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![The unsaturated hydraulic conductivity [K(θ)] is a nonlinear function
of both moisture content and matric suction
coarse- (solid line), medium- (dashed line), and fine-textured (dotted line) soils
van Genuchten and Pachepsky, 2006](https://image.slidesharecdn.com/bappaunsaturated-221118052837-be9cc7e8/75/Unsaturated-hydraulic-conductivity-of-soil-3-2048.jpg)
![The infiltration method is based on the principle that at t→∞, the
steady rate of inflow into a soil (q) tends to be equal to K(θ)
[q→K(θ)] for homogeneous moisture content of soil profile (θ0)
Davidson et al., 1963; Youngs, 1964
Infiltration method](https://image.slidesharecdn.com/bappaunsaturated-221118052837-be9cc7e8/75/Unsaturated-hydraulic-conductivity-of-soil-5-2048.jpg)
![1) The Van Genuchten Functions
θ(Ψ) = θr + (θs – θr)/[1+ (𝜶Ψ)n]1-1/n
θ(ψ) - the measured volumetric water content (cm3 cm-3) at suction ψ
(cm)
θr and θs - residual and saturation moisture content, respectively
𝜶(cm-1) - related to the inverse of air entry suction
n – dimensionless parameter
K(Se)= KO 𝑺𝒆
𝑳 { 1- [1- 𝑺𝒆
𝒏/(𝒏−𝟏)
]1-1/n }
Se = θ(Ψ) - θr /(θs – θr)
Ko (cm d-1) - a fitted matching point at saturation which is similar but not
necessarily equal to saturated hydraulic conductivity, Ks
L - an empirical parameter Van Genuchten (1980)](https://image.slidesharecdn.com/bappaunsaturated-221118052837-be9cc7e8/75/Unsaturated-hydraulic-conductivity-of-soil-18-2048.jpg)
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Similar to Unsaturated hydraulic conductivity of soil
Unsaturated hydraulic conductivity of soil
- 1. Characterization of unsaturatedhydraulic conductivity of structured porous media Bappa Das Roll No.- 10085 Division of Agricultural Physics I.A.R.I., New Delhi-12
- 2. Knowledge of thesoil hydraulic conductivity (K) vs. pressure head (h) relationship is important for characterizing many aspects of unsaturated water flow such as Rainfall partition between infiltration and runoff, Aquifer recharge, Migration of nutrients, pesticides and contaminants through the soil profile, Design and monitoring of irrigation and drainage systems (Reynolds, 1993; Hillel, 1998). The hydraulic conductivity of near-saturated soil is critically important since the water flux and solute transport are highest in near-saturated soils.
- 3. The unsaturated hydraulicconductivity [K(θ)] is a nonlinear function of both moisture content and matric suction coarse- (solid line), medium- (dashed line), and fine-textured (dotted line) soils van Genuchten and Pachepsky, 2006
- 4. Characterization of UnsaturatedHydraulic Conductivity Infiltration method Pressure outflow method Boltzmann Transform Method Internal drainage method Crust-Topped method Sprinkler method Unsaturated Hydraulic Conductivity
- 5. The infiltration methodis based on the principle that at t→∞, the steady rate of inflow into a soil (q) tends to be equal to K(θ) [q→K(θ)] for homogeneous moisture content of soil profile (θ0) Davidson et al., 1963; Youngs, 1964 Infiltration method
- 6. The pressureoutflow method determines the relationship between ψm and θ by subjecting a saturated soil core to successive increments of applied pneumatic pressure P. The increments in pressure heads are kept small so that D can be assumed constant over the change in θ due to change in ψm. Gardner (1956) solved the diffusion form of the Richards equation and gave the following solution for θ vs D relationship and K(θ) determination 𝒍𝒏 𝑽𝟎 − 𝑽𝒕 = 𝒍𝒏 𝟖𝑽𝟎 𝝅𝟐 − 𝝅𝟐𝑫 𝜽 𝒕 𝟒𝑳𝟐 𝑲 𝜽 = 𝑫(𝜽)𝑽𝟎𝝆𝒘𝒈 𝑽𝒔∆𝑷 where V0 is the total outflow volume of water, Vs is the total volume of soil in the core, Vt the outflow volume at time t, L is the length of sample, and ΔP is air pressure difference. 𝑫 𝜽 = − 𝟒𝑳𝟐 𝝅𝟐(𝜽𝒕 − 𝜽𝒇) 𝒅𝜽𝒕 𝒅𝒕 Pressure outflow method
- 7. The sprinklermethod, or sprinkler infiltrometer method, makes a uniform application of water on the soil surface. Water is applied at a rate slightly lower than the effective hydraulic conductivity (Ke) of the soil. Eventually it establishes a steady moisture distribution in the conducting profile. Once steady-state conditions are established, a constant flux exists. Under this situation flux through soil profile is essentially equal to the hydraulic conductivity of soil. The experiment can be repeated for different steady rates of water application and corresponding values of ψm and θ can be obtained. Sprinkler method Peterson and Bubenzer, 1986
- 8. It requiresrather elaborate equipment, which must be maintained in continuous operation for long periods of time. Avoidance of the raindrop impact effect, which can cause the exposed surface soil to disperse and seal, thus reducing infiltrability. Presence of soil layers that might impede flow, thus preventing the attainment throughout the profile of a condition of a zero matric suction gradient. The field plot should normally be at least 1 m2 in size and be surrounded by a buffer area under the same sprinkling so as to minimize the lateral flow component in the test plot. Peterson and Bubenzer, 1986 Disadvantages
- 9. The crust-toppedmethod employs a less permeable crust of topsoil, which reduces the flux density, soil wetness, and corresponding K(θ) and D(θ) values of the infiltrating profile due to the steep hydraulic gradient across the less permeable crust of topsoil. The impeding layer induces the suction in the subsoil, which increases with the increasing hydraulic resistance of the crust. Once steady infiltration is established, flux and conductivity of subsoil becomes equal. The ψm and θ can also be measured simultaneously using tensiometer and nondestructive moisture content measurement device. This method can work for a wide range of ψm and θ measurements, thus eliminating the range limitation of the sprinkler method. For very high suctions, the measurements may take long time and accurate measurement of flux may become difficult to achieve. Crust-Topped method Hillel and Gardner, 1970
- 10. The methodrequires frequent and simultaneous measurements of the soil wetness and matric suction profiles under conditions of drainage alone (evapotranspiration prevented). From these measurements it is possible to obtain instantaneous values of the potential gradients and fluxes operating within the profile and hence also of hydraulic conductivity. To apply this method in the field, a fallow plot that is large enough so that processes at its center are unaffected by the boundaries should be choosen. Within this plot, at least one neutron access tube is installed through and below the root zone. A series of tensiometers is installed at various depths near the access tube so as to represent profile horizons. Water is then ponded on the surface and the plot is irrigated long enough so that the entire profile becomes as wet as it can be. Internal drainage method Watson, 1966
- 11. After this,the soil surface is covered by an opaque (preferably white) plastic sheet so as to minimize soil heating and to prevent evaporation from the soil surface. As internal drainage proceeds, periodic measurements are made of distribution and tension of soil moisture throughout the profile. Advantages The only instruments required are a neutron moisture meter (or some other nondestructive method for repeated determination of the soil moisture profile) and a set of tensiometers. Moreover, the method does not assume previous knowledge of the soil-moisture characteristic (matric suction versus water content) and in fact can yield information on this function in situ. Disadvantages In practice, the moisture range for which conductivity can be measured by the internal drainage method is generally limited to suctions not exceeding about 0.5 bar. The internal drainage method can yield reliable results only if the profile drains vertically. It is likely to fail where the profile contains slanted layers and the flow regime is partly lateral. Watson, 1966
- 12. It would bedesirable to determine all necessary data by direct measurements, but often this is impossible for one or more of the following reasons 1. The measurements are costly and time-consuming 2. The hydraulic properties of soil are of hysteretical nature. Different relationships prevail for wetting and drying processes and the actual relationships between K, ψ and θ depend upon the preceding history 3. The soil variability is such that the amount of data required to represent the hydraulic properties accurately is enormous 4. The available experimental data can not represent the complete relationships describing the hydraulic properties. To replace missing information several empirical, semi-empirical or theoretical models have been applied Problems associated with direct measurements Klute and Dirksen, 1986
- 13. Jackson (1972) gavethe following formulation Ki = Ks θi θs 𝒄 𝒋=𝒊 𝒎 𝟐j + 𝟏 − 𝟐i 𝝍j −𝟐 𝒋=𝟏 𝒎 𝟐j − 𝟏 𝝍j −𝟐 where Ki - the hydraulic conductivity at a moisture content of θi (cm s-1), Ks - the saturated hydraulic conductivity (cm s-1) θs - the saturated moisture content (cm3 cm-3) m - the number of increments of θ, ψj - the suction head at the mid-point of each of θ increment (cm), and C - an arbitrary factor which is reported to be 0–4/3 Jackson Method
- 14. Soil Depth: 30-60cm y = 3.6188x-3.3244 R2 = 0.9862 0 2000 4000 6000 8000 10000 12000 14000 16000 0 0.1 0.2 0.3 0.4 Soil Moisture Content (cm 3 /cm-3 of soil) Soil moisture Suction (cm) Soil Depth: 60-90 cm y = 3.4323x-3.6313 R2 = 0.9876 0 2000 4000 6000 8000 10000 12000 14000 16000 0 0.1 0.2 0.3 0.4 Soil Moisture Content (cm 3 /cm-3 of soil) Soil moisture Suction (cm) Soil Depth: 0-15 cm y = 5.1352x-3.131 R2 = 0.9763 0 2000 4000 6000 8000 10000 12000 14000 16000 0 0.1 0.2 0.3 0.4 Soil Moisture Content (cm 3 /cm-3 of soil) Soil moisture Suction (cm) Soil Depth: 15-30 cm y = 3.231x-3.3954 R2 = 0.9652 0 2000 4000 6000 8000 10000 12000 14000 16000 0 0.1 0.2 0.3 0.4 Soil Moisture Content (cm3 /cm-3 of soil) Soil moisture Suction (cm) Soil Depth: 90-120 cm y = 1.9604x-4.083 R2 = 0.9834 0 2000 4000 6000 8000 10000 12000 14000 16000 0 0.1 0.2 0.3 0.4 Soil Moisture Content (cm 3 /cm-3 of soil) Soil moisture Suction (cm) Relation between soil moisture suction (cm) and content (cm3 cm-3) Estimated Moisture Retention Curves Chattaraj et al. (2013)
- 15. Pore class iVolumetric wetness θi Matric suction head (cm) (ψj at θ interval midpoint) Pore class increment number j Denominator index 2j-1 1 0.40 10 1 1 2 0.38 22 2 3 3 0.36 24 3 5 4 0.34 27 4 7 5 0.32 30 5 9 6 0.30 32.5 6 11 7 0.28 36 7 13 8 0.26 40 8 15 9 0.24 44 9 17 10 0.22 49 10 19 11 0.20 56 11 21 12 0.18 62 12 23 13 0.16 72 13 25 14 0.14 88 14 27 15 0.12 110 15 29 16 0.10 140 16 31 17 0.08 200 17 33 18 0.06 330 18 35 19 0.04 750 19 37 20 0.02 4500 20 39
- 16. Soil Depth: 0-15cm y = 4.0862Ln(x) + 5.2548 R2 = 0.9993 -5.00 -4.00 -3.00 -2.00 -1.00 0.00 1.00 2.00 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 Volumetric Wetness, θi (cm3 /cm-3 of soil) Log (K i ), (cm day -1 ) Soil Depth: 15-30 cm y = 4.3743Ln(x) + 5.4152 R2 = 0.9997 -5.00 -4.00 -3.00 -2.00 -1.00 0.00 1.00 2.00 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 Volumetric Wetness, θi (cm3 /cm-3 of soil) Log (K i ), (cm day -1 ) Soil Depth: 30-60 cm y = 4.3168Ln(x) + 5.3006 R2 = 0.9996 -5.00 -4.00 -3.00 -2.00 -1.00 0.00 1.00 2.00 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 Volumetric Wetness, θi (cm3 /cm-3 of soil) Log (K i ), (cm day -1 ) Soil Depth: 60-90 cm y = 4.9214Ln(x) + 5.6805 R2 = 0.9999 -6.00 -5.00 -4.00 -3.00 -2.00 -1.00 0.00 1.00 2.00 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 Volumetric Wetness, θi (cm3 /cm-3 of soil) Log (K i ), (cm day -1 ) Soil Depth: 90-120 cm y = 4.5111Ln(x) + 5.2074 R2 = 0.9998 -6.00 -5.00 -4.00 -3.00 -2.00 -1.00 0.00 1.00 2.00 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 Volumetric Wetness, θi (cm3 /cm-3 of soil) Log (K i ), (cm day -1 ) Relations between logarithm of unsaturated hydraulic conductivity (Ki, cm day-1) and volumetric wetness (θi, cm3 cm-3) Estimated Moisture Retention Curves Chattaraj et al. (2013)
- 17. Manyame et al.(2007) Study Area: Bagoua village in SW Niger Soil Properties: Water retention and Unsaturated hydraulic conductivity PTFs: a) van Genuchten (1980) model b) Campbell (1998) model c) Vauclin (1983) model Measured Properties: Particle size distribution (PSD), Bulk density (BD)
- 18. 1) The VanGenuchten Functions θ(Ψ) = θr + (θs – θr)/[1+ (𝜶Ψ)n]1-1/n θ(ψ) - the measured volumetric water content (cm3 cm-3) at suction ψ (cm) θr and θs - residual and saturation moisture content, respectively 𝜶(cm-1) - related to the inverse of air entry suction n – dimensionless parameter K(Se)= KO 𝑺𝒆 𝑳 { 1- [1- 𝑺𝒆 𝒏/(𝒏−𝟏) ]1-1/n } Se = θ(Ψ) - θr /(θs – θr) Ko (cm d-1) - a fitted matching point at saturation which is similar but not necessarily equal to saturated hydraulic conductivity, Ks L - an empirical parameter Van Genuchten (1980)
- 19. 2) The CampbellModels Cambell and Norman (1998) Ψm = Ψe(θ / θs)-b θ - volumetric water content (m3 m-3) θs - the saturation water content (m3 m-3) ψm and ψe (-j kg-1) - soil matric potential and air entry water potential, respectively b - the slope of loge ψm vs. loge θ curve K(θ)= Ks (θ/ θs)2b+3 K(θ) and Ks - unsaturated and saturated hydraulic conductivities, respectively
- 20. Vauclin et al.(1983) 3) The Vauclin Model K(θ)= Ko (θ/ θo)β K(θ) (cm h-1) - the hydraulic conductivity at moisture content θ (m3 m-3) Ko (cm h-1) - the hydraulic conductivity at final infiltration β - a dimensionless shape parameter θo (m3 m-3) - the apparent saturated soil moisture content at final infiltration Ko = 28.42 – 1.534 (Clay + Fine Silt) β= 3.67 + 0.437 (Clay + Fine Silt) Ko is in cm h-1 Clay is the clay content (<2.0 μm fraction, %) Fine Silt is the fine silt content (2.0 to 20.0 μm fraction, %)
- 21. - BD andPSD were determined in the soil samples - Van Genuchten parameters from ROSETTA software using BD and PSD - Campbell parameters from SOILPAR software using Campbell PTFs and BD and PSD data - Vauclin parameters from the Vauclin proposed equations Manyame et al. (2007)
- 22. Depth (cm) 0-3030-60 >60 Soil property Sand (g kg-1) 941.5 926.7 934.0 Silt (g kg-1) 22.4 19.1 19.0 Clay (g kg-1) 36.1 54.2 47.0 Bulk Density (g cm-3) 1.58 1.53 1.46 van Genuchten θr (cm3cm-3) 0.05 0.06 0.06 θs (cm3cm-3) 0.36 0.38 0.40 α (cm-1) 0.03 0.03 0.03 L 0.91 0.90 0.88 n 3.19 2.91 3.05 K0 (cm d-1) 19.91 17.95 20.35 Campbell Ψe (-j kg-1) 0.75 0.79 0.71 b 1.97 2.25 2.13 Ks (mm h-1) 61.39 56.27 68.98 Input parameters for moisture retention curves for Bagoua Manyame et al. (2007)
- 23. Estimated Moisture RetentionCurves Estimation of moisture retention curves by van Genuchten and Campbell models compared with measured values of the soil profile at Bagoua Manyame et al. (2007) Suction (kPa) Soil volumetric moisture content (m3 m-3) Suction (kPa) Suction (kPa) Soil volumetric moisture content (m3 m-3) Soil volumetric moisture content (m3 m-3) RMSE 0.04 m3 m−3 0.06 m3 m−3 RMSE 0.08 m3 m−3 0.05 m3 m−3 RMSE 0.09 m3 m−3 0.15 m3 m−3
- 24. Soil volumetric moisturecontent (θ) m3 m-3 Unsaturated hydraulic conductivity (K) (mm/day) Estimated Hydraulic conductivity vs. Moisture content Curves Unsaturated hydraulic conductivity curves estimated by the van Genuchten, Campbell, and Vauclin models and compared with the Klaij and Vachaud field method for the 1.4 m soil depth at Bagoua Manyame et al. (2007) RMSE 0.47 mm d−1 0.61mmd−1 0.91 mm d−1
- 25. Soil: Sandy clayloam soil Climate: Sub-temperate Design: Split-plot design with three tillage management practices (zero, minimum and conventional) in main plots (9 m X 3 m size) and three sequential cropping [soybean (Glycine max (L.) Merr.)–wheat (Triticum aestivum L. Emend. Flori and Paol), soybean–lentil (Lensculinaris Medicus) and soybean–field pea (Pisum sativum L. Sensu Lato) in sub-plots (3 m X 3 m size) Replications: Three
- 26. Saturated hydraulic conductivity (mmday-1) Soil water retention constant (b) Tillage 0-75 mm 75-150 mm 150-225 mm 225-300 mm 0-75 mm 75-150 mm 150-225 mm 225-300 mm CT 344 315 308 300 4.2 4.3 4.1 4.2 MT 370 364 313 306 4.5 4.3 4.3 4.3 ZT 393 372 331 331 4.6 4.6 4.5 4.4 LSD 7.6 2.4 9.3 19.9 0.15 0.25 0.18 0.19 Cropping system S-W 368 348 319 307 4.4 4.4 4.2 4.3 S-L 377 348 320 312 4.5 4.4 4.3 4.2 S-P 361 354 314 318 4.4 4.4 4.3 4.3 LSD 8.3 5.2 8.6 7.7 NS NS 0.08 NS Saturated hydraulic conductivity and soil water retention constant (b) as affected by tillage management and cropping system to a depth of 300 mm Bhattacharyya et al., 2006
- 27.
- 28.
- 29. Hydraulic conductivity ofthe soil with its pore volume divided into n pore-size fractions (all filled with water) can be expressed, following the Darcy’s law, as 𝐊 𝛉𝐢 = 𝐋 (𝐀𝚫𝐇) 𝐢=𝟏 𝐧 𝐐𝐢 𝐢 = 𝟏, 𝟐, 𝟑, … , 𝐧 𝐊(𝛉𝐢) - the hydraulic conductivity (m s-1) of the soil sample at moisture content θi, A - the cross-sectional area of the sample (m2), L/ΔH - the reverse of the hydraulic gradient across the sample length L in the direction of flow and Qi - the volume flow rate (m3 s-1) contributed by the ith pore fraction and expressed as: 𝐐𝐢 = 𝐪𝐢𝐍𝐩𝐢 where qi - the volume flow rate for a single pore (m s-1) and Npi - the number of water-filled pores in the ith pore size fraction Arya and Paris (1981)
- 30. Conceptualizing the flowin a single pore as capillary flow, the flow rate qi is related to pore radius ri by the following equation: 𝐪𝐢 = 𝐜 𝐫𝐢 𝐱 The parameters c and x were evaluated from the plots of logqi v. logri data The pore radius ri can be obtained from PSD curve using the following relation: 𝐫𝐢 = 𝟎. 𝟖𝟏𝟔𝐑𝐢 𝐞 𝐧𝐢 (𝟏−𝛂𝐢) 𝟎.𝟓 Where Ri is the mean particle radius for the ith particle size fraction e is the void ratio, ni is the number of equivalent spherical particles in the ith fraction, and αi is the scaling parameter Total number of pores Npi in the ith pore fraction can be obtained as: 𝐍𝐩𝐢 = 𝐀𝐩𝐢 𝐚𝐩𝐢 where Api is the effective pore area attributed to the ith pore-size fraction and api is the cross-sectional area of a single pore and can be calculated as api = πri 2 Under a unit hydraulic gradient, the hydraulic conductivity function can be calculated as: 𝐊 𝛉𝐢 = 𝐜𝛗𝐞 𝛑 𝐜=𝟏 𝐧 𝐑𝐢 (𝐱−𝟐) 𝐰𝐢 𝟎. 𝟔𝟔𝟕𝐞 𝐧𝐢 (𝟏−𝛂) (𝐱−𝟐) 𝟐 Arya and Paris (1981)
- 31. Relationship between poreflow rate (qi) and pore radius (ri) for (a) sandy clay loam, (b) clay loam, (c) sandy clay and (d) clay textures Chakraborty et al., 2006
- 32. Observed and predictedK (m/day) for (a) sandy clay loam, (b) clay loam, (c) sandy clay, (d) clay and (e) all textures (dotted lines indicate ± 10% deviation from 1:1 line) Chakraborty et al., 2006
- 33. Jackson methodcan be used to predict unsaturated hydraulic conductivity vs. volumetric wetness for sandy loam soil with good accuracy The Campbell model is a cheaper alternative to direct measurement of moisture retention and it was able to differentiate different management practices The van Genuchten function can be used to estimate K as a function of volumetric moisture content (θ) with modest accuracy. The Predicted hydraulic conductivity of soils of the study area based on the model as proposed by Arya and Paris was in good agreement with the measured or true values
Editor's Notes
- #4 Figure 13.3 presents typical curves for sand and a clay soil, and shows that at higher matric potential (i.e., near saturation, or Φm→0) the sand or coarse-textured soil has higher K(θ) compared to clay soils. However, as these soils are desaturated, the hydraulic conductivity in the coarse-textured soil decreases faster than in fine textured soil and these two curves cross each other. After that for a given Φm, the K(θ) of coarse textured soil is always lower than fine-textured soil. This seems logical, because coarse textured soils have larger pores, which drain faster compared to fine-textured soils, which have relatively smaller pores. Since a greater number of pores is filled with water in fine-textured soil, the tortuosity is less and K(θ) is higher than in coarsetextured soil.
- #5 Soil’s hydraulic functions can be estimated both in the lab and field by various methods, which can be classified as: (i) steady flow methods and (ii) unsteady flow methods. In the steady state methods for the determination of K(θ) and D(θ), flux, gradient, and moisture content remain unchanged. However, in transient state methods, all three vary by parameter.
- #8 Both θ and Φm increase gradually and suction gradients become zero. The flow through soil profile is only due to gravity and hydraulic gradient of flow becomes unity. This provides one set of value of Φm and θ. This problem can be avoided by mulching the soil surface with straw. Ideally, therefore, this test applies to uniform (or nearly uniform) soil profiles rather than to distinctly layered ones.
- #10 Evaporation may also become significant if proper care is not taken.
- #11 (say, at least 5 x 5 m) Once the hydraulic conductivity at each elevation within the profile is known in relation to wetness. (The depth interval between succeeding tensiometers should not exceed 30 cm.)
- #12 since the drainage process often slows down within a few days or weeks to become practically imperceptible thereafter.
- #15 as observed using tensiometers (0-816 cm suction) and measured by pressure plate apparatus (102, 306, 612, 1020, 5100 and 15300 cm suction) in five depth intervals.
- #16 This table shows the calculation sheet for Jackson method
- #18 Modeling Hydraulic Properties of Sandy Soils using PTFs
- #23 Output of the ROSETTA software θr, θs, α, n, K0, L are the input for van Genuchten model to predict K(θ)
- #24 the Campbell parameters were strongly related to soil properties especially the sand content and fine earth carbonate whereas only the n parameter for the van Genuchten model showed any strong relationship to sand content. The author concluded that although both models were excellent in describing the functional relationship between the soil moisture content and matric suction, the Campbell model was more useful since its parameters were more strongly correlated with easily measured soil parameters. In this study, although the van Genuchten model consistently overestimated moisture retention at the dry regime, it resulted in better predictions for the wet regime at both sites and for all depth intervals (Figs. 1 and 2).
- #25 The K–theta curves derived from Klaij and Vachaud's direct method at both sites were similar to those derived from neutron probe readings and internal drainage experiments on similar soils in Niger The van Genuchten model consistently estimated K values similar to Klaij and Vachaud's direct method for the 1.4 m soil depth at both sites. The Campbell model on the other hand, underestimated K, making it a less likely candidate for modeling K at the study sites or for similar soils because this may lead to underestimation of root zone drainage in water balance calculations. Wagner et al (2001) found that the performance of the Campbell model could be greatly improved when the particle size distribution data used in determining the Campbell parameters are as detailed as possible and not just the clay, silt and sand contents as used in this study. The Vauclin model underestimated K especially for Banizoumbou which had higher clay content. On the contrary, the Vauclin model gave better results for the Bagoua soil which had higher sand content
- #28 A greater pore continuity (possibly as a result of minimal soil disturbances) was indicated by higher Ksat (Ehlers, 1977; Benjamin, 1993). Greater content of water stable aggregates in the reduced tillage system probably also contributed to its higher Ksat (Singh it is possible that the higher Ksat values for the ZT field might have been partially due to the burrows of the endogenic earthworms (Joschko et al., 1992). The greater Ksat values at the surface soil layer under leguminous cropping system might be due to presence of biochannels as a result of more microbial activities and greater content of soil organic carbon (measured by us) at the surface soil layers. That favourable soil environment might have resulted in better pore continuity. A much larger Ksat in 0–75 mm soil layer than those in the lower layers might be due to more vigorous macro-faunal activity and higher pore continuity in the surface layer (Singh et al., 1996).
- #31 According to Hagen-Poiseuilles law, the flow rate of a single pore can be calculated as: where ri is the mean ith pore radius (cm), S is a shape factor and depends upon pore connectivity and pore tortuosity, η is the viscosity of water (g/cm.s), ρw is the density of water (g/cm3), g is the acceleration due to gravity (cm/s2), and ΔH is the hydraulic head drop (cm) through the length of flow path L (cm). Arya et al. (1999b) reduced this Eqn to the form: 𝐪 𝐢 =𝐜 𝐫 𝐢 𝐱
- #33 The spread of the data around the 1:1 line was obvious in view of the difficulty and complexity involved in estimating hydraulic conductivity of soils. Large differences between measured hydraulic conductivity could also be observed, even if the soil samples are of the same textural class. These variations emerge from the differences in PSD, bulk density, mineralogical compositions, structural properties and organic matter present in soils at the time of collection of samples and other physicochemical characteristics, even within soils of same textural class. In the present study, textural class average values of the model parameters c. and x are used, which is likely to involve some errors in the prediction. But nonetheless the Predicted hydraulic Conductivity of soils of the study area based on the model as proposed by Arya and Paris (1981) was in good agreement with the measured or true values of the same.