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least significant in explaining the relationship between independent watershed parameters and the resultant flood peak. By selecting a T-year flood for use in the regression analysis. the effect of the storm vari- ations was effectively suppressed. Dempster found that the most important watershed variable was the watershed area. A. followed by the imperviousness parameter, K, and lastly a length-slope parameter. L{I:S. The length-slope parameter was related to the watershed time of concentration by Kirpich (1940). The limits of the amount of basic data available did not statistically justify the inclusion of other inde- pendent watershed parameters. As in the case of the analysis by Johnson and Sayre, Dempster also found that the log transformed data worked best. It is interesting to note that Dempster's analysis found that the length-slope parameter was important in the regional equation: Qr aAbKC(L//S)d , where L is the length of the longest collector in miles. S is the slope of the longest stream in feet/ mile. All other variables have been previously defined. The results of Dempster's regional analysis are pre- sented in Table 2. All other variables have been previously defined. The results of Dempster's regional analysis are pre- sented in Table 2. where Q A L 5 K is discharge in cubic feet per second (cfs) is drainage area in square miles (sg mi) is length in miles (mi) is slope in feet per mile (ft/mi) is coefficient of imperviousness is 100 + .0151 is percent of impervious watershed The Dallas and the Houston metropolitan regions have some interesting contrasts. The main channels and drainageways in the Dallas region are more deeply incised into the watershed. As a result even after urbanization the Dallas channels tend to have better flood conveyance capacity. The soil cover in the Dallas region is thin and the soils are tight and therefore before urbanization. large parts of the storm rainfall quickly drain into the channel systems which were deep and on steeper gradients. In Dallas as the urbanization progresses, the residential areas Table 2 Regional Regression Equations for T-year Flood Dallas, Texas Region Standard error Estimate of Equation for indicated of estimate minimum T-year flood discharge (cfs) (percent) prediction error (percent) Ql. 25 195(A)0.88(L/IS)-0.13(K)1.02 11 30 Q2 369(A)0.90(L/IS)-0.19(K)0.65 11 30 \ Q5 621(A)0.93(L/IS)-0.23(K)0.42 10 29 Ql0 776(A)0.95(L/IS)-0.25(K)0.35 10 29 Q25 953(A)0.98(L/I>j-0.27(K)0.32 10 29 Q50 l,067(Ajl.00(L/IS)-0.28(KjO.32 10 29 Q100 l,172(Ajl.02(L/IS)-0.29(K)0.33 10 29 6