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Spatio-Temporal Sensitivity Analysis for Flow and Sediment Load Modeling Using SWAT in a Heterogeneous Agricultural Watershed

Author

Listed:
  • Mansour Talebizadeh

    (Independent Researcher)

  • Daniel N. Moriasi

    (USDA-ARS National Laboratory for Agriculture and The Environment)

  • Jean L. Steiner

    (Kansas State University)

  • Prasanna H. Gowda

    (USDA-ARS Southeast Area)

  • Patrick J. Starks

    (USDA-ARS Oklahoma and Central Plains Agricultural Research Center)

  • Alan J. Verser

    (USDA-ARS Oklahoma and Central Plains Agricultural Research Center)

Abstract

Sensitivity analysis can be used to identify model parameters driving simulation outputs. However, sensitivity analysis is usually performed on an aggregated output or a model performance metric, calculated over a simulation period. This paper studies the spatial and temporal variations of the SWAT model parameter sensitivities for flow and sediment load modeling in an agricultural watershed. The Willow Creek Sub-watershed in central Oklahoma, characterized by diverse land use and agricultural management, was used as the case study. Parameter uncertainties at the hydrologic response unit (HRU) level were characterized through probability distributions, while parameter sensitivities were calculated using Standardized Regression Coefficients (SRCs) at a daily timescale. Significant temporal variations were observed for different parameters, influenced by changes in climate and management conditions. Additionally, the results indicated certain parameters exhibited high sensitivities only during specific periods, while others maintained high sensitivities throughout most of the simulation period. This study underscores the necessity of integrating both temporal and spatial sensitivity analyses to capture the dynamic nature of parameter sensitivities at a finer level of spatial granularity than the watershed scale.

Suggested Citation

  • Mansour Talebizadeh & Daniel N. Moriasi & Jean L. Steiner & Prasanna H. Gowda & Patrick J. Starks & Alan J. Verser, 2025. "Spatio-Temporal Sensitivity Analysis for Flow and Sediment Load Modeling Using SWAT in a Heterogeneous Agricultural Watershed," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 39(5), pages 2281-2298, March.
    • Handle: RePEc:spr:waterr:v:39:y:2025:i:5:d:10.1007_s11269-024-04066-6
    DOI: 10.1007/s11269-024-04066-6
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    References listed on IDEAS

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    1. Yaoze Liu & Indrajeet Chaubey & Laura C. Bowling & Vincent F. Bralts & Bernard A. Engel, 2016. "Sensitivity and Uncertainty Analysis of the L-THIA-LID 2.1 Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(13), pages 4927-4949, October.
    2. C. Giudicianni & I. Di Cicco & A. Di Nardo & R. Greco, 2024. "Variance-based Global Sensitivity Analysis of Surface Runoff Parameters for Hydrological Modeling of a Real Peri-urban Ungauged Basin," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 38(8), pages 3007-3022, June.
    3. Wei Li & Rui Song & Muhammad Awais & Leilei Ji & Shuo Li & Mingjiang Liu & Tao Lang & Handong Qi, 2024. "Global Sensitivity Analysis of Crop Parameters Based on AquaCrop Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 38(6), pages 2039-2058, April.
    4. Majid Hashemi & Najmeh Mahjouri, 2022. "Global Sensitivity Analysis-based Design of Low Impact Development Practices for Urban Runoff Management Under Uncertainty," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(9), pages 2953-2972, July.
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