A dynamic-stochastic model for ¯ood forecasting based on the Kalman ®ltering theory is described. To reduce the computational time that the Kalman ®lter involves, this model is performed using the reduced rank square root algorithm, which approximates the covariance matrix by a matrix of lower rank.
A fast method of flood discharge estimation
✍ Scribed by Yen-Chang Chen; Chao-Lin Chiu
- Publisher
- John Wiley and Sons
- Year
- 2004
- Tongue
- English
- Weight
- 250 KB
- Volume
- 18
- Category
- Article
- ISSN
- 0885-6087
- DOI
- 10.1002/hyp.1476
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✦ Synopsis
Abstract
Discharge, especially during flood periods, is among the most important information necessary for flood control, water resources planning and management. Owing to the high flood velocities, flood discharge usually cannot be measured efficiently by conventional methods, which explains why records of flood discharge are scarce or do not exist for the watersheds in Taiwan. A fast method of flood discharge estimation is presented. The greatest advantage of the proposed method is its application to estimate flood discharge that cannot be measured by conventional methods. It has as its basis the regularity of open‐channel flows, i.e. that nature maintains a constant ratio of mean to maximum velocities at a given channel section by adjusting the velocity distribution and the channel geometry. The maximum velocity at a given section can be determined easily over a single vertical profile, which tends to remain invariant with time and discharge, and can be converted to the mean velocity of the entire cross‐section by multying by the constant ratio. Therefore the mean velocity is a common multiple of maximum velocity and the mean/maximum velocity ratio. The channel cross‐sectional area can be determined from the gauge height, the water depth at the y‐axis or the product of the channel width multiplied by the water depth at the y‐axis. Then the most commonly used method, i.e. the velocity–area method, which determines discharge as the product of the cross‐sectional area multiplied by mean velocity, is applied to estimate the flood discharge. Only a few velocity measurements on the y‐axis are necessary to estimate flood discharge. Moreover the location of the y‐axis will not vary with time and water stage. Once the relationship of mean and maximum velocities is established, the flood estimation can be determined efficiently. This method avoids exposure to hazardous environments and sharply reduces the measurement time and cost. The method can be applied in both high and low flows in rivers. Available laboratory flume and stream‐flow data are used to illustrate accuracy and reliability, and results show that this method can quickly and accurately estimate flood discharges. Copyright © 2004 John Wiley & Sons, Ltd.
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