17 Feb 2023
 | 17 Feb 2023
Status: a revised version of this preprint is currently under review for the journal NHESS.

Seasonal forecasting of local-scale soil moisture droughts with Global BROOK90

Ivan Vorobevskii, Thi Thanh Luong, and Rico Kronenberg

Abstract. Prolonged deficit of soil moisture can result in significant ecosystem and economical losses. General slowdown of vegetation growth and development, withering of foliage cover, reduction of carbon, nutrient and water cycling, increase of fire and insect outbreaks are just a few examples of soil moisture drought impacts. Thus, an early and timely warning via monitoring and forecast could help to prepare for the drought and manage its consequences.

In the study, a new version of Global BROOK90, an automated framework to simulate water balance at any location is presented. The new framework integrates seasonal meteorological forecasts from European Centre for Medium-Range Weather Forecasts (ECMWF). Here we studied how well the framework can predict the soil moisture drought on a local scale. Twelve small European catchments (from 7 to 115 km2) characterised by various geographical conditions were chosen to reconstruct the 2018–2019 period, when a large-scale prolonged drought was observed in Europe. Setting the ERA5-forced soil moisture simulations as a reference, we analysed how the lead time of the ECMWF hindcasts influences the quality of the soil moisture predictions under drought and non-drought conditions.

It was found that the hindcasted soil moisture fits well with the reference model runs only within the first (in some cases until second and third) month of lead time. Afterwards significant deviations up to 50 % of soil water volume were found. Furthermore, within the drought period the ECMWF hindcast forcing resulted in overestimation of the soil moisture for most of the catchment, indicating an earlier end of a drought period. Finally, it was shown that application of the probabilistic forecast using the ensembles’ quantiles to account for the uncertainty of the meteorological input is reasonable only for short-to-medium range lead times (up to three months).

Ivan Vorobevskii et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on nhess-2023-9', Anonymous Referee #1, 04 Apr 2023
    • AC1: 'Reply on RC1', Ivan Vorobevskii, 12 May 2023
  • RC2: 'Comment on nhess-2023-9', Anonymous Referee #2, 04 May 2023
    • AC2: 'Reply on RC2', Ivan Vorobevskii, 12 May 2023

Ivan Vorobevskii et al.

Ivan Vorobevskii et al.


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Short summary
The study presents a new version of a framework which allow to model water balance components at any site for a local scale. In comparison to the first version, the second one incorporates new datasets used to setup and force the model. In particular, we want to highlight the ability of the framework to provide seasonal forecasts. This gives the potential stakeholders (farmers, foresters, policymakers etc.) possibility to forecast e.g. soil moisture drought and thus apply necessary measures.