Abstract
Lumped hydrological models (LHMs) are useful tools for simulating catchment runoff (Q) owing to their low data requirements, high computational efficiency, and robust performance. However, most LHMs are purposely conceptualized for rainfall-runoff modeling with over-simplified consideration of other water balance components, especially evapotranspiration (E). The generalized complementary relationship (GCR) can reliably estimate the regional E using only routine meteorological observations. Here, a lumped hydrological model (Xinanjiang model, XAJ) was integrated with the GCR (XAJ-GCR) to improve the accuracy of the water balance partitioning of LHMs. Long-term daily observations of Q and E in the Seolmacheon experimental watershed (8.54 km2) in South Korea were collected to test the capability of the XAJ-GCR model to capture Q and E dynamics with three different integration schemes and three different calibration strategies (single or multi-objective). Results show that XAJ-GCR model obtained excellent results in simulating Q (NSEQ = 0.91 ± 0.02) and markedly improves simulating E with NSEE from − 0.35 ± 0.27 (mean ± standard deviation) to 0.56 ± 0.10. The multi-objective calibration strategy achieves better simulation results for Q and E simultaneously with NSEQ = 0.93 and NSEE = 0.69 ± 0.01, in which the built-in structure of the XAJ model is the optimal scheme. This study demonstrated that the integration of GCR into LHMs is feasible and applicable for improving water balance partitioning. The integration maintains all the advantages of LHM and does not increase the model complexity and data requirements.
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