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3. Twenty-three unsolved problems in hydrology (UPH)–a community perspective

Author

Blöschl, G., Bierkens, M. F. P., Chambel, A., Cudennec, C., Destouni, G., Fiori, A., Kirchner, J. W., McDonnell, J. J., Savenije, H. H. G., Sivapalan, M., Stumpp, C., Toth, E., Volpi, E., Carr, G., Lupton, C., Salinas, J., Széles, B., Viglione, A., Aksoy, H., Allen, S. T., Amin, A., Andréassian, V., Arheimer, B., Aryal, S. K., Baker, V., Bardsley, E., Barendrecht, M. H., Bartosova, A., Batelaan, O., Berghuijs, W. R., Beven, K., Blume, T., Bogaard, T., Borges de Amorim, P., Böttcher, M. E., Boulet, G., Breinl, K., Brilly, M., Brocca, L., Buytaert, W., Castellarin, A., Castelletti, A., Chen, X., Chen, Y., Chifflard, P., Claps, P., Clark, M. P., Collins, A. L., Croke, B., Dathe, A., David, P. C., de Barros, F. P. J., de Rooij, G., Di Baldassarre, G., Driscoll, J. M., Duethmann, D., Dwivedi, R., Eris, E., Farmer, W. H., Feiccabrino, J., Ferguson, G., Ferrari, E., Ferraris, S., Fersch, B., Finger, D., Foglia, L., Fowler, K., Gartsman, B., Gascoin, S., Gaume, E., Gelfan, A., Geris, J., Gharari, S., Gleeson, T., Glendell, M., Gonzalez Bevacqua, A., González-Dugo, M. P., Grimaldi, S., Gupta, A. B., Guse, B., Han, D., Hannah, D., Harpold, A., Haun, S., Heal, K., Helfricht, K., Herrnegger, M., Hipsey, M., Hlaváčiková, H., Hohmann, C., Holko, L., Hopkinson, C., Hrachowitz, M., Illangasekare, T. H., Inam, A., Innocente, C., Istanbulluoglu, E., Jarihani, B., Kalantari, Z., Kalvans, A., Khanal, S., Khatami, S., Kiesel, J., Kirkby, M., Knoben, W., Kochanek, K., Kohnová, S., Kolechkina, A., Krause, S., Kreamer, D., Kreibich, H., Kunstmann, H., Lange, H., Liberato, M. L. R., Lindquist, E., Link, T., Liu, J., Loucks, D. P., Luce, C., Mahé, G., Makarieva, O., Malard, J., Mashtayeva, S., Maskey, S., Mas-Pla, J., Mavrova-Guirguinova, M., Mazzoleni, M., Mernild, S., Misstear, B. D., Montanari, A., Müller-Thomy, H., Nabizadeh, A., Nardi, F., Neale, C., Nesterova, N., Nurtaev, B., Odongo, V. O., Panda, S., Pande, S., Pang, Z., Papacharalampous, G., Perrin, C., Pfister, L., Pimentel, R., Polo, M. J., Post, D., Prieto Sierra, C., Ramos, M. -H, Renner, M., Reynolds, J. E., Ridolfi, E., Rigon, R., Riva, M., Robertson, D. E., Rosso, R., Roy, T., Sá, J.H.M., Salvadori, G., Sandells, M., Schaefli, B., Schumann, A., Scolobig, A., Seibert, J., Servat, E., Shafiei, M., Sharma, A., Sidibe, M., Sidle, R. C., Skaugen, T., Smith, H., Spiessl, S. M., Stein, L., Steinsland, I., Strasser, U., Su, B., Szolgay, J., Tarboton, D., Tauro, F., Thirel, G., Tian, F., Tong, R., Tussupova, K., Tyralis, H., Uijlenhoet, R., van Beek, R., van der Ent, R. J., van der Ploeg, M., Van Loon, A. F., van Meerveld, I., van Nooijen, R., van Oel, P. R., Vidal, J. -P, von Freyberg, J., Vorogushyn, S., Wachniew, P., Wade, A. J., Ward, P., Westerberg, I. K., White, C., Wood, E. F., Woods, R., Xu, Z., Yilmaz, K. K., Zhang, Y., Blöschl, G., Bierkens, M. F. P., Chambel, A., Cudennec, C., Destouni, G., Fiori, A., Kirchner, J. W., McDonnell, J. J., Savenije, H. H. G., Sivapalan, M., Stumpp, C., Toth, E., Volpi, E., Carr, G., Lupton, C., Salinas, J., Széles, B., Viglione, A., Aksoy, H., Allen, S. T., Amin, A., Andréassian, V., Arheimer, B., Aryal, S. K., Baker, V., Bardsley, E., Barendrecht, M. H., Bartosova, A., Batelaan, O., Berghuijs, W. R., Beven, K., Blume, T., Bogaard, T., Borges de Amorim, P., Böttcher, M. E., Boulet, G., Breinl, K., Brilly, M., Brocca, L., Buytaert, W., Castellarin, A., Castelletti, A., Chen, X., Chen, Y., Chifflard, P., Claps, P., Clark, M. P., Collins, A. L., Croke, B., Dathe, A., David, P. C., de Barros, F. P. J., de Rooij, G., Di Baldassarre, G., Driscoll, J. M., Duethmann, D., Dwivedi, R., Eris, E., Farmer, W. H., Feiccabrino, J., Ferguson, G., Ferrari, E., Ferraris, S., Fersch, B., Finger, D., Foglia, L., Fowler, K., Gartsman, B., Gascoin, S., Gaume, E., Gelfan, A., Geris, J., Gharari, S., Gleeson, T., Glendell, M., Gonzalez Bevacqua, A., González-Dugo, M. P., Grimaldi, S., Gupta, A. B., Guse, B., Han, D., Hannah, D., Harpold, A., Haun, S., Heal, K., Helfricht, K., Herrnegger, M., Hipsey, M., Hlaváčiková, H., Hohmann, C., Holko, L., Hopkinson, C., Hrachowitz, M., Illangasekare, T. H., Inam, A., Innocente, C., Istanbulluoglu, E., Jarihani, B., Kalantari, Z., Kalvans, A., Khanal, S., Khatami, S., Kiesel, J., Kirkby, M., Knoben, W., Kochanek, K., Kohnová, S., Kolechkina, A., Krause, S., Kreamer, D., Kreibich, H., Kunstmann, H., Lange, H., Liberato, M. L. R., Lindquist, E., Link, T., Liu, J., Loucks, D. P., Luce, C., Mahé, G., Makarieva, O., Malard, J., Mashtayeva, S., Maskey, S., Mas-Pla, J., Mavrova-Guirguinova, M., Mazzoleni, M., Mernild, S., Misstear, B. D., Montanari, A., Müller-Thomy, H., Nabizadeh, A., Nardi, F., Neale, C., Nesterova, N., Nurtaev, B., Odongo, V. O., Panda, S., Pande, S., Pang, Z., Papacharalampous, G., Perrin, C., Pfister, L., Pimentel, R., Polo, M. J., Post, D., Prieto Sierra, C., Ramos, M. -H, Renner, M., Reynolds, J. E., Ridolfi, E., Rigon, R., Riva, M., Robertson, D. E., Rosso, R., Roy, T., Sá, J.H.M., Salvadori, G., Sandells, M., Schaefli, B., Schumann, A., Scolobig, A., Seibert, J., Servat, E., Shafiei, M., Sharma, A., Sidibe, M., Sidle, R. C., Skaugen, T., Smith, H., Spiessl, S. M., Stein, L., Steinsland, I., Strasser, U., Su, B., Szolgay, J., Tarboton, D., Tauro, F., Thirel, G., Tian, F., Tong, R., Tussupova, K., Tyralis, H., Uijlenhoet, R., van Beek, R., van der Ent, R. J., van der Ploeg, M., Van Loon, A. F., van Meerveld, I., van Nooijen, R., van Oel, P. R., Vidal, J. -P, von Freyberg, J., Vorogushyn, S., Wachniew, P., Wade, A. J., Ward, P., Westerberg, I. K., White, C., Wood, E. F., Woods, R., Xu, Z., Yilmaz, K. K., and Zhang, Y.

Abstract

QC 20210112

Published
2019
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5. Une comparaison de plusieurs méthodes d'estimation de l'incertitude des courbes de tarage hauteur-débit

Author

Gazoorian, C., Kiang, J., Mason, R., Le Coz, Jérôme, Renard, Benjamin, Mansanarez, V., McMillan, H.K., Westerberg, I., Petersen Overleir, A., Reitan, T., Sikorska, A., Seibert, J., Coxon, G., Freer, J., Belleville, A., Hauet, A., USGS NEW YORK WATER SCIENCE CENTER NEW YORK USA, Partenaires IRSTEA, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), USGS RESTON USA, Hydrologie-Hydraulique (UR HHLY), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), SAN DIEGO STATE UNIVERSITY USA, IVL SWE, STATKRAFT NOR, NVE NOR, UNIVERSITY OF ZURICH CHE, UNIVERSITY OF BRISTOL GBR, and EDF (EDF)

Subjects
[SDE]Environmental Sciences
Abstract

International audience; Stage-discharge rating curves are used to relate streamflow discharge to continuously measured river stage readings to create a continuous record of streamflow discharge. The stage-discharge relationship is estimated and refined using discrete streamflow measurements over time, during which both the discharge and stage are measured. There is uncertainty in the resulting rating curve due to multiple factors including the curve-fitting process, assumptions on the form of the model used, fluvial geomorphology of natural channels, and the approaches used to extrapolate the rating equation beyond available observations. This rating curve uncertainty leads to uncertainty in the streamflow timeseries, and therefore to uncertainty in predictive models that use the streamflow data. Many different methods have been proposed in the literature for estimating rating curve uncertainty, differing in mathematical rigor, in the assumptions made about the component errors, and in the information required to implement the method at any given site. This study describes the results of an international experiment to test and compare streamflow uncertainty estimation methods from 7 research groups across 9 institutions. The methods range from simple LOWESS fits to more complicated Bayesian methods that consider hydraulic principles directly. We evaluate these different methods when applied to three diverse gauging stations using standardized information (channel characteristics, hydrographs, and streamflow measurements). Our results quantify the resultant spread of the stage-discharge Stage-discharge rating curves are developed by relating measured streamflow discharges to concurrent measured river stage readings. Once developed, a rating curve can be used to convert a continuous stage record into a continuous record of streamflow. The stage-discharge relation is estimated and refined using discrete streamflow measurements over time, during which both the discharge and stage are measured. Besides the uncertainties inherently associated with a discharge measurement, there is uncertainty in the resulting rating curve due to multiple factors including the curve-fitting process, assumptions on the form of the model used, fluvial geomorphology of natural channels, and the approaches used to extrapolate the rating equation beyond available observations. A number of different methods have been tested for estimating rating curve uncertainty, differing in mathematical complexity, in the assumptions made about the component errors, and in the information required to implement the method at any given site. This study compares several methods that range from simple regression fits to more complicated Bayesian methods that consider hydraulic principles directly. We evaluate these different methods when applied to three gaging stations using the same information (channel characteristics, hydrographs, and streamflow measurements). We quantify the resultant spread of the stage-discharge curves and compare the level of uncertainty attributed to the streamflow records by the different methods.

Published
2017

6. The role of rating curve uncertainty in real-time flood forecasting

Author

Ocio, D, Le Vine, N, Westerberg, I, Pappenberger, F, and Buytaert, W

Subjects
PARTICLE FILTER, Science & Technology, Environmental Engineering, SCHEME, Environmental Sciences & Ecology, flow measurement error, FREQUENCY, 0905 Civil Engineering, 0907 Environmental Engineering, DATA ASSIMILATION, Physical Sciences, Limnology, ENSEMBLE KALMAN FILTER, DISTRIBUTED HYDROLOGICAL MODEL, Water Resources, MANAGEMENT, Marine & Freshwater Biology, real-time flood forecasting, UNGAUGED CATCHMENTS, Life Sciences & Biomedicine, rating curve uncertainty, 1402 Applied Economics, Environmental Sciences, RAINFALL-RUNOFF MODEL, PARAMETER-ESTIMATION
Abstract

Data assimilation has been widely tested for flood forecasting, although its use in operational systems is mainly limited to a simple statistical error correction. This can be due to the complexity involved in making more advanced formal assumptions about the nature of the model and measurement errors. Recent advances in the definition of rating curve uncertainty allow estimating a flow measurement error that includes both aleatory and epistemic uncertainties more explicitly and rigorously than in the current practice. The aim of this study is to understand the effect such a more rigorous definition of the flow measurement error has on real-time data assimilation and forecasting. This study, therefore, develops a comprehensive probabilistic framework that considers the uncertainty in model forcing data, model structure, and flow observations. Three common data assimilation techniques are evaluated: (1) Autoregressive error correction, (2) Ensemble Kalman Filter, and (3) Regularized Particle Filter, and applied to two locations in the flood-prone Oria catchment in the Basque Country, northern Spain. The results show that, although there is a better match between the uncertain forecasted and uncertain true flows, there is a low sensitivity for the threshold exceedances used to issue flood warnings. This suggests that a standard flow measurement error model, with a spread set to a fixed flow fraction, represents a reasonable trade-off between complexity and realism. Standard models are therefore recommended for operational flood forecasting for sites with well-defined stage-discharge curves that are based on a large range of flow observations.

Published
2017

7. Une expérience pour comparer plusieurs méthodes d'estimation de l'incertitude des débits des cours d'eau

Author

Kiang, J., Mc Millan, H., Gazoorian, C., Mason, R., Le Coz, Jérôme, Renard, Benjamin, Mansanarez, V., Westerberg, I., Petersen Overleir, A., Reitan, T., Sikorska, A., Seibert, J., Coxon, G., Freer, J., Belleville, A., Hauet, A., United States Geological Survey (USGS), SAN DIEGO STATE UNIVERSITY SAN DIEGO USA, Partenaires IRSTEA, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Hydrologie-Hydraulique (UR HHLY), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), IVL SWEDISH ENVIRONMENTAL RESEARCH INSTITUTE STOCKHOLM SWE, STATKRAFT NOR, NVE NOR, UNIVERSITY OF ZURICH CHE, UNIVERSITY OF BRISTOL GBR, and EDF (EDF)

Subjects
[SDE]Environmental Sciences
Abstract

International audience; Stage-discharge rating curves are used to relate streamflow discharge to continuously measured river stage readings to create a continuous record of streamflow discharge. The stage-discharge relationship is estimated and refined using discrete streamflow measurements over time, during which both the discharge and stage are measured. There is uncertainty in the resulting rating curve due to multiple factors including the curve-fitting process, assumptions on the form of the model used, fluvial geomorphology of natural channels, and the approaches used to extrapolate the rating equation beyond available observations. This rating curve uncertainty leads to uncertainty in the streamflow timeseries, and therefore to uncertainty in predictive models that use the streamflow data. Many different methods have been proposed in the literature for estimating rating curve uncertainty, differing in mathematical rigor, in the assumptions made about the component errors, and in the information required to implement the method at any given site. This study describes the results of an international experiment to test and compare streamflow uncertainty estimation methods from 7 research groups across 9 institutions. The methods range from simple LOWESS fits to more complicated Bayesian methods that consider hydraulic principles directly. We evaluate these different methods when applied to three diverse gauging stations using standardized information (channel characteristics, hydrographs, and streamflow measurements). Our results quantify the resultant spread of the stage-discharge curves and compare the level of uncertainty attributed to the streamflow records by each different method. We provide insight into the sensitivity of streamflow uncertainty bounds to the choice of uncertainty estimation method, and discuss the implications for model uncertainty assessment.

Published
2017

8. Five guidelines for selecting hydrological signatures

Author

McMillan, H., Westerberg, I., Branger, F., San Diego State University (SDSU), IVL, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture, IRSTEA, Hydrologie-Hydraulique (UR HHLY), and Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)

Subjects
ComputerApplications_MISCELLANEOUS, HYDROLOGIE, [SDE]Environmental Sciences, hydrology
Abstract

International audience; The aim of this paper is to encourage a more rigorous approach to hydrological signature selection, which considers the ability of signatures to represent hydrological behaviour and underlying processes for the catchment and application in question. To this end, we propose a set of guidelines for selecting hydrological signatures. We describe five criteria that any hydrological signature should conform to: Identifiability, Robustness, Consistency, Representativeness, and Discriminatory Power. We explain why each criterion is important and give examples of design or adaption of signatures to meet the guidelines.

Published
2017

9. A novel framework for discharge uncertainty quantification applied to 500 UK gauging stations

Author

Coxon, G., Freer, J., Westerberg, I. K., Wagener, T., Woods, R., and Smith, P. J.

Subjects
Informatics, rating curve, Uncertainty, Uncertainty Assessment, observational uncertainty, United Kingdom, History of Geophysics, LOWESS, generalized framework, Uncertainty Quantification, discharge data, Hydrology, Mathematical Geophysics, Research Articles, Research Article
Abstract

Benchmarking the quality of river discharge data and understanding its information content for hydrological analyses is an important task for hydrologic science. There is a wide variety of techniques to assess discharge uncertainty. However, few studies have developed generalized approaches to quantify discharge uncertainty. This study presents a generalized framework for estimating discharge uncertainty at many gauging stations with different errors in the stage‐discharge relationship. The methodology utilizes a nonparametric LOWESS regression within a novel framework that accounts for uncertainty in the stage‐discharge measurements, scatter in the stage‐discharge data and multisection rating curves. The framework was applied to 500 gauging stations in England and Wales and we evaluated the magnitude of discharge uncertainty at low, mean and high flow points on the rating curve. The framework was shown to be robust, versatile and able to capture place‐specific uncertainties for a number of different examples. Our study revealed a wide range of discharge uncertainties (10–397% discharge uncertainty interval widths), but the majority of the gauging stations (over 80%) had mean and high flow uncertainty intervals of less than 40%. We identified some regional differences in the stage‐discharge relationships, however the results show that local conditions dominated in determining the magnitude of discharge uncertainty at a gauging station. This highlights the importance of estimating discharge uncertainty for each gauging station prior to using those data in hydrological analyses., Key Points: A generalized framework for discharge uncertainty estimation is presentedAllows estimation of place‐specific discharge uncertainties for many catchmentsLocal conditions dominate in determining discharge uncertainty magnitudes

Published
2015

14. Regional water balance modelling using flow-duration curves with observational uncertainties

Author

Westerberg, I. K., Gong, L., Beven, K. J., Seibert, J., Semedo, A., Xu, C. Y., Halldin, S., Westerberg, I. K., Gong, L., Beven, K. J., Seibert, J., Semedo, A., Xu, C. Y., and Halldin, S.

Abstract

Robust and reliable water-resource mapping in ungauged basins requires estimation of the uncertainties in the hydrologic model, the regionalisation method, and the observational data. In this study we investigated the use of regionalised flow-duration curves (FDCs) for constraining model predictive uncertainty, while accounting for all these uncertainty sources. A water balance model was applied to 36 basins in Central America using regionally and globally available precipitation, climate and discharge data that were screened for inconsistencies. A rating-curve analysis for 35 Honduran discharge stations was used to estimate discharge uncertainty for the region, and the consistency of the model forcing and evaluation data was analysed using two different screening methods. FDCs with uncertainty bounds were calculated for each basin, accounting for both discharge uncertainty and, in many cases, uncertainty stemming from the use of short time series, potentially not representative for the modelling period. These uncertain FDCs were then used to regionalise a FDC for each basin, treating it as ungauged in a cross-evaluation, and this regionalised FDC was used to constrain the uncertainty in the model predictions for the basin. There was a clear relationship between the performance of the local model calibration and the degree of data set consistency - with many basins with inconsistent data lacking behavioural simulations (i.e. simulations within predefined limits around the observed FDC) and the basins with the highest data set consistency also having the highest simulation reliability. For the basins where the regionalisation of the FDCs worked best, the uncertainty bounds for the regionalised simulations were only slightly wider than those for a local model calibration. The predicted uncertainty was greater for basins where the result of the FDC regionalisation was more uncertain, but the regionalised simulations still had a high reliability compared to the locally

Published
2014

17. Stage-discharge uncertainty derived with a non-stationary rating curve in the Choluteca River, Honduras

Author

Westerberg, I., Guerrero, J. -L, Seibert, Jan, Beven, K. J., Halldin, S., Westerberg, I., Guerrero, J. -L, Seibert, Jan, Beven, K. J., and Halldin, S.

Abstract

Uncertainty in discharge data must be critically assessed before data can be used in, e. g. water resources estimation or hydrological modelling. In the alluvial Choluteca River in Honduras, the river-bed characteristics change over time as fill, scour and other processes occur in the channel, leading to a non-stationary stage-discharge relationship and difficulties in deriving consistent rating curves. Few studies have investigated the uncertainties related to non-stationarity in the stage-discharge relationship. We calculated discharge and the associated uncertainty with a weighted fuzzy regression of rating curves applied within a moving time window, based on estimated uncertainties in the observed rating data. An 18-year-long dataset with unusually frequent ratings (1268 in total) was the basis of this study. A large temporal variability in the stage-discharge relationship was found especially for low flows. The time-variable rating curve resulted in discharge estimate differences of -60 to +90% for low flows and +/- 20% for medium to high flows when compared to a constant rating curve. The final estimated uncertainty in discharge was substantial and the uncertainty limits varied between -43 to +73% of the best discharge estimate., authorCount :5

Published
2011
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18. Calibration of hydrological models using flow-duration curves

Author

Westerberg, I. K., Guerrero, J. -L, Younger, P. M., Beven, K. J., Seibert, Jan, Halldin, S., Freer, J. E., Xu, C. -Y, Westerberg, I. K., Guerrero, J. -L, Younger, P. M., Beven, K. J., Seibert, Jan, Halldin, S., Freer, J. E., and Xu, C. -Y

Abstract

The degree of belief we have in predictions from hydrologic models will normally depend on how well they can reproduce observations. Calibrations with traditional performance measures, such as the Nash-Sutcliffe model efficiency, are challenged by problems including: (1) uncertain discharge data, (2) variable sensitivity of different performance measures to different flow magnitudes, (3) influence of unknown input/output errors and (4) inability to evaluate model performance when observation time periods for discharge and model input data do not overlap. This paper explores a calibration method using flow-duration curves (FDCs) to address these problems. The method focuses on reproducing the observed discharge frequency distribution rather than the exact hydrograph. It consists of applying limits of acceptability for selected evaluation points (EPs) on the observed uncertain FDC in the extended GLUE approach. Two ways of selecting the EPs were tested - based on equal intervals of discharge and of volume of water. The method was tested and compared to a calibration using the traditional model efficiency for the daily four-parameter WAS-MOD model in the Paso La Ceiba catchment in Honduras and for Dynamic TOPMODEL evaluated at an hourly time scale for the Brue catchment in Great Britain. The volume method of selecting EPs gave the best results in both catchments with better calibrated slow flow, recession and evaporation than the other criteria. Observed and simulated time series of uncertain discharges agreed better for this method both in calibration and prediction in both catchments. An advantage with the method is that the rejection criterion is based on an estimation of the uncertainty in discharge data and that the EPs of the FDC can be chosen to reflect the aims of the modelling application, e. g. using more/less EPs at high/low flows. While the method appears less sensitive to epistemic input/output errors than previous use of limits of acceptability applied di, authorCount :8

Published
2011
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19. Calibration of hydrological models using flow-duration curves

Author

Westerberg, I K, Guerrero, J L, Younger, P M, Beven, K J, Seibert, Jan; https://orcid.org/0000-0002-6314-2124, Halldin, S, Freer, J E, Xu, C Y, Westerberg, I K, Guerrero, J L, Younger, P M, Beven, K J, Seibert, Jan; https://orcid.org/0000-0002-6314-2124, Halldin, S, Freer, J E, and Xu, C Y

Abstract

The degree of belief we have in predictions from hydrologic models will normally depend on how well they can reproduce observations. Calibrations with traditional performance measures, such as the Nash-Sutcliffe model efficiency, are challenged by problems including: (1) uncertain discharge data, (2) variable sensitivity of different performance measures to different flow magnitudes, (3) influence of unknown input/output errors and (4) inability to evaluate model performance when observation time periods for discharge and model input data do not overlap. This paper explores a calibration method using flow-duration curves (FDCs) to address these problems. The method focuses on reproducing the observed discharge frequency distribution rather than the exact hydrograph. It consists of applying limits of acceptability for selected evaluation points (EPs) on the observed uncertain FDC in the extended GLUE approach. Two ways of selecting the EPs were tested – based on equal intervals of discharge and of volume of water. The method was tested and compared to a calibration using the traditional model efficiency for the daily four-parameter WASMOD model in the Paso La Ceiba catchment in Honduras and for Dynamic TOPMODEL evaluated at an hourly time scale for the Brue catchment in Great Britain. The volume method of selecting EPs gave the best results in both catchments with better calibrated slow flow, recession and evaporation than the other criteria. Observed and simulated time series of uncertain discharges agreed better for this method both in calibration and prediction in both catchments. An advantage with the method is that the rejection criterion is based on an estimation of the uncertainty in discharge data and that the EPs of the FDC can be chosen to reflect the aims of the modelling application, e.g. using more/less EPs at high/low flows. While the method appears less sensitive to epistemic input/output errors than previous use of limits of acceptability applied dire

Published
2011

20. TWINLATIN: Twinning European and Latin American river basins for research enabling sustainable water resources management. Report D8.1 Change effects and vulnerability assessment

Author

Tote, C., Alcoz, S., Collischonn, W., Debels, P., Duque, A., Ekstrand, S., Filiberto, I., Folwell, S., Govers, G., Houghton-Carr, H., Stehr, A., Westerberg, I., Tote, C., Alcoz, S., Collischonn, W., Debels, P., Duque, A., Ekstrand, S., Filiberto, I., Folwell, S., Govers, G., Houghton-Carr, H., Stehr, A., and Westerberg, I.

Published
2009

21. TWINLATIN: Twinning European and Latin-American river basins for research enabling sustainable water resources management. Combined Report D3.1 Hydrological modelling report and D3.2 Evaluation report

Author

Houghton-Carr, Helen, Alcoz, S., Collischonn, W., Debels, P., Duque, A., Ekstrand, S., Filiberto, I., Folwell, S., Govers, G., Houghton-Carr, H., Stehr, A., Tote, C., Westerberg, I., Houghton-Carr, Helen, Alcoz, S., Collischonn, W., Debels, P., Duque, A., Ekstrand, S., Filiberto, I., Folwell, S., Govers, G., Houghton-Carr, H., Stehr, A., Tote, C., and Westerberg, I.

Abstract

Water use has almost tripled over the past 50 years and in some regions the water demand already exceeds supply (Vorosmarty et al., 2000). The world is facing a “global water crisis”; in many countries, current levels of water use are unsustainable, with systems vulnerable to collapse from even small changes in water availability. The need for a scientifically-based assessment of the potential impacts on water resources of future changes, as a basis for society to adapt to such changes, is strong for most parts of the world. Although the focus of such assessments has tended to be climate change, socio-economic changes can have as significant an impact on water availability across the four main use sectors i.e. domestic, agricultural, industrial (including energy) and environmental. Withdrawal and consumption of water is expected to continue to grow substantially over the next 20-50 years (Cosgrove & Rijsberman, 2002), and consequent changes in availability may drastically affect society and economies. One of the most needed improvements in Latin American river basin management is a higher level of detail in hydrological modelling and erosion risk assessment, as a basis for identification and analysis of mitigation actions, as well as for analysis of global change scenarios. Flow measurements are too costly to be realised at more than a few locations, which means that modelled data are required for the rest of the basin. Hence, TWINLATIN Work Package 3 “Hydrological modelling and extremes” was formulated to provide methods and tools to be used by other WPs, in particular WP6 on “Pollution pressure and impact analysis” and WP8 on “Change effects and vulnerability assessment”. With an emphasis on high and low flows and their impacts, WP3 was originally called “Hydrological modelling, flooding, erosion, water scarcity and water abstraction”. However, at the TWINLATIN kick-off meeting it was agreed that some of these issues resided more appropriately in WP6 and WP8, and

Published
2009

27. A novel framework for discharge uncertainty quantification applied to 500 UKgauging stations

Author

Coxon, G., Freer, J., Westerberg, I. K., Wagener, T., Woods, R., and Smith, P. J.

Abstract

Benchmarking the quality of river discharge data and understanding its information content for hydrological analyses is an important task for hydrologic science. There is a wide variety of techniques to assess discharge uncertainty. However, few studies have developed generalized approaches to quantify discharge uncertainty. This study presents a generalized framework for estimating discharge uncertainty at many gauging stations with different errors in the stage‐discharge relationship. The methodology utilizes a nonparametric LOWESS regression within a novel framework that accounts for uncertainty in the stage‐discharge measurements, scatter in the stage‐discharge data and multisection rating curves. The framework was applied to 500 gauging stations in England and Wales and we evaluated the magnitude of discharge uncertainty at low, mean and high flow points on the rating curve. The framework was shown to be robust, versatile and able to capture place‐specific uncertainties for a number of different examples. Our study revealed a wide range of discharge uncertainties (10–397% discharge uncertainty interval widths), but the majority of the gauging stations (over 80%) had mean and high flow uncertainty intervals of less than 40%. We identified some regional differences in the stage‐discharge relationships, however the results show that local conditions dominated in determining the magnitude of discharge uncertainty at a gauging station. This highlights the importance of estimating discharge uncertainty for each gauging station prior to using those data in hydrological analyses. A generalized framework for discharge uncertainty estimation is presentedAllows estimation of place‐specific discharge uncertainties for many catchmentsLocal conditions dominate in determining discharge uncertainty magnitudes

Published
2015
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29. Calibration of hydrological models using flow-duration curves.

Author

Westerberg, I. K., Guerrero, J.-L., Younger, P. M., Beven, K. J., Seibert, J., Halldin, S., Freer, J. E., and C. Y. Xu

Abstract

The degree of belief we have in predictions from hydrologic models depends on how well they can reproduce observations. Calibrations with traditional performance measures such as the Nash-Sutcliffe model efficiency are challenged by problems including: (1) uncertain discharge data, (2) variable importance of the performance with flow magnitudes, (3) influence of unknown input/output errors and (4) inability to evaluate model performance when observation time periods for discharge and model input data do not overlap. A new calibration method using flow-duration curves (FDCs) was developed which addresses these problems. The method focuses on reproducing the observed discharge frequency distribution rather than the exact hydrograph. It consists of applying limits of acceptability for selected evaluation points (EPs) of the observed uncertain FDC in the extended GLUE approach. Two ways of selecting the EPs were tested -- based on equal intervals of discharge and of volume of water. The method was tested and compared to a calibration using the traditional model efficiency for the daily four-parameter WASMOD model in the Paso La Ceiba catchment in Honduras and for Dynamic TOPMODEL evaluated at an hourly time scale for the Brue catchment in Great Britain. The volume method of selecting EPs gave the best results in both catchments with better calibrated slow flow, recession and evaporation than the other criteria. Observed and simulated time series of uncertain discharges agreed better for this method both in calibration and prediction in both catchments without resulting in overpredicted simulated uncertainty. An advantage with the method is that the rejection criterion is based on an estimation of the uncertainty in discharge data and that the EPs of the FDC can be chosen to reflect the aims of the modelling application e.g. using more/less EPs at high/low flows. While the new method is less sensitive to epistemic input/output errors than the normal use of limits of acceptability applied directly to the time series of discharge, it still requires a reasonable representation of the distribution of inputs. Additional constraints might therefore be required in catchments subject to snow. The results suggest that the new calibration method can be useful when observation time periods for discharge and model input data do not overlap. The new method could also be suitable for calibration to regional FDCs while taking uncertainties in the hydrological model and data into account. [ABSTRACT FROM AUTHOR]

Published
2010
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30. Estimating uncertainties in hydraulicallymodelled rating curves for discharge time series assessment

Author

Mansanarez Valentin, Westerberg Ida K., Lyon Steve W., and Lam Norris

Subjects
Environmental sciences, GE1-350
Abstract

Establishing a reliable stage-discharge (SD) rating curve for calculating discharge at a hydrological gauging station normally takes years of data collection. Estimation of high flows is particularly difficult as they occur rarely and are often difficult to gauge in practice. At a minimum, hydraulicallymodelled rating curves could be derived with as few as two concurrent SD and water-surface slope measurements at different flow conditions. This means that a reliable rating curve can, potentially, be developed much faster via hydraulic modelling than using a traditional rating curve approach based on numerous stage-discharge gaugings. In this study, we use an uncertainty framework based on Bayesian inference and hydraulic modelling for developing SD rating curves and estimating their uncertainties. The framework incorporates information from both the hydraulic configuration (bed slope, roughness, vegetation) using hydraulic modelling and the information available in the SD observation data (gaugings). Discharge time series are estimated by propagating stage records through the posterior rating curve results. Here we apply this novel framework to a Swedish hydrometric station, accounting for uncertainties in the gaugings and the parameters of the hydraulic model. The aim of this study was to assess the impact of using only three gaugings for calibrating the hydraulic model on resultant uncertainty estimations within our framework. The results were compared to prior knowledge, discharge measurements and official discharge estimations and showed the potential of hydraulically-modelled rating curves for assessing uncertainty at high and medium flows, while uncertainty at low flows remained high. Uncertainty results estimated using only three gaugings for the studied site were smaller than ±15% for medium and high flows and reduced the prior uncertainty by a factor of ten on average and were estimated with only 3 gaugings.

Published
2018
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32. Twenty-three unsolved problems in hydrology (UPH) - a community perspective

Author

Bloschl, G., Bierkens, M. F. P., Chambel, A., Cudennec, C., Destouni, G., Fiori, A., Kirchner, J. W., McDonnell, J. J., Savenije, H. H. G., Sivapalan, M., Stumpp, C., Toth, E., Volpi, E., Carr, G., Lupton, C., Salinas, J., Szeles, B., Viglione, A., Aksoy, H., Allen, S. T., Amin, A., Andreassian, V., Arheimer, B., Aryal, S. K., Baker, V., Bardsley, E., Barendrecht, M. H., Bartosova, A., Batelaan, O., Berghuijs, W. R., Beven, K., Blume, T., Bogaard, T., De Amorim, P. B., Bottcher, M. E., Boulet, G., Breinl, K., Brilly, M., Brocca, L., Buytaert, W., Castellarin, A., Castelletti, A., Chen, X. H., Chen, Y. B., Chen, Y. F., Chifflard, P., Claps, P., Clark, M. P., Collins, A. L., Croke, B., Dathe, A., David, P. C., De Barros, F. P. J., De Rooij, G., Di Baldassarre, G., Driscoll, J. M., Duethmann, D., Dwivedi, R., Eris, E., Farmer, W. H., Feiccabrino, J., Ferguson, G., Ferrari, E., Ferraris, S., Fersch, B., Finger, D., Foglia, L., Fowler, K., Gartsman, B., Gascoin, S., Gaume, E., Gelfan, A., Geris, J., Gharari, S., Gleeson, T., Glendell, M., Bevacqua, A. G., Gonzalez-Dugo, M. P., Grimaldi, S., Gupta, A. B., Guse, B., Han, D. W., Hannah, D., Harpold, A., Haun, S., Heal, K., Helfricht, K., Herrnegger, M., Hipsey, M., Hlavacikova, H., Hohmann, C., Holko, L., Hopkinson, C., Hrachowitz, M., Illangasekare, T. H., Inam, A., Innocente, C., Istanbulluoglu, E., Jarihani, B., Kalantari, Z., Kalvans, A., Khanal, S., Khatami, S., Kiesel, J., Kirkby, M., Knoben, W., Kochanek, K., Kohnova, S., Kolechkina, A., Krause, S., Kreamer, D., Kreibich, H., Kunstmann, H., Lange, H., Liberato, M. L. R., Lindquist, E., Link, T., Liu, J. G., Loucks, D. P., Luce, C., Mahe, G., Makarieva, O., Malard, J., Mashtayeva, S., Maskey, S., Mas-Pla, J., Mavrova-Guirguinova, M., Mazzoleni, M., Mernild, S., Misstear, B. D., Montanari, A., Muller-Thomy, H., Nabizadeh, A., Nardi, F., Neale, C., Nesterova, N., Nurtaev, B., Odongo, V. O., Panda, S., Pande, S., Pang, Z. H., Papacharalampous, G., Perrin, C., Pfister, L., Pimentel, R., Polo, M. J., Post, D., Prieto, C., Ramos, M. H., Renner, M., Reynolds, J. E., Ridolfi, E., Rigon, R., Riva, M., Robertson, D. E., Rosso, R., Roy, T., Sa, J. H. M., Salvadori, G., Sandells, M., Schaefli, B., Schumann, A., Scolobig, A., Seibert, J., Servat, E., Shafiei, M., Sharma, A., Sidibe, M., Sidle, R. C., Skaugen, T., Smith, H., Spiessl, S. M., Stein, L., Steinsland, I., Strasser, U., Su, B., Szolgay, J., Tarboton, D., Tauro, F., Thirel, G., Tian, F. Q., Tong, R., Tussupova, K., Tyralis, H., Uijlenhoet, R., Van Beek, R., Van Der Ent, R. J., Van Der Ploeg, M., Van Loon, A. F., Van Meerveld, I., Van Nooijen, R., Van Oel, P. R., Vidal, J. P., Von Freyberg, J., Vorogushyn, S., Wachniew, P., Wade, A. J., Ward, P., Westerberg, I. K., White, C., Wood, E. F., Woods, R., Xu, Z. X., Yilmaz, K. K., and Zhang, Y. Q.

Subjects
910 Geography & travel, 500 Science, 6. Clean water
Abstract

This paper is the outcome of a community initiative to identify major unsolved scientific problems in hydrology motivated by a need for stronger harmonisation of research efforts. The procedure involved a public consultation through online media, followed by two workshops through which a large number of potential science questions were collated, prioritised, and synthesised. In spite of the diversity of the participants (230 scientists in total), the process revealed much about community priorities and the state of our science: a preference for continuity in research questions rather than radical departures or redirections from past and current work. Questions remain focused on the process-based understanding of hydrological variability and causality at all space and time scales. Increased attention to environmental change drives a new emphasis on understanding how change propagates across interfaces within the hydrological system and across disciplinary boundaries. In particular, the expansion of the human footprint raises a new set of questions related to human interactions with nature and water cycle feedbacks in the context of complex water management problems. We hope that this reflection and synthesis of the 23 unsolved problems in hydrology will help guide research efforts for some years to come.

33. Twenty-three unsolved problems in hydrology (UPH) – a community perspective

Author

Alena Gonzalez Bevacqua, Murugesu Sivapalan, Rui Tong, Ruud van der Ent, Holger Lange, Krzysztof Kochanek, Kate Heal, Moussa Sidibe, Ida Westerberg, Scott T. Allen, Pablo Borges de Amorim, Eric Lindquist, Georgia Destouni, Maria-Helena Ramos, Bruce Misstear, Andrew J. Wade, Keith Beven, Luca Brocca, Mike Kirkby, Sina Khatami, David K. Kreamer, Pieter R. van Oel, Zahra Kalantari, Shreedhar Maskey, Sergiy Vorogushyn, Shamshagul Mashtayeva, James W. Kirchner, Andis Kalvans, Hubert H. G. Savenije, Sebastian H. Mernild, Gerrit H. de Rooij, Santosh K. Aryal, Ennio Ferrari, Julien Malard, Alberto Montanari, Ladislav Holko, Sonu Khanal, Silvia Kohnová, Camyla Innocente, Mel Sandells, Josie Geris, Tom Gleeson, Felipe P. J. de Barros, Ben Jarihani, Anne Van Loon, Stefan Krause, Maria Mavrova-Guirguinova, Marlies Barendrecht, María José Polo, Flavia Tauro, Zongxue Xu, B. I. Gartsman, Elena Ridolfi, Charles Perrin, Miriam Glendell, Yuanfang Chen, Ilja van Meerveld, Theresa Blume, Harald Kunstmann, Gemma Carr, Alireza Nabizadeh, Ebru Eris, Christopher J. White, Heidi Kreibich, Hannes Müller-Thomy, Ashish Sharma, Laura Foglia, Josep Mas-Pla, Subhabrata Panda, Shervan Gharari, Renzo Rosso, J. E. Reynolds, Stefano Ferraris, Saket Pande, Markus Hrachowitz, Laurent Pfister, David E. Robertson, Thomas Skaugen, Roy C. Sidle, Rafael Pimentel, Ross Woods, Alena Bartosova, Erkan Istanbulluoglu, Grant Ferguson, Anam Amin, Chris Hopkinson, Korbinian Breinl, David A. Post, Mathew Herrnegger, Aldo Fiori, Ingelin Steinsland, Dawei Han, Lina Stein, Alberto Viglione, Akhilendra Bhushan Gupta, Bakhram Nurtaev, Maurizio Mazzoleni, Charles H. Luce, Martine van der Ploeg, Ronald van Nooijen, Jean-Philippe Vidal, Tirthankar Roy, Borbála Széles, Jens Kiesel, Cristina Prieto Sierra, Junguo Liu, Hafzullah Aksoy, Andreas Schumann, Pierluigi Claps, Berit Arheimer, Georgia Papacharalampous, Wouter Buytaert, Keirnan Fowler, Ulrich Strasser, David C. Finger, Elena Volpi, Matthew R. Hipsey, Paula Cunha David, Margarida L. R. Liberato, Alexander Gelfan, Barry Croke, V.O. Odongo, David M. Hannah, Günter Blöschl, Hristos Tyralis, Olga Makarieva, Nataliia Nesterova, Bettina Schaefli, Kamshat Tussupova, Guillaume Thirel, Kay Helfricht, Timothy E. Link, Earl Bardsley, Wouter J. M. Knoben, Vazken Andréassian, Ján Szolgay, Mojtaba Shafiei, Jose Luis Salinas, Jan Seibert, Benjamin Fersch, Doris Duethmann, Azhar Inam, Yongqiang Zhang, Giuliano Di Baldassarre, Simon Gascoin, Hugh Smith, Martyn P. Clark, Xiaohong Chen, Maik Renner, Tissa H. Illangasekare, Remko Uijlenhoet, Victor R. Baker, Ravindra Dwivedi, Eric Servat, Christophe Cudennec, Jeffrey J. McDonnell, Sabine M. Spiessl, Yangbo Chen, Thom Bogaard, Wouter R. Berghuijs, María P. González-Dugo, Gilles Boulet, Fernando Nardi, Eric Gaume, Jana von Freyberg, Gil Mahé, Peter Chifflard, Mitja Brilly, William H. Farmer, Monica Riva, James Feiccabrino, Claire Lupton, Anna Scolobig, João H.M. Sá, Przemysław Wachniew, Daniel P. Loucks, Jessica M. Driscoll, Bob Su, Elena Toth, Okke Batelaan, Eric F. Wood, Annette Dathe, David G. Tarboton, Attilio Castellarin, Alla Kolechkina, Björn Guse, Christopher M. U. Neale, Salvatore Grimaldi, Zhonghe Pang, Fuqiang Tian, Marc F. P. Bierkens, Christine Stumpp, Philip J. Ward, Stefan Haun, António Chambel, Riccardo Rigon, Andrea Castelletti, Michael E. Böttcher, Rens van Beek, Gianfausto Salvadori, Adrian A. Harpold, Adrian L. Collins, Hana Hlaváčiková, Clara Hohmann, Koray K. Yilmaz, Technical University of Vienna [Vienna] (TU WIEN), Utrecht University [Utrecht], University of Évora [Portugal], Sol Agro et hydrosystème Spatialisation (SAS), AGROCAMPUS OUEST-Institut National de la Recherche Agronomique (INRA), Stockholm University, Roma Tre University, Institut Fédéral de Recherches sur la Forêt, la Neige et le Paysage (WSL), Institut Fédéral de Recherches [Suisse], University of Saskatchewan [Saskatoon] (U of S), Delft University of Technology (TU Delft), Department of Civil and Environmental Engineering [Urbana], University of Illinois at Urbana-Champaign [Urbana], University of Illinois System-University of Illinois System, Department of Civil Chemical Environmental and Materials Engineering [Bologna] (DICAM), University of Bologna, Centre for Ecology and Hydrology [Wallingford] (CEH), Natural Environment Research Council (NERC), Politecnico di Torino [Torino] (Polito), Istanbul Technical University, Department of Land, Environment, Agriculture and Forestry (TeSAF), Universita degli Studi di Padova, Hydrosystèmes continentaux anthropisés : ressources, risques, restauration (UR HYCAR), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Swedish Meteorological and Hydrological Institute (SMHI), Water Resources Section, Centre d'études spatiales de la biosphère (CESBIO), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Observatoire Midi-Pyrénées (OMP), Université Fédérale Toulouse Midi-Pyrénées-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Imperial College London, Sun Yat-Sen University (SYSU), Hohai University, Research Applications Laboratory [Boulder] (RAL), National Center for Atmospheric Research [Boulder] (NCAR), Department of Earth Sciences [ Uppsala], Uppsala University, University of Reykjavik [Islande], Structure et fonctionnement des systèmes hydriques continentaux (SISYPHE), Université Pierre et Marie Curie - Paris 6 (UPMC)-École pratique des hautes études (EPHE)-MINES ParisTech - École nationale supérieure des mines de Paris-Centre National de la Recherche Scientifique (CNRS), Département Géotechnique, Eau et Risques (IFSTTAR/GER), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-PRES Université Nantes Angers Le Mans (UNAM), Water Problems Institute of the Russian Academy of Sciences, Russian Academy of Sciences [Moscow] (RAS), The James Hutton Institute, School of Geography, Earth and Environmental Sciences [Birmingham], University of Birmingham [Birmingham], Center for Experimental Study of Subsurface Environmental Processes (CESEP), Colorado School of Mines, Slovak University of Technology in Bratislava, Hydrology Section, German Research Centre for Geosciences - Helmholtz-Centre Potsdam (GFZ), South University of Science and Technology of China, School of Environmental Science and Engineering, Sun Yat-Sen University (SYSU)-Sun Yat-Sen University (SYSU), Hydrosciences Montpellier (HSM), Institut de Recherche pour le Développement (IRD)-Université Montpellier 2 - Sciences et Techniques (UM2)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Department of Water Science and Engineering, Institute for Water Education (UNESCO–IHE), Università di Bologna [Bologna] (UNIBO), Luxembourg Institute of Science and Technology (LIST), Andalusian Institute of Earth Sciences (IACT), Spanish National Research Council [Madrid] (CSIC), University of Pennsylvania [Philadelphia], Dipartimento di Ingegneria Idraulica, Ambientale, Infrastrutture Viarie, Rilevamento, ICT Institute of Politecnico di Milano, University of Edinburgh, Boise State University, Coventry University, University of the Sunshine Coast (USC), Department of Civil and Environmental Engineering, Utah State University (USU), Department of Hydraulic Engineering, State Key Laboratory of Hydroscience and Engineering, Tsinghua University [Beijing], Wagenigen University, Utrecht Centre for Geosciences, Météo-France [Paris], Météo France, Department of Mathematical Sciences, Durham University, Princeton University, Ege Üniversitesi, Water and Climate Risk, Bloschl G., Bierkens M.F.P., Chambel A., Cudennec C., Destouni G., Fiori A., Kirchner J.W., McDonnell J.J., Savenije H.H.G., Sivapalan M., Stumpp C., Toth E., Volpi E., Carr G., Lupton C., Salinas J., Szeles B., Viglione A., Aksoy H., Allen S.T., Amin A., Andreassian V., Arheimer B., Aryal S.K., Baker V., Bardsley E., Barendrecht M.H., Bartosova A., Batelaan O., Berghuijs W.R., Beven K., Blume T., Bogaard T., Borges de Amorim P., Bottcher M.E., Boulet G., Breinl K., Brilly M., Brocca L., Buytaert W., Castellarin A., Castelletti A., Chen X., Chen Y., Chifflard P., Claps P., Clark M.P., Collins A.L., Croke B., Dathe A., David P.C., de Barros F.P.J., de Rooij G., Di Baldassarre G., Driscoll J.M., Duethmann D., Dwivedi R., Eris E., Farmer W.H., Feiccabrino J., Ferguson G., Ferrari E., Ferraris S., Fersch B., Finger D., Foglia L., Fowler K., Gartsman B., Gascoin S., Gaume E., Gelfan A., Geris J., Gharari S., Gleeson T., Glendell M., Gonzalez Bevacqua A., Gonzalez-Dugo M.P., Grimaldi S., Gupta A.B., Guse B., Han D., Hannah D., Harpold A., Haun S., Heal K., Helfricht K., Herrnegger M., Hipsey M., Hlavacikova H., Hohmann C., Holko L., Hopkinson C., Hrachowitz M., Illangasekare T.H., Inam A., Innocente C., Istanbulluoglu E., Jarihani B., Kalantari Z., Kalvans A., Khanal S., Khatami S., Kiesel J., Kirkby M., Knoben W., Kochanek K., Kohnova S., Kolechkina A., Krause S., Kreamer D., Kreibich H., Kunstmann H., Lange H., Liberato M.L.R., Lindquist E., Link T., Liu J., Loucks D.P., Luce C., Mahe G., Makarieva O., Malard J., Mashtayeva S., Maskey S., Mas-Pla J., Mavrova-Guirguinova M., Mazzoleni M., Mernild S., Misstear B.D., Montanari A., Muller-Thomy H., Nabizadeh A., Nardi F., Neale C., Nesterova N., Nurtaev B., Odongo V.O., Panda S., Pande S., Pang Z., Papacharalampous G., Perrin C., Pfister L., Pimentel R., Polo M.J., Post D., Prieto Sierra C., Ramos M.-H., Renner M., Reynolds J.E., Ridolfi E., Rigon R., Riva M., Robertson D.E., Rosso R., Roy T., Sa J.H.M., Salvadori G., Sandells M., Schaefli B., Schumann A., Scolobig A., Seibert J., Servat E., Shafiei M., Sharma A., Sidibe M., Sidle R.C., Skaugen T., Smith H., Spiessl S.M., Stein L., Steinsland I., Strasser U., Su B., Szolgay J., Tarboton D., Tauro F., Thirel G., Tian F., Tong R., Tussupova K., Tyralis H., Uijlenhoet R., van Beek R., van der Ent R.J., van der Ploeg M., Van Loon A.F., van Meerveld I., van Nooijen R., van Oel P.R., Vidal J.-P., von Freyberg J., Vorogushyn S., Wachniew P., Wade A.J., Ward P., Westerberg I.K., White C., Wood E.F., Woods R., Xu Z., Yilmaz K.K., Zhang Y., Vienna University of Technology (TU Wien), Institut National de la Recherche Agronomique (INRA)-AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Politecnico di Torino = Polytechnic of Turin (Polito), Istanbul Technical University (ITÜ), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Sun Yat-Sen University [Guangzhou] (SYSU), Department of Earth Sciences [Uppsala], Université Pierre et Marie Curie - Paris 6 (UPMC)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-MINES ParisTech - École nationale supérieure des mines de Paris, Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), Southern University of Science and Technology of China (SUSTech), Institut national des sciences de l'Univers (INSU - CNRS)-Institut de Recherche pour le Développement (IRD)-Université Montpellier 2 - Sciences et Techniques (UM2)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Alma Mater Studiorum Università di Bologna [Bologna] (UNIBO), Tsinghua University [Beijing] (THU), Austrian Science Fund (FWF) : DK W1219-N28, Institut de Recherche pour le Développement (IRD)-Université Montpellier 2 - Sciences et Techniques (UM2)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Università degli Studi Roma Tre = Roma Tre University (ROMA TRE), University of Bologna/Università di Bologna, Università degli Studi di Padova = University of Padua (Unipd), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Université Pierre et Marie Curie - Paris 6 (UPMC)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Mines Paris - PSL (École nationale supérieure des mines de Paris), Southern University of Science and Technology (SUSTech), University of Pennsylvania, Météo-France, Castellarin, A, Tækni- og verkfræðideild (HR), School of Science and Engineering (RU), Háskólinn í Reykjavík, Reykjavik University, Department of Water Resources, UT-I-ITC-WCC, Faculty of Geo-Information Science and Earth Observation, Bloschl, G., Bierkens, M. F. P., Chambel, A., Cudennec, C., Destouni, G., Fiori, A., Kirchner, J. W., Mcdonnell, J. J., Savenije, H. H. G., Sivapalan, M., Stumpp, C., Toth, E., Volpi, E., Carr, G., Lupton, C., Salinas, J., Szeles, B., Viglione, A., Aksoy, H., Allen, S. T., Amin, A., Andreassian, V., Arheimer, B., Aryal, S. K., Baker, V., Bardsley, E., Barendrecht, M. H., Bartosova, A., Batelaan, O., Berghuijs, W. R., Beven, K., Blume, T., Bogaard, T., Borges de Amorim, P., Bottcher, M. E., Boulet, G., Breinl, K., Brilly, M., Brocca, L., Buytaert, W., Castellarin, A., Castelletti, A., Chen, X., Chen, Y., Chifflard, P., Claps, P., Clark, M. P., Collins, A. L., Croke, B., Dathe, A., David, P. C., de Barros, F. P. J., de Rooij, G., Di Baldassarre, G., Driscoll, J. M., Duethmann, D., Dwivedi, R., Eris, E., Farmer, W. H., Feiccabrino, J., Ferguson, G., Ferrari, E., Ferraris, S., Fersch, B., Finger, D., Foglia, L., Fowler, K., Gartsman, B., Gascoin, S., Gaume, E., Gelfan, A., Geris, J., Gharari, S., Gleeson, T., Glendell, M., Gonzalez Bevacqua, A., Gonzalez-Dugo, M. P., Grimaldi, S., Gupta, A. B., Guse, B., Han, D., Hannah, D., Harpold, A., Haun, S., Heal, K., Helfricht, K., Herrnegger, M., Hipsey, M., Hlavacikova, H., Hohmann, C., Holko, L., Hopkinson, C., Hrachowitz, M., Illangasekare, T. H., Inam, A., Innocente, C., Istanbulluoglu, E., Jarihani, B., Kalantari, Z., Kalvans, A., Khanal, S., Khatami, S., Kiesel, J., Kirkby, M., Knoben, W., Kochanek, K., Kohnova, S., Kolechkina, A., Krause, S., Kreamer, D., Kreibich, H., Kunstmann, H., Lange, H., Liberato, M. L. R., Lindquist, E., Link, T., Liu, J., Loucks, D. P., Luce, C., Mahe, G., Makarieva, O., Malard, J., Mashtayeva, S., Maskey, S., Mas-Pla, J., Mavrova-Guirguinova, M., Mazzoleni, M., Mernild, S., Misstear, B. D., Montanari, A., Muller-Thomy, H., Nabizadeh, A., Nardi, F., Neale, C., Nesterova, N., Nurtaev, B., Odongo, V. O., Panda, S., Pande, S., Pang, Z., Papacharalampous, G., Perrin, C., Pfister, L., Pimentel, R., Polo, M. J., Post, D., Prieto Sierra, C., Ramos, M. -H., Renner, M., Reynolds, J. E., Ridolfi, E., Rigon, R., Riva, M., Robertson, D. E., Rosso, R., Roy, T., Sa, J. H. M., Salvadori, G., Sandells, M., Schaefli, B., Schumann, A., Scolobig, A., Seibert, J., Servat, E., Shafiei, M., Sharma, A., Sidibe, M., Sidle, R. C., Skaugen, T., Smith, H., Spiessl, S. M., Stein, L., Steinsland, I., Strasser, U., Su, B., Szolgay, J., Tarboton, D., Tauro, F., Thirel, G., Tian, F., Tong, R., Tussupova, K., Tyralis, H., Uijlenhoet, R., van Beek, R., van der Ent, R. J., van der Ploeg, M., Van Loon, A. F., van Meerveld, I., van Nooijen, R., van Oel, P. R., Vidal, J. -P., von Freyberg, J., Vorogushyn, S., Wachniew, P., Wade, A. J., Ward, P., Westerberg, I. K., White, C., Wood, E. F., Woods, R., Xu, Z., Yilmaz, K. K., Zhang, Y., Hydrologie, and Landscape functioning, Geocomputation and Hydrology

Subjects
hydrology, science questions, research agenda, interdisciplinary, knowledge gaps, 0208 environmental biotechnology, UT-Hybrid-D, WASS, hydrology, 02 engineering and technology, Oceanografi, hydrologi och vattenresurser, Hydrology and Quantitative Water Management, Oceanography, Hydrology and Water Resources, QE, Þekking, 910 Geography & travel, VDP::Matematikk og Naturvitenskap: 400::Geofag: 450::Hydrologi: 454, ComputingMilieux_MISCELLANEOUS, media_common, Water Science and Technology, knowledge gap, [SHS.SOCIO]Humanities and Social Sciences/Sociology, VDP::Landbruks- og Fiskerifag: 900, Hydroglogy, 6. Clean water, Justice and Strong Institutions, TA, Spite, science questions, Discipline, Hydrologie en Kwantitatief Waterbeheer, research agenda, knowledge gaps, interdisciplinary, SDG 16 - Peace, Process (engineering), media_common.quotation_subject, Hidrologia, Vatnafræði, Context (language use), Digital media, ITC-HYBRID, [SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology, Hydrology, WIMEK, business.industry, SDG 16 - Peace, Justice and Strong Institutions, Public consultation, Rannsóknir, 500 Science, Bodemfysica en Landbeheer, [SDE.ES]Environmental Sciences/Environmental and Society, Water Resources Management, 020801 environmental engineering, Soil Physics and Land Management, Socio-hydrology, ITC-ISI-JOURNAL-ARTICLE, Aðferðafræði, business, Diversity (politics)
Abstract

Publisher's version (útgefin grein), This paper is the outcome of a community initiative to identify major unsolved scientific problems in hydrology motivated by a need for stronger harmonisation of research efforts. The procedure involved a public consultation through online media, followed by two workshops through which a large number of potential science questions were collated, prioritised, and synthesised. In spite of the diversity of the participants (230 scientists in total), the process revealed much about community priorities and the state of our science: a preference for continuity in research questions rather than radical departures or redirections from past and current work. Questions remain focused on the process-based understanding of hydrological variability and causality at all space and time scales. Increased attention to environmental change drives a new emphasis on understanding how change propagates across interfaces within the hydrological system and across disciplinary boundaries. In particular, the expansion of the human footprint raises a new set of questions related to human interactions with nature and water cycle feedbacks in the context of complex water management problems. We hope that this reflection and synthesis of the 23 unsolved problems in hydrology will help guide research efforts for some years to come., We would like to thank the members of the IAHS, EGU, AGU and IAH for supporting this initiative. The LinkedIn group and overall secretariat was hosted by the IAHS, the Splinter meeting by EGU and the Vienna Catchment Science Symposium by the Vienna Doctoral Programme on Water Resource Systems (DK W1219-N28) funded by the Austrian Science Funds (FWF)., "Peer Reviewed"

Published
2019

34. Calibration of hydrological models using flow-duration curves

Author

José-Luis Guerrero, Ida Westerberg, Jim Freer, P. M. Younger, Keith Beven, Sven Halldin, Chong-Yu Xu, Jan Seibert, University of Zurich, and Westerberg, I K

Subjects
lcsh:GE1-350, Scale (ratio), lcsh:T, 1901 Earth and Planetary Sciences (miscellaneous), Hydrological modelling, Flow (psychology), lcsh:Geography. Anthropology. Recreation, Hydrograph, lcsh:Technology, lcsh:TD1-1066, Variable (computer science), 10122 Institute of Geography, 2312 Water Science and Technology, lcsh:G, Statistics, Calibration, Environmental science, Sensitivity (control systems), 910 Geography & travel, lcsh:Environmental technology. Sanitary engineering, GLUE, lcsh:Environmental sciences
Abstract

The degree of belief we have in predictions from hydrologic models will normally depend on how well they can reproduce observations. Calibrations with traditional performance measures, such as the Nash-Sutcliffe model efficiency, are challenged by problems including: (1) uncertain discharge data, (2) variable sensitivity of different performance measures to different flow magnitudes, (3) influence of unknown input/output errors and (4) inability to evaluate model performance when observation time periods for discharge and model input data do not overlap. This paper explores a calibration method using flow-duration curves (FDCs) to address these problems. The method focuses on reproducing the observed discharge frequency distribution rather than the exact hydrograph. It consists of applying limits of acceptability for selected evaluation points (EPs) on the observed uncertain FDC in the extended GLUE approach. Two ways of selecting the EPs were tested – based on equal intervals of discharge and of volume of water. The method was tested and compared to a calibration using the traditional model efficiency for the daily four-parameter WASMOD model in the Paso La Ceiba catchment in Honduras and for Dynamic TOPMODEL evaluated at an hourly time scale for the Brue catchment in Great Britain. The volume method of selecting EPs gave the best results in both catchments with better calibrated slow flow, recession and evaporation than the other criteria. Observed and simulated time series of uncertain discharges agreed better for this method both in calibration and prediction in both catchments. An advantage with the method is that the rejection criterion is based on an estimation of the uncertainty in discharge data and that the EPs of the FDC can be chosen to reflect the aims of the modelling application, e.g. using more/less EPs at high/low flows. While the method appears less sensitive to epistemic input/output errors than previous use of limits of acceptability applied directly to the time series of discharge, it still requires a reasonable representation of the distribution of inputs. Additional constraints might therefore be required in catchments subject to snow and where peak-flow timing at sub-daily time scales is of high importance. The results suggest that the calibration method can be useful when observation time periods for discharge and model input data do not overlap. The method could also be suitable for calibration to regional FDCs while taking uncertainties in the hydrological model and data into account.

Published
2011

35. A chromosome-level assembly of the seed beetle Callosobruchus maculatus genome with annotation of its repetitive elements.

Author

Arnqvist G, Westerberg I, Galbraith J, Sayadi A, Scofield DG, Olsen RA, Immonen E, Bonath F, Ewels P, and Suh A

Subjects
Animals, Genome, Repetitive Sequences, Nucleic Acid, X Chromosome, DNA Transposable Elements genetics, Phylogeny, Coleoptera genetics
Abstract

Callosobruchus maculatus is a major agricultural pest of legume crops worldwide and an established model system in ecology and evolution. Yet, current molecular biological resources for this species are limited. Here, we employ Hi-C sequencing to generate a greatly improved genome assembly and we annotate its repetitive elements in a dedicated in-depth effort where we manually curate and classify the most abundant unclassified repeat subfamilies. We present a scaffolded chromosome-level assembly, which is 1.01 Gb in total length with 86% being contained within the 9 autosomes and the X chromosome. Repetitive sequences accounted for 70% of the total assembly. DNA transposons covered 18% of the genome, with the most abundant superfamily being Tc1-Mariner (9.75% of the genome). This new chromosome-level genome assembly of C. maculatus will enable future genetic and evolutionary studies not only of this important species but of beetles more generally., Competing Interests: Conflicts of interest The authors declare that they have no conflicts of interest., (© The Author(s) 2023. Published by Oxford University Press on behalf of The Genetics Society of America.)

Published
2024
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36. Evolutionary dynamics of the LTR-retrotransposon crapaud in the Podospora anserina species complex and the interaction with repeat-induced point mutations.

Author

Westerberg I, Ament-Velásquez SL, Vogan AA, and Johannesson H

Abstract

Background: The genome of the filamentous ascomycete Podospora anserina shows a relatively high abundance of retrotransposons compared to other interspersed repeats. The LTR-retrotransposon family crapaud is particularly abundant in the genome, and consists of multiple diverged sequence variations specifically localized in the 5' half of both long terminal repeats (LTRs). P. anserina is part of a recently diverged species-complex, which makes the system ideal to classify the crapaud family based on the observed LTR variation and to study the evolutionary dynamics, such as the diversification and bursts of the elements over recent evolutionary time., Results: We developed a sequence similarity network approach to classify the crapaud repeats of seven genomes representing the P. anserina species complex into 14 subfamilies. This method does not utilize a consensus sequence, but instead it connects any copies that share enough sequence similarity over a set sequence coverage. Based on phylogenetic analyses, we found that the crapaud repeats likely diversified in the ancestor of the complex and have had activity at different time points for different subfamilies. Furthermore, while we hypothesized that the evolution into multiple subfamilies could have been a direct effect of escaping the genome defense system of repeat induced point mutations, we found this not to be the case., Conclusions: Our study contributes to the development of methods to classify transposable elements in fungi, and also highlights the intricate patterns of retrotransposon evolution over short timescales and under high mutational load caused by nucleotide-altering genome defense., (© 2024. The Author(s).)

Published
2024
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37. Genome-scale phylogeny and comparative genomics of the fungal order Sordariales.

Author

Hensen N, Bonometti L, Westerberg I, Brännström IO, Guillou S, Cros-Aarteil S, Calhoun S, Haridas S, Kuo A, Mondo S, Pangilinan J, Riley R, LaButti K, Andreopoulos B, Lipzen A, Chen C, Yan M, Daum C, Ng V, Clum A, Steindorff A, Ohm RA, Martin F, Silar P, Natvig DO, Lalanne C, Gautier V, Ament-Velásquez SL, Kruys Å, Hutchinson MI, Powell AJ, Barry K, Miller AN, Grigoriev IV, Debuchy R, Gladieux P, Hiltunen Thorén M, and Johannesson H

Subjects
Humans, Phylogeny, Genome, Base Sequence, Evolution, Molecular, Genomics methods, Sordariales genetics
Abstract

The order Sordariales is taxonomically diverse, and harbours many species with different lifestyles and large economic importance. Despite its importance, a robust genome-scale phylogeny, and associated comparative genomic analysis of the order is lacking. In this study, we examined whole-genome data from 99 Sordariales, including 52 newly sequenced genomes, and seven outgroup taxa. We inferred a comprehensive phylogeny that resolved several contentious relationships amongst families in the order, and cleared-up intrafamily relationships within the Podosporaceae. Extensive comparative genomics showed that genomes from the three largest families in the dataset (Chaetomiaceae, Podosporaceae and Sordariaceae) differ greatly in GC content, genome size, gene number, repeat percentage, evolutionary rate, and genome content affected by repeat-induced point mutations (RIP). All genomic traits showed phylogenetic signal, and ancestral state reconstruction revealed that the variation of the properties stems primarily from within-family evolution. Together, the results provide a thorough framework for understanding genome evolution in this important group of fungi., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Published
2023
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38. Economic assessment of a six-year project with extensive use of dental hygienists in the dental care of children: a pilot study.

Author

Hannerz H and Westerberg I

Subjects
Adolescent, Child, Cost-Benefit Analysis, DMF Index, Dental Caries economics, Dental Caries prevention & control, Dental Clinics economics, Female, Humans, Incidence, Longitudinal Studies, Male, Outcome Assessment, Health Care, Pilot Projects, Prevalence, Regression Analysis, Sweden, Dental Care for Children economics, Dental Hygienists economics
Abstract

The aim of the study was to assess the economic efficiency of an alternative division of labour based on an extensive use of dental hygienists combined with a reduced input of dentists. A test clinic was compared to a conventionally run public clinic in respect of dental and financial effects in the dental care of children. The study comprised 80 adolescents, born in 1975, in their 13th to 18th years. The assessment of economic efficiency was based on a cost/benefit analysis on the clinic level, in which the cost was defined as the difference between the test clinic and the control clinic in yearly running variable costs per child, and the benefit as the difference in the yearly caries increment multiplied by a value factor. The results showed statistically significant, lower caries incidence in the test group. Regression analyses, estimating a caries incidence function gave statistically significant explanation values for the variables "Caries prevalence" at 13 years of age' and 'Clinic'. The cost/benefit analysis showed a benefit/cost ratio of 1.48. The division of labour at the test clinic is discussed as a possible main factor for the outcome and suggests further experiments on a larger scale. The study can be regarded as a pilot, intended to be followed by a comprehensive study using a larger number of patients of different ages and more control clinics.

Published
1996

39. Influence of social factors on the effect of different prophylactic regimens.

Author

Faresjö T, Gamsäter G, Hamp SE, Nilsson T, and Westerberg I

Subjects
Adolescent, Dental Caries prevention & control, Dental Plaque prevention & control, Diet, Cariogenic, Educational Status, Female, Gingivitis prevention & control, Humans, Male, Sex Factors, Socioeconomic Factors, Sweden, Dental Prophylaxis
Published
1981

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