Design rainfalls under climate change scenarios in South East Queensland, Australia: A Brisbane River case study
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Demand for biofuel production driven by the Renewable Fuel Standard (RFS2) has coincided with increased land in corn production and increasing nitrogen (N) loss to the Gulf of Mexico. Diversifying cropland with perennial energy crops (miscanthus and switchgrass) may reduce N loss and improve water quality. However, the extent of these benefits depends on the mix of biomass feedstocks (corn stover, perennials) incentivized by the RFS2 and the extent to which energy crops displace N-intensive row crops. We developed an integrated economic-biophysical model to quantify the water quality impacts of three potential policy scenarios that provided corn ethanol at levels before the RFS2 (RFS1 baseline); 15 billion gallons of corn ethanol (corn ethanol only); or 16 billion gallons of cellulosic ethanol in addition to corn ethanol (corn + cellulosic ethanol). Our results showed that economically optimal locations for perennial energy crop production were distributed across idle cropland with lower intrinsic N loss than active cropland. We found stover removal incentivized by the RFS2 offset N loss benefits of perennial energy crops. Furthermore, this finding suggests that targeted incentives for N loss reduction are needed to supplement the RFS2 to induce displacement of N-intensive row crops with energy crops to reduce N losses.
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Between January 2019 and January 2021, the Mars Science Laboratory team explored the Glen Torridon (GT) region in Gale crater (Mars), known for its orbital detection of clay minerals. Mastcam, Mars Hand Lens Imager, and ChemCam data are used in an integrated sedimentological and geochemical study to characterize the Jura member of the upper Murray formation and the Knockfarril Hill member of the overlying Carolyn Shoemaker formation in northern GT. The studied strata show a progressive transition represented by interfingering beds of fine–grained, recessive mudstones of the Jura member and coarser–grained, cross–stratified sandstones attributed to the Knockfarril Hill member. Whereas the former are interpreted as lacustrine deposits, the latter are interpreted as predominantly fluvial deposits. The geochemical composition seen by the ChemCam instrument show K 2 O–rich mudstones (~1–2 wt.%) versus MgO–rich sandstones (>6 wt.%), relative to the average composition of the underlying Murray formation. We document consistent sedimentary and geochemical data sets showing that low–energy mudstones of the Jura member are associated with the K–rich endmember, and that high–energy cross–stratified sandstones of the Knockfarril Hill member are associated with the Mg–rich endmember, regardless of stratigraphic position. The Jura to Knockfarril Hill transition therefore marks a significant paleoenvironmental change, where a long–lived and comparatively quiescent lacustrine setting progressively changes into a more energetic fluvial setting, as a consequence of shoreline regression due to either increased sediment supply or lake–level drop.
Abstract Delta shoreline structure has long been hypothesized to encode information on the relative influence of fluvial, wave, and tidal processes on delta formation and evolution. We introduce here a novel multiscale characterization of shorelines by defining three process‐informed morphological metrics. We show that this characterization yields self‐emerging classes of morphologically similar deltas, that is, delta morphotypes, and also predicts the dominant forcing of each morphotype. Then we show that the dominant forcings inferred from shoreline structure generally align with those estimated via relative sediment fluxes, while positing that misalignments arise from spatiotemporal heterogeneity in deltaic sediment fluxes not captured in their estimates. The proposed framework for shoreline characterization advances our quantitative understanding of how shoreline features reflect delta forcings, and may aid in deciphering paleoclimate from images of ancient deposits and projecting delta morphologic response to changes in sediment fluxes.
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This software package includes hydro governor and turbine models developed in Simulink (Mathworks Inc.) and RSCAD (RTDS Technologies) for low-head bulb-style Kaplan turbine hydropower plants. The model developed in Simulink has been designed and tuned to match the governor-turbine response for a real-world hydropower unit owned by Idaho Falls Power (IFP). The Simulink and RSCAD models enable real-time testing in a hardware-in-the-loop (HIL) implementation using OPAL-RT and RTDS digital real-time simulators, respectively. An automatic initialization for dynamic simulation has also been integrated to each model in both Simulink and RSCAD. The RSCAD initialization involves a novel python-based interfacing for automatic modification of the initial conditions in the model. The parameters of these models can be tuned to match other hydropower plants in this class.
Lawrence Berkeley National Laboratory (LBNL) contracted the National Ecological Observatory Network Airborne Observation Platform (NEON AOP) to observe watersheds of interest surrounding Crested Butte, CO with remotely sensed data, including LiDAR. The flight box design encompassed the watersheds, surveying a total area of 334 km2 across 72 lines. The instrument used was an Optech Gemini, with a pulse density of 2-9 pulses m-2 across the study area (see final report document for detailed information (Goulden and Musinsky 2020). These LiDAR data are the primary data that were provided by NEON, and include both LiDAR source data and derived surface products. The source data are contained in 'crbu_laz.zip' and 'classified_point_cloud.zip. 'classified_point_cloud.zip' represents an additional processing level on 'crbu_laz.zip'. The derived products are 'dsm_mosaic_min_phase_me.tif', 'dtm_mosaic_min_phase_me.tif', and 'tch_mosaic_min_phase_me.tif'. These files are raster mosaics of a digital surface elevation model (DSM), digital terrain elevation model (DTM), and a canopy height model (CHM) at 1 m resolution with a height threshold of > 2 m, respectively, in geotiff (.tif) format. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. [UPDATE] On 06/26/2026 the files 'crbu_laz.zip' and 'classified_point_cloud.zip' were replaced with original output files from NEON to address zip file corruption and naming errors. No changes were made to the underlying data. (See Methods Step 2 for details).