Integrating LLM-based agents with uncertainty-aware optimization for water-energy-carbon nexus management in irrigation districts - Lei Yu; Zhikai Li; Kai Huang; Fulin Li; Zixiang Lu; Yurui Fan; Yanan Jiang; Chenglong Zhang; Guangtao Fu (Water Research, 2027)

Non-stationary framework of quantifying heat-driven drought propagation mechanisms in the Yellow River Basin of China - Ben Niu; Yi Li; Xingyun Qi; Maokai Song; Guiyuan Zhang; Yurui Fan; Zhi Li; Shie-Yui Liong (Journal of Hydrology, 2026)

Composite copula adaptive metropolis for joint parameter estimation in hydrological models - Feng Wang; Guohe Huang; Yurui Fan; Yongping Li; Zhenyao Shen; Ya Zhou (Journal of Hydrology, 2026)

Revealing the lifecycle evolution of hail-producing deep convective clouds by synergy of multi-source data - Qiang Li; Hongrong Shi; Yurui Xie; Rubin Jiang; Chaoying Wang; Yupeng Teng; Shuo Jia; Jianwei Wen; Disong Fu; Jiefan Yang; Xuehua Fan; Jinqiang Zhang; et al. (Atmospheric Research, 2026)

Relationship between lightning channel extension and charge transfer during initial continuous current and continuing current in negative artificially triggered lightning - Jingxuan Wang; Yang Zhang; Yijun Zhang; Yanfeng Fan; Yurui Li (Atmospheric Research, 2026)

Comparative analysis of GAMLSS modeling approaches for nonstationary runoff dynamics in the Yellow River Basin of China - Ben Niu; Yi Li; Yurui Fan; Lei Gong; Lei Wang; Taishan Wang (Journal of Hydrology, 2026)

Synergistic optimization of water-energy-environment nexus under uncertainty: An interval type-2 fuzzy chance-constrained programming model in a coastal mountainous basin, China - Zhiyi Peng; Lei Jin; Yurui Fan; Li Wang; Jing Liu (Journal of Environmental Management, 2026)

Development of a multi-objective type-2 fuzzy interval stochastic programming model for water allocation in Minnan region integrating agricultural products and greenhouse gas emission under uncertainty - Yi Wei; Lei Jin; HaiYan Fu; Yurui Fan; RuoLin Bai (Environment, Development and Sustainability, 2026)

A semi-infinite type-2 fuzzy multi-objective programming model for irrigation water resource management under uncertainties - Enkang Pan; Lei Jin; Yurui Fan; Li Wang (Hydrological Sciences Journal, 2025)

Compound dry/wet and hot extremes decreased wheat/maize yield revealed by SHAP-RF and R-Vine Copula - Song Li; Yi Li; Guiyuan Zhang; Licheng Wang; Maokai Song; Yurui Fan; Kadambot H.M. Siddique (Field Crops Research, 2025)

Climate and land use regulate vegetation–runoff interaction pathways in the three-river source region - Guiyuan Zhang; Darrell Tang; Song Li; Yurui Fan; Alim Pulatov; Aili Sun; Xingyun Qi; Licheng Wang; Yi Li (Journal of Environmental Management, 2025)

Natural, tough and pH-responsive ultrasound modified soy protein isolate-arabinoxylan based double network hydrogels for controlled nutrients release - Ran Tao; Gaolin Li; Siyang Wang; Yufeng Sun; Yurui Li; Peiying Wang; Shuting Huang; Bei Fan; Fengzhong Wang (Food Hydrocolloids, 2025)

Evaluating Climate Change Impacts on Streamflow Changes in the Source Region of Yellow River: A Bayesian Vine Copula Machine Learning ( BVC ‐ ML ) Approach - Xiaowen Zhuang; Yurui Fan; Baogui Xin (International Journal of Climatology, 2025)
In this study, we proposed a Bayesian Vine Copula Machine Learning (BVC‐ML) method to predict streamflow changes in the Yellow River source area based on projections from three GCMs under various climate change scenarios. The BVC‐ML method was to (i) use the vine copula method to reflect the interdependence between the predicted variable (i.e., streamflow) and predictions from different machine learning (ML) techniques, (ii) derive deterministic and probabilistic predictions from the vine copula model conditional on corresponding ML predictions and (iii) integrate predictions from different vine copula models to generate the final results. The proposed BVC‐ML method was then applied for future streamflow projections based on outputs from CMIP6. The results from the BVC‐ML method show that the studied area would generally experience more streamflow increases in most months, and the increases would become more significant as the climate change shifts from SSP126 to SSP585. The outputs from different GCM models also lead to various streamflow changes in the studied area, with the projections from ACCESS‐CM2 leading to the highest streamflow increases. Furthermore, the BVC‐ML method is capable of deriving both deterministic and probabilistic predictions from the conditional distributions, and the 10% and 90% quantiles can reflect predictive uncertainties. The results from the quantile predictions show that May, July and October would have the highest increases in streamflow, which are consistent with the mean streamflow increases. Overall, the proposed BVC‐ML method is demonstrated to be a promising tool for predicting streamflow changes under different climate change scenarios. The findings would have significant implications for water resource management and climate adaptation over the studied region.

Improved semi-infinite interval type-2 fuzzy multi-objective programming with integrated multi-criteria decision analysis for sustainable water resource management - Xi Zhang; Lei Jin; Yurui Fan; Li Wang; Jing Liu; Pangpang Gao (Journal of Water Process Engineering, 2025)

The clinical characteristics of Streptococcus equi ssp. zooepidemicus causing acute death in pigs and its prevention with chimeric monoclonal antibodies - Chen Yuan; Yuchang Wang; Xiaowen Zhang; Xingyu Tian; Ying Liang; Fei Pan; Haoshuai Song; Linya Xia; Zhihui Wu; Wenqing Wang; Xiaowen Zhang; Yurui Xie; et al. (Veterinary Microbiology, 2025)

Analyzing water resources with sector characteristics in Fujian Province utilizing S2-DR-BIMCCP model integrated with the Gini coefficient - Ruolin Bai; Lei Jin; Yurui Fan; Xi Zhang; Ruoyu Yin; Yi Wei (Journal of Cleaner Production, 2025)

A flexible, highly sensitive, and anti-strain interference sensing fabric based on conjugated electrospinning core–shell conductive nanofiber yarns for ultra-stable pressure sensing and human–machine interaction - Wenqi Wu; Xu Jin; Adilaimu Tiliman; Fan Zhang; Ge Bai; Yurui He; Gaoling Jin; Bin Wang; Xiuqin Zhang; Rui Wang (Chemical Engineering Journal, 2025)

Orbital modulation of an intensified hydrological cycle during the Paleocene-Eocene Thermal Maximum - Jingyu Zhang; Chunlian Wang; Xiaohua Teng; David B. Kemp; Zhixiang Wang; Hu Yang; Congcong Gai; Yurui Zhang; Yi Zhong; Xiaodong Jiang; Qi Zhang; Weijie Zhang; et al. (Earth and Planetary Science Letters, 2024)

Development of a probabilistic agricultural drought forecasting (PADF) framework under climate change - Yizhuo Wen; Yifan Fei; Yurui Fan; Aili Yang; Bingqing Wang; PangPang Gao; Daniel Scott (Agricultural and Forest Meteorology, 2024)

Evaluation Climate Change Impacts on Water Resources Over the Upper Reach of the Yellow River Basin - Xiaowen Zhuang; Yurui Fan; Yongping Li; Chuanbao Wu (Water Resources Management, 2023)

Stepwise cluster ensemble downscaling for drought projection under climate change - Yizhuo Wen; Aili Yang; Yurui Fan; Bingqing Wang; Daniel Scott (International Journal of Climatology, 2023)
Drought is one of the most serious natural disasters exacerbated by climate change. Changes in precipitation and temperature in the future increase the likelihood of drought in China. In this study, a stepwise cluster ensemble downscaling (SCED) model was developed to bias‐correct projections of temperature and precipitation from multiple RCM outputs, and further characterized the drought hazards. The developed SCED model was used to aggregate and correct the results of multiple regional climate models, and its performance was proved to be reliable by comparing with the observed results. The proposed SCED method has been applied for drought projections over the Fujian province, China. The results showed that the changes of precipitation and temperature in Fujian would have obvious spatial heterogeneous characteristics. The temperature in the southeast coastal areas will increase by up to 4°C and the precipitation will decrease by 3.1% in the late 21st century, while the temperature rises and precipitation increases in the southwest. Temperature in inland areas will be lower and precipitation will be less. The drought hazards were also characterized by both SPI and SPEI based on biased‐corrected projections from SCED model. According to the SPI and SPEI indices, although the number of dry months in Fujian province will not change significantly in future, the spatial and temporal heterogeneity may become more explicit. Moreover, the moderate drought (from SPI) may increase while the general drought may decrease (from both SPI and SPEI). For extreme droughts, there would not be visible changes detected by SPI, but an increasing trend characterized since the impact of temperature was included in SPEI. In addition, there would be an increasing trend on drought when increasing temperature and precipitation occurred simultaneously.

Land use and landscape change driven by gully land consolidation project: A case study of a typical watershed in the Loess Plateau - Yurui Li; Yi Li; Pengcan Fan; Jian Sun; Yansui Liu (Journal of Geographical Sciences, 2019)

A coupled dynamical-copula downscaling approach for temperature projections over the Canadian Prairies - Xiong Zhou; Guohe Huang; Xiuquan Wang; Yurui Fan; Guanhui Cheng (Climate Dynamics, 2018)

Future changes of temperature and heat waves in Ontario, Canada - Zhong Li; Guohe Huang; Wendy Huang; Qianguo Lin; Renfei Liao; Yurui Fan (Theoretical and Applied Climatology, 2018)

Multivariate flood risk analysis for Wei River - Ye Xu; Guohe Huang; Yurui Fan (Stochastic Environmental Research and Risk Assessment, 2017)

A Hybrid Dynamic Dual Interval Programming for Irrigation Water Allocation under Uncertainty - Lei Jin; Guohe Huang; Yurui Fan; Xianghui Nie; Guanhui Cheng (Water Resources Management, 2012)

Inexact fuzzy two-stage programming for water resources management in an environment of fuzziness and randomness - Qing Hu; Guohe Huang; Zhenfang Liu; Yurui Fan; Wei Li (Stochastic Environmental Research and Risk Assessment, 2012)