Exploring Signature‐Based Model Calibration for Streamflow Prediction in Ungauged Basins
暂无分享,去创建一个
[1] Jie Chen,et al. Evaluation of Eight Global Precipitation Datasets in Hydrological Modeling , 2021, Remote. Sens..
[2] D. Kavetski,et al. SuperflexPy 1.2.0: an open source Python framework for building, testing and improving conceptual hydrological models , 2020 .
[3] Dimitri Solomatine,et al. Improving AI System Awareness of Geoscience Knowledge: Symbiotic Integration of Physical Approaches and Deep Learning , 2020, Geophysical Research Letters.
[4] M. Zappa,et al. Understanding dominant controls on streamflow spatial variability to set up a semi-distributed hydrological model: the case study of the Thur catchment , 2020 .
[5] S. Hochreiter,et al. Toward Improved Predictions in Ungauged Basins: Exploiting the Power of Machine Learning , 2019, Water Resources Research.
[6] J. Refsgaard,et al. Using a simple post-processor to predict residual uncertainty for multiple hydrological model outputs , 2019, Advances in Water Resources.
[7] Dmitri Kavetski,et al. Flow Prediction in Ungauged Catchments Using Probabilistic Random Forests Regionalization and New Statistical Adequacy Tests , 2019, Water Resources Research.
[8] M. P. Clark,et al. A Ranking of Hydrological Signatures Based on Their Predictability in Space , 2018, Water Resources Research.
[9] P. Jones,et al. An Ensemble Version of the E‐OBS Temperature and Precipitation Data Sets , 2018, Journal of Geophysical Research: Atmospheres.
[10] Dmitri Kavetski,et al. Signature‐Domain Calibration of Hydrological Models Using Approximate Bayesian Computation: Theory and Comparison to Existing Applications , 2018, Water Resources Research.
[11] Dmitri Kavetski,et al. Signature‐Domain Calibration of Hydrological Models Using Approximate Bayesian Computation: Empirical Analysis of Fundamental Properties , 2018, Water Resources Research.
[12] Hubert H. G. Savenije,et al. Constraining Conceptual Hydrological Models With Multiple Information Sources , 2018, Water Resources Research.
[13] Pedro Luiz Borges Chaffe,et al. Extending the Applicability of the Generalized Likelihood Function for Zero‐Inflated Data Series , 2018 .
[14] Yuan Li,et al. Hydrologic model calibration using remotely sensed soil moisture and discharge measurements: The impact on predictions at gauged and ungauged locations , 2018 .
[15] Mario Schirmer,et al. What Do They Have in Common? Drivers of Streamflow Spatial Correlation and Prediction of Flow Regimes in Ungauged Locations , 2017 .
[16] I. Jung,et al. A comparative assessment of rainfall–runoff modelling against regional flow duration curves for ungauged catchments , 2017 .
[17] J. Seibert,et al. Prediction of hydrographs and flow-duration curves in almost ungauged catchments : Which runoff measurements are most informative for model calibration? , 2017 .
[18] Martyn P. Clark,et al. The CAMELS data set: catchment attributes and meteorology for large-sample studies , 2017 .
[19] Mario Schirmer,et al. Patterns of streamflow regimes along the river network: The case of the Thur river , 2017, Environ. Model. Softw..
[20] D. Biondi,et al. Rainfall-runoff model parameter conditioning on regional hydrological signatures: application to ungauged basins in southern Italy , 2017 .
[21] George Kuczera,et al. Improving probabilistic prediction of daily streamflow by identifying Pareto optimal approaches for modeling heteroscedastic residual errors , 2017 .
[22] Leonardo Alfonso,et al. Can assimilation of crowdsourced data in hydrological modelling improve flood prediction , 2017 .
[23] Graham W. Taylor,et al. Prediction of flow duration curves for ungauged basins , 2017 .
[24] Dmitri Kavetski,et al. From spatially variable streamflow to distributed hydrological models: Analysis of key modeling decisions , 2016 .
[25] Mario Schirmer,et al. Predicting streamflow distributions and flow duration curves from landscape and climate , 2015 .
[26] Wouter Buytaert,et al. Accounting for dependencies in regionalized signatures for predictions in ungauged catchments , 2015, Hydrology and Earth System Sciences.
[27] Bryan A. Tolson,et al. Optimizing hydrological consistency by incorporating hydrological signatures into model calibration objectives , 2015 .
[28] Thorsten Wagener,et al. Identifying dominant controls on hydrologic parameter transfer from gauged to ungauged catchments – A comparative hydrology approach , 2014 .
[29] J. Vrugt,et al. Approximate Bayesian Computation using Markov Chain Monte Carlo simulation: DREAM(ABC) , 2014 .
[30] George Kuczera,et al. Comparison of joint versus postprocessor approaches for hydrological uncertainty estimation accounting for error autocorrelation and heteroscedasticity , 2014 .
[31] R. Woods,et al. Comparing and combining physically-based and empirically-based approaches for estimating the hydrology of ungauged catchments , 2014 .
[32] Hubert H. G. Savenije,et al. Using expert knowledge to increase realism in environmental system models can dramatically reduce the need for calibration , 2013 .
[33] P. Whitfield,et al. A review of the Prediction in Ungauged Basins (PUB) decade in Canada , 2013 .
[34] J. Vrugt,et al. Toward diagnostic model calibration and evaluation: Approximate Bayesian computation , 2013 .
[35] J. McDonnell,et al. A decade of Predictions in Ungauged Basins (PUB)—a review , 2013 .
[36] Murugesu Sivapalan,et al. Comparative assessment of predictions in ungauged basins – Part 1: Runoff-hydrograph studies , 2013 .
[37] D. Boyle. Multicriteria Calibration of Hydrologic Models , 2013 .
[38] S. Bastola,et al. Calibration of hydrological models in ungauged basins based on satellite radar altimetry observations of river water level , 2012 .
[39] Hans R. Künsch,et al. A simulated annealing approach to approximate Bayes computations , 2012, Statistics and Computing.
[40] G. O'Donnell,et al. Integrating different types of information into hydrological model parameter estimation: Application to ungauged catchments and land use scenario analysis , 2012 .
[41] D. J. Nott,et al. Approximate Bayesian Computation and Bayes’ Linear Analysis: Toward High-Dimensional ABC , 2011, 1112.4755.
[42] Erwin Zehe,et al. A review of regionalisation for continuous streamflow simulation , 2011 .
[43] Dmitri Kavetski,et al. Elements of a flexible approach for conceptual hydrological modeling: 1. Motivation and theoretical development , 2011 .
[44] Howard Wheater,et al. Bayesian conditioning of a rainfall‐runoff model for predicting flows in ungauged catchments and under land use changes , 2011 .
[45] Keith Beven,et al. Calibration of hydrological models using flow-duration curves , 2010 .
[46] Attilio Castellarin,et al. Calibration of rainfall-runoff models in ungauged basins: A regional maximum likelihood approach , 2010 .
[47] J. Vrugt,et al. A formal likelihood function for parameter and predictive inference of hydrologic models with correlated, heteroscedastic, and non‐Gaussian errors , 2010 .
[48] B. Schaefli,et al. Signature-based model calibration for hydrological prediction in mesoscale Alpine catchments , 2010 .
[49] Xulin Guo,et al. Prediction of snowmelt derived streamflow in a wetland dominated prairie basin , 2010 .
[50] S. Attinger,et al. Multiscale parameter regionalization of a grid‐based hydrologic model at the mesoscale , 2010 .
[51] Hubert H. G. Savenije,et al. On the calibration of hydrological models in ungauged basins: A framework for integrating hard and soft hydrological information , 2009 .
[52] A. Montanari,et al. Prediction of low-flow indices in ungauged basins through physiographical space-based interpolation. , 2009 .
[53] A. Rinaldo,et al. Nonlinear storage‐discharge relations and catchment streamflow regimes , 2009 .
[54] N. Bulygina,et al. Conditioning rainfall-runoff model parameters for ungauged catchments and land management impacts analysis , 2009 .
[55] W. Bastiaanssen,et al. Constraining model parameters on remotely sensed evaporation: Justification for distribution in ungauged basins? , 2008 .
[56] Hoshin Vijai Gupta,et al. Regionalization of constraints on expected watershed response behavior for improved predictions in ungauged basins , 2007 .
[57] E. Toth,et al. Calibration of hydrological models in the spectral domain: An opportunity for scarcely gauged basins? , 2007 .
[58] George Kuczera,et al. Model smoothing strategies to remove microscale discontinuities and spurious secondary optima in objective functions in hydrological calibration , 2007 .
[59] Murugesu Sivapalan,et al. Pattern, Process and Function: Elements of a Unified Theory of Hydrology at the Catchment Scale , 2006 .
[60] Günter Blöschl,et al. Regionalisation of catchment model parameters , 2004 .
[61] P. E. O'connell,et al. IAHS Decade on Predictions in Ungauged Basins (PUB), 2003–2012: Shaping an exciting future for the hydrological sciences , 2003 .
[62] Dara Entekhabi,et al. Basin hydrologic response relations to distributed physiographic descriptors and climate , 2001 .
[63] Dennis P. Lettenmaier,et al. Development of regional parameter estimation equations for a macroscale hydrologic model , 1997 .
[64] S. Sorooshian,et al. Automatic calibration of conceptual rainfall-runoff models: The question of parameter observability and uniqueness , 1983 .
[65] D. Cox,et al. An Analysis of Transformations , 1964 .
[66] E. Toth,et al. Calibration of a rainfall–runoff model at regional scale by optimising river discharge statistics: Performance analysis for the average/low flow regime , 2012 .
[67] Philip Marsh,et al. Regionalisation of land surface hydrological model parameters in subarctic and arctic environments , 2008 .
[68] Pao-Shan Yu,et al. Using synthetic flow duration curves for rainfall–runoff model calibration at ungauged sites , 2000 .