the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Quantifying evapotranspiration in Nepal using multiple constraints
Abstract. Evapotranspiration (ET) research is rare but is essential for understanding the impacts of climate change and forest management on water resource in Nepal. This study assessed eight global remote sensing-based ET products including GLASS, GLEAM, PMLv2, REA, PEW, ETmonitor, SSEBop and SEBAL, and an ecohydrolgical model, WaSSI using locally constructed 12 watershed-scale water balance datasets. Additionally, the Budyko framework was employed to constrain ET estimates. We found serious water imbalance issues in the hydrometeorological records for medium-sized basins where measured streamflow exceeded precipitation (P) and ET/P values substantively deviated from the theoretical Budyko curve. The accuracy of the remote sensing ET products varies at selected watersheds with large elevation gradients. We found considerable modeling errors with ET overestimated, especially in high elevations among these remote sensing products. Nationally, the eight remote sensing models do not agree on the temporal trends for annual ET over the past two decades. We identified potential causes to the large errors of the ET products: 1) meteorological input data used to drive the potential ET model and ET model, 2) model algorithms causing overestimates of ET at high elevations, and 3) underestimation of precipitation and overestimation of leaf area index at high elevations. We estimated mean annual ET for High Himalya, High Mountain, Middle Mountain, Low Mountain, Terai Plain as 257 mm, 544 mm, 764 mm, 844 mm and 892 mm, respectively. This study underscores the importance of ground measuring and integrated modeling of water balances in constraining remotely estimated ET in the Himalya region.
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Status: open (until 07 Oct 2026)
- RC1: 'Comment on egusphere-2026-4161', Anonymous Referee #1, 04 Sep 2026 reply
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This study evaluates the applicability of global ET products in Nepal's complex terrain using watershed water balance, the Budyko framework, and ecohydrological modeling. The research finds significant differences between high- and low-elevation regions and identifies water-balance imbalances in certain watersheds. The findings are interesting, but several important issues remain. A substantial revision is recommended.
1. Why focus on ET in Nepal? Its importance is not clearly demonstrated. From an ecohydrological perspective, ET contributes only a small fraction in this high-altitude Nepalese region, at least currently and historically.
2. Why are only remote sensing ET data used? Multi-source data could be incorporated.
3. Different PET calculation methods significantly affect the Budyko relationship, potentially leading to biased conclusions in watershed selection and comparative assessment. The Hamon algorithm and Penman-Monteith FAO-56 differ substantially.
4. Are SSEBop and SSEBop V6 the same model in Table 1?
5. WaSSI cannot serve as ground truth, including its national-scale partitioned ET values. Is there no site measurement at all for this region?
6. REA is not a satellite product; it is a data fusion product.
7. Equation 2 is missing the variable i.
8. The time periods for water balance data, different remote sensing products, and WaSSI do not align.
9. Spatial scales are mismatched. It is recommended to uniformly aggregate all data to either the watershed scale or the coarsest common resolution.
10. The time span used for trend analysis is too short.
11. Numerous unit and language errors exist: "elevation <1500 mm" should be m; "annual ET 600–1100 m" should be mm. Other spelling errors include "Himalya," "Lessor Himalya," "Mann-Kendell," and "eitht."
12. It is suggested to rewrite the abstract to clearly distinguish observational results, model outputs, and mechanistic assumptions.
13. Quantitative analysis of bias sources is lacking.
14. GLEAM and SSEBop results appear to show little overestimation in high-altitude regions, which differ from the authors' conclusion.