Julie Mai

@julieeemai.bsky.social

Software Developer at ATS Corporation | previously computational hydrology and research | she/her

Mentors matter—especially in challenging times. The latest #EGU special issue Women in #Hydrology shines a light on women who’ve broken ground in hydrological sciences, & the mentees following their path. Essential reads on equity, inclusion, & resilience. Check 👇 blogs.egu.eu/divisions/hs...

Women in Hydrology – The Story of a Special Issue

It was 2021, and we were not feeling good.  COVID-19 was in full force.  Personally we were experiencing lockdown conditions, disruptions to our work, schooling and childcare arrangements.  Our social...

blogs.egu.eu

Hydrology Paper of the Day @rarakihydro.bsky.social on a model of soil moisture loss that utilizes a nonlinear function: model fitting to SMAP remote sensing data; an examination of global-scale patterns; how aridity, sand fraction and landcover affects outputs; and the role of evapotranspiration.

Ryoko Araki@rarakihydro.bsky.social · last yr.

My 2nd PhD chapter is out! Soil drying speeds encode the signature of evapotranspiration. Using SMAP data, we demonstrated that, introducing nonlinearity in a traditional soil model help capture aggressive vs conservative vegetation water consumption. doi.org/10.1029/2024...

Caravan News🐪🐫 I just published Version 1.6. The main update is that the source data for CAMELS-AUS was upgraded to CAMELS-AUS v2. This means more basins (561 vs 222) and more recent streamflow data (2022 vs 2014). All relevant links in thread 🧵 (please share/repost)

Starting on bsky with a new preprint: "How to deal w___ missing input data" doi.org/10.31223/X50... Missing input data is a very common challenge in deep learning for hydrology: weather providers have outages, some data products start later than others, some only exist for certain regions, etc.

Different scenarios for missing input data: outages at individual time steps (top), data products starting at different points in time (middle), and local data products that are not available for all basins (bottom). All of these scenarios reduce the number of training samples for models that cannot cope with missing data (yellow, small box), while the models presented in this paper can be trained on all samples with valid targets (purple, large box).

Ontario is having a colder winter this year. Maybe good for our 2025 blooms.. when winters are warmer it releases all the bound phosphorus in soils and without any crops to take them up it runs off to our lakes patiently waiting for the temperatures to warm theconversation.com/warmer-winte...

Warmer winters are fuelling a growth in algal blooms across the Great Lakes

Algal blooms are typically associated with summer weather but warmer winters caused by climate change are resulting in blooms appearing more frequently, and for longer periods.

theconversation.com