Similarity in Catchment Response: 1. Stationary Rainstorms

Saghafian, Bahram; Juliën, Pierre Y.; Ogden, Fred L.

doi:10.1029/95wr00518

Cited by 72 publications

(50 citation statements)

References 19 publications

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“…[32] Several authors noted that q 5 1 is a critical value in the Monte-Carlo simulation of hillslopes or catchments [Saghafian et al, 1995;Nahar et al, 2004;Morbidelli et al, 2006;Jones et al, 2009]. The case of a periodic variation of infiltrability best illustrates the transition at q 5 1.…”

Section: Fðyþgðx2yþdymentioning

confidence: 99%

“…Vegetation, topography, and soil surface properties (natural or anthropogenic) are recognized to be important sources of variability [Dunne et al, 1991]. Runon, which reduces the total runoff volume and sediment yield, is a hydrological process which must be taken into account in models [Saghafian et al, 1995;Woolhiser et al, 1996;Howes and Abrahams, 2003;Adams et al, 2012]. Because of runon, the runoff volume at the stream is less than the sum of the volumes produced by each pixel of the hillslope or catchment.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, infiltration variability and microtopography, two properties that may be spatially correlated, give rise to the runoff-runon process. That is, runoff generated on an area with low infiltration capacity flows downslope and may infiltrate in another area with higher infiltration capacity [Hawkins and Cundy, 1987;Saghafian et al, 1995;Corradini et al, 1998]. …”

Section: Introductionmentioning

confidence: 99%

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1-D steady state runoff production in light of queuing theory: Heterogeneity, connectivity, and scale

Harel

Mouche

2013

Water Resour. Res.

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[1] We used the frameworks of queuing theory and connectivity to study the runoff generated under constant rainfall on a one-dimensional slope with randomly distributed infiltrability. The equivalence between the stationary runoff-runon equation and the customers waiting time in a single server queue provides a theoretical link between the statistical description of infiltrability and that of runoff flow rate. Five distributions of infiltrability, representing soil heterogeneities at different scales, are considered: four uncorrelated (exponential, bimodal, lognormal, uniform) and one autocorrelated (lognormal, with or without a nugget). The existing theoretical results are adapted to the hydrological framework for the exponential case, and new theoretical developments are proposed for the bimodal law. Numerical simulations validate these results and improve our understanding of runoff-runon for all of the distributions. The quantities describing runoff generation (runoff one-point statistics) and its organization into patterns (patterns statistics and connectivity) are studied as functions of rainfall rate. The variables describing the wet areas are also compared to those describing the rainfall excess areas, i.e., the areas where rainfall exceeds infiltrability. Preliminary results concerning the structural and functional connectivity functions are provided, as well as a discussion about the origin of scale effects in such a system. We suggest that the upslope no-flow boundary condition may be responsible for the dependence of the runoff coefficient on the scale of observation. Queuing theory appears to be a promising framework for runoff-runon modeling and hydrological connectivity problems.Citation: Harel, M.-A., and E. Mouche (2013), 1-D steady state runoff production in light of queuing theory: Heterogeneity, connectivity, and scale, Water Resour. Res., 49,[7973][7974][7975][7976][7977][7978][7979][7980][7981][7982][7983][7984][7985][7986][7987][7988][7989][7990][7991]

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Section: Fðyþgðx2yþdymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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1-D steady state runoff production in light of queuing theory: Heterogeneity, connectivity, and scale

Harel

Mouche

2013

Water Resour. Res.

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“…These basic factors hold when one extends the analysis to infiltration in locally nonuniform soil profiles or spatially varying systems at the scale of the field or the watershed. A large body of research has shown that spatial variability of soil properties affect infiltration at such scale [Russo and Bresler, 1982;Sivapalan and Wood, 1986;Saghafian et al, 1995]. The effect of local heterogeneity within the soil profile on infiltration was also demonstrated for layered or nonuniform soils, mainly relying on the Green and Ampt [1911] approach [Childs and Bybordi, 1969;Beven, 1984;Selker et al, 1999;Chu and Marino, 2005].…”

Section: Introductionmentioning

confidence: 99%

A simple accurate method to predict time of ponding under variable intensity rainfall

Assouline

Selker

Parlange

2007

Water Resources Research

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[1] The prediction of the time to ponding following commencement of rainfall is fundamental to hydrologic prediction of flood, erosion, and infiltration. Most of the studies to date have focused on prediction of ponding resulting from simple rainfall patterns. This approach was suitable to rainfall reported as average values over intervals of up to a day but does not take advantage of knowledge of the complex patterns of actual rainfall now commonly recorded electronically. A straightforward approach to include the instantaneous rainfall record in the prediction of ponding time and excess rainfall using only the infiltration capacity curve is presented. This method is tested against a numerical solution of the Richards equation on the basis of an actual rainfall record. The predicted time to ponding showed mean error 7% for a broad range of soils, with and without surface sealing. In contrast, the standard predictions had average errors of 87%, and worst-case errors exceeding a factor of 10. In addition to errors intrinsic in the modeling framework itself, errors that arise from averaging actual rainfall records over reporting intervals were evaluated. Averaging actual rainfall records observed in Israel over periods of as little as 5 min significantly reduced predicted runoff (75% for the sealed sandy loam and 46% for the silty clay loam), while hourly averaging gave complete lack of prediction of ponding in some of the cases.

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“…However, the efficacy of such water harvesting systems depends on the accuracy of the predicted hydrological response of the water catchments to the local rainfall. Spatial and temporal variability of soil and rainfall properties influence the infiltration process, and consequently, the generation of surface flow [Singh, 1997;Saghafian et al, 1995]. These variables dominate also the process of the soil surface sealing [Assouline, 2004].…”

Section: Introductionmentioning

confidence: 99%

Runoff from heterogeneous small bare catchments during soil surface sealing

Assouline

Mualem

2006

Water Resources Research

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[1] The combined effects of areal heterogeneity of the soil hydraulic properties and the surface seal formation dominate the hydrological response of arid and semiarid water catchments. Here these two phenomena were simulated to study their mutual role in runoff generation in small bare catchments. Seal formation during rainfall was simulated applying the dynamic model of Assouline and Mualem (1997). Areal heterogeneity of the soil was represented by a lognormal distribution of the saturated hydraulic conductivity of the initially undisturbed soil, K s , and by related distributions of the other soil parameters. The runoff hydrograph, at the outlet of a hypothetical bare catchment of 0.5 km 2 , was calculated using the cell model of Diskin et al. (1984). Two water catchments types, homogeneous and heterogeneous, with two different soil surface states, unsealed (mulched) and ongoing dynamic sealing, were considered. Four spatial organizations of the 10 cells in the heterogeneous catchment, all representing the same discrete distribution of K s , were studied. Rainfall events of two rainfall intensities, 20 and 40 mm h À1, of different durations ranging from 10 to 120 min, were applied uniformly over the catchments to study the effect of rainfall intensity and duration on runoff characteristics under the different soils and catchments conditions. The state of the soil surface seal was found to be a dominant factor with regard to runoff generation. Relative to the runoff produced in the homogeneous unsealed catchment under a (40 mm h À1 , 45 min) rainfall, the runoff was augmented by a factor of 10 during soil surface sealing and still more, by a factor of 20, when the soil surface was already sealed. On a relative basis the impact of soil sealing on runoff is much more important than that of soil heterogeneity. The effect of areal heterogeneity on runoff seems to depend on both the soil surface condition and the rainfall intensity and duration. When the soil is unsealed, the total runoff and the discharge peak are higher for the heterogeneous catchment. When the soil surface undergoes a sealing process, the total runoff and the discharge peak are higher for the heterogeneous catchment for the lower rainfall intensity of 20 mm h À1. For the 40 mm h À1 rainfall the catchment relative response was found to depend on the rainfall duration. A higher peak was obtained in the homogeneous catchment for rainfall durations above 60 min, and more runoff was produced for rainfall durations above 90 min. The spatial pattern of the cell organization in the heterogeneous catchment is an additional factor affecting the hydrological response. The hydrographs corresponding to each of four patterns representing the same areal heterogeneity displayed differences regarding concentration time (which varied between 7 and 28 min), timing of the peak runoff (varying between 77 and 146 min), and the peak discharge (varying between 0.41 and 0.57 m 3 s À1 ).Citation: Assouline, S., and Y. Mualem (2006), Runoff from heterogeneous small bare c...

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Similarity in Catchment Response: 1. Stationary Rainstorms

Cited by 72 publications

References 19 publications

1-D steady state runoff production in light of queuing theory: Heterogeneity, connectivity, and scale

1-D steady state runoff production in light of queuing theory: Heterogeneity, connectivity, and scale

A simple accurate method to predict time of ponding under variable intensity rainfall

Runoff from heterogeneous small bare catchments during soil surface sealing

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