Regional flow duration curves: Geostatistical techniques versus multivariate regression. (October 2016)

• Record Type: Journal Article
• Authors: Pugliese, Alessio; Farmer, William H; Castellarin, Attilio; Archfield, Stacey A.; Vogel, Richard M.
• Is Part Of: Advances in water resources. Volume 96(2016)
• Page Start: 11
• Page End: 22
• Publication Date: 2016-10
• Subjects: Flow-duration curve -- Top-kriging -- Linear regression -- Prediction in ungauged basins (pub problem) -- Regional analysis -- Geostatistics -- Southeastern United States; Hydrology -- Periodicals; Hydrodynamics -- Periodicals; Hydraulic engineering -- Periodicals; 551.48
• DOI: 10.1016/j.advwatres.2016.06.008
• Languages: English
• ISSNs: 0309-1708

Abstract

Highlights: We compare two methods for predicting flow-duration curves in ungauged basins. A novel geostatistical technique is compared with a multivariate linear regression. We adopt a three-fold cross-validation procedure to simulate ungauged conditions. The two methods perform similarly from high-flows to low-flows regimes. Complementarities are highlighted in the tails of the duration curves. Abstract: A period-of-record flow duration curve (FDC) represents the relationship between the magnitude and frequency of daily streamflows. Prediction of FDCs is of great importance for locations characterized by sparse or missing streamflow observations. We present a detailed comparison of two methods which are capable of predicting an FDC at ungauged basins: (1) an adaptation of the geostatistical method, Top-kriging, employing a linear weighted average of dimensionless empirical FDCs, standardised with a reference streamflow value; and (2) regional multiple linear regression of streamflow quantiles, perhaps the most common method for the prediction of FDCs at ungauged sites. In particular, Top-kriging relies on a metric for expressing the similarity between catchments computed as the negative deviation of the FDC from a reference streamflow value, which we termed total negative deviation (TND). Comparisons of these two methods are made in 182 largely unregulated river catchments in the southeastern U.S. using a three-fold cross-validation algorithm. Our results reveal that the two methods perform similarly throughout flow-regimes, with average Nash-Sutcliffe Efficiencies 0.566 and 0.662, (0.883 and 0.829 on log-transformed quantiles) for the geostatistical and the linear regression models, respectively. The differences between the reproduction of FDC's occurred mostly for low flows with exceedance probability (i.e. duration) above 0.98.