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Toward Selection and Improving the Performance of the SWAT Hydrological Model: A Review

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Recent Advances in Civil Engineering for Sustainable Communities (IACESD 2023)

Abstract

In watershed hydrology, it is challenging to physically monitor various aspects that influence the hydrological processes. To quantify these watershed processes in a basin with changing spatial and temporal characteristics, public domain hydrological models incorporating inverse modeling are considered. The quantified processes aid in the decision-making, design, and development of hydrological units. But the first confusion that arises in modeling these processes is which hydrological model should be considered and what methods should be adopted to quantify the best hydrological parameters. Even though a best model is considered hydrologists assumption of parameter insensitivity and uniqueness over varying climatic conditions and space, the conditionality of model calibration with unique technique and performance indicator is prone to the poor performance of the model. Betterment of model performance can be achieved by switching parameters sensitive to varying climatic conditions and reprieving the conditionality of model calibration. Hence, the purpose of this paper is to review (i) different hydrological models available around the globe, (ii) the selection criteria for the hydrological model and the superiority of the SWAT model, (iii) the description of the SWAT model, followed by sensitivity analysis and calibration techniques involved in SWAT output, and (iv) summaries of season-based SWAT evaluation.

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Correspondence to Hanumapura Kumaraswamy Yashas Kumar .

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Kumar, H.K.Y., Kumble, V. (2024). Toward Selection and Improving the Performance of the SWAT Hydrological Model: A Review. In: Menon, N.V.C., Kolathayar, S., Rodrigues, H., Sreekeshava, K.S. (eds) Recent Advances in Civil Engineering for Sustainable Communities. IACESD 2023. Lecture Notes in Civil Engineering, vol 459. Springer, Singapore. https://doi.org/10.1007/978-981-97-0072-1_28

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  • DOI: https://doi.org/10.1007/978-981-97-0072-1_28

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