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Dingkun Yin

As seen in: Nature, MDPI
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Articles

Machine learning reveals disruptive nutrient pollution shifts in Chinese rivers to 2100

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By Xiaoyue Zhang, Hong Zhi Zhang, Dingkun Yin, Baojing Gu, Lei Chen
| Nature Verified
Abstract Anticipating nutrient pollution under changing conditions is urgent for water security. Nonetheless, high-resolution predictive frameworks capturing nonlinear driver responses remain limited. Here, we present a nationwide assessment of China’s water-quality evolution from 2023 to 2100, integrating over 3 million daily records with 41 climatic, landscape, and socioeconomic drivers via regionally tailored Random Forest models (R2 of 0.88–0.92).
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The Ecological Effect of Ship Canals on Wetlands

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By Dingkun Yin, Ruixue Zhao, Zijing Liu, Zhaoxing Han
| MDPI
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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A Novel GIS-SWMM-ABM Approach for Flood Risk Assessment in Data-Scarce Urban Drainage Systems

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By Shakeel Ahmad, Haifeng JIA, Anam Ashraf, Dingkun Yin
| MDPI
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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