Variable source areas and storm-flow generation: An update of the concept and a simulation effort

Bernier, P.Y.

doi:10.1016/0022-1694(85)90055-1

Cited by 63 publications

(34 citation statements)

References 24 publications

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“…This event was also associated with an expansion of the stream network [e.g., Hewlett, 1974;Bernier, 1985;Swistock et al, 1989;Bazemore et al, 1994] at the event and seasonal timescales. Visual observations, corroborated by measurements in manually operated piezometers, suggest that the surface saturation pattern is patchy, without presenting slope-scale continuity, and appears to be closely associated with the microtopography.…”

Section: Discussionmentioning

confidence: 99%

Flow, mixing, and displacement in using a data‐based hydrochemical model to predict conservative tracer data

Iorgulescu

Beven

Musy

2007

Water Resources Research

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[1] We extend the data-based hydrochemical model of Iorgulescu et al. (2005), able to simulate discharge and reactive chemical tracer concentrations (silica and calcium) in streamflow for subcatchments of the Haute-Mentue research basin (Switzerland), to the prediction of additional d 18O values treated as a conservative tracer. The hydrochemical model is based on a parameterization of three runoff components (direct precipitation (DP), acid soil water (AS), and deep groundwater (GW)) in a chemical mixing model. Each component is modeled through an identical structure consisting of a nonlinear gain and a linear transfer function with two reservoirs (fast/slow) in parallel having a constant partition between them. We formulate a set of hypotheses concerning the isotope characterization of each component to provide additional information about how new rainfall inputs are processed in the hydrological response of the catchment. In particular, the AS component is modeled through a nested structure of hypotheses (models) of increasing complexity. It will be shown that hydrological processes in the hillslope associated with the DP, AS, and GW components are especially effective in filtering of higher-frequency fluctuations in precipitation isotopic ratios at the intraevent, interevent/seasonal, and annual/multiannual timescales. The highly nonlinear and nonstationary AS component represents predominantly ''recent'' water stored in the upper decimeters of the soil profile. Results also suggest that subsurface pathways are significant for the DP component. A local flow path mechanism is proposed for explaining the large fluxes of subsurface flows.Citation: Iorgulescu, I., K. J. Beven, and A. Musy (2007), Flow, mixing, and displacement in using a data-based hydrochemical model to predict conservative tracer data, Water Resour. Res., 43, W03401,

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Section: Discussionmentioning

confidence: 99%

Flow, mixing, and displacement in using a data‐based hydrochemical model to predict conservative tracer data

Iorgulescu

Beven

Musy

2007

Water Resources Research

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“…Many distributed, physically based models require large amounts of data and calibration, and have given mixed results (Bernier, 1985;Beven, 1989;Grayson et al, 1992;Wigmosta et al, 1994). Grayson et al (1992) concluded that although complex process-based models are useful in research, models used for management decisions should be simple and unpretentious, with few data requirements and clearly stated assumptions.…”

Section: Introductionmentioning

confidence: 99%

A GIS-based variable source area hydrology model

et al. 1999

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Abstract:Eective control of nonpoint source pollution from contaminants transported by runo requires information about the source areas of surface runo. Variable source hydrology is widely recognized by hydrologists, yet few methods exist for identifying the saturated areas that generate most runo in humid regions. The Soil Moisture Routing model is a daily water balance model that simulates the hydrology for watersheds with shallow sloping soils. The model combines elevation, soil, and land use data within the geographic information system GRASS, and predicts the spatial distribution of soil moisture, evapotranspiration, saturation-excess overland¯ow (i.e., surface runo), and inter¯ow throughout a watershed. The model was applied to a 170 hectare watershed in the Catskills region of New York State and observed stream¯ow hydrographs and soil moisture measurements were compared to model predictions. Stream¯ow prediction during non-winter periods generally agreed with measured¯ow resulting in an average r 2 of 0 . 73, a standard error of 0 . 01 m 3 /s, and an average Nash-Sutclie eciency R 2 of 0 . 62. Soil moisture predictions showed trends similar to observations with errors on the order of the standard error of measurements. The model results were most accurate for non-winter conditions. The model is currently used for making management decisions for reducing non-point source pollution from manure spread ®elds in the Catskill watersheds which supply New York City's drinking water.

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“…Radcliffe et al (1990) found that infiltration rates were considerably higher in a Cecil than an adjacent Pacolet soil because the horizon controlling infiltration, Bt1, occurred much deeper in the Cecil than the Pacolet. Much of the literature on the concept of variable sources of runoff generation addresses lowlying zones prone to saturation from surface and subsurface flow (i.e., O'Loughlin, 1981;Bernier 1985;Lyon et al (2004)). This research shows that the concept must be modified for areas in upper parts of landscapes underlain by restrictive horizons.…”

Section: Influence Of Soil Water On Runoff Generationmentioning

confidence: 99%

Soil Water Regime in Space and Time in a Small Georgia Piedmont Catchment under Pasture

Endale

Fisher

Schomberg

2006

Soil Science Soc of Amer J

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Soil water influences hydrological, biological, and biogeochemical processes that determine on-and off-site response of landscapes under different agricultural uses. There are relatively little detailed spatial and temporal soil water measurements to validate current representations of spatial and temporal soil water variability. Soil water was measured over 3 yr at 12 sites to a 1.2-m depth in a 7.8-ha pasture catchment in the Georgia Piedmont in southeastern USA. The Mahalanobis statistical difference was estimated between all pairs of measurement sites for soil water. Multidimensional scaling of the Mahalanobis differences showed that only a single statistical dimension was separating the observed soil water variations at measurement sites (r 5 0.99). This statistical dimension was then found to be most closely correlated with the depth to the Bt and the depth of the Ap horizons for explaining the observed variation in soil water between sampling sites (r 5 0.69 and r 5 0.8, respectively). Those sites where the Bt, an argillic horizon, was close to the surface, even when higher up the landscape, were generally wetter than those in which the Bt was deeper, even in the lower part of the landscape. The depth to the Bt horizon may serve as an indicator of the portions of the watershed most likely to be primary sources of runoff in association with the depth of overlying coarse-textured soil. Volumetric soil water content was generally greatest in winter (22 to 30% average) and least in summer (8 to 12% except when influenced by intense summer storms). To fully understand the soil water dynamics of Piedmont or similar landscapes, it is important to know the spatial distribution of the depth to the Bt horizon. Improved understanding of the soil water dynamics could lead to improved land use decisions, erosion control, and management of water resources. This should be of interest to many researchers across many disciplines.

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Variable source areas and storm-flow generation: An update of the concept and a simulation effort

Cited by 63 publications

References 24 publications

Flow, mixing, and displacement in using a data‐based hydrochemical model to predict conservative tracer data

Flow, mixing, and displacement in using a data‐based hydrochemical model to predict conservative tracer data

A GIS-based variable source area hydrology model

Soil Water Regime in Space and Time in a Small Georgia Piedmont Catchment under Pasture

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