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ML Earth Sciences

@mlearthsciences.bsky.social
188 followers 77 following 13 posts

Followed by 2.5k on twitter (X): x.com/MLEarthSciences We tweet/retweet papers related to machine learning/data science/deep learning for Earth and Environmental Sciences. Just email your paper details to mlearthsciences@gmail.com #research #ML

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Paul Voosen @voosen.me · 09/10/2026
Our story last month in @science.org talked about how the SWOT satellite is radically improving our view of global river behavior, while challenging hydrology models. This new study seems a great example of how its data is now improving these models.
agupubs.onlinelibrary.wiley.com
SWOT‐Fitted River Bathymetry for Global Hydrodynamic Models
Iterative SWOT-fitted bathymetry cuts global median water surface elevation (WSE) bias from 3.10 to 0.18 m in two runs Global median flood-wave timing is preserved (median r = 0.38); modest varia...
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Pure Science @purescience.news · 10/10/2026
Rising water is creating inland ghost forests in the US #Science #EarthSciences #Hydrology #climatechange #ghostforests #inlandforests #risingwater #usforestry purescience.news/read?id=2343210716…
purescience.news
Rising water is creating inland ghost forests in the US | New Scientist
Forests full of dead trees aren’t just found by the US coasts – they are also appearing far from the sea around freshwater lakes
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hydroagent-lab.bsky.social @hydroagent-lab.bsky.social · 6h
New white paper out! Water-Sector AI Agents: Current Landscape, Insights, and Future Directions By Shunan Zhou and Nuo Lei Chinese version + full open LaTeX source. English translations welcome! doi.org/10.5281/zeno... #Water #Hydrology #AIAgents #LLM #OpenScience #HydroAgent #HydroAgentLab
doi.org
水利行业智能体白皮书:现状、洞察与未来方向
水利业务往往涉及多源异构数据、专业模型、业务规则和跨部门协同,并需要在不断变化的水情、工情和管理要求下及时形成判断与行动。面对复杂水情快速响应、多源信息综合研判和跨业务流程协同等需求,如何连接分散的信息、工具与专业知识,并在可控条件下提高业务协同和决策支持效率,正在成为水利数字化转型中的重要问题。 大语言模型(LLM)及由其驱动的智能体正在从问答与内容生成延伸至数据检索、模型调用和工作流组织,并迅...
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John Marsham @johnmarsham.bsky.social · 06/10/2026
ML is revolutionising satellite retrieval. We show ML Rain over Africa beats not only other real-time rainfall estimates, but also high-quality GPM IMERG! Great for nowcasts+warnings. Fantastic work from Simon Ageet, @dougparkermeteo.bsky.social et al. rmets.onlinelibrary.wiley.com/doi/10.1002/...
rmets.onlinelibrary.wiley.com
Evaluation of Satellite Rainfall Products for Nowcasting Over Southern Africa Using Rain‐Gauges and Lightning Data
Three satellite-based rainfall nowcasting products used in the WISER EWSA testbeds, CRR, IMERG-HQ and the new machine-learning-based Rain over Africa (RoA), were evaluated against high-resolution rai...
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ELLIS unit Jena @ellisunitjena.bsky.social · 25/02/2026
🎥𝗧𝗲𝗮𝗺 𝗧𝗮𝗹𝗲𝘀 𝗩𝗶𝗱𝗲𝗼𝘀 #𝟰𝟱 ⚙️🧑‍🔬Thomas Wolfers (thomaswolfers.bsky.social) is 𝗖𝗮𝗿𝗹 𝗭𝗲𝗶𝘀𝘀 𝗣𝗿𝗼𝗳𝗲𝘀𝘀𝗼𝗿 for Artificial Intelligence in Neural Systems Imaging at @uni-jena.de and a member of the Ellis Unit Jena. 🔗 Gain firsthand insights into his research: www.youtube.com/watch?v=w-_Q...
youtube.com
No. 45 Thomas Wolfers - ELLIS unit Jena Team Tales Videos
YouTube video by ELLIS Unit Jena
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Copernicus ECMWF @copernicusecmwf.bsky.social · 20/02/2026
Registration and abstract submission are now open: @ecmwf.int and German Space Agency at DLR are pleased to invite you to the 22nd International Workshop on Greenhouse Gas Measurements from Space, 29 June to 2 July, Bonn, Germany.
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KinarNicholas.bsky.social @kinarnicholas.bsky.social · 21/02/2026
Hydrology Paper of the Day @cambup-archaeology.cambridge.org on the water reservoirs and hydrology of Northern Belize during the Mayan empire: Indigenous civil engineering; urban forest gardens and spatial patterns of settlement; possible wetland management; and mapping drainage by LiDAR techniques.
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Abhilash Singh @abhilashsingh.bsky.social · 19/02/2026
Our recent JGR paper (doi.org/10.1029/2025...) just got featured by Critical Zone News! What’s even better? They’ve explained it in a way anyone can understand. If you’ve ever wondered how soil “talks” about moisture across its layers, this is a fun and accessible read. tinyurl.com/5n93my8k
open.substack.com
The Soil Learns to Speak in Layers
At dawn, a field looks deceptively simple.
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ELLIS unit Jena @ellisunitjena.bsky.social · 25/10/2025
🎓ELLIS Unit Jena Vernissage
“When Machines Learn for Nature: AI Research on Climate and Biodiversity” 🤖🌿 📅 6 Nov 2025 ⏰ 5:15–7:00 PM
📍 University Main Building, Jena (@uni-jena.de)
🖼️ Exhibition runs until Dec 12
🔗 Register: survey.academiccloud.de/index.php/38... @ellis.eu
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KinarNicholas.bsky.social @kinarnicholas.bsky.social · 19/10/2025
Hydrology Paper of the Day @abhilashsingh.bsky.social suggested by @mlearthsciences.bsky.social on obtaining subsurface soil moisture from surface soil moisture observations: conditional generative modeling in the context of Fickian diffusion, and a reverse diffusion process from a neural network.
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Abhilash Singh @abhilashsingh.bsky.social · 18/10/2025
Can weak physics improve machine-learning generalization to new (or any) sites compared to hard-constraint physics-informed machine learning that requires site-specific details? We address this question in our new paper in GRL. doi.org/10.1029/2025... #soilmoisture #machinelearning
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ELLIS unit Jena @ellisunitjena.bsky.social · 15/10/2025
Looking forward to the AI in Science Summit 2025, 📆 3–4 Nov in Copenhagen! Markus Reichstein co-curates the Planet & Climate workshop with Sašo Džeroski. Speakers: Jonas Peters, Gustau Camps-Valls, Florence Rabier & Christian Igel 🔗 ais25-summit.webflow.io/thematic-wor...
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Santiago Gassó @sangasso.bsky.social · 22/09/2025
🧪🛰️🌍 A great use of satellite platforms: ML applied to #geostationary native radiance observations (GOES and TEMPO) with High res model outputs to derive surface PM2.5 pubs.acs.org/doi/10.1021/... @aerosolwatch.bsky.social @mparrington.bsky.social
pubs.acs.org
Hour by Hour PM2.5 Mapping Using Geostationary Satellites
This study estimates ground-level fine particulate matter (PM2.5) concentrations using geostationary satellites-derived Aerosol Optical Depth (AOD) and radiance measurements and meteorological paramet...
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KinarNicholas.bsky.social @kinarnicholas.bsky.social · 21/09/2025
Hydrology Paper of the Day @mlearthsciences.bsky.social on linkages between rainfall and landslides as predicted by machine learning: investigating how ANNs demonstrate a geography of risk; comparisons with known areas of landslides; and application to the Serra Geral region of southern Brazil.
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ML Earth Sciences @mlearthsciences.bsky.social · 20/09/2025
Spatially distributed antecedent rainfall thresholds for landslide occurrence: a multitask machine learning modelling approach doi.org/10.1080/0262... #machinelearning #landslide
doi.org
Spatially distributed antecedent rainfall thresholds for landslide occurrence: a multitask machine learning modelling approach
Landslide susceptibility and the amount of antecedent rainfall required to trigger landslides are conceptually tightly linked but usually modelled separately. We propose an approach for modelling b...
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KinarNicholas.bsky.social @kinarnicholas.bsky.social · 14/09/2025
Hydrology Paper of the Day @mlearthsciences.bsky.social on the use of frequency-domain neural networks for soil moisture imputation: weather station observations and model application by sliding windows and spatial convolution; a comparison of approaches; and rainfall magnitudes and sensitivities.
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ML Earth Sciences @mlearthsciences.bsky.social · 13/09/2025
Worried about missing value? A novel imputation framework based on Fourier neural operators (FNO) for soil moisture. The FNO model outperforms traditional approaches, and incorporating temporal lag reduces error by up to 15% in the diverse climates in India and Zambia. doi.org/10.1029/2025...
doi.org
Leveraging Neural Operator and Sliding Window Technique for Enhanced Subsurface Soil Moisture Imputation Under Diverse Precipitation Scenarios
Developed a novel Fourier Neural Operator (FNO) to enhance subsurface soil moisture imputation by employing a sliding window concept that seamlessly integrates rainfall, soil temperature, and norm...
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IOPP Machine Learning and AI @iopp-mlresearch.bsky.social · 05/09/2025
Recently published in #MachineLearningEngineering 🥳 Read the #openaccess article: 'Understanding interpretable patterns of Shapley behaviours in materials data' 👉 ow.ly/bmmN50WHE2X From Tommy Liu and Amanda S Barnard, (Australian National University) #DataAnalysis #ExplainableArtificialIntelligence
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AMS Committee on Hydrology @amshydrology.bsky.social · 26/08/2025
We are excited to announce openings for SIX new members to join the @ametsoc.org Committee on Hydrology! We are looking for 2 undergrad/grad student members and 4 regular members. Applications are due September 16 (CV and letter of interest required): forms.gle/qKdsLTTK1k9e...
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KinarNicholas.bsky.social @kinarnicholas.bsky.social · 21/08/2025
Hydrology Paper of the Day @pnas.org on how climate change, increases in stream temperature, and latitudinal gradients affect freshwater fish populations: the RivFishTime database paired with the Global Biodiversity Information Facility database for spatial analyses, and identifying decadal trends.
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Critical Zone News @cznews.bsky.social · 17/07/2025
#CriticalZone at #AGU25
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Ben Bond-Lamberty @benbondlamberty.bsky.social · 21/07/2025
BO11 - Advancing Biogeochemical Cycle Modeling with Artificial Intelligence (Al): Bridging Data-Driven Methods and Process-Based Approaches #AGU25
A flyer for the "B011" AGU session
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AGU Catchment Hydrology Technical Committee @agucatchhydro.bsky.social · 23/07/2025
🌎 Are you attending #AGU25? Consider submitting your abstract to our session on Challenges and Solutions for Hydrologic Scaling Across Multiple Processes and Scales. More information below!!!
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Fernando Pérez @fernandoperez.org · 24/07/2025
Open source, open science for earth, climate and geospatial science? Coming to #AGU25? Build tools in #Python @jupyter.org? Submit an abstract for this session and come meet us and like minded scientists!
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Abhilash Singh @abhilashsingh.bsky.social · 23/07/2025
First post !!! Happy to share our new paper is out in Engineering Applications of AI! "Overcoming Data Scarcity" uses transfer learning + satellite fusion to predict soil moisture with 55% less in-situ data 🔗 doi.org/10.1016/j.enga… �� abhilashsingh.net/codes.hthtml #RemoteSensing #ML #AI
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IOPP Machine Learning and AI @iopp-mlresearch.bsky.social · 22/07/2025
Publish in AI for Science for: 🔬 Broad scope for AI-driven scientific breakthroughs 🌍 Open access publishing at no cost to you ✅ Review by top international experts ⚡ Fast publication 📝 Formatting your way and we’ll handle the rest 🔗 Submit now: iopscience.iop.org/journal/3050... #AIResearch
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ML_Hydroclimate @mlhydroclimate.bsky.social · 22/07/2025
A new paper is out in Engineering Applications of AI! "Overcoming Data Scarcity" uses transfer learning + satellite fusion to predict soil moisture with 55% less in-situ data 🔗 doi.org/10.1016/j.enga…
doi.org
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esaclimate @esaclimate.bsky.social · 20/06/2025
✊ From observations to actionable information: Take a look at our mission in our digital flyer! It gives an overview of 40+ years of satellite data from a growing number of Essential Climate Variables to strengthen climate understanding and inform effective decision-making: t1p.de/lbgyl #LPS25
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Margaret Zimmer @margaretzimmer.bsky.social · 06/06/2025
Wrapping up your PhD? I’m planning to hire a postdoc in the next few months (start date flexible). Will start formally advertising soon, but you heard it here first!! Possible research topics include - critical zone hydrology, agricultural water quality, SW-GW interactions. Reach out if interested!
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KinarNicholas.bsky.social @kinarnicholas.bsky.social · 07/06/2025
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.
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petersalamon.bsky.social @petersalamon.bsky.social · 07/06/2025
⏳ Time is running out! Apply by 15 June to join the JRC as a hydrologic modeller and help shape the future of early warnings in Europe and beyond. Make an impact with #CEMS, #EFAS, #GloFAS. 🔗 recruitment.jrc.ec.europa.eu/vacancy/1885 #Floods #Drought #Hydrology
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ML Earth Sciences @mlearthsciences.bsky.social · 26/05/2025
PC: Yifang Ban, KTH
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KinarNicholas.bsky.social @kinarnicholas.bsky.social · 24/05/2025
Hydrology Paper of the Day @bioclimatology.bsky.social on how more than six years of data from a beech forest in Germany indicates changes in Critical Zone hydrology due to climate change: rainfall trends and canopy-scale partitioning; seasonal changes; and identifying storage and drivers.
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Manousos Valyrakis @hydromechanic.bsky.social · 22/05/2025
Calling all river scientists & engineers! #RiverFlow2026 is now accepting abstracts. Share your latest research in fluvial hydraulics and join us in Thessaloniki, Greece! Submit your abstract by August 15, 2025.
🔗 riverflow2026.web.auth.gr 
#Hydraulics #RiverScience
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Hydrology Next @hydrologynext.bsky.social · 22/05/2025
Interesting readings very recently published on 𝘿𝙞𝙜𝙞𝙩𝙖𝙡 𝙏𝙬𝙞𝙣𝙨 𝙤𝙛 𝙩𝙝𝙚 𝙀𝙖𝙧𝙩𝙝 Digital Twins of the Earth Between Vision and Fiction lnkd.in/dYQTs5wM and also: Bring digital twins back to Earth lnkd.in/dih-JvGT
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KinarNicholas.bsky.social @kinarnicholas.bsky.social · 04/05/2025
Hydrology Paper of the Day @ianabrown.bsky.social on how landscape affects drone-based photogrammetry: comparisons with LiDAR DEMs and CHMs for the Kronängen area of boreal forests and meadows; differences in topography; and accuracy comparisons with respect to weather, location and vegetation.
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KinarNicholas.bsky.social @kinarnicholas.bsky.social · 28/04/2025
Hydrology Paper of the Day @okke-batelaan.bsky.social on determining ET and temperature beneath the canopy of a forest by drone and airplane thermal imaging, LiDAR scanning and modelling: two catchments in Australia; satellite optical sensing; upscaling; validation; and quantifying uncertainties.
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KinarNicholas.bsky.social @kinarnicholas.bsky.social · 26/04/2025
Hydrology Paper of the Day @geospatialtao.bsky.social on a novel framework for UAS remote sensing of rangelands: the Reynolds Creek Experimental Watershed in southwest Idaho; machine learning image classification; comparison with existing data products; and the effects of spatial resolution.
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AI4PEX @ai4pex.bsky.social · 22/04/2025
🌍 AI is transforming climate research! Catch us at #EGU25 presenting cutting-edge work on applying #MachineLearning, hybrid models, and causal discovery in climate research. ⚡️ Don’t miss: Camps-Valls, Reid, Ouala, Beucler + more! #AI4Climate #ML4Science #EGU25 #ClimateAI
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Frederik Kratzert @kratzert.bsky.social · 11/04/2025
Currently working on my medal lecture talk for #EGU25. Without any doubt, this lecture youtu.be/yCC09vCHzF8?... by @karpathy.bsky.social was one of the key steps.
youtu.be
CS231n Winter 2016: Lecture 10: Recurrent Neural Networks, Image Captioning, LSTM
YouTube video by Andrej Karpathy
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Environmental Data Science @envdatascience.bsky.social · 15/04/2025
📢 New CFP: Special Collection in EDS! Calling for work exploring the convergence between #data-driven methodologies (#AI, #machinelearning) and physical modeling for Earth system science, building upon an upcoming workshop #EGU25 (@egu.eu). ℹ️ How to submit: bit.ly/3Eq4WLV 📅 Deadline: 31 Oct 2025
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AMS Committee on Hydrology @amshydrology.bsky.social · 09/04/2025
Hi there @bsky.app! The AMS Hydrology committee is excited to join @ametsoc.org here to grow the #hydrology community ahead of #AMS2026! ✅ Follow for hydrology/hydrometeorology facts, news, events, and more!
media.tenor.com
a man wearing a hat and a tank top is standing on a boat near the ocean .
ALT: a man wearing a hat and a tank top is standing on a boat near the ocean .
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KinarNicholas.bsky.social @kinarnicholas.bsky.social · 14/04/2025
Hydrology Paper of the Day @queenofpeat.bsky.social on peatland fires that continue burning during winter in the NWT and Alaska: how biomass controls the spatial prevalence of fires in lieu of fire weather areas; seedlings, soils and trees over a transect; and quantifying biogeochemical cycles.
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KinarNicholas.bsky.social @kinarnicholas.bsky.social · 10/04/2025
Hydrology Paper of the Day @drevaplaganyi.bsky.social on a commentary related to how wealthy countries affect deforestation and the biogeography of other nations: marine ecosystems and impacts; importing of resources in lieu of internal resource management; and recognizing global biodiversity.
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KinarNicholas.bsky.social @kinarnicholas.bsky.social · 08/04/2025
Hydrology Paper of the Day @iflscience.com on weird hydrology: rivers that flow in different drainage basins; why some rivers flow in two directions or have a reversed direction of flow; a lake that drains into two oceans; river capture and geological controls; modelling; and management challenges.
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KinarNicholas.bsky.social @kinarnicholas.bsky.social · 04/04/2025
Hydrology Paper of the Day @agrohydrology.bsky.social on the novel concept of thirstwaves: the standardized reference evapotranspiration must be greater than the 90th percentile of this measurement at a site for a period of three days; mapping thirstwave spatial patterns; and decadal trends.
agupubs.onlinelibrary.wiley.com
Thirstwaves: Prolonged Periods of Agricultural Exposure to Extreme Atmospheric Evaporative Demand for Water
Regional hotspots of thirstwaves do not necessarily align with areas of high overall evaporative demand Intensity, duration, and frequency of thirstwaves have increased significantly (p < 0.05) o...
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ML Earth Sciences @mlearthsciences.bsky.social · 01/04/2025
Excellent paper!!!
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Hydrology Next @hydrologynext.bsky.social · 01/04/2025
Great new paper by H. Mosaffa et al. on Journal of Hydrology: 𝗛𝗥-𝗣𝗿𝗲𝗰𝗶𝗽𝗡𝗲𝘁: 𝗔 𝗺𝗮𝗰𝗵𝗶𝗻𝗲 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗳𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 𝗳𝗼𝗿 𝟭-𝗸𝗺 𝗵𝗶𝗴𝗵-𝗿𝗲𝘀𝗼𝗹𝘂𝘁𝗶𝗼𝗻 𝘀𝗮𝘁𝗲𝗹𝗹𝗶𝘁𝗲 𝗽𝗿𝗲𝗰𝗶𝗽𝗶𝘁𝗮𝘁𝗶𝗼𝗻 𝗲𝘀𝘁𝗶𝗺𝗮𝘁𝗶𝗼𝗻 doi.org/10.1016/j.jh... Effective use of @esa.int Sentinel-1 for actual high-resolution (1 km) precipitation estimation...great!
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KinarNicholas.bsky.social @kinarnicholas.bsky.social · 23/03/2025
Hydrology Paper of the Day @almontanari.bsky.social on a version of BLUECAT to bias correct outputs of deterministic models and obtain an estimate of uncertainty by stochastic processes: quantiles via order statistics; extension to a multimodel case of ensemble members; and hydrology applications.
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KinarNicholas.bsky.social @kinarnicholas.bsky.social · 30/03/2025
Hydrology Paper of the Day @agu.org on a series of papers that influenced our understanding of hydrology: predicting unsaturated hydraulic conductivity; identification of monotonic trends; water management challenges; Colorado River droughts; and machine learning in the context of scale.
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