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day −1 ) by 2.5104 × 10 6 J kg −1 . 3) USGS runoff Monthly runoff data for the Texas–Gulf region (area-averaged runoff) from the U.S. Geological Survey (USGS) were used for evaluating modeled river flow, assuming all surface and subsurface model water eventually makes to the river system ( Seaber et al. 1987 ). The product was derived from flow data from the USGS river gauges with the area-weighted method ( Brakebill et al. 2011 ). Data were obtained from the USGS WaterWatch website ( https
day −1 ) by 2.5104 × 10 6 J kg −1 . 3) USGS runoff Monthly runoff data for the Texas–Gulf region (area-averaged runoff) from the U.S. Geological Survey (USGS) were used for evaluating modeled river flow, assuming all surface and subsurface model water eventually makes to the river system ( Seaber et al. 1987 ). The product was derived from flow data from the USGS river gauges with the area-weighted method ( Brakebill et al. 2011 ). Data were obtained from the USGS WaterWatch website ( https
valley of California, and the southeast United States. Comparatively, the impacts of assimilation over the Northeast and much of the western United States on drought are marginal. Note that many of the areas with the most improvement in correlation to the USDM are cropland in the UMD land cover classification. The more marginal improvements in cropland locations along and east of the Mississippi River are likely due to a combination of fewer drought events in the USDM, lower seasonality of monthly
valley of California, and the southeast United States. Comparatively, the impacts of assimilation over the Northeast and much of the western United States on drought are marginal. Note that many of the areas with the most improvement in correlation to the USDM are cropland in the UMD land cover classification. The more marginal improvements in cropland locations along and east of the Mississippi River are likely due to a combination of fewer drought events in the USDM, lower seasonality of monthly
Colorado River basin was caused primarily by pervasive low-precipitation anomalies across the upper Colorado River basin, and the drought was also exacerbated by negative precipitation anomalies in several of the most productive headwater basins ( Xiao et al. 2018 ). Our findings are consistent with Mo and Lettenmaier (2018) . They used an integrated drought index (IDI) and found that the north-central and northeast subregions of CONUS have become wetter while the southwest has become drier. The
Colorado River basin was caused primarily by pervasive low-precipitation anomalies across the upper Colorado River basin, and the drought was also exacerbated by negative precipitation anomalies in several of the most productive headwater basins ( Xiao et al. 2018 ). Our findings are consistent with Mo and Lettenmaier (2018) . They used an integrated drought index (IDI) and found that the north-central and northeast subregions of CONUS have become wetter while the southwest has become drier. The
-020-10234-7 He , J. , X. Bian , Y. Fu , and Y. Qin , 2012 : Research on water consumption and its law of main crops in west Liaohe River plain . Jieshui Guan’gai , 11 , 1 – 4 . Hirschi , M. , and Coauthors , 2011 : Observational evidence for soil-moisture impact on hot extremes in southeastern Europe . Nat. Geosci. , 4 , 17 – 21 , https://doi.org/10.1038/ngeo1032 . 10.1038/ngeo1032 Huang , P. M. , Y. Li , and M. E. Sumner , 2011 : Handbook of Soil Sciences: Properties and
-020-10234-7 He , J. , X. Bian , Y. Fu , and Y. Qin , 2012 : Research on water consumption and its law of main crops in west Liaohe River plain . Jieshui Guan’gai , 11 , 1 – 4 . Hirschi , M. , and Coauthors , 2011 : Observational evidence for soil-moisture impact on hot extremes in southeastern Europe . Nat. Geosci. , 4 , 17 – 21 , https://doi.org/10.1038/ngeo1032 . 10.1038/ngeo1032 Huang , P. M. , Y. Li , and M. E. Sumner , 2011 : Handbook of Soil Sciences: Properties and
definitions as to the spatial coverage of these two regions for various research purposes. For example, Erfanian and Fu (2019) used the region of 105°–95°W, 30°–39°N for the southern Great Plains and 105°–95°W, 39°–48°N for the northern Great Plains. A more traditionally recognized spatial coverage for the Great Plains is that of Shafer et al. (2014) which spans a large area west of the Mississippi River tallgrass prairie and east of the Rocky Mountains. Here we use the region of 105°–95°W, 35°–47°N
definitions as to the spatial coverage of these two regions for various research purposes. For example, Erfanian and Fu (2019) used the region of 105°–95°W, 30°–39°N for the southern Great Plains and 105°–95°W, 39°–48°N for the northern Great Plains. A more traditionally recognized spatial coverage for the Great Plains is that of Shafer et al. (2014) which spans a large area west of the Mississippi River tallgrass prairie and east of the Rocky Mountains. Here we use the region of 105°–95°W, 35°–47°N
