14 research outputs found

    Using Multi-Scale Uncertainty Information And Specific Forecast Skill To Improve Reservoir Operations

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    Optimization of reservoir operations to time series of forecasted inflows are constrained by a set of multiple objectives that span many time scales, however the temporally evolving skill of the forecasts are usually not considered in the objective functions. For example, a flow forecast time series extending from 1 day to 6 months consists of a medium range flow forecast that draws its skill from initial conditions and weather forecasts and a seasonal flow forecast that relies on the initial conditions only. The skill of the medium range flow forecast is the daily and aggregated values with a range of uncertainties that increases with lead time, while the seasonal flow forecasts only have skill in the monthly volumetric values with a range of uncertainties that is large, but predictable. Unfortunately, the impacts of temporally evolving skill and uncertainty on reservoir operations and operational risk is unknown, which may leave significant room for improvement. To explore this question we conduct a set of optimization experiments of reservoir operations at the snowmelt dominated Gunnison River Basin in Colorado and the snow-rain transition Feather River Basin in California. Each optimization experiment uses the same ensemble flow forecast, which is an ensemble medium range forecast merged with an ensemble seasonal forecast, but utilizes a different set of weights that are applied to the medium and seasonal scale objectives (which are to maximize revenue and envrionmental performance). By comparing the weighted set of optimizations to a non-weighted optimization, we are able to isolate the impact of the skill and uncertainty of the forecasts on reservoir operations. We conclude by using the results to develop a functional relationship between the skill and uncertainty in the forecasts to the objective weights and as a basis to calculate operational risk

    Macroalgae Analysis A National GIS-based Analysis of Macroalgae Production Potential Summary Report and Project Plan

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    The overall project objective is to conduct a strategic analysis to assess the state of macroalgae as a feedstock for biofuels production. The objective in FY11 is to develop a multi-year systematic national assessment to evaluate the U.S. potential for macroalgae production using a GIS-based assessment tool and biophysical growth model developed as part of these activities. The initial model development for both resource assessment and constraints was completed and applied to the demonstration areas. The model for macroalgal growth was extended to the EEZ off the East and West Coasts of the United States, and a plan to merge the findings for an initial composite assessment was developed. In parallel, an assessment of land-based, port, and offshore infrastructure needs based on published and grey literature was conducted. Major information gaps and challenges encountered during this analysis were identified. Also conducted was an analysis of the type of local, state, and federal requirements that pertain to permitting land-based facilities and nearshore/offshore culture operation

    PACIFIC NORTHWEST REGIONAL COLLABORATORY ANNUAL REPORT FOR SYNERGY VII (2007)

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    During this final year of the Pacific Northwest Regional Collaboratory we focused significantly on continuing the relationship between technical teams and government end-users. The main theme of the year was integration. This took the form of data integration via our web portal and integration of our technologies with the end users. The PNWRC's technical portfolio is based on EOS strategies, and focuses on 'applications of national priority: water management, invasive species, coastal management and ecological forecasting.' The products of our technical approaches have been well received by the community of focused end-users. The objective this year was to broaden that community and develop external support to continue and operationalize product development

    Climatological analysis of tropical cyclone impacts on hydrological extremes in the Mid-Atlantic region of the United States

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    Research efforts related to landfalling tropical cyclones (TCs) and their hydrological impacts have focused mostly on the continental or regional scales, whereas many coastal management and infrastructure decisions are made at much finer spatial scales. In this context, this study aims to provide local-scale understandings of the climatological characteristics and hydrological impacts of TCs (from 1950 to 2019) over the Mid-Atlantic region defined as the Delaware River Basin (DRB) and Susquehanna River Basin (SRB). The climatological analysis is based on analyzing long-term, spatially distributed observational datasets of hurricane tracks, precipitation, and streamflows. Results suggest that, despite limited contribution of TCs to regional precipitation (<9%), TC is the dominant driver for extreme floods in the southern part of DRB (e.g. tributaries of the Christina River and lower Schuylkill River) and the southwestern portions of SRB (e.g. tributaries of the Lower Susquehanna and Junita River), where TC’s effect on drought alleviation is also comparatively higher. At the basin level, SRB is more susceptible to flooding associated with TCs and prone to drought relative to DRB; however, strong spatial variability of TC’s impact on hydrological extremes is observed within and across the basins. While the TC effect on flood/drought is negligible for the high-elevation, northern part of the region, TC increases the magnitude of the 100 year flood by up to 19.6% in DRB and 53.0% in SRB; the duration of short-term extreme hydrological drought is reduced by TC by up to 25.0% in SRB and 24.7% in DRB, respectively

    Integrated Modeling Approach for the Development of Climate-Informed, Actionable Information

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    Flooding is a prevalent natural disaster with both short and long-term social, economic, and infrastructure impacts. Changes in intensity and frequency of precipitation (including rain, snow, and rain-on-snow) events create challenges for the planning and management of resilient infrastructure and communities. While there is general acknowledgment that new infrastructure design should account for future climate change, no clear methods or actionable information are available to community planners and designers to ensure resilient designs considering an uncertain climate future. This research demonstrates an approach for an integrated, multi-model, and multi-scale simulation to evaluate future flood impacts. This research used regional climate projections to drive high-resolution hydrology and flood models to evaluate social, economic, and infrastructure resilience for the Snohomish Watershed, WA, USA. Using the proposed integrated modeling approach, the peaks of precipitation and streamflows were found to shift from spring and summer to the earlier winter season. Moreover, clear non-stationarities in future flood risk were discovered under various climate scenarios. This research provides a clear approach for the incorporation of climate science in flood resilience analysis and to also provides actionable information relative to the frequency and intensity of future precipitation events

    National microalgae biofuel production potential and resource

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    [1] Microalgae are receiving increased global attention as a potential sustainable &quot;energy crop&quot; for biofuel production. An important step to realizing the potential of algae is quantifying the demands commercial-scale algal biofuel production will place on water and land resources. We present a high-resolution spatiotemporal assessment that brings to bear fundamental questions of where production can occur, how many land and water resources are required, and how much energy is produced. Our study suggests that under current technology, microalgae have the potential to generate 220 × 10 9 L yr −1 of oil, equivalent to 48% of current U.S. petroleum imports for transportation. However, this level of production requires 5.5% of the land area in the conterminous United States and nearly three times the water currently used for irrigated agriculture, averaging 1421 L water per liter of oil. Optimizing the locations for microalgae production on the basis of water use efficiency can greatly reduce total water demand. For example, focusing on locations along the Gulf Coast, southeastern seaboard, and Great Lakes shows a 75% reduction in consumptive freshwater use to 350 L per liter of oil produced with a 67% reduction in land use. These optimized locations have the potential to generate an oil volume equivalent to 17% of imports for transportation fuels, equal to the Energy Independence and Security Act year 2022 &quot;advanced biofuels&quot; production target and utilizing some 25% of the current irrigation demand. With proper planning, adequate land and water are available to meet a significant portion of the U.S. renewable fuel goals

    Next-Generation Intensity-Duration-Frequency Curves for Diverse Land across the Continental United States

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    Abstract The current methods for designing hydrological infrastructure rely on precipitation-based intensity-duration-frequency curves. However, they cannot accurately predict flooding caused by snowmelt or rain-on-snow events, potentially leading to underdesigned infrastructure and property damage. To address these issues, next-generation intensity-duration-frequency (NG-IDF) curves have been developed for the open condition, characterizing water available for runoff from rainfall, snowmelt, and rain-on-snow. However, they lack consideration of land use land cover (LULC) factors, which can significantly affect runoff processes. We address this limitation by expanding open area NG-IDF dataset to include eight vegetated LULCs over the continental United States, including forest (deciduous, evergreen, mixed), shrub, grass, pasture, crop, and wetland. This NG-IDF 2.0 dataset offers a comprehensive analysis of hydrological extreme events and their associated drivers under different LULCs at a continental scale. It will serve as a useful resource for improving standard design practices and aiding in the assessment of infrastructure design risks. Additionally, it provides useful insights into how changes in LULC impact flooding magnitude, mechanisms, timing, and snow water supply

    Siting Algae Cultivation Facilities for Biofuel Production in the United States: Trade-Offs between Growth Rate, Site Constructability, Water Availability, and Infrastructure

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    Locating sites for new algae cultivation facilities is a complex task. The climate must support high growth rates, and cultivation ponds require appropriate land and water resources, as well as transportation and utility infrastructure. We employ our spatiotemporal Biomass Assessment Tool (BAT) to select promising locations based on the open-pond cultivation of Arthrospira sp. and strains of the order Sphaeropleales. A total of 64 000 sites across the southern United States were evaluated. We progressively applied screening criteria and tracked their impact on the number of potential sites, geographic location, and biomass productivity. Both strains demonstrated maximum productivity along the Gulf of Mexico coast, with the highest values on the Florida peninsula. In contrast, sites meeting all selection criteria for Arthrospira were located along the southern coast of Texas and for Sphaeropleales were located in Louisiana and southern Arkansas. Results were driven mainly by the lack of oil pipeline access in Florida and elevated groundwater salinity in southern Texas. The requirement for low-salinity freshwater (<400 mg L<sup>–1</sup>) constrained Sphaeropleales locations; siting flexibility is greater for salt-tolerant species like Arthrospira. Combined siting factors can result in significant departures from regions of maximum productivity but are within the expected range of site-specific process improvements
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