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Based on temperature data from 24 global climate models (GCMs) in the Coupled Model Intercomparison Project Phase 6 (CMIP6), this study developed a multi-model ensemble based on delta statistical downscaling with multiple interpolation methods and evaluation indicators to predict the spatial and temporal evolution trends of ET0 in the Yellow River Basin (YRB) under four emission scenarios (SSP126, SSP245, SSP370, and SSP585) for the near- (2022\u20132040), mid- (2041\u20132060), and long- (2081\u20132100) term future. Results demonstrate that regional data generated based on delta statistical downscaling had good simulation performance for the monthly mean, maximum, and minimum temperatures in the YRB, and the developed multi-model ensemble had better simulation capability than any single model. Compared to the historical period (1901\u20132014), the annual ET0 showed a highly significant increase for different future emission scenarios, and the increase is faster with increasing radiative forcing. The first main cycle of ET0 change was 52, 53, 60, and 48 years for the SSP126, SSP245, SSP370, and SSP585, respectively. ET0 in the YRB had positive values for EOF1 under all four emission scenarios, responding to a spatially consistent trend across the region. Compared to the historical period, the spatial distribution of ET0 under different future emission scenarios was characterized by being larger in the west and smaller in the east. As the radiative forcing scenario increased and time extended, ET0 significantly increased, with a maximum variation of 112.91% occurring in the western part of the YRB in the long-term future under the SSP585 scenario. This study can provide insight into the water cycle patterns of watersheds and scientific decision support for relevant departments to address the challenges of climate change.<\/jats:p>","DOI":"10.3390\/rs14225674","type":"journal-article","created":{"date-parts":[[2022,11,10]],"date-time":"2022-11-10T21:33:02Z","timestamp":1668115982000},"page":"5674","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Prediction of Future Spatial and Temporal Evolution Trends of Reference Evapotranspiration in the Yellow River Basin, China"],"prefix":"10.3390","volume":"14","author":[{"given":"Shengqi","family":"Jian","sequence":"first","affiliation":[{"name":"Yellow River Laboratory, Zhengzhou University, Zhengzhou 450001, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aoxue","family":"Wang","sequence":"additional","affiliation":[{"name":"Yellow River Laboratory, Zhengzhou University, Zhengzhou 450001, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chengguo","family":"Su","sequence":"additional","affiliation":[{"name":"Yellow River Laboratory, Zhengzhou University, Zhengzhou 450001, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kun","family":"Wang","sequence":"additional","affiliation":[{"name":"China Institute of Water Resources and Hydropower Research, Beijing 100038, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,11,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Nooni, I.K., Hagan, D.F.T., Wang, G., Ullah, W., Lu, J., Li, S., Dzakpasu, M., Prempeh, N.A., and Lim Kam Sian, K.T.C. 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