INTRODUCTION
Uncertainty in the representation of hydrological processes at local
scales in Earth system models can affect the accuracy of the weather
forecasts and climate projections. Water budget and surface energy in
large basins, which are formed by small homogenous hydrological response
units, are primarily affected by regional climatic teleconnection
patterns. Small variations in climatic patterns can lead to large
hydrological responses (Whitfield, 2001), and can affect hydrological
predictability (Rasouli, Hsieh, & Cannon, 2012). Interactions between
local and regional scale hydroclimatic fluxes, however, are not
sufficiently resolved in the Earth system and climate models used for
environmental change studies (Fan et al., 2019). Whitfield, Moore,
Fleming, and Zawadzki (2010) studied the low frequency (e.g.,
multi-decadal) and high frequency (e.g., monthly) variations of climate
and their associations with hydrological changes. A multi-decadal
component of spring streamflow, for instance, is associated with
variations in spring precipitation and air temperature driven by low
frequency atmospheric circulations and sea level pressure (Boé & Habet,
2014). In snow-dominated mountains with shallow soils and high spatial
heterogeneity, streamflow variations also depend on low frequency
variations of groundwater. Because of the lower velocity of groundwater
relative to surface runoff, it can take three to eight years to recycle
and contribute to surface flows in mountainous areas, depending on the
variability of meltwater from fresh snowpack (e.g., Plummer et al.,
2001; Manning et al., 2012). The decomposition of local hydrological
time series into its components can yield comparable scales that are
needed to relate climate circulations with a low frequency and long
cycles to hydrological fluxes with a high frequency and short durations.
Understanding hydrological variations with an intermediate frequency
(e.g., occurring every 3 – 8 years) remains challenging in mountainous
regions with large geological heterogeneity as attribution of antecedent
energy and moisture conditions in the previous years to seasonal snow
and flow regimes in the following year cannot be easily monitored or
estimated. Spatial and temporal variations of snowmelt, runoff,
groundwater storage and flow, antecedent soil moisture, snow
redistribution by blowing wind, and snow sublimation, are high, which
makes modeling and predicting mountain hydrology uncertain (Lehning,
Grünewald, & Schirmer, 2011). This becomes even more challenging when
hydrological models are forced with atmospheric fluxes with uncertain
measurements and large natural variations.
Reynolds Creek Experimental Watershed (RCEW), with a semiarid cool
montane climate in Idaho, USA, is of specific scientific interest. For
example, its critical zone responses to climate change have been
monitored over three decades and subsequently modeled by many studies
(e.g. Seyfried, Grant, Marks, Winstral, & McNamara, 2009; Reba et al.,
2011a; Kumar, Wang, & Link, 2012; Marks, Winstral, Reba, Pomeroy, &
Kumar, 2013; Rasouli, Pomeroy, & Marks, 2015). Reynolds Mountain East
(hereafter, Reynolds Mountain), as a headwater basin within RCEW, has
been widely investigated to understand hydrological changes in the
mountains and often cited in the literature as a representative basin
for semiarid snow dominated regions (e.g. Marks & Winstral, 2001; Reba
et al., 2011a; Kumar, Marks, Dozier, Reba, & Winstral, 2013; Wang,
Kumar, & Marks, 2013; Chen, Kumar, Wang, Winstral, & Marks, 2016).
Reba, Marks, Winstral, Link, and Kumar (2011b) conducted a detailed
study of the sensitivity of the snow cover energetics and classified
hydrological simulations into eight categories based on annual and
winter precipitation and snowpack. All eight categories in Reynolds
Mountain, however, were temporally discontinuous. Dry and cool
conditions, for instance, in 1985 and 2000, may not belong to the same
teleconnection phase and may have different atmospheric driving
mechanisms. Interactions between local hydrological dynamics and
regional climatic teleconnection patterns, along with a physically based
representation of these interactions in climate models, can improve the
understanding of climate and hydrological processes at local scales
(Prein et al., 2015) and the understanding of weather and climate
extremes at regional scales (Langendijk et al., 2019). The large biases
that weather and climate model outputs show against observations
(Fowler, Blenkinsop, & Tebaldi, 2007) can be reduced by linking land
surface processes and local atmospheric convection to climatic
teleconnection patterns across a range of temporal and spatial scales.
The attribution of regional climate patterns over the preceding years to
seasonal hydrological fluxes at local scales in the following year has
not been sufficiently understood. Therefore, the linkage between local
hydrological processes and regional climatic teleconnections patterns
was explored in this study. The linkage between local hydrological
variations and climatic teleconnection patterns, assessed over multiple
hydroclimatic phases in this paper, can be missed when only seasonal
precipitation, snowmelt runoff, and evapotranspiration are investigated.
Misrepresenting low (e.g., multiple decades), intermediate (e.g., 3 – 8
years), and high (e.g., multiple months) frequency variations can result
in uncertainties in climate projections and failure in both short and
long-term hydrological predictions (Dutta & Maity, 2018). This study
addresses the following research questions: how do local hydrological
processes in a small basin relate to regional climatic patterns, and how
does the spatial variability of hydrological fluxes in snow dominated
mountain basins differ under different phases of atmospheric
circulations?