4.6 Article

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

Journal

ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
Volume 23, Issue 8, Pages 11837-11858

Publisher

SPRINGER
DOI: 10.1007/s10668-020-01144-8

Keywords

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

Funding

  1. University Grant Commission
  2. UGC

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This study aimed to assess the path, persistence, and mobility of K and P under different fertilizer doses in the Boro rice cropping system. Results indicated that K simulations outperformed P simulations, with underestimation in the bottom soil layers.
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.

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