Methodology for a multi-country study of soil erosion management

Ciesiolka, C.A.A.; Coughlan, K.; Rose, C. W.; Escalante, M.C.; Hashim, Ghulam M.; Paningbatan, Eduardo P.; Sombatpanit, S.

doi:10.1016/0933-3630(95)00018-6

Cited by 80 publications

(60 citation statements)

References 9 publications

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“…(4) with b = 0.4 (Eq. 5, Ciesiolka et al, 1995), also in reasonable agreement with the data in Table 2, and an a value that is the same for the three watersheds but remains a function of the cumulative rainfall during the rainy phase of the monsoon. Thus, the concentration per unit cropland, C c (averaged over a 14-day period), is…”

Section: Impact Of Croplandsupporting

confidence: 85%

“…4) show the expected general trend downward (but not consistently) as the season progresses (Table 2) and the sediment concentration decreases, however the b exponent does not show the subsequent upward trend suggested by Vanmaercke et al (2010) and Asselman (2000) for changing transport dynamics. Instead, the b exponent stays around the 0.3-0.4 value proposed by Ciesiolka et al (1995) and Yu et al (1997) for a physically based erosion equation. The authors argue that the value b = 0.4 can be derived by assuming that the velocity and the concentration are linearly related in the stream power equation.…”

Section: Similarity Of All Three Watershedsmentioning

confidence: 71%

“…Ciesiolka et al (1995) estimated that a power of 0.4 in this equation is appropriate for the upper limit of sediment concentration (transport limit) using the kinematic flow approximation and assumption of turbulent flow. This value will fluctuate by an erodibility factor, β, which is multiplied by the exponent for the average sediment concentration.…”

Section: Sediment Rating Curvesmentioning

confidence: 99%

“…5. The exponent for the early part was adjusted to 0.45, rising just above 0.4, which according to Ciesiolka et al (1995), Paningbatan et al (1995) and occurs when processes other than flow-driven erosion contribute significantly to the sediment supply, i.e., gully formation, tillage, rain-drop impact erosion, etc. The coefficients of determination for these theoretical rating curve equations become quite good at R 2 = 0.40, 0.63, and 0.60 for the early, middle, and late rainfall periods, respectively.…”

Section: Impact Of Croplandmentioning

confidence: 99%

“…The mean square error for the theoretical rating curves decreases consistently from the early rainfall rating curve to the late rainfall rating curve. Consequently, basing the exponent on the physically based derivations of Ciesiolka et al (1995) and Yu et al (1997) and normalizing by fractional cropland has improved the fit and R 2 of the rating curves. The sediment concentration-discharge points become now quite tight around the theoretical rating curve line, especially when compared to initial sediment concentration data plotted as a function of runoff amounts (Fig.…”

Section: Impact Of Croplandmentioning

confidence: 99%

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Suspended sediment concentration–discharge relationships in the (sub-) humid Ethiopian highlands

Guzmán

Tilahun

Zegeye

et al. 2013

Hydrol. Earth Syst. Sci.

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Abstract. Loss of top soil and subsequent filling up of reservoirs in much of the lands with variable relief in developing countries degrades environmental resources necessary for subsistence. In the Ethiopia highlands, sediment mobilization from rain-fed agricultural fields is one of the leading factors causing land degradation. Sediment rating curves, produced from long-term sediment concentration and discharge data, attempt to predict suspended sediment concentration variations, which exhibit a distinct shift with the progression of the rainy season. In this paper, we calculate sediment rating curves and examine this shift in concentration for three watersheds in which rain-fed agriculture is practiced to differing extents. High sediment concentrations with low flows are found at the beginning of the rainy season of the semi-monsoonal climate, while high flows and low sediment concentrations occur at the end of the rainy season. Results show that a reasonably unique set of rating curves were obtained by separating biweekly data into early, mid, and late rainfall periods and by making adjustments for the ratio of plowed cropland. The shift from high to low concentrations suggests that diminishing sediment supply and dilution from greater base flow during the end of the rainfall period play important roles in characterizing changing sediment concentrations during the rainy season.

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Section: Impact Of Croplandsupporting

confidence: 85%

Section: Similarity Of All Three Watershedsmentioning

confidence: 71%

Section: Sediment Rating Curvesmentioning

confidence: 99%

Section: Impact Of Croplandmentioning

confidence: 99%

Section: Impact Of Croplandmentioning

confidence: 99%

See 3 more Smart Citations

Suspended sediment concentration–discharge relationships in the (sub-) humid Ethiopian highlands

Guzmán

Tilahun

Zegeye

et al. 2013

Hydrol. Earth Syst. Sci.

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Use of GUEST Technology to Parameterize a Physically‐Based Model for Assessing Soil Erodibility and Evaluating Conservation Practices in Tropical Steeplands

Rose

Misra

Coughlan

et al. 2010

Handbook of Erosion Modelling

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Probably the largest body of data on soil erosion has been that collected using the USLE methodology, thus lacking measurement of runoff rates. In the ASIALAND section of this chapter it is demonstrated that the GUEST methodology can be applied to data collected for analysis using the USLE methodology. Thus there is the opportunity, in future, to analyse other USLE data sets to yield values of β which would be expected to provide further evidence of how soil erodibility is affected by soil characteristics and soil management (eg. Fig. 11.9). The advantage of using the erodibility parameter β described in the GUEST methodology is that it has an approximate physical basis in fundamental soil erosion theory. In comparison, the soil erodibility K in the USLE equation is simply a proportionality factor introduced to ensure agreement between measured soil loss and the adopted product-type arrangement of other factors which do not include runoff or runoff rate.Field applications of the GUEST program, such as those recorded in this chapter for the ACIAR and ASIALAND projects, benefited from a more fundamental controlled erosion program using simulated rainfall equipment (eg. Proffitt et al. 1993b; Misra and Rose 1995, 1996). These controlled studies supported the theory used in program GUEST, and

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The erosive growth of hillside gullies

Rose

Ward

Saxton

et al. 2014

Earth Surf Processes Landf

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The rate of erosion of hillside gullies depends both on gully flow characteristics and the resistance offered by the gully soil profile to erosion. This paper describes a method for quantifying a physically‐based resistance measure, illustrated by application to a gully feeding sediment into the Bremer River, southeast Queensland, Australia. The dynamics of discharge down the gully during runoff events is the driver of erosion, but this was unknown. A new method is described whereby this unmeasured flow can be estimated using data on rainfall rate and river gauge monitoring. The data collected on the gully was the increase in dimensions and volume (and so soil loss) over a two year period. This information was obtained from a digital elevation model (DEM) of the catchment, derived from Light Detection and Ranging (LiDAR) observations made at either end of the two year period. The soil profile resistance characteristic evaluated is the energy required to erode a unit mass of soil from the gully walls, a physically‐defined parameter, J, present in flow‐driven erosion theory, which was adapted and applied to predict soil loss from the Bremer River gully. The value of J was evaluated by equating predicted to measured gully soil loss over the two year period using two alternative descriptions of gully cross‐section. Firstly a realistic gully shape description was used, made possible by LiDAR data, yielding J = 405.5 J/kg. Secondly, in order to allow use of more widely‐available aerial photography for such studies, the simplifying assumption of a semi‐circular gully shape was made, yielding J = 455 J/kg. Allowing a ±30% error in estimated effective runoff rate for this ungauged gully, the estimated J value would have an uncertainty of +1%/−7% using the actual gully geometry. The assumptions made in estimating J are discussed, and possible applications of this information listed. Copyright © 2014 John Wiley & Sons, Ltd.

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Methodology for a multi-country study of soil erosion management

Cited by 80 publications

References 9 publications

Suspended sediment concentration–discharge relationships in the (sub-) humid Ethiopian highlands

Suspended sediment concentration–discharge relationships in the (sub-) humid Ethiopian highlands

Use of GUEST Technology to Parameterize a Physically‐Based Model for Assessing Soil Erodibility and Evaluating Conservation Practices in Tropical Steeplands

The erosive growth of hillside gullies

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