IAHS2022-456
https://doi.org/10.5194/iahs2022-456
IAHS-AISH Scientific Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Prediction in quantitative hydrological modelling: a small step away from uncertainty

Djigbo Félicien Badou1, Yacouba Yira3, and Jean Hounkpè2
Djigbo Félicien Badou et al.
  • 1Ecole d’Horticulture et d’Aménagement des espaces Verts, Université Nationale d’Agriculture, Kétou, Benin
  • 2Laboratoire d’Hydrologie Appliquée, Institut National de l’Eau, Université d’Abomey-Calavi, Abomey-Calavi, Benin
  • 3Applied Science and Technology Research Institute – IRSAT/CNRST, Ouagadougou, Burkina Faso

Water use planning is vital, making hydrological modelling crucial for the development of human society. This role of hydrological modelling is rendered even more prominent given current population growth and global warming resulting in more pressure on water resources. Nonetheless, most quantitative hydrological predictions remain fundamentally uncertain leading to uncertain water availability assessment. This is so, partly, because streamflow continues to be used as the main dependent variable, calibration and validation data length and content are arbitrarily selected, and water balance components taken individually are not quantified with the best prediction models. This paper discusses three ideas for stepping further away from uncertainty in quantitative hydrological predictions. Less uncertain hydrological predictions can be achieved through (i) blue water and green water-based hydrological models validation, (ii) blue water and green water-based multi-model evaluation of water resources, and (iii) a conditioned selection of calibration and validation data.

How to cite: Badou, D. F., Yira, Y., and Hounkpè, J.: Prediction in quantitative hydrological modelling: a small step away from uncertainty, IAHS-AISH Scientific Assembly 2022, Montpellier, France, 29 May–3 Jun 2022, IAHS2022-456, https://doi.org/10.5194/iahs2022-456, 2022.