Effect of catchment area on flood magnitude

Alexander, Gavin

doi:10.1016/0022-1694(72)90054-6

Cited by 54 publications

(36 citation statements)

References 3 publications

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“…The values of the drainage area exponents in the cited studies are summarized in Table 1, which shows that the exponent of the drainage area decreases generally with increased drainage area, which was in agreement with the results of Creager et al (1944) and Alexander (1972). The existing peak flow equations are primarily derived from the data on the watershed scale.…”

Section: Introductionsupporting

confidence: 86%

“…Later, Benson (1964) used data from semi-arid regions of Texas and New Mexico and found that θ was 0.59 for a return period of 2.33 yr. at 219 watersheds (2.5-91,000 km 2 ). Alexander (1972) obtained an average estimate of 0.7 for θ using data from U.S. and British catchments with drainage areas that varied from 130 km 2 to 5200 km 2 . Murphey et al (1977) found a mean θ value of 0.62 using data from 149 events and 11 watersheds in Walnut Gulch, Arizona, U.S. Goodrich et al (1997) also used data collected in the Walnut Gulch watershed and found that θ was 0.85 for 2-yr. return periods and drainage areas less than 1 km 2 but 0.55 for 2-yr. return periods and drainage areas exceeding 1 km 2 .…”

Section: Introductionmentioning

confidence: 99%

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Estimation of Peak Flow Rates for Small Drainage Areas

Liu

Wang

et al. 2017

Water Resour Manage

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Runoff plots are important for soil loss measurements, and increasing numbers of plots use automatic equipment. To choose equipment with appropriate capacities, the peak flow rate must be known. The peak flow rate is also an important parameter in the modified universal soil loss equation (MUSLE) which calculate the soil loss from upland slope. The available peak flow rate equations are primarily for the watershed scale, not for small drainage areas like runoff plot. This study's purpose was to derive an equation suitable for the small drainage areas. A total of 149 runoff events on 5 runoff plots were used to develop a peak flow rate equation for the hillslope scale. All plots are located in the Tuanshangou catchment, Zizhou county, Shaanxi province, China. Dimensionless analyses were used to determine the equation form of linear regression analyses. The results revealed that the peak flow rate was significantly correlated with plot area, slope steepness, runoff depth, rainfall depth and the maximum 30-min rainfall intensity. Two equations were developed to estimate peak flow. The model efficiencies of both equations exceeded 0.9. The equations developed in this study Water Resour Manage (2017) represent an important complement to existing peak flow rate equations. These new equations will facilitate the design of soil conservation practices and/or the selection of flow-observation equipment for small drainage areas.

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Section: Introductionsupporting

confidence: 86%

Section: Introductionmentioning

confidence: 99%

Estimation of Peak Flow Rates for Small Drainage Areas

Liu

Wang

et al. 2017

Water Resour Manage

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“…In this analysis, the higher flows are assumed to be equal to the ratio of the catchment area to the power of b. The exponent value, b, varies widely, ranging from 0·5 to 0·85 (see, e.g., Alexander, 1972); however, use of a median value of 0·7 is considered appropriate (Grayson et al, 1996).…”

Section: Data Collectionmentioning

confidence: 99%

Bank erosion and channel width change in a tropical catchment

Bartley¹,

Keen²,

Hawdon³

et al. 2008

Earth Surf Processes Landf

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Catchment sediment budget models are used to predict the location and rates of bank erosion in tropical catchments draining to the Great Barrier Reef lagoon, yet the reliability of these predictions has not been tested due to a lack of measured bank erosion data. This paper presents the results of a 3 year field study examining bank erosion and channel change on the Daintree River, Australia. Three different methods were employed: (1) erosion pins were used to assess the influence of riparian vegetation on bank erosion, (2) bench-marked cross-sections were used to evaluate annual changes in channel width and (3) historical aerial photos were used to place the short term data into a longer temporal perspective of channel change . The erosion pin data suggest that the mean erosion rate of banks with riparian vegetation is 6·5 times (or 85%) lower than that of banks without riparian vegetation. The changes measured from cross-section surveys suggest that channel width has increased by an average of 0·74 (± ± ± ± ±0·47) m a − − − − −1 over the study period (or ~0·8% yr − − − − −1 ). The aerial photo results suggest that over the last 30 years the Daintree River has undergone channel contraction of the order of 0·25 m a − − − − −1 . The cross-section data were compared against modelled SedNet bank erosion rates, and it was found that the model underestimated bank erosion and was unable to represent the variable erosion and accretion processes that were observed in the field data. The reach averaged bank erosion rates were improved by the inclusion of locally derived bed slope and discharge estimates; however, the results suggest that it will be difficult for catchment scale sediment budget models to ever accurately predict the location and rate of bank erosion due to the variation in bank erosion rates in both space and time. Figure 1. (A) Daintree River catchment, showing the location of the main stream gauge, broad vegetation types and major tributaries. (B) Study reach between the stream gauge and Daintree Village, showing the location of field monitoring sites and additional aerial photo cross-sections and pin sites. This figure is available in colour online at

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“…Similar relation has been widely explored in flood calculations (e.g. Jarvis 1936, Alexander 1972, Willgoose et al 1991, where the quantities are of the total valley. Distinction here relies on the fact that debris flow is not really a full-valley process.…”

Section: Figurementioning

confidence: 83%

A probabilistic view of debris flow

Cui

et al. 2008

J. Mt. Sci.

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Most debris flows occur in valleys of area smaller than 50 km 2 . While associated with a valley, debris flow is by no means a full-valley event but originates from parts of the valley, i.e., the tributary sources. We propose that debris flow develops by extending from tributaries to the mainstream. The debris flow observed in the mainstream is the confluence of the tributary flows and the process of the confluence can be considered as a combination of the tributary elements. The frequency distribution of tributaries is found subject to the Weibull form (or its generalizations). And the same distribution form applies to the discharge of debris flow. Then the process of debris flow is related to the geometric structure of the valley. Moreover, viewed from a large scale of water system, all valleys are tributaries, which have been found to assume the same distribution. With each valley corresponding to a debris flow, the distribution can be taken as the frequency distribution of debris flow and therefore provides a quantitative description of the fact that debris flow is inclined to occur at valley of small size. Furthermore, different parameters appear in different regions, suggesting the regional differentials of debris flow potential. We can use the failure rate, instead of the size per se, to describe the risk of a valley of a given area. Finally we claim that the valleys of debris flow in different regions are in the similar episode of evolution.

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Effect of catchment area on flood magnitude

Cited by 54 publications

References 3 publications

Estimation of Peak Flow Rates for Small Drainage Areas

Estimation of Peak Flow Rates for Small Drainage Areas

Bank erosion and channel width change in a tropical catchment

A probabilistic view of debris flow

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