EGU24-12211, updated on 09 Mar 2024
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Developing a national scale drought modelling and short to medium-term forecasting framework for Scotland

Shaini Naha1, Zisis Gagkas1, Nick Schurch2, Johan Strömqvist3, Alena Bartosova3, Kit Macleod1, and Miriam Glendell1
Shaini Naha et al.
  • 1The James Hutton Institute, Craigiebuckler, Aberdeen AB15 8QH, UK (
  • 2Biomathematics and Statistics Scotland, Aberdeen AB15 8QH, UK
  • 3Swedish Meteorological and Hydrological Institute, Norrköping, Sweden

Climate change is resulting in many countries including Scotland being increasingly vulnerable to periods of dry weather, impacting water users and the natural environment. In 2022, large parts of Scotland experienced water shortages, resulting in Scotland Environmental Protection Act (SEPA) suspending water abstractions for abstraction licence holders in some Scottish catchments. Managing these water scarcity events requires the development of a national-scale short- to medium- term drought forecasting capability. In this study, the applicability of widely used open source hydrological models for simulating low flows depends on how various hydrological processes are accounted for in the model structures, the use of diverse calibration criteria and analysis of the associated uncertainties. Currently, few studies exist that consider all these criteria for modelling low flow events. In this study, we choose a lumped conceptual model, GR6J and a semi distributed hydrological response unit-based model, HYPE, for simulating river discharge across 81 catchments in Scotland, used by SEPA to assess water scarcity events. Our modelling framework considered model structural uncertainties by using models of different complexities and model parametric uncertainties, through robust multi-objective model calibration. We first tested this framework on an experimental Scottish catchment where GR6J outperformed HYPE in simulating river discharge after automatic calibration against objective functions KGE and logNSE. Further, calibration against logNSE improved low flow simulation in both models. We then upscaled this methodology for 81 catchments using GR6J, resulting in overall a very good model performance in simulating river discharge in both calibration and validation period with KGE and logNSE ranging from 0.37-0.96 and 0.2-0.93 for 81 gauged catchments respectively. Our next task is to calibrate HYPE for these 81 catchments and use both calibrated models to derive an ensemble of short-term river flow forecasts using 5-days meteorological forecasts from the UK Met Office. Results in overall shall highlight the need for using ensemble of hydrological models and also indicate careful consideration of objective functions, while simulating and forecasting low flows.

How to cite: Naha, S., Gagkas, Z., Schurch, N., Strömqvist, J., Bartosova, A., Macleod, K., and Glendell, M.: Developing a national scale drought modelling and short to medium-term forecasting framework for Scotland, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12211,, 2024.