in

Marshland soil quality assessment in a developing country: a preliminary study


Abstract

Enhancing soil quality in the marshland of the coastal region in Bangladesh, it is essential to gain a deeper understanding of how soil series and the timing of sampling affect soil properties. This study involved analyzing topsoil samples (0–20 cm depth) collected at different times throughout the year to evaluate soil quality indices. Physico-chemical parameters such as soil texture, density, porosity, infiltration rate, organic carbon (OC), pH, electrical conductivity (EC), phosphorus (P), nitrogen (N), calcium (Ca), potassium (K), magnesium (Mg), sulfur (S), sodium (Na), and trace elements i.e., iron (Fe), manganese (Mn), zinc (Zn), chromium (Cr), nickel (Ni), copper (Cu), lead (Pb), arsenic (As), and cadmium (Cd) were analyzed to evaluate the overall soil quality in the coastal regions of Amtali and Kalapara Upazila, Bangladesh. Soil from the Jhalokathi series was sandy loam, whereas Ramgati and Barisal soil series fall in the clay loam texture. The mean concentrations of P, N, S, K, Ca, Na, and Mg were 0.006–0.009%, 0.071–0.086%, 0.014–0.036%, 4.10–6.23 Cmol kg−1, 3.80–6.60 Cmol kg−1, 5.54–10.8 Cmol kg−1, and 7.72–10.3 Cmol kg−1, respectively. Distinct variations were observed among the soil series for P, S, K, Ca, Na, and Mg. The average value of trace elements was observed as 39,024, 321.3, 92.9, 48.7, 28.9, 22.6, 13.7, 4.78, and 1.93 mg kg−1, respectively, for Fe, Mn, Zn, Cr, Ni, Cu, Pb, As, and Cd. Principal component analysis (PCA) suggested that OC, EC, pH, N, P, K, Na, As, Cd, Pb, and Ni were the key soil health indicators for the study’s soil quality index (SQI) assessment. The Barisal soil series had the highest SQI. The study highlighted that the seasonal variations had a potential influence on soil properties. These insights pave the way for developing targeted management and mitigation strategies to improve soil quality in the future.

Similar content being viewed by others

Development of soil quality index for coastal saline soils of Bangladesh

Inclusion of key soil parameters in the modified contamination factor (MCF) model as a tool for assessing heavy metal pollution in agricultural soils

Assessing the impact of eucalyptus trees on soil chemical properties in rice fields

Subjects

  • Ecology
  • Environmental sciences

Acknowledgements

The authors are thankful to the authorities of Patuakhali Science and Technology University and Khulna Agricultural University, Bangladesh, for the field survey. Furthermore, the authors are thankful to the members of Jashore University of Science and Technology, Jashore-7408, Bangladesh, for sample analysis. The authors are grateful for financial support from the Research and Training Center (Grants code: 4829 and 5921) at Patuakhali Science and Technology University (PSTU) and also for the Research Collaboration Fund provided by the University Grants Commission (UGC), Bangladesh.

Funding

The authors extend their appreciation to the Deanship of Research and Graduate Studies at King Khalid University for funding this work through Large Research Groups Program under grant number RGP2/156/47.

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to
Tusar Kanti Roy or Md. Saiful Islam.

Ethics declarations

Methods validation

The authors confirm that all methods were carried out in accordance with relevant guidelines and regulations. This study also confirms that the ethical committee of Patuakhali Science and Technology University, Bangladesh, approved all experimental protocols. For sampling and analysis, informed consent was obtained from all subjects and legal guardians from the ethical committee of the concerned authority.

Ethics approval and consent to participate

The Research Ethics Committee of Patuakhali Science and Technology University approved this study, and all respondents consented to participate.

Competing interests

The corresponding author, on behalf of the other authors, declares that there are no conflicts of interest directly or indirectly related to the work submitted for publication to disclose.

Additional information

Publisher’s note

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

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Cite this article

Roy, T.K., Islam, M. ., Ismail, Z. et al. Marshland soil quality assessment in a developing country: a preliminary study.
Sci Rep (2026). https://doi.org/10.1038/s41598-026-63480-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s41598-026-63480-5

Keywords

  • Soil quality indicators
  • Nutrient status
  • Seasonal fluctuations
  • Soil series
  • Trace elements


Source: Ecology - nature.com

Bioindicator properties of Ligula intestinalis for selected trace metals: the example of Kürtün Dam Lake, Türkiye

A multi-objective decision support system for zone-specific fertilizer recommendation using soil fertility prediction models

Back to Top