Regional Evapotranspiration Estimation and Partitioning Model Based on Energy Balance: A Case Study of the Tibetan Plateau

This research presents a novel regional two-source evapotranspiration (ET) model designed to simulate and partition total evapotranspiration into soil evaporation (E) and vegetation transpiration (Tr) over the Qinghai-Tibetan Plateau (QTP) with high precision. Developed by extending the energy balance framework of Wang and Yamanaka (2014) from point to kilometer scale, the model's key innovation is its ability to operate without relying on land surface temperature—a parameter often challenging to obtain—enabling daily simulations at a 1 km resolution from 2003 to 2018. The model is grounded in the physical energy balance principles of both the vegetation canopy and the soil layer. It simultaneously solves the energy balance equations for these two surfaces through an iterative Newton-Raphson method, optimizing leaf and soil surface temperatures to derive the corresponding latent heat fluxes for Tr and E. Critical model components include the calculation of canopy solar radiation transmittance based on leaf area index and clumping index, as well as the dynamic parameterization of canopy and soil surface resistances, which are informed by variables such as soil moisture and incoming solar radiation. Inputs to the model integrate multi-source data, including meteorological drivers, vegetation parameters from satellite-derived LAI and land cover products, and soil properties from reanalysis and observational datasets. This comprehensive data integration supports robust simulation across the plateau's diverse ecosystems. Validation against flux tower observations at nine sites and comparison with existing regional ET products confirm the model's strong performance and reliability. It effectively captures seasonal and spatial ET dynamics and demonstrates superior skill in partitioning the total flux into its soil and vegetation components. By combining physical rigor, operational feasibility without land surface temperature, and high spatiotemporal resolution, this model provides a valuable tool for advancing water and energy cycle studies across the heterogeneous landscapes of the Tibetan Plateau. The datasets used for the model simulation are detailed in the Data Availability Statement. The corresponding code, written in Python, is located in the file SPAC.py.