Evaluation of baseflow modelling structure in monthly water balance models using 443 Australian catchments

It is critical for monthly water balance models (MWBMs) to achieve realistic hydrological modelling of total flow and its components (i.e. quick flow and baseflow) in practical application. Various methods have been developed to improve the performances of the three flow components by focusing on calibration procedures. However, the understanding of runoff partitioning structure in MWBMs for better performances is still very limited, especially whether the storage-discharge relationship is linear or nonlinear at monthly time scale. In this study, model structures for baseflow simulation in 5 widely used MWBMs are reviewed and modified from a linear storage-discharge relationship to a nonlinear exponential storage-discharge relationship to achieve realistic baseflow simulation in 443 catchments from Australia with diverse hydro-climatic conditions. The performances of original and modified models are evaluated and compared through four assessment criteria including Nash-Sutcliffe efficiency (NSE), logarithmic form of NSE (NSE(log)), Pearson correlation coefficient (r) and Bias (B). Basically, the original models with linear storage-discharge relationship perform satisfactorily in simulating total streamflow and quick flow, but degrade remarkably for simulating baseflow with an underestimation of -60 +/- 36% in all study catchments. The modified MWBMs with nonlinear storage-discharge relationship significantly outperform the original ones for simulating both total streamflow and baseflow. The assessment criteria NSE, NSE(log), r and B of total streamflow improve in 82 +/- 4.0% (mean +/- 1 standard deviation of 5 MWBMs), 72 +/- 4.7%, 76 +/- 4.5% and 51 +/- 2.4% study catchments, respectively. The NSE(log) and r of baseflow simulated using the modified MWBMs have improved in 68 +/- 4.6% and 83 +/- 4.1% catchments with median improvement of 0.17 +/- 0.03 and 0.14 +/- 0.03, respectively. It suggests that the exponential nonlinear storage-discharge relationship is more capable for MWBMs to capture storage-discharge dynamics than the linear one at monthly time scale. This study highlights that, at monthly time scale, the nonlinearity in catchment storage-discharge relationship is a very important factor for MWBMs performance and more studies are required to reveal catchment monthly runoff generation mechanisms.