Methods For Designing Regional Flood Estimation: A review

Methods For Designing Regional Flood Estimation: A review

Abstract

Regional flood estimation methods are necessary to estimate design of hydrological processes and structures related to it. It is also required to estimate the risks associated with hydraulic structures. The major issue regarding flood estimation method is that these methods were developed in late 1970’s and require a time to time up gradation with respect to new approaches. This paper is a collaboration of various studies that will form the basis of future recommendations and needs to upgrade methods for designing accurate flood estimates. The paper suggested that rational method approach is the most widely used method worldwide comparative to others. This paper reviews the need to develop a regional approach for design flood estimates.

Keywords: Regional flood estimation, Designing and Rational method, other approaches

Introduction

Flood is a natural disaster that affects a considerable part of world every year causing a great extent of damage. There is a need to quantify the magnitude of risks associated with floods in order to minimize damage. Regional flood estimation methods, are important for proper planning, accuracy and functioning of hydraulic structures such as causeways, dams, culverts, small bridges etc. (Rahman et al., 1998; Pegram and Parak, 2004; Reis and Stedinger, 2005).

Peak flows, volume, rate, velocity and duration are some of the statistical analysis kept in mind while working with standard techniques of flood estimation (Cameron et al., 1999). Regional flood design can be estimated using rainfall or runoff models or by flood frequency analysis. Estimating design floods peaks focused on large catchments, small (< 25 km2 ) – medium sized catchments (< 250–1 000 km2 ) rather than the most required one i.e., < 15 km2- intermediate sized (10 to 5 000 km2) (Pilgrim, 1987).

Design Approaches

Fig. 1: Methods for design flood estimation (Source- an assessment of predictive accuracy for two regional flood-frequency estimation methods, Mishra et al., 2010)

Mishra et al., (2010) proposed two methods of regional flood estimation as direct-regression and index-flood method. However, it was found that index-flood method is more accurate than regional flood method. A similar approach for flood design estimation was found, Beven (2000) used rainfall-runoff model, regionalisation method and samples to distinguish other statistical estimation.

Hosking and Wallis (1993) proposed the balanced use of both the index flood method and regional flood method using curves of L- moments.(Hosking, 1990). This combined method is still the most widespread method for regional flood estimation. The regionalisation and the at site variates are plotted on the growth curves separately with variation in index factor (a scale).

Campbell et al. (1986) suggested that engineers and hydrological designers encounters problem related to streamflow data of design floods at various sites. So, relevant techniques and methods are reviewed for regional flood estimation designs.

Campbell et al. (1986) conducted a survey indicating that:

• Rational Method was the widespread method.
• Peak discharge along with storm hydrograph are needed to be estimated.
• Catchments was enclosed to area <10 km2.
• Techniques and methods were found to be unfamiliar during the survey.

Another approach emphasized by SANRAL (1986) for flood estimation highlights rational, statistical and empirical methods to be the most appropriate ones. Therefore, to predict the variations such as relationship between physiology of catchments and regional flood or rational flood frequency there is a need to assess different approaches and methods to design the most suitable estimation method. (e.g. Blosch and Sivapalan, 1997; Pandey and Nguyen, 1999).

Methodology

Though, flood frequency analysis provides accurate flood estimation, rainfall related datas require a more complex variability method for at sites streamflow records. Recorded streamflow data provides a choice to select among flood frequency analysis and rainfall related methods. (Pilgrim and Cordery, 1993). Cordery and Pilgrim (2000) suggested three methods for designing flood estimation on the basis of recorded flood data as:

Empirical equations (envelope curves, flood frequency analysis)

Index flood method

Rational method

Empirical equations- Empirical equations are formulas that shows statistical correlation between physiology and climatic properties of catchments with their peak discharges. These equations are applied to regions with frequently observed floods. They provide the largest flood value without the use of frequency scale. The two equations used for estimation are:

Dickens Formula (1865) proposed that

Qp = CD A 3/4

where Qp = maximum flood discharge in m3 /s

A = catchment area in km2 and CD = Dickens constant (value range 6-30)

Ryves Formula- This formula is based on flood data of catchments

Qp = CR 2/3

where Q = maximum flood discharge in m3 /s

A = catchment area in km2 and CR = Ryves coefficient

Cordery and Pilgrim (2000) suggested to avoid these equations as they are hazardous if

not calibrated properly.

1.1 Flood frequency analysis

Regional flood estimation can be done using flood frequency analysis method based on flow records. Gumbel (1941) proposed a method to calculate flood frequency analysis. It is a risk analysis technique to estimate the flow of floods based on return periods. Statistical analysis is done to calculate mean and standard deviation based on peak flow data. This data is used to create frequency graphs to assess design flow values. Flood frequency analysis provides a pre estimation of floods and helps to design accurate hydraulic structures.

Fig. 1: Different flood estimation approaches (Source- Tamer A. Gado and Van-Thanh-Van Nguyen, 2016)

Tamer A. Gado and Van-Thanh-Van Nguyen (2016) classifies flood frequency analysis in regional and at – site. Flood frequency analysis is also known as probability of occurrence. Equated as:

P(Q) = 1/T where,T = return period and P(Q) = probability of occurrence (exceeds 0)

S No.

Peak flood (m3 /s)

Probability p= m/N+1

Return period T = 1/P years

1.

910

0.048

21.0

2.

670

0.238

4.2

3.

540

0.333

3.0

4.

510

0.381

2.6

5.

430

0.524

1.9

6.

400

0.619

1.6

7.

350

0.714

1.4

8.

330

0.762

1.3

9.

300

0.857

1.1

10.

100

0.952

1.0

Table 1: Weibull formula to calculate the Return Period T (1/P).

At site analysis- At site analysis involves analysis of peak flows data and designing an accurate distribution of observed data when streamflow records are long and less variant. (Schulze (1989). However, at site analysis have some limitations as proposed by Beven (2000):

Probability distribution of data results in different design estimation.

The frequency of rainfall have changed greatly since last calculated

The recorded data of at site floods is influenced by non calibration of runoff gauges.

Regional Analysis- Regional analysis estimates that different data in a particular region with a little variation that can be put together to draw a curve with site scaling frequencies – Homogenous regions (Cunnane, 1989; Gabriele and Arnell, 1991; Hosking and Wallis, 1997). Regionalisation helps to keep a record a annual floods by distributing data in short records in the form of at site data. These short datas are used to estimate frequencies of annual floods. (Bobee and Rasmussen, 1995). Practically, regional analysis approach is efficient than at site yielding accurate estimates.

Regional analysis approach as reviewed, proved to be advantageous for designing flood estimation. Many countries such as Australia and UK have already adopted this approach for flood estimation.

2. Index Flood Method

Dalrymple (1960) first proposed index flood method, which is the most widely used. Data from different homogenous regions is identical with little variation in index factor, a scaled parameter forms the basis of index flood method. To estimate index flood and derive frequency curves are the two main stages of Index flood method. These stages helps to calculate the MAF (mean annual flood). (Malekinezhad et al., 2011). MAF is the mean of maximum peak flows over a period of time. AREA and AAR and SL, the catchment parameters along with MAF helps to define multiple regression analysis through equation (Meigh, 1995; Meigh et al., 1997):

MAF= k1 x AREAk2 x AARk3 x SLk4

where MAF = estimated mean annual flood

AREA = catchment area

AAR = catchment annual average rainfall

SL = upstream catchment slope and

k1, k2, k3 and k4 = exponents estimated by solving a least-squares objective function.

Index flood based method consists of three major steps: homogenous regions, frequency distribution selection and index flood estimation. This method can be used for designing flood estimation of return periods expressed by:

Qt = qt μi

This equation is used to estimate flood variation = Qt where t is the return period and i = at site and μi = index flood product as a function of basin area.

3. Rational Method-

In rural and urban catchments both the rational method can be used widely to estimate peak flows. (Pilgrim and Cordery, 1993; Alexander, 2001). The Rational Method is a simplified method sensitive to intensity of rainfall and runoff coefficient. This method suggested that peak flows occurs during high intensity of rainfalls distributed evenly with little variation over the catchment. Selection of accurate runoff coefficient provides a successful application of this method.

Rational method application is based on intensity of rainfall and runoff coefficient over a period of time given by the formula:

Q = CuCi

where Q = design discharge in L3/T,

Cu = units conversion coefficient,

C = runoff coefficient which is a dimensionless ratio, and

i = rainfall intensity (L/T)

Runoff coefficient is the amount of rainfall converted to runoff. (Pegram and Parak, 2004). As compared to other methods rational method give better results.(SANRAL, 2007). Parak and Pegram (2006), suggested that a probabilistic approach will help to overcome limitations associated with rational methods as it converts a rainfall design into a flood design estimation consisting of the same return periods. Runoff coefficients of different return period is used to develop the rational method without showing considerable variation along with catchment parameters. (Pilgrim and Cordery, 1993).

Summary

From the review, it is concluded that their is a requirement of more updated methods and approaches that would lead to improved designing of flood estimation on the basis of annual records and data collected. Smithers and Schulze (2003) proposed recommendations to design better and improvised methods:

New approaches should be evaluated to improve flood design estimation. These approaches can then be used to overcome limitations associated with present methods. Many such approaches can be combined to estimate accurate peak flows. A statistical approach based on regional method should be used to identify homogeneous regions, plotting of growth curves for regions and development of algorithms for estimation. More improvised rational methods should be investigated.

Additionally, Gericke (2010) summarises different approaches to improve flood estimation such as combining recorded data and to estimate design floods on the basis of improved methods such as probability distribution.

Discussion

From the review, it is concluded that flood frequency analysis method based on recorded peak flows is adequate to design upgraded flood estimation. Comparing both the at site and regional approach methods, regional method is the most preferred and advantageous as discussed in the reviews above. The index flood method proposed by Dalrymple (1960) required further improvement and upgradation. When the recorded data is not enough for at site method, runoff method or rational method should be used for better design flood estimation of a region with evenly distributed flow.

A probabilistic approach i.e., rational method which will overcome the limitations of currently used methods and approaches should be used. Alexander (2002a; 2002b; 2002d). There is an urgent need to evaluate new methods for designing flood estimation to improvise and upgrade approaches. More research is required to improve estimation of floods.

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