrier-Uijl A. P. , Veenendaal E. M. , Kabat P.
Published: February 2011

Simulation of emissions of the greenhouse gas N2O from agricultural land is still a challenge. This is mainly due to its high temporal variability, with low background emissions and a few transient peaks. In this study, a first attempt was made to simulate observations of N2O fluxes with a daily time step from managed peat soils. We used a new N2O module added to the extensively tested hydrological–biogeochemical model combination SWAP‐ANIMO, hypothesizing that accurate simulation of the controlling factors would imply accurate simulation of the dynamics of the N2O emissions as well. We used daily N2O emission data from three sites in the Netherlands, with complementary data on soil moisture, mineral N content, and soil N2O concentration. Simulation of soil moisture, mineral N, and N2O concentration was reasonable to good. Still, simulation of the daily N2O emissions was poor, with model efficiencies <0, mainly due to overestimation of N2O emission from denitrification in the topsoil. We expect that the model overestimated diffusion of N2O from the topsoil to the atmosphere, thereby underestimating further reductions of N2O to N2 This was probably linked to the complex peat pore geometry. We concluded that the description of the N2O processes in our model was insufficient to accurately simulate daily N2O emissions from peat soils, even when the main controlling factors are accurately simulated. Improvement is expected from incorporation of the effects of (peat) pore geometry on soil moisture and consequently on N2O production, reduction, storage, and transport.
Coupled Vegetation and Soil Moisture Dynamics Modeling in Heterogeneous and Sloping Terrains
Authors: Cervarolo G. , Mendicino G. , Senatore A.
Published: February 2011

Two vegetation dynamic models (VDMs) were coupled to a soil–vegetation–atmosphere transfer scheme aimed at simulating water, heat, and CO2 fluxes and to a three‐dimensional unsaturated flow and heat diffusion model allowing the study of heterogeneous soils and vegetation. The VDMs differ in reproducing gross photosynthesis. One was adapted from a daily model, while the other is a more complex model, needing the continuous monitoring of CO2 concentration and a larger number of parameters, although it is useful for assessing feedback due to an increase in CO2 concentration. The two coupled models were validated on a half‐hour time step through leaf area index (LAI), ground energy, and water flux measurements performed during the summer of 2007 and 2009 in an alfalfa (Medicago sativa L.) field in the Mediterranean (southern Italy) and during the spring of 2001 in a predominantly C3 grass covered field (California). Furthermore, the models were used at the field scale in numerical experiments for assessing the effects of model dimensionality on evapotranspiration, CO2 flux, and LAI in the presence of flat heterogeneous or sloping homogeneous terrains using both the fully three‐dimensional soil water flow model and a simpler model allowing only vertical flow. For the flat terrain experiment, one‐dimensional modeling generally provided significant differences in the simulated quantities with respect to the three‐dimensional model, even though in some cases similar results were found. For the sloping terrain, one‐dimensional modeling proved quite unsuitable for analyzing slope effects, while three‐dimensional modeling allowed detailed description of different degrees of slope interactions between soil moisture dynamics and surface fluxes for different slope angles.
The Effect of Contact Angle on Saturation Overshoot
Authors: Aminzadeh Behdad , DiCarlo David A. , Wallach Rony
Published: February 2011

For certain porous media and initial conditions, constant flux infiltrations show a saturation profile that exhibits overshoot. This overshoot, which is the cause of gravity‐driven fingering, cannot be described by standard models of unsaturated flow, and it is likely controlled by the exact nature of the pore filling at the initial front. These frontal dynamics have recently been studied as a function of infiltrating flux and infiltrating fluid and were present in our earlier paper. The overshoot behavior is found to disappear below a certain flux which has been named the overshoot flux. We found that, except for water, the overshoot flux qover is a linear function of surface tension σ divided by the viscosity μ, qover ∼ σ/μ. This is expected if the physics at the front that controls overshoot are the same physics that controls the capillary desaturation curve, but the overshoot flux for water did not fall on this curve. To resolve this discrepancy, we conducted additional experiments to test how wettability affects the saturation overshoot.
Soil Hydraulic Functions Determined from Measurements of Air Permeability, Capillary Modeling, and High‐Dimensional Parameter Estimation
Authors: Dane Jacob H. , Vrugt Jasper A. , Unsal Evren
Published: February 2011

Prediction of flow and transport through unsaturated porous media requires knowledge of the water retention and unsaturated hydraulic conductivity functions. In the past few decades many different laboratory procedures have been developed to estimate these hydraulic properties. Most of these procedures are time consuming and require significant human commitment. Furthermore, multiple measurement techniques are typically required to yield an accurate characterization of the retention and hydraulic conductivity function between full and residual saturation. We present a more efficient and robust approach to estimating the hydraulic properties of porous media. Our method derives an optimized pore‐size distribution from measurements of air permeability and using recent advances in capillary modeling and high‐dimensional parameter estimation. The section diameters of different parallel capillaries representing the pore structure of a porous medium are optimized with a multi‐algorithm optimization method by comparing measured and modeled air permeability values. The optimized pore model is subsequently used to predict the water retention and water permeability functions. The predicted soil hydraulic properties are shown to be in excellent agreement with experimentally determined data from an unconsolidated porous medium column. Our approach does not impose any functional form of the hydraulic properties and requires only measurements of air permeability.
Pore‐Scale Simulations to Determine the Applied Hydrodynamic Torque and Colloid Immobilization
Authors: Bradford Scott A. , Torkzaban Saeed , Wiegmann Andreas
Published: February 2011

Values of the applied hydrodynamic torque (Tapplied) and the resisting adhesive torque (Tadhesion) will determine whether a colloid will be immobilized (Tapplied ≤ Tadhesion) or roll (Tapplied > Tadhesion) on a solid water interface. Previous literature has demonstrated in 1–2 collector (grain) systems that the influence of Tapplied on colloid retention can be significant under unfavorable attachment conditions and that only a fraction of the solid surface may contribute to retention. However, many questions remain on how to obtain, analyze, and upscale information on the forces and torques that act on colloids near solid surfaces in porous media. To address some of these gaps in knowledge, high resolution pore‐scale water flow simulations were conducted for sphere packs (25 spheres) over a range of Darcy velocities, grain sizes and distributions, and porosities. The spatial variability of Tapplied was calculated from this information, and successfully described using a lognormal cumulative density function (CDF). Linear interpolation and scaling techniques were subsequently used to predict the lognormal CDF of Tapplied for various colloid sizes, grain sizes and distributions, and water velocities. The lognormal CDF of Tapplied was then evaluated at select values of Tadhesion (i.e, interaction energy) to quantify the fraction and locations on the solid surface that contributes to colloid retention (Sf), and the theoretical maximum solid phase concentration of retained colloids (Smax).
Preferential Flow Effects on Infiltration and Runoff in Grassland and Forest Soils
Authors: Alaoui A. , Caduff U. , Gerke H.H. , Weingartner R.
Published: February 2011

Due to the heterogeneity of soil hydraulic properties, there are many ways in which natural soils respond to rainfall, making upscaling of flow processes from plot to catchment scale difficult. The objectives of this study were to qualitatively characterize the flow pathways on forest and grassland hillslopes and to quantitatively define the relevant parameters controlling surface runoff generation by using infiltration and dye tracer experiments supplemented with measurements of the saturated hydraulic conductivity Ksat, the structural porosity nSP, and the pore‐size distribution PSD. While infiltration excess overland flow dominates in grassland, forest soil structure characterized by relatively high values of Ksat and nSP enhances the infiltrability of the soil and consequently prevents or at least reduces surface runoff. The dye patterns suggest that macropores are more efficient in forest than in grassland soil. The low efficiency of grassland soil macropores in transporting all water vertically downward can be explained by (i) the fine and dense few topsoil layers caused by the land use that limit water flux into the underlying macropores and (ii) their restricted number, their tortuosity, and the restricted interaction between macropores and the matrix below the topsoil layer. The larger root water uptake of forest soil as compared to grassland soil can be viewed as an additional factor enhancing its storage capacity and, consequently, may reduce the generation of surface runoff. It remains unclear, however, what effect the low interaction between macropores and soil matrix in the upper part of the subsoil has on surface runoff in grassland soil; this should be investigated in future studies.
Three‐Dimensional Electrical Resistivity Tomography to Monitor Root Zone Water Dynamics
Authors: Garré S. , Javaux M. , Vanderborght J. , Pagès L. , Vereecken H.
Published: February 2011

Knowledge of soil moisture dynamics and its spatial variability is essential to improve our understanding of root water uptake and soil moisture redistribution at the local scale and the field scale. We investigated the potential and limitations of electrical resistivity tomography (ERT) to measure three‐dimensional soil moisture changes and variability in a large, undisturbed, cropped soil column and examined the interactions between soil and root system. Our analysis sustained the value of ERT as a tool to monitor and quantify water contents and water content changes in the soil, as long as the root biomass does not influence the observed resistivity. This is shown using a global water mass balance and a local validation using time domain reflectometry (TDR) probes. The observed soil moisture variability was rather high compared to values reported in the literature for bare soil. The measured water depletion rate, being the result of combined effects of root water uptake and soil water redistribution, was compared with the evaporative demand and root length densities. We observed a gradual downward movement of the maximum water depletion rate combined with periods of redistribution when there was less transpiration. Finally, the maximum root length density was observed at −70 cm depth, pointing out that root architecture can strongly depend on soil characteristics and states.
Comparison of Hydrological Simulations of Climate Change Using Perturbation of Observations and Distribution‐Based Scaling
Authors: van Roosmalen Lieke , Sonnenborg Torben O. , Jensen Karsten H. , Christensen J.H.
Published: February 2011

Projected climate change effects on groundwater and stream discharges were investigated through simulations with a distributed, physically based, surface water–groundwater model. Input to the hydrological model includes precipitation, reference evapotranspiration, and temperature data of the HIRHAM4 regional climate model (RCM). The aim of this study was to determine whether the choice of bias‐correction method, applied to the RCM data, affected the projected hydrological changes. One method consisted of perturbation of observed data (POD) using climate change signals derived from the RCM output, while the other consisted of distribution‐based scaling (DBS) of the RCM output. Distribution‐based scaling resulted in RCM control period data closely approaching the observed climate data and thereby considerably improved the simulation of recharge and stream discharges. When comparing the simulations using both methods, only small differences between the projected changes in hydrological variables for the scenario period were found. Mean annual recharge increased by 15% for the DBS method and 12% for POD, and drain flow increased by 24 and 19%, respectively, while the increases in base flow were similar (7%). For both methods, daily stream discharges up to and including the median showed little change, while increases occurred for the higher quantile values. This study showed that the choice of bias‐correction method did not have a significant influence on the projected changes of mean hydrological responses in this catchment, although further analysis is necessary to determine whether extremes are affected. Furthermore, the characteristics of the hydrological system likely reduced the sensitivity of the projected changes to the choice of method.
A fast approach for multiobjective design of water distribution networks under demand uncertainty
Authors: Sun S. , Khu S.-T. , Kapelan Z. , Djordjević S.
Published: February 2011

Water distribution system (WDS) design has received much attention lately from the point of view of uncertainties. Designers are generally interested in the Pareto optimal cost-robustness trade off curve. This paper aims to find a solution to the multiobjective problem in a computationally time-efficient way in comparison to previous methods from the literature. A parameter θ, which is linked to the system robustness through a derived analytic formula, is introduced. The robustness of the WDS can be approximated by one single model simulation; consequently a large amount of computational time is saved compared to using a sampling-based technique. The application of the method to the New York tunnels problem demonstrates that, although the resulting design is conservative on cost, the proposed method is very computationally efficient. This is of importance when high computational cost is the major obstacle for some real-world problems.
Remote sensing and GIS application for river runoff and water quality modeling in a hilly forested watershed of Japan
Authors: Shivakoti Binaya R. , Fujii Shigeo , Tanaka Shuhei , Ihara Hirotaka , Moriya Masashi
Published: February 2011

The main objective of this study is to present a simplified distributed modeling framework based on the storage balance concept of a Tank Model and by utilizing inputs from remote sensing data and GIS analysis. The modeling process is simplified by (1) minimizing the number of parameters with unknown values and 2) retaining important characteristics (such as land cover, topography, geology) of the study area in order to account for spatial variability. Remote sensing is used as a main source of distributed data and the GIS environment is used to integrate spatial information into the model. Remote sensing is utilized mainly to derive land cover, leaf area index (Lai) and transpiration coefficient (Tc). Topographic variables such as slope, drainage direction and soil topographic index (Tindex) are derived from a digital elevation model (DEM) using GIS. The model is used to estimate evapotranspiration (Et) loss, river flow rate and selected water quality parameters (CODMn and TP). Model verification adopted a comparison of estimated results with observed data collected at different temporal scales (storm events, daily, alternate days and every 10 days). A simplified distributed modeling framework coupled with remote sensing and GIS is expected to be an alternative to complex distributed modeling processes, which required values of parameters usually unavailable at a grid scale.
A comparison between artificial neural network method and nonlinear regression method to estimate the missing hydrometric data
Authors: Bahrami J. , Kavianpour M. R. , Abdi M. S. , Telvari A. , Abbaspour K. , Rouzkhash B.
Published: February 2011

Missing values are a common problem faced in the analysis of hydrometric data. The need for complete hydrological data, especially hydrometric data for planning, development and designing hydraulic structures, has become increasingly important. Reasonably estimating these missing values is significant for the complete analysis and modeling of the hydrological cycle. The major objective of this paper is to estimate the missing annual maximum hydrometric data by using artificial neural networks (ANN). Sixteen stations, with 28 years of measurements, in the catchment area of the Sefidroud watershed in the north of Iran were selected for this investigation. Comparison between the results of ANN and the nonlinear regression method (NLR) illustrated the efficiency of artificial neural networks and their ability to rebuild the missing data. According to the coefficient of determination (R2) and the root mean squared value of error (RMSE), it was concluded that ANN provides a better estimation of the missing data.