Sensitivity and uncertainty analysis of the conceptual HBV rainfall–runoff model: Implications for parameter estimation

HBV is a conceptual hydrological model extensively used in operational hydrological forecasting and water balance studies. In this paper, we apply the HBV model on the 1924 km2 semi-humid Leaf River catchment near Collins, Mississippi. We analyze individual sensitivity of the parameters by calibrating the model using the Multi-Objective Shuffled Complex Evolution (MOSCEM) algorithm, perform Monte-Carlo based identifiability analysis and investigate the dynamic behavior of the parameters using the Dynamic Identifiability Analysis (DYNIA) approach in reference to the hydrological process in the catchment. The sensitivity analysis using two objective measures showed that there are distinct groups of parameters that control total runoff volume errors and errors from the high-flow series. The DYNIA analysis revealed that parameters have specific periods where they show higher identifiability and play a crucial role in representing the predicted stream flow. Temporal changes of parameter optima were observed due either to inadequacies in the model structure or possible time-varying catchment response subject to unsteady hydrodynamic and hydroclimatic conditions.