Vertical Saturated Hydraulic Conductivity Research Articles

Impacts of Topography‐Driven Water Redistribution on Terrestrial Water Storage Change in California Through Ecosystem Responses

AbstractLateral subsurface flow plays an essential role in sustaining the terrestrial ecosystem, but it is not explicitly represented in most Earth System Models. In this study, we implemented an explicit lateral saturated flow model into the E3SM land model (ELM). The model explicitly describes lateral flow in the saturated zone by representing, for each model grid, an idealized hillslope consisting of five hydrologically connected soil columns. We conducted three model experiments driven by 0.125° atmospheric forcing data during 1980–2015 over California using models of the default ELM, a modified version of ELM to enhance infiltration, and the model with the lateral saturated flow model. The simulated runoff, evapotranspiration, and terrestrial water storage anomaly (TWSA) from the three simulations were evaluated against available observations, and the model explicitly representing lateral flow performs best. The new model produces greater gridcell‐averaged evapotranspiration especially over the mountainous regions with moderate relief and seasonally dry climates. Most importantly, it improves the modeled seasonal variations, interannual variabilities, and the recent decadal decline of TWSA. Many of these improvements can be attributed to the enhanced ecosystem resilience to droughts as demonstrated by transpiration increases caused by lateral flow. Model sensitivity experiments suggest that subsurface runoff is most sensitive to the ratio between horizontal and vertical saturated hydraulic conductivity, followed by hillslope planforms (convergent, divergent, and uniform), number of columns, and lower boundary conditions. Future work should effectively characterize hillslopes in global models and explore the long‐term influences of lateral water movement on modeled biogeochemical cycle.

Spatial variability of the vertical saturated hydraulic conductivity of sediments around typical thermokarst lakes

The formation and development of thermokarst lakes is a key factor causing permafrost degradation, in which the vertical hydraulic conductivity (Kv) of lakebed sediments plays an important role as it affects the water and heat transfer between thermokarst lakes and permafrost. However, the spatial variability of Kv of lakebed sediments in the Qinghai–Tibet Plateau (QTP) remains unclear. Hence, in this study, the Kv values of sediments in two thermokarst lakebeds were measured in situ using the standpipe method, and the grain size of the sediments was analyzed. The statistical results showed that BLH-A and B (lakes A and B in Beiluhe) had moderate and strong spatial variabilities, respectively. Lilliefors test results showed a log-normal distribution of the Kv measurements of the sediment samples. From the results of the geostatistical method, it was concluded that the Gaussian model best fitted the variograms of the Kv values. The d50 (grain size for which 50 % of grains are finer) had the strongest correlation with Kv, and the relationship between Kv and the grain size of d50 was a quadratic function. The estimated Kv value (0.03 m/d) was close to the measurements (0.005–0.58 m/d), and the specific discharge of BLH-B ranged from − 0.0038 to 0.00056 m/d. BLH-A and BLH-B would gradually expand under the influence of future climate due to the special geology (low Kv). This basic research on thermokarst lake regions can help understand the properties of thermokarst lakebed sediments and provide parameters for the numerical simulations of the hydrological cycle in thermokarst lake regions.

Quantification of soil water balance components based on continuous soil moisture measurement and the Richards equation in an irrigated agricultural field of a desert oasis

Abstract. An accurate assessment of soil water balance components (SWBCs) is necessary for improving irrigation strategies in any water-limited environment. However, quantitative information on SWBCs is usually challenging to obtain, because none of the components (i.e., irrigation, drainage, and evapotranspiration) can be easily measured under actual conditions. Soil moisture is a variable that integrates the water balance components of land surface hydrology, and the evolution of soil moisture is assumed to contain the memory of antecedent hydrologic fluxes, and can thus be used to determine SWBCs from a hydrologic balance. A database of soil moisture measurements from six experimental plots with different treatments in the middle Heihe River basin of China was used to test the potential of a such a database for estimating SWBCs. We first compared the hydrophysical properties of the soils in these plots, such as vertical saturated hydraulic conductivity (Ks) and soil water retention features, for supporting SWBC estimations. We then determined evapotranspiration and other SWBCs using a method that combined the soil water balance method and the inverse Richards equation (a model of unsaturated soil water flow based on the Richards equation). To test the accuracy of our estimation, we used both indirect methods (such as power consumption of the pumping irrigation well and published SWBCs values at nearby sites) and the water balance equation technique to verify the estimated SWBCs values, all of which showed good reliability with respect to our estimation method. Finally, the uncertainties of the proposed methods were analyzed to evaluate the systematic error of the SWBC estimation and any restrictions regarding its application. The results showed significant variances among the film-mulched plots in both the cumulative irrigation volumes (652.1–867.3 mm) and deep drainages (170.7–364.7 mm). Moreover, the un-mulched plot had remarkably higher values in both cumulative irrigation volumes (1186.5 mm) and deep drainages (651.8 mm) compared with the mulched plots. Obvious correlation existed between the volume of irrigation and that of drained water. However, the ET demands for all of the plots behaved pretty much the same, with the cumulative ET values ranging between 489.1 and 561.9 mm for the different treatments in 2016, suggesting that the superfluous irrigation amounts had limited influence on the accumulated ET throughout the growing season due to the poor water-holding capacity of the sandy soil. This work confirmed that relatively reasonable estimations of the SWBCs in coarse-textured sandy soils can be derived by using soil moisture measurements; the proposed methods provided a reliable solution over the entire growing season and showed a great potential for identifying appropriate irrigation amounts and frequencies, and thus a move toward sustainable water resources management, even under traditional surface irrigation conditions.

Vegetative filter strips—Effect of vegetation type and shape of strip on run‐off and sediment trapping

AbstractVegetative filter strips (VFSs) are a common type of off‐site method used to enhance the sustainability of catchment systems by promoting desirable soil and landscape functions. The transport of water run‐off and sediment to downstream reaches can be restricted by VFSs in the flow path. The adoption of VFSs is increasing because they have been demonstrated to be effective for trapping run‐off and sediment. Thus, an optimized design procedure for developing VFSs is required. To further understand the roles of both vegetation type and geometric size in the design of VFSs, global sensitivity analysis (GSA) within the Vegetative Filter Strip Modeling System was conducted using a traditional elementary effect test and a novel density‐based method called PAWN. The analysis involved both a uniform and a concentrated flow scenario. The GSA outcomes indicated that the inputs related to vegetation type were vital for the VFS design, especially in terms of the run‐off reduction function of the VFS, irrespective of the scenario that was used. The vertical saturated hydraulic conductivity was the main input responsible for the influence of vegetation type. The inputs related to vegetation type had limited influences on the sediment trapping performance of the VFS, which was shown to be mainly controlled by the length of the VFS. The role of vegetation type in the design of VFSs must be fully considered, especially in cases in which VFSs are established primarily for flood control or run‐off reduction purposes.

Estimation of saturated hydraulic conductivity from ring infiltrometer test taking into account the surface moisture stain extension

Abstract A large single-ring infiltrometer test was performed in order to characterize the saturated hydraulic conductivity below an infiltration basin in the well field of Lyon (France). Two kinds of data are recorded during the experiment: the volume of water infiltrated over time and the extension of the moisture stain around the ring. Then numerical analysis was performed to determine the saturated hydraulic conductivity of the soil by calibration. Considering an isotropic hydraulic conductivity, the saturated hydraulic conductivity of the alluvial deposits is estimated at 3.8 10−6 m s−1. However, with this assumption, we are not able to represent accurately the extension of the moisture stain around the ring. When anisotropy of hydraulic conductivity is introduced, experimental data and simulation results are in good agreement, both for the volume of water infiltrated over time and the extension of the moisture stain. The vertical saturated hydraulic conductivity in the anisotropic configuration is 4.75 times smaller than in the isotropic configuration (8.0 10−7 m s−1), and the horizontal saturated hydraulic conductivity is 125 times higher than the vertical saturated hydraulic conductivity (1.0 10−4 m s−1).

Dynamics of runoff and sediment trapping performance of vegetative filter strips: Run-on experiments and modeling

Vegetative filter strips (VFSs) are a labor-saving and cost-effective agricultural best management practice to trap water runoff and sediment from the source areas. They also provide forage and/or fuel and are therefore potentially profitable for land owners. VFSs are however a dynamic system: the runoff delivery ratio (RDR) and sediment delivery ratio (SDR) vary with growth stage and vegetation types. The impacts of vegetation characteristics as well as soil physical properties modified by vegetation growth, on the RDR and SDR of VFS were evaluated by a flume experiment. Two plant species (cocksfoot (Dactylis glomerata L.) and white clover (Trifolium repens L.)) were tested at three stages in the growing season of 2016 (May, July, and August). The measured RDR and SDR were compared with the simulated results from Vegetative Filter Strip Modeling System (VFSMOD). In the early stages of the growing season, the cocksfoot formed a dense network of stems with high strip Manning's roughness faster than white clover. The runoff and sediment trapping effects of the white clover VFS were greater than that of cocksfoot VFS in all the three stages (lower RDR and SDR). This is likely attributed to strongly tillering, creeping stem posture and high infiltration capacity of the white clover VFS. VFSMOD simulated the RDR and SDR reliably except under low vegetation coverage conditions (white clover in May). The results suggested that (1) both soil physical properties and vegetation characteristics should be considered for the species-specific, temporally variable performance of VFS; and (2) when using VFSMOD inform the VFS design, modelers should take the dynamics of vegetation, mainly through vertical saturated hydraulic conductivity, stem spacing and strip Manning's roughness into account, and select parameters that reflect the actual field conditions.

Flood quantiles scaling with upper soil hydraulic properties for different land uses at catchment scale

Changes in land use within a catchment are among the causes of non-stationarity in the flood regime, as they modify the upper soil physical structure and its runoff production capacity. This paper analyzes the relation between the variation of the upper soil hydraulic properties due to changes in land use and its effect on the magnitude of peak flows: (1) incorporating fractal scaling properties to relate the effect of the static storage capacity (the sum of capillary water storage capacity in the root zone, canopy interception and surface puddles) and the upper soil vertical saturated hydraulic conductivity on the flood regime; (2) describing the effect of the spatial organization of the upper soil hydraulic properties at catchment scale; (3) examining the scale properties in the parameters of the Generalized Extreme Value (GEV) probability distribution function, in relation to the upper soil hydraulic properties. This study considered the historical changes of land use in the Combeima River catchment in South America, between 1991 and 2007, using distributed hydrological modeling of daily discharges to describe the hydrological response. Through simulation of land cover scenarios, it was demonstrated that it is possible to quantify the magnitude of peak flows in scenarios of land cover changes through its Wide-Sense Simple Scaling with the upper soil hydraulic properties.

Estimation of saturated hydraulic conductivity from double‐ring infiltrometer measurements

SummaryThis research aims to determine soil vertical saturated hydraulic conductivity (Ks) in situ from the measured steady infiltration rate (I), initial soil properties and double‐ring infiltrometer (DRI) test data. Characterizing the effects of these variables on the measured steady infiltration rate will enable more accurate prediction of Ks. We measured the effects of the ring diameter, head of ponding, ring depth, initial effective saturation and soil macroscopic capillary length on measured steady infiltration rates. We did this by simulating 864 DRI tests with the finite element program HYDRUS‐2D and by conducting 39 full‐scale in situ DRI tests, 30 Mini‐Disk infiltrometer experiments and four Guelph Permeameter tests. The M5′ model trees and genetic programming (GP) methods were applied to the data to establish formulae to predict the Ks of sandy to sandy‐clay soils. The nine field DRI tests were used to verify the computer models. We determined the accuracy of the methods with 30% of the simulated DRI data to compare I/KS values of the finite element models with estimates from the suggested formulae. We also used the suggested formulae to predict the Ks values of 30 field DRI experiments and compared them with values measured by Guelph Permeameter tests. Compared with the GP method, the M5′ model was better at predicting KS, with a correlation coefficient of 0.862 and root mean square error (RMSE) of 0.282 cm s−1. In addition, the latter method estimated Ksvalues of the field experiments more accurately, with an RMSE of 0.00346 cm s−1.

Sensitivity Analysis of a Physically Based Distributed Model

The objective of this study is to perform a sensitivity analysis of the SHETRAN model on the example of the torrential Lukovska River catchment in Serbia. The sensitivity analysis of the model was performed for the following parameters: the vertical saturated hydraulic conductivity of the subsurface soil, the horizontal saturated hydraulic conductivity in the saturated zone, the Strickler roughness coefficients for overland flow and for streams, the available water content in the soil and the erodibility coefficients due to rain and due to overland flow. It can be concluded that the water and sediment discharge are very sensitive to the values of the vertical saturated hydraulic conductivity of the subsurface soil in the range of 0.001 to 0.1 m/day; to the values of the horizontal saturated hydraulic conductivity in the saturated zone in the range of 0.01 to 5 m/day and to the values of the Strickler’s coefficients for overland flow and for rivers in the range of 0.1 to 100 m1/3s-1 and 15 to 40 m1/3s, respectively. The sediment concentrations in a flow and sediment discharge are very sensitive to the values of erodibility coefficient due to overland flow in the range of 0.5 to 1.5 mg/m2s and to the values of erodibility coefficient due to rain in the range between 0.1 and 40 J-1. The obtained results could be used to simplify the parameter calibration procedure and to facilitate estimation of parameters in ungauged mountainous basins of similar characteristics.

Assessment of water budgets and the hydrologic performance of a created mitigation wetland—A modeling approach

The study used a water balance model (DRAINMOD) to compute water budgets of a mitigation wetland created in the Piedmont region of Virginia. The calibration of the model was conducted with automated well data collected during the 17 month monitoring period along with precipitation, temperature, soil physical properties (soil water characteristic curve and saturated hydraulic conductivity) and estimated site characteristics (surface roughness and surface storage). The model was tested for two areas, one nondisturbed and the other disturbed, by construction practices commonly adopted for a mitigation wetland created in the region. A third model was created to represent the disturbed boundary conditions (wetland design), but substituted soil data observed at the nondisturbed study area. DRAINMOD successfully predicted the hydrologic regimes of both nondisturbed and disturbed areas. The model of the nondisturbed area could not accurately predict hydrology of the disturbed area. More importantly, the model of the disturbed area with the soils data from the nondisturbed area could not accurately predict the hydrology of the disturbed area. The models were used to evaluate a set of performance criteria across a 60-year (1952 to 2011) simulation period. Ponding for longer than 60 consecutive days during the growing season occurred at the disturbed study area in 39 out of 60 years and these conditions lasted the entire growing season (219 days) in multiple years. Prolonged inundation of the surface for longer than 100 consecutive days took place in at least 15 of the years simulated compared to two years in the nondisturbed model. The modified disturbed model (using nondisturbed soil data) satisfied jurisdictional hydrology more frequently compared to the disturbed model (33 years versus 22 years, respectively) and prolonged inundation was limited to 8 years during the simulation period with the longest single event lasting 168 consecutive days. The differences were attributed to the reduced drainable porosity and vertical saturated hydraulic conductivity in the disturbed wetland area which translated to a demand for surface storage in order to achieve accurate model calibration and jurisdictional wetland hydrology. The study shows that disturbance to key soil properties will require surface storage to achieve jurisdictional hydrology, and that construction practices can result in longer durations of ponding during the growing season, thus potentially altering the habitat type for the wetland from what was originally designed (e.g., from a forested wetland to open water or emergent habitats).

On the implementation of the surface conductance approach using a block-centred surface–subsurface hydrology model

• The surface conductance (SC) approach is explored for rainfall partitioning in a block-centred code. • A discrepancy arises between saturation of the uppermost node and the head reaching the land surface. • Previous research suggests the exchange interface be represented by the uppermost half-cell in MODHMS. • Our work suggests that the previous recommendation prevents accurate simulation of rainfall partitioning. • Adding a thin surface layer improves model accuracy with minimal increase in run time. In physically based catchment hydrology models, dynamic surface–subsurface interactions are often represented using the surface conductance (SC) coupling approach. Guidance on SC parameterisation within block-centred codes is limited, and common practice is to express the SC coefficient as the quotient of the vertical saturated hydraulic conductivity and the half-cell thickness of the uppermost layer. This study evaluates the implementation of the SC approach utilising a popular block-centred, surface–subsurface hydrology model (MODHMS) to simulate one-dimensional infiltration experiments under Hortonian conditions. Results show that defining the SC coefficient based on a half-cell thickness of the uppermost subsurface cell inhibits accurate prediction of infiltration rates ( q e ) and the time to initiate surface runoff ( t ro ) for the adopted rainfall–runoff scenario. Increasing the SC coefficient independently of the grid allows for accurate simulation of q e , but not t ro . The addition of a thin layer at the surface is shown to improve model accuracy substantially, such that q e and t ro approach those obtained using an equivalent mesh-centred model (i.e. where the surface and upper subsurface nodes are coincident). Whilst the addition of a single thin layer in block-centred codes allows improved prediction of surface–subsurface interaction, it does not provide a surrogate for fine discretisation throughout the subsurface that is necessary for accurate simulation of unsaturated zone flow. This study offers guidance on the implementation of the SC approach in a block-centred code and demonstrates the importance of systematic testing of parameters (that are otherwise calibrated) in physically based surface–subsurface hydrology models.

Indirect measurements of field-scale hydraulic conductivity of waste from two landfill sites

Management and prediction of the movement and distribution of fluids in large landfills is important for various reasons. Bioreactor landfill technology shows promise, but in arid or semi-arid regions, the natural content of landfilled waste may be low, thus requiring addition of significant volumes of water. In more humid locations, landfills can become saturated, flooding gas collection systems and causing sideslope leachate seeps or other undesirable occurrences. This paper compares results from two different approaches to monitoring water in waste. At the Brock West Landfill in eastern Canada, positive pore pressures were measured at various depths in saturated waste. The downward seepage flux through the waste is known, thus the vertical saturated hydraulic conductivity of the waste at this landfill was determined to be 3 × 10 −7 cm/s. By comparison, the Spadina Landfill in western Canada is predominantly unsaturated. The infiltration of moisture into the waste was measured using moisture sensors installed in boreholes which determined arrival time for moisture fronts resulting from major precipitation events as well as longer-term change in moisture content resulting from unsaturated drainage during winter when frozen ground prevented infiltration. The unsaturated hydraulic conductivity calculated from these data ranged from approximately 10 −6 cm/s for the slow winter drainage in the absence of significant recharge to 10 −2 cm/s or higher for shallow waste subject to high infiltration through apparent preferential pathways. These two very different approaches to field-scale measurements of vertical hydraulic conductivity provide insight into the nature of fluid movement in saturated and unsaturated waste masses. It is suggested that the principles of unsaturated seepage apply reasonably well for landfilled waste and that the hydraulic behavior of waste is profoundly influenced by the nature and size of voids and by the degree of saturation prevailing in the landfill.

Modeling Runoff Generation in a Small Snow‐Dominated Mountainous Catchment

Snowmelt in mountainous areas is an important contributor to river water flows in the western United States. We developed a distributed model that calculates solar radiation, canopy energy balance, surface energy balance, snow pack dynamics, soil water flow, snow–soil–bedrock heat exchange, soil water freezing, and lateral surface and subsurface water flow. The model was applied to describe runoff generation in a subcatchment of the Dry Creek Experimental Watershed near Boise, ID. Calibration was achieved by optimizing the soil water field capacity (a trigger for lateral subsurface flow), lateral saturated soil hydraulic conductivity, and vertical saturated hydraulic conductivity of the bedrock. Validation results show that the model can successfully calculate snow dynamics, soil water content, and soil temperature. Modeled streamflow for the validation period was underestimated by 53%. The timing of the streamflow was captured reasonably well (modeling efficiency was 0.48 for the validation period). The model calculations suggest that 50 to 53% of the yearly incoming precipitation in the subcatchment is consumed by evapotranspiration. The model results further suggest that 34 to 36% of the incoming precipitation is transformed into deep percolation into the bedrock, while only 11 to 16% is transformed into streamflow.

Spatial Variability of Irrigation Water Percolation Rates and Its Relation to Rice Productivity

Problem statement: Study on spatial variability of vertical saturated hydraulic conductivity or percolation loss was conducted within a plot of an area of 1.2 ha paddy plot to find out the relationship between percolation rate and rice productivity. A paddy soil condition that permits percolation rate of 10-20 mm irrigation water day-1 was recommended in order to get high yield of rice. This value is very high when compared to typical values from 1-4 mm day-1 for the Malaysian engineers practiced in paddy fields. Approach: This study presented results of a study that relate the distribution of percolation rates with respect to rice yield productivity. Soil samples at 36 sampling points were collected. DGPS was used to locate the sampling points and then rice yields of the same point were collected. The relationship was determined by statistical correlation factor. Kriging method was used to map the distribution of percolation and yield. Results: The results of the study showed that percolation loss was very low and varied even within a small area. Spatial variability maps show that the area of high percolation rates is the same area that produced high yield. Even though high yields can be obtained from the areas of high percolation rate, it may not be the optimum rate. Conclusion: Higher yield within the area of high percolation may be due to less toxic since it is easily be drained out.

Calibration of a Vadose Zone Model Using Water Injection Monitored by GPR and Electrical Resistance Tomography

The noninvasive characterization of the vadose zone has been the objective of intense research aiming at collecting data for the calibration of flow and transport models. This interest is motivated by the difficulty of accessing the vadose zone with direct methods without causing disturbance to the natural conditions. On the other hand, characterizing the vadose zone requires detailed knowledge of space and time variations of water distribution. Geophysical methods capable of imaging the moisture content, such as ground penetrating radar (GPR) and electrical resistance tomography (ERT), provide data with high resolution in space and time: natural infiltration and artificial injection (tracer) tests can be imaged, by repeating measurements over time (time‐lapse mode). We conducted a forced‐injection experiment at a test site in Gorgonzola, east of Milan (Italy). The site is characterized by Quaternary sand and gravel sediments that house an extensive unconfined aquifer. We used ERT and GPR in two‐dimensional cross‐hole configuration and time‐lapse mode during a period of several days preceding and following a tracer experiment with the injection of about 20 m3 of fresh water in a purposely excavated trench. The calibration of a three‐dimensional infiltration model on the basis of the geophysical data provides useful estimates of vertical saturated hydraulic conductivity; however, we observed a discrepancy in mass balance between calibrated simulations and measurements. This fact cannot be explained using a simple isotropic model for hydraulic properties; therefore, the method requires further investigation before being fully established.

Application of DRAINMOD-Ks-STMAX to Predict Deep Chiseling Effects on a Drained Southern Alluvial Soil

Deep chiseling in heavy drained soils can help increase infiltration and hence reduce erosion, potentially enhancing growth by reducing excess water in the root zone and reducing nutrient losses through the reduction of runoff to surface waters. The goals of this study were to apply DRAINMOD-Ks-STMAX, a modified form of the water management model, DRAINMOD 1) to predict the effects of deep chiseling on hydrology for a subsurface drained plot and 2) to determine the frequency and timing of deep chiseling. Data from a subsurface drained plot at Ben Hur Research site near Baton Rouge, Louisiana, were used. Simulation results indicated that deep chiseling a Commerce silt loam, a southern alluvial soil, increased cumulative infiltration (CI) by 16% and reduced cumulative sub-surface drainage (CSD) and cumulative surface runoff (CRO) by 26% and 37%, respectively, between 28 September 1995 and 21 November 1996. Between 22 November 1996 and 22 November 1997, it increased CI and CSD by 9% and 17%, respectively, and reduced CRO by 22%. Vertical saturated hydraulic conductivity (Ks) had decreased by 99%, from a maximum initial value immediately after deep chiseling, by the time 150 cm of rain had fallen (approximately 12 months) since deep chiseling. For high rainfall states like Louisiana, with average annual rainfall often exceeding 150 cm, this translates to deep chiseling once every year whereas in drier states deep chiseling can be done once every two to three years depending on the amount of rainfall. Depending on the cumulative amount of rainfall at planting, producers can lose 85% or more of the maximum deep chiseling benefits due to reduced Ks. Because of great rainfall variability in Louisiana and other southern states, it is advisable for farmers to deep chisel their fields just prior to the planting season. Results of this model simulation study indicate that DRAINMOD-Ks-STMAX can be used as a cost-effective (saving time and money) tool to predict the effects of deep chiseling in poorly drained soils with subsurface drainage and potentially open ditch drainage, and to advise farmers on the frequency and timing of deep chiseling based on science. However, the model needs to be tested for longer time periods and under different climatic conditions and soil types before it can be recommended for general application for the purposes listed above.

Effective Hydraulic Properties Determined from Transient Unsaturated Flow in Anisotropic Soils

An important requirement for accurate modeling of field‐scale unsaturated transport using local‐scale parameters is a method to account for multiscale heterogeneity and the connectivity of the facies that control flow. A series of infiltration tests were conducted at the Hanford Site along a 60‐m‐long transect, instrumented at 1‐m intervals to measure water content (θ) and capillary pressure head (h) to quantify the spatial correlation structure of hydraulic properties and assess connectivity of the facies. Hydraulic parameters including the pore connectivity–tortuosity tensor (Li) were inversely estimated using the Subsurface Transport Over Multiple Phases (STOMP) numerical simulator coupled with the parameter estimation code, UCODE. Results show that six of eight parameters required for a modified van Genuchten–Mualem model could be inversely estimated using θ measured during transient infiltration from a surface line source and approximated prior information. Soils show evidence of saturation‐dependent anisotropy that was well described with the connectivity tensor. Variability of the vertical saturated hydraulic conductivity, Ksv, was larger than the horizontal, Ksh The autocorrelation ranges for Ksh, Ksv, the inverse of the air‐entry value, α, and the horizontal connectivity, Lh, were between 2.4 and 4.6 m, whereas the van Genuchten shape parameter, n, and saturated water content, θs, showed no autocorrelation. Accurate upscaling of hydraulic properties requires the correct assessment of the connectivity of facies.

Modeling the Effects of Deep Chiseling with DRAINMOD for Alluvial Soils

DRAINMOD is a drainage model that has been widely used in the shallow water table regions of the U.S., including the southeastern U.S. Therefore, it is important that DRAINMOD realistically simulate the water balance components for alluvial soils that are prone to surface seal formation, which are the predominant soils in much of the southeastern U.S. In this study, DRAINMOD 5.1 was modified to address the problems associated with the assumption of constant vertical saturated hydraulic conductivity (Ks) and constant maximum surface depressional storage (STMAX) for these alluvial soils. The first objective was to modify DRAINMOD 5.1 to incorporate the effects of deep chiseling (Ks and STMAX vary) in order to improve its prediction of infiltration and surface runoff. The second objective was to evaluate the modified DRAINMOD models with dynamic Ks and STMAX subroutines (DRAINMOD-Ks, DRAINMOD-STMAX, and the combined DRAINMOD-Ks-STMAX), using two years (Sept. 1995 to Nov. 1996 and Nov. 1996 to Nov. 1997 when deep chiseling was carried out) of measured surface runoff data from the USDA-ARS Ben Hur research site. Simulations by DRAINMOD 5.1 were compared with those by DRAINMOD-Ks, DRAINMOD-STMAX, and DRAINMOD-Ks-STMAX to further determine the effect of the modifications on surface runoff and infiltration predictions. In general, DRAINMOD-STMAX, DRAINMOD-Ks, and DRAINMOD-Ks-STMAX improved surface runoff prediction by 57%, 73%, and 82%, respectively, in the 1995-1996 season and by 27%, 45%, and 62%, respectively, in the 1996-1997 season.

Uncertainties in DRAINMOD predictions of subsurface drain flow for an Indiana silt loam using the GLUE methodology

AbstractGood modelling practice requires the incorporation of uncertainty analysis into hydrologic/water quality models. The generalized likelihood uncertainty estimation procedure was used to evaluate the uncertainty in DRAINMOD predictions of daily, monthly, and yearly subsurface drain flow. A variance‐based sensitivity analysis technique, the extended Fourier amplitude sensitivity test, was used to identify the main sources of prediction uncertainty. The analysis was conducted for the experimental drainage field at the Southeast Purdue Agricultural Center in Indiana. Six years of data were used and the uncertainties in eight model parameters were considered to analyse how uncertainties in input parameters propagate to model outputs. The width of 90% confidence interval bands of drain flow ranged from 0 to 0·6 cm day−1 for daily predictions, from 0 to 3·1 cm month−1 for the monthly predictions, and from 7·6 to 12·4 cm year−1 for yearly predictions. Annual drain flow predicted by DRAINMOD fell well within the 90% confidence bounds. Model results were most sensitive to the vertical saturated hydraulic conductivity of the restrictive layer and the lateral hydraulic conductivity of the deepest soil layer, followed by the lateral hydraulic conductivity of the top soil layer and surface micro‐storage. Parameter interactions also contributed to the prediction uncertainty. Copyright © 2006 John Wiley & Sons, Ltd.

Modeling hydrology and sediment transport in vegetative filter strips

The performance of vegetative filter strips is governed by complex mechanisms. Models can help simulate the field conditions and predict the buffer effectiveness. A single event model for simulating the hydrology and sediment filtration in buffer strips is developed and field tested. Input parameters, sensitivity analysis, calibration and field testing of the model are presented. The model was developed by linking three submodels to describe the principal mechanisms found in natural buffers: a Petrov–Galerkin finite element kinematic wave overland flow submodel, a modified Green–Ampt infiltration submodel and the University of Kentucky sediment filtration model for grass areas. The new formulation effectively handles complex sets of inputs similar to those found in natural events. Major outputs of the model are water outflow and sediment trapping on the strip. The strength of the model is a good description of the hydrology within the filter area, which is essential for achieving good sediment outflow predictions or trapping efficiency. The sensitivity analysis indicates that the most sensitive parameters for the hydrology component are initial soil water content and vertical saturated hydraulic conductivity, and sediment characteristics (particle size, fall velocity and sediment density) and grass spacing for the sediment component. A set of 27 natural runoff events (rainfall amounts from 0.003 to 0.03 m) from a North Carolina Piedmont site was used to test the hydrology component, and a subset of nine events for the sediment component. Good predictions are obtained with the model if shallow uniform sheet flow (no channelization) occurs within the filter.