Evaluation of satellite-retrieved evapotranspiration based on a nonparametric approach over an arid region

ABSTRACT

Daily evapotranspiration (ET) controlled by latent energy (LE) is an important variable used in the study of hydrology, meteorology, and ecology. A constant solar radiation ratio approach was introduced to the LE retrieval algorithm based on a nonparametric ET approach to upscale instantaneous LE temporally. On the basis of the proposed algorithm, this study retrieved the daily and eight-day LE using Moderate-resolution Imaging Spectroradiometer (MODIS) and China Meteorological Administration Land Data Assimilation System products and evaluated the daily and eight-day LE retrieval by using the ground observations and MOD16 product in Zhangye City during 25 June to 15 September 2012. Results show that the temporal-spatial distribution of retrieved result was reliable. The retrieved daily/eight-day LE could capture the dynamic change of ground observations, whereas the MOD16 LE was invalid. The retrieved daily (eight-day) LE was underestimated at all four (two) sites, with bias, root mean square error, and R² of −7.9 to −2.2 W m⁻² (approximately −5 W m⁻²), 19.8 to 39.0 W m⁻² (approximately 10 W m⁻²), and 0.72 to 0.84 (approximately 0.9), respectively. The proposed approach showed more satisfactory performance than the triangle approach under clear sky condition. The eight-day LE retrieval was considerably better than MOD16 LE and had (no/slight) influence on MOD16 LE (eight-day retrieval). In addition, the accurate estimation of net radiation, soil heat flux, land surface temperature, and air temperature could aid in improving LE retrieval. Future studies would focus on the improvement of the retrieval algorithm, input accuracy, and residuals.

Acknowledgements

This study is supported by the National Nature Science Foundation of China (41701487; 91437220), by the Fundamental Research Funds for the Central Universities of China (2019B02714), National Key Research and Development Program of China (2018YFC0407903), the Open Research Fund of Jiangsu Key Laboratory of Resources and Environmental Information Engineering, CUMT and the Science and the Water Affairs Technology Project of Nanjing. We thank the Cold and Arid Regions Science Data Center at Lanzhou for providing observation data (http://westdc.westgis.ac.cn). We also thank the National Satellite Meteorological Center, China Meteorological Administration for providing CLDAS data. In addition, we thank Professor Liu S. M. and Dr Xu Z. W. for their kind assistance in providing field data and help in field visit.

Disclosure statement

No potential conflict of interest was reported by the authors.

Author contributions

Xin Pan designed and performed the experiments, and wrote this paper. Chaoshuai You analyzed a part of the data. Yuanbo Liu proposed the main idea. Chunxiang Shi and Shuai Han contributed materials. Yingbao Yang and Jia Hu made some comments on the manuscript.

List of symbols

G_s – Surface soil heat flux

LE – Latent heat flux

NDVI – Normalized difference vegetation index

R_n – Net surface radiation

R_sd – Downwelling shortwave radiation

R_ld – Downwelling longwave radiation

T_a – Near-surface air temperature

T_c – Cloud temperature

T_s – Land surface temperature

$T_{\mathrm{s}}^i$ – T_s in a pixel

$T_{\mathrm{m}\mathrm{a}\mathrm{x}}^i$ – Highest temperature for each NDVI interval

$T_{\mathrm{m}\mathrm{i}\mathrm{n}}^i$ – Lowest temperature for each NDVI interval

e₀ – Water vapour pressure

p – Near-surface air pressure

q – Relative humidity

$\varphi$ – P-T coefficient

${\varphi }_{\mathrm{m}\mathrm{a}\mathrm{x}}$ – P-T coefficient of 1.26

Δ – Slope of saturated vapour pressure at temperature T_a

α – Surface albedo

α₁ – Nadir Bidirectional Reflectance Distribution Function (BRDF)-adjusted albedos in bands 1 of Moderate-resolution Imaging Spectroradiometer (MODIS)

α₂ – Nadir BRDF-adjusted albedos in bands 2 of MODIS

α₃ – Nadir BRDF-adjusted albedos in bands 3 of MODIS

α₄ – Nadir BRDF-adjusted albedos in bands 4 of MODIS

α₅ – Nadir BRDF-adjusted albedos in bands 5 of MODIS

α₇ – Nadir BRDF-adjusted albedos in bands 7 of MODIS

γ – Psychometric constant

ε – Land surface emissivity

ε_a – Air emissivity

ε_c – Cloud emissivity

ε₃₁ – Emissivity in bands 31 of MODIS

ε₃₂ – Emissivity in bands 32 of MODIS

σ – Stefan-Boltzmann’s constant

VI – Vegetation index

Additional information

Funding

This work was supported by the National Nature Science Foundation of China [41701487; 91437220], the Fundamental Research Funds for the Central Universities of China [2019B02714], the National Key Research and Development Program of China [2018YFC0407903], the Open Research Fund of Jiangsu Key Laboratory of Resources and Environmental Information Engineering, CUMT [JS201902] and the Science and the Water Affairs Technology Project of Nanjing.