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The Rational Formula is the most applied equation in practical hydrology due to its simplicity and the effective compromise between theory and data availability. Although the Rational Formula has several drawbacks, it is reliable and surprisingly accurate considering the paucity of input information. However, after more than a century, the recent progress in computational ability, theory and large-scale monitoring compel us to try to suggest a more advanced yet still empirical procedure for estimating peak discharge in small and ungauged basins. In this paper, an alternative empirical procedure is described and discussed, and then a discussion as to whether the Rational Formula is still necessary is presented. The presented methodology integrates the three standard steps of the common event-based approach (design hyetograph, rainfall excess and rainfall–runoff transformation) accurately adapted for application with a lack of observed data. The proposed procedure requires the same input information as necessary for application of the Rational Formula (soil properties, intensity–duration–frequency rainfall curves andTc) and provides both the peak discharge and the design hydrograph shape and, most importantly, reduces the subjectivity of the hydrologist in its application.Editor D. Koutsoyiannis [ABSTRACT FROM AUTHOR]

The present research study investigates the application of nonlinear normalizing data transformations in conjunction with ordinary kriging (OK) for the accurate prediction of groundwater level spatial variability in a sparsely-gauged basin. We investigate three established normalizing methods, Gaussian anamorphosis, trans-Gaussian kriging and the Box-Cox method to improve the estimation accuracy. The first two are applied for the first time to groundwater level data. All three methods improve the mean absolute prediction error compared to the application of OK to the non-transformed data. In addition, a modified Box-Cox transformation is proposed and applied to normalize the hydraulic heads. The modified Box-Cox transformation in conjunction with OK is found to be the optimal spatial model based on leave-one-out cross-validation. The recently established Spartan semivariogram family provides the optimal model fit to the transformed data. Finally, we present maps of the groundwater level and the kriging variance based on the optimal spatial model. Editor D. Koutsoyiannis; Associate editor A. Montanari Citation Varouchakis, E.A., Hristopoulos, D.T., and Karatzas, G.P., 2012. Improving kriging of groundwater level data using nonlinear normalizing transformations—a field application. Hydrological Sciences Journal, 57 (7), 1404–1419. [ABSTRACT FROM AUTHOR]

In this study, a parsimonious hydrological modelling algorithm is proposed based on the automated DEM-based geomorphic characterization of runoff dynamics in scarcely monitored river basins. The proposed approach implements the instantaneous unit hydrograph (IUH) concept, estimated using the width function (WF), for characterizing the travel time distribution using just one parameter, the river network flow velocity. Hillslope velocities are defined using spatially-distributed empirical formulas based on slope and soil-use information extrapolated from digital topographic data. Case studies are presented for testing model performance and comparing simulated and observed hydrographs of 25 selected flood events, as well as investigating the differences with the geomorphological instantaneous unit hydrograph (GIUH) model results. The calibration of the WFIUH channel flow velocity parameter using the concentration time is investigated providing interesting insights for the use of such a method for hydrological prediction in ungauged basins. Editor D. Koutsoyiannis Citation Grimaldi, S., Petroselli, A. and Nardi, F., 2012. A parsimonious geomorphological unit hydrograph for rainfall–runoff modelling in small ungauged basins. Hydrological Sciences Journal, 57 (1), 73–83. [ABSTRACT FROM AUTHOR]

This paper presents a calibration framework for a precipitation-runoff model for flood prediction in a mesoscale Alpine basin with discharges strongly influenced by hydraulic works. The developed methodology addresses two classical hydrological calibration challenges: computational limitations to run optimization algorithms for distributed hourly models and the absence of concomitant meteorological and natural discharge time series. The presented processes-oriented, multi-signal approach is based on hydrological data from a variety of sources and for different periods, corresponding to various spatial scales. The model parameters are calibrated by sequentially minimizing differences between observed and simulated values for different hydrological signals and signatures such as: (a) the phase of precipitations, (b) the time evolution of point-scale snow heights, (c) the mean inter-annual cycle of daily discharges, and (d) timing of snowmelt-induced spring runoff. We compare the model performance to a benchmark model obtained by simply using the globally optimal parameter values from the nearest gauged and non perturbed catchment. For prediction of flow seasonality and also extreme events, the calibration methodology outperforms the benchmark. Citation Hingray, B., Schaefli, B., Mezghani, A. & Hamdi, Y. (2010) Signature-based model calibration for hydrological prediction in mesoscale Alpine catchments. Hydrol. Sci. J. 55(6), 1002-1016. [ABSTRACT FROM AUTHOR]