Work

Soil vertical heterogeneity reduces rootzone soil moisture bias in hyper-resolution land surface model over smallholder agricultural systems

Year: 2026

Type: article

Abstract: Conventional Land Surface Models (LSMs), operating at coarse resolution, inadequately represent soil heterogeneity and typically assume soil hydraulic parameters (SHPs) derived from surface-layer texture are uniform across the soil column. This introduces systematic errors in rootzone soil moisture (SM) simulations whenever soil properties vary with depth. This limitation becomes significant for their application over smallholder agricultural systems, where fine-scale heterogeneity strongly influences SM dynamics. We hypothesize that representing SHPs as vertically heterogeneous (VHet) over vertically homogeneous (VHom) improves rootzone SM simulations by reducing systematic bias. We modified HydroBlocks, a hyper-resolution (30 m) LSM, to incorporate VHet SHPs in a smallholder agriculture-dominated basin in India, representing the first such applications in India. Both VHet and VHom configurations are evaluated against in-situ observations, SMAP L3/L4, ERA5-Land, and GLEAM products. HydroBlocks simulations show strong temporal consistency with macroscale products (R=0.76–0.94, ubRMSE=0.045–0.053 m3m−3) while capturing higher sub-grid spatial variability, emphasizing their suitability over agricultural landscapes. At in-situ, VHet systematically reduces subsurface SM bias by ∼14% relative to VHom, while ubRMSE and correlation remain unchanged, indicating the model’s ability to correct the mean state while maintaining temporal consistency. Sobol sensitivity analysis across multiple soil layers and seasons reveals that soil porosity, Brooks-Corey parameter, and wilting point are most influential, with their sensitivities varying across layers and interactions intensifying during the monsoon. These results highlight the seasonal and depth-dependent influence of SHPs on subsurface SM. The study also demonstrates the potential of hyper-resolution LSMs with VHet to improve farm-scale SM simulations and support agricultural water management.

Source: Agricultural Water Management

DOI: 10.1016/j.agwat.2026.110673

Authors: Vishnu U. Krishnan, Noemi Vergopolan, Bhupendra Bahadur Singh, J. Indu, Lanka Karthikeyan

Language: English

Topic: Soil Moisture and Remote Sensing

Subfield: Environmental Engineering

Field: Environmental Science

Domain: Physical Sciences

SDGs: Life on land, Zero hunger, Climate action

Open Access status: gold

Estimated APC paid: $3,070

Funder: Ministry of Earth Sciences