| 02 Oct 2025
Drought propagation in the Rhine River basin and its impact on navigation using LAERTES-EU regional climate model dataset
Abstract. Drought events have become more frequent in Europe over the past decades. The shipping and industrial sectors are severely affected by these events, e.g., due to significant reductions in water levels in the Rhine River and interruptions in the transport of goods. Hydrological droughts in the Rhine closely resemble extreme meteorological droughts identified using the Standardized Precipitation Evapotranspiration Index (SPEI) over both short and long periods. However, the possibility of determining low water level events using non-observed meteorological data, e.g., from large regional climate model datasets, and their implication on navigation has not yet been explored. The main objective of this study is to utilize the Large Ensemble of Regional Climate Model Simulations for Europe (LAERTES-EU) to search for extreme drought years, to assess their contribution to discharge, and to determine possible navigation restrictions on the waterways in the Rhine. We employed a methodology that evaluates the SPEI values to identify meteorological drought, which are then used to obtain discharge values by applying the hydrological model WRF-Hydro. The top 10 most extreme meteorological drought events in the LAERTES-EU dataset are considered in this study, assessing drought propagation by using the SPEI. These events displayed different degrees of severity in terms of duration and reduction of the streamflow as measured by the navigable threshold GlQ20 than the extreme drought observed in 2018. In the selected gauges, several LAERTES-EU events were ranked above 2018 when comparing them with the historical records in terms of mean discharge of the period June–November. These results imply that, even under today's climatic conditions, the streamflow values in the Rhine can be substantially worse than in 2018, generating costly economic and ecological consequences if mitigation measures are not implemented.
Competing interests: At least one of the (co-)authors is a member of the editorial board of Natural Hazards and Earth System Sciences
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Evaluation of "Drought propagation in the Rhine River basin and its impact on navigation using the LAERTES-EU regional climate model dataset."
This study assessed hydrological droughts in the Rhine basin using model output simulations and a hydrological model. The purpose was to evaluate the ability of atmospheric drought indices to capture hydrological drought variability across the large Rhine basin. Although the topic of the proposal is of great scientific and applied management interest, I identify significant data and methodological issues. The focus of the project is not clearly defined, and there are substantial uncertainties in the experimental design—particularly regarding the hydrological modelling, which is poorly detailed, the use of model outputs, and their comparability with observations. Moreover, the manuscript lacks a meaningful discussion section. Further details on methodological uncertainties are provided below.
Line 145. The method used to calculate atmospheric evaporative demand is overly simplistic and uncertain. If the available data do not allow the application of the Penman–Monteith equation, the appropriate alternative would be the Hargreaves equation, which uses maximum and minimum temperature.
Lines 161–170. These formulations are unnecessary and confusing, as they merge the calculation of potential evaporation with the fitting of data to compute the SPEI.
Section 2. This section is confusing, and it is not possible to infer a logical structure in the methodological design. It remains unclear how the various elements described—simulations from GCMs and RCMs, the drought index, and hydrological modelling—are integrated into a coherent methodological framework aligned with the stated objectives. Overall, the hydrological modelling component is not sufficiently informative. Planning a hydrological model for such a large basin is an enormous task, subject to major uncertainties, and these challenges and methodological limitations are not adequately addressed in the manuscript’s methodology section.
A key issue is whether the assessment based on climate models accounts for the fact that these models do not reproduce the natural climate variability observed in reality. This must be considered when comparing observations with model simulations, as in Figures 2 and 3. The authors explain that LAERTES-EU is a model-generated dataset from decadal hindcasts (i.e., initialized with historical data), but this does not guarantee that model simulations reproduce the observed variability. This is an essential point that must be clarified, since if the model simulations do not match observed variability, they cannot be reliably used in this study, which aims to evaluate drought propagation based on real drought events. For example, forcing the hydrological model with data that do not reflect the observed variability may introduce substantial bias into the conclusions, as the most significant drought events are identified from observations.
Indeed, Table 3 clearly shows that the simulations using model-generated data overestimate the severity of drought events. However, it is not possible to determine whether this problem arises from the input data or from the inherent uncertainties associated with modelling such a large basin.