Subsurface nutrient modelling using finite element model under Boro rice cropping system

Abstract

Boro rice, an emerging low-risk crop variety of rice, cultivated using residual or stored water after Kharif season. To enhance the quality and production of rice, potassium (K) and phosphorus (P) are the common constituents of agricultural fertilizers. However, excess application of fertilizers causes leaching of nutrients and contaminates the groundwater system. Therefore, assessment and optimization of fertilizer dose are needed for better management of fertilizers. Towards this, the present study determines the path, persistence, and mobility of K and P under the Boro rice cropping system. The experimental site consisted of four plots having Boro rice with four different fertilizer doses of nitrogen (N), P, K viz. 100%, 75%, 50%, and 25% of the recommended dose. Disturbed soil samples were analysed for K and P from pre-sown land to tillering stage at 0–5, 5–10, 10–15, 15–30, 30–45, and 45–60 cm depths. Simultaneously, K and available P were also simulated in the subsurface soil layers through the HYDRUS-1D model. The statistical comparisons were made with RMSER, E, and PBIAS between the modelled values and laboratory-measured values. Although, the results showed that all the treatments considered had agreeable simulations for both K and P, the K simulations were found to be better as compared to P simulations except for 25% where P simulations outperformed K. The simulated concentration at all doses was found most appropriate when measured for the subsurface layers (up to 45 cm), while showed an underestimation in the bottom layers (45–60 cm) of soil.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

References

  1. Behera, S., & Panda, R. (2011). Assessing soil and groundwater contamination with HYDRUS-1D: A study from West Bengal. Environmental Quality Management, 20(3), 59–75.

    Article  Google Scholar 

  2. Benedetti, M. F., Van Riemsdijk, W. H., Koopal, L. K., Kinniburgh, D. G., Gooddy, D. C., & Milne, C. J. (1996). Metal ion binding by natural organic matter: from the model to the field. Geochimica et Cosmochimica Acta, 60(14), 2503–2513.

    CAS  Article  Google Scholar 

  3. CO, A., et al. (2011). Rice production and water use efficiency for self-sufficiency in Malaysia: A review. Trends in Applied Sciences Research, 6(10), 1127–1140.

    Article  Google Scholar 

  4. De Datta, S. (1986). Improving nitrogen fertilizer efficiency in lowland rice in tropical Asia. In Nitrogen economy of flooded rice soils (pp. 171–186). Berlin: Springer.

  5. Ernani, P. R., Dias, J., & Flore, J. A. (2002). Annual additions of potassium to the soil increased apple yield in Brazil. Communications in Soil Science and Plant Analysis, 33(7–8), 1291–1304.

    CAS  Article  Google Scholar 

  6. Feddes, R., Kowalik, P., & Zaradny, H. (1978). Simulation of field water use and crop yield. Simulation monographs (pp. 9–30). Wageningen: Pudoc.

    Google Scholar 

  7. Freiberger, R. P., Heeren, D. M., Eisenhauer, D. E., Mittelstet, A. R., & Baigorria, G. (2018). Tradeoffs in model performance and effort for long-term phosphorus leaching based on in situ field data. Vadose Zone Journal, 17(1), 1–12.

    CAS  Article  Google Scholar 

  8. Garg, N., & Gupta, M. J. I. S. (2015). Assessment of improved soil hydraulic parameters for soil water content simulation and irrigation scheduling. Irrigation Science, 33(4), 247–264.

    Article  Google Scholar 

  9. Gupta, M., Garg, N., Joshi, H., & Sharma, M. (2012). Persistence and mobility of 2, 4-D in unsaturated soil zone under winter wheat crop in sub-tropical region of India. Agriculture, Ecosystems & Environment, 146(1), 60–72.

    CAS  Article  Google Scholar 

  10. Gupta, M., Garg, N., Joshi, H., Sharma, M. J. E., et al. (2014a). Assessing the impact of irrigation treatments on thiram residual trends: Correspondence with numerical modelling and field-scale experiments. Environmental Monitoring and Assessment, 186(3), 1639–1654.

    CAS  Article  Google Scholar 

  11. Gupta, M., Srivastava, P. K., Islam, T., & Ishak, A. M. B. J. E. E. S. (2014b). Evaluation of TRMM rainfall for soil moisture prediction in a subtropical climate. Environmental Earth Sciences, 71(10), 4421–4431.

    Article  Google Scholar 

  12. Haefele, S., Konboon, Y., Wongboon, W., Amarante, S., Maarifat, A., Pfeiffer, E., et al. (2011). Effects and fate of biochar from rice residues in rice-based systems. Field Crops Research, 121(3), 430–440.

    Article  Google Scholar 

  13. Hatfield, J., Edwards, O., & Dunn, R. (1966). Diffusion coefficients of aqueous solutions of ammonium and potassium orthophosphates at 25°. The Journal of Physical Chemistry, 70(8), 2555–2561.

    CAS  Article  Google Scholar 

  14. Havlin, J. L., Tisdale, S. L., Nelson, W. L., & Beaton, J. D. (2016). Soil fertility and fertilizers. Chennai: Pearson Education India.

    Google Scholar 

  15. Haws, N. W., Rao, P. S. C., Simunek, J., & Poyer, I. C. (2005). Single-porosity and dual-porosity modeling of water flow and solute transport in subsurface-drained fields using effective field-scale parameters. Journal of Hydrology, 313(3–4), 257–273.

    CAS  Article  Google Scholar 

  16. INTER, I. (2011). Toolkit for identification and quantification of mercury releases.

  17. Keen, B. A., & Raczkowski, H. (1921). The relation between the clay content and certain physical properties of a soil. The Journal of Agricultural Science, 11(4), 441–449.

    CAS  Article  Google Scholar 

  18. Khan, A. A., Jilani, G., Akhtar, M. S., Naqvi, S. M. S., & Rasheed, M. (2009). Phosphorus solubilizing bacteria: Occurrence, mechanisms and their role in crop production. J agric biol sci, 1(1), 48–58.

    Google Scholar 

  19. Lal, B., Gautam, P., Panda, B., & Raja, R. (2013). Boro rice: a way to crop intensification in Eastern India.

  20. Lallemand-Barres, A., & Peaudecerf, P. (1978). Investigation of the relationship between the value of the macroscopic dispersiveness of an aquifer medium, its other characteristics, and the measurement conditions—Bibliographic study. Bull BRGM Ser, 2(3), 4.

    Google Scholar 

  21. Lobo, V. M., Ribeiro, A. C., & Verissimo, L. M. (1998). Diffusion coefficients in aqueous solutions of potassium chloride at high and low concentrations. Journal of Molecular Liquids, 78(1–2), 139–149.

    CAS  Article  Google Scholar 

  22. Masto, E. (2004). Soil quality assessment in maize-wheat-cowpea cropping system under long-term fertiliser USE. Division of Soil Science And Agricultural Chemistry Indian Agricultural.

  23. Mathevet, T., Michel, C., Andreassian, V., & Perrin, C. (2006). A bounded version of the Nash-Sutcliffe criterion for better model assessment on large sets of basins. IAHS Publication, 307, 211.

    Google Scholar 

  24. Moterle, D. F., Kaminski, J., dos Santos Rheinheimer, D., Caner, L., & Bortoluzzi, E. C. (2016). Impact of potassium fertilization and potassium uptake by plants on soil clay mineral assemblage in South Brazil. Plant and Soil, 406(1–2), 157–172.

    CAS  Article  Google Scholar 

  25. Nash, J. E., & Sutcliffe, J. V. (1970). River flow forecasting through conceptual models part I—A discussion of principles. Journal of Hydrology, 10(3), 282–290.

    Article  Google Scholar 

  26. Nohra, J. A., Madramootoo, C., & Hendershot, W. (2004). Modeling phosphorus transport in soil and water. In 2004 ASAE annual meeting. American Society of Agricultural and Biological Engineers (p. 1).

  27. Pawar, D., Shah, K. J. G. O. M. W. R. D., Directorate of Irrigation Research, & Development, P. (2009). Laboratory testing procedure for soil and water sample analysis.

  28. Qiao, S. Y. (2014). Modeling water flow and phosphorus fate and transport in a tile-drained clay loam soil using HYDRUS (2D/3D). Montreal: McGill University Libraries.

    Google Scholar 

  29. Salalia, R., & Walia, R. (2017). Effect of soil texture and water regimes on the pathogenicity of rice root-knot nematode, meloidogyne graminicola on rice. Indian Journal of Nematology, 47(1), 136–138.

    Google Scholar 

  30. Sarangi, S. K., Maji, B., Singh, S., Sharma, D. K., Burman, D., Mandal, S., et al. (2014). Crop establishment and nutrient management for dry season (boro) rice in coastal areas. Agronomy Journal, 106(6), 2013–2023.

    Article  Google Scholar 

  31. Sekhon, G. (1999). Potassium in Indian soils and crops. Proceedings of Indian National Science Academy B, 65, 83–108.

    CAS  Google Scholar 

  32. Sikder, M. S., & Hossain, F. (2018). Improving operational flood forecasting in monsoon climates with bias-corrected quantitative forecasting of precipitation. International Journal of River Basin Management, 17, 1–11.

    Google Scholar 

  33. Šimůnek, J., Jarvis, N. J., Van Genuchten, M. T., & Gärdenäs, A. (2003). Review and comparison of models for describing non-equilibrium and preferential flow and transport in the vadose zone. Journal of Hydrology, 272(1–4), 14–35.

    Article  Google Scholar 

  34. Šimůnek, J., & van Genuchten, M. T. (2008). Modeling nonequilibrium flow and transport processes using HYDRUS. Vadose Zone Journal, 7(2), 782–797.

    Article  Google Scholar 

  35. Šimůnek, J., van Genuchten, M. T., & Šejna, M. (2008). Development and applications of the HYDRUS and STANMOD software packages and related codes. Vadose Zone Journal, 7(2), 587–600.

    Article  Google Scholar 

  36. Singh, R. (2003). Harnessing Boro rice potential for increasing rice production in deepwater areas of eastern India: an overview. Boro Rice.

  37. Srivastava, P. K., Singh, P., Mall, R., Pradhan, R. K., Bray, M., Gupta, A. J. T., et al. (2020). Performance assessment of evapotranspiration estimated from different data sources over agricultural landscape in Northern India, 1–12.

  38. Teo, Y., Beyrouty, C., & Gbur, E. (1992). Nitrogen, phosphorus, and potassium influx kinetic parameters of three rice cultivars. Journal of Plant Nutrition, 15(4), 435–444.

    Article  Google Scholar 

  39. Teo, Y. H., Beyrouty, C. A., Norman, R. J., & Gbur, E. E. (1995). Nutrient uptake relationship to root characteristics of rice. Plant and Soil, 171(2), 297–302.

    CAS  Article  Google Scholar 

  40. Vilela, N., Thebaldi, M. S., Leal, B. D. P., Silva, A. V., & Martins, I. P. (2018). Transport parameters of potassium from different sources in soil columns. Engenharia Agrícola, 38(1), 135–141.

    Article  Google Scholar 

  41. Walkley, A., & Black, I. A. (1934). An examination of the Degtjareff method for determining soil organic matter, and a proposed modification of the chromic acid titration method. Soil Science, 37(1), 29–38.

    CAS  Article  Google Scholar 

  42. Zotarelli, L., Dukes, M. D., Romero, C. C., Migliaccio, K. W., & Morgan, K. T. (2010). Step by step calculation of the Penman–Monteith evapotranspiration (FAO-56 method). Florida: Institute of Food and Agricultural Sciences, University of Florida.

    Google Scholar 

Download references

Acknowledgements

The authors thank the University Grant Commission for financial support. Authors are also thankful for SAP funding provided by UGC to the Department of Agronomy, Institute of Agricultural Sciences, Banaras Hindu University. The authors also acknowledge Institute of Environment and Sustainable Development, Banaras Hindu University for providing the necessary laboratory support for the study.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Prashant K. Srivastava.

Ethics declarations

Conflict of interest

None.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Gupta, A., Gupta, M., Srivastava, P.K. et al. Subsurface nutrient modelling using finite element model under Boro rice cropping system. Environ Dev Sustain (2021). https://doi.org/10.1007/s10668-020-01144-8

Download citation

Keywords

  • HYDRUS-1D
  • Boro rice
  • Subsurface modelling
  • Optimization