Scaling property of regional floods in New South Wales Australia

Ishak, Elias H; Haddad, Khaled; Zaman, Mohammad A; Rahman, Ataur

doi:10.1007/s11069-011-9719-6

Cited by 34 publications

(25 citation statements)

References 29 publications

(43 reference statements)

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“…Previous investigators have sought to identify well‐behaved, homogenous regions suitable for the application of techniques like the index‐flood method [ Skaugen and Vaeringstad , ]. Because of the practical importance of the problem, most research on spatial scaling has focused on flood flows [ Gupta and Waymire , ; Smith , ; Gupta et al ., ; Dawdy and Gupta , ; Gupta and Dawdy , ; Pandey , ; Eaton et al ., ; Yue and Gan , ; Ishak et al ., ]. Additionally, some studies have examined the scaling behavior of mean annual flows: Vogel and Sankarasubramanian [] found that U.S. mean annual flows exhibited simple scaling while Yue and Gan [] and Buttle and Eimers [] reached similar conclusions with respect to flows in Canada.…”

Section: Introductionmentioning

confidence: 99%

“…Typical of the wider literature, the studies reviewed for this work almost exclusively considered drainage area alone when examining scaling behavior [ Yue and Gan , ; Yue and Wang , , among others], though some studies consider, at most, one or two other explanatory variables, including precipitation [ Modarres , ] and rainfall intensities and stream density [ Ishak et al ., ]. Ishak et al .…”

Section: Introductionmentioning

confidence: 99%

“…Ishak et al . [] considered other variables, but found them to be insignificant. Even if the goal is to understand how streamflow scales with drainage area, excluding other variables in regression analyses can lead to significant confusion or misinterpretation.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Multiple regression and inverse moments improve the characterization of the spatial scaling behavior of daily streamflows in the Southeast United States

Farmer

Over

Vogel

2015

Water Resources Research

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Understanding the spatial structure of daily streamflow is essential for managing freshwater resources, especially in poorly gaged regions. Spatial scaling assumptions are common in flood frequency prediction (e.g., index-flood method) and the prediction of continuous streamflow at ungaged sites (e.g. drainage-area ratio), with simple scaling by drainage area being the most common assumption. In this study, scaling analyses of daily streamflow from 173 streamgages in the southeastern United States resulted in three important findings. First, the use of only positive integer moment orders, as has been done in most previous studies, captures only the probabilistic and spatial scaling behavior of flows above an exceedance probability near the median; negative moment orders (inverse moments) are needed for lower streamflows. Second, assessing scaling by using drainage area alone is shown to result in a high degree of omitted-variable bias, masking the true spatial scaling behavior. Multiple regression is shown to mitigate this bias, controlling for regional heterogeneity of basin attributes, especially those correlated with drainage area. Previous univariate scaling analyses have neglected the scaling of low-flow events and may have produced biased estimates of the spatial scaling exponent. Third, the multiple regression results show that mean flows scale with an exponent of one, low flows scale with spatial scaling exponents greater than one, and high flows scale with exponents less than one. The relationship between scaling exponents and exceedance probabilities may be a fundamental signature of regional streamflow. This signature may improve our understanding of the physical processes generating streamflow at different exceedance probabilities.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Multiple regression and inverse moments improve the characterization of the spatial scaling behavior of daily streamflows in the Southeast United States

Farmer

Over

Vogel

2015

Water Resources Research

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“…One of the most important objectives in regional Flood Frequency Analysis (FFA) is to design flood estimates for regions for which there are no observational data. Flood estimates have been used to design hydraulic structures, such as dams, cheddars, brigs, channels, and other structures that are used in flood management (Aziz, Rahman, Fang, & Shrestha, ; Cunnane, ; Ishak, Haddad, Zaman, & Rahman, ; Merz & Blöschl, ; Ouarda, Girard, Cavadias, & Bobee, ; Taylor, Haddad, Zaman, & Rahman, ). The risk of damage from flooding can be greatly reduced if the construction of various structures and the development of towns and villages are based on flood forecasting and information.…”

Section: Introductionmentioning

confidence: 99%

Flood frequency analysis for the Iranian interior deserts using the method ofL‐moments: A case study in the Loot River Basin

Mesbahzadeh

Sardoo

Kouhestani

2019

Natural Resource Modeling

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Floods are one of the greatest natural disasters, especially in arid land ecosystems. These phenomena damage fragile ecosystems and human societies. If construction of various structures and the development of towns and villages are based on flood forecasting and information, the risk of damage from flooding can be reduced to a large extent. We analyzed the frequency of flooding in the Loot Basin, central Iran, using annual peak discharge series and the method of maximum L‐moment. We found that the distribution based on the H test was homogeneous and the ZDIST statistic selected a regional Log Pearson Type III (LPIII) distribution. The results also showed a high correlation coefficient between the return period and flood discharge, and it was possible to estimate the relationship between flood discharge and area parameters. These methods can be used for areas which lack observational data or statistics. Recommendations for Resource Managers Floods are one of the most destructive of natural phenomena, especially in arid and semiarid regions. It is important to be aware of the flood peaks in areas without statistics. In arid and semiarid regions, there is always a lack of information. Frequency analysis methods are useful in these areas. The method of L‐moments is one of the most widely used methods for analyzing the frequency of floods. This method predicts the future behavior of data using statistical distributions. In areas without observational data or statistics, such as the Loot River Basin, Iran, the method of L‐moments can be used to predict floods by using the physical characteristics of the watersheds.

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“…2) with a maximum of 2.5 m in some areas. Several methods have been proposed for creating flood estimation models for areas lacking gauging stations by using empirical, regression, curve number method, for determining the rainfall-runoff relationships [Ishak et al, 2011;Liu et al, 2011;Subyani, 2011;Sen 2008a]. In the present work we aim to use the SCS (Soil Conservation System) Curve Number method to create a flood hazard zone based on runoff values from rainfall data for the flooding event of November 23-24th 2006.…”

Section: Introductionmentioning

confidence: 99%

Flooding in Jamaica with assessment of riverine inundation of Port Maria, St Mary

Mandal

Maharaj

2013

Bulletin De La Société Géologique De France

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Flash flooding, from extreme rainfall is one of the major natural disasters affecting Jamaica and other small island states of the Caribbean. Flooding in Jamaica is mainly riverine, coastal and depression with the major coastal towns being affected owing to their location on low lying areas. Such localization is driven by increase in urbanization and tourism along the coastal areas. The present work aims in a broad discussion of the flooding in Jamaica with special reference to riverine flooding of Port Maria, the capital of St Mary, one of the parishes lying in the high rain zone of the island and being affected by repeated events of flooding. Analysis of the extreme rainfall event of November 23 rd -24 th , 2006 shows that it exceeded the 30 yr annual rainfall of the area and the 100 yr return period as calculated from 30 yr annual rainfall data for the island. The Port Maria river lacks a gauging station to monitor flow data and flood discharge peaks. Several methods are used to calculate the run-off in such small ungauged catchments. In this study the Soil Conservation Systems Curve Number (CN) method was used to calculate the run-off from the measured rainfall data using empirical equations. Results show an unprecedented high of 13-14 inches affecting the buildings and other infrastructures, leading to the collapse of a newly constructed bridge over the river Port Maria. The town continues to get flooded from intense short duration rainfall continuing to affect life and property. Flood plain maps exist for the larger watersheds of the island but smaller yet flood prone ones have not been mapped so far. Hence this becomes very important to create a floodplain map showing the extent of the runoff from rainfall with respect to the buildings and other infrastructures of the area. The present work thus aims in creating a spatial distribution map of the runoff from the rainfall measurements aiding in developing a no build zone for this and for other low lying coastal areas of the island.

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Scaling property of regional floods in New South Wales Australia

Cited by 34 publications

References 29 publications

Multiple regression and inverse moments improve the characterization of the spatial scaling behavior of daily streamflows in the Southeast United States

Multiple regression and inverse moments improve the characterization of the spatial scaling behavior of daily streamflows in the Southeast United States

Flood frequency analysis for the Iranian interior deserts using the method ofL‐moments: A case study in the Loot River Basin

Flooding in Jamaica with assessment of riverine inundation of Port Maria, St Mary

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