Ray K. Linsley was formerly the Head of the Department of Civil Engineering at
The following paper was written during his tenure at Hydrocomp, Inc. Although it was written thirty years ago, in 1976, many of Linsley's points are equally valid today. While computers have become increasingly affordable, powerful, and fast, hydrologic simulation remains an underutilized tool for hydrologic analysis.
The question is often asked, why should we use simulation in hydrology? What is wrong with conventional techniques which have been in use for many years? Doesn't simulation require a lot more data? Doesn't it cost more and take more time? Is it really worthwhile to use computer simulation when we have so little data?
Simulation techniques in hydrology started about 1960 in research at
The general characteristics of a simulation model are based on concepts that were developed many years ago but could not be utilized because of computational limitations. The concept of infiltration which is the heart of continuous simulation was first proposed by Horton in 1933. The idea of continuous soil moisture accounting was suggested by Linsley and Ackermann in 1942. In 1934 Zoch first introduced the use of routing to construct the runoff hydrograph. The basic concepts of computer simulation were recognized as preferable approaches to hydrologic analysis long before the computational ability was available.
Prior to the development of simulation, a number of techniques were used in hydrology to arrive at estimates of flow when no observed values existed. All of these procedures utilize approximations because the work had to be done with pencil and paper, and it was not possible to deal in detail with the problem and expect a solution within a reasonable time. Classical methods resorted to simplification of procedures. For example, in the unit hydrograph technique for constructing a graph of streamflow, it was assumed that flow rate was in linear proportion to volume of runoff. This assumption conveniently permits superposition of runoff from several storm increments. This is not absolutely correct, however, and in watersheds where large flood plains exist the errors may be very large. The computer permits a much more detailed calculation using kinematic routing which relies on the actual stream cross-sections and the theory of flow in channels.
Similarly, in estimating the runoff from rainfall, relatively simple relationships were employed. The most complex of these used time of year, an antecedent precipitation index, and the duration of rain as parameters in a statistically derived relationship. By contrast, simulation allows for the continuous calculation of soil moisture, infiltration, and the movement of moisture in overland flow to the stream. A detailed computation represents the actual physical processes realistically, and consequently provides a more reliable basins for extrapolation in time or space.
The development of the computer has permitted the modern hydrologist to approach hydrologic problems without making many of the simplifying assumptions that are inherent in the classical solutions. For example, the calculation of runoff should be carried forward on a relatively short time interval. However, for pencil and paper computations it was customary to use time intervals no shorter than 6 hours and more frequently 12 or 24 hours. With modern computer simulation it is routine to compute on a one-hour interval which more accurately deals with infiltration and hydrograph characteristics for small watersheds.
In classical procedures it was customary to start with average rainfall over the watershed although it was recognized that when the actual rainfall varied widely above and below this average, the computation could not be correct. It is now possible to use computer simulation to calculate runoff independently over many segments of the watershed. Each segment represents an area of different rainfall, soil conditions, vegetative cover, or any one of many factors which might influence runoff. The degree to which the watershed is divided is limited only by the fact that each additional segment requires a complete repetition of the simulation and thus does increase computer time.
Simulation models of the continuous type permit the generation of streamflow for watersheds of any size for as long as is
required. Streamflow synthesis for a period of 500
years has been undertaken in connection with research at
One of the weaknesses of observed streamflow records lies in the fact that changing conditions in the watershed may have so altered streamflow that the records collected 25 or 30 years ago are no longer comparable to the records collected today. For planning and design it would be desirable to be able to use flows which might be expected in the future as a result of prospective changes in the land use or other factors which might change streamflow. Streamflow records cannot provide such information but simulation can. By calibrating a simulation model to the streamflow of the last three or five years, simulated streamflow for a period extending as far back as the available rainfall records can represent flows which would have occurred under current conditions. Flows for future conditions can be simulated by adjusting the parameters of the simulation model to assumed future conditions.
The comments above offer many reasons why simulation is to be preferred over conventional methods. What about the charge that it is more difficult and more costly? Simulation requires input of a considerably larger quantity of data than is normally used in most conventional hydrologic studies. However, in the conventional study an equal volume of data is usually reviewed, but because of difficulties of hand computation, only selected data items are actually used--usually much less than 10 percent of the available data. It is a relatively simple matter to get the required streamflow and rainfall data from responsible federal agencies.(2) The actual work of preparing the data for use may, in fact, be less than that of selecting from this same mass of data the cases to be studied by conventional means.
It is often implied that because one has limited data, one should use approximate methods. However, there is nothing about approximate methods that makes better use of the limited data and most such approximate methods have been demonstrated to be highly unreliable. There are many techniques which can be used to adapt the limited data to simulation. By careful use of a simulation program, data of poor quality can be checked, missing records completed, and a considerable extension of the record can be made. The most critical data for simulation are the rainfall data. Without rainfall data, it is impossible to carry out a simulation study. However, it is also impossible to carry on a study by any other reasonably adequate hydrologic technique without rainfall.
Simulation techniques cannot compete with the use of empirical formulae for computation of design flows on the basis of time and cost, but can easily compete with conventional methods such as rainfall-runoff relations and unit hydrographs. It will usually take no more time to develop the necessary data for simulation than it will require to develop the estimates desired. Meanwhile, one simulation run will provide an abundance of data which can answer many hydrologic problems. Although the data from the run may not be required in all its detail for a study of flood flows, it may subsequently have considerable value in dealing with streamflow volumes or minimum flows. If one wishes to explore the effect of changing vegetal cover on the watershed, of increasing the amount of urban land use, or other possible land use changes, this is easily done with simulation. Using conventional methods, is would be difficult, if not impossible, to estimate the effect of such changes.
In summary then it can be said that the answer to "Why simulate?" is given by the following points:
(1) Norman H. Crawford and Ray K. Linsley developed the earliest hydrologic simulation models at
(2) Hydrometeorologic data are now readily available on CD-ROM databases.