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Analysis and visualization of coastal ocean model data in the cloud

The traditional flow of coastal ocean model data is from High Performance Computing (HPC) centers to the local desktop, or to a file server where just the data needed can be extracted via services such as OPeNDAP. Analysis and visualization is then conducted using local hardware and software. This requires moving large amounts of data across the internet as well as acquiring and maintaining local hardware, software and support personnel. Further, as data sets increase in size, the traditional workflow may not be scalable. Alternatively, recent advances make it possible to move data from HPC to the Cloud and perform interactive, scalable, data-proximate analysis and visualization, with simply a web browser user interface. We use the framework advanced by the NSF-funded Pangeo project, a free, open-source Python system which provides multi-user login via JupyterHub and parallel analysis via Dask, both running in Docker containers orchestrated by Kubernetes. Data is stored in the Zarr format, a Cloud-friendly ndarray format that allows performant extraction of data by anyone without relying on data services like OPeNDAP. Interactive visual exploration of data on massive model grids is made possible by new tools in the Python PyViz ecosystem, which can render maps at screen resolution, dynamically updating on pan and zoom operations. Two example are given: (1) calculating the maximum water level at each grid cell from a 53GB, 720 time step, 9 million node triangular mesh ADCIRC simulation of Hurricane Ike; (2) creating a dashboard for visualizing data from the curvilinear orthogonal COAWST/ROMS forecast model.

Journal of Marine Science and Engineering↗

Phosphorus component in AnnAGNPS

The USDA Annualized Agricultural Non-Point Source Pollution model (AnnAGNPS) has been developed to aid in evaluation of watershed response to agricultural management practices. Previous studies have demonstrated the capability of the model to simulate runoff and sediment, but not phosphorus (P). The main purpose of this article is to evaluate the performance of AnnAGNPS on P simulation using comparisons with measurements from the Deep Hollow watershed of the Mississippi Delta Management Systems Evaluation Area (MDMSEA) project. A sensitivity analysis was performed to identify input parameters whose impact is the greatest on P yields. Sensitivity analysis results indicate that the most sensitive variables of those selected are initial soil P contents, P application rate, and plant P uptake. AnnAGNPS simulations of dissolved P yield do not agree well with observed dissolved P yield (Nash-Sutcliffe coefficient of efficiency of 0.34, R2 of 0.51, and slope of 0.24); however, AnnAGNPS simulations of total P yield agree well with observed total P yield (Nash-Sutcliffe coefficient of efficiency of 0.85, R2 of 0.88, and slope of 0.83). The difference in dissolved P yield may be attributed to limitations in model simulation of P processes. Uncertainties in input parameter selections also affect the model's performance.

Transactions of the American Society of Agricultur↗

Time-averaged near-bed suspended sediment concentrations under waves and currents: Comparison of measured and model estimates

Profiles of suspended sediment concentration and velocity were measured over a 15-day period at a near-shore site off Santa Cruz, CA in Monterey Bay. The concentration and velocity data were collected with an Acoustic Backscattering System (ABS) and Acoustic Current Profiler (ACP) that were mounted on a bottom tripod. High-resolution bottom scanning sonar was also attached to the tripod to provide images of bed features during the experiment. Hourly time-averaged near-bed concentrations of suspended sediment were calculated from three models and compared with the measurements. Surface waves and currents that were generated by a storm of moderate intensity caused bed stresses that exceeded threshold stress for D 50 =0.02 cm, the median size of the moderately well-sorted bottom sediment, over a period of about 7 days. Estimates of the concentration at 1 cm above the bottom, C a1 , were obtained using the ABS measurements. These observations have been compared with predictions for the concentration at 1 cm above the bottom, C 1 . Nielsen's models for reference concentration C o [Nielsen, P., 1986. Suspended sediment concentrations under waves. Coastal Engineering 10, 32-31; Nielsen, P., 1992. Coastal Bottom Boundary Layers and Sediment Transport, Advanced Series on Ocean Engineering. World Scientific, Hackensack, NJ.] are purely wave-based and do not include effects of bottom currents on bed stress and bedform scales. C 1 calculated from this model compared well with measured C a1 when currents were weak and small oscillatory ripples were observed in the sonar images. However, during the 3-day period of highest bottom stresses modeled C 1 did not compare well to C a1 . The other two models for C 1 , Glenn and Grant [Glenn, S.M., Grant, W.D., 1987. A suspended sediment stratification correction for combined wave and current flows. Journal of Geophysical Research 92(C8), 8244-8264.] and van Rijn and Walstra [Van Rijn, L.C., Walstra, D.J.R., 2004. Description of TRANSPOR2004 and implementation in Delft3D-ONLINE. Interim Report prepared for DG Rijkswaterstaat, Rijksinstituut voor Kust en Zee. Delft Hydraulics Institute, The Netherlands.], accounted for combined wave-current stresses and included different formulations for predicting bedform scales. C 1 calculated from these models compared well with measurements throughout the early and middle period of the storm, but underpredicted measured values during the latter part of the experiment. An alternative method based on dimensional analysis provided a straightforward way to relate C 1 to bed stress and sediment parameters. This new relationship based on dimensional analysis explained about 77% of the variability in C a1 derived from the ABS data.

California↗

Classifying crop types using two generations of hyperspectral sensors (Hyperion and DESIS) with machine learning on the cloud

Advances in spaceborne hyperspectral (HS) remote sensing, cloud-computing, and machine learning can help measure, model, map and monitor agricultural crops to address global food and water security issues, such as by providing accurate estimates of crop area and yield to model agricultural productivity. Leveraging these advances, we used the Earth Observing-1 (EO-1) Hyperion historical archive and the new generation DLR Earth Sensing Imaging Spectrometer (DESIS) data to evaluate the performance of hyperspectral narrowbands in classifying major agricultural crops of the U.S. with machine learning (ML) on Google Earth Engine (GEE). EO-1 Hyperion images from the 2010–2013 growing seasons and DESIS images from the 2019 growing season were used to classify three world crops (corn, soybean, and winter wheat) along with other crops and non-crops near Ponca City, Oklahoma, USA. The supervised classification algorithms: Random Forest (RF), Support Vector Machine (SVM), and Naive Bayes (NB), and the unsupervised clustering algorithm WekaXMeans (WXM) were run using selected optimal Hyperion and DESIS HS narrowbands (HNBs). RF and SVM returned the highest overall producer’s, and user’s accuracies, with the performances of NB and WXM being substantially lower. The best accuracies were achieved with two or three images throughout the growing season, especially a combination of an earlier month (June or July) and a later month (August or September). The narrow 2.55 nm bandwidth of DESIS provided numerous spectral features along the 400–1000 nm spectral range relative to smoother Hyperion spectral signatures with 10 nm bandwidth in the 400–2500 nm spectral range. Out of 235 DESIS HNBs, 29 were deemed optimal for agricultural study. Advances in ML and cloud-computing can greatly facilitate HS data analysis, especially as more HS datasets, tools, and algorithms become available on the Cloud.

Remote Sensing↗

Bathymetry and acoustic backscatter data collected in 2010 from Cat Island, Mississippi

Scientists from the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center (SPCMSC), in collaboration with the U.S. Army Corps of Engineers (USACE), conducted geophysical and sedimentological surveys around Cat Island, the westernmost island in the Mississippi-Alabama barrier island chain (fig. 1). The objectives of the study were to understand the geologic evolution of Cat Island relative to other barrier islands in the northern Gulf of Mexico and to identify relationships between the geologic history, present day morphology, and sediment distribution. This report contains data from the bathymetry and side-scan sonar portion of the study collected during two geophysical cruises. Interferometric swath bathymetry and side-scan sonar data were collected aboard the RV G.K. Gilbert September 7-15, 2010. Single-beam bathymetry was collected in shallow water around the island (< 2 meter (m)) from the RV Streeterville from September 28 to October 2, 2010, to cover the data gap between the landward limit of the previous cruise and the shoreline. This report serves as an archive of processed interferometric swath and single-beam bathymetry and side scan sonar data. GIS data products include a 50-m cell size interpolated gridded bathymetry surface, trackline maps, and an acoustic side-scan sonar image. Additional files include error analysis maps, Field Activity Collection System (FACS) logs, and formal Federal Geographic Data Committee (FDGC) metadata.

Alabama;Mississippi↗

Should ground-motion records be rotated to fault-normal/parallel or maximum direction for response history analysis of buildings?

In the United States, regulatory seismic codes (for example, California Building Code) require at least two sets of horizontal ground-motion components for three-dimensional (3D) response history analysis (RHA) of building structures. For sites within 5 kilometers (3.1 miles) of an active fault, these records should be rotated to fault-normal and fault-parallel (FN/FP) directions, and two RHAs should be performed separately—when FN and then FP direction are aligned with transverse direction of the building axes. This approach is assumed to lead to two sets of responses that envelope the range of possible responses over all nonredundant rotation angles. The validity of this assumption is examined here using 3D computer models of single-story structures having symmetric (torsionally stiff) and asymmetric (torsionally flexible) layouts subjected to an ensemble of near-fault ground motions with and without apparent velocity pulses. In this parametric study, the elastic vibration period is varied from 0.2 to 5 seconds, and yield-strength reduction factors, R , are varied from a value that leads to linear-elastic design to 3 and 5. Further validations are performed using 3D computer models of 9-story structures having symmetric and asymmetric layouts subjected to the same ground-motion set. The influence of the ground-motion rotation angle on several engineering demand parameters (EDPs) is examined in both linear-elastic and nonlinear-inelastic domains to form benchmarks for evaluating the use of the FN/FP directions and also the maximum direction (MD). The MD ground motion is a new definition for horizontal ground motions for use in site-specific ground-motion procedures for seismic design according to provisions of the American Society of Civil Engineers/Seismic Engineering Institute (ASCE/SEI) 7-10. The results of this study have important implications for current practice, suggesting that ground motions rotated to MD or FN/FP directions do not necessarily provide the most critical EDPs in nonlinear-inelastic domain; however, they tend to produce larger EDPs than as-recorded (arbitrarily oriented) motions.

Open-File Report↗

An oilspill trajectory analysis model with a variable wind deflection angle

The oilspill trajectory movement algorithm consists of a vector sum of the surface drift component due to wind and the surface current component. In the U.S. Geological Survey oilspill trajectory analysis model, the surface drift component is assumed to be 3.5% of the wind speed and is rotated 20 degrees clockwise to account for Coriolis effects in the Northern Hemisphere. Field and laboratory data suggest, however, that the deflection angle of the surface drift current can be highly variable. An empirical formula, based on field observations and theoretical arguments relating wind speed to deflection angle, was used to calculate a new deflection angle at each time step in the model. Comparisons of oilspill contact probabilities to coastal areas calculated for constant and variable deflection angles showed that the model is insensitive to this changing angle at low wind speeds. At high wind speeds, some statistically significant differences in contact probabilities did appear.

Ocean Engineering↗

Improved first-order uncertainty method for water-quality modeling

Uncertainties are unavoidable in water-quality modeling and subsequent management decisions. Monte Carlo simulation and first-order uncertainty analysis (involving linearization at central values of the uncertain variables) have been frequently used to estimate probability distributions for water-quality model output due to their simplicity. Each method has its drawbacks: Monte Carlo simulation's is mainly computational time; and first-order analysis are mainly questions of accuracy and representativeness, especially for nonlinear systems and extreme conditions. An improved (advanced) first-order method is presented, where the linearization point varies to match the output level whose exceedance probability is sought. The advanced first-order method is tested on the Streeter-Phelps equation to estimate the probability distribution of critical dissolved-oxygen deficit and critical dissolved oxygen using two hypothetical examples from the literature. The advanced first-order method provides a close approximation of the exceedance probability for the Streeter-Phelps model output estimated by Monte Carlo simulation using less computer time - by two orders of magnitude - regardless of the probability distributions assumed for the uncertain model parameters.

Journal of Environmental Engineering↗

Lag and seasonality considerations in evaluating AVHRR NDVI response to precipitation

Assessment of the relationship between the normalized difference vegetation index (NDVI) and precipitation is important in understanding vegetation and climate interaction at a large scale. NDVI response to precipitation, however, is difficult to quantify due to the lag and seasonality effects, which will vary due to vegetation cover type, soils and climate. A time series analysis was performed on biweekly NDVI and precipitation around weather stations in the northern and central U.S. Great Plains. Regression models that incorporate lag and seasonality effects were used to quantify the relationship between NDVI and lagged precipitation in grasslands and croplands. It was found that the time lag was shorter in the early growing season, but longer in the mid- to late-growing season for most locations. The regression models with seasonal adjustment indicate that the relationship between NDVI and precipitation over the entire growing season was strong, with R 2 values of 0.69 and 0.72 for grasslands and croplands, respectively. We conclude that vegetation greenness can be predicted using current and antecedent precipitation, if seasonal effects are taken into account.

Photogrammetric Engineering and Remote Sensing↗

Water-quality assessment of the Albemarle-Pamlico Drainage Basin, North Carolina and Virginia; organochlorine compounds in Asiatic clam (Corbicula fluminea) soft tissues and whole redbrest sunfish (Lepomis auritus) 1992-93

The analysis of potential contaminants in biological tissues is an important part of many water-quality assessment programs, including the National Water-Quality Assessment (NAWQA) Program. Tissue analyses often are used to provide information about (1) direct threats to ecosystem integrity, and (2) the occurrence and distribution of potential contaminants in the environment. During 1992-93, Asiatic clam (Corbicula fluminea) soft tissues and whole redbreast sunfish (Lepomis auritus) samples were collected and analyzed to obtain information about the occurrence and distribution of organochlorine compounds in the Albemarle-Pamlico drainage Basin of North Carolina and Virginia. The investigation was conducted as part of the NAWQA Program. Relatively few organochlorine compounds were detected and of the compounds detected, all were detected in relatively low concentrations. The organochlorine compounds detected were p,p'-DDD, p,p'-DDE, p,p'-DDT, dieldrin, trans-nonachlor, PCB's, and toxaphene. Multiple compounds were detected at 16 of 19 sites sampled. Compared to Asiatic clams, redbreast sunfish appear to be better bioindicators of organochlorine contamination in aquatic systems. Except for one detection of toxaphene, pesticide concentrations are well below the National Academy of Sciences and National Academy of Engineering (NAS/NAE) guidelines for the protection of fish-eating wildlife.

North Carolina, Virginia↗

Metal prices in the United States through 2010

This report, which updates and revises the U.S. Geological Survey (USGS) (1999) publication, “Metal Prices in the United States Through 1998,” presents an extended price history for a wide range of metals available in a single document. Such information can be useful for the analysis of mineral commodity issues, as well as for other purposes. The chapter for each mineral commodity includes a graph of annual current and constant dollar prices for 1970 through 2010, where available; a list of significant events that affected prices; a brief discussion of the metal and its history; and one or more tables that list current dollar prices. In some cases, the metal prices presented herein are for some alternative form of an element or, instead of a price, a value, such as the value for an import as appraised by the U.S. Customs Service. Also included are the prices for steel, steel scrap, and iron ore—steel because of its importance to the elements used to alloy with it, and steel scrap and iron ore because of their use in steelmaking. A few minor metals, such as calcium, potassium, sodium, strontium, and thorium, for which price histories were insufficient, were excluded. The annual prices given may be averages for the year, yearend prices, or some other price as appropriate for a particular commodity. Certain trade journals have been the source of much of this price information—American Metal Market, ICIS Chemical Business, Engineering and Mining Journal, Industrial Minerals, Metal Bulletin, Mining Journal, Platts Metals Week, Roskill Information Services Ltd. commodity reports, and Ryan’s Notes. Price information also is available in minerals information publications of the USGS (1880–1925, 1996–present) and the U.S. Bureau of Mines (1926–95), such as Mineral Commodity Summaries, Mineral Facts and Problems, Mineral Industry Surveys, and Minerals Yearbook. In addition to prices themselves, these journals and publications contain information relevant to prices, which has been helpful in the preparation of this publication. Prices in this report have been graphed in 1992 constant dollars to show the effects of inflation as measured by the U.S. Bureau of Labor Statistics Consumer Price Index for All Urban Consumers, a widely used measure of overall inflation in the United States. These prices are not tabulated, but a table of the deflators used is given in an appendix. Constant dollar prices can be used to show how prices that producers receive would have less purchasing power.

Scientific Investigations Report↗

An analysis of potential water availability from the Charles Mill, Clendening, Piedmont, Pleasant Hill, Senecaville, and Wills Creek Lakes in the Muskingum River Watershed, Ohio

This report presents the results of a study to assess potential water availability from the Charles Mill, Clendening, Piedmont, Pleasant Hill, Senecaville, and Wills Creek Lakes, located within the Muskingum River Watershed, Ohio. The assessment was based on the criterion that water withdrawals should not appreciably affect maintenance of recreation-season pool levels in current use. To facilitate and simplify the assessment, it was assumed that historical lake operations were successful in maintaining seasonal pool levels, and that any discharges from lakes constituted either water that was discharged to prevent exceeding seasonal pool levels or discharges intended to meet minimum in-stream flow targets downstream from the lakes. It further was assumed that the volume of water discharged in excess of the minimum in-stream flow target is available for use without negatively impacting seasonal pool levels or downstream water uses and that all or part of it is subject to withdrawal. Historical daily outflow data for the lakes were used to determine the quantity of water that potentially could be withdrawn and the resulting quantity of water that would flow downstream (referred to as “flow-by”) on a daily basis as a function of all combinations of three hypothetical target minimum flow-by amounts (1, 2, and 3 times current minimum in-stream flow targets) and three pumping capacities (1, 2, and 3 million gallons per day). Using both U.S. Geological Survey streamgage data (where available) and lake-outflow data provided by the U.S. Army Corps of Engineers resulted in analytical periods ranging from 51 calendar years for Charles Mill, Clendening, and Piedmont Lakes to 74 calendar years for Pleasant Hill, Senecaville, and Wills Creek Lakes. The observed outflow time series and the computed time series of daily flow-by amounts and potential withdrawals were analyzed to compute and report order statistics (95th, 75th, 50th, 25th, 10th, and 5th percentiles) and means for the analytical period, in aggregate, and broken down by calendar month. In addition, surplus-water mass curve data were tabulated for each of the lakes. Monthly order statistics of computed withdrawals indicated that, for the three pumping capacities considered, increasing the target minimum flow-by amount tended to reduce the amount of water that can be withdrawn. The reduction was greatest in the lower percentiles of withdrawal; however, increasing the flow-by amount had no impact on potential withdrawals during high flow. In addition, for a given target minimum flow-by amount, increasing the pumping rate typically increased the total amount of water that could be withdrawn; however, that increase was less than a direct multiple of the increase in pumping rate for most flow statistics. Potential monthly withdrawals were observed to be more variable and more limited in some calendar months than others. Monthly order statistics and means of computed daily mean flow-by amounts indicated that flow-by amounts generally tended to be lowest during June–October. Increasing the target minimum flow-by amount for a given pumping rate resulted in some small increases in the magnitudes of the mean and 50th percentile and lower order statistics of computed mean flow-by, but had no effect on the magnitudes of the higher percentile statistics. Increasing the pumping rate for a given target minimum flow-by amount resulted in decreases in magnitudes of higher-percentile flow-by statistics by an amount equal to the flow equivalent of the increase in pumping rate; however, some lower percentile statistics remained unchanged.

Ohio↗

Terrestrial lidar datasets of New Orleans, Louisiana, levee failures from Hurricane Katrina, August 29, 2005

Hurricane Katrina made landfall with the northern Gulf Coast on August 29, 2005, as one of the strongest hurricanes on record. The storm damage incurred in Louisiana included a number of levee failures that led to the inundation of approximately 85 percent of the metropolitan New Orleans area. Whereas extreme levels of storm damage were expected from such an event, the catastrophic failure of the New Orleans levees prompted a quick mobilization of engineering experts to assess why and how particular levees failed. As part of this mobilization, civil engineering members of the United States Geological Survey (USGS) performed terrestrial lidar topographic surveys at major levee failures in the New Orleans area. The focus of the terrestrial lidar effort was to obtain precise measurements of the ground surface to map soil displacements at each levee site, the nonuniformity of levee height freeboard, depth of erosion where scour occurred, and distress in structures at incipient failure. In total, we investigated eight sites in the New Orleans region, including both earth and concrete floodwall levee breaks. The datasets extend from the 17th Street Canal in the Orleans East Bank area to the intersection of the Gulf Intracoastal Waterway (GIWW) with the Mississippi River Gulf Outlet (MRGO) in the New Orleans East area. The lidar scan data consists of electronic files containing millions of surveyed points. These points characterize the topography of each levee’s postfailure or incipient condition and are available for download through online hyperlinks. The data serve as a permanent archive of the catastrophic damage of Hurricane Katrina on the levee systems of New Orleans. Complete details of the data collection, processing, and georeferencing methodologies are provided in this report to assist in the visualization and analysis of the data by future users.

Louisiana↗

Data management challenges in species distribution modeling

An important component in the fields of ecology and conservation biology is understanding the environmental conditions and geographic areas that are suitable for a given species to inhabit. A common tool in determining such areas is species distribution modeling which uses computer algorithms to determine the spatial distribution of organisms. Most commonly the correlative relationships between the organism and environmental variables are the primary consideration. The data requirements for this type of modeling consist of known presence and possibly absence locations of the species as well as the values of environmental or climatic covariates thought to define the species habitat suitability at these locations. These covariate data are generally extracted from remotely sensed imagery, interpolated/gridded historical climate data, or downscaled climate model output. Traditionally, ecologists and biologists have constructed species distribution models using workflows and data that reside primarily on their local workstations or networks. This workflow is becoming challenging as scientists increasingly try to use these modeling techniques to inform management decisions under different climate change scenarios. This challenge stems from the fact that remote sensing products, gridded historical climate, and downscaled climate models are not only increasing in spatial and temporal resolution but proliferating as well. Any rigorous assessment of uncertainty requires a computationally intensive sensitivity analysis accounting for various sources of uncertainty. The scientists fitting these models generally do not have the background in computer science required to take advantage of recent advances in web-service based data acquisition, remote high-powered data processing, or scientific workflow systems. Ecologists in the field of modeling are in need of a tractable platform that abstracts the inherent computational complexity required to incorporate the burgeoning field of coupled climate and ecological response modeling. In this paper we describe the computational challenges in species distribution modeling and solutions using scientific workflow systems. We focus on the Software for Assisted Species Modeling (SAHM) a package within VisTrails, an open-source scientific workflow system.

Bulletin of the Technical Committee on Data Engine↗

Completion of the 2011 National Land Cover Database for the conterminous United States – Representing a decade of land cover change information

The National Land Cover Database (NLCD) provides nationwide data on land cover and land cover change at the native 30-m spatial resolution of the Landsat Thematic Mapper (TM). The database is designed to provide five-year cyclical updating of United States land cover and associated changes. The recent release of NLCD 2011 products now represents a decade of consistently produced land cover and impervious surface for the Nation across three periods: 2001, 2006, and 2011 (Homer et al., 2007; Fry et al., 2011). Tree canopy cover has also been produced for 2011 (Coluston et al., 2012; Coluston et al., 2013). With the release of NLCD 2011, the database provides the ability to move beyond simple change detection to monitoring and trend assessments. NLCD 2011 represents the latest evolution of NLCD products, continuing its focus on consistency, production, efficiency, and product accuracy. NLCD products are designed for widespread application in biology, climate, education, land management, hydrology, environmental planning, risk and disease analysis, telecommunications and visualization, and are available for no cost at http://www.mrlc.gov. NLCD is produced by a Federal agency consortium called the Multi-Resolution Land Characteristics Consortium (MRLC) (Wickham et al., 2014). In the consortium arrangement, the U.S. Geological Survey (USGS) leads NLCD land cover and imperviousness production for the bulk of the Nation; the National Oceanic and Atmospheric Administration (NOAA) completes NLCD land cover for the conterminous U.S. (CONUS) coastal zones; and the U.S. Forest Service (USFS) designs and produces the NLCD tree canopy cover product. Other MRLC partners collaborate through resource or data contribution to ensure NLCD products meet their respective program needs (Wickham et al., 2014).

Conterminous United States↗

A demonstration of the instream flow incremental methodology, Shenandoah River, Virginia

Current and projected demands on the water resources of the Shenandoah River have increased concerns for the potential effect of these demands on the natural integrity of the Shenandoah River system. The Instream Flow Incremental Method (IFIM) process attempts to integrate concepts of water-supply planning, analytical hydraulic engineering models, and empirically derived habitat versus flow functions to address water-use and instream-flow issues and questions concerning life-stage specific effects on selected species and the general well being of aquatic biological populations. The demonstration project also sets the stage for the identification and compilation of the major instream-flow issues in the Shenandoah River Basin, development of the required multidisciplinary technical team to conduct more detailed studies, and development of basin specific habitat and flow requirements for fish species, species assemblages, and various water uses in the Shenandoah River Basin. This report presents the results of an IFIM demonstration project, conducted on the main stem Shenandoah River in Virginia, during 1996 and 1997, using the Physical Habitat Simulation System (PHABSIM) model. Output from PHABSIM is used to address the general flow requirements for water supply and recreation and habitat for selected life stages of several fish species. The model output is only a small part of the information necessary for effective decision making and management of river resources. The information by itself is usually insufficient for formulation of recommendations regarding instream-flow requirements. Additional information, for example, can be obtained by analysis of habitat time-series data, habitat duration data, and habitat bottlenecks. Alternative-flow analysis and habitat-duration curves are presented.

Virginia↗

Effects of flood control alternatives on fish and wildlife resources of the Malheur-Harney lakes basin

Malheur Lake is the largest freshwater marsh in the western contiguous United States and is one of the main management units of the Malheur National Wildlife Refuge in southeastern Oregon. The marsh provides excellent waterfowl production habitat as well as vital migration habitats for birds in the Pacific flyway. Water shortages have typically been a problem in this semiarid area; however, record snowfalls and cool summers have recently caused Malheur Lake to rise to its highest level in recorded history. This has resulted in the loss of approximately 57,000 acres of important wildlife habitat as well as extensive flooding of local ranches, roads, and railroad lines. Because of the importance of the Refuge, any water management plan for the Malheur-Harney Lakes Basin needs to consider the impact of management alternatives on the hydrology of Malheur Lake. The facilitated modeling workshop described in this report was conducted January 14-18, 1985, under the joint sponsorship of the Portland Ecological Services Field Office and the Malheur National Wildlife Refuge, Region 1, U.S. Fish and Wildlife Service (FWS). The Portland Field Office is responsible for FWS reporting requirements on Federal water resource projects while the Refuge staff has management responsibility for much of the land affected by high water levels in the Malheur-Harney Lakes Basin. The primary objective of the workshop was to begin gathering and analyzing information concerning potential fish and wildlife impacts, needs, and opportunities associated with proposed U.S. Army Corps of Engineers (COE) flood control alternatives for Malheur Lake. The workshop was structured around the formulation of a computer model that would simulate the hydrologic effects of the various alternatives and any concommitant changes in vegetation communities and wildlife use patterns. The simulation model is composed of three connected submodels. The Hydrology submodel calculates changes in lake volume, elevation, and surface area, as well as changes in water quality, that result from the proposed water management projects (upstream storage, upstream diversions, drainage canals) and the no action alternative. The Vegetation submodel determines associated changes in the areal extent of wetland and upland vegetation communities. Finally, the Wildlife submodel calculates indices of abundance or habitat suitability for colonial nesting birds (great egret, double-crested cormorant, white-faced ibis), greater sandhill crane, diving ducks, tundra swan, dabbling ducks, and Canada goose based on hydrologic and vegetation conditions. The model represents the Malheur-Harney Lakes Basin, but provides water quantity and quality indicators associated with additional flows that might occur in the Malheur River Basin. Several management scenarios, representing various flood control alternatives and assumptions concerning future runoff, were run to analyze model behavior. Scenario results are not intended as an analysis of all potential management actions or assumptions concerning future runoff. Rather, they demonstrate the type of analysis that could be conducted if the model was sufficiently refined and tested. Early in a model development project, the process of building the model is usually of greater benefit than the model itself. The model building process stimulates interaction among agencies, assists in integrating existing information, and helps identify research needs. These benefits usually accrue even in the absence of real predictive power in the resulting model. This workshop initiated interaction among the primary State and Federal resource and development agencies in a nonadversarial forum. The exchange of information and expertise among agencies provided the FWS with the best information currently available for use in the Planning Aid Letter it will develop at the Reconnaissance state of the COE study. If the COE subsequently initiates a Feasability Study, this information will be refined further and will aid the FWS in preparing its Coordination Act Report on any flood control alternative proposed by the COE. The model building and testing process also helped identify model limitations and more general information needs that should be evaluated for further study prior to preparation of an FWS Coordination Act Report. Major needs associated with the Hydrology submodel include a more detailed representation of hydrologic units (separately consider Harney Lake, Mud Lake, and Malheur Lake or the three hydrological units within Malheur Lake, rather than a combined lake system) and explicitly representation of groundwater storage and discharge in water budget calculations. A better representation of the hydrological units will require more detailed topographic data for the basin, capacity-elevation and elevation-surface area curves for each unit, and better water flow data between the units. Additional water quality parameters and constraints on proposed canal operation due to conditions in the Malheur River might also be added. Key Vegetation submodel needs include fine-tuning existing vegetation relationships in the model and adding relationships to address the influence of historical conditions on vegetation development, effects of very rapid changes in lake level, effects of wildlife populations (e.g., carp, muskrat), responses of vegetation to habitat management actions (e.g, haying, grazing, burning), and better representation of sago pondweed dynamics. A complementary geographic information system might also be developed for spatial analyses. Major needs that should be evaluated for the Wildlife submodel include addition of other wildlife species that have important effects on habitat on the Refuge (e.g., carp, muskrat) and consideration of additional life-cycle requisites and controlling variable for species presently in the model. Some of these limitations could perhaps be overcome if historical data on habitat conditions were developed to use with historical data on wildlife populations.

Oregon↗

Evaluation of the physical process controlling beach changes adjacent to nearshore dredge pits

Numerical modeling of a beach nourishment project is conducted to enable a detailed evaluation of the processes associated with the effects of nearshore dredge pits on nourishment evolution and formation of erosion hot spots. A process-based numerical model, Delft3D, is used for this purpose. The analysis is based on the modification of existing bathymetry to simulate "what if" scenarios with/without the bathymetric features of interest. Borrow pits dredged about 30??years ago to provide sand for the nourishment project have a significant influence on project performance and formation of erosional hot spots. It was found that the main processes controlling beach response to these offshore bathymetric features were feedbacks between wave forces (roller force or alongshore component of the radiation stress), pressure gradients due to differentials in wave set-up/set-down and bed shear stress. Modeling results also indicated that backfilling of selected borrow sites showed a net positive effect within the beach fill limits and caused a reduction in the magnitude of hot spot erosion. ?? 2008 Elsevier B.V. All rights reserved.

Coastal Engineering↗