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Hydraulic conductivity determination by infiltration models in unsaturated soils overlying shallow groundwater regimes
Abstract
The hydraulic conductivity (k) of unsaturated soil overlying shallow groundwater was measured based on a new hydrologic theory with a higher accuracy and greater convenience. The hydraulic conductivity was obtained via the average accumulated water depth after a period longer than 24 h based on infiltration capacity data extension of the Horton and power law infiltration models considering the infiltration rate curve (IRC). The theory basically relies on a mathematical derivation of Darcy’s law and experimental tests. The field tests included double-ring infiltrometer tests, measurements of the groundwater depth, and collection of 26 undisturbed soil samples within a 67-km2 area. Soil samples were selected with the Global Positioning System (GPS) and Geographic information system (GIS) to cover most of the area within the Mesopotamian region, which consists of Quaternary deposits in Hashymia, Central Iraq, whereas the lab tests included traditional k measurement methods. Statistical analysis was performed to estimate the convergence between the hydraulic conductivity values kIRC and klab obtained by IRC and traditional tests, respectively. Statistically, the root-mean-square error (RMSE) was considered to determine the convergence constant (£). The most precise kIRC values were obtained as the product of the final infiltration rate (fc) and £ = 1.15, which is associated with RMSE value of 0.104. The kIRC values were also compared to the obtained kLab values. It was concluded that the kIRC values greatly converged to the lab-measured hydraulic conductivity (klab), resulting in a correlation factor R2of 0.949. It was finally concluded, for any soil overlying shallow groundwater, that the k value is equal to 1.15fc.
... Furthermore, the water infiltrates slowly and eventually reaches a steady level which is called the basic infiltration rate [14]. The application of the ring infiltrometer method is commonly used to measure the infiltration rate of the soil to the unsaturated zone boundary above the shallow groundwater table and land cover [15,16]. ...
The rapid development and growth of Purwokerto requires greater groundwater resources. Research on groundwater vulnerability in Purwokerto is important in order to maintain groundwater resources, sustainability and development of the city. The approach or methods used in this research were: groundwater level measurement, geoelectric survey, and infiltration rate measurement to calculate the aquifer vulnerability index or AVI. This research uses soil infiltration rate data from the surface to a certain depth and the hydraulic conductivity of the lithologies located below the soil. The application of soil infiltration rate data and lithological hydraulic conductivity located below the soil provides a more continuous AVI level without any level voids than solely using lithological hydraulic conductivity data in the previous study. The AVI level of Purwokerto area ranges from low, moderate, high to extremely high. The level of AVI vulnerability in the lithology of the Slamet Volcano Lahar Deposits and Alluvium or its weathered soil is more varied than the lithology of the Tapak Formation and its weathered soil. This is thought to be related to variations in the composition of the components that make up each lithology which causes variations in weathering and AVI levels.
... The amount of water supplied, the duration of irrigation, the physical, chemical, and biological characteristics of the soil and water, temperature, topography, divergence, and accumulation of hydraulic characters in the soil profile, as well as migrating processes, all have an impact on the complex process of infiltration. Estimating infiltration experimentally is a challenging, expensive, labor-intensive and prolonged time-consuming process (Lakzian et al. 2010;Emami et al. 2012;Kalkhajeh et al. 2012;Adeniji et al. 2013;Fereshte 2014;Angelaki et al 2021a;Jabbar et al. 2021;Sepahvand et al. 2021;Pandhiani 2022). To determine the cumulative infiltration and infiltration rate of the soil from easily measurable soil parameters, indirect techniques based on predictive approaches are developed (Schuh and Bauder 1986). ...
The design and assessment of sustainable irrigation systems heavily rely on infiltration models. This study aims to assess the performance of different infiltration models for estimating the infiltration rate of the soil under different soil and land use conditions. The experiment was conducted in the field for measuring the infiltration rate using double-ring infiltrometer instrument. Using data from field infiltration tests, some well-known infiltration models, like Horton's, Philip’s, Kostiakov’s, and Green–Ampt, were developed. The performance of the developed models was evaluated using the R² value. The constant infiltration rate of the forest, hard surface, cultivated and barren land was found to be 6 cm/h, 1.36 cm/h, 2.4 cm/h and 1.153 cm/h, respectively. Here, it was discovered that Horton's model outperforms other models for predicting infiltration rate for the forest, hard surface, and cultivated land with the R² values of 0.9884, 0.935, and 0.98, respectively. Kostiakov’s model outperformed all other models in barren land for the prediction of infiltration rate with the R² value of 0.9706. Green–Ampt’s model performed worse than all other models under different soil and land-use conditions for the prediction of infiltration rate. The developed models will be useful for designing irrigation systems and modeling hydrological processes in the study area.
Research on the spatial variability of loess permeability is important for revealing the uncertainty of groundwater flow in loess areas and improving water resource protection measures. The Jing River and Gan River watersheds in northwest China were selected as a typical study area in this study to explore the spatial variability of soil permeability in the loess areas. A total of 48 infiltration tests were performed within the study area and hydraulic conductivity coefficients were calculated at each point. Statistical and geostatistical methods were employed to analyse the spatial variability of hydraulic conductivity in the study area and the influencing factors such as irrigation activity, land use types, and topography. The IDW method was used for spatial interpolation of hydraulic conductivity. The results revealed that the hydraulic conductivity in the study area ranged from 0.16 to 5.93 m/d and generally exhibited higher values in the northeast and lower values in the southwest. Irrigation had a weak impact on soil permeability, while land use type and topography had a more significant influence. Specifically, wild ground areas had the smallest mean hydraulic conductivity value of 0.786 m/d, while grassland areas had the largest mean hydraulic conductivity value of 2.302 m/d. Regarding topography, slope exhibited a positive correlation with hydraulic conductivity, with a Pearson correlation coefficient of 0.894, while elevation had no significant effect. The findings of this study can serve as a theoretical foundation for subsequent measures related to water environmental protection and management, as well as soil erosion prevention and control.
According to the theoretical concept, the infiltration rate gradually decreases as the shallow groundwater rises to the surface of unsaturated soil regardless of the hydraulic conductivity value. It is expected to decrease to the least when the shallow groundwater level reaches the soil surface and the soil is waterlogged. For this, a deep infiltration test was conducted for four types namely as; (soil no.1: sandy clay, soils no.2, 3 and 4: clayey sand) in the laboratory by means of the infiltration box, in which the amount of infiltration is measured with the hypothetical depth of shallow groundwater. In addition, a site test of infiltration was carried out on a sandy clay field soil in the Abu-Gharaq area, west of Babylon Governorate, Iraq, by means of an infiltration square trench with dimensions of 3 m * 3 m * 2.5 m depth. The trench is connected to a drainage ditch by pipes of 3 inches in diameter for removing excess water to maintain constant artificial groundwater. The results showed that the amount of accumulated infiltration depth increases with increasing shallow groundwater depth and k of unsaturated soil zone. The mathematical relationship between them is linear with a correlation coefficient of more than 0.99. Soil texture did not affect the amount of penetration as much as the depth of groundwater.
This study presents experimental investigation of indigenous clays mixed with Bentonite to assess their suitability in potential use as clay liners. Soil samples with 0, 4, 8, and 12% Bentonite content from three different sites in Peshawar region were tested for various geotechnical properties. Grain size distribution, specific gravity, Atterberg limits and free swell were found through laboratory tests using appropriate ASTM procedures. Maximum dry density and optimum moisture content were calculated using Atterberg limits in available relationships. Finally, one dimensional consolidation tests were conducted to find relevant parameters for calculating hydraulic conductivity. A decrease in specific gravity, increase in free swell, and in optimum moisture content, decline in maximum dry density and hydraulic conductivity was observed with increase in Bentonite content across all three soil samples. During free swell, the soil clusters become larger leading to formation of floccules resulting in the narrowing of inter-particle space and thus blocking of permeable paths. It is concluded that 8% Bentonite content by weight yields a suitable mixture for a clay liner that has hydraulic conductivity in the range of recommended limits.
Agricultural and livestock farms are the major sources of freshwater pollution in rural areas in the Philippines. Small and unregulated dairy farms operate without appropriate wastewater treatment before discharge because it is too expensive to do so. With this scenario, the emergence of the need for a sustainable and cheaper alternative for wastewater treatment gave rise to the research and development studies of the efficiency of constructed wetlands. The study aims to analyze the treatment efficiency of series type vertical subsurface flow constructed wetlands planted with Napier Grass (Pennisetum Purpureum Schumach) on University of the Philippines Los Baños (UPLB) Dairy Farm wastewater with a focus on fecal coliform concentration, electric conductivity, total dissolved solids content, nitrite and nitrate concentration and pH level. The study showed that after treatment using the vertical subsurface flow constructed wetlands, all the parameters except the fecal coliform concentration were below the standard limits set by the Department of Agriculture with average removal efficiencies of 12.94% on Electric Conductivity (EC), 12.86% on Total Dissolved Solids (TDS), 216.44% on Nitrite (NO2-N), -125.64% on Nitrate (NO3-N), and -25.64% on Fecal Coliforms (FC). With the results of the analysis, a design of series type vertical subsurface flow constructed wetland for dairy farm wastewater treatment is suggested. Doi: 10.28991/cej-2021-03091654 Full Text: PDF
Recently, the DSSs application is strongly increasing in the agricultural sector due to continuous climate changes and the need to conduct more productive and sustainable agriculture. In this paper, we describe the prototype agricultural DSS LANDS developed for monitoring the main crop productions in Sardinia. The DSS collects, organizes, integrates, and analyses several types of data with different mathematical models. In particular, a case study on forecasting potato late blight is presented. We employed the Negative Prognosis model and Fry model to forecast the period in which it is opportune to carry out fungicide treatments useful against the appearance of the pathogen. The experiments allowed to outline the best criteria for local conditions as well as the evaluation showed the effectiveness of the approach in a concrete case study.
Determination of recharge from precipitation and its distribution in karst areas is of great importance in water budget calculations. Several multi-parameter weighting-rating methods have been proposed to determine the recharge into karst aquifers; one of the most precise methods used in this field is the KARSTLOP. It is always necessary that the weight of recharge estimation method becomes calibrated by new techniques due to the diversity conditions of each area. Therefore, in this study, the analytical hierarchy process (AHP) technique has been used as a powerful decision-helping subjective tool. Using this method, the weights of the original KARSTLOP method were modified and improved based on the comments from water experts in the area. The mean annual recharge in the study area was 27.5% and 34.5% for the KARSTLOP-AHO and KARSTLOP methods, respectively. The results of KARSTLOP–AHP method are in accordance with the discharge of selected springs in the study area and budget reports.
Purpose
Infiltration modeling is an important tool to describe the process of water infiltration in the soil. However, direct measurements of the parameters of infiltration models are usually time-consuming and laborious. The present study proposed an effective method to estimate parameters of the Kostiakov-Lewis model (a classical infiltration model) from soil physical properties (SPPs).
Materials and methods
Parameters k, α, and f0 of the Kostiakov-Lewis infiltration models were measured in 240 double-ring field experiments in Shanxi Province, China. SPPs at the corresponding experimental points were measured at the topsoil layer (TL, 0–20 cm) and the top-subsoil layer (TSL, 0–20 and 20–40 cm). The Kennard-Stone (KS) sampling method and principal component analysis (PCA) were used for dividing training samples and extracting principal components (PCs) of SPPs, respectively. Partial least squares (PLS), back-propagation neural networks (BPNNs), and a support vector machine (SVM) were used to establish models for estimating k, α, and f0 with the SPPs of TL and TSL as the input variables (IV).
Results and discussion
The differences in soil density (BD), texture, and moisture content (θv) were found in topsoil and subsoil, but loading distributions of SPPs on PCs present different degrees of correlation. Moreover, SVM produced the most accurate estimation among these three methods for using the SPP of TL and TSL as inputs. The highest accuracy for k estimations was obtained by SVM using the SPP of TL as IV; R and RMSE in the model test process were 0.78 and 0.3 cm min⁻¹, respectively. However, using SPP of TSL as IV obtained the highest accuracy for both α and f0 estimations with the SVM method (R values were 0.71 and 0.82, respectively, and RMSE values were 0.03 and 0.018 cm min⁻¹) in the model testing.
Conclusions
The SVM method with SPPs as inputs is an effective and practical method for estimating the parameters of the Kostiakov-Lewis infiltration model.
The drawbacks of Horton model for infiltration potential estimate in arid regions are a serious problem the hydrologists are facing. Horton model is inapplicable in regions of initial rainfall intensities less than initial infiltration capacity of soils as basically outlined by Horton. Four infiltration models including Horton are adopted to evaluate their validity for infiltration potential estimate namely as Horton, power, polynomial, and mixed fitting models. Infiltration field measurements by double ring infiltrometer, and geotechnical investigations for soils to estimating infiltration rate, specific gravity, and bulk density were conducted at Hashimiya area of 110 km². The entire area was divided into nine administrative sectors namely as Jerboeyia, Hashyimia, Niwedra, Tebra, Sada, Zineyia, H3, Fayadhiya, and Bazul due to spatial hydrology. Geologically, the area consists of Mesopotamian plain which comprises the recent river sediments of Tigris and Euphrates, which consists of silts and clays and stacked river channel sands with occasional marsh deposits. The power model offers best fit to the measured infiltration with correlation coefficient of 0.996, whereas polynomial, mixed fitting, and Horton models offer 0.947, 0.958, and 0.84 respectively. Moreover, Horton model offers less infiltration potentials for both dry and wet seasons of 3 and 1 mm/day causing a rise in the average groundwater levels equal to 8.4 and 2.8 mm/day respectively. Similarly, the average infiltration potentials estimated by power model for both dry and wet seasons were 3.55 and 1.19 mm/day to rise in the average groundwater levels 9.88 and 3.31 mm/day respectively. These models create a paradigm for hydrology and environmental sustainability.
Characterizing soil hydraulic properties of the unsaturated zone is mandatory for reliable modeling of flow process and effective flood/drought modeling. The objective of this study is to evaluate infiltration characteristics of an area comprising of four different types of soils, namely, sand, loamy sand, loam and silt. A handy mini disk infiltrometer was used to determine cumulative infiltration based on which near saturated hydraulic conductivity values were determined. To verify its accuracy, simulations were carried out in HYDRUS 2D/3D which solves Richard’s equation by using Van Genuchten’s model. It is found that for loamy sand soil HYDRUS is giving quite appreciable results. However, for sandy and loamy soil, the numerically simulated results are underestimated whereas for silt soil the simulated results are overestimated when compared with the experimental results. This variability is mainly due to the variation in the parameters used for numerical simulation. Therefore, an inverse simulation was carried out using HYDRUS for getting the optimized values of the hydraulic parameters. Model performance is assessed by different statistics, such as correlation coefficient, the root mean square error, and the Nash-Sutcliffe efficiency index. HYDRUS is a software package for simulating water, heat, and solute movement in two- and three-dimensional variably saturated media. The software package consists of a computational computer program and an interactive graphics-based user interface.
During many tests on ground water sample that were carried out in the labs of Babylon environment directorate, Radon among many pollutants was encountered in concentrations exceeded the allowable limits according to WHO. Hashyimia unconfined aquifer with an area of about 100 Km 2 was found to be polluted with Radon (222 Rn) with concentrations exceed the maximum permitted value according to WHO (100 Bq/liter) in many locations. Preliminary tests with Alpha GUAR PQ2000 PRO, Alpha PUMP and Aqua KIT device of many GW samples reveal that their concentrations reach 113 Bq/liter after 3 hrs since a continuous pumping start. Geologically Hashyimia is consisted of a quaternary deposits of unconsolidated and finer grained of flood plains of the Euphrates River which mainly consist of clay, silt, sand and gypsum layers. A mathematical estimation of GW velocity (<1 cm/day) proved that 222 Rn origin is created by the local geologic formation of the aquifer and instantaneously the aquifer endures concentrations rise during the pumping process. It is found that the annual dosage reaches (453 SV year-1) with residence time of (12 day-1). A mathematical model has been designed to simulate and execute the theory of GW recirculationand purification against 222 Rn infection using the property of radon releasing during an exposure to air.The results indicates that 216 and 112 pumping and injecting wells are needed to recycle 100% strategic GW storage of the selected polluted sector respectively. It is concluded that 222 Rn is instantaneously produced by unknown source around the pumping well during a continuous pumping process and its concentration increases to a constant values.
This paper describes a new method (NSQE) to estimate soil hydraulic properties (sorptivity, S, and hydraulic conductivity, K) from full-time cumulative infiltration curves. The technique relies on an inverse procedure involving the quasi-exact equation of Haverkamp et al. (1994). The numerical resolution is described and the sensitivity of the method is theoretically evaluated, showing that the accuracy of the estimates depends on the measured infiltration time. A new procedure to detect and remove the effect of the contact sand layer on the cumulative infiltration curve is also given. The method was subsequently compared to the differentiated linearization procedure (DL), which calculate K and S from the simplified Haverkamp et al. (1994) equation, valid only for short to medium times. A total of 264 infiltration measurements performed with a 10cm diameter disc under different soil conditions were used. Compared to the DL procedure, field measurements showed that the NSQE method allowed better estimates of soil hydraulic properties, independently on the infiltration noise and the presence of contact sand layer. Overall, although comparable S values were estimated with both methods, the longer infiltration times allowed by the proposed method made this procedure more accurate estimations of K. In conclusion, the NSQE method have shown to be a significant advance to accurate estimate of the soil hydraulic properties form the transient water flow. (C) 2013 The Authors. Published by Elsevier B.V.
Both the root mean square error (RMSE) and the mean absolute error
(MAE) are regularly employed in model evaluation studies.
Willmott and Matsuura (2005) have suggested that the RMSE is not a good indicator
of average model performance and might be a misleading indicator of
average error, and thus the MAE would be a better metric for that
purpose.
While some concerns over using RMSE raised by Willmott and Matsuura (2005) and
Willmott et al. (2009) are valid, the proposed avoidance of RMSE
in favor of MAE is not the solution. Citing the aforementioned papers,
many researchers chose MAE over RMSE to present their model evaluation
statistics when presenting or adding the RMSE measures could be more beneficial.
In this technical note, we demonstrate that the RMSE is not
ambiguous in its meaning, contrary to what was claimed by
Willmott et al. (2009). The RMSE is more appropriate to represent model
performance than the MAE when the error distribution is expected to
be Gaussian. In addition, we show that the RMSE satisfies the
triangle inequality requirement for a distance metric, whereas
Willmott et al. (2009) indicated that the sums-of-squares-based
statistics do not satisfy this rule. In the end, we discussed
some circumstances where using the RMSE will be more beneficial.
However, we do not contend that the RMSE is superior over the MAE.
Instead, a combination of metrics, including but certainly not limited
to RMSEs and MAEs, are often required to assess model performance.
Several studies aimed at linking hydraulic conductivity at saturation (Kw,s) to air permeability (Ka(θw)) of soil at given water content (θw) since it can be measured more rapidly and nondestructively than Kw,s especially regarding some new in situ technologies for Ka(θw) measurement. Following this, the current research aimed to develop a semi-theoretical relation between Kw,s and Ka(θw) using measured data in 27 soil samples. The Ka(θw) was measured at 12 different θw contents between 1.5 to 1,500 kPa suctions. Applying these measured data, we proposed a semi-theoretical function to predict Kw,s using Ka(θw) as input variable. The results showed that the proposed function was able to predict Kw,s using Ka(θw) at any individual θw content with really high accuracy consisting of R2 = 0.986 and evaluating error (ER) of the 2% between measured and predicted Kw,s. However, the outcomes revealed that Ka(θw) measurement at lower θw contents resulted in greater accuracy for proposed model. The pertinent section of the article applied multivariate linear regression (MLR) to develop pedo-transfer functions (PTFs) to estimate the parameters of the proposed model. The results revealed that the developed PTFs had relatively greater accuracy and reliability showing average determination coefficient (R2) of 0.807 and 0.729 for training and test datasets, respectively. However, more detailed investigation with wide range of soil parameters are needed for more general PTFs development.
Estimation of soil sorptivity (S) and hydraulic conductivity (K) is fundamental to model the water infiltration into the soil. This process can be affected by soil water repellency, which is defined as a reduction in soil wettability due to coating of soil particles by hydrophobic substances. Unlike to wettable soils, this phenomenon can generate infiltration curves with double-slope shape: a transient infiltration curve followed by a steady-state section. Because the topsoil final volumetric water content (θ1) of the transient phase of the double-slope curve is not a measurable data, in principle, the standard model based on the Haverkamp et al. (1994) model cannot be used to estimate S and K. This work presents two different approaches based on the Haverkamp et al. (1994) equation, which allow estimating S and K from the first phase of a double-slope infiltration curve, when θ1 data are not available. The methods, which are based on the analysis of both short-medium time transient infiltration curve (Tr) and the combination of both short-medium transient and steady-state infiltration steps (Mx), were applied on 20 soils affected by different degrees of water repellency. The Haverkamp et al. (1994) model was also valid for infiltration curves measured on hydrophobic soils, and the final volumetric water content was not an essential data to estimate K and S. Although the steady-state infiltration rate (q1) calculated with Mx was about 26% larger than that estimated with Tr, comparable K and S values were obtained with both methods. Overall, a large dispersion on the estimate of θ1 was observed with both methods. The gravimetric time, tgrav, estimated in the studied soils was low, <500 s. While the Mx method required simpler numerical calculus, Tr looked like to be more robust and less subjective.
The quasi-exact implicit (QEI) analytical formulation of Haverkamp equation, which might be also known as Parlange model, and its one- and two-term approximate expansions are among the mostly used equations for in situ determination of soil sorptivity, S, and saturated hydraulic conductivity, Ks, from unsaturated one-dimensional (1D) cumulative infiltration into soils. However, from practical point of view, the approximate expansions are only valid from short to intermediate times and the QEI analytical formulation has a complex resolution, which makes its use complicated in inverting procedures. Therefore, alternative functions are needed to compute cumulative infiltration for longer times and improve inverting procedures for easier, more robust and accurate predictions of S and Ks. In this regard, current work presents and evaluates a new three-term approximation of the QEI analytical formulation. As a first step, we checked the accuracy of the proposed three-term approximate expansion with respect to the QEI formulation for three different soils (sand, loam and silt) in order to define its time domain validity. Next, the accuracy of the three-term approximate expansion to estimate S, Ks and the β parameter was compared to those obtained with one- and two-term approximate expansions. Lastly, a large dataset of field experimental data was inverted using the proposed three approximate expansions and the QEI analytical formulation, and goodness of fits predicted and measured cumulative infiltration curves and accuracy of the parameters (S, Ks and the β) estimates were compared. The results revealed that the three-term approximate has a larger validity time interval compared to one- and two-term approximate expansions, which allows its use for larger infiltration times durations resulting in more accurate estimates of Ks. Its capability of estimating S is also improved. The accurate prediction of β parameter is not still guaranteed for none of the approximate expansions. Compared to the one- and two-term approximate expansions, the experimental infiltration data usage revealed that the three-term approximate expansion resulted in higher performance and better prediction of hydraulic parameters.
In this paper, a model is proposed for the assessment of the effectiveness of various mulches in increasing deep percolation of rainfalls for enhancing arid zones aquifers. For this purpose, 8 precipitations were selected from the Intensity-Duration-Frequency (IDF) curves of the study area with a return period of 2 and 5 years. The deep percolation of these precipitations were examined in lysimeters with gravel, sand and mixed mulches and without any mulch. Then 192 data of soil moisture, daily maximum air-temperature and deep percolation were measured for driving empirical equations. Moreover, the efficiency and accuracy of these empirical equations were investigated using Coefficient of Determination (CD) and Nash–Sutcliffe Efficiency Coefficient (NSEC). The results showed that the obtained empirical equations could estimate deep percolation and evaporation with an acceptable accuracy. Using these equations and the soil-water balance equation, a soil moisture model was developed for the assessment of deep percolation. Then it was examined to evaluate the efficiency of the mulched soils in increasing soil moisture and aquifer recharging of three years’ precipitations in Shahrekord plain, Iran. The results showed that the deep percolation increased in all examined mulched soils compared to unmulched soil, its maximum and cumulative increase were in gravel mulch with 21.3% and 30%, respectively. Furthermore, groundwater modeling results showed that the mulching could improve groundwater level as 0.34 m over a three year period. Finally, this paper proposes soil mulching for enhancing groundwater resources and a model to assess it.
Infiltration measurements are important for the hydrological modelling of catchment. Different methodologies adopted for measurements exhibit variability in infiltration characterization, which needs to be studied in detail. This study compared the infiltration characteristics measured using double ring infiltrometer (DRI), mini-disc Infiltrometer (MDI) and tension disc infiltrometer (TI) for identical field conditions and two seasons within a river sub-catchment in north-east India. It was noted that the initial infiltration rate (ii) was highest and final infiltration rate (if) was lowest for DRI while in most of the cases it was comparable for disc infiltrometers. The study proposed normalized infiltration rate curves for alleviating instrument related variabilities for comparing infiltration measurements performed using different infiltrometers. A non-linear asymptotic curve adequately represent the normalized infiltration rate curve as compared to the Horton form of infiltration equation. Statistical evaluation of the measured results indicates that initial water content exhibits a negative correlation and particle size fraction have statistically insignificant correlation with hydraulic conductivity (Kh0) determined from infiltrometers. Further, Kh0 exhibited a positive correlation with all the infiltration characteristics with higher correlation coefficient for ii, and (ii − if). The Kh0 determined by disc infiltrometers (MDI and TI) are found to be approximately two-thirds of DRI values. The study clearly demonstrates the usefulness of disc infiltrometers vis-à-vis DRI for rigorous and repeatable measurements for establishing near saturated infiltration characteristics at catchment scale.
Soil water infiltration can be described with the quasi-analytical Haverkamp et al. (1994) equation, defined by the hydraulic conductivity (Ks), sorptivity (S) and the β parameter. Ks and S are commonly estimated from the transient cumulative infiltration curve, using a constant β value. The objective of this work was to study the influence of β on the estimation of Ks and S. The study was first performed on synthetic 1-D infiltration curves generated at different infiltration times for loam sandy, loamy and silty soils, and next extrapolated to a 3-D loam synthetic soil and on 10 infiltrations curves measured on the field with a disc infiltrometer on different types of soils. The infiltration measurements lasted between 600 and 900 s. The results showed that, while early infiltration times (i.e. 100 s) promoted good estimations for S, longer infiltrations (i.e. 1.000 s) were required to estimate accurately Ks. Only very long infiltration (i.e. 10.000 s) allowed defining the actual β value. A similar behaviour was observed for the 3-D infiltration measurements. Except for β significant relationships (R² = 0.99) were obtained between the Ks and S of the three theoretical soils and the corresponding values calculated by optimizing the three hydraulic parameters on 2.000 s 1-D infiltration curves. The large confidence interval observed in β (between 0.3 and 2.0) resulted from the fact that β had a small effect on the infiltration curve. A significant relationship (R² = 0.99) was also obtained between the Ks and S optimized from the experimental curves using a β = 1.1 and the corresponding values obtained by simultaneous optimization of the three hydraulic parameters. These results demonstrated that S and Ks can be accurately estimated using a constant β and that downward infiltration is not an appropriate procedure to estimate β.
The aim of this study is to present an inverse modelling approach with a genetic algorithm for estimating soil hydraulic and solute transport parameters in two subsurface drainage systems in Iran. In this study, measured data were obtained from Amirkabir and Shoaybiyeh sugarcane fields equipped with subsurface drainage systems. The SWAP model was used for simulating the outputs of subsurface drainage systems. The accuracy of different objective functions which were based on the discrepancies between measured and simulated values of drainage discharge, groundwater depth and drainage water salinity was evaluated in the inverse modelling approach. Based on sensitivity analysis of the SWAP model in studied areas, n shape parameter, lateral hydraulic conductivity, depth to impermeable layer, saturated water content and α shape parameter were selected in the inverse modelling approach. By applying the objective function which is based on drainage discharge and salinity in the Amirkabir study area, the Nash–Sutcliffe Efficiency (NSE) values for predicting drainage discharge and salinity were 0.63 and 0.79, respectively. In the Shoaybiyeh study area, the objective function which includes drainage discharge, groundwater depth and drainage water salinity resulted in NSE values of 0.83, 0.95 and 0.89 for predicting drainage discharge, groundwater depth and drainage water salinity, respectively. Copyright © 2017 John Wiley & Sons, Ltd.
Even though soil is a mixture of solids with voids that are filled by air and water, most previous studies on rainfall infiltration and its influence on slope stability were based on a single-phase water flow model by assuming that the pore air pressure was atmospheric. The purpose of this study is to examine the effect of interactions between air and water flow due to heavy rainfall on the mechanical stability of an unsaturated soil slope. Water-air two-phase flow analyses were conducted to investigate the contribution of pore-air pressure on infiltration by rainfall. In order to study the infiltration behavior with respect to soil type, flow analyses were performed with two types of soil under similar settings. Results obtained from the two-phase infiltration analysis were then used as input to the stability analysis by the strength reduction method. Infiltration and stability analyses based on a single-phase water flow model were also carried out, which helped clarify the effects of air flow induced by rainfall infiltration on an unsaturated soil slope. The results showed an increase in pore air pressure during infiltration because rainwater displaced the air in the unsaturated zone; hence, remarkable delaying effects on water flow were induced. Such water-air interactions in the pore space of soil significantly affected the stability and behavior of the soil slope.
Previous research has indicated that the measurements of soil saturated hydraulic conductivity (K-s) are influenced by both the radial size and depth of a double-ring infiltrometer. Few studies are available, however, on how the depth to which an infiltrometer is driven affects K-s measurement. In this study, six inner ring depths (d(i) = 5, 10, 15, 25, 40, and 60 cm), six outer ring depths (d(o) = 5, 10, 15, 25, 40, and 60 cm), and their combinations were designed. Thus 24 sets of driven depths of infiltrometer were involved. For each infiltrometer set, 31 stochastic fields of K-s were randomly generated in the simulation domain by adopting six correlation lengths (L = 0, 10, 20, 50, 100, and 200 cm) and six standard deviations (SD = 0, 0.1, 0.25, 0.5, 0.75, and 1.0). Therefore, a total of 7224 simulations were conducted to investigate the driven-depth effect of the double-ring infiltrometer on the measurements of soil saturated hydraulic conductivity of the wetted zone (K-w). Results demonstrated that the inner ring depth plays a more important role than the outer ring depth in K-w measurements by double-ring infiltrometer, and increasing the inner ring depth could obtain a better approximation of accurate K-w measurements. Meanwhile, the outer ring added to a single-ring infiltrometer was necessary in guaranteeing vertical water flow in the inner ring and improving measurement accuracy. Considering that the disturbance of soil caused by ring installation will increase with increasing ring depth, the ring depth of 5 to 15 cm that has been adopted in most ring-infiltrometer-related field experiments is acceptable and recommended for K-w measurements.
Saturated hydraulic conductivity measurements are important for understanding and modeling hydrologic processes at the field scale. Few systematic studies have been conducted on how the size of double-ring infiltrometers affects the measured hydraulic conductivity. To determine this size effect, we measured saturated hydraulic conductivity at seven sites using four different sizes of double-ring infiltrometers. Inner-ring diameters, d(i), were 20, 40, 80, and 120 cm. Detailed numerical investigations were also conducted to explain how the inner-ring size of a double-ring infiltrorneter influences the measured hydraulic conductivity in a heterogeneous soil. Field and simulation results both demonstrated that the variability in measured hydraulic conductivity was greater for smaller inner rings (e.g., d(i) <40 cm), and gradually decreased as the ring size increased. Our study indicates that where soil spatial variability is high, infiltrometers having a large inner ring (in general, d(i) >80 cm) are essential for reliable measurement.
The double-ring infiltrometer is widely used to measure soil saturated hydraulic conductivity in the field. Both the inner ring size and outer ring size (two factors in the buffer index) of an infiltrometer affect the measurements of saturated hydraulic conductivity. Few systematic studies have been conducted to investigate the combined effects of the inner and outer ring sizes of a double-ring infiltrometer on the measurements of field saturated hydraulic conductivity. A total of 7224 numerical simulations were conducted to investigate the optimum combination of inner and outer ring sizes for reliable saturated hydraulic conductivity measurements by using 24 infiltrometers with six inner ring diameters (10, 20, 40, 80, 120, and 200 cm) and, for each ring diameter, four buffer indices (b = 0.2, 0.33, 0.5, and 0.71). Results demonstrated that the inner ring size is a more important factor to be considered than the buffer index itself (or the outer ring size) in practice, and a larger inner ring diameter assembled with an outer ring (in most cases, with diameter >= 80 cm and b >= 0.33) is recommended to obtain reliable in situ measurement of soil field saturated hydraulic conductivity.
Understanding infiltration processes is one of the fundamental points in the theory of drainage and irrigation engineering. The infiltration phenomenon has two limiting behaviors given by the two-parameter Green-Ampt and Talsma-Parlange equations. Both equations are unified to form a general three-parameter formula. The third parameter interpolates between these two limiting cases. This investigation attempts to find an explicit form of the generalized equation. The explicit equation is accurate, simple and easy to use in practical situations.
Mountainous soils usually contain a large number of rock fragments (particle diameter > 2 mm), which influence soil hydraulic and retention properties. Data characterizing the properties of these soils usually describe only the fine earth (particle diameter < 2 mm). To quantitatively describe soil water movement in stony soils, their most important characteristic, i.e., the effective saturated hydraulic conductivity (Kse), must be known. The objective of this study was to use a numerical method for estimating the saturated soil hydraulic conductivity that depends on relative stone content (stoniness), and sizes and shapes of stony parts. The method is based on a numerical version of the classical experiment of Darcy. The steady-state water flow under a unit hydraulic gradient through hypothetical soils containing stones was simulated using the two-dimensional simulation model HYDRUS-2D. Four soil textural types were considered. Special attention was paid to the moraine soil from the FIRE site in High Tatras. A relationship between the relative saturated hydraulic conductivity, Kr, and the relative stone content, Rv, was derived. Kr(Rv) function is decreasing slower for larger stones. Numerical results were used to propose an empirical equation to estimate Kr of soils containing rock fragments of a spherical shape of various diameters.
Previous mathematical developments of so-called two-term infiltration equations have been approximate instead of exact and thus provide little insight to account for any experimental shortcomings of such equations. In contrast, it is here shown that one form of two-term infiltration equations is obtainable by integration from an exact solution of the one-dimensional downward Richards equation subject to the customary initial and boundary conditions. The mathematical trial solution is a variables-separable combination of product and additive forms. Intrinsic to the solution are two further stipulations: (1) the unsaturated hydraulic conductivity function must be linear with the water content, and (2) the ponded-water head on the soil surface must increase as the square root of time from initial water application. The absence of both these stipulations in customary ponded-infiltration measurements thus accounts for why the two-term equation frequently fails experimentally. Nonetheless, the mathematical simplicity of the new solution makes it useful pedagogically.
Fourteen popular, representative infiltration models, some physically
based, some semi-empirical and some empirical, were selected for a
comparative evaluation. Using the Nash and Sutcliffe efficiency
criterion, the models were evaluated and compared for 243 sets of
infiltration data collected from field and laboratory tests conducted in
India and the USA on soils ranging from coarse sand to fine clay. Based
on a relative grading scale, the semi-empirical Singh-Yu general model,
Holtan model and Horton model were graded respectively as 6·52,
5·57 and 5·48 out of 10. The empirical Huggins and Monke
model, modified Kostiakov and Kostiakov model were graded as
5·57, 5·30 and 5·22, respectively. The physically
based non-linear and linear models of Smith-Parlange were graded as
5·48 and 5·22, respectively. Other models were ranked
lower than these models. All the models generally performed poorly in
field tests on Georgia's sandy soils, except the Robertsdale loamy sand.
Copyright
In many vadose zone hydrological studies, it is imperative that the soil's unsaturated hydraulic conductivity is known. Frequently, the Mualem-van Genuchten model (MVG) is used for this purpose because it allows prediction of unsaturated hydraulic conductivity from water retention parameters. For this and similar equations, it is often assumed that a measured saturated hydraulic conductivity (K(s)) can be used as a matching point (K(o)) while a factor S(c)/(L) is used to account for pore connectivity and tortuosity (where S(e) is the relative saturation and L = 0.5). We used a data set of 235 soil samples with retention and unsaturated hydraulic conductivity data to test and improve predictions with the MVG equation. The standard practice of using K(o) = K(s) and L = 0.5 resulted in a root mean square error for log(K) (RMSE(K)) of 1.31. Optimization of the matching point (K(o)) and L to the hydraulic conductivity data yielded a RMSE(K) of 0.41. The fitted K(o) were, on average, about one order of magnitude smaller than measured K(s). Furthermore, L was predominantly negative, casting doubt that the MVG can be interpreted in a physical way. Spearman rank correlations showed that both K(o) and L were related to van Genuchten water retention parameters and neural network analyses confirmed that K(o) and L could indeed be predicted in this way. The corresponding RMSE(K) was 0.84, which was half an order of magnitude better than the traditional MVG model. Bulk density and textural parameters were poor predictors while addition of K(s) improved the RMSE(K) only marginally. Bootstrap analysis showed that the uncertainty in predicted unsaturated hydraulic conductivity was about one order of magnitude near saturation and larger at lower water contents.
Disk infiltrometers are established as standard devices for measuring soil surface hydraulic properties. This study explored the validity of a semiempirical approach that is used to obtain estimates of the near-saturated hydraulic conductivity from disk infiltrometer data. The approach was compared with two other estimation expressions. The analysis was based on three-dimensional numerical modeling of the infiltration process, i.e., on synthetic data. The results of the validation procedure showed that the original expression performed best among the compared methods, but still failed for fine-textured soils and the selected Cambisols. This is due to the overwhelming importance of lateral soil water movement by capillarity, which is not adequately addressed by any of the models. The study showed that improved estimates, specifically for fine-textured soils and Cambisols and for small infiltrometer radii (minidisks), can be obtained by extending the original approach. This is achieved primarily (i) by using the modified van Genuchten parameterization of soil hydraulic functions instead of the original one, and (ii) by including a more representative set of soils in the objective function when optimizing the estimation formula.
In conclusion, we have to acknowledge our indebtedness to Professors T. R. Lyle and R. J. A. Barnard for valuable advice and suggestions and to the Victorian Government for financial assistance towards the expenses of this research.
Studies on soil physics
- W H Green
- G A Amb
- WH Green
Towards Bayesian quantification of permeability in micro-scale porous structures-the database of micro networks
- B Fazelabdolabadi
- M H Golestan
Estimation of near-saturated hydraulic conductivity values using a mini disc infiltrometer
- G Kargas
- P A Londra
- J D Valiantzas