Soil Water Retention Function Research Articles

Performance evaluation of different soil water retention functions for modeling of water flow under transient condition

ABSTRACT ABSTRACT: Description and prediction of water flow through unsaturated soils is necessary to understand their hydraulic properties, including soil water retention curve (SWRC). Many models have been developed for estimation of SWRC and many researchers compared water retention curve derived from these models with the measured values. In this paper, in addition to comparing measured and derived SWRC, a functional evaluation of SWRC for modeling of soil water movement was carried out using van Genuchten, Brooks-Corey, Campbell and Hutson-Cass models in three sites including Loamy sand, Loam and Clay loam soils. Therefore, the functional behavior of SWRC was quantitatively compared by applying mentioned SWRC to numerical code (HydroGeoSphere) to simulate soil profile drainage under steady-state and transient conditions. The agreement between simulated and measured free drainages values was evaluated using statistical criteria including mean absolute error (MAE), modified index of agreement (d’), modified coefficient efficiency (E’), and t-test. The results demonstrated that the van Genuchten model was slightly better than the other models for estimation of SWRC (MAE 0.014 – 0.016,E’ 0.80 – 0.87 and d’ 0.90 – 0.93) while according to t-test, it was found that the measured and estimated SWRC using various models did not differ significantly. Therefore, it is expected that the simulated free drainage using mentioned SWRC models did not differ significantly with observed values. But the results demonstrated that the simulated free drainage using Brooks-Corey model for Loamy sand soil and van Genuchten and Brooks-Corey models for Loam soil differed significantly (p ≤ 0.05) with measured values.

Drywell infiltration and hydraulic properties in heterogeneous soil profiles

Drywells are increasingly used to capture stormwater runoff for surface infiltration and aquifer recharge, but little research has examined the role of ubiquitous subsurface heterogeneity in hydraulic properties on drywell performance. Numerical experiments were therefore conducted using the HYDRUS (2D/3D) software to systematically study the influence of subsurface heterogeneity on drywell infiltration. Subsurface heterogeneity was described deterministically by defining soil layers or lenses, or by generating stochastic realizations of soil hydraulic properties with selected variance (σ) and horizontal (X) and vertical (Z) correlation lengths. The infiltration rate increased when a high permeability layer/lens was located at the bottom of the drywell, and had larger vertical and especially horizontal dimensions. Furthermore, the average cumulative infiltration (I) for 100 stochastic realizations of a given subsurface heterogeneity increased with σ and X, but decreased with Z. This indicates that the presence of many highly permeable, laterally extending lenses provides a larger surface area for enhanced infiltration than the presence of isolated, highly permeable lenses. The ability to inversely determine soil hydraulic properties from numerical drywell infiltration results was also investigated. The hydraulic properties and the lateral extension of a highly permeable lens could be accurately determined for certain idealized situations (e.g., simple layered profiles) using constant head tests. However, variability in soil hydraulic properties could not be accurately determined for systems that exhibited more realistic stochastic heterogeneity. In this case, the heterogeneous profile could be replaced with an equivalent homogeneous profile and values of an effective isotropic saturated conductivity (Ks) and the shape parameter in the soil water retention function (α) could be inversely determined. The average value of Ksfor 100 stochastic realizations showed a similar dependency to I on σ, X, and Z. Whereas, the average value of α had large confidence interval for soil heterogeneity parameters and played a secondary role in drywell infiltration. This research provides valuable insight on the selection of site, design, installation, and long-term performance of a drywell.

SPorDyn: A Python code for modeling the evolution of soil pore size distribution after tillage

Surface soil structure is very responsive to natural and anthropogenic impacts and these changes alter soil hydraulic properties and the soil water budget. In the midst of a dearth of efforts to capture soil structural dynamics, an analytical solution to the Fokker-Planck Equation with physically-based coefficients has shown promising results in predicting the evolution of soil pore space in agricultural soils. In this study, the Python code for the analytical solution is shown along with steps to estimate coefficients leading towards obtaining the analytical solution.•Python code for modeling the evolution of soil pore space based on an existing model is shared.•The code for the estimation of physically-based coefficients of the model and parameter optimization are also shown.•The final output of the model may be used in estimation of soil water retention and hydraulic conductivity functions.

Development of a steady-state model to predict daily water table depth and root zone soil matric potential of a cranberry field with a subirrigation system

Maintaining a steady water table depth (WTD) to ensure an optimal soil matric potential in the root zone (RMAP) is vital when growing cranberry under a subirrigation system; owing to losses and other hydrological processes. The excessive rising or falling of the WTD may threaten the plant transpiration either by saturation or lack of moisture in the root soil. A steady-state model was developed for a uniform soil column to predict WTD and RMAP under different weather conditions. The model is based on van Genuchten (VG) and Brooks and Corey (BC) analytical soil water retention functions coupled with Mualem, Brooks and Corey, and Gardner hydraulic conductivity models. The results show that the model is capable of predicting satisfactorily both WTD and RMAP. The VG model performed with a 78.13% accuracy for the WTD and an 88.59% precision according to the Kling Gupta Efficiency coefficient (r2 = 0.90, β = 1.00, and γ = 0.99) for the field storage. Meanwhile for the RMAP the Mualem and Gardner hydraulic conductivity models, predictions were successful 71.87% and 75.00% of the time, respectively. The BC model had a 78.13% success for the WTD, 86.93% accuracy in estimating the field water storage according to Kling-Gupta efficiency coefficient (r2 = 0.89, β = 1.00, and γ = 1.00) and the BC and Gardner hydraulic conductivity models had 65.63% and 71.88% success, respectively. A sensitivity analysis of the model, by means of the Morris method, reveals that for both models, the lower boundary condition impacts significantly both variables which are, however, less affected by the field capacity and the residual soil moisture content. The lower boundary condition interacts with the slope of the soil water retention functions, the height of the capillary fringe, the saturated conductivity, and the saturation moisture content which have non-linear effects. An uncertainty analysis shows that both variables for both models are normally distributed.

An Alert Regarding a Common Misinterpretation of the Van Genuchten α Parameter

ABSTRACT Among the equations available to describe the relation between matric potential and soil water content, the soil water retention function, the most commonly used is the equation proposed by Van Genuchten in his 1980 landmark paper. In soil physics literature, especially in Brazil, several authors relate the inverse of the Van Genuchten parameter α to the air-entry pressure. This study aimed to show this common interpretation to be erroneous, as 1/α corresponds to water contents lower than saturation. The [...]

Temporal dynamics of subsurface soil water content estimated from surface measurement using wavelet transform

Temporal variation of water in the vadose zone is important to understand processes such as solute transport and nutrient cycling. Measurements of soil water content (SWC) in the subsurface are less common than those near the surface and predictions using numerical models are limited by data availability. Wavelet decomposition of surface measurements of SWC could improve modeling of subsurface SWC by segregating features at different temporal scales and projecting them to the subsurface. The objectives of this work were to: 1) predict subsurface SWC using surface SWC and a combination of wavelet analysis and linear regression, and 2) investigate relationships between soil properties and the movement of soil water at various temporal scales, s. Climate data and SWC at various depths were collected from eight sites in the Atlantic Coastal Plain of the USA. Soil water retention and hydraulic conductivity (k) functions of each horizon were optimized by comparing measured and predicted (using HYDRUS-1D) soil water contents. Each time series of SWC was decomposed into 50 scale components using the Mexican Hat wavelet and later reduced to 5 group components with minimal impact on the characteristics of the signal. Changes in the values of each group component with depth were represented with transfer coefficients that could be estimated with predictors derived from particle size distributions and optimized soil hydraulic functions. Prediction depth and saturated k were the two most important predictors for s < 256 h, while k at −10 kPa was the best predictor for 256 h < s < 724 h, and the median value of particle size diameters for s > 724 h. Subsurface soil water content can be reasonably predicted with the proposed approach, particularly when vertical movement of soil water is unrestricted.

Numerical Simulation and Sensitivity Analysis for Nitrogen Dynamics Under Sewage Water Irrigation with Organic Carbon

This study is focused on investigating the impacts of organic carbon on the denitrification process of nitrogen transformation and transport. A numerical model, Nitrogen-2D, is modified by considering the impact of organic carbon in the denitrification equation. The modified model is used to simulate the soil nitrogen (including nitrate and ammonium) dynamics under the primary and secondary sewage water irrigation with different organic carbon concentrations. The simulated results of accumulated drainage water amount, soil nitrogen concentration, and nitrogen concentration in the drainage water show that the simulations and measurements are consistent. The comparison of results from the original and improved models shows the necessity to consider the impact of organic carbon. The nitrogen mass balance is calculated to analyze the nitrogen transformation processes quantitatively under different input organic carbon sources. Furthermore, the effect of different input organic carbon sources on the soil nitrogen dynamics is investigated by using the modified Nitrogen-2D model with the calibrated parameters. The input organic carbon source helps to speed up the mineralization and denitrification, which contributes to the slight increase of ammonium concentration and the decrease of nitrate concentration in the shallow soil. Since a large number of soil water and nitrogen transformation and transport parameters are needed when setting up the model, a local sensitivity method is conducted to evaluate the input parameters by the sewage water irrigation case. The results show that the drainage water amount is very sensitive to the exponent n and the coefficient α of the soil water retention function and that the ammonium concentration is very sensitive to the first-order nitrification rate constant, the decomposition rate coefficient in humus pool, and the soil ammonium adsorption coefficient. The nitrate concentration is sensitive to more parameters, especially to the exponent n and the coefficient α in the soil water retention function and to the denitrification rate constant.

Spatial prediction of near surface soil water retention functions using hydrogeophysics and empirical orthogonal functions

The hydrological community often turns to widely available spatial datasets such as the NRCS Soil Survey Geographic database (SSURGO) to characterize the spatial variability of soil properties. When used to spatially characterize and parameterize watershed models, this has served as a reasonable first approximation when lacking localized or incomplete soil data. Within agriculture, soil data has been left relatively coarse when compared to numerous other data sources measured. This is because localized soil sampling is both expensive and time intense, thus a need exists in better connecting spatial datasets with ground observations. Given that hydrogeophysics is data-dense, rapid, non-invasive, and relatively easy to adopt, it is a promising technique to help dovetail localized soil sampling with spatially exhaustive datasets. In this work, we utilize two common near surface geophysical methods, cosmic-ray neutron probe and electromagnetic induction, to identify temporally stable spatial patterns of measured geophysical properties in three 65 ha agricultural fields in western Nebraska. This is achieved by repeat geophysical observations of the same study area across a range of wet to dry field conditions in order to evaluate with an empirical orthogonal function. Shallow cores were then extracted within each identified zone and water retention functions were generated in the laboratory. Using EOF patterns as a covariate, we quantify the predictive skill of estimating soil hydraulic properties in areas without measurement using a bootstrap validation analysis. Results indicate that sampling locations informed via repeat hydrogeophysical surveys, required only five cores to reduce the cross-validation root mean squared error by an average of 64% as compared to soil parameters predicted by a commonly used benchmark, SSURGO and ROSETTA. The reduction to five strategically located samples within the 65 ha fields reduces sampling efforts by up to ∼90% as compared to the common practice of soil grid sampling every 1 ha.

Variability in soil-water retention properties and implications for physics-based simulation of landslide early warning criteria

Rainfall-induced shallow landsliding is a persistent hazard to human life and property. Despite the observed connection between infiltration through the unsaturated zone and shallow landslide initiation, there is considerable uncertainty in how estimates of unsaturated soil-water retention properties affect slope stability assessment. This source of uncertainty is critical to evaluating the utility of physics-based hydrologic modeling as a tool for landslide early warning. We employ a numerical model of variably saturated groundwater flow parameterized with an ensemble of texture-, laboratory-, and field-based estimates of soil-water retention properties for an extensively monitored landslide-prone site in the San Francisco Bay Area, CA, USA. Simulations of soil-water content, pore-water pressure, and the resultant factor of safety show considerable variability across and within these different parameter estimation techniques. In particular, we demonstrate that with the same permeability structure imposed across all simulations, the variability in soil-water retention properties strongly influences predictions of positive pore-water pressure coincident with widespread shallow landsliding. We also find that the ensemble of soil-water retention properties imposes an order-of-magnitude and nearly two-fold variability in seasonal and event-scale landslide susceptibility, respectively. Despite the reduced factor of safety uncertainty during wet conditions, parameters that control the dry end of the soil-water retention function markedly impact the ability of a hydrologic model to capture soil-water content dynamics observed in the field. These results suggest that variability in soil-water retention properties should be considered for objective physics-based simulation of landslide early warning criteria.

Water Flow Modeling with Dry Bulk Density Optimization to Determine Hydraulic Properties in Mountain Soils

Core Ideas The GEOtop model was used to calculate water flow in mountain soils. Dry soil bulk density was optimized to determine soil hydraulic properties. Soil water contents for two watersheds were used to test the optimization procedure. A new method for determining profile‐average and depth‐wise hydraulic properties in heterogeneous mountain soils is presented using the GEOtop watershed model in 1‐D vertical mode. Dry soil bulk density–converted volumetric soil water retention data are used to determine van Genuchten soil water retention parameters, and the Kozeny–Carman equation is used to determine saturated soil hydraulic conductivity. Optimum dry soil bulk densities are identified by minimizing the sum of squared error between measured and calculated soil water content time series. The new method was tested using soil moisture data from soil profiles at the Dry Creek Experimental Watershed, Boise, ID, and the Libby Creek Experimental Watershed, Laramie, WY. Results of different scenarios showed that the optimization of a single profile‐average dry soil bulk density is a good option for describing soil water flow in the heterogeneous mountain soils. Soil water content modeling efficiency (ME) values of 0.084 ≤ ME ≤ 0.745 and –2.443 ≤ ME ≤ 0.373 were found for the Dry Creek and Libby Creek sites, respectively. Relatively low ME values for the deepest sensor depths for some scenarios were attributed to the overestimation of soil water freezing and uncertainty in the soil water retention function near saturation. The resulting calibration procedure is computationally efficient because only one parameter (dry soil bulk density) is optimized.

Predicting the Campbell Soil Water Retention Function: Comparing Visible–Near‐Infrared Spectroscopy with Classical Pedotransfer Function

Core Ideas The Campbell model was anchored at a soil water content of −1000 cm H2O matric potential. The two model parameters were predicted using either soil fines or vis–NIR spectroscopy. Both methods accurately predicted the soil water retention curve. The soil water retention curve (SWRC) is essential for the modeling of water flow and chemical transport in the vadose zone. The Campbell function and its b (pore‐size distribution index) parameter fitted to measured data is a simple method to quantify retention under relatively moist conditions. Measuring soil water retention is time consuming, and a method to accurately predict the Campbell relation from either typically available soil parameters such as bulk density, clay‐size fraction, and organic matter content (soil fines) or from visible–near‐infrared (vis–NIR) spectroscopy may provide a fast and inexpensive alternative. However, the traditional Campbell model has a reference point at saturated water content, and this soil‐structure‐dependent water content will typically be poorly related to basic texture properties and thus be poorly predicted from vis–NIR spectra. In this study, we anchor the Campbell model at the water content at −1000 cm H2O matric potential [log(1000)= pF 3]. Agricultural soil samples with a wide textural range from across Denmark were used. Soil water retention was measured at a number of matric potentials between pF 1 and 3. The soil water content at pF 3 and Campbell b were both well predicted using either a soil‐fines‐based pedotransfer function or vis–NIR spectroscopy. The resulting Campbell function anchored at pF 3 compared closely to measured water retention data for a majority of soils. The ability of the two methods to also predict field average SWRC was evaluated for three fields. Field average, predicted SWRC compared well with field average measured data, with vis–NIR overall performing better.

A binary mixing model for characterizing stony-soil water retention

A century of research focused primarily on agricultural soils has largely ignored stony soils, which dominate some forests and are poorly understood in terms of the stone influence on soil hydraulic properties. Motivated by this knowledge gap, we quantified the influence of soil-containing stone fragments on bulk soil hydraulic properties by determining the water retention curve (WRC) of soil, stone and stone-soil mixtures with varied volumetric stone content. The measured WRC for seven different stone types based on their composition showed maximum and minimum saturated water contents of 0.55m3m−3 in pumice and 0.025m3m−3 in fine sandstone, respectively. The stony soil water retention function was measured using the simplified evaporation method. Contrasting scenarios were studied considering a broad range of stone inclusions; (i) negligibly porous, (ii) significantly porous but less porous than the background soil, (iii) more porous than the background soil. An averaging scheme to describe the WRC of stony soil was proposed based on the individual WRC of the background and stone inclusion which was in good agreement with the experimental data. The HYDRUS-3D model was also employed to simulate the evaporation experiment used for the WRC measurements. The model simulations supported the basic assumptions of the proposed averaging scheme.

Soil hydro-physical characteristics and water retention function of typical shrubbery stands in the Yellow River Delta of China

The shell ridge worldwide that presents a combination of old and new shell ridges is located in the Yellow River Delta of China. The water storage and retention capacities of the shell sand soil are key factors for the growth and development of vegetation and act as important indicators in evaluations of vegetation-related soil and water conservation. We investigated the hydrological and physical characteristics of the soil and the interactions of these characteristics for the following dominant shrubbery stands on the shell ridge: Tamarix chinensis Lour, Periploca sepium Bunge and Ziziphus jujuba var. Spinosa. The different shrubbery stands presented significantly different physical shell sand parameters, such as water storage capacity, permeability and water-holding capacity. Compared with the bare soil, the shrubbery-covered shell sand soils showed significantly reduced bulk densities; increased porosities, water storage capacities, infiltration rates and water-holding capacities; and reduced particle sizes. The shrubbery increased the amount of soil water-stable aggregates and reduced the amount of soil air-dried aggregates, and the fractal dimension of the soil water-stable aggregates was significantly higher than that of the air-dried aggregates. T. chinensis shrub growth yielded a better soil aggregate structure compared with that of Z. jujuba, whereas the P. sepium shrub yielded the poorest structure. The soil porosity and the mean weight diameter of the soil aggregates were the major factors that affected the water retention capability of the shell sand. The best water retention capability was observed with the T. chinensis shrub stand followed by the Z. jujuba and P. sepium stands, whereas the bare soil exhibited the poorest results. Our results indicate that T. chinensis seedlings are the best choice for planting to improve soil porosity and soil aggregates on the shell ridges of the Yellow River Delta.

Impact of stoniness correction of soil hydraulic parameters on water balance simulations of forest plots

AbstractLong‐term estimates of the water balance of forests are essential for forest ecosystem analysis. Such estimates can be achieved by using numerical modelling approaches for water balance calculations. These modelling approaches require data, e.g., for the description of the hydraulic properties of forest soils using soil water retention or hydraulic conductivity functions. However, these functions are usually valid only for fine‐earth conditions. However, many forest soils, especially those located in mountainous regions, contain larger fractions of gravel and rock fragments in the soil profiles. In our study, the impact of stoniness correction of soil hydraulic functions on the performance of a numerical water balance modelling approach was evaluated by using continuously measured time series of daily throughfall, soil water contents and pressure heads provided from three different ICP Forests Level II plots with high stoniness in the soil profiles. These measured data were compared with the corresponding model outputs. The application of stoniness correction of the soil hydraulic functions improved the model performance in terms of the Nash‐Sutcliffe Index NS and the coefficient of determination R2. This indicated the need for such a correction.

The recent similarity hypotheses to describe water infiltration into homogeneous soils

A similarity hypothesis recently presented to describe horizontal infiltration into homogeneous soils, developed for coarse-textured soils like sieved marine sand, implies that the soil water retention function θ(h) is the mirror image of an extended Boltzmann transform function θ(λ2). A second hypothesis applicable to vertical infiltration suggests that the soil water retention function θ(h) is also the mirror image of the soil water profile θ(z). Using previously published infiltration data, we investigated whether these two similarity solutions successfully describe infiltration into two “normal” soils. Although the theory using the first similarity assumption adequately describes horizontal cumulative infiltration and infiltration rate into both soils, it fails to estimate soil water distributions measured between soil profiles. The second similarity solution for vertical infiltration into either soil completely fails to coincide with measured soil water distributions, cumulative infiltration and infiltration rate.

Analytical solution to transient Richards' equation with realistic water profiles for vertical infiltration and parameter estimation

AbstractA general analytical model for one‐dimensional transient vertical infiltration is presented. The model is based on a combination of the Brooks and Corey soil water retention function and a generalized hydraulic conductivity function. This leads to power law diffusivity and convective term for which the exponents are functions of the inverse of the pore size distribution index. Accordingly, the proposed analytical solution covers many existing realistic models in the literature. The general form of the analytical solution is simple and it expresses implicitly the depth as function of water content and time. It can be used to model infiltration through semi‐infinite dry soils with prescribed water content or flux boundary conditions. Some mathematical expressions of practical importance are also derived. The general form solution is useful for comparison between models, validation of numerical solutions and for better understanding the effect of some hydraulic parameters. Based on the analytical expression, a complete inverse procedure which allows the estimation of the hydraulic parameters from water content measurements is presented.

Effects of disturbed landforms on the soil water retention function during urbanization process in the Three Gorges Reservoir Region, China

Decreases in the water retention function of various artificial disturbed landform units (DLUs) caused by urbanization activities, compared to original landform units (OLUs), are the main factor that causes urban water and soil loss and the aggravation of urban floods under certain rainfall conditions and specially designed drainage network capabilities. Field investigations, laboratorial analyses of soil physical properties and analytic hierarchy process (AHP) composite methods were performed to comprehensively analyse the effects of various DLUs on the water retention function of OLUs. The results indicated as the following: (і) The >5mm particle content (>54%) for various DLUs was higher than that for OLUs (lower than 3%); the natural repose angles of soil-rock mixtures (32–37°) and soil bulk density (1.41–1.74g/cm3) in the DLUs were all higher than those in the OLUs (30–31°, 1.18–1.14g/cm3); and the uniformity coefficients and curvature coefficients were 10.00–80.00 and 3.24–5.70 in the DLUs and 6.00–75.00 and 0.17–2.50 in the OLUs, respectively. (ii) The soil steady state infiltration rate in the DLUs decreased from disturbed soil accumulation with 2months (DSA2m, 15.00mm/min) to disturbed soil accumulation with 2years (DSA2a, 5.63mm/min), disturbed soil accumulation with 4years (DSA4a, 3.82mm/min), the slope greening belt (SGB, 1.24mm/min), and construction roads (CR, 0.51mm/min). The conversion from forests to DSA2m had the greatest impact on the soil infiltration capacity and soil storage capacity, while the conversion to CR had the lowest impact. (iii) The total reservoir storage in the DLUs' soil was ordered as follows: DSA4a>SGB>DSA2a>DSA2m>CR. The conversion process from grass to CR exerted the greatest impact on storing water and regulating the overland flow. (iv) The water retention functions in the DLUs were all weaker than those in the OLUs: DSA2m was the weakest (0.287), while paddy fields were the strongest (0.668). Thus, the occupied areas of urban water surfaces (e.g., lakes, rivers and ponds), forests and grassland and their spatial distribution during urbanization must be carefully considered. These results could help to understand the ecological service functions of urban soil and water conservation, provide relevant knowledge to landscape rehabilitation, alleviate urban floods during urban development and recover the functions of soil and water conservation ecological services in project areas during the urbanization construction process.

Unsaturated zone flow and solute transport modelling with MIKE SHE: model test and parameter sensitivity analysis using lysimeter data

This study presents the test of the widely used model MIKE SHE at the lysimeter in Wagna in Southern Styria (Austria). At the lysimeter comprehensive data of vegetation, i.e., cultivation types, and soil hydraulic properties are available to parameterise the model. The aim of the study is to test the water movement and solute transport simulation in the unsaturated zone and the evapotranspiration module by a comparison with measured recharge rates at the lysimeter bottom and measured soil water contents and soil tensions in different depths. For the unsaturated zone calculation, the Richards equation and the Van Genuchten–Mualem approach is used. With the parameterised model the solute transport module is tested against data of a tracer experiment (Bromide). The water content simulation in the different soil depths yielded good results. However, particularly in the gravel zone (below 70 cm) the strong recharge dynamics and at the same time also strong water content dynamics can hardly be reproduced by one individual soil physical parameter set. Two different sets were identified and the corresponding soil water retention functions are located at the opposite ends of the relatively large range obtained by the measurements in this zone. Also, the saturated hydraulic conductivity had to be increased by an order of magnitude to accurately represent the recharge dynamics. The test of the solute transport simulation showed generally very good results. However, the early rapid rise of the measured concentrations could not be reproduced with either parameter set. The discrepancies found in the study indicate a complex pore system in the gravel zone consisting of different flow paths (e.g., system of matrix flow and macro-pore flow) activated at different soil moisture conditions, which cannot be fully represented by the used approach. However, the parameter study herein highlights the main parameters to be altered in a calibration procedure at point scale. The paper includes also a step from point to regional scale. For comparison test calculations with data, which are usually available on regional scale, showed good results for the 5-year average balance (−7 % compared to measurements) but rather large deviations from the measurements at shorter time scales.

The soil water characteristic as new class of closed-form parametric expressions for the flow duration curve

Summary The flow duration curve is a signature catchment characteristic that depicts graphically the relationship between the exceedance probability of streamflow and its magnitude. This curve is relatively easy to create and interpret, and is used widely for hydrologic analysis, water quality management, and the design of hydroelectric power plants (among others). Several mathematical expressions have been proposed to mimic the FDC. Yet, these efforts have not been particularly successful, in large part because available functions are not flexible enough to portray accurately the functional shape of the FDC for a large range of catchments and contrasting hydrologic behaviors. Here, we extend the work of Vrugt and Sadegh (2013) and introduce several commonly used models of the soil water characteristic as new class of closed-form parametric expressions for the flow duration curve. These soil water retention functions are relatively simple to use, contain between two to three parameters, and mimic closely the empirical FDCs of 430 catchments of the MOPEX data set. We then relate the calibrated parameter values of these models to physical and climatological characteristics of the watershed using multivariate linear regression analysis, and evaluate the regionalization potential of our proposed models against those of the literature. If quality of fit is of main importance then the 3-parameter van Genuchten model is preferred, whereas the 2-parameter lognormal, 3-parameter GEV and generalized Pareto models show greater promise for regionalization.

A study on the saturation degree dependency of the seismic behaviour of retaining walls

Retaining walls are important geotechnical structures that are often used in soil slopes and trenches to bring ground surface at appropriate level for the construction of roads, highways and buildings. It is common practice to assume that the soil behind a retaining structure is either fully saturated or completely dry. However, for the case the soil is partially saturated, mechanical behaviour of the soil above the water table is different than that of the dry soil. Thus, it is necessary to investigate the effect of the variations of degree of saturation on lateral pressure behind retaining walls. In this research, the seismic behaviour of unsaturated soils behind a retaining structure is analysed. A finite difference code was employed to conduct the necessary analyses and a series of equivalent linear analyses is performed to reveal the effect of the degree of saturation on the general response of the retaining structures. The required functions for unsaturated zone were defined and implemented in the code. For this purpose, a soil water retention function was employed and the soil shear modulus is assumed to vary with the mean effective stress for both saturated and unsaturated zones which naturally introduces the required hydro-mechanical coupling in unsaturated and saturated zone. The results of the analyses compared to the conventional methods which does not include the unsaturated mechanical properties, indicate that in the unsaturated state, the increase in the effective stress, and hence, the shear modulus considerably affects the seismic forces on the retaining wall.