Literature DB >> 25865338

Simulating yield response of rice to salinity stress with the AquaCrop model.

M Shahjahan Mondal1, Abul Fazal M Saleh, Md Abdur Razzaque Akanda, Sujit K Biswas, Abu Zofar Md Moslehuddin, Sinora Zaman, Attila N Lazar, Derek Clarke.   

Abstract

The FAO AquaCrop model has been widely applied throughout the world to simulate crop responses to deficit water applications. However, its application to saline conditions is not yet reported, though saline soils are common in coastal areas. In this study, we parameterized and tested AquaCrop to simulate rice yield under different salinity regimes. The data and information required in the model were collected through a field experiment at the Bangladesh Agricultural Research Institute, Gazipur. The experiment was conducted with the BRRI Dhan28, a popular boro rice variety in Bangladesh, with five levels of saline water irrigation, three replicates for each level. In addition, field monitoring was carried out at Satkhira in the southwest coastal region of Bangladesh to collect data and information based on farmers' practices and to further validate the model. The results indicated that the AquaCrop model with most of its default parameters could replicate the variation of rice yield with the variation of salinity reasonably well. The root mean square error and mean absolute error of the model yield were only 0.12 t per ha and 0.03 t per ha, respectively. The crop response versus soil salinity stress curve was found to be convex in shape with a lower threshold of 2 dS m(-1), an upper threshold of 10 dS m(-1) and a shape factor of 2.4. As the crop production system in the coastal belt of Bangladesh has become vulnerable to climate induced sea-level rise and the consequent increase in water and soil salinity, the AquaCrop would be a useful tool in assessing the potential impact of these future changes as well as other climatic parameters on rice yield in the coastal region.

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Year:  2015        PMID: 25865338     DOI: 10.1039/c5em00095e

Source DB:  PubMed          Journal:  Environ Sci Process Impacts        ISSN: 2050-7887            Impact factor:   4.238


  2 in total

1.  Modeling salinity effect on rice growth and grain yield with ORYZA v3 and APSIM-Oryza.

Authors:  A M Radanielson; D S Gaydon; T Li; O Angeles; C H Roth
Journal:  Eur J Agron       Date:  2018-10       Impact factor: 5.124

2.  Optimization of water and land allocation in salinity and deficit- irrigation conditions at farm level in Qazvin plain.

Authors:  Sara Bulukazari; Hossein Babazadeh; Niazali Ebrahimipak; Seyed-Habib Mousavi-Jahromi; Hadi Ramezani Etedali
Journal:  PLoS One       Date:  2022-07-08       Impact factor: 3.752

  2 in total

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