Expansion and contraction of the flowing stream network alter hillslope flowpath lengths and the shape of the travel time distribution

Meerveld, H. J. Ilja van; Kirchner, James W.; Vis, Marc; Assendelft, Rick; Seibert, Jan

doi:10.5194/hess-23-4825-2019

Cited by 62 publications

(76 citation statements)

References 43 publications

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“…In particular, if the distributions of L and v are multimodal for various physical reasons (see Section 2), it can be expected that the TTD is multimodal as well (see Figure 7, note, however, the implicit assumption of independence between L and v ). This has been recently observed in a catchment in Switzerland where the extension and the contraction of the flow network for different wetness conditions creates complex patterns of flow paths leading to multimodal TTDs (assuming a constant, homogeneous velocity field) (van Meerveld, Kirchner, Vis, Assendelft, & Seibert, 2019). In reality, the shape of TTDs will depend on the relationship between L and v .…”

Section: Discussionmentioning

confidence: 76%

“…For instance, one may start with an age component for young water after detecting surface runoff in the catchment and mapping its extent from manual survey and/or aerial images. The characteristics of this age component may then be deduced from GIS analysis, using initially simple assumptions of flow paths and water velocities (c.f., van Meerveld et al, 2019). Spectral slopes of stream chemistry suggest that a gamma distribution with a shape parameter k < 1 may be an appropriate candidate for this young water component (Kirchner et al, 2000).…”

Section: Discussionmentioning

confidence: 99%

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Multimodal water age distributions and the challenge of complex hydrological landscapes

Rodriguez

Benettin

Klaus

2020

Hydrological Processes

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Travel time distributions (TTDs) are concise descriptions of transport processes in catchments based on water ages, and they are particularly efficient as lumped hydrological models to simulate tracers in outflows. Past studies have approximated catchment TTDs with unimodal probability distribution functions (pdf) and have successfully simulated tracers in outflows with those. However, intricate flow paths and contrasting water velocities observed in complex hydrological systems may generate multimodal age distributions. This study explores the occurrence of multimodal age distributions in hydrological systems and investigates the consequences of multimodality for tracer transport.Lumped models based on TTDs of varying complexity (unimodal and multimodal) are used to simulate tracers in the discharge of hydrological systems under well-known conditions. Specifically, we simulate tracer data from a controlled lysimeter irrigation experiment showing a multimodal response and we provide results from a virtual catchment-scale experiment testing the ability of a unimodal age distribution to simulate a known and more complex multimodal age system. Models are based on composite StorAge Selection functions, defined as weighted sums of pdfs, which allow a straightforward implementation of uni-or multi-modal age distributions while accounting for unsteady conditions. These two experiments show that simple unimodal models provide satisfactory simulations of a given tracer, but they fail in reproducing processes occurring at different temporal scales. Multimodal distributions, instead, can better capture the detailed dynamics embedded in the observations. We conclude that experimental knowledge of flow paths and the systematic use of data from multiple, independent tracers can be used to validate the assumption of water age unimodality. Multimodal age distributions are more likely to emerge in landscapes where the distributions of flow path lengths and/or water velocities are themselves multimodal. In general, age multimodality may not be particularly pronounced and detectable, unless comparable amounts of water with contrasting ages reach a given outflow. K E Y W O R D Shydrological tracer, lumped model, multimodal distribution, StorAge Selection function, travel time, water age distribution, water chemistry, water velocity

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Section: Discussionmentioning

confidence: 76%

Section: Discussionmentioning

confidence: 99%

Multimodal water age distributions and the challenge of complex hydrological landscapes

Rodriguez

Benettin

Klaus

2020

Hydrological Processes

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“…In SHAKTI, this englacial void ratio is also included as an option (Sommers et al, 2018), but our simulations considered here do not employ this term in the equations. Our results present that the supraglacial hydrologic system acts as short-term storage for surface meltwater, as exhibited by the time lag of moulin inputs between models; therefore, application of an appropriate surface meltwater routing model may reduce the dependence of some subglacial models on a somewhat arbitrary englacial storage term to produce realistic diurnal effective-pressure variations and timing lags (Werder et al, 2013;Hoffman et al, 2016). It is conceivable, for example, that routing models could help to parameterize the storage term built into sub-glacial hydrology models or that some portion of this term should in fact be apportioned to supraglacial routing delays.…”

Section: Influence On Diurnal Subglacial Pressure Variationsmentioning

confidence: 79%

“…Many subglacial hydrology models commonly invoke a numerical term (the "englacial void ratio") to represent englacial storage in order to provide short-term storage and release of meltwater that cannot be accommodated rapidly within the subglacial system in the absence of a more realistic representation of supraglacial and englacial storage (Hewitt, 2013;Werder et al, 2013;Hoffman et al, 2016). In SHAKTI, this englacial void ratio is also included as an option (Sommers et al, 2018), but our simulations considered here do not employ this term in the equations.…”

Section: Influence On Diurnal Subglacial Pressure Variationsmentioning

confidence: 99%

Intercomparison of surface meltwater routing models for the Greenland ice sheet and influence on subglacial effective pressures

et al. 2020

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Abstract. Each summer, large volumes of surface meltwater drain off the Greenland ice sheet (GrIS) surface through moulins to the bed, impacting subglacial hydrology and ice flow dynamics. Supraglacial surface routing delays may propagate to englacial and subglacial hydrologic systems, requiring accurate assessment to correctly estimate subglacial effective pressures. We compare hourly supraglacial moulin discharge simulations from three surface meltwater routing models – the synthetic unit hydrograph (SUH), the bare-ice component of surface routing and lake filling (SRLF), and the rescaled width function (RWF) – for four internally drained catchments on the southwestern Greenland ice sheet surface. The routing models are forced identically using surface runoff from the Modèle Atmosphérique Régionale regional climate model (RCM). For each catchment, simulated moulin hydrographs are input to the SHAKTI subglacial hydrologic model to simulate diurnally varying subglacial effective-pressure variations in the vicinity of a single moulin. Overall, all three routing models produce more realistic moulin discharges than simply using RCM runoff outputs without surface routing but produce significant differences in peak moulin discharge and time to peak. In particular, the RWF yields later, smaller peak moulin discharges than the SUH or SRLF due to its representation of slow interfluve flow between supraglacial meltwater channels, and it can readily accommodate the seasonal evolution of supraglacial stream and river networks. Differences among the three routing models are reflected in a series of simple idealized subglacial hydrology simulations that yield different diurnal effective-pressure amplitudes; however, the supraglacial hydrologic system acts as short-term storage for surface meltwater, and the temporal mean effective pressure is relatively consistent across routing models.

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“…Therefore we extracted average values of MODIS snow and vegetation indices for each of the catchments and subcatchments, to track their seasonal evolution in greater detail. We calculated NDSI, the normalized difference snow index, as (GREEN-SWIR)/(GREEN + SWIR), where GREEN is band 4 and SWIR (shortwave infrared) is band 6, directly from daily surface reflectance data from the MODIS Terra and Aqua satellites, file series MOD09GA and MYD09GA (level 2G-lite, collection 6: Vermote et al, 2015). Terra and Aqua are identical satellites on nearly identical orbits, but Terra passes over Northern Hemisphere midlatitudes in the morning, and Aqua passes over Northern Hemisphere midlatitudes in the afternoon, so solar illumination of the surface differs between the two.…”

Section: Remote Sensing Evidence Of Snowpack Retreat and Expansion Ofmentioning

confidence: 99%

The pulse of a montane ecosystem: coupling between daily cycles in solar flux, snowmelt, transpiration, groundwater, and streamflow at Sagehen Creek and Independence Creek, Sierra Nevada, USA

Kirchner

Godsey

Solomon

et al. 2020

Hydrol. Earth Syst. Sci.

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Abstract. Water levels in streams and aquifers often exhibit daily cycles during rainless periods, reflecting daytime extraction of shallow groundwater by evapotranspiration (ET) and, during snowmelt, daytime additions of meltwater. These cycles can aid in understanding the mechanisms that couple solar forcing of ET and snowmelt to changes in streamflow. Here we analyze 3 years of 30 min solar flux, sap flow, stream stage, and groundwater level measurements at Sagehen Creek and Independence Creek, two snow-dominated headwater catchments in California's Sierra Nevada mountains. Despite their sharply contrasting geological settings (most of the Independence basin is glacially scoured granodiorite, whereas Sagehen is underlain by hundreds of meters of volcanic and volcaniclastic deposits that host an extensive groundwater aquifer), both streams respond similarly to snowmelt and ET forcing. During snow-free summer periods, daily cycles in solar flux are tightly correlated with variations in sap flow, and with the rates of water level rise and fall in streams and riparian aquifers. During these periods, stream stages and riparian groundwater levels decline during the day and rebound at night. These cycles are reversed during snowmelt, with stream stages and riparian groundwater levels rising during the day in response to snowmelt inputs and falling at night as the riparian aquifer drains. Streamflow and groundwater maxima and minima (during snowmelt- and ET-dominated periods, respectively) lag the midday peak in solar flux by several hours. A simple conceptual model explains this lag: streamflows depend on riparian aquifer water levels, which integrate snowmelt inputs and ET losses over time, and thus will be phase-shifted relative to the peaks in snowmelt and evapotranspiration rates. Thus, although the lag between solar forcing and water level cycles is often interpreted as a travel-time lag, our analysis shows that it is mostly a dynamical phase lag, at least in small catchments. Furthermore, although daily cycles in streamflow have often been used to estimate ET fluxes, our simple conceptual model demonstrates that this is infeasible unless the response time of the riparian aquifer can be determined. As the snowmelt season progresses, snowmelt forcing of groundwater and streamflow weakens and evapotranspiration forcing strengthens. The relative dominance of snowmelt vs. ET can be quantified by the diel cycle index, which measures the correlation between the solar flux and the rate of rise or fall in streamflow or groundwater. When the snowpack melts out at an individual location, the local groundwater shifts abruptly from snowmelt-dominated cycles to ET-dominated cycles. Melt-out and the corresponding shift in the diel cycle index occur earlier at lower altitudes and on south-facing slopes, and streamflow integrates these transitions over the drainage network. Thus the diel cycle index in streamflow shifts gradually, beginning when the snowpack melts out near the gauging station and ending, months later, when the snowpack melts out at the top of the basin and the entire drainage network becomes dominated by ET cycles. During this long transition, snowmelt signals generated in the upper basin are gradually overprinted by ET signals generated lower down in the basin. The gradual springtime transition in the diel cycle index is mirrored in sequences of Landsat images showing the springtime retreat of the snowpack to higher elevations and the corresponding advance of photosynthetic activity across the basin. Trends in the catchment-averaged MODIS enhanced vegetation index (EVI2) also correlate closely with the late springtime shift from snowmelt to ET cycles and with the autumn shift back toward snowmelt cycles. Seasonal changes in streamflow cycles therefore reflect catchment-scale shifts in snowpack and vegetation activity that can be seen from Earth orbit. The data and analyses presented here illustrate how streams can act as mirrors of the landscape, integrating physical and ecohydrological signals across their contributing drainage networks.

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Expansion and contraction of the flowing stream network alter hillslope flowpath lengths and the shape of the travel time distribution

Cited by 62 publications

References 43 publications

Multimodal water age distributions and the challenge of complex hydrological landscapes

Multimodal water age distributions and the challenge of complex hydrological landscapes

Intercomparison of surface meltwater routing models for the Greenland ice sheet and influence on subglacial effective pressures

The pulse of a montane ecosystem: coupling between daily cycles in solar flux, snowmelt, transpiration, groundwater, and streamflow at Sagehen Creek and Independence Creek, Sierra Nevada, USA

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