What is the carbon restoration potential on global land taking into consideration of water resource constraints? Check this paper out nature.com/articles/s4422… rdcu.be/d0VgS

New study models global mangrove Net Primary Productivity (NPP) from 1980–2094 using existing leaf litter data & advanced algorithms (MLR & Random Forest). Key insights across regions defined by the Marine Ecoregions of the World framework. 🌿🌍 doi.org/10.1016/j.scit…

Happy to share that our paper titled "PIML-SM: Physics-informed machine learning to estimate surface soil moisture from multi-sensor satellite images by leveraging swarm intelligence" has been published in 𝐈𝐄𝐄𝐄 𝐓𝐆𝐑𝐒. doi.org/10.1109/TGRS.2… #soilmoisture #cop29

Global Prediction of Flash Drought Using ML: in GRL 1. ML is used for Global Flash Drought (GFD) prediction up to 2 week lead time 2. 33% and 24% GFD onset and termination events can be correctly predicted at 7 day lead time 3. ML improves GFD prediction over dynamic model

Dr. Debora Oliveira (Debora Yumi de Oliveira) from our group will present her poster on "Water Resources Vulnerability and Coping Capacity Assessment" today at #AGU24. 📍 Poster Number: 1138 🗓️ Date: Dec. 11 ⏰ Time: 1:40 PM – 5:30 PM Looking forward to seeing you there....

We are organising a workshop on "𝐆𝐄𝐎𝐒𝐏𝐀𝐓𝐈𝐀𝐋 𝐓𝐄𝐂𝐇𝐍𝐈𝐐𝐔𝐄𝐒 𝐓𝐎 𝐌𝐎𝐍𝐈𝐓𝐎𝐑 𝐒𝐀𝐍𝐃 𝐌𝐈𝐍𝐈𝐍𝐆 𝐈𝐌𝐏𝐀𝐂𝐓𝐒" 📅 Jan 13-18, 2025 📍 IISER Bhopal Apply by Dec 22, 2024! link to apply bit.ly/41ssclp

Day 3 Update! Hands-on learning at our workshop! Participants explored 𝗶𝗻-𝗵𝗼𝘂𝘀𝗲-𝗺𝗮𝗱𝗲 𝗳𝗹𝘂𝗺𝗲 𝘁𝗮𝗯𝗹𝗲𝘀, replicating fluvial systems on a small scale to study riverine processes, sediment transport, and sand mining impacts. #GeospatialTechniques #SandMining

🌍 Day 4: Fieldwork at the 𝗰𝗼𝗻𝗳𝗹𝘂𝗲𝗻𝗰𝗲 of the 𝗡𝗮𝗿𝗺𝗮𝗱𝗮 and 𝗧𝗮𝘄𝗮 𝗿𝗶𝘃𝗲𝗿𝘀 Participants explored state-of-the-art field techniques, including 𝗔𝗗𝗖𝗣, 𝗠𝘂𝗹𝘁𝗶𝗯𝗲𝗮𝗺, 𝗘𝗥𝗧, and 𝗗𝗿𝗼𝗻𝗲 𝘀𝘂𝗿𝘃𝗲𝘀. #GeospatialTechniques #Fieldwork

We're pleased to release DIFFICE-jax v1.0, the foundation of our Science paper and the first #DIFFerentiable #NeuralNetwork solver for #DataAssimilation of ICE shelves written in #JAX: 🔗Docs: diffice-jax.readthedocs.io/en/latest/inde… 📄Peer-reviewed by JOSS #OpenSource: joss.theoj.org/papers/10.2110…

🌊 Continuing our #AGU Catchment Hydrology TC Early Career Competition 2024 series with Franziska Clerc-Schwarzenbach! Thank you for sharing your favorite #hydrology paper with us! 📖💧 We’ll spotlight #EarlyCareer voices twice a month—stay tuned for more insights! 🔍

Global Lake and Wetland Database GLWD_v2 is released. We contributed to provide flood inundation related data. essd.copernicus.org/articles/17/22…

Latest publication in npj Natural Hazards led by our recently graduated PhD Scholar Sai Kiran Kuntla. Although India has densely populated floodplains, national-scale trends in flood discharge observations remain largely unknown. Using painstakingly collected data from 173

📢 Explore SEN12-FLOOD – a rich, multi-sensor dataset for advancing flood detection using SAR and optical satellite imagery 🌊 Built to support all-weather flood monitoring, even under heavy cloud cover and during extreme events 🛰️ Features time series of co-registered Sentinel-1

📉 Spring 2025 saw the lowest seasonal river flow across Europe since #EFAS records began in 1992. This new map, featured in the May #C3S Climate Bulletin, highlights widespread below-average flows in central, eastern & northern Europe. More details: visitclimate.copernicus.eu/climate-bullet…

Pleased to share our recent publication: Soil Moisture Rapid Transitions Between Dry and Wet Extremes in India, 1951–2024 in JGR-Atmospheres agupubs.onlinelibrary.wiley.com/doi/10.1029/20… Soil moisture rapid transitions are detrimental for agriculture and food production Agriculture INDIA DSTIndia MoES GoI

My PhD work on Flash Floods in US National Weather Center from way back in 2016/17 got cited by The New York Times today in the context of the devastating Texas floods, along with Zhi Li's work. I had proposed a new variable called 'Flashiness' as a new measure of flash flood

🚨 New Publication! Our study presents the 1st national-scale ML model to predict forest fire counts across India. Includes SHAP & sensitivity analysis to reveal key drivers for data-driven policy. 📄Read: sciencedirect.com/science/articl… #ML #ForestFires #Research #India

Researchers from IISER Bhopal have developed a promising framework for forest fire prediction using ML. 🔥🌲 It supports evidence-based decision-making and helps policy makers design targeted fire prevention strategies. 👏 Applause to the team addressing this vital issue! #ML

Deadline approaching soon! Submit your abstract to #AGU25 Session H038: Advancing #Watershed Science Through #Hybrid #ML and #Physical #Modeling Chaopeng Shen Praveen Kumar Charuleka Varadharajan Berkeley AI Research Berkeley Lab

🌍ELLIS Summer School Jena 2025 AI for Earth & Climate Sciences 🧑‍🎓Tutors: 20 of 22 📚Topic: Hybrid 🎓Sujan Koirala 🎓Nuno Carvalhais Universität Jena Max Planck Institute for Biogeochemistry Michael Stifel Center Jena (MSCJ) Carl-Zeiss-Stiftung Climate Change AI AI for Good 🇺🇳 #AIforGood ELSA - European Lighthouse on Secure and Safe AI European Space Agency Max Planck Society 🔗 tinyurl.com/63b4p62b