Search Results - Zaherpour, Jamal

Improving global and catchment estimates of runoff through computationally-intelligent ensemble approaches Applications of intelligent multi-model combination, cross-scale model c... by Zaherpour, Jamal

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Exploring the value of machine learning for weighted multi-model combination of an ensemble of global hydrological models by Zaherpour, Jamal, Mount, Nick J., Gosling, Simon N., Dankers, Rutger, Eisner, Stephanie, Dieter, Gerten, Liu, Xingcai, Masaki, Yoshimitsu, Müller Schmied, Hannes, Tang, Qiuhong, Wada, Yoshihide

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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 by 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, Zhang, Xinxin

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Human impact parameterizations in global hydrological models improves estimates of monthly discharges and hydrological extremes: a multi-model validation study by 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, Wada, Y.

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Worldwide evaluation of mean and extreme runoff from six global-scale hydrological models that account for human impacts by 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, Wada, Yoshihide

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