A Telescopic Approach to Modeling Leachate Dynamics and Migration at the St. Johns Landfill, Portland, Oregon

The St. Johns Landfill is a 225-acre site that lies near the confluence of the Columbia and Willamette Rivers, in the North Portland Industrial District of Portland, Oregon. A slough system surrounds the landfill on three sides with the fourth side adjacent to a shallow lake. The landfill first opened in 1930 when it was operated as an open dump. It operated as an open dump until 1969 when it was converted to a sanitary landfill, employing daily cover and compaction. The landfill was closed in 1991. The landfill sits directly on top of a thick layer of silty overbank deposits. Directly below the overbank deposits lie a highly productive aquifer system. Concern has arisen about the landfill\u27 s impact on the underlying aquifers as well as the surface waters directly adjacent to the site. Past studies have hypothesized that the thick layer of overbank deposits provides a barrier to contaminant transport into the lower aquifers. The purpose of this project is to quantify the fate and transport of contamination exiting the landfill. To properly assess the flow and transport dynamics, a telescopic approach is used which nests a series of six groundwater models; each designed to provide uniquely specific information concerning the site. Contaminant mounding within the landfill due to rainfall provides the driving force for contaminant migration. The modeling system represents the quantitative inter-relationships between the landfill, the surface waters, and the underlying aquifer system. The distribution of fluxes between the surface and groundwater is controlled by the anisotropy of the overbank deposits. Predictions show that the majority of the contaminants move laterally out of the landfill and into the surrounding slough system. The model also predicts that the underlying aquifer system has been impacted, but only in localized \u27hot spots\u27. After the landfill is capped in 1991, contaminant migration is slowed due to the reduction of the contaminant mound. Future impact on the surrounding area at this point is due to regional flow dynamics controlled mainly by the regional recharge characteristics and the Columbia and Willamette Rivers

Reconstruction of a high-resolution late holocene arctic paleoclimate record from Colville River delta sediments.

This work was partially supported by the Sandia National Laboratories,Laboratory Directed Research and Development' (LDRD) fellowship program in conjunction with Texas A&M University (TAMU). The research described herein is the work of Kathryn M. Schreiner (Katie') and her advisor, Thomas S. Bianchi and represents a concise description of Katie's dissertation that was submitted to the TAMU Office of Graduate Studies in May 2013 in partial fulfillment of her doctorate of philosophy degree. High Arctic permafrost soils contain a massive amount of organic carbon, accounting for twice as much carbon as what is currently stored as carbon dioxide in the atmosphere. However, with current warming trends this sink is in danger of thawing and potentially releasing large amounts of carbon as both carbon dioxide and methane into the atmosphere. It is difficult to make predictions about the future of this sink without knowing how it has reacted to past temperature and climate changes. This project investigated long term, fine scale particulate organic carbon (POC) delivery by the high-Arctic Colville River into Simpson's Lagoon in the near-shore Beaufort Sea. Modern POC was determined to be a mixture of three sources (riverine soils, coastal erosion, and marine). Downcore POC measurements were performed in a core close to the Colville River output and a core close to intense coastal erosion. Inputs of the three major sources were found to vary throughout the last two millennia, and in the Colville River core covary significantly with Alaskan temperature reconstructions

Viability report for the ByWater Lakes project

This report presents the results from the hydrological, ecological, and renewable energy assessments conducted by Sandia National Laboratories at the ByWater Lakes site in Espanola, New Mexico for ByWater Recreation LLC and Avanyu Energy Services through the New Mexico small business assistance (NMSBA) program. Sandia's role was to assess the viability and provide perspective for enhancing the site to take advantage of renewable energy resources, improve and sustain the natural systems, develop a profitable operation, and provide an asset for the local community. Integral to this work was the identification the pertinent data and data gaps as well as making general observations about the potential issues and concerns that may arise from further developing the site. This report is informational only with no consideration with regards to the business feasibility of the various options that ByWater and Avanyu may be pursuing

SNL-NUMO collaborative : development of a deterministic site characterization tool using multi-model ranking and inference.

Uncertainty in site characterization arises from a lack of data and knowledge about a site and includes uncertainty in the boundary conditions, uncertainty in the characteristics, location, and behavior of major features within an investigation area (e.g., major faults as barriers or conduits), uncertainty in the geologic structure, as well as differences in numerical implementation (e.g., 2-D versus 3-D, finite difference versus finite element, grid resolution, deterministic versus stochastic, etc.). Since the true condition at a site can never be known, selection of the best conceptual model is very difficult. In addition, limiting the understanding to a single conceptualization too early in the process, or before data can support that conceptualization, may lead to confidence in a characterization that is unwarranted as well as to data collection efforts and field investigations that are misdirected and/or redundant. Using a series of numerical modeling experiments, this project examined the application and use of information criteria within the site characterization process. The numerical experiments are based on models of varying complexity that were developed to represent one of two synthetically developed groundwater sites; (1) a fully hypothetical site that represented a complex, multi-layer, multi-faulted site, and (2) a site that was based on the Horonobe site in northern Japan. Each of the synthetic sites were modeled in detail to provide increasingly informative 'field' data over successive iterations to the representing numerical models. The representing numerical models were calibrated to the synthetic site data and then ranked and compared using several different information criteria approaches. Results show, that for the early phases of site characterization, low-parameterized models ranked highest while more complex models generally ranked lowest. In addition, predictive capabilities were also better with the low-parameterized models. For the latter iterations, when more data were available, the information criteria rankings tended to converge on the higher parameterized models. Analysis of the numerical experiments suggest that information criteria rankings can be extremely useful for site characterization, but only when the rankings are placed in context and when the contribution of each bias term is understood

Merging spatially variant physical process models under an optimized systems dynamics framework.

The complexity of water resource issues, its interconnectedness to other systems, and the involvement of competing stakeholders often overwhelm decision-makers and inhibit the creation of clear management strategies. While a range of modeling tools and procedures exist to address these problems, they tend to be case specific and generally emphasize either a quantitative and overly analytic approach or present a qualitative dialogue-based approach lacking the ability to fully explore consequences of different policy decisions. The integration of these two approaches is needed to drive toward final decisions and engender effective outcomes. Given these limitations, the Computer Assisted Dispute Resolution system (CADRe) was developed to aid in stakeholder inclusive resource planning. This modeling and negotiation system uniquely addresses resource concerns by developing a spatially varying system dynamics model as well as innovative global optimization search techniques to maximize outcomes from participatory dialogues. Ultimately, the core system architecture of CADRe also serves as the cornerstone upon which key scientific innovation and challenges can be addressed

initMIP-Antarctica: an ice sheet model initialization experiment of ISMIP6

Ice sheet numerical modeling is an important tool to estimate the dynamic contribution of the Antarctic ice sheet to sea level rise over the coming centuries. The influence of initial conditions on ice sheet model simulations, however, is still unclear. To better understand this influence, an initial state intercomparison exercise (initMIP) has been developed to compare, evaluate, and improve initialization procedures and estimate their impact on century-scale simulations. initMIP is the first set of experiments of the Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6), which is the primary Coupled Model Intercomparison Project Phase 6 (CMIP6) activity focusing on the Greenland and Antarctic ice sheets. Following initMIP-Greenland, initMIP-Antarctica has been designed to explore uncertainties associated with model initialization and spin-up and to evaluate the impact of changes in external forcings. Starting from the state of the Antarctic ice sheet at the end of the initialization procedure, three forward experiments are each run for 100 years: a control run, a run with a surface mass balance anomaly, and a run with a basal melting anomaly beneath floating ice. This study presents the results of initMIP-Antarctica from 25 simulations performed by 16 international modeling groups. The submitted results use different initial conditions and initialization methods, as well as ice flow model parameters and reference external forcings. We find a good agreement among model responses to the surface mass balance anomaly but large variations in responses to the basal melting anomaly. These variations can be attributed to differences in the extent of ice shelves and their upstream tributaries, the numerical treatment of grounding line, and the initial ocean conditions applied, suggesting that ongoing efforts to better represent ice shelves in continental-scale models should continue

Future Sea Level Change Under Coupled Model Intercomparison Project Phase 5 and Phase 6 Scenarios From the Greenland and Antarctic Ice Sheets

Projections of the sea level contribution from the Greenland and Antarctic ice sheets (GrIS and AIS) rely on atmospheric and oceanic drivers obtained from climate models. The Earth System Models participating in the Coupled Model Intercomparison Project phase 6 (CMIP6) generally project greater future warming compared with the previous Coupled Model Intercomparison Project phase 5 (CMIP5) effort. Here we use four CMIP6 models and a selection of CMIP5 models to force multiple ice sheet models as part of the Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6). We find that the projected sea level contribution at 2100 from the ice sheet model ensemble under the CMIP6 scenarios falls within the CMIP5 range for the Antarctic ice sheet but is significantly increased for Greenland. Warmer atmosphere in CMIP6 models results in higher Greenland mass loss due to surface melt. For Antarctica, CMIP6 forcing is similar to CMIP5 and mass gain from increased snowfall counteracts increased loss due to ocean warming

Atmospheric methane isotopes identify inventory knowledge gaps in the Surat Basin, Australia, coal seam gas and agricultural regions

In-flight measurements of atmospheric methane (CH4(a)) and mass balance flux quantification studies can assist with verification and improvement in the UNFCCC National Inventory reported CH4 emissions. In the Surat Basin gas fields, Queensland, Australia, coal seam gas (CSG) production and cattle farming are two of the major sources of CH4 emissions into the atmosphere. Because of the rapid mixing of adjacent plumes within the convective boundary layer, spatially attributing CH4(a) mole fraction readings to one or more emission sources is difficult. The primary aims of this study were to use the CH4(a) isotopic composition (13CCH4(a)) of in-flight atmospheric air (IFAA) samples to assess where the bottom-up (BU) inventory developed specifically for the region was well characterised and to identify gaps in the BU inventory (missing sources or over- and underestimated source categories). Secondary aims were to investigate whether IFAA samples collected downwind of predominantly similar inventory sources were useable for characterising the isotopic signature of CH4 sources (13CCH4(s)) and to identify mitigation opportunities. IFAA samples were collected between 100-350m above ground level (ma.g.l.) over a 2-week period in September 2018. For each IFAA sample the 2h back-trajectory footprint area was determined using the NOAA HYSPLIT atmospheric trajectory modelling application. IFAA samples were gathered into sets, where the 2h upwind BU inventory had >50% attributable to a single predominant CH4 source (CSG, grazing cattle, or cattle feedlots). Keeling models were globally fitted to these sets using multiple regression with shared parameters (background-air CH4(b) and 13CCH4(b)). For IFAA samples collected from 250-350ma.g.l. altitude, the best-fit 13CCH4(s) signatures compare well with the ground observation: CSG 13CCH4(s) of -55.4‰ (confidence interval (CI) 95%±13.7‰) versus 13CCH4(s) of -56.7‰ to -45.6‰; grazing cattle 13CCH4(s) of -60.5‰ (CI 95%±15.6‰) versus -61.7‰ to -57.5‰. For cattle feedlots, the derived 13CCH4(s) (-69.6‰, CI 95%±22.6‰), was isotopically lighter than the ground-based study (13CCH4(s) from -65.2‰ to -60.3‰) but within agreement given the large uncertainty for this source. For IFAA samples collected between 100-200ma.g.l. the 13CCH4(s) signature for the CSG set (-65.4‰, CI 95%±13.3‰) was isotopically lighter than expected, suggesting a BU inventory knowledge gap or the need to extend the population statistics for CSG 13CCH4(s) signatures. For the 100-200ma.g.l. set collected over grazing cattle districts the 13CCH4(s) signature (-53.8‰, CI 95%±17.4‰) was heavier than expected from the BU inventory. An isotopically light set had a low 13CCH4(s) signature of -80.2‰ (CI 95%±4.7‰). A CH4 source with this low 13CCH4(s) signature has not been incorporated into existing BU inventories for the region. Possible sources include termites and CSG brine ponds. If the excess emissions are from the brine ponds, they can potentially be mitigated. It is concluded that in-flight atmospheric 13CCH4(a) measurements used in conjunction with endmember mixing modelling of CH4 sources are powerful tools for BU inventory verification

Risk assessment of climate systems for national security.

Climate change, through drought, flooding, storms, heat waves, and melting Arctic ice, affects the production and flow of resource within and among geographical regions. The interactions among governments, populations, and sectors of the economy require integrated assessment based on risk, through uncertainty quantification (UQ). This project evaluated the capabilities with Sandia National Laboratories to perform such integrated analyses, as they relate to (inter)national security. The combining of the UQ results from climate models with hydrological and economic/infrastructure impact modeling appears to offer the best capability for national security risk assessments

The status of the world's land and marine mammals: diversity, threat, and knowledge

Knowledge of mammalian diversity is still surprisingly disparate, both regionally and taxonomically. Here, we present a comprehensive assessment of the conservation status and distribution of the world's mammals. Data, compiled by 1700+ experts, cover all 5487 species, including marine mammals. Global macroecological patterns are very different for land and marine species but suggest common mechanisms driving diversity and endemism across systems. Compared with land species, threat levels are higher among marine mammals, driven by different processes (accidental mortality and pollution, rather than habitat loss), and are spatially distinct (peaking in northern oceans, rather than in Southeast Asia). Marine mammals are also disproportionately poorly known. These data are made freely available to support further scientific developments and conservation action