• Associate professor
• Supervisor of Master's Candidates
• Name (Simplified Chinese):Jieru Yan
• Name (English):Jieru Yan
• Name (Pinyin):yanjieru
• E-Mail:05e6de50e70918bda5e8d4f191f96ce65e85c43cacec9b48fad716d0ec6dc54cee36c2d71270dd3e224d9b5b7b1152164b4071be8565ceb276d3b86fe2130a86ced7b5fc2ff769e2b6243d1a487527b4c2f6d628147df2d810f8d45afb7db29b13e773b1b36d883d777e4ecb80941da11fc0d4c415caef3a2aa16e47e244295d
• School/Department:实验中心
• Education Level:Postgraduate (Postdoctoral)
• Business Address:纬地楼S202
• Gender:Female
• Degree:Doctoral degree
• Status:Employed
• Alma Mater:德国斯图加特大学
• Discipline:Hydrology and Water Resources
  

• PostalAddress:17c952adf631c9377ed08729ce3362ba15726010a0e8b959b53aa1222f8388b206259e8b1298785206cc8249e6154ac1054b12a4e8b5a9309f77d9ed665f28ece2ac8f82357ef618b2b5bbe4a573fdce82315170a5ba223d013ed8372c77f2f1cead43ceca3a6565d578e1462318d25a197bcc42a9e7c66ba2dfbd341dda638a

阎洁如，博士毕业于德国斯图加特大学，师从国际著名水文统计学家András Bárdossy教授，拥有 7 年留德科研积累（2012.04-2018.12）；博士毕业后进入同济大学从事博士后研究，合作导师为水文预报领域知名专家陶涛教授；2023年入选合肥工业大学“黄山学者学术骨干”。在Water Research, Hydrology and Earth System Sciences, Journal of Hydrology 等水文水资源领域主流期刊发表论文 10 篇，主持/参与包括国家自然科学基金项目、德国研究基金会（DFG）项目、国家重大水体专项独立课题、安徽省自然科学基金面上项目等在内的科研项目 10 项。主要研究方向包括：极端降水预报、水旱灾害模拟、机器学习赋能的水资源管理、地表-地下水相互作用与耦合模拟等。欢迎愿意发展计算机编程能力，有志于开展水文AI技术研发的研究生报考！主持/参与项目 [1] 安徽省自然科学基金面上项目：基于希尔伯特黄变换及非高斯Copula的跨尺度随机降水模拟，2408085MD091，2024.09- 2027.08，在研，主持 [2] 产学研合作课题：郑州城外城陶瓷艺术博物馆防洪应急预案编制，W2025JSFW1059，2025.11- 2028.12，在研，主持 [3] 国家自然科学基金青年基金项目：基于数值模拟和非线性融合技术对高分辨率降水场实时构建的研究，42001369，2021.01-2023.12，结题，主持 [4] 中国博士后科学基金面上项目：基于数值模拟和非线性融合技术对高分辨率雨量场实时构建的研究，2020M671219，2020.09-2022.08，结题，主持 [5] 国家重大水体专项独立课题：苏州市饮用水安全保障技术集成与综合应用示范，2017ZX07201001，3390.87万，2017.1-2020.12，结题，参与 [6] 国家自然科学基金面上项目：城市雨水系统光滑粒子动力学模拟理论研究，51778452， 80万，2018.01-2021.12，结题，参与 [7] 产学研合作课题：温州市鹿城区丰门街道排水管网运行状态诊断研究，48.5万，2020.06-2021.12，结题，参与（科研秘书） [8] 德国研究基金会项目：Space-Time Dynamics of Extreme Floods (SPATE)，12.8万欧元，2016.12-2018.12，结题，参与论文专著[1] Yan, J., Zheng, T.*, Zhao, J., and Luo, J. (2025). Bridging rarity of drought-flood abrupt alternation events with reverse distributions or reverse copulas，Water Research, 287, 124433. (SCI，JCR Q1区, 中科院一区, 自然指数期刊)[2] Yan, J.* and Bárdossy, A. (2019). Short time precipitation estimation using weather radar and surface observations: With rainfall displacement information integrated in a stochastic manner, Journal of Hydrology, 574, 672–682, 2019. (SCI，JCR Q1区, 中科院一区，IF = 6.708)[3] Yan, J.*, Bárdossy, A., Hörning, S., and Tao, T. (2020). Conditional simulation of surface rainfall fields using modified phase annealing, Hydrology and Earth System Sciences (HESS), 24, 2287– 2301. (SCI，JCR Q1, 中科院一区，IF = 6.617)[4] Yan, J., Li, F., Bárdossy, A., and Tao, T.* (2021) Conditional simulation of spatial rainfall fields using random mixing: a study that implements full control over the stochastic process, Hydrology and Earth System Sciences (HESS), 25, 3819–3835. (SCI，JCR Q1, 中科院一区，IF = 6.617)[5] Yan, J. and Tao, T.* (2022). Unsupervised anomaly detection in hourly water demand data using an asymmetric encoder-decoder model, Journal of Hydrology, 613, 128389. (SCI，JCR Q1区, 中科院一区，IF = 6.708)[6] Zhu W., Tao T.*, Yan H., Yan J.*, Wang J., Li S., and Xin K. An optimized LSTM-based approach applied to early warning and forecasting of ponding in the urban drainage system, Hydrology and Earth System Sciences (HESS). (SCI，JCR Q1, 中科院一区，IF = 6.617)[7] Li F. , Yan, J., Yan H., Tao T., Duan H. (2023) 2D Modelling and energy analysis of entrapped air-pocket propagation and spring-like geysering in the drainage pipeline system, Engineering Applications of Computational Fluid Mechanics, 17:1. (SCI，JCR Q1, 中科院一区，IF = 6.1)[8] Chen, L., Yan, H., Yan, J., Wang, J.*, Tao, T., Xin, K., Li, S., Pu, Z., & Qiu, J. (2022). Short-term water demand forecast based on automatic feature extraction by one-dimensional convolution, Journal of Hydrology, 606, 127440. (SCI，JCR Q1区, 中科院一区，IF = 6.708)[9] Li, F.†, Yan, J.†, Xiong, X., Yan, H., *Tao, T. and Wang, L. (2023). GIS-based fuzzy comprehensive evaluation of urban flooding risk with socioeconomic-index system development., Environmental Science and Pollution Research (SCI，JCR Q2区，中科院三区，IF = 5.190)[10] Pu, Z., Yan, J., Li, Z., Chen, L., Tian, W., Xin, K.*, Tao, T. (2023). A hybrid Wavelet-CNN-LSTM Deep Learning model for short-term Urban Water Demand Forecasting, Frontiers of Environmental Science & Engineering. (SCI，JCR Q2区, 中科院二区，IF = 6.048)[11] Yan, Jieru (2018). Nonlinear estimation of short time precipitation using weather radar and surface observations. Universität Stuttgart, Stuttgart. ISBN：978-3-942036-68-9. URL: http:// elib.uni-stuttgart.de/handle/11682/10287. (学术专著)[12] Yan, J., Zhang, Y., and Wei, S.* (2025). AI-Driven Identification of Optimal Distribution Models for Extreme Precipitation Data in China, International Journal of High Speed Electronics and Systems, 2540633. https://doi.org/10.1142/S0129156425406333