I think this paper may be worth highlighting because it provides a thorough description of a cross-disciplinary problem that has yet to be addressed in practice. The use of PTFs measured at small scales within global models represents a huge discrepancy. This paper challenges us to reconsider how we do things in this field.

A rigorous analytical hydrological model for Ensemble Rainfall-Runoff Analysis (ERRA) of catchments. The paper gives the concepts, mathematical details and several proof-of-concepts. ERRA was designed as a tool for iterative and exploration of hydrological data, through trial and error with analyses of varying degrees of complexity. The broad geosciences community could benefit from this statistical approach. The discussion cites some good examples of applications possible in hydrology, but potential also in other related fields as well.

This paper is the first to present a mechanism for greening of the Sahara that relies on westerlies intensity as the primary mechanism. This mechanism, which is based on cutting edge analysis and observations, has the potential to move the 30 year-long debate on African Humid Period forward. This interdisciplinary study joins several fields, including climatology, paleoclimate, remote sensing, and hydrology.

Large sample hydrology datasets such as Caravan provides the community with hydrometeorological information and catchment attributes for many catchments in the world and offers the opportunity for hydrological research. However, there are considerable differences between the forcing data of Caravan compared to the CAMELS datasets, especially with potential evaporation. This can lead to wrong conclusions on catchment hydrological drivers and affect regionalization. This papers shows the important of robustness of large sample datasets and the need to keep assessing that.

The topic is of interest to a wide audience. The authors have developed a new approach to assess changes in the spatial extent of flooding.

The paper includes a very rare 3 year data collection of stable water isotopes in surface and subsurface waters. The innovative analysis challenge general conceptualizations of new precipitation inputs wetting dry soils or displacing previously stored waters from those soils. These observations illustrate how measurements of isotopic variability across different subsurface depths, hillslope positions, and time scales can help to constrain potential flow processes delivering precipitation to deep soils and streams.

This paper uses information from news sites with natural language processing tools to infer data on a hydrological process at the regional scale (flooding). The paper demonstrates the technique's applicability and opens new avenues to use advanced computing techniques and web resources to improve the understanding of hydrological processes.

This paper is of great interest to the geoscience community and the broader public because it offers a comprehensive European flood event catalogue that merges historical records with modelled data, providing an extensive overview of coastal, riverine and compound flood impacts across Europe over seventy years. This will help enhance the accuracy and completeness of flood impact assessments, crucial for improving flood risk management and mitigation strategies. It also provides a milestone dataset for understanding changes in hazard, vulnerability and exposure for national, regional and continental flood risk assessments.

This study integrates deep learning techniques into hydrological modelling to reconstruct runoff data. The extended reconstruction of runoff spanning over six decades (1962-2023) provides an unprecedented data basis to study long-term runoff patterns and trends in Switzerland. The findings spotlight a shift towards less frequent wet years and more frequent dry conditions in Switzerland. This insight is also relevant given the current situation of extreme droughts and floods in Europe.