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Soil Water Dynamics on Irrigated Garlic and Pepper Crops Using Hydrus–1D Model in the Lake Tana-Basin, Northwestern Ethiopia

  • Enguday BekeleEmail author
  • Seifu Tilahun
  • Abebech Beyene
  • Sisay Asres
  • Berhanu Geremew
  • Haimanot Atinkut
Conference paper
  • 41 Downloads
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 308)

Abstract

Soil water is an important variable in regulating and predicting hydrological process for optimal irrigation. Hydrus-1D was used to simulate soil water dynamics under overhead irrigation in Dengeshita watershed at the plot level. Experiments were carried out from October-February 2017/2018 and from March – June 2018. The treatments were conservation agriculture (CA) and conventional tillage (CT). Irrigation depth, crop phenology, meteorological and soil parameters were determined. Soil parameters were estimated using a K-nearest neighbor approach (KNN) pedotransfer functions for tropical soils and fitted using retention curve optimization program. Sensitivity analysis result showed saturated soil water content (θs), saturated hydraulic conductivity (Ks), and pore size distribution (n) were the most important parameters for the model. The model performance using measured soil water content (SWC) was good with R2 of (0.64–0.77) and errors; RMSE of 0.021–0.063 and ME of 0.0013–0.040. Based on overall evaluation, CA plots had higher average SWC (0.39–0.40 cm3.cm−3) than CT plots (0.36–0.37 cm3.cm−3). The average seasonal actual transpiration was lower for CT (88.76%) than CA (93.46%) plots due to higher evaporation loss (CT = 7.69% and CA = 1.15%); the difference is statistically insignificant. Seasonal deep percolation from CT and CA plots was 0.38% and 3.15% respectively. Therefore, CA was better than CT due to store more water for plants.

Keywords

Soil water dynamics Hydrus-1D Hydraulic parameters Conservation agriculture Conventional tillage Overhead irrigation 

Notes

Acknowledgements

This research was financially supported by Appropriate Scale Mechanization Continuum (ASMC) project, a cooperative research project implemented through the United States Agency for International Development (USAID) to support the Feed the Future program in Collaboration with Bahir Dar University Institute of Technology (BIT). We would like to thank Amhara Design and Supervision works Enterprise, Soil Laboratory experts. We also thank the data collector Ato GirmaYihune. I am thankful for Ethiopian road authority (ERA) for full sponsorship of my Master’s degree education.

References

  1. Allen, R.G., Pereira, L.S., Raes, D., Smith, M.: Crop Evapotranspiration-Guidelines for Computing Crop Water Requirements-FAO Irrigation and Drainage Paper 56, vol. 300, D05109. Fao, Rome (1998)Google Scholar
  2. Arnold, J., Allen, P.: Estimating hydrologic budgets for three Illinois watersheds. J. Hydrol. 176, 57–77 (1996)CrossRefGoogle Scholar
  3. Beyene, A., et al.: Estimating the actual evapotranspiration and deep percolation in irrigated soils of a tropical floodplain, northwest Ethiopia. Agric. Water Manag. 202, 42–56 (2018)CrossRefGoogle Scholar
  4. Böhme, B., Becker, M., Diekkrüger, B., Förch, G.: How is water availability related to the land use and morphology of an inland valley wetland in Kenya? Phy. Chem. Earth Parts A/B/C 93, 84–95 (2016)CrossRefGoogle Scholar
  5. Botula, Y.-D., Nemes, A., Mafuka, P., Van Ranst, E., Cornelis, W.M.: Prediction of water retention of soils from the humid tropics by the nonparametric k-nearest neighbor approach. Vadose Zone J. 12 (2013)Google Scholar
  6. Chang, C.-W., Wu, C.-R., Lin, C.-T., Chen, H.-C.: An application of AHP and sensitivity analysis for selecting the best slicing machine. Comput. Ind. Eng. 52, 296–307 (2007)CrossRefGoogle Scholar
  7. Chauhan, N., Miller, S., Ardanuy, P.: Spaceborne soil moisture estimation at high resolution: a microwave-optical/IR synergistic approach. Int. J. Remote Sens. 24, 4599–4622 (2003)CrossRefGoogle Scholar
  8. Chen, M., Willgoose, G.R., Saco, P.M.: Spatial prediction of temporal soil moisture dynamics using HYDRUS-1D. Hydrol. Process. 28, 171–185 (2014)CrossRefGoogle Scholar
  9. Daniel, S., et al.: Spatial distribution of soil hydrological properties in the Kilombero floodplain, Tanzania. Hydrology 4, 57 (2017)CrossRefGoogle Scholar
  10. Espejo-Pérez, A.J., Brocca, L., Moramarco, T., Giráldez, J.V., Triantafilis, J., Vanderlinden, K.: Analysis of soil moisture dynamics beneath olive trees. Hydrol. Process. 30, 4339–4352 (2016)Google Scholar
  11. Gabiri, G., Burghof, S., Diekkrüger, B., Leemhuis, C., Steinbach, S., Näschen, K.: Modeling spatial soil water dynamics in a tropical floodplain, East Africa. Water 10, 191 (2018)CrossRefGoogle Scholar
  12. González, M.G., et al.: Modelling soil water dynamics of full and deficit drip irrigated maize cultivated under a rain shelter. Biosyst. Eng. 132, 1–18 (2015)CrossRefGoogle Scholar
  13. Han, M., Zhao, C., Feng, G., Yan, Y., Sheng, Y.: Evaluating the effects of mulch and irrigation amount on soil water distribution and root zone water balance using HYDRUS-2D. Water 7, 2622–2640 (2015)CrossRefGoogle Scholar
  14. Jurik, L., Kaletova, T., Huska, D.: Soil water regime of agricultural areas in small experimental catchment. J. Landscape Manag. (Czech Republic) (2012)Google Scholar
  15. Kandelous, M.M., Kamai, T., Vrugt, J.A., Šimůnek, J., Hanson, B., Hopmans, J.W.: Evaluation of subsurface drip irrigation design and management parameters for alfalfa. Agric. Water Manag. 109, 81–93 (2012)CrossRefGoogle Scholar
  16. Kuhl, A.S., Kendall, A.D., Van Dam, R.L., Hyndman, D.W.: Quantifying soil water and root dynamics using a coupled hydrogeophysical inversion. Vadose Zone J. 17 (2018)Google Scholar
  17. Li, H., et al.: Modeling of soil water and salt dynamics and its effects on root water uptake in Heihe arid wetland, Gansu, China. Water 7, 2382–2401 (2015)CrossRefGoogle Scholar
  18. Li, Y., Šimůnek, J., Jing, L., Zhang, Z., Ni, L.: Evaluation of water movement and water losses in a direct-seeded-rice field experiment using Hydrus-1D. Agric. Water Manag. 142, 38–46 (2014)CrossRefGoogle Scholar
  19. Liang, Z., Zhang, J., Guo, B.: Research on the dynamic soil moisture contents using Hydrus-3D model (2015)Google Scholar
  20. Mei-Xian, L., Jing-Song, Y., Xiao-Ming, L., Mei, Y., Jin, W.: Numerical simulation of soil water dynamics in a drip irrigated cotton field under plastic mulch. Pedosphere 23, 620–635 (2013)CrossRefGoogle Scholar
  21. Mulebeke, R., Kironchi, G., Tenywa, M.M.: Soil moisture dynamics under different tillage practices in cassava–sorghum based cropping systems in eastern Uganda. Ecohydrol. Hydrobiol. 13, 22–30 (2013)CrossRefGoogle Scholar
  22. Qiu, Y., Fu, B., Wang, J., Chen, L.: Soil moisture variation in relation to topography and land use in a hillslope catchment of the Loess Plateau, China. J. Hydrol. 240, 243–263 (2001)CrossRefGoogle Scholar
  23. Rubio, C.M., Poyatos, R.: Applicability of Hydrus-1D in a Mediterranean mountain area submitted to land use changes. ISRN Soil Sci. 2012 (2012)Google Scholar
  24. Saifadeen, A., Gladneyva, R.: Modeling of solute transport in the unsaturated zone using HYDRUS-1D (2012)Google Scholar
  25. Sánchez, N., et al.: Water balance at plot scale for soil moisture estimation using vegetation parameters. Agric. For. Meteorol. 166, 1–9 (2012)CrossRefGoogle Scholar
  26. Siebert, S., et al.: Groundwater use for irrigation–a global inventory. Hydrol. Earth Syst. Sci. 14, 1863–1880 (2010)CrossRefGoogle Scholar
  27. Simunek, J., Van Genuchten, M.T., Sejna, M.: The HYDRUS-1D software package for simulating the one-dimensional movement of water, heat, and multiple solutes in variably-saturated media. Univ. Calif. Riverside Res. Rep. 3, 1–240 (2005)Google Scholar
  28. Šimunek, J., Van Genuchten, M.T., Šejna, M.: HYDRUS: model use, calibration, and validation. Trans. ASABE 55, 1263–1274 (2012)CrossRefGoogle Scholar
  29. Šimůnek, J., Van Genuchten, M.T., Šejna, M.: Development and applications of the HYDRUS and STANMOD software packages and related codes. Vadose Zone J. 7, 587–600 (2008)CrossRefGoogle Scholar
  30. Soylu, M., Istanbulluoglu, E., Lenters, J., Wang, T.: Quantifying the impact of groundwater depth on evapotranspiration in a semi-arid grassland region. Hydrol. Earth Syst. Sci. 15, 787–806 (2011)CrossRefGoogle Scholar
  31. Thierfelder, C., Wall, P.C.: Effects of conservation agriculture techniques on infiltration and soil water content in Zambia and Zimbabwe. Soil Tillage Res. 105, 217–227 (2009)CrossRefGoogle Scholar
  32. Van Dam, J., De Rooij, G., Heinen, M., Stagnitti, F.: Concepts and dimensionality in modeling unsaturated water flow and solute transport. Frontis, 1–36 (2005)Google Scholar
  33. Van Der Kwast, J.: Quantification of top soil moisture patterns: evaluation of field methods, process-based modelling, remote sensing and an integrated approach. Utrecht University, Royal Dutch Geographical Society (2009)Google Scholar
  34. Van Genuchten, M.V., Leij, F., Yates, S.: The RETC code for quantifying the hydraulic functions of unsaturated soils (1991)Google Scholar
  35. Varut, G., Wei, X., Huang, D., Shinde, D., Price, R.: Application of MODHMS to simulate integrated water flow and phosphorous transport in a highly interactive surface water groundwater system along the eastern boundary of the Everglades National Park, Florida. In: Proceedings of the MODFLOW and More (2011)Google Scholar
  36. Ward, J., et al.: Effects of conservation systems on soil moisture and productivity in cotton. In: 2006 ASAE Annual Meeting, American Society of Agricultural and Biological Engineers, p. 1 (2006)Google Scholar
  37. Yadav, B.K., Mathur, S., Siebel, M.A.: Soil moisture flow modeling with water uptake by plants (wheat) under varying soil and moisture conditions. J. Irrig. Drain. Eng. 135, 375–381 (2009)CrossRefGoogle Scholar
  38. Zhang, X., Zhao, W., Liu, Y., Fang, X., Feng, Q.: The relationships between grasslands and soil moisture on the Loess Plateau of China: a review. CATENA 145, 56–67 (2016)CrossRefGoogle Scholar

Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2020

Authors and Affiliations

  • Enguday Bekele
    • 1
    Email author
  • Seifu Tilahun
    • 1
  • Abebech Beyene
    • 1
  • Sisay Asres
    • 1
  • Berhanu Geremew
    • 1
    • 2
  • Haimanot Atinkut
    • 3
  1. 1.Faculty of Civil and Water Resource EngineeringBahir Dar UniversityBahir DarEthiopia
  2. 2.Gondar Institute of TechnologyUniversity of GondarGondarEthiopia
  3. 3.College of Agriculture and Environmental ScienceUniversity of GondarGondarEthiopia

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