Jim Best on Muck Rack

Jim Best

  • Professor, University of Illinois at Urbana Champaign and Contributor
Urbana
As seen in: Nature, Wiley Online Library, Science Magazine, Berkeleyside, NewsBreak, Geographical, Lebanon Enterprise
... interested in fluid flow, sediment transport and sedimentary environments ... both modern and ancient...and in lab and field .... views my own .....
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Articles

Global patterns of reservoir sedimentation and overlooked risks in small reservoirs

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By Kai Liu, Chenyu Fan, Chunqiao Song, Jim Best, Jida Wang, Linghong Ke, Yoshihide Wada, Dongfeng Li, Dai Yamazaki, Anjun Deng, Jiaming Na, Safat Sikder, R. Iestyn Woolway
| Nature
Abstract Reservoir sedimentation is an escalating threat to global water security. While most existing assessments focus on large, well-managed reservoirs, they overlook the vast and vulnerable network of smaller reservoirs, which hampers our understanding of global sedimentation risks.
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Water scarcity and infrastructure risk of amplified seasonal sediment transport

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By Ting Zhang, Jim Best, Amy E. East, Lorenzo Rosa, Qianhan Wu, Yiyi Li, Yu Qi, Yunkai Li, Dongfeng Li
| Nature
Abstract Climate warming and deglaciation are reshaping hydrological seasonality in cold–dry regions, threatening the long-term sustainability of agriculture, ecosystems and local communities. However, existing evidence is limited to runoff seasonality. Changing sediment-transport seasonality, a more sensitive component, is emerging as a substantial yet under-recognized threat to water infrastructure.
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Human alterations to global riverine phosphorus fluxes to the ocean

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By Georgios Efthymiou, Ziqi Song, Muddassir Malik, Guowangchen Liu, Dongfeng Li, Ting Zhang, Jim Best, James J. Elser, Gabriel Filippelli, Hanqin Tian, Yi Zhao, Shang Tian, Shouliang Huo, Hanxiao Zhang, Wei Zhi, Lei Chen, Feng Zhou, Qiuwen Chen, Yong Liu, Jinren Ni, Guowangchen Liu, Anmeng Sha, Zhenyao Shen
| Science Magazine
Abstract Rivers regulate land-ocean total phosphorus (TP) fluxes critical to ecosystem health and food security, yet global dynamics remain poorly understood due to limited observations. Here, we develop a machine learning framework integrating multimodal data and 280,000 TP measurements to reconstruct TP flux patterns over 1980–2019 across 420 major rivers. Results reveal a deceptive global equilibrium.
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See all 40 licensed articles (42 Total)

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