Hussain et al. (2025) Spatiotemporal dynamics of carbon, water, and energy balance in Bangladesh using multi-source remote sensing and climate data

Identification

• Journal: Remote Sensing Applications Society and Environment
• Year: 2025
• Date: 2025-12-27
• Authors: Nur Hussain, Md Saifuzzaman, Didar Islam, S. M. Shahriar Ahmed, Md. Shamim Ahamed, Dara Shamsuddin
• DOI: 10.1016/j.rsase.2025.101847

Research Groups

• Department of Biology, University of Toronto, Canada
• Department of Biology, McGill University, Canada
• Department of Geography and Planning, University of Saskatchewan, Canada
• Center for Environmental and Geographic Information Services (CEGIS), Bangladesh
• Department of Biological and Agricultural Engineering, University of California Davis, USA
• Department of Geography & Environment, Jahangirnagar University, Bangladesh

Short Summary

This study investigated the spatiotemporal dynamics of carbon, water, and energy fluxes and their impacts on ecosystem processes in Bangladesh from 2005 to 2022 using multi-source remote sensing and climate data. It found that Photosynthetically Active Radiation (PAR) is the dominant driver of Gross Primary Productivity (GPP), while temperature and precipitation significantly influence carbon uptake, highlighting the increasing disparity between ecosystem carbon sequestration capacity and rising anthropogenic emissions.

Objective

• To investigate long-term (2005–2022) carbon, water, and energy fluxes in Bangladesh using multi-source remote sensing data and climate records from weather stations.
• To assess seasonal and interannual variations in biomass productivity using satellite-derived phenological indicators.
• To quantify the spatiotemporal dynamics of carbon, water, and energy fluxes across diverse tropical ecosystems.
• To investigate the role of key climatic drivers in regulating carbon uptake, evapotranspiration, and energy exchange processes.

Study Configuration

• Spatial Scale: National scale (Bangladesh, 148,460 km²), with data resolutions ranging from 250 m to approximately 8.5 km.
• Temporal Scale: 18 years (2005–2022), with data resolutions from daily to yearly.

Methodology and Data

• Models used:
  • Light Use Efficiency (LUE) model for GPP estimation.
  • Modified Q10 temperature sensitivity model for Ecosystem Respiration (RE).
  • Penman–Monteith energy balance approach for energy fluxes (Net Radiation, Latent Heat, Sensible Heat, Ground Heat).
  • Multiple Linear Regression (MLR) for analyzing relationships between climatic variables and fluxes.
  • Savitzky–Golay filter for smoothing NDVI time series.
  • Inverse Distance Weighting (IDW) for interpolating weather station data.
• Data sources:
  • Satellite: MODIS (PAR, NDVI, LAI, ET, GPP, LULC, LST), NASA's Land Information System Data (LISD) (Latent Heat, Sensible Heat, Ground Heat).
  • Reanalysis/Modeled: FLUXCOM GPP, GOSIF GPP.
  • Observation: Bangladesh Meteorological Department (BMD) ground-based meteorological data (temperature, precipitation, wind speed) from 25 stations.

Main Results

• Gross Primary Productivity (GPP) varied from 2351.29 g C m⁻² y⁻¹ in 2009 to 2178.45 g C m⁻² y⁻¹ in 2020.
• Net Primary Production (NPP) ranged from 1248.13 g C m⁻² y⁻¹ in 2012 to 929.46 g C m⁻² y⁻¹ in 2020.
• The ratio of Latent Heat (LE) to Net Radiation (Rn) varied from 0.72 to 1.01, with an average of 0.83 (83%), indicating significant radiative energy transfer as turbulent flux.
• Validation of LUE-based GPP showed a moderate correlation with FLUXCOM-GPP (R² = 0.61, p < 0.005) and GOSIF GPP (R² = 0.58, p < 0.005).
• Photosynthetically Active Radiation (PAR) was identified as the primary and dominant driver of GPP (R² = 0.97), while temperature and precipitation significantly influenced carbon uptake.
• Total carbon uptake slightly decreased from 1253.60 MtCO₂e in 2005 to 1240.44 MtCO₂e in 2022.
• Carbon emissions increased substantially from 39.77 MtCO₂e in 2005 to 281.08 MtCO₂e in 2022.
• Water Use Efficiency (WUE) showed significant interannual and seasonal variability, with higher values in dry winter months and lower values during the monsoon period.

Contributions

• Provides a comprehensive, integrated assessment of carbon, water, and energy fluxes at the national scale across Bangladesh, filling a significant knowledge gap for monsoon-dominated regions.
• Emphasizes the crucial role of climate variables in shaping these fluxes and offers valuable insights for climate-resilient land management and sustainable carbon strategies.
• Leverages multi-source remote sensing with ground-based weather station data to provide enhanced spatial and temporal resolution compared to previous research in similar ecosystems.
• Offers a framework for addressing climate change challenges and enhancing agricultural and ecological stability in regions with similar climatic conditions.

Funding

• CHINTA Research Bangladesh (CHINTA Research fund 2024)

Citation

@article{Hussain2025Spatiotemporal,
  author = {Hussain, Nur and Saifuzzaman, Md and Islam, Didar and Ahmed, S. M. Shahriar and Ahamed, Md. Shamim and Shamsuddin, Dara},
  title = {Spatiotemporal dynamics of carbon, water, and energy balance in Bangladesh using multi-source remote sensing and climate data},
  journal = {Remote Sensing Applications Society and Environment},
  year = {2025},
  doi = {10.1016/j.rsase.2025.101847},
  url = {https://doi.org/10.1016/j.rsase.2025.101847}
}