Global Rainfall-Runoff Modelling
A special issue of Hydrology (ISSN 2306-5338). This special issue belongs to the section "Hydrology–Climate Interactions".
Deadline for manuscript submissions: 30 November 2026 | Viewed by 6
Special Issue Editors
Interests: hydrological modeling; rainfall runoff modeling; water resources engineering; hydrologic and water resource modeling
Interests: cold-region hydrology; soil–water–energy interactions; climate change impacts; process-based hydrological modelling
Interests: hydrological modelling; deep learning; climate change
Special Issue Information
Dear Colleagues,
Rainfall-runoff processes are the core of the global water cycle, linking atmospheric precipitation to surface/groundwater runoff and underpinning critical applications such as flood forecasting, drought mitigation and water resource planning. Under global change, increasing climate variability and human activities have shifted hydrological systems from steady to non-steady states, challenging traditional models that rely on stationary assumptions. Historically, rainfall-runoff modelling has evolved from empirical methods to process-based models and recent hybrid approaches integrating machine learning and uncertainty analysis, yet gaps remain in global-scale integration and adaptation to ungauged basins.
The goal of this Special Issue is to collect papers (original research articles and review papers) to provide insights into the latest advances in global rainfall-runoff modelling, including uncertainty quantification under non-stationary conditions, model adaptation to human-induced and climatic changes and innovative applications in large river basins or ungauged regions. This aligns with the journal’s scope of advancing hydrological science and its practical implications for global water management.
This Special Issue will welcome manuscripts that link the following themes:
- Non-stationary rainfall-runoff simulation under climate change and human activities
- Parameterization and validation of global-scale models in ungauged basins
- Integration of AI and remote-sensing data in rainfall-runoff modelling
- Uncertainty quantification for extreme event prediction
- Cross-basin comparison of hydrological responses to global environmental changes
We look forward to receiving your original research articles and reviews.
Dr. Kang Xie
Dr. Ziwei Li
Dr. Xiongpeng Tang
Dr. Maoyuan Feng
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Hydrology is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- global rainfall-runoff modelling
- non-stationary hydrology
- uncertainty quantification
- AI in hydrology
- ungauged basins
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