Assessment of Regional Analyses Methods for Spatial Interpolation of Flood Quantiles in the Basins of Bosnia and Herzegovina and Serbia

Mulaomerović-Šeta, Ajla; Blagojević, Borislava; Imširović, Šemsa; Nedić, Bojana

doi:10.1007/978-3-030-90055-7_35

Cited by 3 publications

(4 citation statements)

References 25 publications

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“…Due to input data issues (e.g., data gaps), the use of LP3 with the expected moments algorithm (EMA) should be reconsidered [11]. Overall better Q100 estimates were achieved in previous research [33] conducted using the Hydrologic Engineering Center's Statistical Software Package (HEC-SSP) where EMA is installed. In addition to the 53 HSs here, more HSs were included, and a study area comprising 74 HSs was delineated in the three regions.…”

Section: Discussionmentioning

confidence: 99%

“…In the study area for this research, i.e., Bosnia and Herzegovina, specific runoff diagrams or regression that relates flood quantiles and catchment area are most often used for flood quantile estimation in ungauged catchments [32]. It was shown that this approach can give significant under-/overestimation of flood quantiles and that geographically continuous regions of water basins are considered homogeneous regions without testing [33,34]. Other methods for flood data transfer used to improve flood quantile estimation included an extension of the gauged peak flow data based on gauged water stage, assumed rating curves [35], and historic floods [36].…”

Section: Introductionmentioning

confidence: 99%

“…A comparative presentation of statistical results, empirical expressions, and a geomorphological unit hydrograph using the EBA4SUB model is also considered [37]. Regional analysis using the cluster method was performed for stations from Bosnia and Herzegovina with the addition of stations from Serbia, where the advantage of hierarchical (Ward's algorithm) over partition (k-means) clustering was demonstrated in flood quantile estimation [33].…”

Section: Introductionmentioning

confidence: 99%

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A Silhouette-Width-Induced Hierarchical Clustering for Defining Flood Estimation Regions

et al. 2023

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Flood quantile estimation in ungauged basins is often performed using regional analysis. A regionalization procedure consists of two phases: the definition of homogeneous regions among gauged basins, i.e., clusters of stations, and information transfer to the ungauged sites. Due to its simplicity and widespread use, a combination of hierarchical clustering by Ward’s algorithm and the index-flood method is applied in this research. While hierarchical clustering is very efficient, its shortcomings are the lack of flexibility in the definition of clusters/regions and the inability to transfer objects/stations from one cluster center to another. To overcome this, using silhouette width for induced clustering of stations in flood studies is proposed in this paper. A regionalization procedure is conducted on 53 gauging stations under a continental climate in the West Balkans. In the induced clustering, a negative silhouette width is used as an indicator for the relocation of station(s) to another cluster. The estimates of mean annual flood and 100-year flood quantiles assessed by the original and induced clustering are compared. A jackknife procedure is applied for mean annual flood estimation and 100-year flood quantiles. Both the Hosking–Wallis and Anderson–Darling bootstrap tests provide better results regarding the homogeneity of the defined regions for the induced clustering compared to the original one. The goodness-of-fit measures indicate improved clustering results by the proposed intervention, reflecting flood quantile estimation at the stations with significant overestimation by the original clustering.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Silhouette-Width-Induced Hierarchical Clustering for Defining Flood Estimation Regions

et al. 2023

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“…Estimates of extreme rainfall are often derived from analyses of long-term rain gauge data. Due to the scarcity of rain gauges in many parts of the world, an interpolation approach is often used to provide a spatial map for the predicted frequency [26]. However, the sparse spatial density of rain gauges has a substantial impact on the dependability of estimations of extreme rainfall.…”

Section: Introductionmentioning

confidence: 99%

Spatial Frequency Analysis by Adopting Regional Analysis with Radar Rainfall in Taiwan

Chang¹,

Rahmad²,

Wu³

et al. 2022

Preprint

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This study proposed a spatially and temporally improving methodology adopting the Regional Frequency Analysis with L-moments approach to estimate rainfall quantiles from 22787 grids of radar rainfall in Taiwan for a 24-hour duration. Due to limited radar coverage in the eastern region, significant discordant grids were found in the coastal area of the eastern region. A K-means cluster analysis using scaled at-site characteristics was used to group the QPESUMS grids in Taiwan into 22 clusters/sub-regions based on their characteristics. Spatially, homogeneous subregions with QPESUMS data produce more detailed homogeneous subregions with clear and continuous boundaries, especially in the mountain range area where the number of rain stations is still very limited. According to the results of z-values and L-moment ratio diagrams, the Wakeby (WAK), Generalized Extreme Value (GEV), and Generalized Pareto (GPA) distributions of rainfall extremes fitted well for the majority of subregions. The Wakeby distribution was the dominant best-fitted distribution, especially in the central and eastern regions. The east of the northern part and southern part of Taiwan had the highest extreme rainfall for each return period. Both areas were frequently struck by typhoons. By using grid-based (at-site) as the basis for assessing regional frequency analysis, the results show that the regional approach in determining extreme rainfall is very suitable for large-scale applications and even better for smaller scales such as watershed areas. The spatial investigation was performed by establishing regions of interest in small subregions across the northern part. It showed that regionalization was correct and consistent.

show abstract

Spatial Frequency Analysis by Adopting Regional Analysis with Radar Rainfall in Taiwan

Chang

Rahmad

et al. 2022

Water

View full text Add to dashboard Cite

This study proposed a spatially and temporally improving methodology adopting the Regional Frequency Analysis with an L-moments approach to estimate rainfall quantiles from 22,787 grids of radar rainfall in Taiwan for a 24-hour duration. Due to limited radar coverage in the eastern region, significant discordant grids were found in the coastal area of the eastern region. A total of 171 grids with Di > 6 were set as discordant grids and removed for further analysis. A K-means cluster analysis using scaled at-site characteristics was used to group the QPESUMS grids in Taiwan into 22 clusters/sub-regions based on their characteristics. Spatially, homogeneous subregions with QPESUMS data produce more detailed homogeneous subregions with clear and continuous boundaries, especially in the mountain range area where the number of rain stations is still very limited. According to the results of z-values and L-moment ratio diagrams, the Wakeby (WAK), Generalized Extreme Value (GEV), and Generalized Pareto (GPA) distributions of rainfall extremes fitted well for the majority of subregions. The Wakeby distribution was the dominant best-fitted distribution, especially in the central and eastern regions. The east of the northern part and southern part of Taiwan had the highest extreme rainfall especially for a 100-year return period with an extreme value of more than 1200 mm/day. Both areas were frequently struck by typhoons. By using grid-based (at-site) as the basis for assessing regional frequency analysis, the results show that the regional approach in determining extreme rainfall is very suitable for large-scale applications and even better for smaller scales such as watershed areas. The spatial investigation was performed by establishing regions of interest in small subregions across the northern part. It showed that regionalization was correct and consistent.

show abstract

Assessment of Regional Analyses Methods for Spatial Interpolation of Flood Quantiles in the Basins of Bosnia and Herzegovina and Serbia

Cited by 3 publications

References 25 publications

A Silhouette-Width-Induced Hierarchical Clustering for Defining Flood Estimation Regions

A Silhouette-Width-Induced Hierarchical Clustering for Defining Flood Estimation Regions

Spatial Frequency Analysis by Adopting Regional Analysis with Radar Rainfall in Taiwan

Spatial Frequency Analysis by Adopting Regional Analysis with Radar Rainfall in Taiwan

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