Journal: Scientific Reports

Article Title: US Power Production at Risk from Water Stress in a Changing Climate

doi: 10.1038/s41598-017-12133-9

Figure Lengend Snippet: Spatial profile of water scarcity and stream temperature over near-term projection horizons. (A) Projected changes in low surface runoff (10 th percentile of all climate realizations [see Methods]) during 2006–2020 (top), 2011–2025 (middle), and 2021–2035 (bottom), relative to current estimates (1991–2005). Calculations are performed in MATLAB 2015a (Version 8.5, http://www.mathworks.com ) [Software]. Shades of blue show positive changes in future freshwater availability relative to current estimates, but they do not necessarily indicate water surplus. (B) Same as in ( A ) but for projected changes in high stream temperature (90 th percentile of all climate simulations). The red (blue)-colored upward (downward) triangles in ( B ) indicate increase (decrease) in stream temperature. ( C ) Same as in (A ) but for projected changes in 2-meter surface air temperature (90 th percentile). Spatial patterns of current estimates are shown in Figures , and . Maps are generated using MATLAB 2015a (Version 8.5, http://www.mathworks.com ) and ArcGIS Desktop (Version 10.3.1, http://www.esri.com ). Finally, all these maps are organized and labelled in Adobe Photoshop CS Desktop (Version 5.1, https://www.adobe.com ) [Software].

Article Snippet: Figures are generated using MATLAB 2015a (Version 8.5, http://www.mathworks.com ) [Software].

Techniques: Software, Generated

Journal: Scientific Reports

Article Title: US Power Production at Risk from Water Stress in a Changing Climate

doi: 10.1038/s41598-017-12133-9

Figure Lengend Snippet: Association between indicators of water stress. ( A – D ) Correlation coefficient between monthly surface runoff and stream temperature as measured by Kendall’s tau at 145 USGS gauge stations for (A) current (1991–2005) and ( B – D ) future time horizons (2006–2035). Correlations are statistically significant at 5% at all gauge stations for both current and future periods. Maps are generated using MATLAB 2015a (Version 8.5, http://www.mathworks.com ). Finally, all these maps are organized and labelled in Adobe Photoshop CS Desktop (Version 5.1, https://www.adobe.com ) [Software].

Article Snippet: Figures are generated using MATLAB 2015a (Version 8.5, http://www.mathworks.com ) [Software].

Techniques: Generated, Software

Journal: Scientific Reports

Article Title: US Power Production at Risk from Water Stress in a Changing Climate

doi: 10.1038/s41598-017-12133-9

Figure Lengend Snippet: Scatter diagrams between indicators of water stress. ( a – d) Scatter plots showing the relationship between mean surface runoff and maximum stream temperature for nine climatologically homogeneous regions, each shown by different colors, for current (1991–2005) and future time periods (2006–2035). The size of the color-filled circles represents strength of the association, as measured by Kendall’s tau (shown in Fig. ), between surface runoff and water temperature. For a given region, nature of the association is captured by the different shades of the color; darker (lighter) shades or negative (positive) values of Kendall’s tau represent inverse (direct) relationship. The two dotted horizontal lines are drawn at the ensemble mean of stream temperatures and a critical water temperature limit of 27 °C (a limit over which water is not suitable for cooling; it is ~5 °C lower than the Environmental Protection Agency [EPA] prescribed maximum allowed temperature of ~32 °C). The vertical dotted line is drawn at no flow. The left side of the vertical line represents water scare situations, and the side above 27 °C represents warmer. Each of the scatter plots is divided into four quadrants: scarcer, warmer (top left); scarcer, cooler (bottom left); wetter, warmer (top right); and wetter, cooler (bottom right) as shown in ( d ). The partitioning of the scatter diagrams explicitly identify regions with hot spots – a combination of low flow and high temperature. The figure legend at ( a ) indicates negative values of Kendall’s tau whereas at ( b ) shows positive values. Legends are same for all panels. Figures were generated using MATLAB 2015a (Version 8.5, http://www.mathworks.com ). Finally, all these figures are organized and labelled in Adobe Photoshop CS Desktop (Version 5.1, https://www.adobe.com ) [Software].

Article Snippet: Figures are generated using MATLAB 2015a (Version 8.5, http://www.mathworks.com ) [Software].

Techniques: Generated, Software

Journal: Scientific Reports

Article Title: US Power Production at Risk from Water Stress in a Changing Climate

doi: 10.1038/s41598-017-12133-9

Figure Lengend Snippet: Time series comparison of SWSI relative to univariate water stress indices. Sample time series of 3-month SWSI is compared with standardized low surface runoff flow and high stream temperature indices at 3-month time scale. The top and bottom panel shows selected USGS gauge locations over Southeast (North Carolina, USGS Station ID 02077200, latitude 36.39° and longitude 79.20°) and West (California, USGS Station ID 373822118514401, latitude 37.64° and longitude 118.86°). Figures are generated using MATLAB 2015a (Version 8.5, http://www.mathworks.com ) [Software].

Article Snippet: Figures are generated using MATLAB 2015a (Version 8.5, http://www.mathworks.com ) [Software].

Techniques: Generated, Software

Journal: Scientific Reports

Article Title: US Power Production at Risk from Water Stress in a Changing Climate

doi: 10.1038/s41598-017-12133-9

Figure Lengend Snippet: Spatial trend of Standardized Anomaly of SWSI. Time series of standardized anomaly for each of the nine climatologically homogeneous regions for 45 years (1991–2035). Years that are water stressed (negative values of standardized anomaly) are shown in red. The horizontal dashed lines are drawn at −0.5, −1.0, and −2.0 Standard Deviations (SDs) to indicate three water stress levels: 0.5-, 1-, and 2-SD. The vertical line demarcates current and future time periods. Figures are generated using MATLAB 2015a (Version 8.5, http://www.mathworks.com ). Finally, all these figures are organized and labelled in Adobe Photoshop CS Desktop (Version 5.1, https://www.adobe.com ) [Software].

Article Snippet: Figures are generated using MATLAB 2015a (Version 8.5, http://www.mathworks.com ) [Software].

Techniques: Generated, Software

Journal: Scientific Reports

Article Title: US Power Production at Risk from Water Stress in a Changing Climate

doi: 10.1038/s41598-017-12133-9

Figure Lengend Snippet: Contours of standardized water stress index. ( A – D ) Spatial location, installed power production capacity (in Quad), and primary fuel types of thermoelectric power plants superimposed over contours of decadal mean of standardized water stress index for current (1996–2005) and future (2006–2035) time periods. Size of the filled color circle is directly proportional to the installed production capacity. Different shades of water stress contours indicate risk level due to the joint effects of low flow and high stream temperature. Grey shades in the map indicate regions where data is not available. Figures are generated using MATLAB 2015a (Version 8.5, http://www.mathworks.com ). Finally, all these maps are organized and labelled in Adobe Photoshop CS Desktop (Version 5.1, https://www.adobe.com ) [Software].

Article Snippet: Figures are generated using MATLAB 2015a (Version 8.5, http://www.mathworks.com ) [Software].

Techniques: Generated, Software

Journal: Scientific Reports

Article Title: US Power Production at Risk from Water Stress in a Changing Climate

doi: 10.1038/s41598-017-12133-9

Figure Lengend Snippet: Regional distribution of power production at risk under various water stress levels (WSL). ( a – d ) Bar plots showing the breakup of power production at risk for five different water stress risk levels over nine regions for ( a ) current (1996–2005) and ( b – d ) future (2006–2035) time periods. The annual power production capacity for each region is shown in ( c ). The total production capacity is 11.07 Quad (Table ). The number of power plants in a specific region is shown in ( d ). The total number of power plants is 815 (Table ). Five water stress levels (WSL) are defined as follows: WSL1 (−0.5 ≤ WSI ≤ 0), WSL2 (−0.75 ≤ WSI ≤ −0.5), WSL3 (−1.0 ≤ WSI ≤ −0.75), WSL4 (−1.5 ≤ WSI ≤ −1.0), and WSL5 (WSI ≤ −1.5), where WSI stands for water stress index. WSL1 (WSL5) indicates the less (most) severe condition. WNC: West North Central, SW: Southwest, SE: Southeast, NW: Northwest, NE: Northeast, and ENC: East North Central. Figures are generated using MATLAB 2015a (Version 8.5, http://www.mathworks.com ). Finally, all these figures are organized and labelled in Adobe Photoshop CS Desktop (Version 5.1, https://www.adobe.com ) [Software].

Article Snippet: Figures are generated using MATLAB 2015a (Version 8.5, http://www.mathworks.com ) [Software].

Techniques: Generated, Software

Journal: Scientific Reports

Article Title: Persisting influence of continental inheritance on early oceanic spreading

doi: 10.1038/s41598-025-93942-1

Figure Lengend Snippet: Topography over the Red Sea region and estimated depth of the Lithosphere-Asthenosphere boundary (LAB). ( a ) Topography with spreading centers and Dead Sea Transform fault as thick solid lines (where high-resolution topographic data are available), inferred spreading centers as thin solid lines (where the ridge axis is only covered by GEBCO bathymetry), and other inferred plate boundary locations as dashed lines (where the oceanic crust is not exposed or absent). Small circles indicating the Arabia-Nubia relative motion are from ref. , and onshore volcanic fields compiled from ref. , . ( b ) Estimated depth of the LAB from the Sp-receiver functions mapping of ref. , and the limits of accreted Proterozoic terranes and the Arabo-Nubian Shield . Figure generated by MATLAB R2020b software ( https://ww2.mathworks.cn/products/new_products/release2020b.html ).

Article Snippet: Figure generated by MATLAB R2020b software ( https://ww2.mathworks.cn/products/new_products/release2020b.html ).

Techniques: Generated, Software

Journal: Scientific Reports

Article Title: Persisting influence of continental inheritance on early oceanic spreading

doi: 10.1038/s41598-025-93942-1

Figure Lengend Snippet: Volcano-structural mapping of the Red Sea ridge axis. The seafloor mapping in between the 5.3 Ma isochrons was achieved from the analysis of available high-resolution bathymetric data , , shown here as shaded relief map, and GEBCO bathymetry. No high-resolution bathymetric data is available within white areas. Coordinates apply only to the high-resolution shaded relief map, with the mapping shifted by 100 km to the East. Figure generated by MATLAB R2020b software ( https://ww2.mathworks.cn/products/new_products/release2020b.html ).

Article Snippet: Figure generated by MATLAB R2020b software ( https://ww2.mathworks.cn/products/new_products/release2020b.html ).

Techniques: Generated, Software

Journal: Scientific Reports

Article Title: Persisting influence of continental inheritance on early oceanic spreading

doi: 10.1038/s41598-025-93942-1

Figure Lengend Snippet: Variations of topographic, gravity, tectonic and volcanic metrics along the axial trough of the Red Sea (for the purpose of comparison with Fig. , note that the UTM Northing interval captured here is ~1900–2850 km). ( a ) Observed and filtered (filter parameters specified in ( b )) axial bathymetry extracted from GEBCO 2021 and free-air gravity anomaly , used together to compute the Mantle Bouguer Anomaly (see ), whose range of variations depends on sediment corrections ( and Supplementary Fig. ) and is included within the red curve except where the axial trough is covered by salt flows, then it is depicted as a transparent red envelope. Note that the large negative anomaly around K1400–K1500 results from unconstrained sediment thickness (Supplementary Fig. ). ( b ) Residual topography computed as the difference between the observed and filtered topography shown in ( a ). ( c ) Gray envelopes depict the average axial depth (2σ) computed across a 50-km-wide moving window; the flanks of the axial trough above this envelope are color-coded as a function of the local average slope with antithetic-slopes depicted in black (see ). ( d ) Black dots depict cumulative throw of individual faults (sum of all throws from the ridge axis to this fault: see ); color-coded envelopes represent the maximum fault throw recorded across a 1.1-km-wide moving window; blue dots show the magmatic contribution assuming a constant fault dip angle of 60° (see ). ( e ) Fault azimuth of individual strands is plotted as their deviation from the normal to the predicted opening direction (rotated clockwise (CW) when >0 and counter-clockwise (CCW) when <0); the cumulative transform offset of the axial volcanic ridge (in red; starting from the SE edge) is computed along the small circles predicted by model Arabia-Nubia rotation parameters (see ). ( f ) Relative proportion of terrain type in between the 0.7 Ma isochrons (see ). ( g ) Distance of onshore Arabian volcanic fields relative to the ridge axis (computed along small circles) in their current position and at 13 Ma (see ). Red arrows point to the maximum seaward extension of volcanism at Lunayyir and Tufail. Gray bands in all sub-figures correspond to inter-trough zones (sea-floor covered by allochtonous salt flows). Figure generated by MATLAB R2020b software ( https://ww2.mathworks.cn/products/new_products/release2020b.html ).

Article Snippet: Figure generated by MATLAB R2020b software ( https://ww2.mathworks.cn/products/new_products/release2020b.html ).

Techniques: Comparison, Generated, Software

Journal: Scientific Reports

Article Title: Persisting influence of continental inheritance on early oceanic spreading

doi: 10.1038/s41598-025-93942-1

Figure Lengend Snippet: 3D view of the Red Sea axial trough around the Suakin segment looking NW. The bathymetry visualized here is the elevation above the mean axial depth (see for calculation, and note that it generated subtle artefacts visible in the image in the form of axis-normal fabrics mostly outside the limit of high-resolution bathymetric data) and allows capturing the increased cumulative fault throw at the Suakin segment (white sections of the upper shelf in the middle of the image). Note the larger than average normal fault offsets shown by the black arrows and the coincident reduction of the axial volcanic ridge. The dotted line depicts the limit of high-resolution bathymetric data. The thick black lines on the Figure edges represent the 5.3 Ma isochrons. Figure generated by MATLAB R2020b software ( https://ww2.mathworks.cn/products/new_products/release2020b.html ).

Article Snippet: Figure generated by MATLAB R2020b software ( https://ww2.mathworks.cn/products/new_products/release2020b.html ).

Techniques: Generated, Software

Journal: Scientific Reports

Article Title: Persisting influence of continental inheritance on early oceanic spreading

doi: 10.1038/s41598-025-93942-1

Figure Lengend Snippet: Numerical simulations of the lateral spreading of low-density plume material from rifting to spreading. ( a ) Model Lithosphere thickness 1 Ma before the onset of continental rifting showing the two inherited sub-lithospheric channel running oblique to the future plate boundary. The vector field depicts plate motion relative to the Afar hotspot (15 mm/yr SW of the rift, and 15 mm/yr + model rotation of Arabia relative to Nubia NE of the rift). ( b ) Plume thickness after 16 Ma of lateral propagation followed by 10 Ma of continental rifting along 2 arms during which the lithosphere is homogeneously thinned across a 160-km-wide symmetric zone of active extension (see ). Vectors are same as in ( a ). The red star denotes the hotspot position. The dashed black line represents the axis of a pre-rift 150-km-wide sub-lithospheric channel along which the initial lithospheric thickness is reduced to 90 km (versus 140 km over the rest of the grid). Note the enhanced accumulation of plume material at the intersection between the rift and the sub-lithospheric channel. ( c ) Cumulative accumulation of plume material (relative to stage in ( b )) after 4 Ma of oceanic spreading. Note the accumulation deficit at the intersection between the rift and the sub-lithospheric channel. This deficit grows during the first ~1 Ma in our model, after which sub-axis flow remains similar to nearby sections. Also note the lateral escape flow NE of this intersection, which lasts up to 4–5 Ma in our model. The second sub-lithospheric channel (not yet reached by plume material in ( b )) is also depicted with a dashed blue line. Note that inflow of plume material is set to zero from the onset of oceanic spreading, such that NNW-directed redistribution of plume material along the rift occurs to achieve gravitational stability. Figure generated by MATLAB R2020b software ( https://ww2.mathworks.cn/products/new_products/release2020b.html ).

Article Snippet: Figure generated by MATLAB R2020b software ( https://ww2.mathworks.cn/products/new_products/release2020b.html ).

Techniques: Plasmid Preparation, Generated, Software