A comparative study of ponded infiltration in a desert sandy soil based on multi-hydrological models

  • Hong ZHOU
Expand
  • 1. Hexi Corridor Research Institute, Tourism College, Northwest Normal University, Lanzhou 730070, Gansu, China
    2. Linze Inland River Basin Research Station, China Ecosystem Research Network, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, Gansu, China

Received date: 2021-06-30

  Revised date: 2021-08-06

  Online published: 2022-01-24

Abstract

Water infiltration of the vadose zone plays a key role in the water cycle. A better understanding of the relationships among rainfall, ponded water, and soil infiltration processes is critical to estimate groundwater replenishment and redistribution in desert environments. However, research on the moisture distribution in the vadose zone of sandy soil is still limited. In particular, few studies have examined the water transport processes in the desert vadose zone. Therefore, we aimed to determine the soil moisture distribution and variation in homogenous sandy soil under ponded infiltration and to validate models using data from these observations. This study was conducted in a nature dune slack through dynamic in situ observations using profile infiltration experiment and continuous soil moisture measurements at 1 min intervals. A single-ring infiltrometer (diameter, 20 cm; insertion depth, 5 cm) was used to keep a constant water head. Kostiakov-Lewis, Green-Ampt, Philip, Hydrus-1D/2D/3D numerical software based on Richard’s equation were used to describe the vertical infiltration and soil water movement processes and to identify suitable models for ponded infiltration processes in sandy soil. The validation indices included the sum of squared error and root mean squ are error. A comparison between the simulated and measured results indicated that the Philip model could predict the infiltration rate, cumulative infiltration, and wetting front advancement correctly, with an RMSE value of 0.0003, 0.04, and 0.24 cm·min-1 and R 2 of 0.95, 0.99, and 0.94, respectively. These values were clearly less than those of the Kostiakov-Lewis, Green-Ampt, and Hydrus-1D models, although the other models also showed good overall agreement with the field measured cumulative infiltration. The Hydrus-3D model yielded a better fit to the simulated soil moisture than the Hydrus-2D in the wetted zone based on the coefficient of determination, average RMSE (0.018 cm3·cm-3) and R 2 (0.93). Altogether, it appears that the combination of the Philip and Hydrus-3D models is a highly effective approach to estimate ponded infiltration parameters and simulate the water transport process in variably saturated sandy soil. The three-dimensional soil water diffusivity must be considered to predict water infiltration in sandy soils. Our results also demonstrate that the integration of numerical simulation and field measurements can improve the research efficiency of soil water infiltration in dry environments. In practice, the accurate prediction of soil water infiltration can be done by the selection of the proper models based on the soil properties of the particular sites.

Cite this article

Hong ZHOU . A comparative study of ponded infiltration in a desert sandy soil based on multi-hydrological models[J]. Arid Zone Research, 2022 , 39(1) : 123 -134 . DOI: 10.13866/j.azr.2022.01.13

References

[1] Reynolds W D. An assessment of borehole infiltration analyses for measuring field-saturated hydraulic conductivity in the vadose zone[J]. Engineering Geology, 2013, 159: 119-130.
[2] Bagarello V, Sferlazza S, Sgroi A. Comparing two methods of analysis of single-ring infiltrometer data for a sandy-loam soil[J]. Geoderma, 2009, 149(3-4): 415-420.
[3] Xiao B, Sun F H, Hu K L. Biocrusts reduce surface soil infiltrability and impede soil water infiltration under tension and ponding conditions in dryland ecosystem[J]. Journal of Hydrology, 2019, 568: 792-802.
[4] Verbist K, Torfs S, Cornelis W M, et al. Comparison of single-and double-ring infiltrometer methods on stony soils[J]. Vadose Zone Journal, 2010, 9(2): 462.
[5] Alagna V, Bagarello V, Di Prima S, et al. Determining hydraulic properties of a loam soil by alternative infiltrometer techniques[J]. Hydrological Processes, 2016, 30(2): 263-275.
[6] Wang X J, Li H L, Yang J Z, et al. Measuring in situ vertical hydraulic conductivity in tidal environments[J]. Advances in Water Resources, 2014, 70: 118-130.
[7] Daly E, Porporato A. A review of soil moisture dynamics: From rainfall infiltration to ecosystem response[J]. Environmental Engineering Science, 2005, 22(1): 9-24.
[8] 任杰, 沈振中, 杨杰, 等. 基于HYDRUS模型低温水入渗下土壤水热运移模拟[J]. 干旱区研究, 2016, 33(2): 246-252.
[8] [Ren Jie, Shen Zhengzhong, Yang Jie, et al. Simulation of water and heat transfer in soil under low-temperature water infiltration based on the HYDRUS model[J]. Arid Zone Research, 2016, 33(2): 246-252. ]
[9] Regalado C M, Ritter A, Álvarez B, et al. Simplified method to estimate the Green-Ampt wetting front suction and soil sorptivity with the Philip-Dunne falling-head permeameter[J]. Vadose Zone Journal, 2005, 4(2): 291.
[10] Putte A V, Govers G, Leys A, et al. Estimating the parameters of the Green-Ampt infiltration equation from rainfall simulation data: Why simpler is better[J]. Journal of Hydrology, 2013, 476: 332-344.
[11] Huo W, Li Z, Zhang K, et al. GA-PIC: An improved Green-Ampt rainfall-runoff model with a physically based infiltration distribution curve for semi-arid basins[J]. Journal of Hydrology, 2020, 586: 124900.
[12] Zhang J, Lei T G, Chen T Q. Impact of preferential and lateral flows of water on single-ring measured infiltration process and its analysis[J]. Soil Science Society of America Journal, 2016, 80(4): 859.
[13] Wang C Y, Mao X M, Hatano R. Modeling ponded infiltration in fine textured soils with coarse interlayer[J]. Soil Science Society of America Journal, 2014, 78(3): 745-753.
[14] Sansoulet J L, Cabidoche Y M, Cattan P, et al. Spatially distributed water fluxes in an andisol under banana plants: Experiments and three-dimensional modeling[J]. Vadose Zone Journal, 2008, 7(2): 819-829.
[15] Mashayekhi P, Ghorbanidashtaki S, Mosaddeghi M R, et al. Different scenarios for inverse estimation of soil hydraulic parameters from double-ring infiltrometer data using HYDRUS-2D/3D[J]. International Agrophysics, 2016, 30(2): 203-210.
[16] Kandelous M M, Šimůnek J. Numerical simulations of water movement in a subsurface drip irrigation system under field and laboratory conditions using HYDRUS-2D[J]. Agricultural Water Management, 2010, 97(7): 1070-1076.
[17] Yi J, Zhao Y, Shao M A, et al. Hydrological processes and eco-hydrological effects of farmland-forest-desert transition zone in the middle reaches of Heihe River Basin, Gansu, China[J]. Journal of Hydrology, 2015, 529: 1690-1700.
[18] Stratford C J, Robins N S, Clarke D, et al. An ecohydrological review of dune slacks on the west coast of England and Wales[J]. Ecohydrology, 2013, 6(1): 162-171.
[19] Zhang C C, Li X Y, Wang Y, et al. Responses of two desert shrubs to simulated rainfall pulses in an arid environment, northwestern China[J]. Plant and Soil, 2019, 435(1): 239-255.
[20] Diego Rivera, Mario Lillo, Stalin Granda. Representative locations from time series of soil water content using time stability and wavelet analysis[J]. Environmental Monitoring and Assessment, 2014, 186(12): 9075-9087.
[21] Wang S, Fu B J, Gao G Y, et al. Responses of soil moisture in different land cover types to rainfall events in a re-vegetation catchment area of the Loess Plateau, China[J]. Catena, 2013, 101: 122-128.
[22] Dohnal M, Vogel T, Dusek J, et al. Interpretation of ponded infiltration data using numerical experiments[J]. Journal of Hydrology and Hydromechanics, 2016, 64(3): 289-299.
[23] Chamizo S, Cantón Y, Domingo F, et al. Evaporative losses from soils covered by physical and different types of biological soil crusts[J]. Hydrological Processes, 2013, 27(3): 324-332.
[24] Cheng Q B, Chen X, Chen X H, et al. Water infiltration underneath single-ring permeameters and hydraulic conductivity determination[J]. Journal of Hydrology, 2011, 398(1-2): 135-143.
[25] 石兰君, 乔晓英, 曾磊, 等. 甘肃黑方台黄土水分运移规律模拟[J]. 干旱区研究, 2018, 35(4): 813-820.
[25] [Shi Lanjun, Qiao Xiaoying, Zeng Lei, et al. Loess moisture migration in Heifangtai of Gansu Province[J]. Arid Zone Research, 2018, 35(4): 813-820. ]
[26] Smith R E. The infiltration envelope: Results from a theoretical infiltrometer[J]. Journal of Hydrology, 1972, 17: 1-21.
[27] Uloma A R, Samuel A C, Kingsley I K. Estimation of Kostiakov’s infiltration model parameters of some sandy loam soils of Ikwuano-Umuahia, Nigeria[J]. Open Transactions on Geosciences, 2014, 1(1): 34-38.
[28] Duan R B, Fedler C, Borrelli J. Field evaluation of infiltration models in lawn soils[J]. Irrigation Science, 2011, 29(5): 379-389.
[29] Lewis J D. Assessment of a Single-ring Sprinkle Infiltrometer Method for Evaluating Soil-based Stormwater Management Practices[D]. North Carolina, Raleigh: Graduate Faculty of North Carolina State University, 2016.
[30] Sihag P, Tiwari N K, Ranjan S. Modelling of infiltration of sandy soil using gaussian process regression[J]. Modeling Earth Systems and Environment, 2017, 3(3): 1091-1100.
[31] Zolfaghari A A, Mirzaee S, Gorji M. Comparison of different models for estimating cumulative infiltration[J]. International Journal of Soil Science, 2012, 7(3): 108-115.
[32] Ogbe V B, Jayeoba O J, Ode S O. Comparison of four soil infiltration models on a sandy soil in Lafia, Southern Guinea Savanna Zone of Nigeria[J]. Production Agriculture and Technology, 2011, 7(2): 116-126.
[33] 孙程鹏, 赵文智, 杨淇越. 绿洲边缘夹黏沙丘持水特性[J]. 生态学报, 2018, 38(11): 3879-3888.
[33] [Sun Chengpeng, Zhao Wenzhi, Yang Qiyue. Water retention of the clay interlayer of dunes at the edge of an oasis[J]. Acta Ecologica Sinica, 2018, 38(11): 3879-3888. ]
[34] 崔浩浩, 张冰, 冯欣, 等. 不同土体构型土壤的持水性能[J]. 干旱地区农业研究, 2016, 34(4): 1-5.
[34] [Cui Haohao, Zhang Bing, Feng Xin, et al. Soil water-holding properties of different soil body configuration[J]. Agricultural Research in the Arid Areas, 2016, 34(4): 1-5. ]
Outlines

/