论文成果

出版物

期刊与会议发表。

Journal articles

  1. 01

    Low impact development technologies for mitigating climate change: Summary and prospects

    Zhang, Z., & Valeo, C. (2024)

    National Science Open, 3(1), 20230025

    从气候减缓视角综述 LID 技术的证据基础与未来研究方向。

    PDF DOI
  2. 02

    Verification of PCSWMM’s LID processes and their scalability over time and space

    Zhang, Z., & Valeo, C. (2022)

    Frontiers in Water, 4, 1058883

    验证主流水文模型中的 LID 模块，并评估其在时间与空间尺度上的可迁移性。

    PDF DOI

Preprints / Working papers

  1. 01

    Quantifying uncertainty from spatial data inputs using hydrological processes and fuzzy entropy

    Zhang, Z., & Valeo, C. (2025)

    SSRN

    面向水文决策的流程感知型空间输入不确定性量化方法，基于模糊熵。

    PDF DOI

Under review / In revision

  1. 01

    Quantifying flowrate uncertainty using spatially defined fuzzy entropy based on hydrological processes in a catchment

    Zhang, Z., & Valeo, C. (in revision)

    Journal of Hydrology

    提出引入水文过程信息的模糊熵框架，用于刻画由空间输入差异引起的流量不确定性。

  2. 02

    Fuzzy-based input methods for uncertainty quantification in a deterministic model comparison with ChatGPT for peak flow prediction

    Zhang, Z., & Valeo, C. (in revision)

    Journal of Hydrology X

    将模糊隶属输入策略与大语言模型辅助基线进行对比，用于城市汇水区洪峰预测。

Conference papers

  1. 01

    Quantifying Scaling-Up Uncertainty in Soil Data Using Fuzzy C-Means Clustering: A Framework for Application to Hydrological Modeling

    Zhang, Z., & Valeo, C. (2025)

    Environmental Science and Technology: Sustainable Development III (pp. 17–29). Springer Nature Switzerland

    提出基于模糊 C 均值的土壤数据尺度放大流程，尽量保留与水文模拟相关的信息。

    PDF DOI
  2. 02

    Quantifying Spatial Data Uncertainty with Fuzzy Entropy

    Zhang, Z., & Valeo, C. (2024)

    Conference Proceedings (IEEE Pacific Rim Conference on Communications, Computers, and Signal Processing), 1–6

    使用模糊熵对环境空间数据的不确定性进行归纳，支撑工程分析与决策。

    PDF DOI
  3. 03

    Quantifying scaling-up uncertainty in soil data using fuzzy C-means clustering: A framework for application to hydrological modeling

    Zhang, Z., & Valeo, C. (2024)

    In Proceedings of the International Conference on Environmental Science and Technology (ICEST) (pp. 17–29). Xiamen, China.

    ICEST 论文，提出保留水文学相关性的土壤数据尺度放大方法（模糊 C 均值）。

  4. 04

    Assessing Optimal LID Areas for Flood Mitigation: A Case Study on Vancouver Island, Canada

    Zhang, Z., & Valeo, C. (2023)

    Environmental Science and Technology: Sustainable Development (pp. 89–100). Springer International Publishing AG

    基于实地资料的案例研究，量化 LID 布设对城市内涝与洪峰的降低效果。

    PDF DOI
  5. 05

    Potential for nature-based solutions to mitigate impacts of climate change

    Zhang, Z., & Valeo, C. (2022, April 25–28)

    In Proceedings of the 3rd International Conference on New Horizons in Green Civil Engineering (NHICE-03). Victoria, BC, Canada.

    概述自然本底解决方案在城市排水系统气候适应中的潜力与局限。

Conference posters

  1. 01

    Potential in nature-based solutions for mitigating impacts of climate change [Conference poster]

    Zhang, Z., & Valeo, C. (2022, June 5–8)

    CWRA 2022 National Conference: Valuing Shared Waters, Canmore, AB, Canada.

    海报汇总了模糊指标与气候导向 LID 设计的初步联系与启示。

Conference presentations (talks/abstracts)

  1. 01

    Shannon entropy in urban drainage systems under changing climate: A case study of small-scale urban stormwater management system

    Zhang, Z., & Valeo, C. (2024)

    In Proceedings of the 4th International Conference on New Horizons in Green Civil Engineering (NHICE 04).

    探讨 LID 建模的尺度效应与信息损失，并提出保留决策有效信号的路径。

  2. 02

    Scale-up challenges and information loss in low impact development modeling for urban stormwater management in changing climate

    Zhang, Z., & Valeo, C. (2023)

    Presentation at the SUDS Conference, Jiaxing, China.

    针对输入聚合导致的信息损失，提出面向规划实践的缓解建议。

  3. 03

    Scale-up challenges and information loss in low impact development modeling for urban stormwater management in changing climate

    Zhang, Z., & Valeo, C. (2023)

    Presentation at the International Conference on Environmental Science and Technology (ICEST), Qingdao, China.

    ICEST 报告，强调不确定性传播路径与应对策略，服务于气候友好的 LID 模型。

  4. 04

    Determining LID performance for mitigating flooding under a changing climate [Conference abstract]

    Zhang, Z., & Valeo, C. (2023, June 18–21)

    CWRA 2023 National Conference: Conferencing with the Tide: Working Together to Address Water Resource Challenges, Halifax, Canada.

    会议摘要，展示气候变化情景下 LID 缓解内涝效果的早期分析。