{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,7]],"date-time":"2025-05-07T11:36:06Z","timestamp":1746617766524,"version":"3.37.3"},"reference-count":62,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2021,6,20]],"date-time":"2021-06-20T00:00:00Z","timestamp":1624147200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52009028","51879067"],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2018YFC1508101"],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2020M671323"],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004608","name":"Natural Science Foundation of Jiangsu Province","doi-asserted-by":"publisher","award":["BK20180022"],"id":[{"id":"10.13039\/501100004608","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["B210202115 and B200204038"],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"Evapotranspiration (ET) is a vital part of the hydrological cycle and the water\u2013energy balance. To explore the characteristics of five typical remote sensing evapotranspiration datasets and provide guidance for algorithm development, we used reconstructed evapotranspiration (Recon) data based on ground and GRACE satellite observations as a benchmark and evaluated five remote sensing datasets for 592 watersheds across the continental United States. The Global Land Evaporation Amsterdam Model (GLEAM) dataset (with bias and RMSE values of 23.18 mm\/year and 106.10 mm\/year, respectively), process-based land surface evapotranspiration\/heat flux (P-LSH) dataset (bias = 22.94 mm\/year and RMSE = 114.44 mm\/year) and the Penman\u2013Monteith\u2013Leuning (PML) algorithm generated ET dataset (bias = \u221217.73 mm\/year and RMSE = 108.97 mm\/year) showed the better performance on a yearly scale, followed by the model tree ensemble (MTE) dataset (bias = 99.45 mm\/year and RMSE = 141.32 mm\/year) and the moderate-resolution imaging spectroradiometer (MODIS) dataset (bias = \u2212106.71 mm\/year and RMSE = 158.90 mm\/year). The P-LSH dataset outperformed the other four ET datasets on a seasonal scale, especially from March to August. Both PML and MTE showed better overall accuracy and could accurately capture the spatial variability of evapotranspiration in arid regions. The P-LSH and GLEAM products were consistent with the Recon data in middle-value section. MODIS and MTE had larger bias and RMSE values on a yearly scale, whereby the MODIS and MTE datasets tended to underestimate and overestimate ET values in all the sections, respectively. In the future, the aim should be to reduce bias in the MODIS and MTE algorithms and further improve seasonality of the ET estimation in the GLEAM algorithm, while the estimation accuracy of the P-LSH and MODIS algorithms should be improved in arid regions. Our analysis suggests that combining artificial intelligence algorithms or data-driven algorithms and physical process algorithms will further improve the accuracy of ET estimation algorithms and the quality of ET datasets, as well as enhancing their capacity to be applied in different climate regions.<\/jats:p>","DOI":"10.3390\/rs13122414","type":"journal-article","created":{"date-parts":[[2021,6,21]],"date-time":"2021-06-21T01:50:15Z","timestamp":1624240215000},"page":"2414","source":"Crossref","is-referenced-by-count":67,"title":["A Comprehensive Evaluation of Five Evapotranspiration Datasets Based on Ground and GRACE Satellite Observations: Implications for Improvement of Evapotranspiration Retrieval Algorithm"],"prefix":"10.3390","volume":"13","author":[{"given":"Lijun","family":"Chao","sequence":"first","affiliation":[{"name":"State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China"},{"name":"Yangtze Institute for Conservation and Development, Hohai University, Nanjing 210098, China"},{"name":"College of Agricultural Science and Engineering, Hohai University, Nanjing 210098, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5288-9372","authenticated-orcid":false,"given":"Ke","family":"Zhang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China"},{"name":"Yangtze Institute for Conservation and Development, Hohai University, Nanjing 210098, China"},{"name":"College of Hydrology and Water Resources and CMA-HHU Joint Laboratory for Hydro-Meteorological Studies, Hohai University, Nanjing 210098, China"}]},{"given":"Jingfeng","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA"}]},{"given":"Jin","family":"Feng","sequence":"additional","affiliation":[{"name":"College of Hydrology and Water Resources and CMA-HHU Joint Laboratory for Hydro-Meteorological Studies, Hohai University, Nanjing 210098, China"}]},{"given":"Mengjie","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Earth and Environmental Engineering, Columbia University, New York, NY 10027, USA"}]}],"member":"1968","published-online":{"date-parts":[[2021,6,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"392","DOI":"10.1016\/j.jhydrol.2015.09.050","article-title":"An evapotranspiration product for arid regions based on the three-temperature model and thermal remote sensing","volume":"530","author":"Xiong","year":"2015","journal-title":"J. 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