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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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76 records · Page 5

Identifying Robust Decarbonization Pathways for the Western U.S. Electric Power System Under Deep Climate Uncertainty

Climate change threatens the resource adequacy of future power systems. Existing research and practice lack frameworks for identifying decarbonization pathways that are robust to climate-related uncertainty. We create such an analytical framework, then use it to assess the robustness of alternative pathways to achieving 60% emissions reductions from 2022 levels by 2040 for the Western U.S. power system. Our framework integrates power system planning and resource adequacy models with 100 climate realizations from a large climate ensemble. Climate realizations drive electricity demand; thermal plant availability; and wind, solar, and hydropower generation. Among five initial decarbonization pathways, all exhibit modest to significant resource adequacy failures under climate realizations in 2040, but certain pathways experience significantly less resource adequacy failures at little additional cost relative to other pathways. By identifying and planning for an extreme climate realization that drives the largest resource adequacy failures across our pathways, we produce a new decarbonization pathway that has no resource adequacy failures under any climate realizations. This new pathway is roughly 5% more expensive than other pathways due to greater capacity investment, and shifts investment from wind to solar and natural gas generators. Our analysis suggests modest increases in investment costs can add significant robustness against climate change in decarbonizing power systems. Our framework can help power system planners adapt to climate change by stress testing future plans to potential climate realizations, and offers a unique bridge between energy system and climate modeling.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Probabilistic Diffusion Models Advance Extreme Flood Forecasting

Extreme floods pose escalating risks in a changing climate, yet forecasting remains challenging due to peak flow underestimation and high uncertainty. We introduce diffusion-based runoff model (DRUM), a probabilistic deep learning (DL) approach that advances extreme flood forecasting across representative basins in the contiguous United States. DRUM outperforms state-of-the-art benchmarks, enhancing nowcasting skill for the top 1‰ of flows in 72.3% of studied basins. Under operational scenarios, DRUM extends reliable lead times by nearly a full day for 20- and 50-year floods. When evaluated with measured precipitation, an ideal condition, recall improves by 0.3–0.4 and the early warning window extends by 2.3 days for 50-year floods. The enhancement potential varies regionally, with precipitation-driven flood zones in the eastern and northwestern US benefiting most, gaining 3–7 days in lead time. These findings highlight the transformative potential of diffusion models as a cutting-edge generative AI technique for advancing hydrology and broader Earth system sciences.

54 ENVIRONMENTAL SCIENCES↗

Geological study of an outburst flood event in the upper Yangtze River and risk of similar extreme events

Here, outburst flood sediments are studied on the upper course of the Yangtze River (known as the Jinsha River) where is a key region for the development of hydroelectric power. As the history and magnitude of outburst flooding in this stretch of the Jinsha River during historic times has remained largely undocumented, we have endeavored as part of this study to conduct field investigations into, and provide numerical dating (using OSL and 14 C dating techniques) of outburst flood evidence found in the First Bend area of the Yangtze River. Carbonized nutshells and charcoal from the ancient settlement yielded 14 C ages that precisely pinpointed an outburst flood event ~1200–1300 cal yr BP, during China's Tang Dynasty (618–907 CE). However, OSL ages using the minimum age model for all outburst flood samples ranged from 9.1 to 1.8 ka, which was ~0.5–7.8 ka older than the 14 C-dated outburst flood. This discrepancy suggests a potential overestimation of quartz age when dating outburst flood sediments from the Holocene period. Furthermore, using 2D hydraulic modeling, we estimated the magnitude of the aforementioned outburst flood, revealing a reconstructed peak flow discharge of 51,000–55,300 m 3 /s. This discharge was three times greater than the 10,000-year flood for the hydroelectric power station nearest to the study area. Our study underscores the significant role of combining archaeological and geological evidence in enhancing paleoflood hydrology research. Through a multidisciplinary approach, our findings emphasize the importance of paleoflood hydrology studies in comprehending both the latent and catastrophic flood risks in alpine mountain areas amid the context of global warming.

14C dating↗

Indicators of carbon alteration (ICAs) suggest patterns in reservoir methane emissions

Reservoir operations influence emissions via multiple causal pathways. In this paper, we quantify indicators of carbon alteration (ICAs) focused on methane. ICAs were chosen to reflect the potential for methane emission along four causal pathways: 1) water column mixing, 2) wet-dry cycles in sediment, 3) sediment redistribution, and 4) vegetation. We developed algorithms to calculate ICAs for three reservoirs along a longitudinal gradient in the Tennessee River basin of the southeast US. The ICAs revealed interesting longitudinal patterns. Indicators of both methane production and destruction increased downstream. The potential for ebullitive methane emissions driven by sub-daily water level fluctuations and emissions mediated by vegetation were higher in downstream mainstem reservoirs than in the upstream tributary reservoir. Along the remaining two pathways, longitudinal patterns were equivocal (sediment pathway) or suggested decreased emissions downstream (water-column mixing). We also observed seasonal patterns and, by combining ICAs, inferred times when ramping could be achieved with lower risk of emissions. The ICAs demonstrated here are the first step in quantifying mechanistic relationships between reservoir operation and methane emissions. In future, they may lead to improved operations in reservoir cascades and regional-scale estimates of emissions that account for differences among reservoirs.

Greenhouse gases↗