A practical approach is developed for frequency analysis of multiyear drought durations of annual streamflow series. The proposed approach utilizes a technique which smooths the frequency‐curve irregularity of drought durations and, therefore, reduces the statistical uncertainties associated with sample‐size limitations. Several hazard‐function models are examined with regard to their ability to represent the duration‐dependent termination rate of a drought data set. The logistic model with an exponential correction for short durations is considered to have sufficient flexibility for describing most portions of the termination‐rate function. The parameters of the logistic model are identified using a piecewise linear regression for the linearized termination probability curve. Once the form of the hazard model is specified arid its parameters are estimated, the probability distribution and exceedance probability of drought durations can be determined from their corresponding relationships with the hazard model. The historic droughts of Feather River, California, are used to demonstrate the methodology. Results indicate that the observed nine‐year drought of Feather River has a return period of 360 years.

This paper is concerned with regional frequency analysis of hydrologic multiyear droughts. A drought event is defined by three parameters: severity, duration, and magnitude. A method is proposed here to standardize drought severities with a duration adjustment to enable comparison among drought events. For purposes of a regional study, the index drought method is selected and applied to standardized droughts to give a regional frequency curve. However, the recurrence intervals of the drought events obtained from index drought method are limited to the historic period of record. Therefore, by taking advantage of random variations of droughts in both time and space, a multivariate simulation model is used to estimate exceedence probabilities associated with regional drought maxima. This method, named the regional extreme drought method, is capable of generating a series of drought events which, although they have not occurred historically, are more severe than historic events. By combining the results of the index drought method and regional extreme drought analysis, a regional drought probability graph is constructed which ranges from severe droughts to more frequent droughts. This procedure is applied to the mean annual flow records of streams located in the San Joaquin Valley of California, and drought‐severity‐frequency plots are prepared for 1‐year, 2‐year, and 3‐year durations.

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This paper concerns the methods of estimating aquifer transmissivities on the basis of unsteady state hydraulic head data. Traditionally, the criterion of minimizing the sum of the squares of errors has been used to match the observed data with the model response. The data used for optimization usually contain noise that is not necessarily uncorrelated. It is well understood that the results of identification methods are very sensitive to measurement errors in data. In this study, the ordinary least squares (OLS) technique is carried out along with a generalized least squares (GLS) technique specifically designed to reduce the effect of correlated errors. The trace of the covariance matrix is used as a measure of overall accuracy and reliability of the estimated parameters. The effectiveness of the OLS and GLS techniques in dealing with noisy data is demonstrated by using a hypothetical example. The results of numerical experiments suggest that GLS offers a promising approach in efficiently improving the reliability of the estimated parameters.

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