Model diagnostics

that characterize the information contained in the data and in the models, and point toward the aspects of the model that need improvement. 

Recommended references

Pechlivanidis I.G., Crochemore L., Rosberg J., Bosshard T., 2020, 'What are the key drivers controlling the forecasts of seasonal streamflow volumes?', Water Resources Research, doi: 10.1029/2019WR026987

Pechlivanidis, I. G., McIntyre N., Wheater H. S., 2017, The significance of spatial variability of rainfall on simulated runoff: an evaluation based on the Upper Lee catchment, UK, Hydrol. Res., 1-13, doi:10.2166/nh.2016.038.

Nijzink R., Hutton C., Pechlivanidis I.G., Capell R., Arheimer B., Freer J., Han D., Wagener W., McGuire K., Savenije H., Hrachowitz M., 2016, 'The evolution of root-zone moisture capacities after deforestation: a step towards hydrological predictions under change?', Hydrol. Earth Syst. Sci., 20, 4775-4799, doi:10.5194/hess-20-4775-2016.

Pechlivanidis I.G., Jackson B., McMillan H., Gupta H., 2016, 'Robust informational entropy-based descriptors of flow in catchment hydrology', Hydrological Sciences Journal, 61(1), 1-18, doi: 10.1080/02626667.2014.983516

Pechlivanidis I.G., Arheimer, B., 2015, 'Large-scale hydrological modelling by using modified PUB recommendations: the India-HYPE case', Hydrol. Earth Syst. Sci., 19, 4559-4579, doi: 10.5194/hess-19-4559-2015

Andersson J.C.M., Pechlivanidis I.G., Gustafsson D., Donnelly C., Arheimer B., 2015, 'Key factors for improving large-scale hydrological model performance', European Water, 49, 77-88.

Pechlivanidis I.G., Jackson B., McMillan H., Gupta H., 2014, 'Use of an entropy-based metric in multi-objective calibration to improve model performance', Water Resources Research, 50, 8066-8083, doi: 10.1002/2013WR014537

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