The detrimental impacts of surface runoff and soil erosion, particularly in cultivated areas, call for the use of distributed runoff and soil erosion models with a view to supporting adapted catchment management strategies. However, runoff model parameterization remains challenging in agricultural catchments due to the high spatial and seasonal variability of soil properties. Data acquisition is demanding and may not always be feasible. Therefore, model parameterization in such environments have been the subject of numerous research efforts. The combined analysis of land use management and soil surface state was proposed in literature to address this issue and demonstrated its potential for runoff analysis and modelling. However, these research findings were related to specific rainfall sequences and/or soil surface state. In this study, existing knowledge on soil surface state and its application to runoff model parameterization were synthetized and included in an easy-to-use parameterization software (PREMACHE), providing a framework for modelers lacking of means and/or data for modelling complex agricultural catchments. To develop and evaluate the software, a dataset was acquired over 9 years on more than 110 plots in a 1045 ha agricultural catchment, including crop types, soil surface state, rainfall and runoff time series. Soil surface state dynamics was modeled based on crop types and daily rainfall. It was evaluated in the experimental catchment and validated in a nearby catchment. Soil hydrodynamic properties (e.g. infiltration capacity) were deduced from this framework and literature data at a daily time step, for each plots. Moreover, runoff events were measured when the modeled infiltration capacity was low, indicating that the parametrization adequately captured its temporal dynamics. The software developed in this study, as well as setup values deduced from the monitoring campaigns are provided with the manuscript for application in other ungauged catch