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The two-parameter recursive digital filter method (Eckhardt) and the conductivity mass balance (CMB) method are two widely used baseflow separation methods favored by hydrologists. Some divergences in the application of these two methods have emerged in recent years. Some scholars believe that deviation of baseflow separation results of the two methods is due to uncertainty of the parameters of the Eckhardt method and that the Eckhardt method should be corrected by reference to the CMB method. However, other scholars attribute the deviation to the fact that they contain different transient water components. This study aimed to resolve this disagreement by analyzing the effectiveness of the CMB method for correcting the Eckhardt method through application of the methods to 26 basins in the United States by comparison of the biases between the generated daily baseflow series. The results showed that the approach of calibrating the Eckhardt method against the CMB method provides a "false" calibration of total baseflow by offsetting the inherent biases in the baseflow sequences generated by the two methods. The baseflow sequence generated by the Eckhardt method usually includes slow interflow and bank storage return flow, whereas that of the CMB method usually includes high-conductivity water flushed from swamps and depressions by rainfall, but not low-conductivity interflow and bank storage return flow. This difference results in obvious peak misalignment and periodic deviation between the baseflow sequences obtained by the two methods, thereby preventing calibration. However, multi-component separation of streamflow can be achieved through comparison. Future research should recognize the deviations between the separation results obtained by the different methods, identify the reasons for these differences, and explore the hydrological information contained therein. [ABSTRACT FROM AUTHOR]

Choosing a probability distribution to represent daily precipitation depths is important for precipitation frequency analysis, stochastic precipitation modeling and in climate trend assessments. Early studies identified the two-parameter gamma (G2) distribution as a suitable distribution for wet-day precipitation based on the traditional goodness-of-fit tests. Here, probability plot correlation coefficients and L-moment diagrams are used to examine distributional alternatives for the wet-day series of daily precipitation for hundreds of stations at the point and catchment scales in the United States. Importantly, both Pearson Type-III (P3) and kappa (KAP) distributions perform very well, particularly for point rainfall. Our analysis indicates that the KAP distribution best describes the distribution of wet-day precipitation at the point scale, whereas the performance of G2 and P3 distributions are comparable for wet-day precipitation at the catchment scale, with P3 generally providing the improved goodness of fit over G2. Since the G2 distribution is currently the most widely used probability density function, our findings could be considerably important, especially within the context of climate change investigations. [ABSTRACT FROM AUTHOR]

This study is an update of the information contained in the precipitation-frequency atlas published by the US National Weather Service in 1973. Data collection for the NWS study ended in 1966 while this study uses the current data base which more than doubles the record length used in the NWS study. Washington State has highly variable topography and climate; in particular Mean Annual Precipitation (MAP) varies from over 260 inches a year to less than 7 inches. Steep high mountain ranges provide very wet slopes as well as pronounced rain shadows with large climate changes occurring in relatively short distances. In addition there are four distinct sources for the atmospheric moisture needed for precipitation which gives rise to complex seasonal and spatial interactions. The PRISM mapping system used in this study has greatly improved the spatial mapping of precipitation and increased the reliability of estimates of precipitation in the broad areas between precipitation measurement stations. Further, the development and use of regional L-Moments has greatly improved the reliability of precipitation magnitude-frequency estimates, particularly for the rarer and more extreme storms. Washington State could be specified adequately by 12 regions for the purposes of estimating the 2-hour and 24 hour precipitation frequencies. Within each region algorithms were developed for LCV and L-Skewness expressed as functions of the MAP. The GEV distribution was acceptable statistically for all regions up to the 1 in 500 recurrence interval, beyond which the four-parameter Kappa distribution is recommended. The estimated changes in precipitation magnitudes for a given frequency as regional boundaries were crossed were found to be small, and well within the expected differences likely from sampling errors. An interesting transition zone was observed at the eastern edge of the Cascade foothills, associated with the maxima having a seasonal change from autumn-winter synoptic scale general storms in the west to spring-summer maxima in the east that were produced by a mix of storm types. (Comment: storms were a mix of general storms and more-isolated convective storms). [ABSTRACT FROM AUTHOR]

This study is an update of the information contained in the precipitation-frequency atlas published by the US National Weather Service in 1973. Data collection for the NWS study ended in 1966 while this study uses the current data base which more than doubles the record length used in the NWS study. Washington State has highly variable topography and climate; in particular Mean Annual Precipitation (MAP) varies from over 260 inches a year to less than 7 inches. Steep high mountain ranges provide very wet slopes as well as pronounced rain shadows with large climate changes occurring in relatively short distances. In addition there are four distinct sources for the atmospheric moisture needed for precipitation which gives rise to complex seasonal and spatial interactions. The PRISM mapping system used in this study has greatly improved the spatial mapping of precipitation and increased the reliability of estimates of precipitation in the broad areas between precipitation measurement stations. Further, the development and use of regional L-Moments has greatly improved the reliability of precipitation magnitude-frequency estimates, particularly for the rarer and more extreme storms. Washington State could be specified adequately by 12 regions for the purposes of estimating the 2-hour and 24 hour precipitation frequencies. Within each region algorithms were developed for L-CV and L-Skewness expressed as functions of the MAP. The GEV distribution was acceptable statistically for all regions up to the 1 in 500 recurrence interval, beyond which the four-parameter Kappa distribution is recommended. The estimated changes in precipitation magnitudes for a given frequency as regional boundaries were crossed were found to be small, and well within the expected differences likely from sampling errors. An interesting transition zone was observed at the eastern edge of the Cascade foothills, associated with the maxima having a seasonal change from autumn--winter synoptic scale general storms in the west to spring--summer maxima in the east that were produced by a mix of storm types. [ABSTRACT FROM AUTHOR]