Increasing concentrations of carbon dioxide and other gases are expected to warm the earth several degrees in the next century, which would raise sea level a few feet and alter precipitation patterns. Both of these changes would have major impacts on the operation of coastal drainage systems. However, because sea level rise and climate change resulting from the greenhouse effect are still uncertain, most planners and engineers are ignoring the potential implications. Case studies of the potential impact on watersheds in Charleston, South Carolina, and Fort Walton Beach, Florida, suggest that the cost of designing a new system to accommodate a rise in sea level will sometimes be small compared with the retrofit cost that may ultimately be necessary if new systems are not designed for a rise. Rather than ignore the greenhouse effect until its consequences are firmly established, engineers and planners should evaluate whether it would be worthwhile to insure that new systems are not vulnerable to the risks of climate change and sea level rise.

A procedure for estimating the joint probability of occurrence of correlated extreme tides and corresponding freshwater flows in estuaries is presented. The method uses the Box-Cox transformation to transform the original data to near normality, and therefore the search for a parent distribution is avoided. It is also shown that the traditional assumption of statistical independence for the jointly distributed random variables may lead to the underestimation of flows and tidal heights. The methodology is applied to the Rappahannock River in Virginia which flows into the Chesapeake Bay.

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The transformations (i) SMEMAX (ii) Modified SMEMAX (iii) Power and Probability Distributions (iv) Weibull (a,P,y) or Extreme value type 111 (v) Weibull (a,P,O) (vi) Log Pearson Type 111 (vii) Log Boughton are considered for the low flow analysis. Also, different parameter estimating procedures are considered. Both the Weibull and log Pearson can have positive lower bounds and thus their use in fitting low flow probabilities may not be physically justifiable. A new derivation generalizing the SMEMAX transformation is proposed. A new estimator for the log Boughton distribution is presented. It is found that the Boughton distribution with Cunnane's plotting position provides a good fit to low flows for Virginia streams. Downloaded from https://iwaponline.com/hr/article-pdf/16/2/105/2359/105.pdf by guestPower Transformation -This transformation was first proposed by Box andCox (1964), andChander et al. (1978) used this transformation for flood frequency analysis. In a paper by Kumar and Devi (1982), the power transformation was applied to the frequency analysis of low flows for one station. The power transformation is formwhere: z is normally distributed with mean M, and standard deviation S,; y is the original sample value; h is a parameter of transformation. Also, y can be replaced by (y+ k) for y >k. Downloaded from https://iwaponline.com/hr/article-pdf/16/2/105/2359/105.pdf by guest + Z,) 12 Z1 largest (chosen arbitrarily). Considering Fig. 1 for f o r It is noted that Z1 = 22, for Z, = 0. For this special case the transformation given by Eqs. (4) and (5) becomes for X < X < X m S --Downloaded from https

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