FEATURE ARTICLE

# Real-time Flood Forecasting

We’ve learned to predict typhoons. What is required to predict the floods they bring?

# Modeling a Tide-affected River Basin

There are two approaches to mathematical modeling of complex phenomena. A deterministic model manipulates variables in ways that are numerically explicit—specific parameter values are operated on to produce a discrete result. An example of deterministic modeling would be applying Newton’s laws to determine the precise location of a planet, say Jupiter, at a future point in time. An alternative, stochastic modeling, employs sampling and probabilities to produce answers. Large-scale weather modeling, for example, proceeds by such strategies, averaging the results of several probability models to produce a stochastically derived outcome with an acceptable balance of accuracy versus uncertainty.

The simulation model we developed for the Tamsui River basin was deterministic. The deterministic approach generally entails rather sophisticated and elaborate mathematics, while offering the advantage of rapid calculation, which is required for a real-time forecasting system, and rather precise results, which could prove to be quite important when the time came to sound a warning. An additional advantage is the limited amount of input data required to run the simulation.

The Tamsui River is the third largest river in Taiwan, with its longest limb stretching 159 kilometers. In terms of numerical modeling, the river system presents great complexity. It has large and small tributaries, it branches and rejoins, and the junctions have diverse shapes, angles, and rapidly changing flow patterns and rates.

The Tamsui River collects water from three main tributaries: Tahhan Stream, Hsintian Stream and the Keelung River. It meanders through the Taipei Basin and enters the Taiwan Strait at He-Kou (River Mouth). The upstream regions of the tributaries are marked by steep channels and rapid flows. In the estuary and near coastal areas, however, the Tamsui River is flat and strongly affected by the tides, including daily reversals in the direction of flow. The actual flow of water at the point where the three branches meet can be any imaginable combination of forward and reverse flow.

In the study of river dynamics, flows that exhibit changes over time in stage (water surface elevation), depth, discharge, velocity and so on are known as unsteady flows. There are three basic types of unsteady flows in river channels: tidal, flood and rapidly varied (either naturally occurring or human-induced). All three types can occur at the same time and place in the Tamsui River basin. A useful flood forecast model must be able to incorporate all of this geometrical complexity and intricate flow dynamics in a real-time simulation.

Achieving an accurate simulation begins with a careful study of the geometry of the waterway. The Taipei basin is a compound complex channel (CCC) system that includes dendritic and network channels. To build a simulation model, this natural CCC system must be schematized into a geometrically simplified channel system that can be interpreted by a computer. Figure 4 illustrates how we schematized a section of the Tamsui network by designating junctions and the reaches between them. Junctions may be one-, two-, three- or four-way. A one-way junction is a boundary point—for example, the terminus of a reach at the edge of the simulation region. The other junctions are internal boundary points, for example, the point where two reaches meet in a contiguous line (two-way junction) or where three or more reaches meet at an intersection* (inset, Figure 4)*. For each of the junctions and reaches, an appropriate method must be devised for evaluating mathematically the state of flow in the region. These solutions will ultimately be combined in a simulation of the entire system.

Our schematized framework has two roles. First, it represents the conversion of a general flow model into a site-specific model—in this case, an unsteady flow model of the Tamsui River basin. Second, it identifies a significant portion of the initial input data.

At this point, a review of the principles of predicting unsteady flow is in order. In general terms, unsteady flow in open channels can be described by a specialized set of partial differential equations (PDEs) designed to model fluid motion. In our model, the basic unsteady-flow PDEs are transformed using a technique called the *method of characteristics,* in which physical quantities are modeled as characteristics, mathematical entities that can be thought of as waves with direction components and the ability to interact. We take this technique further with a recent development called the multimode method of characteristics of the second kind (MMOC-II), designed to facilitate complex flow simulation on the computer. (Readers interested in the more mathematical and mechanistic aspects of this model should see Lai 1986, 1988, 1994 and 1999.) The mathematics in our model has several special features, including the ability to accommodate characteristic waves of greatly different speeds, from very fast to extremely slow, and to keep all characteristic curves in the numerically explicit mode. The ability to compute entirely in the explicit mode allows us to rapidly evaluate unknowns at grid points in our model, one grid point at a time. The alternative, a matrix solution, would need to be very large and would be potentially very troublesome.

A hint of the challenge is given by the types of variables that must be evaluated, including, but by no means limited to, the cross-sectional area of flow, the width at the top of the flow channel, the depth of the flow, its velocity, and so on. This model assumes a fixed bed, removing the need to consider sedimentation and bed deformation. Even simplified however, the analysis of unsteady, open-channel flow remains a difficult challenge for hydraulic engineers.

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