GENERALIZED LOW‐FLOW FREQUENCY RELATIONSHIPS FOR UNGAGED SITES IN MASSACHUSETTS¹

Abstract

Regional hydrologic procedures such as generalized least squares regression and streamflow record augmentation have been advocated for obtaining estimates of both flood‐flow and low‐flow statistics at ungaged sites. While such procedures are extremely useful in regional flood‐flow studies, no evaluation of their merit in regional low‐flow estimation has been made using actual streamflow data. This study develops generalized regional regression equations for estimating the d‐day, T‐year low‐flow discharge, Qd, t, at ungaged sites in Massachusetts where d = 3, 7, 14, and 30 days. A two‐parameter lognormal distribution is fit to sequences of annual minimum d‐day low‐flows and the estimated parameters of the lognormal distribution are then related to two drainage basin characteristics: drainage area and relief. The resulting models are general, simple to use, and about as precise as most previous models that only provide estimates of a single statistic such as Q7,10. Comparisons are provided of the impact of using ordinary least squares regression, generalized least squares regression, and streamflow record augmentation procedures to fit regional low‐flow frequency models in Massachusetts.

August median streamflows in Massachusetts

“…Although generalized-least-squares regression analysis (GLS) could correct for cross correlation, it was not used for this study because potential gains in model precision did not justify the added effort for the GLS analysis. Vogel and Kroll (1990) used GLS to develop a regression equation to predict 7-day 10-year low flows for Massachusetts streams, and found that the regression model parameter estimates were nearly identical, and the decrease in prediction errors was marginal compared to a model developed by use of ordinary-least-squares regression analysis, which does not correct for differences in record length or crosscorrelation. Cross correlation in Vogel and Kroll's model was 0.35.…”

“…WLS and GLS models with large standard errors and low cross correlations were nearly identical. Cross correlation was expected to be low and standard error was expected to be moderate for the equation to predict August median streamflows on the basis of results of Vogel and Kroll (1990) and Ries (1994a and1994b).…”

“…Several investigators have used regression analysis to obtain equations for estimating low-flow statistics for ungaged New England streams, although none have developed an equation for estimating August median streamflows (Thomas, 1966;Johnson, 1970;Tasker, 1972;Parker, 1977;Dingman, 1978;Cervione and others, 1982;Male and Ogawa, 1982;Fennessey and Vogel, 1990;Vogel and Kroll, 1990;Cervione and other, 1993;Risley, 1994;andRies, 1994a, 1994b). These investigators found drainage area the land area that contributes streamflow to the location on the stream to be the variable most highly correlated with low streamflow statistics.…”

Development of Regional Regression Model for Estimating Mean Low Flow in Ungauged Basins

“…(2)와 같다. Vogel and Kroll (1992)은 기존의 다중회귀방법 (Parker, 1977;Vogel and Kroll, 1990;Fennessey and Vogel, 1990)이 미계측 유역의 평균갈수량 추정에 한계가 있음을 지적하고, 그 대안으로 간단한 Dupuit-Boussinesq stream-aquifer 모형을 이용하여 Eq.…”

Baseflow characteristics in alpine rivers — a multi-catchment analysis in Northwest China

“…Baseflow index (BFI), calculated as the long-term ratio of baseflow to total streamflow (Institute of Hydrology 1980), is useful for analyzing baseflow characteristics (Abebe and Foerch 2006). Several studies have related baseflow to climatic and topographic factors, land cover and soil types, and hydrogeological properties, the impacts of which vary from catchment to catchment (Vogel and Kroll 1990;Ponce and Shetty 1995a, b;Nathan et al 1996;Lacey and Grayson 1998;Haberlandt et al 2001;Mwakalila et al 2002;Longobardi and Villani 2008).…”