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Zaherpour, Jamal, Mount, Nick J., Gosling, Simon N., Dankers, Rutger, Eisner, Stephanie, Dieter, Gerten, Liu, Xingcai, Masaki, Yoshimitsu, Müller Schmied, Hannes, 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, Gosling, Simon N., Mount, Nick J., Müller Schmied, Hannes, Veldkamp, Ted, Dankers, Rutger, Eisner, Stephanie, Gerten, Dieter, Gudmundsson, Lukas, Haddeland, I., Hanasaki, Naota, Kim, Hyungjun, Leng, Guoyong, Liu, Junguo, Masaki, Yoshimitsu, Oki, Taikan, Pokhrel, Yadu, Satoh, Yusuke, 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, Zhao, Fang, Ward, Philip J., Moel, Hans de, Aerts, Jeroen C.J.H., Müller Schmied, Hannes, Portmann, Felix T., Masaki, Yoshimitsu, Pokhrel, Yadu, Liu, Xingcai, Satoh, Yusuke, Gerten, Dieter, Gosling, Simon N., 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, Zaherpour, Jamal, Mount, Nick J., Hattermann, Fred, Dankers, Rutger, Arheimer, Berit, Breuer, Lutz, Ding, Jie, Haddeland, Ingjerd, Kumar, Rohini, Kundu, Dipangkar, Liu, Junguo, van Griensven, Ann, Veldkamp, Ted, Vetter, Tobias, 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.