Flood frequency analysis of southern Africa: I. Delineation of homogeneous regions

Kachroo, R.K.; Mkhandi, S.; Parida, B.P.

doi:10.1080/02626660009492340

Cited by 27 publications

(23 citation statements)

References 11 publications

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“…One of the prevalent approaches for delineating homogeneous regions is based on clustering techniques (Clarke, 2011;Guse et al, 2010;Everitt, 2001;Zrinji and Burn, 1996;Aldenderfer and Blashfield, 1984;Roger, 1980) and have been applied in many flood frequency analysis studies (e.g., Clarke, 2011;Ramachandra Rao and Srinivas, 2005;Kachroo et al, 2000;Kim and Hawkins, 1993;Acreman and Sinclair, 1986). However, application of the different clustering techniques to the same dataset, normally leads to different results (Lubomír, 2005).…”

Section: Clusteringmentioning

confidence: 99%

“…Omission of landuse and soil types in the clustering was established to be insignificant for this study. Each characteristic was standardised by its corresponding mean value before use for clustering to give each characteristic equal weight in the clustering (Kachroo et al, 2000). A two case approach was adopted in the clustering.…”

Section: Cluster Analysismentioning

confidence: 99%

“…Regional flood frequency analysis using physical catchment characteristics have been shown to produce reliable results if the physical catchment characteristics, chosen objectively, influence the spatial variability of hydrological characteristics (Kjeldsen et al, 2001;Kachroo et al, 2000;Parida et al, 1998;Zrinji and Burn, 1996;Kim and Hawkins, 1993;LeBoutillier and Waylen, 1993;Cunnane, 1988;Wiltshire, 1986;Acreman and Sinclair, 1986;Mosley, 1981). One of the key steps in such analysis is the delineation of the study area into homogeneous regions.…”

Section: Introductionmentioning

confidence: 99%

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An elusive search for regional flood frequency estimates in the River Nile basin

Nyeko-Ogiramoi

Willems

Mutua

et al. 2012

Hydrol. Earth Syst. Sci.

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Abstract. Estimation of peak flow quantiles in ungauged catchments is a challenge often faced by water professionals in many parts of the world. Approaches to address such problem exist, but widely used techniques such as flood frequency regionalisation is often not subjected to performance evaluation. In this study, the jack-knifing principle is used to assess the performance of the flood frequency regionalisation in the complex and data-scarce River Nile basin by examining the error (regionalisation error) between locally and regionally estimated peak flow quantiles for different return periods (Q T ). Agglomerative hierarchical clustering based algorithms were used to search for regions with similar hydrological characteristics. Hydrological data employed were from 180 gauged catchments and several physical characteristics in order to regionalise 365 identified catchments. The Generalised Extreme Value (GEV) distribution, selected using L-moment based approach, was used to construct regional growth curves from which peak flow growth factors could be derived and mapped through interpolation. Inside each region, variations in at-site flood frequency distribution were modelled by regression of the mean annual maximum peak flow (MAF) versus catchment area. The results showed that the performance of the regionalisation is heavily dependent on the historical flow record length and the similarity of the hydrological characteristics inside the regions. The flood frequency regionalisation of the River Nile basin can be improved if sufficient flow data of longer record length of at least 40 yr become available.

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Section: Clusteringmentioning

confidence: 99%

Section: Cluster Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An elusive search for regional flood frequency estimates in the River Nile basin

Nyeko-Ogiramoi

Willems

Mutua

et al. 2012

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

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“…Kachroo et al (2000) reviewed recent literature and concluded that no objective methods of regionalisation are universally accepted. A significant development in the identification of homogeneous regions is the region of influence approach developed by and Zrinji and Burn (1994) and which has been adopted by the FEH (Reed, 1999).…”

Section: Regional Analysismentioning

confidence: 99%

Methods for design flood estimation in South Africa

Smithers¹

2012

WSA

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The estimation of design floods is necessary for the design of hydraulic structures and to quantify the risk of failure of the structures. Most of the methods used for design flood estimation in South Africa were developed in the late 1960s and early 1970s and are in need of updating with more than 40 years of additional data currently available and with new approaches used internationally. This paper reviews methods used for design flood estimation in South Africa and internationally and highlights research needs in order to update the methods used for design flood estimation in South Africa.

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“…that were directly obtained from the daily streamflow data to group catchments in southwest Nigeria into five hydrologic regions. Kachroo et al (2000) used the combined data of annual maximum flood and physiographic attribute information from 77 gauged catchments in Tanzania to partition the country into 12 homogeneous regions.…”

Section: Introductionmentioning

confidence: 99%

Hydrologic similarity among catchments under variable flow conditions

Patil

Stieglitz

2011

Hydrol. Earth Syst. Sci.

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Abstract. An assessment of regional similarity in catchment stream response is often needed for accurate predictions in ungauged catchments. However, it is not clear whether similarity among catchments is preserved at all flow conditions. We address this question through the analysis of flow duration curves for 25 gauged catchments located across four river basins in the northeast United States. The coefficient of variation of streamflow percentiles is used as a measure of variability among catchments across flow conditions. Results show that similarity in catchment stream response is dynamic and highly dependent on flow conditions. Specifically, within each of the four basins, the coefficient of variation is high at low flow percentiles and gradually reduces for higher flow percentiles. Analysis of the inter-annual variation in streamflow percentiles shows a similar reduction in variability from low flow to high flow percentiles. Greater similarity in streamflows is observed during the winter and spring (wet) seasons compared to the summer and fall (dry) seasons. Results suggest that the spatial variability in streamflow at low flows is primarily controlled by the dominance of high evaporative demand during the warm period. On the other hand, spatial variability at high flows during the cold period is controlled by the increased dominance of precipitation input over evapotranspiration. By evaluating variability over the entire range of streamflow percentiles, this work explores the nature of hydrologic similarity from a seasonal perspective.

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Flood frequency analysis of southern Africa: I. Delineation of homogeneous regions

Cited by 27 publications

References 11 publications

An elusive search for regional flood frequency estimates in the River Nile basin

An elusive search for regional flood frequency estimates in the River Nile basin

Methods for design flood estimation in South Africa

Hydrologic similarity among catchments under variable flow conditions

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