It has long been assumed that over a sufficiently long period of time, changes in catchment water storage (ΔS) are a relatively minor term compared to other fluxes and can be neglected in the catchment water balance equation. However, the validity of this fundamental assumption has rarely been tested, and the associated uncertainties in water balance calculations remain unknown. Here, we use long‐term (1982–2011) observations of monthly streamflow (Q) and precipitation (P) for 1,057 global unimpaired catchments, combined with four independent evapotranspiration (E) estimates to infer ΔS and to provide a global assessment of the steady‐state assumption in catchment water balance calculations. Results show that when the threshold for steady state is set to 5% of the mean monthly P, ~70% of the catchments attain steady state within 10 years while ~6% of the catchments fail to reach a steady state even after 30 years. The time needed for a catchment to reach steady state (τs) shows a close relationship with climatic aridity and vegetation coverage, with arid/semiarid and sparsely vegetated catchments generally having a longer τs. Additionally, increasing snowfall fraction also increases τs. The imbalance (ewb) caused by ignoring ΔS decreases as averaging period for water balance calculations increases as expected. For a typical 10‐year averaging period, ewb accounts for ~7% of P in arid, but that decreases to ~3% of P in humid catchments. These results suggest that catchment properties should be considered when applying the steady‐state assumption and call for caution when ignoring ΔS in arid/semiarid regions.
Snowmelt provides water resources for more than one-sixth of the world's population (Barnett et al., 2005). The snow accumulates in winter and contributes to the river flow in the following spring to summer. The snowmelt is one of the main contributors to streamflow in mountainous areas, like the western US (Godsey et al., 2014;Li et al., 2017). In the context of global warming, the storage of snow is compromised (Milly et al., 2008;Musselman et al., 2021). The precipitation phase shifts (PPS) from snowfall to rainfall and earlier snowmelt timing complicate the flow regime and place more stress on water resource management in snow-affected regions (Barnett et al., 2005;Evan & Eisenman, 2021).The impact of PPS on streamflow mean value has gained much attention recently. Berghuijs et al. (2014) presented an evidence-based positive correlation between long-term streamflow and the snowfall fraction (r s ) based on the Budyko framework, indicating a possible decrease in streamflow in a warmer climate. The underlying mechanisms have also been discussed. For example, Zhang et al. (2015) suggested that less energy is needed to melt the snow due to r s decrease, thus more energy can be available for evaporation which in turn leads to a decrease in streamflow. Barnhart et al. (2016) argued that slower snowmelt induced by smaller r s could generate less subsurface flow and greater partitioning to evaporation which further decreases the streamflow (Trujillo & Molotch, 2014). Some works have also noted that earlier and slower snowmelt accompanied by less snowfall might be the main reason for streamflow declines (Godsey et al., 2014;Musselman et al., 2017Musselman et al., , 2021. A decrease in snowfall would lead to a decline in interannual water storage in snow-affected regions (Milly et al., 2008), which could potentially affect the interannual streamflow variability. Despite the numerous studies on the PPS
<p>With persistent global warming, more precipitation will land on the earth's surface as rainfall instead of snowfall. Here, based on observations from hundreds of catchments, we proposed a framework (the second-order Budyko framework) to investigate hydro-climatic relationships between annual streamflow and snowfall fraction. Results show that in addition to the mean annual streamflow, the inter-annual streamflow variability will also decrease with lower snowfall fraction in the context of warming. The positive relationship between streamflow variability and snowfall fraction may result from the asymmetric hydrological effects of snowfall in the wet and dry years. To our knowledge, it is the first attempt to detect the role of snowfall on the streamflow variability. This study provides new way and understandings of the second-order hydro-climatic effects, and these findings will facilitate decisions for water resource management in a changing climate.</p>
<p>With the ongoing climate warming, changes in intra-annual distribution, annual volume, and their inter-annual variability of streamflow have been key research topics of ever-increasing interest. For settling the question of how changing climate shapes streamflow dynamics, here, we used long-term (1950-2010) observations of monthly streamflow (<em>Q</em>) for 2960 global unimpaired catchments, combined with snowfall (SF) and precipitation (<em>P</em>) estimates from ERA5-Land to provide a global assessment of effect of snowfall on streamflow variability. Results showed that precipitation was the main control of intra-annual and inter-annual streamflow variability while the propagation process of variability would be regulated by snow. As the snowfall fraction (sf) decreased, the annual runoff coefficient decreased, while the timing of streamflow got advanced and the intra-annual distribution became more even. Besides, the inter-annual variability of streamflow shows a negative relationship with snowfall fraction. The negative relationship between streamflow inter-annual variability and snowfall fraction may result from the asymmetric hydrological effects of snowfall in the wet and dry years.</p>
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