University of Oulu

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.

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

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Author: Panchanathan, Anandharuban1; Oussalah, Mourad1; Torabi Haghighi, Ali2
Organizations: 1Department of Information Technology and Electrical Engineering, University of Oulu, P.O. Box 4300, 90014 Oulu, Finland
2Water Resources and Environmental Engineering, University of Oulu, P.O. Box 4300, 90014 Oulu, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.2 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2022
Publish Date: 2023-03-31


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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Series: IEEE International Symposium on Geoscience and Remote Sensing
ISSN: 2153-6996
ISSN-E: 2153-7003
ISSN-L: 2153-6996
ISBN: 978-1-6654-2792-0
ISBN Print: 978-1-6654-2793-7
Pages: 7875 - 7878
DOI: 10.1109/IGARSS46834.2022.9884211
Host publication: IGARSS 2022 : 2022 IEEE International Geoscience and Remote Sensing Symposium
Conference: International Geoscience and Remote Sensing Symposium
Type of Publication: A4 Article in conference proceedings
Field of Science: 113 Computer and information sciences
Funding: This work is partly supported Waterline project which is an EU CHIST-ERA-2019-funded research project under the Grant reference number 344750.
Academy of Finland Grant Number: 344750
Detailed Information: 344750 (Academy of Finland Funding decision)
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