Global prediction of extreme floods in ungauged watersheds.

Floods are one of the most common natural disasters, with a disproportionate impact in developing countries that often lack dense streamflow gauge networks1. Accurate and timely warnings are critical for mitigating flood risks2, but hydrological simulation models typically must be calibrated to long data records in each watershed. Here we show that artificial intelligence-based forecasting achieves reliability in predicting extreme riverine events in ungauged watersheds at up to a five-day lead time that is similar to or better than the reliability of nowcasts (zero-day lead time) from a current state-of-the-art global modelling system (the Copernicus Emergency Management Service Global Flood Awareness System). In addition, we achieve accuracies over five-year return period events that are similar to or better than current accuracies over one-year return period events. This means that artificial intelligence can provide flood warnings earlier and over larger and more impactful events in ungauged basins. The model developed here was incorporated into an operational early warning system that produces publicly available (free and open) forecasts in real time in over 80 countries. This work highlights a need for increasing the availability of hydrological data to continue to improve global access to reliable flood warnings.

Caravan - A global community dataset for large-sample hydrology.

High-quality datasets are essential to support hydrological science and modeling. Several CAMELS (Catchment Attributes and Meteorology for Large-sample Studies) datasets exist for specific countries or regions, however these datasets lack standardization, which makes global studies difficult. This paper introduces a dataset called Caravan (a series of CAMELS) that standardizes and aggregates seven existing large-sample hydrology datasets. Caravan includes meteorological forcing data, streamflow data, and static catchment attributes (e.g., geophysical, sociological, climatological) for 6830 catchments. Most importantly, Caravan is both a dataset and open-source software that allows members of the hydrology community to extend the dataset to new locations by extracting forcing data and catchment attributes in the cloud. Our vision is for Caravan to democratize the creation and use of globally-standardized large-sample hydrology datasets. Caravan is a truly global open-source community resource.

A mosaic of sex-related structural changes in the human brain following exposure to real-life stress.

Whereas sex differences in the brain's response to stress have been reported in both humans and animals, it is unknown whether they 'add up' consistently within individual brains. Here, we studied this question in a unique data set of magnetic resonance imaging (MRI) scans obtained before and after exposure to extreme real-life stress in the form of combative military service in 34 (15 women) young (18-19 years old) healthy soldiers. Across two data sets, one of regional volume and one of cortical thickness, only a few regions (seven and three, respectively) showed sex/gender-specific changes (i.e., the most common structural change in women and men was different). The number of internally consistent brains (a male-typical or a female-typical response in all regions) was not different from the number expected by chance nor from that observed in regions showing a sex-similar response, and was lower than the number of mosaic brains (at least one region with a male-typical response and one with a female-typical response). Although these findings do not reveal the source of sex/gender differences in response to stress and of within-brain variability in this response, they demonstrate that these differences do not consistently add up to create a female-typical and a male-typical neural response to stress.

A Doctor's Testimony: Medical Neutrality and the Visibility of Palestinian Grievances in Jewish-Israeli Publics.

This paper follows the testimony of Izzeldin Abuelaish, a Palestinian physician who bears witness to his experiences working, living, and suffering under Israeli rule. He presents his story as a doctor's story, drawing on his identity as a medical professional to gain credibility and visibility and to challenge the limited legitimacy of Palestinian grievances. In this paper, I explore his testimony as a medical voice that at once recounts the suffering and loss endured by the Palestinian people and also struggles to negotiate the values associated with being a "reliable" witness. Consequently, I ethnographically examine the social life and reception of his story in Jewish-Israeli publics. In comparison with most Palestinian narratives, Abuelaish's testimony achieved an extremely rare degree of visibility and sympathy, a phenomenon that calls out for analysis. I identify the boundaries that typically render Palestinian grievances invisible to Israeli publics and suggest how medicine's self-proclaimed ethos of neutrality served as a channel for crossing them. Finally, I reflect on the political possibilities and limitations of medical witnessing to render suffering visible and arouse compassion toward those construed as a dangerous/enemy Other.