The WSR-57 weather radar operated by the National Weather Service at Sacramento, California, plus a network of precipitation gages provided data for this comparison of radar reflectivity with precipitation rates. Located in a valley with mountains within range of the radar on three sides, this radar has varying sensitivity for precipitation rates as a result of the terrain effects. Variation in the terrain surrounding the radar has led to a very wide scatter in precipitation rates associated with any particular radar reflectivity. The radar failed to detect precipitation up to 77% of the time over the Coast Range at ranges greater than 100 nm. Linear regression analyses revealed very poor correlation between the raingage indicated precipitation rate and the radar reflectivity. These analyses resulted in values of (R²), the coefficient of determination, ranging from zero as a minimum to only 0.502 as a maximum. Such results are generally much poorer than results obtained by others. The poor correlations and both overestimation and underestimation of rainfall resulted from factors such as range, terrain blocking, windward or leeward exposure, freezing level height, beam height and width, and the distribution of water vapor in the vertical. / Graduation date: 1976

The effect of altitude on individual storm precipitation in some of the San Dimas experimental watersheds is investigated. It is found that there is a well- defined increase of storm precipitation with altitude for storms greater than one inch. This increase is a linear function of storm depth. Using 41 storms of different magnitudes, a precipitation -altitude relationship is derived for a small area in the San Dimas Experimental Forest. The regionalization of this relationship and its transferability are tested by analyzing differences (errors) between computed and observed storm precipitation values in each case. In testing the regionalization of the precipitation- altitude relationship by computing mean areal storm precipitation over a larger area the standard error of estimate is around 11 percent. In transfering the same relationship the results are not as good and give a standard error of 16 percent. For individual points, however, the error is much higher. A rainfall- runoff model is used as a tool for evaluating the effect of precipitation errors, on simulated streamflow, in a watershed of 4.5 square miles. For annual flows, errors range between 3.4 and 12.3 percent while errors in simulated monthly flows are as high as 22 percent. It is also evident that there is a strong dependence of the error magnitude on the state (wet, dry, etc.) of the preceding year or months, whichever is applicable. An error propagation is observed as a result of consistently over -estimating the precipitation input to the model. This evaluation is more of a qualitative nature and the values of error given should be viewed in this sense.