2023
DOI: 10.1029/2022wr033506
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A Comparison of Hydrological and Geophysical Calibration Data in Layered Hydrologic Models of Mountain Hillslopes

Abstract: Hillslopes are often considered the basic landscape unit in hydrologic studies (Graham et al., 2010). At this scale, water inputs are transformed into various storage and flux components of the hydrological cycle. In mountainous terrain, the transformation of water inputs into storage and fluxes is influenced by the timing and magnitude of water input (

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Cited by 4 publications
(1 citation statement)
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References 127 publications
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“…Multi‐variate calibration evaluates model fluxes and stores more directly. Various studies have highlighted the value of detailed in‐situ observations of snow (Corbari et al., 2022; Kelleher et al., 2017; Sleziak et al., 2020), actual evapotranspiration (Stisen et al., 2018; Széles et al., 2020), soil moisture (Denager et al., 2023; Pleasants et al., 2023; Stisen et al., 2018), overland flow (Széles et al., 2020), or groundwater (Fowler et al., 2020; Kelleher et al., 2017; Pleasants et al., 2023) for improving model internal consistency in experimental catchments. As many catchments lack ground‐based measurements beyond streamflow, remote sensing‐based observations may provide an important and valuable source of information for hydrological data (Ali et al., 2023; Jiang & Wang, 2019) despite the challenges related to their observation uncertainty or spatiotemporal resolution (Beck et al., 2021; Chen et al., 2021; Mortimer et al., 2020; Sun et al., 2018; Zhang et al., 2016).…”
Section: Introductionmentioning
confidence: 99%
“…Multi‐variate calibration evaluates model fluxes and stores more directly. Various studies have highlighted the value of detailed in‐situ observations of snow (Corbari et al., 2022; Kelleher et al., 2017; Sleziak et al., 2020), actual evapotranspiration (Stisen et al., 2018; Széles et al., 2020), soil moisture (Denager et al., 2023; Pleasants et al., 2023; Stisen et al., 2018), overland flow (Széles et al., 2020), or groundwater (Fowler et al., 2020; Kelleher et al., 2017; Pleasants et al., 2023) for improving model internal consistency in experimental catchments. As many catchments lack ground‐based measurements beyond streamflow, remote sensing‐based observations may provide an important and valuable source of information for hydrological data (Ali et al., 2023; Jiang & Wang, 2019) despite the challenges related to their observation uncertainty or spatiotemporal resolution (Beck et al., 2021; Chen et al., 2021; Mortimer et al., 2020; Sun et al., 2018; Zhang et al., 2016).…”
Section: Introductionmentioning
confidence: 99%