Towards a semi-asynchronous method for hydrological modeling in climate change studies

Abstract. This study assesses the performance of the asynchronous approach used in hydrological modeling, which stands apart from the conventional approach by calibrating streamflow distributions without relying on meteorological observations. The focus is on comparing the two methods within the context of climate change impact studies, particularly in their ability to simulate key hydroclimatic processes across catchments. The analysis, conducted across multiple catchments, including a detailed case study of the Matane catchment in Southern Quebec, explores the potential of the asynchronous method as a viable alternative for future hydrological modeling. By eliminating the dependency on meteorological observations, the asynchronous approach offers potential advantages in regions with limited or unreliable observational data, providing a more flexible tool for climate change impact assessments.

The results reveal that while the asynchronous method effectively captures the overall distribution of streamflow and preserves extreme values, it faces significant challenges in accurately representing the timing of hydrological events, particularly those related to snowmelt. This issue stems, in part, from the method’s decision to work directly with the biases present in raw climate model outputs, without adjusting for the timing discrepancies in meteorological inputs. Consequently, the asynchronous approach inherits these biases, leading to timing inconsistencies and increased variability across different climate models, which raises concerns about the method's ability to reliably simulate critical hydroclimatic variables under future climate scenarios. In contrast, the conventional method, which incorporates bias correction, demonstrates greater reliability in capturing the timing and magnitude of streamflow events, making it a more robust tool for most hydrological applications.

The study also highlights the concept of equifinality, where different methods achieve similar outcomes through potentially flawed mechanisms, particularly in the case of the asynchronous method. Despite projecting changes in hydroclimatic variables similar to those of the conventional method, the asynchronous approach may do so for reasons that are not hydrologically sound, particularly in snow-dominated catchments.

While the asynchronous method shows promise in preserving streamflow extremes, its current implementation requires further refinement to improve its accuracy and reliability, particularly in how it simulates the timing of seasonal dynamics. However, as climate model simulations continue to improve and their biases are progressively reduced, the asynchronous approach is poised to benefit significantly, enhancing its potential for more accurate and reliable future hydrological projections. The conventional method remains the preferred choice for applications requiring hydrological simulations, but future research should focus on developing semi-asynchronous approaches that combine the asynchronous method’s strength in preserving extremes with the conventional method’s ability to handle event-specific timing.