River flow forecasting through conceptual models part I — A discussion of principles☆
TL;DR: In this article, the principles governing the application of the conceptual model technique to river flow forecasting are discussed and the necessity for a systematic approach to the development and testing of the model is explained and some preliminary ideas suggested.
About: This article is published in Journal of Hydrology.The article was published on 1970-04-01. It has received 19601 citations till now. The article focuses on the topics: Conceptual model & Flood forecasting.
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Max Planck Society1, Laval University2, Harvard University3, McMaster University4, Karlsruhe Institute of Technology5, Lund University6, Dresden University of Technology7, Institut national de la recherche agronomique8, University of Toledo9, University College Cork10, Oregon State University11, ETH Zurich12, United States Forest Service13, Free University of Bozen-Bolzano14, Wageningen University and Research Centre15, National Research Council16, Clark University17
TL;DR: In this paper, the authors upscaled FLUXNET observations of carbon dioxide, water, and energy fluxes to the global scale using the machine learning technique, model tree ensembles (MTE), to predict site-level gross primary productivity (GPP), terrestrial ecosystem respiration (TER), net ecosystem exchange (NEE), latent energy (LE), and sensible heat (H) based on remote sensing indices, climate and meteorological data, and information on land use.
Abstract: We upscaled FLUXNET observations of carbon dioxide, water, and energy fluxes to the global scale using the machine learning technique, model tree ensembles (MTE). We trained MTE to predict site-level gross primary productivity (GPP), terrestrial ecosystem respiration (TER), net ecosystem exchange (NEE), latent energy (LE), and sensible heat (H) based on remote sensing indices, climate and meteorological data, and information on land use. We applied the trained MTEs to generate global flux fields at a 0.5 degrees x 0.5 degrees spatial resolution and a monthly temporal resolution from 1982 to 2008. Cross-validation analyses revealed good performance of MTE in predicting among-site flux variability with modeling efficiencies (MEf) between 0.64 and 0.84, except for NEE (MEf = 0.32). Performance was also good for predicting seasonal patterns (MEf between 0.84 and 0.89, except for NEE (0.64)). By comparison, predictions of monthly anomalies were not as strong (MEf between 0.29 and 0.52). Improved accounting of disturbance and lagged environmental effects, along with improved characterization of errors in the training data set, would contribute most to further reducing uncertainties. Our global estimates of LE (158 +/- 7 J x 10(18) yr(-1)), H (164 +/- 15 J x 10(18) yr(-1)), and GPP (119 +/- 6 Pg C yr(-1)) were similar to independent estimates. Our global TER estimate (96 +/- 6 Pg C yr(-1)) was likely underestimated by 5-10%. Hot spot regions of interannual variability in carbon fluxes occurred in semiarid to semihumid regions and were controlled by moisture supply. Overall, GPP was more important to interannual variability in NEE than TER. Our empirically derived fluxes may be used for calibration and evaluation of land surface process models and for exploratory and diagnostic assessments of the biosphere.
927 citations
TL;DR: In this paper, the authors developed, present and evaluate a refined, statistical index of model performance, which is a reformulation of Willmott's index of agreement, which was developed in the 1980s.
Abstract: In this paper, we develop, present and evaluate a refined, statistical index of model performance. This ‘new’ measure (dr) is a reformulation of Willmott's index of agreement, which was developed in the 1980s. It (dr) is dimensionless, bounded by − 1.0 and 1.0 and, in general, more rationally related to model accuracy than are other existing indices. It also is quite flexible, making it applicable to a wide range of model-performance problems. The two main published versions of Willmott's index as well as four other comparable dimensionless indices—proposed by Nash and Sutcliffe in 1970, Watterson in 1996, Legates and McCabe in 1999 and Mielke and Berry in 2001—are compared with the new index. Of the six, Legates and McCabe's measure is most similar to dr. Repeated calculations of all six indices, from intensive random resamplings of predicted and observed spaces, are used to show the covariation and differences between the various indices, as well as their relative efficacies. Copyright © 2011 Royal Meteorological Society
924 citations
Cites background or result from "River flow forecasting through conc..."
...Of the six comparable measures, the indices of Nash and Sutcliffe (1970) and Legates and McCabe (1999) are most closely related to dr, because – within these measures –...
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...In addition, the relative performance of the new index was compared with the performances of comparable indices proposed by Nash and Sutcliffe (1970), Watterson (1996), Legates and McCabe (1999) and Mielke and Berry (2001)....
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TL;DR: In this article, a simple groundwater flow and height model was added to an existing basin-scale surface water model and validated on a 471 km2 watershed near Waco, Texas.
916 citations
Delft University of Technology1, UNESCO-IHE Institute for Water Education2, Vienna University of Technology3, University of Saskatchewan4, University of Illinois at Urbana–Champaign5, Swedish Meteorological and Hydrological Institute6, National Center for Atmospheric Research7, Karlsruhe Institute of Technology8, University of Bristol9, Russian Academy of Sciences10, University of Arizona11, Rhodes University12, University of Bologna13, University of Aberdeen14, Agrocampus Ouest15
TL;DR: The Prediction in Ungauged Basins (PUB) initiative of the International Association of Hydrological Sciences (IAHS) launched in 2003 and concluded by the PUB Symposium 2012 held in Delft (23-25 October 2012), set out to shift the scientific culture of hydrology towards improved scientific understanding of hydrological processes, as well as associated uncertainties and the development of models with increasing realism and predictive power as discussed by the authors.
Abstract: The Prediction in Ungauged Basins (PUB) initiative of the International Association of Hydrological Sciences (IAHS), launched in 2003 and concluded by the PUB Symposium 2012 held in Delft (23–25 October 2012), set out to shift the scientific culture of hydrology towards improved scientific understanding of hydrological processes, as well as associated uncertainties and the development of models with increasing realism and predictive power. This paper reviews the work that has been done under the six science themes of the PUB Decade and outlines the challenges ahead for the hydrological sciences community.Editor D. KoutsoyiannisCitation Hrachowitz, M., Savenije, H.H.G., Bloschl, G., McDonnell, J.J., Sivapalan, M., Pomeroy, J.W., Arheimer, B., Blume, T., Clark, M.P., Ehret, U., Fenicia, F., Freer, J.E., Gelfan, A., Gupta, H.V., Hughes, D.A., Hut, R.W., Montanari, A., Pande, S., Tetzlaff, D., Troch, P.A., Uhlenbrook, S., Wagener, T., Winsemius, H.C., Woods, R.A., Zehe, E., and Cudennec, C., 2013. A d...
848 citations
Cites background from "River flow forecasting through conc..."
...The Nash-Sutcliffe Efficiency (NSE; Nash and Sutcliffe 1970) is one of the objective functions that became popular as a convenient and normalized measure of model performance....
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TL;DR: In this paper, the most relevant approach to calculate potential evapotranspiration (PE) for use in a daily rainfall-runoff model, while answering the following question: How can we use available atmospheric variables to represent the evaporative demand at the basin scale?
827 citations