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A review of integrated surface-subsurface numerical hydrological models

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Abstract

Hydrological modeling, leveraging mathematical formulations to represent the hydrological cycle, is a pivotal tool in representing the spatiotemporal dynamics and distribution patterns inherent in hydrology. These models serve a dual purpose: they validate theoretical robustness and applicability via observational data and project future trends, thereby bridging the understanding and prediction of natural processes. In rapid advancements in computational methodologies and the continuous evolution of observational and experimental techniques, the development of numerical hydrological models based on physically-based surface-subsurface process coupling have accelerated. Anchored in micro-scale conservation principles and physical equations, these models employ numerical techniques to integrate surface and subsurface hydrodynamics, thus replicating the macro-scale hydrological responses of watersheds. Numerical hydrological models have emerged as a leading and predominant trend in hydrological modeling due to their explicit representation of physical processes, heightened by their spatiotemporal resolution and reliance on interdisciplinary integration. This article focuses on the theoretical foundation of surface-subsurface numerical hydrological models. It includes a comparative and analytical discussion of leading numerical hydrological models, encompassing model architecture, numerical solution strategies, spatial representation, and coupling algorithms. Additionally, this paper contrasts these models with traditional hydrological models, thereby delineating the relative merits, drawbacks, and future directions of numerical hydrological modeling.

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Acknowledgements

The Grammarly (https://Grammarly.com) and GPT-4 (https://chat.openai.com) assisted only in language refinement. This work was supported by the National Natural Science Foundation of China (Grant Nos. 41930759, 42325502), the West Light Foundation of the Chinese Academy of Sciences (Grant No. xbzg-zdsys-202215), the Chinese Academy Sciences Talents Program, National Cryosphere Desert Data Center, the Qinghai Key Laboratory of Disaster Prevention (Grant No. QFZ-2021-Z02), and 2023 First Batch of Science and Technology Plan Projects of Lanzhou City (Grant No. 2023-1-49).

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Authors and Affiliations

  1. Key Laboratory of Cryospheric Science and Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, China

    Lele Shu, Hao Chen, Xianhong Meng & Yan Chang

  2. College of Water Sciences, Beijing Normal University, Beijing, 100038, China

    Litang Hu

  3. School of Water and Environment, Chang’an University, Xi’an, 710064, China

    Wenke Wang

  4. College of Hydrology and Water Resources, Hohai University, Nanjing, 210098, China

    Longcang Shu

  5. State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, 210008, China

    Xuan Yu

  6. Department of Civil and Environmental Engineering, Pennsylvania State University, State College, PA, 16801, USA

    Christopher Duffy

  7. Department of Earth and Environmental Science, School of Human Settlements and Civil Engineering, Xi’an Jiaotong University, Xi’an, 710049, China

    Yingying Yao

  8. Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, 100101, China

    Donghai Zheng

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Shu, L., Chen, H., Meng, X. et al. A review of integrated surface-subsurface numerical hydrological models. Sci. China Earth Sci. 67, 1459–1479 (2024). https://doi.org/10.1007/s11430-022-1312-7

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