International Journal of Environmental and Rural Development
Online ISSN : 2433-3700
Print ISSN : 2185-159X
ISSN-L : 2185-159X
Estimation of Long-term River Discharge in Forested Watershed in Snowy Region by SWAT
SHOTARO KIKUCHIHIROMU OKAZAWASARVESH MASKEYSERGIO AZAEL MAY CUEVASMAKOTO OBASHOGO NAKAMURASEIJI HAYASHI
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2022 Volume 13 Issue 2 Pages 105-112

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Abstract

Utilizing a hydrological model for analyzing the hydrological cycle throughout a river basin is an effective method to assess the impacts of climate change on water resource management, flood control, and agriculture. Although there are various hydrological models developed, in this study, Soil and Water Assessment Tool plus (SWAT+) is used as it is widely used and predicts the impacts of land use management in watershed management. SWAT+ is a complex quasi−physically based water quality model relying on numerous input files and parameters, thus this poses a great challenge when attempting to set up the model manually, and there is a lack of information regarding the validation of SWAT+'s of performance for snow accumulation and melting processes. The objective of this study is to estimate long-term streamflow in forested watershed in snowy region using SWAT+, and to verify the accuracy of the estimation and to confirm the improvement of the accuracy by adjusting parameters. In order to improve the accuracy of simulation, “the saturated hydraulic conductivity of soil layer” and “the available water capacity of soil layer” were adjusted for parameter of soil moisture content, moreover, we adjusted parameter of temperature of “snowfall” and “snowmelt”. Finally, “the time of lateral flow travel” which is difficult to measure was calibrated using the auto-calibration of SWAT+. As the results, it was difficult to achieve high accuracy in predicting river discharge with the default parameters of SWAT+, but some months (May-Oct) could be accurately predicted after adjusting parameters using measured data and conducting the auto-calibration. On the other hand, simulations during snowfall and snowmelt term (Dec-Mar) were less accurate and need to set more detailed conditions.

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© 2022 Institute of Environmental Rehabilitation and Conservation Research Center
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