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Hansen, Carly H.

Publications and source records attributed to Hansen, Carly H..

6 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Technical Potential for Hydropower Capacity at Non-powered Dams

In the last decade, retrofits of existing nonpowered dams (NPDs) have made up the largest share of capacity increases for US hydropower. Accurate estimates of potential capacity and generation at NPDs help identify sites that may be worth investing in detailed feasibility analyses and design exploration. This dataset consists of NPDs in the conterminous US with at least 100kW of theoretical potential based on earlier resource assessments. Historical daily streamflow (modeled or from USGS gauge records), hydraulic head (based on historical observations or primary purpose and dam height) are the main inputs for HydroGenerate which determines design flow and turbine efficiencies and then calculates nominal capacity, daily generation, and capacity factor. These outputs are summarized on a monthly basis (i.e., generation (MWh) and capacity factor averaged for each month from January to December) and overall (i.e., nominal capacity, average annual generation (MWh), and average annual capacity factor). A total of 4.1 GW capacity is estimated across all 2,564 NPDs included in the dataset.

13 HYDRO ENERGY↗
DOE OSTI2024

Hydropower Infrastructure – LAkes, Reservoirs, and RIvers (HILARRI)

HILARRI is a database of links between major datasets of operational hydropower dams and powerplants, and inland water bodies. These connections are critical for conducting large-scale analysis of hydropower infrastructure and their associated natural and engineered water systems. Features include: – Dams from the National Inventory of Dams (2024) and the Global Reservoir and Dam Database (GRanD v1.3) – Hydropower plants from the Existing Hydropower Assets dataset (EHA 2024) These hydropower infrastructure features are linked to several major datasets that provide hydrologic and hydraulic information relevant for analysis of hydropower systems that includes the integral water resources. That information comes from: – Products from the National Hydrography Dataset (NHD) – NHDPlusV2 Medium Resolution river network flowlines, – NHD waterbodies (limited to lakes and reservoirs), – NHD Watershed Boundary Dataset (HUC12-level for the Conterminous United States (CONUS)) – NHD High Resolution waterbodies – HydroLAKES water bodies (lakes and reservoirs) – LAGOS-US lakes and reservoirs – EPA National Lakes Assessment (2007, 2012, 2017, and 2022) – The Reservoir Sedimentation Database (RESSED) Unique identifiers are used to facilitate joining to the original full datasets. For example, characteristics of NHD flowlines such as estimated average flow rate can be joined from the NHDPlusV2 dataset to a dam or power plant listed in HILARRI based on the ID field, “COMID”, that is common to both datasets. HILARRI only includes basic information about identifiers, location, and data quality or usage notes. It does not contain the attributes or time series data associated with these sites. The HILARRI dataset incorporates information from several datasets to facilitate more effective and accurate analysis of hydropower infrastructure and their associated waterbodies. For example, dams were checked against the most recent American Rivers Dam Removal Database to identify and flag facilities that may no longer exist. Additionally, dams that are listed multiple times in the NID are identified and flagged to avoid double-counting when analyzing and summarizing information. Other quality flags include certainty of operational hydropower (i.e., if one or more datasets indicates hydropower at a particular location), whether an associated water body is accurate or composed of multiple polygons, or whether there is a known issue with reported characteristics in one of the underlying datasets. These additional data flags are designed to increase confidence in data usage for individual to large-scale analyses.

13 HYDRO ENERGY↗
DOE OSTI2024

Shifts in Carbon Emissions Versus Sequestration From Hydropower Reservoirs in the Southeastern United States

Reservoirs are a significant source of carbon (C) to the atmosphere, but their emission rates vary in space and time. Here we compared C emissions via diffusive and ebullitive pathways at several stations in six large hydropower reservoirs in the southeastern US that were previously sampled in summer 2012. We found that carbon dioxide (CO 2 ) diffusion was the dominant flux pathway during 2012 and 2022, with only three exceptions where methane (CH 4 ) diffusion or CH 4 ebullition dominated. CH 4 diffusion rates were positively associated with water temperature. However, we found no clear predictors of CH 4 ebullition, which had extremely high variability, with rates ranging from 0 to 739 mg C m -2 day -1 . For CO 2 diffusion, the direction of the flux shifted between 2012 and 2022, where all but three stations across all reservoirs emitted CO 2 in summer 2012, but every station sequestered CO 2 in summer 2022. Here, indicators of greater algal production were associated with CO 2 sequestration, including surface chlorophyll- a concentration, surface dissolved oxygen saturation, and pH. Additional sampling campaigns outside the summer season highlighted the importance of seasonal phenology in primary production on the direction of CO 2 diffusive fluxes, which shifted to positive CO 2 fluxes by the end of August as productivity decreased. Our results demonstrate the importance of capturing CO 2 sequestration in field and modeling measurements and understanding the seasonal drivers of these estimates. Measuring C emissions from multiple pathways in reservoirs and understanding their spatiotemporal responses and variability are vital to reducing uncertainties in global upscaling efforts.

13 HYDRO ENERGY↗
DOE OSTI2023

Understanding How Reservoir Operations Influence Methane Emissions: A Conceptual Model

Because methane is a potent greenhouse gas (GHG), understanding controls on methane emissions from reservoirs is an important goal. Yet, reservoirs are complex ecosystems, and mechanisms by which reservoir operations influence methane emissions are poorly understood. In part, this is because emissions occur in ‘hot spots’ and ‘hot moments’. In this study, we address three research questions, ‘What are the causal pathways through which reservoir operations and resulting water level fluctuations (WLF) influence methane emissions?’; ‘How do influences from WLF differ for seasonal drawdown and diurnal hydropeaking operations?’; and ‘How does understanding causal pathways inform practical options for mitigation?’. A graphical conceptual model is presented that links WLF in reservoirs to methane emissions via four causal pathways: (1) water-column mixing (2) drying–rewetting cycles, (3) sediment delivery and redistribution, and (4) littoral vegetation. We review what is known about linkages for WLF at seasonal and diurnal resolutions generate research questions, and hypothesize strategies for moderating methane emissions by interrupting each causal pathway. Those related to flow management involve basin-scale management of tributary flows, seasonal timing of hydropeaking (pathway #1), timing and rates of drawdown (pathway #2). In addition, we describe how sediment (pathway #3) and vegetation management (pathway #4) could interrupt linkages between WLF and emissions. We demonstrate the strength of conceptual modeling as a tool for generating plausible hypotheses and suggesting mitigation strategies. Future research is needed to develop simpler models at appropriate timescales that can be validated and used to manage flow releases from reservoirs.

13 HYDRO ENERGY↗
DOE OSTI2022

Designing Hydropower Flows to Balance Energy and Environmental Needs (HydroWIRES Topic A Final Project Report)

Hydropower is expected to play a new role in the US electricity grid as more variable renewable energy sources like wind and solar come online. Wind and solar generation increase fluctuations in electrical supply increasing the value of flexible generation sources that can quickly ramp generation up and down. The flexible generation hydropower can provide as well as the ancillary services (e.g., frequency and voltage regulation and reserves, black start capability) it provides for balancing and stabilizing the power grid are predicted to be of increased value in these future grid scenarios. Yet, the flexibility of hydropower may come with environmental costs due to up- and down-ramping of hydropower plants (i.e., quickly increasing or decreasing generation flows, respectively) which may strand fish, dewater or scour fish nests, alter habitat, or create unsafe recreational conditions that may be unacceptable to participants in the hydropower regulatory process. These types of environmental impacts are often mitigated through environmental flow requirements that specify minimum or maximum flow releases, or ramp-rates changes allowed at a hydropower facility. While it is not currently known to what degree electrical grid reliability could be affected by environmental flow requirements, gaining a better understanding of these interactions before the grid becomes more deeply decarbonized can help define what policy, regulation, or infrastructure may be needed to support the clean energy transition. As the future grid will rely on hydropower to provide both flexibility and robust environmental protections, the analyses and tools described in this report are centered on making mechanistic linkages between energy and the environment in hydropower systems. This understanding of energy-environment linkages can provide the foundational understanding needed to quantitatively assess the trade-offs between the increased generation flexibility that hydropower will be expected to provide and the environmental impacts of this flexibility. This report seeks to provide an objective foundation for building future science and tools that can be used by a broad spectrum of the hydropower community that is involved in licensing or environmental regulatory proceedings tasked with balancing energy and environmental objectives through flow management.

13 HYDRO ENERGY↗