Modeling ponded infiltration in fine textured soils with. coarse interlayer. Chunying Wang 1,2, Xiaomin Mao 1* and Ryusuke Hatano 2.

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1 Page 1 of 37 Soil Sci. Soc. Am. J.Accepted paper, posted 3/31/214. doi:1.2136/sssaj Modeling ponded infiltration in fine textured soils with coarse interlayer Chunying Wang 1,2, Xiaomin Mao 1* and Ryusuke Hatano Center for Agricultural Water Research in China, China Agricultural University, Beijing, 183, China; 2 Laboratory of Soil Science, Graduate School of Agriculture, Hokkaido University, Sapporo, , Japan. 9 1 *Corresponding author ( maoxiaomin@cau.edu.cn). 1

2 Soil Sci. Soc. Am. J.Accepted paper, posted 3/31/214. doi:1.2136/sssaj Page 2 of Modeling ponded infiltration in fine textured soils with coarse interlayer ABSTRACT: To understand the mechanism of infiltration into fine textured soil with coarse interlayer and to justify the capability of Richards equation-based models, ponded infiltration experiments were conducted in homogenous (loam and three types of sand) and layered soil (loam with sand interlayer) columns. The HYDRUS-1D numerical software based on Richards equation was used to simulate the above processes, where soil hydraulic parameters of the two kinds of soil were calibrated from infiltration experiments in correspondent homogenous soil columns and were used directly to simulate the infiltration process in layered soil columns. Comparison between the model simulations and the experiments shows that HYDRUS-1D model was able to predict the infiltration rate and wetting front advancement correctly. Simulation results show abrupt variation of soil water profile along the interface in layered soil columns. It also demonstrates that the matric suction immediately under the interface was the controlling factor for the stable infiltration rate, where a coarse interlayer with higher matric suction tended to facilitate infiltration instead of inhibiting it, contrary to the previous research Key words: infiltration; sand interlayer; soil column; Richards equation; HYDRUS-1D. 2

3 Page 3 of 37 Soil Sci. Soc. Am. J.Accepted paper, posted 3/31/214. doi:1.2136/sssaj Introduction Infiltration is the process of water entering the soil from ground surface. As a major process of the hydrologic cycle, infiltration provides water for vegetation consumption in the root zone, recharges groundwater as well as controls the quantity of surface runoff. Soil profiles are heterogeneous in the vertical direction, typically in horizontally layered structure due to natural evolutions or artificial activities. For example, in Loess Plateau in Northwest China, farmland is generally a surface layer of loess overlying a layer of coarse material (Wang et al., 1999). Another example is the volcanic ash soils in Japan, which account for 4% of agricultural land in Hokkaido and formed from repeated volcanic ash falls. Therefore it is commonly multi-layered with notably different soil properties, e.g., the fine textured soil layers sandwiching a coarse layer to the depth of 1 m of volcanic ash soils (Shoji and Takahashi, 22). Water infiltration in layered soil, especially in coarse textured soils covered by fine textured soil, behaves distinctly from that in homogeneous soil, regarding the infiltration rate, the soil water content inside the coarse layer, and the wetting front advancement, etc. For example, laboratory infiltration experiments and analysis showed that wetting front pauses temporarily at interface, and the infiltration rate slows down to a constant value (Hillel and Baker, 1988; Wang et al., 1999). The lower coarse layer remains unsaturated with stable moisture content (Tagaki, 196; Wang et al., 21) and the pore water pressure head of the finer layer near the soil interface may not increase with the evolution of infiltration process (Yang et al., 24). The wetting front even becomes unstable and breaks into narrow wetting columns or "fingers" in some cases (Hill and Parange, 1972; Hillel and Baker, 1988). Previous studies on infiltration into layered soil mainly focused on identifying the 3

4 Soil Sci. Soc. Am. J.Accepted paper, posted 3/31/214. doi:1.2136/sssaj Page 4 of controlling factors, e.g., water entry suction (S w ) of sub-layer, describing the fingering phenomenon and its mechanism, and exploring suitable models to depict the infiltration process. S w usually refers to the suction at which the soil becomes conductive, which is an important factor for identifying the onset of wetting front instability and predicting infiltration rate (Hillel and Baker, 1988; Baker and Hillel, 199). Normally S w for waterrepellent soil is negative (i.e., positive water pressure head), while positive for wettable soil (i.e., negative water pressure head). S w can be measured using tension-pressure infiltrometer method in both water-repellent and wettable soils (Wang et al., 1998, 2). It can also be estimated from soil water retention curves (Baker and Hillel, 199; Wang et al., 1997), or predicted by numerical simulation (Kassim et al., 28). Previous researches mainly agree that when the water pressure at the sub-layer meet the water entry value (i.e., -S w ), water can infiltrate into sub-layer. However, how S w varies with different types of soil and how it influences the infiltration behavior in the distinctly layered soil still require to be explored. Richards equation is the commonly used governing equation for describing soil water dynamics and infiltration process. Due to the soil heterogeneity and the complex initial and boundary conditions in real world, this equation was usually solved with numerical methods, using the finite difference or finite element techniques. Several numerical codes, such as HYDRUS (Šimůnek et al., 1998), SWAP (Van Dam et al., 28), SoWaM (Wesseling et al., 29), were based on the Richards equation and widely used for simulating various hydrologic processes in the vadose zone. HYDRUS-1D was used to assess the storm water fate of a modular block green roof, and could accurately predict runoff especially for small rain events (Hilten et al., 28). It was also used for simulating water flow in non-uniform soils. For example, Jiang et al. (21) simulated water flow in 4

5 Page 5 of 37 Soil Sci. Soc. Am. J.Accepted paper, posted 3/31/214. doi:1.2136/sssaj non-uniform soils under natural climatic conditions and spray irrigation in a dairy farm. Tan et al. (214) simulated multi-layer soil water flow under ponded condition in paddy fields. Satchithanantham et al. (214) investigated the shallow groundwater uptake and irrigation water redistribution in two layered sandy loam soil within the potato root zone. However, few focused on its capability of modeling distinctly layered soil under deliberately designed experiments. As we mentioned above, in distinctly layered soil, infiltration behavior may vary greatly from the homogenous one, even fingering flow would occur. Under such circumstance, the performance of traditional Richards equationbased numerical models need to be verified with experiments. Main objectives of this study were to identify the characteristics of infiltration into distinctly layered soil, through column experiment of fine textured soil with different types of coarse interlayer, and to verify the feasibility of Richards equation-based numerical model HYDRUS-1D for simulating infiltration process in such distinctly layered soil Materials and methods Infiltration experiment Infiltration experiments were carried out in polymenthyl methacry cylinders with the inner diameter of 18.3 cm and the height of 85 cm (Fig. 1). <Fig. 1 near here> Four types of soil were used in infiltration experiments. Their particle size distributions were analyzed with sieve and hydrometer methods, and the soils are one loam and three types of sand, according to the USDA soil texture classification (Bormann, 21). Results were shown in Table 1. <Table 1 near here> 5

6 Soil Sci. Soc. Am. J.Accepted paper, posted 3/31/214. doi:1.2136/sssaj Page 6 of Three groups of infiltration experiment were designed (Table 2). Each group included three column experiments, i.e., homogenous loam, homogenous sand, and loam with sand interlayer. Note that the experiment with homogenous loam (case L1 in Table 2) refers to the same experiment in the three groups, therefore actually seven experiments (i.e., cases L1, S1, S2, S3, L1S1L1, L1S2L1, L1S3L1) were conducted. <Table 2 near here> Although repacked soil may restrict generalizing the result to real world, it was used in soil columns to avoid preferential flow caused by cracks or macropores. Such kind of preferential flow may mask the influence of layered soil which is the focus of this research. Also, repacked soil can produce a higher uniform packing than field situation and allow repeated experiments and comparisons. Weight of air-dried soil for each packed layer was calculated according to the designed packing dry bulk density (Table 3) and packed volume. Then water was added to the air-dried soil to achieve designed initial water content (Table 3). Then the soil were packed into the cylinder and hammered to get the designed density in 5-cm increments. All interfaces in packing were scarified after compaction and before addition of another increment to ensure hydraulic connectivity between the layers (Plummer et al., 24). The bottom of the column was filled with gravel as filtering layer. Mariotte bottle was used to supply water and keep constant water head of 2 cm for surface ponded infiltration. Soil water content was measured in every.5 minute by 6 soil moisture sensors (ECH 2 O EC-5) at 5, 15, 25, 35, 45, 55 cm from soil surface. Soil water content near the sensors was also measured using oven-drying method with soil samples dug at the end of infiltration experiments. Time was recorded when wetting front advanced about every 5 cm, meanwhile, cumulative infiltration was measured by reading water level drop in the Mariotte bottle, which was further used to 6

7 Page 7 of 37 Soil Sci. Soc. Am. J.Accepted paper, posted 3/31/214. doi:1.2136/sssaj calculate the infiltration rate. 127 <Table 3 near here> Simulation model of the infiltration process using HYDRUS-1D Here we used HYDRUS-1D for the numerical simulations, where Richards equation was applied for describing water flow in saturated-unsaturated soil. 131 θ ( h, t) h = K ( h) 1 t z z [1] where h is the matric potential (negative) in the unsaturated zone or pressure head (positive) in the saturated zone (cm); t is time (min); z is the vertical coordinate, positive downward (cm); θ is the soil water content (cm 3 cm -3 ); and K is hydraulic conductivity (cm min -1 ). The relationships between θ, K and h were determined by soil water retention model and the soil hydraulic conductivity model. The commonly used Van Genuchten (198) model for soil water retention curve and the associated model for soil hydraulic conductivity (Mualem, 1976) were used here, i.e., 14 θ s θ r θ r +, for h < n m θ ( h) = [1 + α h ] θ s, for h K h K S S S = ( θ θ ) /( θ θ ) l 1 m m ( ) = s e 1 (1 e ) e r s r 2 [2] where θ r and θ s are the residual water content and saturated water content, respectively (cm 3 cm -3 ); α (cm -1 ), m, n and l are empirical parameters, where m=1 1/n and l=.5 is applicable for most soils; and K s is saturated hydraulic conductivity (cm min -1 ). The initial condition was described by h(z, ) = h (z) z (,L) [3] 7

8 Soil Sci. Soc. Am. J.Accepted paper, posted 3/31/214. doi:1.2136/sssaj Page 8 of where L is the length of simulation area (cm), i.e., 6 cm, h is the initial soil water pressure head (cm) calculated from the designed initial water content θ, which was assumed to be uniform in each soil layer. The top boundary condition can be described by h(, t) = h top [4] where the ponded water head at the surface h top is 2 cm for this experiment. By assuming the water entry suction of the gravel filter layer is, the bottom boundary can be described by ( h + z ) =, for h < z h =, for h [5] It indicates that infiltration cannot occur when the bottom boundary is unsaturated (i.e., the suction is higher than or h<). However, when the bottom boundary becomes saturated, infiltration will occur and a zero pressure head is imposed at the lower boundary. Infiltration rate i (cm min -1 ), cumulative infiltration I (cm) and wetting front depth Z f (cm) at time t (min) can be obtained from HYDRUS-1D simulation Model performance evaluation Model efficiency coefficient (E NS ) (Nash and Sutcliffe, 197) and root mean square error (RMSE) were used as two criteria to evaluate the performance of the above numerical simulation, which can be described by 164 E NS = 1 N i= 1 N i= 1 ( X X ) s ( X X ) 2 2 [6] RMSE= X X N 2 ( s ) [7] N i = 1 8

9 Page 9 of 37 Soil Sci. Soc. Am. J.Accepted paper, posted 3/31/214. doi:1.2136/sssaj where N is the total number of data, X s is the simulated output, X o is the observed data, and is the averaged value of the measured data. 3. Results and comparisons Experimental results Infiltration Figure 2 shows the observed infiltration rates for cases L1, L1S1L1, L1S2L1, and L1S3L1. Obviously the infiltration rates decreased rapidly in the early stage and the values were similar for all cases, mainly because of their same soil texture in the upper layers. After the wetting fronts reached 22.5 cm (i.e., the upper interface for layered soils, about 4 minutes), the infiltration rates started deviating from each other. L1S1L1and L1S2L1 showed lower infiltration rate than L1, while L1S3L1 showed higher value (as also demonstrated from Fig. 3). For all cases, the monitored cumulative infiltration showed a gradual increase with time over the whole infiltration process, and a linear relationship with time in the later infiltration stage (Fig. 3). The observed infiltration rates for cases S1, S2 and S3 are presented in Fig. 4. For sand soil, the infiltration rates decreased more rapidly than loam soil (L1) in the beginning and entered stable infiltration stages earlier. It is strange that although S1 and S3 had similar sand fraction, the stable infiltration rate of S3 was much higher than S1, which will be discussed later. <Figures 2, 3 and 4 near here> Wetting front advancement Figure 5a shows the observed wetting front advancement for cases L1, L1S1L1, L1S2L1 and L1S3L1. The initial advancement of wetting front was similar for all cases, 9

10 Soil Sci. Soc. Am. J.Accepted paper, posted 3/31/214. doi:1.2136/sssaj Page 1 of because they had the same soil texture in the upper soil layer. The difference appeared after 4 minutes, the advancement in L1 was slower than that in the other cases, while the advancement in L1S1L1 and L1S3L1 were similar and faster than that in L1S2L1. When looking at the advancement rates at location cm (where interlayer presented for layered soil column), the values were higher for layered soil than for homogenous soil (Fig 5b). This indicates that the wetting front advances faster when entering into the sand interlayer, then it slowed down when the wetting front passed through the sand interlayer and entered into the bottom loam layer ( cm in Fig. 5). <Fig. 5 near here> Soil water content along the length of layered soil columns A data logger was connected with soil water moisture sensor probes and it recorded soil water content variation at different locations along the soil columns. Comparison between recorded data and the data from oven-drying method after the experiment showed higher soil water content in the later and indicated that the recorded data from sensors systematically underestimated the soil water content. However as it would not affect the general trend of water variation during infiltration, the original recorded data are shown here without calibrations. Taking experiment L1S1L1 as an example (Fig. 6), probes 1, 2, 5 and 6 showed sharp increase of soil water content when wetting front arrived, which soon reached a stable and nearly saturated value. The water content at probes 5 and 6 were a little higher than that at probes 1 and 2. It indicates that ponded infiltration had caused sealed air and resulted in unsaturated condition in the top loam layer while it was not so pronounced in the bottom loam layer. For probes 3 and 4 in sand interlayer, the obvious increase of soil water content not only occurred when wetting front arrived but also after wetting front had reached the bottom of soil column (at about 15 minutes). It indicates 1

11 Page 11 of 37 Soil Sci. Soc. Am. J.Accepted paper, posted 3/31/214. doi:1.2136/sssaj that the sand interlayer kept unsaturated when wetting front passed through (in accordance with previous research, e.g., Wang et al. 1999). Furthermore, the second increase of soil water content was most likely caused by water accumulation from below. It is because the wetting front stopped for a while at the interface because of the low water entry suction of gravel (which used as filtering layer), while infiltration at the surface did not stop. Therefore water started accumulating from the bottom and upwardly rewetting the sand interlayer. In cases L1S2L1 and L1S3L1, we found similar two stages of soil water increase in sand interlayer. <Fig. 6 near here> Numerical simulation and results comparison Parameter determination It should be noted that for ponded infiltration the saturated zone could not actually be fully filled with water because of entrapped air (Hammecker et al., 23). The parameters of saturated water content θ s and saturated hydraulic conductivity K s were derived from the infiltration experiments in homogenous soil columns, where θ s was close to the averaged water content in the wetted zone and K s to the stable infiltration rate. Results are shown in Table 4, which were used for the numerical simulation. The other model parameters, i.e., residual water content θ r, α and n of soil water characteristics were initially given by the neural network prediction model embedded in the HYDRUS-1D code, then they were manually calibrated to get the minimum RMSE, based on the measured data from homogenous infiltration cases L1, S1, S2 and S3. Cases L1S1L1, L1S2L1 and L1S3L1 were simulated with the calibrated parameters from the homogenous infiltration experiments (Table 4) in order to assess the model capability of simulating infiltration in distinctly layered soils. 11

12 Soil Sci. Soc. Am. J.Accepted paper, posted 3/31/214. doi:1.2136/sssaj Page 12 of <Table 4 near here> Comparison between observed and simulated results Comparison between observed and HYDRUS-1D simulated infiltration rate and wetting front advancement of the homogenous columns (L1, S1, S2 and S3) is shown in Fig. 7. The model performance of HYDRUS-1D for homogenous soil columns L1, S1, S2 and S3 was quantified by E NS and RMSE. For infiltration rates of cases L1, S1, S2 and S3, the E NS values are.94,.74,.99 and.73, respectively, and the RMSE values are.18,.43,.13 and.13, respectively. For wetting front advancement, the E NS values are higher than.98 for all the above homogenous cases, and the RMSE values are 1.75,.32,.39 and 2.22 for L1, S1, S2 and S3, respectively. Results all show high E NS values (higher than.7) and low RMSE values, indicating that HYDRUS-1D could well depict ponded infiltration in homogenous soil columns. <Fig. 7 near here> Using the same set of parameters, simulation results by HYDRUS-1D in layered soil columns (L1S1L1, L1S2L1, L1S3L1) and the comparison with observed data are shown in Fig. 8. The simulation results fit well with the experiments, both showing sharp decrease in earlier stage for infiltration rate and then keeping stable when wetting front entered the coarse sand interlayer. For infiltration rates of L1S1L1, L1S21L1 and L1S3L1, the E NS values are.68,.56 and.95, respectively, and the RMSE values are.5,.59, and.46, respectively. For wetting front advancement, the E NS values are higher than.99 for all the above layered cases, and the RMSE values are.62, 1.28 and.51 for L1S1L1, L1S2L1 and L1S3L1, respectively. The good comparison was also indicated by their high E NS values (higher than.55) and low RMSE values. The above results demonstrated that Richards equation-based numerical simulation 12

13 Page 13 of 37 Soil Sci. Soc. Am. J.Accepted paper, posted 3/31/214. doi:1.2136/sssaj model could well simulate layered soil infiltration by directly using parameters from simulations of homogenous soil infiltration. <Fig. 8 near here> Discussion Soil water content profile Soil water distribution is an important factor concerned by agronomists for effective root uptake. Simulation results of soil water content profile for L1S1L1 at 2, 7 and 12 minutes (i.e., when wetting front was in the first loam layer, sand interlayer and bottom loam layer, respectively) are shown in Fig. 9. HYDRUS-1D depicts the characteristics of water content evolution with time, e.g., the water content reached saturated condition at upper loam layer while it cannot reach saturated condition at the sand interlayer even when the wetting front passed through. It is in accordance with the observed water content evolution shown in Fig.6. This phenomenon was also reported by other researchers, e.g., Eisenhauer et al. (1992) found that a tillage layer remained unsaturated because it was overlaid by fine-textured constant seal condition with the silty clay loam soil. Rao et al. (26) further demonstrated that under such cases, it is necessary to consider seal effect on tillage layer to calculate the unsaturated hydraulic conductivity and moisture content of the tillage layer. Simulation results show some oscillations at the interface of the layered soil. Some oscillations were due to numerical error, e.g., the oscillations at 2 min, which is because the model try to redistribute soil water into hydro-static condition (the designed initial 13

14 Soil Sci. Soc. Am. J.Accepted paper, posted 3/31/214. doi:1.2136/sssaj Page 14 of water content could not satisfy the hydro-static condition). But, the sharp jump at both interfaces at 12 min was physically meaningful because the layered soil may produce soil water content profile with large jump in order to keep continuous pore water pressure head along the interface. <Fig. 9 near here> According to water balance, the variation of water content θ (cm 3 cm -3 ) and the infiltration rate i (cm min -1 ) determine the wetting front advancement depth Z f (cm) at time t (min). Based on piston type assumption (Jia and Tamai, 1997), the relationship can be expressed as dz f /dt= i / θ [8] The Eq. [8] indicates that a higher infiltration rate and smaller increase of water content cause a faster wetting front advancement, while a lower infiltration rate and higher increase of water content cause a slower wetting front advancement. The water content of sand beneath the upper interface (22.8 cm) for cases L1S1L1, L1S2L1 and L1S3L1 was initially.65,.15 and.2 (Table 3), increased to about.24,.29 and.22 cm 3 cm -3, respectively, when wetting front passed through the sand interlayer. Therefore the water content of sand interlayer increased about.175,.275 and.2 cm 3 cm -3, respectively. The saturated water content of S1, S2 and S3 was.275,.3 and.3 cm 3 cm -3 (Table 4), respectively. It indicates the sand interlayer remained unsaturated with lower water content increase even when wetting front had passed through. The homogenous soil L1 increased from initial water content.8 cm 3 cm -3 (Table 3) to 14

15 Page 15 of 37 Soil Sci. Soc. Am. J.Accepted paper, posted 3/31/214. doi:1.2136/sssaj saturated water content.4 cm 3 cm -3 (Table 4) which showed the highest water content increase of.32 cm 3 cm -3 compared with the layered columns. It explains why wetting front could advance faster in layered soil than in homogeneous soil (as shown in Fig. 5), as mentioned above, the former requires less water for wetting front advancement than the later. Among the layered soils, the highest soil water content increase in sand interlayer is L1S2L1. It explains why wetting front in L1S2L1 advanced slower than that of L1S1L1 and L1S3L1 (Fig.5), although the infiltration rate and cumulative infiltration of L1S2L1 were similar with that of L1S1L1 (Fig.2 and Fig.3). While for L1S3L1, its infiltration was higher than L1S1L1 (Fig.2), which remedies the relative higher soil water content increase and results in similar wetting front advancement for L1S3L1 and L1S1L1 (Fig.5) Water entry suction of sand interlayer Baker and Hillel (199) found that when the matric potential of the interface reached the water entry value of the coarse underlying layer, the wetting front could break through the interface and enter the underlying layer, meanwhile the infiltration rate became stable. Their analysis emphasized the importance of water entry suction, which was commonly used to calculate stable infiltration rate by Darcy s Law (Darcy, 1856). The water entry suction was not considered directly in HYDRUS-1D, i.e., no value of water entry suction was required in the model input. Instead, it was indicated by the soil water retention curve, thus embedded in the Richards equation. We examined the matric potential immediately beneath the upper interface simulated by HYDRUS-1D, which would be an indicator of the water entry suction. The data were collected from simulation results at depth 22.8 cm (the depth closest to the upper interface due to profile discretization in numerical simulation, which is.3 cm 15

16 Soil Sci. Soc. Am. J.Accepted paper, posted 3/31/214. doi:1.2136/sssaj Page 16 of below the interface) at different time during stable infiltration stage (Table 5). It varied slightly when wetting front passed through the interface, with the average matric suction in cases L1S1L1, L1S2L1 and L1S3L1 1.7, 13. and 46.2 cm, respectively. The values in L1S1L1 and L1S2L1 were similar to the water entry suction of wettable sand measured by Wang et al. (2), while L1S3L1 shows much higher value. It may be because the sand interlayer in L1S3L1 has more proportion of silt and clay (see Table 1), and the surface hydrophilicity of soil particles is strong. <Table 5 near here> HYDRUS-1D simulation result demonstrates that the infiltration approached stable infiltration stage (q st ) when wetting front broke through the interface and entered the underlying sand interlayer for cases L1S1L1, L1S2L1, L1S3L1 (see Fig. 1). It indicates that although with the same soil texture in upper and lower layer, infiltration characteristics can vary considerably due to the difference of the interlayer. The q st of L1S1L1 was similar to that of L1S2L1, it is mainly because water entry suction of sand interlayer in case L1S1L1 (1.7 cm) was similar to that in case L1S2L1 (13. cm). The highest and lowest q st were found in L1S3L1 and L1S1L1, respectively. Thus, L1S1L1 had the largest infiltration reduction, and the lowest matric suction of sand interlayer (i.e., 1.7cm), which was in accordance with previous findings that greater infiltration reduction can be caused by lower water entry suction of underlying layer (Eisenhauer et al., 1992). However, our study revealed that coarse interlayer can not only reduce the infiltration rate (e.g., L1S1L1 and L1S2L1), in some circumstances it can even increase the infiltration rate, e.g., for case L1S3L1 with coarse interlayer S3 (Fig. 1). It contradicts previous research conclusions that coarse medium overlain by fine-textured soil can result in significant reduction in infiltration rate (Miller and Gardner, 1962). We 16

17 Page 17 of 37 Soil Sci. Soc. Am. J.Accepted paper, posted 3/31/214. doi:1.2136/sssaj suppose the main reason is that previous research had focused on coarse interlayer with low water entry suction, while S3 had much higher water entry suction (i.e., 46.2 cm) which would increase infiltration rate. As generally coarse soil has high hydraulic conductivity but low water entry suction, that explains why the coarse lower layer is usually inhibiting infiltration instead of facilitating it, as found by Miller and Gardner (1962) and by Yang et al. (26) from their laboratory tests. <Fig. 1 near here> 4 Conclusions Ponded infiltration experiments were conducted in homogenous and three layered soil columns, where infiltration behaviors showed much difference in the layered and the homogeneous ones. Using directly the parameters of each soil layer calibrated from their homogeneous column, HYDRUS-1D showed good performance of modeling layered soil column. It indicates that Richards equation-based numerical simulation were reliable to simulate infiltration into fine textured soil with coarse sand interlayer, regarding their infiltration rate, wetting front advancement and the averaged soil moisture condition in such distinctly layered soil, which could be used for predictions of hydrologic processes and for irrigation design and management. Note that in such layered soil, fingering flow could occur in the coarse interlayer. Being a 1D model, the water content in coarse interlayer predicted by HYDRUS-1D represents the averaged water content of both the unwetted and fingering zone. Therefore, it is unable to describe the detailed fingering phenomenon and the associated solute transport, which should leave to the 2D/3D simulation approaches

18 Soil Sci. Soc. Am. J.Accepted paper, posted 3/31/214. doi:1.2136/sssaj Page 18 of Acknowledgements The research was sponsored by the National Natural Science Foundation of China (Grant Nos and ) References Baker, R.S., and D. Hillel Laboratory tests of a theory of fingering during infiltration into layered soils. Soil Sci. Soc. Am. J. 54: 2 3. doi:1.2136/sssaj x Bormann, H. 21. Towards a hydrologically motivated soil texture classification, Geoderma, 157: doi:1.116/j.geoderma Darcy, H Les Fontaines Publiques de la Ville de Dijon, Dalmont, Paris. Eisenhauer, D.E., Heermann, D.F., and A. Klute Surface sealing effects on infiltration with surface irrigation. Trans. ASABE. 35: doi: / Hammecker, C., Antonino, A.C.D., Maeght, J.L., and P. Boivin. 23. Experimental and numerical study of water flow in soil under irrigation in northern Senegal: evidence of air entrapment. Eur. J. Soil. Sci. 54: doi: 1.146/j x Hill, D.E., and J.-Y. Parlange Wetting front instability in layered soils. Soil Sci. Soc. Am. J. 36: doi:1.2136/sssaj x Hillel, D., and R.S. Baker A descriptive theory of fingering during infiltration into layered soils. Soil Sci. 146: doi: 1.197/ Hilten, R.N., Lawrence, T.M., and E.W. Tollner. 28. Modeling stormwater runoff from green roofs with HYDRUS-1D. J. Hydrol. 358: doi: 1.116/j.jhydrol

19 Page 19 of 37 Soil Sci. Soc. Am. J.Accepted paper, posted 3/31/214. doi:1.2136/sssaj Jia, Y., and N. Tamai Modeling infiltration into a multi-layered soil during an unsteady rain. Annu J Hydrol Eng, JSCE, 1997, 41: Jiang, S., Pang, L., Buchan, G.D., Šimůnek, J., Noonan, M.J., and M.E. Close. 21. Modeling water flow and bacterial transport in undisturbed lysimeters under irrigations of dairy shed effluent and water using HYDRUS-1D. Water Res. 44: doi: 1.116/j.watres Kassim, A., Gofar, N., and M.L. Lee. 28. Numerical simulation of infiltration through unsaturated layered soil column. Malays J Civ Eng, 2: Miller, D.E., and W.H. Gardner Water infiltration into stratified soil. Soil Sci. Am. Proc. 26: doi:1.2136/sssaj xmualem, Y A new model for predicting the hydraulic conductivity of unsaturated porous media. Water Resour. Res. 12: doi: 1.129/WR12i3p513 Nash, J.E., and J.V. Sutcliffe River flow forecasting through conceptual models part I A discussion of principles. J. Hydrol. 1: doi: 1.116/ (7) Plummer, M.A., Hull, L.C., and D.T. Fox. 24. Transport of carbon-14 in a large unsaturated soil column. Vadose Zone J. 3: doi:1.2136/vzj24.19 Rao, M.D., Raghuwanshi, N.S., and R. Singh. 26. Development of a physically based 1D-infiltration model for irrigated soils. Agr. Wat. Man. 85: doi: 1.116/j.agwat Satchithanantham, S., Krahn, V., Sri Ranjan, R., and S. Sager Shallow groundwater uptake and irrigation water redistribution within the potato root zone Agri. Water Manage. 132: doi:1.116/j.agwat Shoji, S., and T. Takahashi. 22. Environmental and agricultural significance of volcanic 19

20 Soil Sci. Soc. Am. J.Accepted paper, posted 3/31/214. doi:1.2136/sssaj Page 2 of ash soils. Glob. Environ. Res. 6: Šimůnek, J., Šejna, M., and M.Th. van Genuchten The HYDRUS-1D Software Package for Simulating the One-dimensional Movement of Water, Heat and Multiple Solutes in Variably Saturated Media, Version 2.. International Ground Water Modelling Center, Colorado School of Mines, Golden, CO, USA. Tagaki, S Analysis of the vertical downward flow of water through a two-layered soil. Soil Sci. 9: doi: 1.197/ Tan, X., Shao, D., and H. Liu Simulating soil water regime in lowland paddy fields under different water managements using HYDRUS-1D. Agri. Water Manage. 132: doi:1.116/j.agwat Van Dam, J.C., Groenendijk, P., Hendriks, R.F.A., and J.G. Kroes. 28. Advances of modeling water flow in variably saturated soils with SWAP. Vadose Zone J. 7: doi:1.2136/vzj27.6 van Genuchten, M.Th A closed-form equation for predicting the hydraulic conductivity of unsaturated soils. Soil Sci. Soc. Am. J. 44: doi:1.2136/sssaj x Wang, C., Mao, X., and B. Zhao. 21. Experiments and simulation on infiltration into layered soil column with sand interlayer under ponding condition. (In Chinese, with English abstract.) Trans. Chin. Soc. Agric. Eng. 26: doi: /j.issn Wang, Q., Shao, M., and R. Horton Modified Green-Ampt models for layered soil infiltration and muddy water infiltration. Soil Sci. 164: doi: 1.197/ Wang, Z., Feyen, J., and D.E. Elrick Prediction of fingering in porous media. Water 2

21 Page 21 of 37 Soil Sci. Soc. Am. J.Accepted paper, posted 3/31/214. doi:1.2136/sssaj Resour. Res. 34: doi: 1.129/98WR1472 Wang, Z., Feyen, J., Nielsen, D.R., and M.Th. Van Genuchten Two-phase flow infiltration equations accounting for air entrapment effects. Water Resour. Res. 33: doi: 1.129/97WR178 Wang, Z., Wu, L., and Q.J. Wu. 2. Water-entry value as an alternative indicator of soil water-repellency and wettability. J. Hydro, : doi: 1.116/S ()185-2 Wesseling, J.G.,, Ritsema, C.J., Oostindie, K., Stoof, C.R., and L.W. Dekker. 29. A new, flexible and widely applicable software package for the simulation of onedimensional moisture flow: SoWaM. Environ. Modell. Softw. 24: doi: 1.116/j.envsoft Yang, H., Rahardjo, H., Leong, E.C., and D.G. Fredlund. 24. A study of infiltration on three sand capillary barriers. Can. Geotech. J. 41: doi: /t4-21 Yang, H., Rahardjo, H., and E.C. Leong. 26. Behavior of unsaturated layered soil columns during Infiltration. J. Hydrol. Eng. 11: doi: 1.161/(ASCE) (26)11:4(329)

22 Soil Sci. Soc. Am. J.Accepted paper, posted 3/31/214. doi:1.2136/sssaj Page 22 of Figure captions: 464 Fig. 1. Schematic diagram of experimental setup 465 Fig. 2. Observed infiltration rates for cases L1, L1S1L1, L1S2L1 and L1S3L1 466 Fig. 3. Observed cumulative infiltration for cases L1, L1S1L1, L1S2L1 and L1S3L1 467 Fig. 4. Observed infiltration rates for cases S1, S2 and S Fig. 5. Observed wetting front advancement for cases L1, L1S1L1, L1S2L1 and L1S3L1, depth of wetting front advancement (a), advancing rate of wetting front (b) Fig. 6. Observed soil water content variation with time at different locations along the soil column (case L1S1L1) Fig. 7. Comparison between measured and HYDRUS-1D simulated results for cases L1 (a), S1 (b), S2 (c) and S3 (d) Fig. 8. Comparison between measured and HYDRUS-1D simulated results for layered cases L1S1L1 (a), L1S2L1 (b) and L1S3L1 (c) 476 Fig. 9. Soil water content profile (for L1S1L1) from HYDRUS-1D model Fig.1. Stable infiltration rates of cases L1S1L1, L1S2L1 and L1S3L1 and comparison with case L1, simulation results from HYDRUS-1D 22

23 Page 23 of 37 Soil Sci. Soc. Am. J.Accepted paper, posted 3/31/214. doi:1.2136/sssaj Table 1 Soil particle size distribution (%) Texture Shortened as Gravel Sand Silt Clay (>2 mm) (.5-2mm) ( mm) (<.2 mm) Loam L Sand S Sand S Sand S

24 Soil Sci. Soc. Am. J.Accepted paper, posted 3/31/214. doi:1.2136/sssaj Page 24 of Table 2 Experimental design for column infiltration experiments. Depth Group No.1 Group No.2 Group No.3 (cm) Case Soil Case Soil Case Soil -6 L1 L1 L1 L1 L1 L1-6 S1 S1 S2 S2 S3 S L1 L1 L L1S1L1 S1 L1S2L1 S2 L1S3L1 S L1 L1 L1 24

25 Page 25 of 37 Soil Sci. Soc. Am. J.Accepted paper, posted 3/31/214. doi:1.2136/sssaj Table 3 Designed soil bulk density and initial water content for column infiltration experiments. Soil Bulk density (g cm -3 ) Initial water content (cm 3 cm -3 ) L S S S

26 Soil Sci. Soc. Am. J.Accepted paper, posted 3/31/214. doi:1.2136/sssaj Page 26 of Table 4 Soil hydraulic parameters used for simulations Texture θ r ( cm 3 cm -3 ) θ s (cm 3 cm -3 ) α (cm -1 ) n K s (cm min -1 ) l Loam L Sand S Sand S Sand S

27 Page 27 of 37 Soil Sci. Soc. Am. J.Accepted paper, posted 3/31/214. doi:1.2136/sssaj Table 5 Simulated matric suction (-h) at.3 cm below upper interface (i.e., in the sand interlayer) during stable infiltration stage Time L1S1L1 L1S2L1 L1S3L1 (min) -h (cm) -h (cm) -h (cm) Average

28 Soil Sci. Soc. Am. J.Accepted paper, posted 3/31/214. doi:1.2136/sssaj Page 28 of 37 Fig. 1. Schematic diagram of experimental setup

29 Page 29 of 37 Soil Sci. Soc. Am. J.Accepted paper, posted 3/31/214. doi:1.2136/sssaj Fig. 2. Observed infiltration rates for cases L1, L1S1L1, L1S2L1 and L1S3L1 Infiltration rate (cm min -1 ).4.2 L1 L1S1L1 L1S2L1 L1S3L Time (min)

30 Soil Sci. Soc. Am. J.Accepted paper, posted 3/31/214. doi:1.2136/sssaj Page 3 of 37 Fig. 3. Observed cumulative infiltration for cases L1, L1S1L1, L1S2L1 and L1S3L1 Cumulative infiltration (cm) L1 L1S1L1 L1S2L1 L1S3L Time (min)

31 Page 31 of 37 Soil Sci. Soc. Am. J.Accepted paper, posted 3/31/214. doi:1.2136/sssaj Fig. 4. Observed infiltration rates for cases S1, S2 and S3 Infiltration rate (cm min -1 ) S1 S2 S3 5 1 Time (min)

32 Soil Sci. Soc. Am. J.Accepted paper, posted 3/31/214. doi:1.2136/sssaj Page 32 of 37 Fig. 5. Observed wetting front advancement for cases L1, L1S1L1, L1S2L1 and L1S3L1, depth of wetting front advancement (a), advancing rate of wetting front (b) 6 Depth of wetting front (cm) L1 L1S1L1 L1S2L1 L1S3L Time (min) a Advancing rate of wetting front (cm min -1 ) L1 L1S1L1 L1S2L1 L1S3L1 Interface Soil depth (cm) b

33 Page 33 of 37 Soil Sci. Soc. Am. J.Accepted paper, posted 3/31/214. doi:1.2136/sssaj Fig. 6. Observed soil water content variation with time at different locations along the soil column (case L1S1L1) Volume water content (cm 3 cm -3 ) (5cm) 2 (15cm) 3 (25cm) 4 (35cm) 5 (45cm) 6 (55cm) Time (min)

34 Soil Sci. Soc. Am. J.Accepted paper, posted 3/31/214. doi:1.2136/sssaj Page 34 of 37 Fig. 7. Comparison between measured and HYDRUS-1D simulated results for cases L1 (a), S1 (b), S2 (c) and S3 (d) a b.6 measured infiltration rate simulated infiltration rate measured depth of wetting front simulated depth of wetting front Infiltration rate (cmmin -1 ) Time (min) Depth of wetting front (cm) Infiltration rate (cmmin -1 ) Time (min) Depth of wetting front (cm) c d Infiltration rate (cm min -1 ) Time (min) Depth of wetting front (cm) Infiltration rate (cmmin -1 ) Time (min) Depth of wetting front (cm)

35 Page 35 of 37 Soil Sci. Soc. Am. J.Accepted paper, posted 3/31/214. doi:1.2136/sssaj Fig. 8. Comparison between measured and HYDRUS-1D simulated results for layered cases L1S1L1 (a), L1S2L1 (b) and L1S3L1 (c) a b Infiltration rate (cm min -1 ) measured infiltration rate simulated infiltration rate measured depth of wetting front simulated depth of wetting front Time (min) Depth of wetting front (cm) Infiltration rate (cm min -1 ) Time (min) Depth of wetting front (cm) c.6 6 Infiltration rate (cm min -1 ) Depth of wetting front (cm) Time (min)

36 Soil Sci. Soc. Am. J.Accepted paper, posted 3/31/214. doi:1.2136/sssaj Page 36 of 37 Fig. 9. Soil water content profile (for L1S1L1) from HYDRUS-1D model Soil water content (cm 3 cm -3 ) Soil depth (cm) Initial Saturated 2 minutes 7 minutes 12 minutes 5 6

37 Page 37 of 37 Soil Sci. Soc. Am. J.Accepted paper, posted 3/31/214. doi:1.2136/sssaj Fig.1. Stable infiltration rates of cases L1S1L1, L1S2L1 and L1S3L1 and comparison with case L1, simulation results from HYDRUS-1D Infiltration rate (cm min -1 ).15.1 L1 L1S1L1 L1S2L1 L1S3L Time (min)