Distributed parameter hydrology model (ANSWERS) applied to a range of catchment scales using rainfall simulator data I: Infiltration modelling and parameter measurement

Silburn, D. M.; Connolly, R. D.

doi:10.1016/0022-1694(95)02740-g

Cited by 40 publications

(22 citation statements)

References 17 publications

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“…Variations of measured and predicted infiltration rate with time for Plot30 and Plot75 during the two simulated rainfalls. Two modelling scenarios are presented: the first (Model Kvar) assumed that the hydraulic conductivity decreases exponentially with time (Silburn and Connolly, 1995), while the second (Model Kconst) considered that the hydraulic conductivity is constant (final value K f , see Table 6). …”

Section: Generation Of High-resolution Bulk Density Imagesmentioning

confidence: 99%

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Impact of slope gradient on soil surface features and infiltration on steep slopes in northern Laos

Ribolzi¹,

Patin²,

Bresson³

et al. 2011

Geomorphology

147

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Section: Generation Of High-resolution Bulk Density Imagesmentioning

confidence: 99%

“…Chahinian et al (2006) successfully used this approach to simulate the infiltration dynamics in a layered soil, under field conditions. We used the Green and Ampt model considering that the hydraulic conductivity decreases exponentially with time as indicated by Silburn and Connolly (1995):…”

Section: Model Of Dynamic Infiltration Through Sloping Soil Surfacesmentioning

confidence: 99%

Impact of slope gradient on soil surface features and infiltration on steep slopes in northern Laos

Ribolzi¹,

Patin²,

Bresson³

et al. 2011

Geomorphology

147

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“…Time to ponding was recorded, together with rainfall and runoff using tipping bucket methodology (Ciesiolka et al 1995). Infiltration rate and total infiltration were calculated by subtracting runoff rate and total runoff from rainfall rate and total rainfall at any time, neglecting surface retention (Silburn and Connolly 1995). Each run of the rainfall simulation covered 2 subplots (0.75 m by 2 m each), so that a total of 24 rainfall simulation subplots were conducted (Fig.…”

Section: Rainfall Simulationmentioning

confidence: 99%

Traffic and residue cover effects on infiltration

Li¹,

Tullberg²,

Freebairn³

2001

Soil Res.

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Wheel traffic can lead to compaction and degradation of soil physical properties. This study, as part of a study of controlled traffic farming, assessed the impact of compaction from wheel traffic on soil that had not been trafficked for 5 years. A tractor of 40 kN rear axle weight was used to apply traffic at varying wheelslip on a clay soil with varying residue cover to simulate effects of traffic typical of grain production operations in the northern Australian grain belt. A rainfall simulator was used to determine infiltration characteristics.Wheel traffic significantly reduced time to ponding, steady infiltration rate, and total infiltration compared with non-wheeled soil, with or without residue cover. Non-wheeled soil had 4-5 times greater steady infiltration rate than wheeled soil, irrespective of residue cover. Wheelslip greater than 10% further reduced steady infiltration rate and total infiltration compared with that measured for self-propulsion wheeling (3% wheelslip) under residue-protected conditions. Where there was no compaction from wheel traffic, residue cover had a greater effect on infiltration capacity, with steady infiltration rate increasing proportionally with residue cover (R 2 = 0.98). Residue cover, however, had much less effect on infiltration when wheeling was imposed.These results demonstrated that the infiltration rate for the non-wheeled soil under a controlled traffic zero-till system was similar to that of virgin soil. However, when the soil was wheeled by a medium tractor wheel, infiltration rate was reduced to that of long-term cropped soil. These results suggest that wheel traffic, rather than tillage and cropping, might be the major factor governing infiltration. The exclusion of wheel traffic under a controlled traffic farming system, combined with conservation tillage, provides a way to enhance the sustainability of cropping this soil for improved infiltration, increased plant-available water, and reduced runoff-driven soil erosion.

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“…However, as processes dominating infiltration and surface runoff generation may vary inter-and intra-annually Vivoni et al, 2007) and even within an event (e.g. Silburn and Connolly, 1995), it is important to address potential switches between runoff generation mechanisms in advanced modelling approaches Tian et al, 2012).…”

Section: P Fiener Et Al: Surface Runoff From Arable Fields In Centrmentioning

confidence: 99%

“…Auerswald et al, 1994;Silburn and Connolly, 1995;Choudhary et al, 1995) and thus acknowledge the prominent impact of tillage on runoff. However, these comparisons are usually done between treatments, while the changes over time are hardly considered although tillage impacts many physical and biological soil properties, which then gradually change until the next tillage (Caron et al, 1992;Dexter et al, 1998;Franzluebbers et al, 1995;Zobeck and Onstad 1987).…”

Section: Hydrograph Shapementioning

confidence: 99%

Statistical analysis and modelling of surface runoff from arable fields in central Europe

Fiener

Auerswald²,

Winter³

et al. 2013

Hydrol. Earth Syst. Sci.

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Abstract. Surface runoff generation on arable fields is an important driver of flooding, on-site and off-site damages by erosion, and of nutrient and agrochemical transport. In general, three different processes generate surface runoff (Hortonian runoff, saturation excess runoff, and return of subsurface flow). Despite the developments in our understanding of these processes it remains difficult to predict which processes govern runoff generation during the course of an event or throughout the year, when soil and vegetation on arable land are passing many states. We analysed the results from 317 rainfall simulations on 209 soils from different landscapes with a resolution of 14 286 runoff measurements to determine temporal and spatial differences in variables governing surface runoff, and to derive and test a statistical model of surface runoff generation independent from an a priori selection of modelled process types. Measured runoff was related to 20 time-invariant soil properties, three variable soil properties, four rain properties, three land use properties and many derived variables describing interactions and curvilinear behaviour. In an iterative multiple regression procedure, six of these properties/variables best described initial abstraction and the hydrograph. To estimate initial abstraction, the percentages of stone cover above 10 % and of sand content in the bulk soil were needed, while the hydrograph could be predicted best from rain depth exceeding initial abstraction, rainfall intensity, soil organic carbon content, and time since last tillage. Combining the multiple regressions to estimate initial abstraction and surface runoff allowed modelling of event-specific hydrographs without an a priori assumption of the underlying process. The statistical model described the measured data well and performed equally well during validation. In both cases, the model explained 71 and 58 % of variability in accumulated runoff volume and instantaneous runoff rate (RSME: 5.2 mm and 0.23 mm min −1 , respectively), while RMSE of runoff volume predicted by the curve number model was 50 % higher (7.7 mm). Stone cover, if it exceeded 10 %, was most important for the initial abstraction, while time since tillage was most important for the hydrograph. Time since tillage is not taken into account either in typical lumped hydrological models (e.g. SCS curve number approach) or in more mechanistic models using Horton, Green and Ampt, or Philip type approaches to address infiltration although tillage affects many physical and biological soil properties that subsequently and gradually change again. This finding should foster a discussion regarding our ability to predict surface runoff from arable land, which seemed to be dominated by agricultural operations that introduce man-made seasonality in soil hydraulic properties.

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Distributed parameter hydrology model (ANSWERS) applied to a range of catchment scales using rainfall simulator data I: Infiltration modelling and parameter measurement

Cited by 40 publications

References 17 publications

Impact of slope gradient on soil surface features and infiltration on steep slopes in northern Laos

Impact of slope gradient on soil surface features and infiltration on steep slopes in northern Laos

Traffic and residue cover effects on infiltration

Statistical analysis and modelling of surface runoff from arable fields in central Europe

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