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Number of items: 5.

Article

Zaherpour, Jamal and Mount, Nick J. and Gosling, Simon N. and Dankers, Rutger and Eisner, Stephanie and Dieter, Gerten and Liu, Xingcai and Masaki, Yoshimitsu and Müller Schmied, Hannes and Tang, Qiuhong and Wada, Yoshihide (2019) Exploring the value of machine learning for weighted multi-model combination of an ensemble of global hydrological models. Environmental Modelling and Software . ISSN 1873-6726 (In Press)

Zaherpour, Jamal and Gosling, Simon N. and Mount, Nick J. and Müller Schmied, Hannes and Veldkamp, Ted and Dankers, Rutger and Eisner, Stephanie and Gerten, Dieter and Gudmundsson, Lukas and Haddeland, I. and Hanasaki, Naota and Kim, Hyungjun and Leng, Guoyong and Liu, Junguo and Masaki, Yoshimitsu and Oki, Taikan and Pokhrel, Yadu and Satoh, Yusuke and Schewe, Jacob and Wada, Yoshihide (2018) Worldwide evaluation of mean and extreme runoff from six global-scale hydrological models that account for human impacts. Environmental Research Letters, 13 (6). 065015. ISSN 1748-9326

Veldkamp, Ted Isis Elize and Zhao, Fang and Ward, Philip J. and Moel, Hans de and Aerts, Jeroen C.J.H. and Müller Schmied, Hannes and Portmann, Felix T. and Masaki, Yoshimitsu and Pokhrel, Yadu and Liu, Xingcai and Satoh, Yusuke and Gerten, Dieter and Gosling, Simon N. and Zaherpour, Jamal and Wada, Y. (2018) Human impact parameterizations in global hydrological models improves estimates of monthly discharges and hydrological extremes: a multi-model validation study. Environmental Research Letters, 13 (5). 055008/1-055008/16. ISSN 1748-9326

Gosling, Simon and Zaherpour, Jamal and Mount, Nick J. and Hattermann, Fred and Dankers, Rutger and Arheimer, Berit and Breuer, Lutz and Ding, Jie and Haddeland, Ingjerd and Kumar, Rohini and Kundu, Dipangkar and Liu, Junguo and van Griensven, Ann and Veldkamp, Ted and Vetter, Tobias and Wang, Xiaoyan and Zhang, Xinxin (2016) A comparison of changes in river runoff from multiple global and catchment-scale hydrological models under global warming scenarios of 1°C, 2°C and 3°C. Climatic Change . ISSN 1573-1480

Thesis (University of Nottingham only)

Zaherpour, Jamal (2018) Improving global and catchment estimates of runoff through computationally-intelligent ensemble approaches Applications of intelligent multi-model combination, cross-scale model comparisons, ensemble analyses, and new model parameterisations. PhD thesis, University of Nottingham.

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