Krishnan et al. (2026) Soil vertical heterogeneity reduces rootzone soil moisture bias in hyper-resolution land surface model over smallholder agricultural systems

Identification

• Journal: Agricultural Water Management
• Year: 2026
• Date: 2026-08-06
• Authors: Vishnu U. Krishnan, Noemi Vergopolan, Bhupendra Bahadur Singh, Jayaluxmi Indu, L. Karthikeyan
• DOI: 10.1016/j.agwat.2026.110673

Research Groups

• Centre for Climate Studies, Indian Institute of Technology Bombay, Mumbai 400076, India
• Rice University, Department of Earth, Environmental and Planetary Sciences, Houston, TX, USA
• Centre of Studies in Resources Engineering, Indian Institute of Technology Bombay, Mumbai 400076, India
• Department of Civil Engineering, Indian Institute of Technology Bombay, Mumbai 400076, India
• Centre for Climate Change Research, Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Government of India, Pune 411008, India

Short Summary

This study evaluates the impact of incorporating vertically heterogeneous soil properties into a hyper-resolution land surface model (HydroBlocks) on rootzone soil moisture simulations in smallholder agricultural systems. The results show that representing soil texture as vertically heterogeneous reduces systematic bias in rootzone soil moisture simulations compared to the homogeneous assumption.

Objective

• Investigate the effect of incorporating vertical heterogeneity in soil properties on rootzone soil moisture simulations using a hyper-resolution land surface model (HydroBlocks).
• Evaluate the performance of HydroBlocks with vertically heterogeneous and homogeneous soil configurations against in-situ observations and satellite/reanalysis products.
• Assess the sensitivity of soil parameters to depth and seasonality.

Study Configuration

• Spatial Scale: 30 m resolution, covering an agriculturally dominated basin in India (Upper Bhima Basin).
• Temporal Scale: Daily time step for a year (2020).

Methodology and Data

• Models used: HydroBlocks, a semi-distributed hyper-resolution land surface model.
• Data sources:
  • ERA5-Land reanalysis dataset as meteorological forcing.
  • SoilGrids dataset for soil characteristics.
  • PTFs (Saxton and Rawls, 2006) to estimate other soil hydraulic properties.
  • In-situ soil moisture observations from the India Meteorological Department (IMD).
  • Satellite and reanalysis products: SMAP L3/L4, ERA5-Land, GLEAM.

Main Results

• HydroBlocks with vertically heterogeneous soil properties shows improved rootzone soil moisture simulations compared to the homogeneous assumption.
• The model's ability to capture temporal dynamics of coarse-resolution soil moisture products is evaluated using metrics such as bias, unbiased Root Mean Square Error (ubRMSE), Pearson’s correlation (R), and Spearman’s rank (Rsp) correlations.

Contributions

• This study contributes to the understanding of the importance of incorporating vertical heterogeneity in soil properties for accurate rootzone soil moisture simulations.
• The results highlight the potential of hyper-resolution land surface models with vertically heterogeneous soil properties to improve farm-scale soil moisture simulations and support agricultural water management decisions.

Funding

• Not specified in the provided text.

Citation

@article{Krishnan2026Soil,
  author = {Krishnan, Vishnu U. and Vergopolan, Noemi and Singh, Bhupendra Bahadur and Indu, Jayaluxmi and Karthikeyan, L.},
  title = {Soil vertical heterogeneity reduces rootzone soil moisture bias in hyper-resolution land surface model over smallholder agricultural systems},
  journal = {Agricultural Water Management},
  year = {2026},
  doi = {10.1016/j.agwat.2026.110673},
  url = {https://doi.org/10.1016/j.agwat.2026.110673}
}