Assessment of reservoir inflow prediction through constraining SWAT parameters to remotely sensed ET data in data scarce region of Chennai, India

Panchanathan, Anandharuban; Oussalah, Mourad; Torabi Haghighi, Ali (2022-09-28)
 
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https://doi.org/10.1109/IGARSS46834.2022.9884211

Panchanathan, Anandharuban
Oussalah, Mourad
Torabi Haghighi, Ali
Institute of Electrical and Electronics Engineers
28.09.2022

A. Panchanathan, M. Oussalah and A. T. Haghighi, "Assessment of Reservoir Inflow Prediction Through Constraining SWAT Parameters to Remotely Sensed ET Data in Data Scarce Region of Chennai, India," IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, Kuala Lumpur, Malaysia, 2022, pp. 7875-7878, doi: 10.1109/IGARSS46834.2022.9884211.

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doi:https://doi.org/10.1109/IGARSS46834.2022.9884211
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Abstract

Prediction of reservoir inflow is an important aspect of water supply management in an urbanized region. In this regard, this study aims to improve the reservoir inflow prediction using the calibration of the MODIS (Moderate resolution Imaging Spectroradiometer) evapotranspiration (ET) data in addition to the streamflow in the SWAT (Soil and Water Assessment Tool) model. The results of this study show that constraining SWAT parameters to the ET combined with streamflow helps to improve the simulation of ET. Thereby, it enhances the representation of vertical fluxes in regional hydrology. The reservoir inflow was calibrated with streamflow alone with Nash-Sutcliffe Efficiency (NSE) of 0.63, whereas the inclusion of ET provides an NSE of 0.59. However, the simulation of ET has improved by 10%. The results of this study demonstrate that the inclusion of ET data helps to improve the simulation of hydrologic processes in the region.

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