Position paper: Domain knowledge-driven intelligentization of watershed modeling and scenario analysis for precise watershed management

Watershed modeling and scenario analysis based on the simulation–optimization framework, which comprehensively represents the most (if not all) of characteristics of geographical information science and geography, is crucial to support scientific decision-making for precise watershed management with increasing practical need. Meanwhile, it is still highly complex to be conducted in a way being not only scientific reasonable but also highly accessible for wide real applications with diverse users, especially those non-expert stakeholders. To narrow such a so-called “digital divide” between specialized modeling and real applications mainly with non-experts, this position paper advocates that intelligentization of watershed modeling and scenario analysis is the key. This position paper presents the state-of-the-art research landscape of intelligent methods for watershed modeling and scenario analysis, and particularly advocates that research on domain knowledge-driven intelligent methods is emerging and promising. • Watershed modeling and scenario analysis using simulation–optimization framework is crucial for precise watershed management. • The simulation–optimization framework is highly complex for real applications, especially for those non-expert stakeholders. • Intelligentization of watershed modeling and scenario analysis is key to narrow such a “digital divide”. • The state-of-the-art research landscape of intelligent methods for watershed modeling and scenario analysis is presented. • We particularly advocate the domain knowledge-driven intelligent methods.

Authors

Institutions

Publication Details

Journal
Information Geography
Published
2025-04-18
DOI
https://doi.org/10.1016/j.infgeo.2025.100016
Citations
2
Primary Topic
Hydrology and Watershed Management Studies
Type
article
Field-Weighted Citation Impact
1.63

Funders

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article

Position paper: Domain knowledge-driven intelligentization of watershed modeling and scenario analysis for precise watershed management

Liang‐Jun Zhu, A‐Xing Zhu, Cheng‐Zhi Qin
2 citations
Information Geography
Hydrology and Watershed Management Studies
1.63
article

Position paper: Domain knowledge-driven intelligentization of watershed modeling and scenario analysis for precise watershed management

Liang‐Jun Zhu, A‐Xing Zhu, Cheng‐Zhi Qin
article en
2 citations

Abstract

Watershed modeling and scenario analysis based on the simulation–optimization framework, which comprehensively represents the most (if not all) of characteristics of geographical information science and geography, is crucial to support scientific decision-making for precise watershed management with increasing practical need. Meanwhile, it is still highly complex to be conducted in a way being not only scientific reasonable but also highly accessible for wide real applications with diverse users, especially those non-expert stakeholders. To narrow such a so-called “digital divide” between specialized modeling and real applications mainly with non-experts, this position paper advocates that intelligentization of watershed modeling and scenario analysis is the key. This position paper presents the state-of-the-art research landscape of intelligent methods for watershed modeling and scenario analysis, and particularly advocates that research on domain knowledge-driven intelligent methods is emerging and promising. • Watershed modeling and scenario analysis using simulation–optimization framework is crucial for precise watershed management. • The simulation–optimization framework is highly complex for real applications, especially for those non-expert stakeholders. • Intelligentization of watershed modeling and scenario analysis is key to narrow such a “digital divide”. • The state-of-the-art research landscape of intelligent methods for watershed modeling and scenario analysis is presented. • We particularly advocate the domain knowledge-driven intelligent methods.

Information GeographyVol. 1(1)
University of Wisconsin–Madison (US), Chinese Academy of Sciences (CN), Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application (CN), Institute of Geographic Sciences and Natural Resources Research (CN), University of Chinese Academy of Sciences (CN)
National Natural Science Foundation of China, Chinese Academy of Sciences, State Key Laboratory of Resources and Environmental Information System, National Key Research and Development Program of China, Key Research and Development Projects of Shaanxi Province
Climate action
Openalex Percentile: Top 17%
Hydrology and Watershed Management Studies
1.63
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