The Influence of the Annual Number of Storms on the Derivation of the Flood Frequency Curve through Event-Based Simulation
Abstract
:1. Introduction
2. Materials and Methods
2.1. Stochastic Rainfall Series Generation and Storm Identification
2.2. Estimation of the Peak Flow Frequency Curves
2.3. Case Studies
2.4. Limitations of the Methodology
3. Results and Discussion
3.1. Rainfall Model Calibration/Validation and Rainfall Events Identification/Characterisation
3.2. FFCs Estimation and Effect of Considering Different Number of Storms Each Year
3.3. Joint Analysis of Maximum Annual Peak Flow and Hydrograph Volume
3.4. Sensitivity Analysis of Inter-Event Time Determination
4. Conclusions
- The degree of alignment between the calculated flood frequency curves and the reference flood frequency curve depends on the return period of the peak flow considered.
- Considering the criterion of the total rainfall depth to define when one storm is larger than another, a strong correlation was found between this criterion and the corresponding peak flow. Considering the three largest storms each year, the probability of achieving the maximum annual peak flow ranges between 83% and 92% depending on the analyzed basin.
- The flood frequency curve for high return period (50 ≤ return period ≤ 1000 years) generated by considering the three largest storms each year can be estimated with a difference lower than 3% regarding the reference flood frequency curve.
- By using the largest storm each year, for return periods higher than 10 years, the derived flood frequency curve determines which storms of order 1 show a difference lower than 10% regarding the reference flood frequency curve (considering all the identified storms).
- Basins with larger catchment areas would require more annual largest storms than in smaller basins in order to achieve the maximum peak flow each year.
- Considering the three largest storms each year, the probability of achieving simultaneously a hydrograph with the maximum annual peak flow and the maximum annual volume for a return period higher than 100 years is 94%, the return period being calculated from the maximum annual peak flows series. If we calculated the return period from the maximum annual hydrograph volume series, the probability would increase to 98%.
- The inter-storm time shows low influence on determining the minimum number of largest storms to be considered for achieving the maximum annually peak flow. Considering a wide range of inter-storm time (3 to 33 h) for the identification of storm events, the difference of the probability of including the maximum peak flow for a specific number of storms considered each year is lower than 3% in all cases.
Acknowledgments
Author Contributions
Conflicts of Interest
Abbreviations
CF | Cumulative frequency distribution |
CV | Coefficient of variation |
FFCi | Peak-flow frequency curve considering the i largest storms of each year |
FFCR | Reference peak-flow frequency curve considering a maximum of 25 largest storms of each year |
IDF | Intensity–Duration–Frequency curves |
MIT | Minimum inter-event time (hours) |
NS | Nash–Sutcliffe coefficient |
RF | Relative frequency distribution |
Rq | Ratio between the FFCs for different maximum storm orders and the reference FFCR |
Tr | Return period (years) |
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Name | Area (km2) | N° Sub-Basins | Sub-Basin Area (km2) | |
---|---|---|---|---|
Average | Range | |||
Santillana | 211 | 5 | 42 | 6.4/89 |
Pardo | 495 | 7 | 71 | 6.4/196 |
Manzanares | 1294 | 14 | 92 | 6.4/255 |
Probability (%) | Tr (Years) | Maximum Storm Order to Be Considered | ||
---|---|---|---|---|
Santillana | Pardo | Manzanares | ||
95/99 | 1 ≤ Tr < 10 | 5/11 | 4/9 | 6/10 |
95/99 | 10 ≤ Tr < 50 | 2/5 | 2/5 | 3/6 |
95/99 | 50 ≤ Tr ≤ 100 | 2/5 | 2/5 | 3/6 |
95/99 | 100 ≤ Tr ≤ 500 | 2/5 | 2/5 | 2/5 |
95/99 | 500 ≤ Tr ≤ 1000 | 1/2 | 2/3 | 2/5 |
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Sordo-Ward, A.; Bianucci, P.; Garrote, L.; Granados, A. The Influence of the Annual Number of Storms on the Derivation of the Flood Frequency Curve through Event-Based Simulation. Water 2016, 8, 335. https://doi.org/10.3390/w8080335
Sordo-Ward A, Bianucci P, Garrote L, Granados A. The Influence of the Annual Number of Storms on the Derivation of the Flood Frequency Curve through Event-Based Simulation. Water. 2016; 8(8):335. https://doi.org/10.3390/w8080335
Chicago/Turabian StyleSordo-Ward, Alvaro, Paola Bianucci, Luis Garrote, and Alfredo Granados. 2016. "The Influence of the Annual Number of Storms on the Derivation of the Flood Frequency Curve through Event-Based Simulation" Water 8, no. 8: 335. https://doi.org/10.3390/w8080335