Search

Goodness-of-fit measures are important for an objective evaluation of runoff model performance. The Kling-Gupta efficiency (RKG), which has been introduced as an improvement of the widely used Nash-Sutcliffe efficiency, considers different types of model errors, namely the error in the mean, the variability, and the dynamics. The calculation of RKG is implicitly based on the assumptions of data linearity, data normality, and the absence of outliers. In this study, we propose a modification of RKG as an efficiency measure comprising non-parametric components, i.e. the Spearman rank correlation and the normalized flow-duration curve. The performances of model simulations for 100 catchments using the new measure were compared to those obtained using RKG based on a number of statistical metrics and hydrological signatures. The new measure resulted overall in better or comparable model performances, and thus it was concluded that efficiency measures with non-parametric components provide a suitable alternative to commonly used measures. [ABSTRACT FROM AUTHOR]

Abstract: In scientific communication, ambiguities in term usage can go unnoticed due not only to the distance between reader and writer but also to the existence of highly specialized scientific subcommunities. This commentary therefore aims at raising awareness about the use of terms that have different meanings within different hydrological subcommunities such as field hydrology, hydrological modelling, or statistical hydrology. To do so, we discuss the use of the following commonly used hydrological terms: sample, runoff, discharge, and streamflow. We performed three types of analyses to provide evidence of term usage and understanding, including both qualitative and quantitative approaches: a drawing exercise, a survey, and a literature corpus analysis. These analyses allow for a comparison of spontaneous definitions and the actual use of these terms in scientific publications. Our various information sources revealed that the dialogue between hydrologists within and across subdisciplines is substantially influenced by personal conceptualizations of terms that are not always shared across conversational partners. The terms discussed and illustrated in this commentary have to be seen as a small sample used to demonstrate the need for a thoughtful use of hydrological terms when communicating research, not only to a general audience but even across subdisciplines within hydrology. [ABSTRACT FROM AUTHOR]

Ecologically relevant streamflow characteristics (SFCs) of ungauged catchments are often estimated from simulated runoff of hydrologic models that were originally calibrated on gauged catchments. However, SFC estimates of the gauged donor catchments and subsequently the ungauged catchments can be substantially uncertain when models are calibrated using traditional approaches based on optimization of statistical performance metrics (e.g., Nash- Sutcliffe model efficiency). An improved calibration strategy for gauged catchments is therefore crucial to help reduce the uncertainties of estimated SFCs for ungauged catchments. The aim of this study was to improve SFC estimates from modeled runoff time series in gauged catchments by explicitly including one or several SFCs in the calibration process. Different types of objective functions were defined consisting of the Nash-Sutcliffe model efficiency, single SFCs, or combinations thereof. We calibrated a bucket-type runoff model (HBV - Hydrologiska Byråns Vattenavdelning - model) for 25 catchments in the Tennessee River basin and evaluated the proposed calibration approach on 13 ecologically relevant SFCs representing major flow regime components and different flow conditions. While the model generally tended to underestimate the tested SFCs related to mean and high-flow conditions, SFCs related to low flow were generally overestimated. The highest estimation accuracies were achieved by a SFC-specific model calibration. Estimates of SFCs not included in the calibration process were of similar quality when comparing a multi-SFC calibration approach to a traditional model efficiency calibration. For practical applications, this implies that SFCs should preferably be estimated from targeted runoff model calibration, and modeled estimates need to be carefully interpreted. [ABSTRACT FROM AUTHOR]