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Evaluation of Using Remote Sensing Evapotranspiration Data in SWAT

Author

Listed:
  • Prem B. Parajuli

    (Mississippi State University)

  • Priyantha Jayakody

    (New South Wales Department of Primary Industries)

  • Ying Ouyang

    (USDA Forest Service)

Abstract

This study applied a time series evapotranspiration (ET) data derived from the remote sensing to evaluate Soil and Water Assessment Tool (SWAT) model calibration, which is a unique method. The SWAT hydrologic model utilized monthly stream flow data from two US Geological Survey (USGS) stations within the Big Sunflower River Watershed (BSRW) in Northwestern, Mississippi. Surface energy balance algorithm for land (SEBAL), which utilized MODerate Resolution Imaging Spectro-radiometer (MODIS) to generate monthly ET time series data images were evaluated with the SWAT model. The SWAT hydrological model was calibrated and validated using monthly stream flow data with the default, flow only, ET only, and flow-ET modeling scenarios. The flow only and ET only modeling scenarios showed equally good model performances with the coefficient of determination (R2) and Nash Sutcliffe Efficiency (NSE) from 0.71 to 0.86 followed by flow-ET only scenario with the R2 and NSE from 0.66 to 0.83, and default scenario with R2 and NSE from 0.39 to 0.78 during model calibration and validation at Merigold and Sunflower gage stations within the watershed. The SWAT model over-predicted ET when compared with the Modis-based ET. The ET-based ET had the closest ET prediction (~8% over-prediction) as followed by flow-ET-based ET (~16%), default-based ET (~27%) and flow-based ET (~47%). The ET-based modeling scenario demonstrated consistently good model performance on streamflow and ET simulation in this study. The results of this study demonstrated use of Modis-based remote sensing data to evaluate the SWAT model streamflow and ET calibration and validation, which can be applied in watersheds with the lack of meteorological data.

Suggested Citation

  • Prem B. Parajuli & Priyantha Jayakody & Ying Ouyang, 2018. "Evaluation of Using Remote Sensing Evapotranspiration Data in SWAT," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(3), pages 985-996, February.
    • Handle: RePEc:spr:waterr:v:32:y:2018:i:3:d:10.1007_s11269-017-1850-z
    DOI: 10.1007/s11269-017-1850-z
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    References listed on IDEAS

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    1. Santosh Thampi & Kolladi Raneesh & T. Surya, 2010. "Influence of Scale on SWAT Model Calibration for Streamflow in a River Basin in the Humid Tropics," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(15), pages 4567-4578, December.
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    6. Abdullah O. Dakhlalla & Prem B. Parajuli, 2016. "Evaluation of the Best Management Practices at the Watershed Scale to Attenuate Peak Streamflow Under Climate Change Scenarios," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(3), pages 963-982, February.
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    Cited by:

    1. Sangchul Lee & Junyu Qi & Hyunglok Kim & Gregory W. McCarty & Glenn E. Moglen & Martha Anderson & Xuesong Zhang & Ling Du, 2021. "Utility of Remotely Sensed Evapotranspiration Products to Assess an Improved Model Structure," Sustainability, MDPI, vol. 13(4), pages 1-18, February.
    2. Farzaneh Najimi & Babak Aminnejad & Vahid Nourani, 2023. "Assessment of Climate Change’s Impact on Flow Quantity of the Mountainous Watershed of the Jajrood River in Iran Using Hydroclimatic Models," Sustainability, MDPI, vol. 15(22), pages 1-21, November.
    3. Gianluigi Busico & Maria Margarita Ntona & Sílvia C. P. Carvalho & Olga Patrikaki & Konstantinos Voudouris & Nerantzis Kazakis, 2021. "Simulating Future Groundwater Recharge in Coastal and Inland Catchments," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(11), pages 3617-3632, September.
    4. Lee, Sangchul & Qi, Junyu & McCarty, Gregory W. & Anderson, Martha & Yang, Yun & Zhang, Xuesong & Moglen, Glenn E. & Kwak, Dooahn & Kim, Hyunglok & Lakshmi, Venkataraman & Kim, Seongyun, 2022. "Combined use of crop yield statistics and remotely sensed products for enhanced simulations of evapotranspiration within an agricultural watershed," Agricultural Water Management, Elsevier, vol. 264(C).
    5. Manfei Zhang & Xiao Wang & Weibo Zhou, 2021. "Effects of Water-Saving Irrigation on Hydrological Cycle in an Irrigation District of Northern China," Sustainability, MDPI, vol. 13(15), pages 1-19, July.
    6. Sakine Koohi & Asghar Azizian & Luca Brocca, 2022. "Calibration of a Distributed Hydrological Model (VIC-3L) Based on Global Water Resources Reanalysis Datasets," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(4), pages 1287-1306, March.

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