Uncertain Benefits of Using Remotely Sensed Evapotranspiration for Streamflow Estimation—Insights From a Randomized, Large-Sample Experiment

Hong Xuan Do, Hung T.T. Nguyen (), Vinh Ngoc Tran, Manh-Hung Le, Binh Quang Nguyen, Hung T. Pham, Tu Hoang Le, Doan Binh, Thanh Duc Dang, Hoang Tran and Tam V. Nguyen ()
Additional contact information
Hong Xuan Do: Nong Lam University – Ho Chi Minh City
Hung T.T. Nguyen: Columbia University
Vinh Ngoc Tran: University of Michigan
Manh-Hung Le: NASA Goddard Space Flight Center
Binh Quang Nguyen: The University of Danang - University of Science and Technology
Hung T. Pham: The University of Danang - University of Science and Technology
Tu Hoang Le: Nong Lam University – Ho Chi Minh City
Doan Binh: Vietnamese German University
Thanh Duc Dang: University of South Florida
Hoang Tran: Pacific Northwest National Laboratory
Tam V. Nguyen: Helmholtz Centre for Environmental Research - UFZ

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2024, vol. 38, issue 10, No 14, 3819-3835

Abstract: Abstract Remotely sensed evapotranspiration (ETRS) shows promise for enhancing hydrological models, especially in regions lacking in situ streamflow observations. However, model calibration studies showed conflicting results regarding the ability of ETRS products to improve streamflow simulation. Rather than relying on model calibration, here we produce the first randomized experiment that explores the full streamflow–ET skill distribution, and also the first probabilistic assessment of the value of different global ETRS products for streamflow simulation. Using 280,000 randomized SWAT (Soil and Water Assessment Tool) model runs across seven catchments and four ETRS products, we show that the relationship between ET and streamflow skills is complex, and simultaneous improvement in both skills is only possible in a limited range. Parameter sensitivity analysis indicates that the most sensitive parameters can have opposite contributions to ET and streamflow skills, leading to skill trade-offs. Conditional probability assessment reveals that models with good ET skills are likely to produce good streamflow skills, but not vice versa. We suggest that randomized experiments such as ours should be performed before model calibration to determine whether using ETRS is worthwhile, and to help in interpreting the calibration results.

Keywords: Remote sensing evapotranspiration; Streamflow simulation; Uncertainty analysis; Calibration; SWAT (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11269-024-03840-w Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:waterr:v:38:y:2024:i:10:d:10.1007_s11269-024-03840-w

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11269

DOI: 10.1007/s11269-024-03840-w

Access Statistics for this article

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA) is currently edited by G. Tsakiris

More articles in Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA) from Springer, European Water Resources Association (EWRA)
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().