If you’re enjoying the articles in this newsletter, we’d be grateful for your support. You can contribute by making a donation, submitting your own articles, joining us as a paid member(click here to pay in INR), or sponsoring us(Contact us for more details. Email at contact@baipatra.ws). Your support, in any form, is vital to helping us sustain and grow. Thank you!
1
“Flood peaks in Mid-Atlantic U.S. watersheds show a V-shaped response to urbanization: they decrease at low urban development (below 10% PDAW), then rise sharply as urbanization increases further due to complex climate-landscape interactions. A neural network model confirmed this nonlinear behavior, underscoring the need to consider more than just urban area when predicting flood risk.”…..Hua et.al.(2025).
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2
“Artificial neural network (ANN) models using climate indices outperformed ARIMA models for long-term streamflow forecasting at six Victorian stations, with the best ANN achieving Pearson R = 0.90, RMSE = 0.04, and MAE = 2.50 for six-month advance prediction. ANN’s superior accuracy highlights its suitability for operational streamflow forecasts in this region.ANN models using lagged climate indices significantly outperformed ARIMA models for forecasting streamflow at Victoria’s stations, especially at Acheron where the ANN achieved Pearson R = 0.90, RMSE = 0.04, and MAE = 2.50. These results show ANN’s strong capability for accurate six-month-ahead streamflow forecasts.”……Oad and Imteaz(2025).
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3
“This research demonstrates that multi-site LSTM models with trainable site embeddings can accurately predict groundwater levels globally, learning site-specific patterns directly from time series data without relying on inconsistent external descriptors. The study also finds that, while predictive performance is strong in data-rich regions, simply increasing dataset size does not guarantee better predictions in data-sparse areas, highlighting both the potential and challenges of scalable deep learning for groundwater forecasting.”….Nolte et.al.(2025)
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4
The Knowledge Transfer Partnership funded by Innovate UK helped University of Exeter develop “Ground Truth,” a digital twin combining physical and numerical modeling with machine learning to predict water pipe deterioration and failures under various conditions. The tool, now used by multiple UK and European utilities, enhances pipe condition assessment and maintenance efficiency, earning the Exeter Knowledge Exchange Award 2024 for its impactful innovation.
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5
The University of Exeter has joined the ENFORCE project for the period from 2024 to 2028. The ENFORCE project promotes sustainable environmental practices by integrating citizen science, AI, and geospatial intelligence to improve data quality, monitoring, and regulatory compliance across Europe. It establishes a pan-European collaboration hub, tests innovative tools at eight pilot sites, and supports policy development aligned with the EU Green Deal and UN SDGs.
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6
Cairo Water Week (CWW) has emerged as a cornerstone event for global water discourse, uniting governments, organizations, and innovators who share a common vision: safeguarding water as the lifeblood of sustainable development will be held from 12th to 16th Oct 2025 in Cairo.
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7
The University of Iowa’s Hydroinformatics Lab patented an innovative water level measurement technology combining cameras and standard sensors, offering a cost-effective, accurate solution for monitoring streams, rivers, and reservoirs worldwide, enhancing flood resilience and environmental decision-making.
This technology, developed through years of research and real-world trials, empowers underserved and remote communities with robust flood monitoring capabilities while protecting intellectual property to attract partnerships for broader implementation.
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8
A Workshop is scheduled to introduce the HydroLearn platform, showcasing its interactive modules and gathering attendee feedback to guide the development of future educational content tailored to CIROH research goals.
HydroLearn enables CIROH projects to create pedagogically sound, adaptable learning modules, with contributions from experienced fellows and instructors demonstrating practical classroom and training applications.
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9
In 2020, California’s Creek Fire became so intense that it created its own thunderstorm known as a pyrocumulonimbus cloud, which has been difficult for scientists to replicate in climate models until now.
A new study has successfully simulated these explosive fire-born storms, reproducing the Creek Fire’s pyrocumulonimbus and others, improving understanding of their formation, behavior, and global climate impacts.
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10
Researchers at King Abdullah University of Science and Technology(KAUST) confirmed that about 6.2 million years ago, the Red Sea completely dried out, becoming a barren salt desert due to tectonic shifts severing its connection to the Mediterranean and blockage by a volcanic ridge.
A catastrophic flood from the Indian Ocean breached this barrier within 100,000 years, rapidly refilling the Red Sea, carving deep submarine canyons, restoring marine life, and redefining the region’s geological and ecological history.
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If you’re enjoying the articles in this newsletter, we’d be grateful for your support. You can contribute by making a donation, submitting your own articles, joining us as a paid member(click here to pay in INR), or sponsoring us(Contact us for more details. Email at contact@baipatra.ws). Your support, in any form, is vital to helping us sustain and grow. Thank you!
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