Traditional flood-frequency techniques are based on the assumption that the observed flood record represents a sample that has been drawn from a single climatically homogeneous population of floods. A hydroclimatic approach was used to evaluate this assumption by identifying the circulation patterns and atmospheric flood-generating mechanisms which control the temporal and spatial variability of flooding. Mean monthly discharges and instantaneous peak flows of the partial duration series were analyzed for thirty gaging stations in the climatically sensitive, semiarid, Gila River basin for the period 1950 to 1980. Correlation fields and composite maps were constructed to define the relationship between 700 mb height circulation anomalies and mean monthly streamflow. Individual flood events were linked to climate by analyzing daily synoptic weather maps and classifying each flood event into one of eight hydroclimatic categories on the basis of the atmospheric mechanisms which generated each flow. The analysis demonstrated that floods and anomalously high streamflow in the Gila River basin originate from a variety of atmospheric processes which vary spatially, seasonally, and from year-to-year. The mechanisms most important for generating floods included winter fronts, cutoff lows, tropical storms, snowmelt, and widespread and localized summer monsoon-related circulation patterns. When flood discharges were grouped into hydroclimatically homogeneous categories, histogram plots of their frequency distributions exhibited means and variances that differed from those of the overall frequency distribution of the entire flood series. The means of the discharges generated by frontal precipitation and tropical storms tended to plot above the mean of the overall series, while the means of floods generated by snowmelt tended to plot below the overall mean. Flood estimates computed from a series containing mixed distributions were not the same as flood estimates computed from climatically homogeneous subsets of the same series. These results have implications for traditional flood-frequency analysis and other stochastic methods of analyzing hydrologic time series. The hydroclimatically-defined subgroups in the flood series of the Gila River basin indicate that nonhomogeneity and nonstationarity can be imparted to a hydrologic time series by differing atmospheric mechanisms alone.

}, keywords = {floods, Hydrology, mixed populations}, url = {http://ezproxy.library.arizona.edu/login?url=http://proquest.umi.com/pqdweb?did=753278081\&sid=23\&Fmt=2\&clientId=43922\&RQT=309\&VName=PQD}, author = {Hirschboeck, K.} } @mastersthesis {533, title = {Applications of Box-Jenkins Methods of the Time Series Analysis to the Reconstruction of Drought from Tree Rings}, volume = {PhD}, year = {1981}, school = {University of Arizona}, abstract = {The lagged responses of tree-ring indices to annual climatic or hydrologic series are examined in this study. The objectives are to develop methods to analyze the lagged responses of individual tree-ring indices, and to improve upon conventional methods of adjusting for the lag in response in regression models to reconstruct annual climatic or hydrologic series. The proposed methods are described and applied to test data from Oregon and Southern California. Transfer-function modeling is used to estimate the dependence of the current ring on past years{\textquoteright} climate and to select negative lags for reconstruction models. A linear system is assumed; the input is an annual climatic variable, and the output is a tree-ring index. The estimated impulse response function weights the importance of past and current years{\textquoteright} climate on the current year{\textquoteright}s ring. The identified transfer function model indicates how many past years{\textquoteright} rings are necessary to account for the effects of past years{\textquoteright} climate. Autoregressive-moving-average (ARMA) modeling is used to screen out climatically insensitive tree-ring indices, and to estimate the lag in response to climate unmasked from the effects of autocorrelation in the tree-ring and climatic series. The climatic and tree-ring series are each prewhitened by ARMA models, and crosscorrelation between the ARMA residuals are estimated. The absence of significant crosscorrelations implies low sensitivity. Significant crosscorrelations at lags other than zero indicate lag in response. This analysis can also aid in selecting positive lags for reconstruction models. An alternative reconstruction method that makes use of the ARMA residuals is also proposed. The basic concept is that random (uncorrelated in time) shocks of climate induce annual random shocks of tree growth, with autocorrelation in the tree-ring index resulting from inertia in the system. The steps in the method are (1) fit ARMA models to the tree-ring index and the climatic variable, (2) regress the ARMA residuals of the climatic variable on the ARMA residuals of the tree-ring index, (3) substitute the long-term prewhitened tree-ring index into the regression equation to reconstruct the prewhitened climatic variable, and (4) build autocorrelation back into the reconstruction with the ARMA model originally fit to the climatic variable. The trial applications on test data from Oregon and Southern California showed that the lagged response of tree rings to climate varies greatly from site to site. Sensitive tree-ring series commonly depend significantly only on one past year{\textquoteright}s climate (regional rainfall index). Other series depend on three or more past years{\textquoteright} climate. Comparison of reconstructions by conventional lagging of predictors with reconstructions of the random-shock method indicate that while the lagged models may reconstruct the amplitude of severe, long-lasting droughts better than the random-shock model, the random-shock model generally has a flatter frequency response. The random-shock model may therefore be more appropriate where the persistence structure is of prime interest. For the most sensitive series with small lag in response, the choice of reconstruction method makes little difference in properties of the reconstruction. The greatest divergence is for series whose impulse response weights from the transfer function analysis do not die off rapidly with time.}, keywords = {Hydrology}, url = {http://ezproxy.library.arizona.edu/login?url=http://proquest.umi.com/pqdweb?did=753124981\&sid=10\&Fmt=2\&clientId=43922\&RQT=309\&VName=PQD}, author = {Meko, David Michael} } @mastersthesis {569, title = {The Feasibility of Augmenting Hydrologic Records using Tree-Ring Data}, volume = {PhD}, year = {1971}, school = {University of Arizona}, abstract = {Two catchments of diverse hydrologic character were chosen in which to test the hypothesis that tree-ring indices contain information about runoff that is of pertinent interest to the hydrologist\…[Bright Angel Creek basin, Arizona and Upper San Francisco River basin, Arizona/New Mexico]

}, keywords = {Hydrology}, url = {http://ezproxy.library.arizona.edu/login?url=http://proquest.umi.com/pqdweb?did=760166291\&sid=14\&Fmt=1\&clientId=43922\&RQT=309\&VName=PQD}, author = {Stockton, C.} }