Multiple linear equations to predict selected parameters for the Kentucky watershed model (KWM) are presented. The independent variables consist of easily determinable watershed characteristics. The relationship provides a means by which the KWM can be used to predict streamflows from ungaged drainage basins. Examples are given for five test watersheds. Results are variable. INTRODUCTION include watershed data from other states in the southern re-Competition among users for a relatively fixed supply of gion. water has focused attention on the need for effective means to plan for the optimum use of this vital resource. Parametric models, which lend themselves to computer application and attempt to simulate the hydrologic cycle, have become recognized as useful aids to such planning. One of the better known and more comprehensive parametric models is the Stanford watershed model [Crawford and Linsley, 1966]. Because of its popularity it has undergone numerous modifications [e.g., James, 1965; Claborne and Moore, 1970; $hanholtz et al., 1972; Ligon et al., 1969]. However, each modification is basically a soil moisture accounting procedure in which mathematical expressions are used to define relationships between elements of the hydrologic cycle and the interactions between its components. Numerous parameters are utilized in this process, some of which are derived from historical records, some from climatological data, others from physical watershed characteristics, and still other nonmeasurable entities from estimation by trial-and-adjustment or optimization procedures. The effectiveness of these routines depends on the availability of a streamflow record of sufficient length to calibrate the model. Typically, several different combinations of parameters are utilized before an acceptable match can be found between predicted and recorded streamflows. The need of prior calibration makes it difficult to apply existing watershed models to ungaged watersheds. To circumvent this problem, attempts have been made to correlate model parameters to measurable physical watershed characteristics. James [1972], reporting on work by Ross [1970], discusses linear regression relationships that were developed to relate plant available water capacity (AWC), permeability of the A soil horizon, and overland flow surface slope to selected parameters in the Kentucky watershed model (KWM). Jarboe and Haan [1974] used a multiregression approach to estimate parameters for use in a monthly water yield model. Ambaruch and Simmons [1973] also reported some success with a multiregression approach, using data from several Tennessee Valley Authority watersheds. The study reported herein was undertaken to extend the work of Ross [1970] and Ambaruch and Simmons [1973] to

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Dr T e m p l e m a n and M r W a i t e r s The Paper covers theoretical aspects of the methods we have developed. Fig. 11 shows the layout of the optimum design of the computer program. At its core is the existing Highway Engineering Computer Branch's program DAPHNE which is used twice. Using BIPS road data and user-specified drainage data, DAPHNE is first used to prepare a conventional minimum cover design assuming manholes at each possible location. This provides design flows, pipe sizes and depths. These sizes and depths are used to define a new range of depth and diameter variables for optimization and an optimum design is then generated which has optimal manhole positions and pipe diameters. This optimum design is again input to DAPHNE which adjusts the pipe slopes keeping the optimal manhole positions and pipe diameters.37. As DAPHNE is a practical design program the optimizing program which relies heavily on DAPHNE also produces fully practical designs. Our program uses only those methods currently used in design offices for drainage design but uses them in an optimal way to produce cheaper designs than could be produced manually. Initial results seem to show that in terms of cost savings size/slope optimization saves a lot, manhole positions rather less and cross-drain positions very little. In its final version the optimizing program omits the variable cross-drain facility because the difficulties of integrating it with the DAPHNE program seemed to outweigh the potential advantages. Fig. 11 shows that the rational design basis could be easily replaced by alternative methods if necessary.The Authors' methods should provide engineers with powerful tools to produce economic and efficient designs. However, their use will depend on a number of factors including their reliability and robustness, the amount of data to be collected and prepared for the programs, and their success.39. Design methods have a tendency to perform well for those who develop them but less well for other users. I think designers should be encouraged to use the methods advocated. Therefore, before they are made generally available, the methods should be clearly and concisely documented, and objectively tested by

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