The ecohydrological effects of climate and landscape interactions within the Budyko framework under non-steady state conditions

• The Budyko parameter ω was estimated under non-steady state conditions. • The parameter ω shows the largest fluctuation at the monthly scale, followed by the seasonal scale and annual scale. • The precipitation partitioning is controlled by climate and landscape characteristics interactions. • The ecohydrological interactions of climate and landscape are generally stronger at the seasonal scale. Catchment water yield is controlled by the partitioning of precipitation into evapotranspiration, runoff, and water storage changes. As one form of the Budyko framework, Fu's equation has been widely employed to estimate the influences of climatic factors and landscape characteristics on the precipitation partitioning, with a single parameter ω reflecting the integrated ecohydrological effects of these influencing factors. However, the ecohydrological effects under non-steady state conditions are not fully understood owing to the complex hydrological and ecological processes at finer spatial and temporal scales. In addition, the finer spatial and temporal scales limit the application of the Budyko framework, since the original framework assumes that water storage changes are negligible. In this study, combining two hydrological models (the abcd model and GR2M model) and Fu's equation based on an extended Budyko framework, we estimated the ecohydrological effects of climatic factors and landscape characteristics under non-steady state conditions for 59 small catchments (≤9805 km 2 ) in Qinba Mountains. The outputs of the two hydrological models exist good consistency with satellite-based data, with NSE exceeding 0.5 in 93% and 97% of catchments, respectively. Factors influencing the precipitation partitioning vary with timescale and exhibit greater variability at intra-annual scales. Moreover, the hydrological effects of these time-varying factors are influenced by catchment characteristics (R 2 ranging from 0.01 to 0.68), implying the precipitation partitioning is controlled by the ecohydrological interactions of climate and landscape at different timescales.