Articles | Volume 17, issue 7
https://doi.org/10.5194/hess-17-2669-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-17-2669-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
11 Jul 2013
Research article |
| 11 Jul 2013
Assessing the predictive capability of randomized tree-based ensembles in streamflow modelling
S. Galelli
Singapore-Delft Water Alliance, National University of Singapore 2 Engineering Drive 2, 117577, Singapore
A. Castelletti
Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano Piazza L. da Vinci, 32, 20133 Milano, Italy
Centre for Water Research, University of Western Australia, Crawley, Western Australia, Australia
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Related subject area
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Guofeng Zhu, Zhigang Sun, Yuanxiao Xu, Yuwei Liu, Zhuanxia Zhang, Liyuan Sang, and Lei Wang
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-75, https://doi.org/10.5194/hess-2022-75, 2022
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Wencong Yang, Hanbo Yang, Dawen Yang, and Aizhong Hou
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Weifei Yang, Changlai Xiao, Zhihao Zhang, and Xiujuan Liang
Hydrol. Earth Syst. Sci., 25, 1747–1760, https://doi.org/10.5194/hess-25-1747-2021, https://doi.org/10.5194/hess-25-1747-2021, 2021
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This study analyzed the effectiveness of the conductivity mass balance (CMB) method for correcting the Eckhardt method. The results showed that the approach of calibrating the Eckhardt method against the CMB method provides a
falsecalibration of total baseflow by offsetting the inherent biases in the baseflow sequences generated by the two methods. The reason for this phenomenon is the baseflow series generated by the two methods containing different transient water sources.
Juliane Mai, James R. Craig, and Bryan A. Tolson
Hydrol. Earth Syst. Sci., 24, 5835–5858, https://doi.org/10.5194/hess-24-5835-2020, https://doi.org/10.5194/hess-24-5835-2020, 2020
James W. Kirchner and Julia L. A. Knapp
Hydrol. Earth Syst. Sci., 24, 5539–5558, https://doi.org/10.5194/hess-24-5539-2020, https://doi.org/10.5194/hess-24-5539-2020, 2020
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Ensemble hydrograph separation is a powerful new tool for measuring the age distribution of streamwater. However, the calculations are complex and may be difficult for researchers to implement on their own. Here we present scripts that perform these calculations in either MATLAB or R so that researchers do not need to write their own codes. We explain how these scripts work and how to use them. We demonstrate several potential applications using a synthetic catchment data set.
Antoine Allam, Roger Moussa, Wajdi Najem, and Claude Bocquillon
Hydrol. Earth Syst. Sci., 24, 4503–4521, https://doi.org/10.5194/hess-24-4503-2020, https://doi.org/10.5194/hess-24-4503-2020, 2020
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With serious concerns about global change rising in the Mediterranean, we established a new climatic classification to follow hydrological and ecohydrological activities. The classification coincided with a geographical distribution ranging from the most seasonal and driest class in the south to the least seasonal and most humid in the north. RCM scenarios showed that northern classes evolve to southern ones with shorter humid seasons and earlier snowmelt which might affect hydrologic regimes.
Mingguo Zheng
Hydrol. Earth Syst. Sci., 24, 2365–2378, https://doi.org/10.5194/hess-24-2365-2020, https://doi.org/10.5194/hess-24-2365-2020, 2020
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This paper developed a mathematically precise method to partition climate and catchment effects on streamflow. The method reveals that both the change magnitude and pathway (timing of change), not the magnitude alone, dictate the partition unless for a linear system. The method has wide relevance. For example, it suggests that the global warming effect of carbon emission is path dependent, and an optimal pathway would facilitate a higher global budget of carbon emission.
José Manuel Tunqui Neira, Vazken Andréassian, Gaëlle Tallec, and Jean-Marie Mouchel
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This paper deals with the mathematical representation of concentration–discharge relationships. We propose a two-sided affine power scaling relationship (2S-APS) as an alternative to the classic one-sided power scaling relationship (commonly known as
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Hydrol. Earth Syst. Sci., 23, 4367–4388, https://doi.org/10.5194/hess-23-4367-2019, https://doi.org/10.5194/hess-23-4367-2019, 2019
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Hui-Min Wang, Jie Chen, Chong-Yu Xu, Hua Chen, Shenglian Guo, Ping Xie, and Xiangquan Li
Hydrol. Earth Syst. Sci., 23, 4033–4050, https://doi.org/10.5194/hess-23-4033-2019, https://doi.org/10.5194/hess-23-4033-2019, 2019
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When using large ensembles of global climate models in hydrological impact studies, there are pragmatic questions on whether it is necessary to weight climate models and how to weight them. We use eight methods to weight climate models straightforwardly, based on their performances in hydrological simulations, and investigate the influences of the assigned weights. This study concludes that using bias correction and equal weighting is likely viable and sufficient for hydrological impact studies.
Nathalie Folton, Eric Martin, Patrick Arnaud, Pierre L'Hermite, and Mathieu Tolsa
Hydrol. Earth Syst. Sci., 23, 2699–2714, https://doi.org/10.5194/hess-23-2699-2019, https://doi.org/10.5194/hess-23-2699-2019, 2019
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The long-term study of precipitation, flows, flood or drought mechanisms, in the Réal Collobrier research Watershed, located in South-East France, in the Mediterranean forest, improves knowledge of the water cycle and is unique tool for understanding of how catchments function. This study shows a small decrease in rainfall and a marked tendency towards a decrease in the water resources of the catchment in response to climate trends, with a consistent increase in drought severity and duration.
Vazken Andréassian and Tewfik Sari
Hydrol. Earth Syst. Sci., 23, 2339–2350, https://doi.org/10.5194/hess-23-2339-2019, https://doi.org/10.5194/hess-23-2339-2019, 2019
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In this Technical Note, we present two water balance formulas: the Turc–Mezentsev and Tixeront–Fu formulas. These formulas have a puzzling numerical similarity, which we discuss in detail and try to interpret mathematically and hydrologically.
Jan De Niel and Patrick Willems
Hydrol. Earth Syst. Sci., 23, 871–882, https://doi.org/10.5194/hess-23-871-2019, https://doi.org/10.5194/hess-23-871-2019, 2019
James W. Kirchner
Hydrol. Earth Syst. Sci., 23, 303–349, https://doi.org/10.5194/hess-23-303-2019, https://doi.org/10.5194/hess-23-303-2019, 2019
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How long does it take for raindrops to become streamflow? Here I propose a new approach to this old problem. I show how we can use time series of isotope data to measure the average fraction of same-day rainfall appearing in streamflow, even if this fraction varies greatly from rainstorm to rainstorm. I show that we can quantify how this fraction changes from small rainstorms to big ones, and from high flows to low flows, and how it changes with the lag time between rainfall and streamflow.
Ane Zabaleta, Eneko Garmendia, Petr Mariel, Ibon Tamayo, and Iñaki Antigüedad
Hydrol. Earth Syst. Sci., 22, 5227–5241, https://doi.org/10.5194/hess-22-5227-2018, https://doi.org/10.5194/hess-22-5227-2018, 2018
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This study establishes relationships between land cover and river discharge. Using discharge data from 20 catchments of the Bay of Biscay findings showed the influence of land cover on discharge changes with the amount of precipitation, with lower annual water resources associated with the greater presence of forests. Results obtained illustrate the relevance of land planning to the management of water resources and the opportunity to consider it in future climate-change adaptation strategies.
Dusan Jovanovic, Tijana Jovanovic, Alfonso Mejía, Jon Hathaway, and Edoardo Daly
Hydrol. Earth Syst. Sci., 22, 3551–3559, https://doi.org/10.5194/hess-22-3551-2018, https://doi.org/10.5194/hess-22-3551-2018, 2018
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A relationship between the Hurst (H) exponent (a long-term correlation coefficient) within a flow time series and various catchment characteristics for a number of catchments in the USA and Australia was investigated. A negative relationship with imperviousness was identified, which allowed for an efficient catchment classification, thus making the H exponent a useful metric to quantitatively assess the impact of catchment imperviousness on streamflow regime.
Chuanhao Wu, Bill X. Hu, Guoru Huang, Peng Wang, and Kai Xu
Hydrol. Earth Syst. Sci., 22, 1971–1991, https://doi.org/10.5194/hess-22-1971-2018, https://doi.org/10.5194/hess-22-1971-2018, 2018
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China has suffered some of the effects of global warming, and one of the potential implications of climate warming is the alteration of the temporal–spatial patterns of water resources. In this paper, the Budyko-based elasticity method was used to investigate the responses of runoff to historical and future climate variability over China at both grid and catchment scales. The results help to better understand the hydrological effects of climate change and adapt to a changing environment.
Samuel Saxe, Terri S. Hogue, and Lauren Hay
Hydrol. Earth Syst. Sci., 22, 1221–1237, https://doi.org/10.5194/hess-22-1221-2018, https://doi.org/10.5194/hess-22-1221-2018, 2018
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We investigate the impact of wildfire on watershed flow regimes, examining responses across the western United States. On a national scale, our results confirm the work of prior studies: that low, high, and peak flows typically increase following a wildfire. Regionally, results are more variable and sometimes contradictory. Our results may be significant in justifying the calibration of watershed models and in contributing to the overall observational analysis of post-fire streamflow response.
Annette Witt, Bruce D. Malamud, Clara Mangili, and Achim Brauer
Hydrol. Earth Syst. Sci., 21, 5547–5581, https://doi.org/10.5194/hess-21-5547-2017, https://doi.org/10.5194/hess-21-5547-2017, 2017
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Here we present a unique 9.5 m palaeo-lacustrine record of 771 palaeofloods which occurred over a period of 10 000 years in the Piànico–Sèllere basin (southern Alps) during an interglacial period in the Pleistocene (sometime between 400 000 and 800 000 years ago). We analyse the palaeoflood series correlation, clustering, and cyclicity properties, finding a long-range cyclicity with a period of about 2030 years superimposed onto a fractional noise.
Steve J. Birkinshaw, Selma B. Guerreiro, Alex Nicholson, Qiuhua Liang, Paul Quinn, Lili Zhang, Bin He, Junxian Yin, and Hayley J. Fowler
Hydrol. Earth Syst. Sci., 21, 1911–1927, https://doi.org/10.5194/hess-21-1911-2017, https://doi.org/10.5194/hess-21-1911-2017, 2017
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The Yangtze River basin in China is home to more than 400 million people and susceptible to major floods. We used projections of future precipitation and temperature from 35 of the most recent global climate models and applied this to a hydrological model of the Yangtze. Changes in the annual discharge varied between a 29.8 % decrease and a 16.0 % increase. The main reason for the difference between the models was the predicted expansion of the summer monsoon north and and west into the basin.
Maurizio Mazzoleni, Martin Verlaan, Leonardo Alfonso, Martina Monego, Daniele Norbiato, Miche Ferri, and Dimitri P. Solomatine
Hydrol. Earth Syst. Sci., 21, 839–861, https://doi.org/10.5194/hess-21-839-2017, https://doi.org/10.5194/hess-21-839-2017, 2017
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This study assesses the potential use of crowdsourced data in hydrological modeling, which are characterized by irregular availability and variable accuracy. We show that even data with these characteristics can improve flood prediction if properly integrated into hydrological models. This study provides technological support to citizen observatories of water, in which citizens can play an active role in capturing information, leading to improved model forecasts and better flood management.
Martin Durocher, Fateh Chebana, and Taha B. M. J. Ouarda
Hydrol. Earth Syst. Sci., 20, 4717–4729, https://doi.org/10.5194/hess-20-4717-2016, https://doi.org/10.5194/hess-20-4717-2016, 2016
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For regional flood frequency, it is challenging to identify regions with similar hydrological properties. Therefore, previous works have mainly proposed to use regions with similar physiographical properties. This research proposes instead to nonlinearly predict the desired hydrological properties before using them for delineation. The presented method is applied to a case study in Québec, Canada, and leads to hydrologically relevant regions, while enhancing predictions made inside them.
Donghua Zhang, Henrik Madsen, Marc E. Ridler, Jacob Kidmose, Karsten H. Jensen, and Jens C. Refsgaard
Hydrol. Earth Syst. Sci., 20, 4341–4357, https://doi.org/10.5194/hess-20-4341-2016, https://doi.org/10.5194/hess-20-4341-2016, 2016
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We present a method to assimilate observed groundwater head and soil moisture profiles into an integrated hydrological model. The study uses the ensemble transform Kalman filter method and the MIKE SHE hydrological model code. The proposed method is shown to be more robust and provide better results for two cases in Denmark, and is also validated using real data. The hydrological model with assimilation overall improved performance compared to the model without assimilation.
Morgan Fonley, Ricardo Mantilla, Scott J. Small, and Rodica Curtu
Hydrol. Earth Syst. Sci., 20, 2899–2912, https://doi.org/10.5194/hess-20-2899-2016, https://doi.org/10.5194/hess-20-2899-2016, 2016
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We design and implement a theoretical experiment to show that, under low-flow conditions, observed streamflow discrepancies between early and late summer can be attributed to different flow velocities in the river network. By developing an analytic solution to represent flow along a given river network, we emphasize the dependence of streamflow amplitude and time delay on the geomorphology of the network. We also simulate using a realistic river network to highlight the effects of scale.
Zhongwei Huang, Hanbo Yang, and Dawen Yang
Hydrol. Earth Syst. Sci., 20, 2573–2587, https://doi.org/10.5194/hess-20-2573-2016, https://doi.org/10.5194/hess-20-2573-2016, 2016
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The hydrologic processes have been influenced by different climatic factors. However, the dominant climatic factor driving annual runoff change is still unknown in many catchments in China. By using the climate elasticity method proposed by Yang and Yang (2011), the elasticity of runoff to climatic factors was estimated, and the dominant climatic factors driving annual runoff change were detected at catchment scale over China.
Jørn Rasmussen, Henrik Madsen, Karsten Høgh Jensen, and Jens Christian Refsgaard
Hydrol. Earth Syst. Sci., 20, 2103–2118, https://doi.org/10.5194/hess-20-2103-2016, https://doi.org/10.5194/hess-20-2103-2016, 2016
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In the paper, observations are assimilated into a hydrological model in order to improve the model performance. Two methods for detecting and correcting systematic errors (bias) in groundwater head observations are used leading to improved results compared to standard assimilation methods which ignores any bias. This is demonstrated using both synthetic (user generated) observations and real-world observations.
Mohammed Achite and Sylvain Ouillon
Hydrol. Earth Syst. Sci., 20, 1355–1372, https://doi.org/10.5194/hess-20-1355-2016, https://doi.org/10.5194/hess-20-1355-2016, 2016
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Changes of T, P, Q and sediment fluxes in a semi-arid basin little affected by human activities are analyzed from 40 years of measurements. T increased, P decreased, an earlier onset of first summer rains occurred. The flow regime shifted from perennial to intermittent. Sediment flux almost doubled every decade. The sediment regime shifted from two equivalent seasons of sediment delivery to a single major season regime. The C–Q rating curve ability declined due to enhanced hysteresis effects.
C. E. M. Lloyd, J. E. Freer, P. J. Johnes, and A. L. Collins
Hydrol. Earth Syst. Sci., 20, 625–632, https://doi.org/10.5194/hess-20-625-2016, https://doi.org/10.5194/hess-20-625-2016, 2016
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This paper examines the current methodologies for quantifying storm behaviour through hysteresis analysis, and explores a new method. Each method is systematically tested and the impact on the results is examined. Recommendations are made regarding the most effective method of calculating a hysteresis index. This new method allows storm hysteresis behaviour to be directly compared between storms, parameters, and catchments, meaning it has wide application potential in water quality research.
W. Hu and B. C. Si
Hydrol. Earth Syst. Sci., 20, 571–587, https://doi.org/10.5194/hess-20-571-2016, https://doi.org/10.5194/hess-20-571-2016, 2016
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Spatiotemporal SWC was decomposed into into three terms (spatial forcing, temporal forcing, and interactions between spatial and temporal forcing) for near surface and root zone; Empirical orthogonal function indicated that underlying patterns exist in the interaction term at small watershed scales; Estimation of spatially distributed SWC benefits from decomposition of the interaction term; The suggested decomposition of SWC with time stability analysis has potential in SWC downscaling.
Y. Chen, J. Li, and H. Xu
Hydrol. Earth Syst. Sci., 20, 375–392, https://doi.org/10.5194/hess-20-375-2016, https://doi.org/10.5194/hess-20-375-2016, 2016
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Parameter optimization is necessary to improve the flood forecasting capability of physically based distributed hydrological model. A method for parameter optimization with particle swam optimization (PSO) algorithm has been proposed for physically based distributed hydrological model in catchment flood forecasting and validated in southern China. It has found that the appropriate particle number and maximum evolution number of PSO algorithm are 20 and 30 respectively.
D. Hawtree, J. P. Nunes, J. J. Keizer, R. Jacinto, J. Santos, M. E. Rial-Rivas, A.-K. Boulet, F. Tavares-Wahren, and K.-H. Feger
Hydrol. Earth Syst. Sci., 19, 3033–3045, https://doi.org/10.5194/hess-19-3033-2015, https://doi.org/10.5194/hess-19-3033-2015, 2015
J. Rasmussen, H. Madsen, K. H. Jensen, and J. C. Refsgaard
Hydrol. Earth Syst. Sci., 19, 2999–3013, https://doi.org/10.5194/hess-19-2999-2015, https://doi.org/10.5194/hess-19-2999-2015, 2015
C. Kormann, T. Francke, M. Renner, and A. Bronstert
Hydrol. Earth Syst. Sci., 19, 1225–1245, https://doi.org/10.5194/hess-19-1225-2015, https://doi.org/10.5194/hess-19-1225-2015, 2015
S. Gharari, M. Shafiei, M. Hrachowitz, R. Kumar, F. Fenicia, H. V. Gupta, and H. H. G. Savenije
Hydrol. Earth Syst. Sci., 18, 4861–4870, https://doi.org/10.5194/hess-18-4861-2014, https://doi.org/10.5194/hess-18-4861-2014, 2014
S. G. Leibowitz, R. L. Comeleo, P. J. Wigington Jr., C. P. Weaver, P. E. Morefield, E. A. Sproles, and J. L. Ebersole
Hydrol. Earth Syst. Sci., 18, 3367–3392, https://doi.org/10.5194/hess-18-3367-2014, https://doi.org/10.5194/hess-18-3367-2014, 2014
J. Niu, J. Chen, and B. Sivakumar
Hydrol. Earth Syst. Sci., 18, 1475–1492, https://doi.org/10.5194/hess-18-1475-2014, https://doi.org/10.5194/hess-18-1475-2014, 2014
K. Rasouli, M. A. Hernández-Henríquez, and S. J. Déry
Hydrol. Earth Syst. Sci., 17, 1681–1691, https://doi.org/10.5194/hess-17-1681-2013, https://doi.org/10.5194/hess-17-1681-2013, 2013
M. Nied, Y. Hundecha, and B. Merz
Hydrol. Earth Syst. Sci., 17, 1401–1414, https://doi.org/10.5194/hess-17-1401-2013, https://doi.org/10.5194/hess-17-1401-2013, 2013
B. Gräler, M. J. van den Berg, S. Vandenberghe, A. Petroselli, S. Grimaldi, B. De Baets, and N. E. C. Verhoest
Hydrol. Earth Syst. Sci., 17, 1281–1296, https://doi.org/10.5194/hess-17-1281-2013, https://doi.org/10.5194/hess-17-1281-2013, 2013
P. Gao, V. Geissen, C. J. Ritsema, X.-M. Mu, and F. Wang
Hydrol. Earth Syst. Sci., 17, 961–972, https://doi.org/10.5194/hess-17-961-2013, https://doi.org/10.5194/hess-17-961-2013, 2013
Cited articles
Babovic, V. and Keijzer, M.: Rainfall-runoff modeling based on genetic programming, Nord. Hydrol., 5, 331–346, 2002.
Bachmair, S. and Weiler, M.: Hillslope characteristics as controls of subsurface flow variability, Hydrol. Earth Syst. Sci., 16, 3699–3715, https://doi.org/10.5194/hess-16-3699-2012, 2012.
Beck, M.: Forecasting environmental change, J. Forecast., 10, 3–19, 1991.
Beven, K.: How far can we go in distributed hydrological modelling?, Hydrol. Earth Syst. Sci., 5, 1–12, https://doi.org/10.5194/hess-5-1-2001, 2001.
Bhattacharya, B. and Solomatine, D.: Neural networks and M5 model trees in modelling water level-discharge relationship, Neurocomputing, 63, 381–396, 2005.
Box, G. E. P., Hunter, J. S., and Hunter, W. G.: Statistics for Experimenters: Design, Innovation, and Discovery, 2nd Edition, Wiley, New York, USA, 2005.
Breiman, L.: Bagging predictors, Mach. Learn., 24, 123–140, 1996.
Breiman, L.: Random forests, Mach. Learn., 45, 5–32, 2001.
Breiman, L., Friedman, J., Olsen, R., and Stone, C.: Classification and Regression Trees, Wadsworth & Brooks, Pacific Grove, CA, 1984.
Castelletti, A., Galelli, S., Restelli, M., and Soncini-Sessa, R.: Tree-based reinforcement learning for optimal water reservoir operation, Water Resour. Res., 46, W09507, https://doi.org/10.1029/2009WR008898, 2010.
Cutler, A. and Guohua, Z.: PERT – Perfect Random Trees Ensembles, Comp. Sci. Stat., 33, 490–497, 2001.
Dawson, C., Brown, M., and Wilby, R.: Inductive learning approaches to rainfall-runoff modelling, Int. J. Neural Syst., 10, 43–57, 2000.
Dietterich, T.: Ensemble methods in machine learning, Lect. Notes Comput Sc., 1857, 1–15, 2000.
Elshorbagy, A., Corzo, G., Srinivasulu, S., and Solomatine, D. P.: Experimental investigation of the predictive capabilities of data driven modeling techniques in hydrology –Part 1: Concepts and methodology, Hydrol. Earth Syst. Sci., 14, 1931–1941, https://doi.org/10.5194/hess-14-1931-2010, 2010a.
Elshorbagy, A., Corzo, G., Srinivasulu, S., and Solomatine, D. P.: Experimental investigation of the predictive capabilities of data driven modeling techniques in hydrology –Part 2: Application, Hydrol. Earth Syst. Sci., 14, 1943-1961, https://doi.org/10.5194/hess-14-1943-2010, 201b.
Erdal, H. and Karakurt, O.: Advancing monthly streamflow prediction accuracy of CART models using ensemble learning paradigms, J. Hydrol., 477, 119–128, 2013.
Fonteneau, R., Wehenkel, L., and Ernst, D.: Variable selection for dynamic treatment regimes: a reinforcement learning approach, in: Proceedings of the European Workshop on Reinforcement Learning, 30 June–4 July 2008, Villeneuve d'Ascq, France, 2008.
Freund, Y. and Schapire, R.: Experiments with a new boosting algorithm, in: Proceedings of 13th International Conference on Mach. Learn., 3–6 July 1996, Bari, Italy, 148–146, 1996.
Galelli, S., Goedbloed, A., Schwanenberg, D., and van Overloop, D.: Optimal real-time operation of multi-purpose urban reservoirs: a case study in Singapore, J. Water Res. Pl.-ASCE, https://doi.org/10.1061/(ASCE)WR.1943-5452.0000342, in press, 2013.
Geurts, P.: Contributions to Decision Tree Induction: Bias/Variance Tradeoff and Time Series Classification, Ph.D. thesis, University of Liège, Liège, Belgium, 2002.
Geurts, P., Ernst, D., and Wehenkel, L.: Extremely randomized trees, Mach. Learn., 63, 3–42, 2006.
Hejazi, M. and Cai, X.: Input variable selection for water resources systems using a modified minimum redundancy maximum relevance (mMRMR) algorithm, Adv. Water Resour., 32, 582–593, 2009.
Ho, T.: Random decision forests, in: Proceedings of the Third International Conference on Document Analysis and Recognition, Vol. 1, ontreal, Quebec, 278–282, 1995.
Ho, T.: The random subspace method for constructing decision forests, IEEE T. Pattern Anal., 20, 832–844, 1998.
Hsu, K., Gupta, H., and Sorooshian, S.: Artificial neural-network modeling of the rainfall-runoff process, Water Resour. Res., 31, 2517–2530, 1995.
Hundecha, Y., Bardossy, A., and Theisen, H.: Development of a fuzzy logic-based rainfall-runoff model, Hydrolog. Sci. J., 46, 363–376, 2001.
Hwang, S., Ham, D., and Kim, J.: A new measure for assessing the efficiency of hydrological data-driven forecasting models, Hydrolog. Sci. J., 57, 1–18, 2012.
Hyafil, L. and Rivest, R.: Constructing optimal binary decision trees in NP-Complete, Inform. Process. Lett., 5, 15–17, 1976.
Iorgulescu, I. and Beven, K.: Nonparametric direct mapping of rainfall-runoff relationships: an alternative approach to data analysis and modeling?, Water Resour. Res., 40, W08403, https://doi.org/10.1029/2004WR003094, 2004.
Jakeman, A. and Hornberger, G.: How much complexity is warranted in a rainfall-runoff model, Water Resour. Res., 29, 2637–2649, 1993.
Jekabsons, G.: M5PrimeLab – M5' Regression Tree and Model Tree Toolbox for Matlab/Octave, Technical Report ver. 1.0.1, Faculty of Computer Science and Information Technology – Riga Technical University, Riga, Latvia, 2010.
Jong, K., Mary, J., Cornuéjols, A., Marchiori, E., and Sebag, M.: Ensemble feature ranking, in: Knowledge Discovery in Databases, Springer, 267–278, 2004.
Jothiprakash, V. and Kote, A.: Effect of pruning and smoothing while using M5 model tree technique for reservoir inflow prediction, J. Hydrol. Eng., 16, 563–574, 2011.
Kuncheva, L. and Whitaker, C.: Measures of diversity in classifier ensembles and their relationship with the ensemble accuracy, Mach. Learn., 51, 181–207, 2003.
Laaha, G. and Blöschl, G.: A comparison of low flow regionalisation methods – catchment grouping, J. Hydrol., 323, 193–214, 2006.
Lin, J.-Y., Cheng, C.-T., and Chau, K.-W.: Using support vector machines for long-term discharge prediction, Hydrolog. Sci. J., 51, 599–612, 2006.
Maier, H. and Dandy, G.: Neural networks for the prediction and forecasting of water resources variables: a review of modelling issues and applications, Environ. Model. Softw., 15, 101–124, 2000.
Quinlan, J.: Learning with continuous classes, in: Proceedings of the 5th Australian Joint Conference on Artificial Intelligence, 16–18 November, Hobart, Australia, 343–348, 1992.
Rasmussen, P., Salas, J., Fagherazzi, L., Rassam, J., and Bobee, B.: Estimation and validation of contemporaneous PARMA models for streamflow simulation, Water Resour. Res., 32, 3151–3160, 1996.
Romanowicz, R., Young, P., Beven, K., and Pappenberger, F.: A data based mechanistic approach to nonlinear flood routing and adaptive flood level forecasting, Adv. Water Resour., 31, 1048–1056, 2008.
Sauquet, E. and Catalogne, C.: Comparison of catchment grouping methods for flow duration curve estimation at ungauged sites in France, Hydrol. Earth Syst. Sci., 15, 2421–2435, https://doi.org/10.5194/hess-15-2421-2011, 2011.
See, L., Jain, A., Dawson, C., and Abrahart, R.: Visualisation of hidden neuron behaviour in a neural network rainfall-runoff model, in: Practical Hydroinformatics, vol. 68 of Water Science and Technology Library, edited by: Abrahart, R., See, L., and Solomatine, D., Springer, Berlin, Heidelberg, 87–99, 2008.
Selvalingam, S., Liong, S., and Manoharan, P.: Use of RORB and SWMM models to an urban catchment in Singapore, Adv. Water Resour., 10, 78–86, 1987.
Shamseldin, A. Y., Nasr, A. E., and O'Connor, K. M.: Comparison of different forms of the Multi-layer Feed-Forward Neural Network method used for river flow forecasting, Hydrol. Earth Syst. Sci., 6, 671–684, https://doi.org/10.5194/hess-6-671-2002, 2002.
Snelder, T., Lamouroux, N., Leathwick, J., Pella, H., Sauquet, E., and Shankar, U.: Predictive mapping of the natural flow regimes of France, J. Hydrol., 373, 57–67, 2009.
Solomatine, D. and Dulal, K.: Model trees as an alternative to neural networks in rainfall-runoff modelling, Hydrolog. Sci. J., 48, 399–411, 2003.
Solomatine, D. and Ostfeld, A.: Data-driven modelling: some past experiences and new approaches, J. Hydroinform., 10, 3–22, 2008.
Solomatine, D. and Xue, Y.: M5 model trees compared to neural networks: application to flood forecasting in the upper reach of the Huai River in China, J. Hydrol. Eng., 9, 491–501, 2004.
Stravs, L. and Brilly, M.: Development of a low-flow forecasting model using the M5 machine learning method, Hydrolog. Sci. J., 52, 466–477, 2007.
Vezza, P., Comoglio, C., Rosso, M., and Viglione, A.: low flows regionalization in North-Western Italy, Water Resour. Manage., 24, 4049–4074, 2010.
Wang, Y. and Witten, I.: Induction of model trees for predicting continuous classes, in: Proceedings of the European Conference on Mach. Learn., Prague, Czech Republic, 128–137, 1997.
Wehenkel, L.: Automatic Learning Techniques in Power Systems, Kluwer Academic, Boston, USA, 1998.
Wei, W. and Watkins Jr., D.: Data mining methods for hydroclimatic forecasting, Adv. Water Resour., 34, 1390–1400, 2011.
Wheater, H., Jakeman, A., and Beven, K.: Progress and Directions in Rainfall-Runoff Modelling, John Wiley, Chichester, 101–132, 1993.
Xie, J.: Dealing with Water Scarcity in Singapore: Institutions, Strategies, and Enforcement, China: Addressing Water Scarcity Background Paper No. 4, The World Bank – Environment and Social Development Department – East Asia and Pacific Region, Washington, DC, available at: http://www.worldbank.org/eapenvironment/ChinaWaterAAA (last access: 15 January 2013), 2006.
Young, P.: Data-based mechanistic and top-down modelling, in: Proceedings of the First Biennial Meeting of the International Environmental Modelling & Software Society, Vol. I, Lugano, Suisse, 363–374, 2002.
Young, P.: Top-down and data-based mechanistic modelling of rainfall–flow dynamics at the catchment scale, Hydrol. Process., 17, 2195–2217, 2003.
Young, P.: Rainfall-Runoff Modeling: Transfer Function Models, John Wiley & Sons, Ltd, 2006.
Young, P.: Hypothetico-inductive data-based mechanistic modeling of hydrological systems, Water Resour. Res., 49, 915–935, 2013.
Young, P. and Beven, K.: Data-based mechanistic modeling and the rainfall-flow nonlinearity, Environmetrics, 3, 335–363, 1994.
Young, P., Jakeman, A., and Post, D.: Recent advances in the data-based modelling and analysis of hydrological systems, Water Sci. Technol., 36, 99–116, 1997.
