Estimation of Fractional Plant Lifeform Cover Using Landsat and Airborne LiDAR/hyperspectral Data

NASA Astrophysics Data System (ADS)

Parra, A. S.; Xu, Q.; Dilts, T.; Weisberg, P.; Greenberg, J. A.

2017-12-01

Land-cover change has generally been understood as the result of local, landscape or regional-scale processes with most studies focusing on case-study landscapes or smaller regions. However, as we observe similar types of land-cover change occurring across different biomes worldwide, it becomes clear that global-scale processes such as climate change and CO2 fertilization, in interaction with local influences, are underlying drivers in land-cover change patterns. Prior studies on global land-cover change may not have had a suitable spatial, temporal and thematic resolution for allowing the identification of such patterns. Furthermore, the lack of globally consistent spatial data products also constitutes a limiting factor in evaluating both proximate and ultimate causes of land-cover change. In this study, we derived a global model for broadleaf tree, needleleaf tree, shrub, herbaceous, and "other" fractional cover using Landsat imagery. Combined LiDAR/hyperspectral data sets were used for calibration and validation of the Landsat-derived products. Spatially explicit uncertainties were also created as part of the data products. Our results highlight the potential for large-scale studies that model local and global influences on land-cover transition types and rates at fine thematic, spatial, and temporal resolutions. These spatial data products are relevant for identifying patterns in land-cover change due to underlying global-scale processes and can provide valuable insights into climatic and land-use factors determining vegetation distributions.

Impact of Land Cover Characterization and Properties on Snow Albedo in Climate Models

NASA Astrophysics Data System (ADS)

Wang, L.; Bartlett, P. A.; Chan, E.; Montesano, P.

2017-12-01

The simulation of winter albedo in boreal and northern environments has been a particular challenge for land surface modellers. Assessments of output from CMIP3 and CMIP5 climate models have revealed that many simulations are characterized by overestimation of albedo in the boreal forest. Recent studies suggest that inaccurate representation of vegetation distribution, improper simulation of leaf area index, and poor treatment of canopy-snow processes are the primary causes of albedo errors. While several land cover datasets are commonly used to derive plant functional types (PFT) for use in climate models, new land cover and vegetation datasets with higher spatial resolution have become available in recent years. In this study, we compare the spatial distribution of the dominant PFTs and canopy cover fractions based on different land cover datasets, and present results from offline simulations of the latest version Canadian Land Surface Scheme (CLASS) over the northern Hemisphere land. We discuss the impact of land cover representation and surface properties on winter albedo simulations in climate models.

Distributed Modelling of Stormflow Generation: Assessing the Effect of Ground Cover

NASA Astrophysics Data System (ADS)

Jarihani, B.; Sidle, R. C.; Roth, C. H.; Bartley, R.; Wilkinson, S. N.

2017-12-01

Understanding the effects of grazing management and land cover changes on surface hydrology is important for water resources and land management. A distributed hydrological modelling platform, wflow, (that was developed as part of Deltares's OpenStreams project) is used to assess the effect of land management practices on runoff generation processes. The model was applied to Weany Creek, a small catchment (13.6 km2) of the Burdekin Basin, North Australia, which is being studied to understand sources of sediment and nutrients to the Great Barrier Reef. Satellite and drone-based ground cover data, high resolution topography from LiDAR, soil properties, and distributed rainfall data were used to parameterise the model. Wflow was used to predict total runoff, peak runoff, time of rise, and lag time for several events of varying magnitudes and antecedent moisture conditions. A nested approach was employed to calibrate the model by using recorded flow hydrographs at three scales: (1) a hillslope sub-catchment: (2) a gullied sub-catchment; and the 13.6 km2 catchment outlet. Model performance was evaluated by comparing observed and predicted stormflow hydrograph attributes using the Nash Sutcliffe efficiency metric. By using a nested approach, spatiotemporal patterns of overland flow occurrence across the catchment can also be evaluated. The results show that a process-based distributed model can be calibrated to simulate spatial and temporal patterns of runoff generation processes, to help identify dominant processes which may be addressed by land management to improve rainfall retention. The model will be used to assess the effects of ground cover changes due to management practices in grazed lands on storm runoff.

Spatial analysis and statistical modelling of snow cover dynamics in the Central Himalayas, Nepal

NASA Astrophysics Data System (ADS)

Weidinger, Johannes; Gerlitz, Lars; Böhner, Jürgen

2017-04-01

General circulation models are able to predict large scale climate variations in global dimensions, however small scale dynamic characteristics, such as snow cover and its temporal variations in high mountain regions, are not represented sufficiently. Detailed knowledge about shifts in seasonal ablation times and spatial distribution of snow cover are crucial for various research interests. Since high mountain areas, for instance the Central Himalayas in Nepal, are generally remote, it is difficult to obtain data in high spatio-temporal resolutions. Regional climate models and downscaling techniques are implemented to compensate coarse resolution. Furthermore earth observation systems, such as MODIS, also permit bridging this gap to a certain extent. They offer snow (cover) data in daily temporal and medium spatial resolution of around 500 m, which can be applied as evaluation and training data for dynamical hydrological and statistical analyses. Within this approach two snow distribution models (binary snow cover and fractional snow cover) as well as one snow recession model were implemented for a research domain in the Rolwaling Himal in Nepal, employing the random forest technique, which represents a state of the art machine learning algorithm. Both bottom-up strategies provide inductive reasoning to derive rules for snow related processes out of climate (temperature, precipitation and irradiance) and climate-related topographic data sets (elevation, aspect and convergence index) obtained by meteorological network stations, remote sensing products (snow cover - MOD10-A1 and land surface temperatures - MOD11-A1) along with GIS. Snow distribution is predicted reliably on a daily basis in the research area, whereas further effort is necessary for predicting daily snow cover recession processes adequately. Swift changes induced by clear sky conditions with high insolation rates are well represented, whereas steady snow loss still needs continuing effort. All approaches underline the technical difficulties of snow cover modelling during the monsoon season, in accordance with previous studies. The developed methods in combination with continuous in situ measurements provide a basis for further downscaling approaches.

Neutral model analysis of landscape patterns from mathematical morphology

Treesearch

Kurt H. Riitters; Peter Vogt; Pierre Soille; Jacek Kozak; Christine Estreguil

2007-01-01

Mathematical morphology encompasses methods for characterizing land-cover patterns in ecological research and biodiversity assessments. This paper reports a neutral model analysis of patterns in the absence of a structuring ecological process, to help set standards for comparing and interpreting patterns identified by mathematical morphology on real land-cover maps. We...

Spatially explicit land-use and land-cover scenarios for the Great Plains of the United States

USGS Publications Warehouse

Sohl, Terry L.; Sleeter, Benjamin M.; Sayler, Kristi L.; Bouchard, Michelle A.; Reker, Ryan R.; Bennett, Stacie L.; Sleeter, Rachel R.; Kanengieter, Ronald L.; Zhu, Zhi-Liang

2012-01-01

The Great Plains of the United States has undergone extensive land-use and land-cover change in the past 150 years, with much of the once vast native grasslands and wetlands converted to agricultural crops, and much of the unbroken prairie now heavily grazed. Future land-use change in the region could have dramatic impacts on ecological resources and processes. A scenario-based modeling framework is needed to support the analysis of potential land-use change in an uncertain future, and to mitigate potentially negative future impacts on ecosystem processes. We developed a scenario-based modeling framework to analyze potential future land-use change in the Great Plains. A unique scenario construction process, using an integrated modeling framework, historical data, workshops, and expert knowledge, was used to develop quantitative demand for future land-use change for four IPCC scenarios at the ecoregion level. The FORE-SCE model ingested the scenario information and produced spatially explicit land-use maps for the region at relatively fine spatial and thematic resolutions. Spatial modeling of the four scenarios provided spatial patterns of land-use change consistent with underlying assumptions and processes associated with each scenario. Economically oriented scenarios were characterized by significant loss of natural land covers and expansion of agricultural and urban land uses. Environmentally oriented scenarios experienced modest declines in natural land covers to slight increases. Model results were assessed for quantity and allocation disagreement between each scenario pair. In conjunction with the U.S. Geological Survey's Biological Carbon Sequestration project, the scenario-based modeling framework used for the Great Plains is now being applied to the entire United States.

Research on application of intelligent computation based LUCC model in urbanization process

NASA Astrophysics Data System (ADS)

Chen, Zemin

2007-06-01

Global change study is an interdisciplinary and comprehensive research activity with international cooperation, arising in 1980s, with the largest scopes. The interaction between land use and cover change, as a research field with the crossing of natural science and social science, has become one of core subjects of global change study as well as the front edge and hot point of it. It is necessary to develop research on land use and cover change in urbanization process and build an analog model of urbanization to carry out description, simulation and analysis on dynamic behaviors in urban development change as well as to understand basic characteristics and rules of urbanization process. This has positive practical and theoretical significance for formulating urban and regional sustainable development strategy. The effect of urbanization on land use and cover change is mainly embodied in the change of quantity structure and space structure of urban space, and LUCC model in urbanization process has been an important research subject of urban geography and urban planning. In this paper, based upon previous research achievements, the writer systematically analyzes the research on land use/cover change in urbanization process with the theories of complexity science research and intelligent computation; builds a model for simulating and forecasting dynamic evolution of urban land use and cover change, on the basis of cellular automation model of complexity science research method and multi-agent theory; expands Markov model, traditional CA model and Agent model, introduces complexity science research theory and intelligent computation theory into LUCC research model to build intelligent computation-based LUCC model for analog research on land use and cover change in urbanization research, and performs case research. The concrete contents are as follows: 1. Complexity of LUCC research in urbanization process. Analyze urbanization process in combination with the contents of complexity science research and the conception of complexity feature to reveal the complexity features of LUCC research in urbanization process. Urban space system is a complex economic and cultural phenomenon as well as a social process, is the comprehensive characterization of urban society, economy and culture, and is a complex space system formed by society, economy and nature. It has dissipative structure characteristics, such as opening, dynamics, self-organization, non-balance etc. Traditional model cannot simulate these social, economic and natural driving forces of LUCC including main feedback relation from LUCC to driving force. 2. Establishment of Markov extended model of LUCC analog research in urbanization process. Firstly, use traditional LUCC research model to compute change speed of regional land use through calculating dynamic degree, exploitation degree and consumption degree of land use; use the theory of fuzzy set to rewrite the traditional Markov model, establish structure transfer matrix of land use, forecast and analyze dynamic change and development trend of land use, and present noticeable problems and corresponding measures in urbanization process according to research results. 3. Application of intelligent computation research and complexity science research method in LUCC analog model in urbanization process. On the basis of detailed elaboration of the theory and the model of LUCC research in urbanization process, analyze the problems of existing model used in LUCC research (namely, difficult to resolve many complexity phenomena in complex urban space system), discuss possible structure realization forms of LUCC analog research in combination with the theories of intelligent computation and complexity science research. Perform application analysis on BP artificial neural network and genetic algorithms of intelligent computation and CA model and MAS technology of complexity science research, discuss their theoretical origins and their own characteristics in detail, elaborate the feasibility of them in LUCC analog research, and bring forward improvement methods and measures on existing problems of this kind of model. 4. Establishment of LUCC analog model in urbanization process based on theories of intelligent computation and complexity science. Based on the research on abovementioned BP artificial neural network, genetic algorithms, CA model and multi-agent technology, put forward improvement methods and application assumption towards their expansion on geography, build LUCC analog model in urbanization process based on CA model and Agent model, realize the combination of learning mechanism of BP artificial neural network and fuzzy logic reasoning, express the regulation with explicit formula, and amend the initial regulation through self study; optimize network structure of LUCC analog model and methods and procedures of model parameters with genetic algorithms. In this paper, I introduce research theory and methods of complexity science into LUCC analog research and presents LUCC analog model based upon CA model and MAS theory. Meanwhile, I carry out corresponding expansion on traditional Markov model and introduce the theory of fuzzy set into data screening and parameter amendment of improved model to improve the accuracy and feasibility of Markov model in the research on land use/cover change.

Transient and asymptotic behavior in a regular network model for the ice-albedo feedback under thermal forcing

NASA Astrophysics Data System (ADS)

Mueller-Stoffels, M.; Wackerbauer, R.

2010-12-01

The Arctic ocean and sea ice form a feedback system which plays an important role in the global climate. Variations of the global ice and snow distribution have a significant effect on the planetary albedo which governs the absorption of shortwave radiation. The complexity of highly parametrized GCMs makes it very difficult to assess single feedback processes in the climate system without the concurrent use of simple models where the physics are understood [1][2][3]. We introduce a complex systems model to investigate thermodynamic feedback processes in an Arctic ice-ocean layer. The ice-ocean layer is represented as a regular network of coupled cells. The state of each cell is determined by its energy content, which also defines the phase of the cell. The energy transport between cells is described with nonlinear and heterogeneous diffusion constants. And the time-evolution of the ice-ocean is driven by shortwave, longwave and lateral oceanic and atmospheric thermal forcing. This model is designed to study the stability of an ice cover under various heat intake scenarios. The network structure of the model allows to easily introduce albedo heterogeneities due to aging ice, wind blown snow cover, and ice movement to explore the time-evolution and pattern formation (melt ponds) processes in the Arctic sea ice. The solely thermodynamic model exhibits two stable states; one in the perennially ice covered domain and one in the perennially open water domain. Their existence is due to the temperature dependence of the longwave radiative budget. Transition between these states can be forced via lateral heat fluxes. During the transition from the ice covered to the open water stable state the ice albedo feedback effects are manifested as an increased warming rate of the ice cover together with enhanced seasonal energy oscillations. In the current model realization seasonal ice cover is present as a transient state only. Furthermore, the model exhibits hysteresis between the ice covered and the open water state when varying the lateral atmospheric (or oceanic) heat intake. Once the ice-ocean layer has transitioned from the ice covered to the open water stable state significant cooling (reduction of lateral fluxes) is necessary to return to the ice covered stable state. We also find that ocean heat fluxes are more efficient than atmospheric heat fluxes to melt Arctic sea ice; only small portions of heat entering from the bottom of the ice-ocean layer induce already a transition to the stable asymptotic state with perennial open water. This indicates that ocean currents, understood as heat conveyors, can play a significant role in melting continuous ice covers. This is consistent with the findings of Shimada et al. for the Canada basin [4]. References: [1] S. Bony et al., How well do we understand and evaluate climate change feedback processes?, J of Climate 19, 3445 (2006). [2]I. Eisenman and J.S. Wettlaufer, Nonlinear threshold behavior during the loss of Arctic sea ice, PNAS 106, 28 (2009). [3]A.S. Thorndike, A Toy Model Linking Atmospheric and Thermal Radiation and Sea Ice Growth, JGR 97, 9401 (1992). [4] K. Shimada et al., Paci[|#12#|]c Ocean inflow: Influence on catastrophic reduction of sea ice cover in the Arctic Ocean, GRL 33, L08605 (2006).

Integrated modelling of anthropogenic land-use and land-cover change on the global scale

NASA Astrophysics Data System (ADS)

Schaldach, R.; Koch, J.; Alcamo, J.

2009-04-01

In many cases land-use activities go hand in hand with substantial modifications of the physical and biological cover of the Earth's surface, resulting in direct effects on energy and matter fluxes between terrestrial ecosystems and the atmosphere. For instance, the conversion of forest to cropland is changing climate relevant surface parameters (e.g. albedo) as well as evapotranspiration processes and carbon flows. In turn, human land-use decisions are also influenced by environmental processes. Changing temperature and precipitation patterns for example are important determinants for location and intensity of agriculture. Due to these close linkages, processes of land-use and related land-cover change should be considered as important components in the construction of Earth System models. A major challenge in modelling land-use change on the global scale is the integration of socio-economic aspects and human decision making with environmental processes. One of the few global approaches that integrates functional components to represent both anthropogenic and environmental aspects of land-use change, is the LandSHIFT model. It simulates the spatial and temporal dynamics of the human land-use activities settlement, cultivation of food crops and grazing management, which compete for the available land resources. The rational of the model is to regionalize the demands for area intensive commodities (e.g. crop production) and services (e.g. space for housing) from the country-level to a global grid with the spatial resolution of 5 arc-minutes. The modelled land-use decisions within the agricultural sector are influenced by changing climate and the resulting effects on biomass productivity. Currently, this causal chain is modelled by integrating results from the process-based vegetation model LPJmL model for changing crop yields and net primary productivity of grazing land. Model output of LandSHIFT is a time series of grid maps with land-use/land-cover information that can serve as basis for further impact analysis. An exemplary simulation study with LandSHIFT is presented, based on scenario assumptions from the UNEP Global Environmental Outlook 4. Time horizon of the analysis is the year 2050. Changes of future food production on country level are computed by the agro-economy model IMPACT as a function of demography, economic development and global trade pattern. Together with scenario assumptions on climatic change and population growth, this data serves as model input to compute the changing land-use und land-cover. The continental and global scale model results are then analysed with respect to changes in the spatial pattern of natural vegetation as well as the resulting effects on evapotranspiration processes and land surface parameters. Furthermore, possible linkages of LandSHIFT to the different components of Earth System models (e.g. climate and natural vegetation) are discussed.

Rapid Crop Cover Mapping for the Conterminous United States.

PubMed

Dahal, Devendra; Wylie, Bruce; Howard, Danny

2018-06-05

Timely crop cover maps with sufficient resolution are important components to various environmental planning and research applications. Through the modification and use of a previously developed crop classification model (CCM), which was originally developed to generate historical annual crop cover maps, we hypothesized that such crop cover maps could be generated rapidly during the growing season. Through a process of incrementally removing weekly and monthly independent variables from the CCM and implementing a 'two model mapping' approach, we found it viable to generate conterminous United States-wide rapid crop cover maps at a resolution of 250 m for the current year by the month of September. In this approach, we divided the CCM model into one 'crop type model' to handle the classification of nine specific crops and a second, binary model to classify the presence or absence of 'other' crops. Under the two model mapping approach, the training errors were 0.8% and 1.5% for the crop type and binary model, respectively, while test errors were 5.5% and 6.4%, respectively. With spatial mapping accuracies for annual maps reaching upwards of 70%, this approach demonstrated a strong potential for generating rapid crop cover maps by the 1 st of September.

Toward a space materials systems program

NASA Technical Reports Server (NTRS)

Vontiesenhausen, G. F.

1981-01-01

A program implementation model is presented which covers the early stages of space material processing and manufacturing. The model includes descriptions of major program elements, development and experiment requirements in space materials processing and manufacturing, and an integration of the model into NASA's long range plans as well as its evolution from present Materials Processing in Space plans.

Towards extensive spatio-temporal reconstructions of North American land cover: a comparison of state-of-the-art pollen-vegetation models

NASA Astrophysics Data System (ADS)

Dawson, A.; Trachsel, M.; Goring, S. J.; Paciorek, C. J.; McLachlan, J. S.; Jackson, S. T.; Williams, J. W.

2017-12-01

Pollen records have been extensively used to reconstruct past changes in vegetation and study the underlying processes. However, developing the statistical techniques needed to accurately represent both data and process uncertainties is a formidable challenge. Recent advances in paleoecoinformatics (e.g. the Neotoma Paleoecology Database and the European Pollen Database), Bayesian age-depth models, and process-based pollen-vegetation models, and Bayesian hierarchical modeling have pushed paleovegetation reconstructions forward to a point where multiple sources of uncertainty can be incorporated into reconstructions, which in turn enables new hypotheses to be asked and more rigorous integration of paleovegetation data with earth system models and terrestrial ecosystem models. Several kinds of pollen-vegetation models have been developed, notably LOVE/REVEALS, STEPPS, and classical transfer functions such as the modern analog technique. LOVE/REVEALS has been adopted as the standard method for the LandCover6k effort to develop quantitative reconstructions of land cover for the Holocene, while STEPPS has been developed recently as part of the PalEON project and applied to reconstruct with uncertainty shifts in forest composition in New England and the upper Midwest during the late Holocene. Each PVM has different assumptions and structure and uses different input data, but few comparisons among approaches yet exist. Here, we present new reconstructions of land cover change in northern North America during the Holocene based on LOVE/REVEALS and data drawn from the Neotoma database and compare STEPPS-based reconstructions to those from LOVE/REVEALS. These parallel developments with LOVE/REVEALS provide an opportunity to compare and contrast models, and to begin to generate continental scale reconstructions, with explicit uncertainties, that can provide a base for interdisciplinary research within the biogeosciences. We show how STEPPS provides an important benchmark for past land-cover reconstruction, and how the LandCover 6k effort in North America advances our understanding of the past by allowing cross-continent comparisons using standardized methods and quantifying the impact of humans in the early Anthropocene.

Spatially explicit modeling of 1992-2100 land cover and forest stand age for the conterminous United States

USGS Publications Warehouse

Sohl, Terry L.; Sayler, Kristi L.; Bouchard, Michelle; Reker, Ryan R.; Friesz, Aaron M.; Bennett, Stacie L.; Sleeter, Benjamin M.; Sleeter, Rachel R.; Wilson, Tamara; Soulard, Christopher E.; Knuppe, Michelle; Van Hofwegen, Travis

2014-01-01

Information on future land-use and land-cover (LULC) change is needed to analyze the impact of LULC change on ecological processes. The U.S. Geological Survey has produced spatially explicit, thematically detailed LULC projections for the conterminous United States. Four qualitative and quantitative scenarios of LULC change were developed, with characteristics consistent with the Intergovernmental Panel on Climate Change (IPCC) Special Report on 5 Emission Scenarios (SRES). The four quantified scenarios (A1B, A2, B1, and B2) served as input to the Forecasting Scenarios of Land-use Change (FORE-SCE) model. Four spatially explicit datasets consistent with scenario storylines were produced for the conterminous United States, with annual LULC maps from 1992 through 2100. The future projections are characterized by a loss of natural land covers in most scenarios, with corresponding expansion of 10 anthropogenic land uses. Along with the loss of natural land covers, remaining natural land covers experience increased fragmentation under most scenarios, with only the B2 scenario remaining relatively stable in both proportion of remaining natural land covers and basic fragmentation measures. Forest stand age was also modeled. By 2100, scenarios and ecoregions with heavy forest cutting have relatively lower mean stand ages compared to those with less 15 forest cutting. Stand ages differ substantially between unprotected and protected forest lands, as well as between different forest classes. The modeled data were compared to the National Land Cover Database (NLCD) and other data sources to assess model characteristics. The consistent, spatially explicit, and thematically detailed LULC projections and the associated forest stand age data layers have been used to analyze LULC impacts on carbon and greenhouse gas fluxes, 20 biodiversity, climate and weather variability, hydrologic change, and other ecological processes.

Temperature Calculations in the Coastal Modeling System

DTIC Science & Technology

2017-04-01

tide) and river discharge at model boundaries, wave radiation stress, and wind forcing over a model computational domain. Physical processes calculated...calculated in the CMS using the following meteorological parameters: solar radiation, cloud cover, air temperature, wind speed, and surface water temperature...during a clear (i.e., cloudless) sky (Wm-2); CLDC is the cloud cover fraction (0-1.0); SWR is the surface reflection coefficient; and SHDf is the

Global land-atmosphere coupling associated with cold climate processes

NASA Astrophysics Data System (ADS)

Dutra, Emanuel

This dissertation constitutes an assessment of the role of cold processes, associated with snow cover, in controlling the land-atmosphere coupling. The work was based on model simulations, including offline simulations with the land surface model HTESSEL, and coupled atmosphere simulations with the EC-EARTH climate model. A revised snow scheme was developed and tested in HTESSEL and EC-EARTH. The snow scheme is currently operational at the European Centre for Medium-Range Weather Forecasts integrated forecast system, and in the default configuration of EC-EARTH. The improved representation of the snowpack dynamics in HTESSEL resulted in improvements in the near surface temperature simulations of EC-EARTH. The new snow scheme development was complemented with the option of multi-layer version that showed its potential in modeling thick snowpacks. A key process was the snow thermal insulation that led to significant improvements of the surface water and energy balance components. Similar findings were observed when coupling the snow scheme to lake ice, where lake ice duration was significantly improved. An assessment on the snow cover sensitivity to horizontal resolution, parameterizations and atmospheric forcing within HTESSEL highlighted the role of the atmospheric forcing accuracy and snowpack parameterizations in detriment of horizontal resolution over flat regions. A set of experiments with and without free snow evolution was carried out with EC-EARTH to assess the impact of the interannual variability of snow cover on near surface and soil temperatures. It was found that snow cover interannual variability explained up to 60% of the total interannual variability of near surface temperature over snow covered regions. Although these findings are model dependent, the results showed consistency with previously published work. Furthermore, the detailed validation of the snow dynamics simulations in HTESSEL and EC-EARTH guarantees consistency of the results.

Global albedo change and radiative cooling from anthropogenic land-cover change, 1700 to 2005 based on MODIS, land-use harmonization and radiative kernels

USDA-ARS?s Scientific Manuscript database

Widespread anthropogenic land-cover change over the last five centuries has influenced the global climate system through both biogeochemical and biophysical processes. Models indicate that warming from carbon emissions associated with land cover conversion have been partially offset if not outweigh...

Application of a COSMO Mesoscale Model to Assess the Influence of Forest Cover Changes on Regional Weather Conditions

NASA Astrophysics Data System (ADS)

Olchev, A.; Rozinkina, I.; Kuzmina, E.; Nikitin, M.; Rivin, G. S.

2017-12-01

Modern changes in land use and forest cover have a significant influence on local, regional, and global weather and climate conditions. In this study, the mesoscale model COSMO is used to estimate the possible influence of forest cover change in the central part of the East European Plain on regional weather conditions. The "model region" of the study is surrounded by geographical coordinates 55° and 59°N and 28° and 37°E and situated in the central part of a large modeling domain (50° - 70° N and 15° 55° E), covering almost the entire East European Plain in Northern Eurasia. The forests cover about 50% of the area of the "model region". The modeling study includes 3 main numerical experiments. The first assumes total deforestation of the "model region" and replacement of forests by grasslands. The second is represented by afforestation of the "model region." In the third, weather conditions are simulated with present land use and vegetation structures of the "model region." Output of numerical experiments is at 13.2 km grid resolution, and the ERA-Interim global atmospheric reanalysis (with 6-h resolution in time and 0.75°×0.75° in space) is used to quantify initial and boundary conditions. Numerical experiments for the warm period of 2010 taken as an example show that deforestation and afforestation processes in the selected region can lead to significant changes in weather conditions. Deforestation processes in summer conditions can result in increased air temperature and wind speed, reduction of precipitation, lower clouds, and relative humidity. The afforestation process can result in opposite effects (decreased air temperature, increased precipitation, higher air humidity and fog frequency, and strengthened storm winds). Maximum meteorological changes under forest cover changes are projected for the summer months (July and August). It was also shown that changes of some meteorological characteristics (e.g., air temperature) is observed in the "model region" only, and changes in precipitation amount are seen in the entire territory of the East European Plain, even in areas which are a great distance from the boundaries of the "model region." The study was supported by a grant from the Russian Science Foundation (14-14-00956).

A conceptual water balance model to explore the impact of different soil management on water availability for vineyards under contrasting environments

NASA Astrophysics Data System (ADS)

Gomez, Jose Alfonso; Guzman, Gema; Lorite, Ignacio

2016-04-01

Vines are one of the most extended tree crops in Europe covering a wide range of environmental and management conditions. Soil management is a key element in maintaining vines in adequate agronomic conditions, as well as in determining not only yield but also grape quality. The soil management practices adopted in vineyards could favor accelerated erosion. Particularly, cultivation with rows running up-and-down the slope on sloping vineyards, maintenance of bare soil, compaction due to high traffic of machinery are some of the vineyard's management practices that expose soil to degradation, favoring runoff and soil erosion processes. In fact high erosion rates in vines have been recently reported by Gomez et al., (2011). The adoption of grass cover in vineyards as a soil management technique has a fundamental role in soil protection against erosion, but it can have a major impact on water balance and then in grape yield and quality. This effect, the possibility of competition for soil water with the vine, is in fact mentioned by vine growers as a limiting factor for use of cover crops in vineyards under semiarid conditions or during dry periods even in sub-humid climates. To evaluate the interaction between the use of cover crops and soil management adjustments (eg. spatial extension in the vineyard and time for seeding and mowing) In order to achieve an optimum equilibrium between soil protection and grape production we developed a conceptual water balance model that reproduces the major processes in vineyards, WABYN. This model simulates the effect of different soil management alternatives, as for instance conventional tillage or cover crop, on soil water balance components. It has been implemented in a user friendly interface in order to allow its use by technicians and other stakeholders in the vine sector. It follows the methodology of a previous model specific for olive orchards (Abazi et al., 2012) using a model called WABOL. In spite of this simplified interface for the user, the model uses process-based methodologies to describe the key processes controlling water balance in rainfed or irrigated vines, such as runoff, deep percolation, cover crop growth, soil evaporation and vine and cover crop transpiration. This is possible using a complete model programmed in Fortran and executed from Excel as a DLL. This communication presents a preliminary version of the model, as well as an evaluation of different scenarios of soil management impact on soil water balance in vines of different typologies under different soil and climate conditions. Keywords: vines, cover crop, soil management, water balance References Abazi, U., Lorite, I.J., Cárceles, B., Martínez Raya, A., Durán, V.H., Francia, J.R., Gómez, J.A. 2012. WABOL: A conceptual water balance model for analyzing rainfall water use in olive orchards under different soil and cover crop management strategies. Computers and Electronics in Agriculture, 91: 35-48. Gómez, J.A., Llewellyn, C., Basch, G, Sutton, P.B., Dyson, J.S., Jones, C.A. 2011. The effects of cover crops and conventional tillage on soil and runoff loss in vineyards and olive groves in several Mediterranean countries. Soil Use and Management 27: 502 - 514

Integrating land management into Earth system models: the importance of land use transitions at sub-grid-scale

NASA Astrophysics Data System (ADS)

Pongratz, Julia; Wilkenskjeld, Stiig; Kloster, Silvia; Reick, Christian

2014-05-01

Recent studies indicate that changes in surface climate and carbon fluxes caused by land management (i.e., modifications of vegetation structure without changing the type of land cover) can be as large as those caused by land cover change. Further, such effects may occur on substantial areas: while about one quarter of the land surface has undergone land cover change, another fifty percent are managed. This calls for integration of management processes in Earth system models (ESMs). This integration increases the importance of awareness and agreement on how to diagnose effects of land use in ESMs to avoid additional model spread and thus unnecessary uncertainties in carbon budget estimates. Process understanding of management effects, their model implementation, as well as data availability on management type and extent pose challenges. In this respect, a significant step forward has been done in the framework of the current IPCC's CMIP5 simulations (Coupled Model Intercomparison Project Phase 5): The climate simulations were driven with the same harmonized land use dataset that, different from most datasets commonly used before, included information on two important types of management: wood harvest and shifting cultivation. However, these new aspects were employed by only part of the CMIP5 models, while most models continued to use the associated land cover maps. Here, we explore the consequences for the carbon cycle of including subgrid-scale land transformations ("gross transitions"), such as shifting cultivation, as example of the current state of implementation of land management in ESMs. Accounting for gross transitions is expected to increase land use emissions because it represents simultaneous clearing and regrowth of natural vegetation in different parts of the grid cell, reducing standing carbon stocks. This process cannot be captured by prescribing land cover maps ("net transitions"). Using the MPI-ESM we find that ignoring gross transitions underestimates emissions substantially, for historical times by about 40%. Implementation of land management such as gross transitions is a step forward in terms of comprehensiveness of simulated processes. However, it has increased model spread in carbon fluxes, because land management processes have been considered by only a subset of recent ESMs contributing to major projects such as IPCC or the Global Carbon Project. This model spread still causes the net land use flux to be the most uncertain component in the global carbon budget. Other causes have previously been identified as differences in land use datasets, differing types of vegetation model, accounting of nutrient limitation, the inclusion of land use feedbacks (increase in atmospheric CO2 due to land use emissions causing terrestrial carbon uptake), and a confusion of whether the net land use flux in ESMs should be reported as instantaneous emissions, or also account for delayed carbon responses and regrowth. These differences explain a factor 2-6 difference between model estimates and are expected to be further affected by interactions with land management. This highlights the importance of an accurate protocol for future model intercomparisons of carbon fluxes from land cover change and land management to ensure comparison of the same processes and fluxes.

Predicting future land cover change and its impact on streamflow and sediment load in a trans-boundary river basin

NASA Astrophysics Data System (ADS)

Wang, Jie; Wang, Hao; Ning, Shaowei; Hiroshi, Ishidaira

2018-06-01

Sediment load can provide very important perspective on erosion of river basin. The changes of human-induced vegetation cover, such as deforestation or afforestation, affect sediment yield process of a catchment. We have already evaluated that climate change and land cover change changed the historical streamflow and sediment yield, and land cover change is the main factor in Red river basin. But future streamflow and sediment yield changes under potential future land cover change scenario still have not been evaluated. For this purpose, future scenario of land cover change is developed based on historical land cover changes and land change model (LCM). In addition, future leaf area index (LAI) is simulated by ecological model (Biome-BGC) based on future land cover scenario. Then future scenarios of land cover change and LAI are used to drive hydrological model and new sediment rating curve. The results of this research provide information that decision-makers need in order to promote water resources planning efforts. Besides that, this study also contributes a basic framework for assessing climate change impacts on streamflow and sediment yield that can be applied in the other basins around the world.

High resolution climate scenarios for snowmelt modelling in small alpine catchments

NASA Astrophysics Data System (ADS)

Schirmer, M.; Peleg, N.; Burlando, P.; Jonas, T.

2017-12-01

Snow in the Alps is affected by climate change with regard to duration, timing and amount. This has implications with respect to important societal issues as drinking water supply or hydropower generation. In Switzerland, the latter received a lot of attention following the political decision to phase out of nuclear electricity production. An increasing number of authorization requests for small hydropower plants located in small alpine catchments was observed in the recent years. This situation generates ecological conflicts, while the expected climate change poses a threat to water availability thus putting at risk investments in such hydropower plants. Reliable high-resolution climate scenarios are thus required, which account for small-scale processes to achieve realistic predictions of snowmelt runoff and its variability in small alpine catchments. We therefore used a novel model chain by coupling a stochastic 2-dimensional weather generator (AWE-GEN-2d) with a state-of-the-art energy balance snow cover model (FSM). AWE-GEN-2d was applied to generate ensembles of climate variables at very fine temporal and spatial resolution, thus providing all climatic input variables required for the energy balance modelling. The land-surface model FSM was used to describe spatially variable snow cover accumulation and melt processes. The FSM was refined to allow applications at very high spatial resolution by specifically accounting for small-scale processes, such as a subgrid-parametrization of snow covered area or an improved representation of forest-snow processes. For the present study, the model chain was tested for current climate conditions using extensive observational dataset of different spatial and temporal coverage. Small-scale spatial processes such as elevation gradients or aspect differences in the snow distribution were evaluated using airborne LiDAR data. 40-year of monitoring data for snow water equivalent, snowmelt and snow-covered area for entire Switzerland was used to verify snow distribution patterns at coarser spatial and temporal scale. The ability of the model chain to reproduce current climate conditions in small alpine catchments makes this model combination an outstanding candidate to produce high resolution climate scenarios of snowmelt in small alpine catchments.

Land Surface Model Biases and their Impacts on the Assimilation of Snow-related Observations

NASA Astrophysics Data System (ADS)

Arsenault, K. R.; Kumar, S.; Hunter, S. M.; Aman, R.; Houser, P. R.; Toll, D.; Engman, T.; Nigro, J.

2007-12-01

Some recent snow modeling studies have employed a wide range of assimilation methods to incorporate snow cover or other snow-related observations into different hydrological or land surface models. These methods often include taking both model and observation biases into account throughout the model integration. This study focuses more on diagnosing the model biases and presenting their subsequent impacts on assimilating snow observations and modeled snowmelt processes. In this study, the land surface model, the Community Land Model (CLM), is used within the Land Information System (LIS) modeling framework to show how such biases impact the assimilation of MODIS snow cover observations. Alternative in-situ and satellite-based observations are used to help guide the CLM LSM in better predicting snowpack conditions and more realistic timing of snowmelt for a western US mountainous region. Also, MODIS snow cover observation biases will be discussed, and validation results will be provided. The issues faced with inserting or assimilating MODIS snow cover at moderate spatial resolutions (like 1km or less) will be addressed, and the impacts on CLM will be presented.

Strategy and the Learning Organization: A Maturity Model for the Formation of Strategy

ERIC Educational Resources Information Center

Kenny, John

2006-01-01

Purpose: To develop a theoretical model for strategic change that links learning in an organization to the strategic process. Design/methodology/approach: The model was developed from a review of literature covering a range of areas including: management, strategic planning, psychology of learning and organizational learning. The process of…

Improving Running Times for the Determination of Fractional Snow-Covered Area from Landsat TM/ETM+ via Utilization of the CUDA® Programming Paradigm

NASA Astrophysics Data System (ADS)

McGibbney, L. J.; Rittger, K.; Painter, T. H.; Selkowitz, D.; Mattmann, C. A.; Ramirez, P.

2014-12-01

As part of a JPL-USGS collaboration to expand distribution of essential climate variables (ECV) to include on-demand fractional snow cover we describe our experience and implementation of a shift towards the use of NVIDIA's CUDA® parallel computing platform and programming model. In particular the on-demand aspect of this work involves the improvement (via faster processing and a reduction in overall running times) for determination of fractional snow-covered area (fSCA) from Landsat TM/ETM+. Our observations indicate that processing tasks associated with remote sensing including the Snow Covered Area and Grain Size Model (SCAG) when applied to MODIS or LANDSAT TM/ETM+ are computationally intensive processes. We believe the shift to the CUDA programming paradigm represents a significant improvement in the ability to more quickly assert the outcomes of such activities. We use the TMSCAG model as our subject to highlight this argument. We do this by describing how we can ingest a LANDSAT surface reflectance image (typically provided in HDF format), perform spectral mixture analysis to produce land cover fractions including snow, vegetation and rock/soil whilst greatly reducing running time for such tasks. Within the scope of this work we first document the original workflow used to assert fSCA for Landsat TM and it's primary shortcomings. We then introduce the logic and justification behind the switch to the CUDA paradigm for running single as well as batch jobs on the GPU in order to achieve parallel processing. Finally we share lessons learned from the implementation of myriad of existing algorithms to a single set of code in a single target language as well as benefits this ultimately provides scientists at the USGS.

Sampling intensity and normalizations: Exploring cost-driving factors in nationwide mapping of tree canopy cover

Treesearch

John Tipton; Gretchen Moisen; Paul Patterson; Thomas A. Jackson; John Coulston

2012-01-01

There are many factors that will determine the final cost of modeling and mapping tree canopy cover nationwide. For example, applying a normalization process to Landsat data used in the models is important in standardizing reflectance values among scenes and eliminating visual seams in the final map product. However, normalization at the national scale is expensive and...

High dimensional land cover inference using remotely sensed modis data

NASA Astrophysics Data System (ADS)

Glanz, Hunter S.

Image segmentation persists as a major statistical problem, with the volume and complexity of data expanding alongside new technologies. Land cover classification, one of the most studied problems in Remote Sensing, provides an important example of image segmentation whose needs transcend the choice of a particular classification method. That is, the challenges associated with land cover classification pervade the analysis process from data pre-processing to estimation of a final land cover map. Many of the same challenges also plague the task of land cover change detection. Multispectral, multitemporal data with inherent spatial relationships have hardly received adequate treatment due to the large size of the data and the presence of missing values. In this work we propose a novel, concerted application of methods which provide a unified way to estimate model parameters, impute missing data, reduce dimensionality, classify land cover, and detect land cover changes. This comprehensive analysis adopts a Bayesian approach which incorporates prior knowledge to improve the interpretability, efficiency, and versatility of land cover classification and change detection. We explore a parsimonious, parametric model that allows for a natural application of principal components analysis to isolate important spectral characteristics while preserving temporal information. Moreover, it allows us to impute missing data and estimate parameters via expectation-maximization (EM). A significant byproduct of our framework includes a suite of training data assessment tools. To classify land cover, we employ a spanning tree approximation to a lattice Potts prior to incorporate spatial relationships in a judicious way and more efficiently access the posterior distribution of pixel labels. We then achieve exact inference of the labels via the centroid estimator. To detect land cover changes, we develop a new EM algorithm based on the same parametric model. We perform simulation studies to validate our models and methods, and conduct an extensive continental scale case study using MODIS data. The results show that we successfully classify land cover and recover the spatial patterns present in large scale data. Application of our change point method to an area in the Amazon successfully identifies the progression of deforestation through portions of the region.

Geophysical study of the structure and processes of the continental convergence zones: Alpine-Himalayan belt

NASA Technical Reports Server (NTRS)

Toksoz, M. N.; Molnar, P.

1983-01-01

Studies of the structure of the continental collision zones using seismic and body waves, theoretical modelling of the thermal regime of the convergence processes, and studies of earthquake mechanisms and deformation aspects of the model are covered.

NASA/MSFC FY-85 Atmospheric Processes Research Review

NASA Technical Reports Server (NTRS)

Vaughan, W. W. (Compiler); Porter, F. (Compiler)

1985-01-01

The two main areas of focus for the research program are global scale processes and mesoscale processes. Geophysical fluid processes, satellite doppler lidar, satellite data analysis, atmospheric electricity, doppler lidar wind research, and mesoscale modeling are among the topics covered.

Rapid crop cover mapping for the conterminous United States

USGS Publications Warehouse

Dahal, Devendra; Wylie, Bruce K.; Howard, Daniel

2018-01-01

Timely crop cover maps with sufficient resolution are important components to various environmental planning and research applications. Through the modification and use of a previously developed crop classification model (CCM), which was originally developed to generate historical annual crop cover maps, we hypothesized that such crop cover maps could be generated rapidly during the growing season. Through a process of incrementally removing weekly and monthly independent variables from the CCM and implementing a ‘two model mapping’ approach, we found it viable to generate conterminous United States-wide rapid crop cover maps at a resolution of 250 m for the current year by the month of September. In this approach, we divided the CCM model into one ‘crop type model’ to handle the classification of nine specific crops and a second, binary model to classify the presence or absence of ‘other’ crops. Under the two model mapping approach, the training errors were 0.8% and 1.5% for the crop type and binary model, respectively, while test errors were 5.5% and 6.4%, respectively. With spatial mapping accuracies for annual maps reaching upwards of 70%, this approach demonstrated a strong potential for generating rapid crop cover maps by the 1st of September.

Process of establishing a plane-wave system on ice cover over a dipole moving uniformly in an ideal fluid column

NASA Astrophysics Data System (ADS)

Il'ichev, A. T.; Savin, A. S.

2017-12-01

We consider a planar evolution problem for perturbations of the ice cover by a dipole starting its uniform rectilinear horizontal motion in a column of an initially stationary fluid. Using asymptotic Fourier analysis, we show that at supercritical velocities, waves of two types form on the water-ice interface. We describe the process of establishing these waves during the dipole motion. We assume that the fluid is ideal and incompressible and its motion is potential. The ice cover is modeled by the Kirchhoff-Love plate.

Modelling catchment hydrological responses in a Himalayan Lake as a function of changing land use and land cover

NASA Astrophysics Data System (ADS)

Badar, Bazigha; Romshoo, Shakil A.; Khan, M. A.

2013-04-01

In this paper, we evaluate the impact of changing land use/land cover (LULC) on the hydrological processes in Dal lake catchment of Kashmir Himalayas by integrating remote sensing, simulation modelling and extensive field observations. Over the years, various anthropogenic pressures in the lake catchment have significantly altered the land system, impairing, inter-alia, sustained biotic communities and water quality of the lake. The primary objective of this paper was to help a better understanding of the LULC change, its driving forces and the overall impact on the hydrological response patterns. Multi-sensor and multi-temporal satellite data for 1992 and 2005 was used for determining the spatio-temporal dynamics of the lake catchment. Geographic Information System (GIS) based simulation model namely Generalized Watershed Loading Function (GWLF) was used to model the hydrological processes under the LULC conditions. We discuss spatio-temporal variations in LULC and identify factors contributing to these variations and analyze the corresponding impacts of the change on the hydrological processes like runoff, erosion and sedimentation. The simulated results on the hydrological responses reveal that depletion of the vegetation cover in the study area and increase in impervious and bare surface cover due to anthropogenic interventions are the primary reasons for the increased runoff, erosion and sediment discharges in the Dal lake catchment. This study concludes that LULC change in the catchment is a major concern that has disrupted the ecological stability and functioning of the Dal lake ecosystem.

Using weather prediction data for simulation of mesoscale atmospheric processes

NASA Astrophysics Data System (ADS)

Bart, Andrey A.; Starchenko, Alexander V.

2015-11-01

The paper presents an approach to specify initial and boundary conditions from the output data of global model SLAV for mesoscale modelling of atmospheric processes in areas not covered by meteorological observations. From the data and the model equations for a homogeneous atmospheric boundary layer the meteorological and turbulent characteristics of the atmospheric boundary layer are calculated.

Modeling Paragenesis: Erosion Opposite to Gravity in Cave Channels

NASA Astrophysics Data System (ADS)

Cooper, M. P.; Covington, M. D.

2017-12-01

Sediment plays an important role in bedrock channels, providing both tools and cover that influence patterns of bed erosion. It has also been shown that sediment load influences bedrock channel width, with increased sediment leading to wider channels. A variety of models have been developed to explore these effects. In caves, it is hypothesized that sediments covering the floors of fully flooded channels that are forming beneath the water table (phreatic zone) can force dissolution upwards towards the water table, leading to upward erosion balanced by gradual deposition of sediment within the channel bottom. This strange process is termed paragenesis, and while there are conceptual and experimental models of the process, no prior mathematical models of cave passage evolution has captured these effects. Consequently, there is little quantitative understanding of the processes that drive paragenesis and how they link to the morphology of the cave channels that develop. We adapt a previously developed algorithm for estimating boundary shear stress within channels with free-surface flows to enable calculation of boundary shear stress in pipe-full conditions. This model successfully duplicates scaling relationships in surface channels, and geometries of caves formed in the phreatic zone such as phreatic tubes. Once sediment flux is incorporated the model successfully duplicates the hypothesized processes of paragenetic gallery formation: the cover effect prevents dissolution in the direction of gravity; passages are enlarged upwards reducing the sediment transport capacity; sediment is deposited and the process drives a continuing feedback loop. Simulations reveal that equilibrium paragenetic channel widths scale with both sediment flux and discharge. Unlike in open channel settings, increased sediment load actually narrows paragenetic channels. The cross section evolution model also reveals that the existence of equilibrium widths in such galleries requires erosion to scale with shear stress, suggesting a role of either mechanical erosion or transport limited dissolution. These types of erosion contrast with current numerical models of speleogenesis, where chemically limited dissolution, a process independent of shear stress, is predicted to occur in most turbulent flow settings.

Electrospining of polyaniline/poly(lactic acid) ultrathin fibers: process and statistical modeling using a non-gaussian approach

USDA-ARS?s Scientific Manuscript database

Cover: The electrospinning technique was employed to obtain conducting nanofibers based on polyaniline and poly(lactic acid). A statistical model was employed to describe how the process factors (solution concentration, applied voltage, and flow rate) govern the fiber dimensions. Nanofibers down to ...

How Students Learn: Information Processing, Intellectual Development and Confrontation

ERIC Educational Resources Information Center

Entwistle, Noel

1975-01-01

A model derived from information processing theory is described, which helps to explain the complex verbal learning of students and suggests implications for lecturing techniques. Other factors affecting learning, which are not covered by the model, are discussed in relationship to it: student's intellectual development and effects of individual…

Species richness and soil properties in Pinus ponderosa forests: A structural equation modeling analysis

USGS Publications Warehouse

Laughlin, D.C.; Abella, S.R.; Covington, W.W.; Grace, J.B.

2007-01-01

Question: How are the effects of mineral soil properties on understory plant species richness propagated through a network of processes involving the forest overstory, soil organic matter, soil nitrogen, and understory plant abundance? Location: North-central Arizona, USA. Methods: We sampled 75 0.05-ha plots across a broad soil gradient in a Pinus ponderosa (ponderosa pine) forest ecosystem. We evaluated multivariate models of plant species richness using structural equation modeling. Results: Richness was highest at intermediate levels of understory plant cover, suggesting that both colonization success and competitive exclusion can limit richness in this system. We did not detect a reciprocal positive effect of richness on plant cover. Richness was strongly related to soil nitrogen in the model, with evidence for both a direct negative effect and an indirect non-linear relationship mediated through understory plant cover. Soil organic matter appeared to have a positive influence on understory richness that was independent of soil nitrogen. Richness was lowest where the forest overstory was densest, which can be explained through indirect effects on soil organic matter, soil nitrogen and understory cover. Finally, model results suggest a variety of direct and indirect processes whereby mineral soil properties can influence richness. Conclusions: Understory plant species richness and plant cover in P. ponderosa forests appear to be significantly influenced by soil organic matter and nitrogen, which are, in turn, related to overstory density and composition and mineral soil properties. Thus, soil properties can impose direct and indirect constraints on local species diversity in ponderosa pine forests. ?? IAVS; Opulus Press.

Development of a MODIS-Derived Surface Albedo Data Set: An Improved Model Input for Processing the NSRDB

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maclaurin, Galen; Sengupta, Manajit; Xie, Yu

A significant source of bias in the transposition of global horizontal irradiance to plane-of-array (POA) irradiance arises from inaccurate estimations of surface albedo. The current physics-based model used to produce the National Solar Radiation Database (NSRDB) relies on model estimations of surface albedo from a reanalysis climatalogy produced at relatively coarse spatial resolution compared to that of the NSRDB. As an input to spectral decomposition and transposition models, more accurate surface albedo data from remotely sensed imagery at finer spatial resolutions would improve accuracy in the final product. The National Renewable Energy Laboratory (NREL) developed an improved white-sky (bi-hemispherical reflectance)more » broadband (0.3-5.0 ..mu..m) surface albedo data set for processing the NSRDB from two existing data sets: a gap-filled albedo product and a daily snow cover product. The Moderate Resolution Imaging Spectroradiometer (MODIS) sensors onboard the Terra and Aqua satellites have provided high-quality measurements of surface albedo at 30 arc-second spatial resolution and 8-day temporal resolution since 2001. The high spatial and temporal resolutions and the temporal coverage of the MODIS sensor will allow for improved modeling of POA irradiance in the NSRDB. However, cloud and snow cover interfere with MODIS observations of ground surface albedo, and thus they require post-processing. The MODIS production team applied a gap-filling methodology to interpolate observations obscured by clouds or ephemeral snow. This approach filled pixels with ephemeral snow cover because the 8-day temporal resolution is too coarse to accurately capture the variability of snow cover and its impact on albedo estimates. However, for this project, accurate representation of daily snow cover change is important in producing the NSRDB. Therefore, NREL also used the Integrated Multisensor Snow and Ice Mapping System data set, which provides daily snow cover observations of the Northern Hemisphere for the temporal extent of the NSRDB (1998-2015). We provide a review of validation studies conducted on these two products and describe the methodology developed by NREL to remap the data products to the NSRDB grid and integrate them into a seamless daily data set.« less

An in-mold packaging process for plastic fluidic devices.

PubMed

Yoo, Y E; Lee, K H; Je, T J; Choi, D S; Kim, S K

2011-01-01

Micro or nanofluidic devices have many channel shapes to deliver chemical solutions, body fluids or any fluids. The channels in these devices should be covered to prevent the fluids from overflowing or leaking. A typical method to fabricate an enclosed channel is to bond or weld a cover plate to a channel plate. This solid-to-solid bonding process, however, takes a considerable amount of time for mass production. In this study, a new process for molding a cover layer that can enclose open micro or nanochannels without solid-to-solid bonding is proposed and its feasibility is estimated. First, based on the design of a model microchannel, a brass microchannel master core was machined and a plastic microchannel platform was injection-molded. Using this molded platform, a series of experiments was performed for four process or mold design parameters. Some feasible conditions were successfully found to enclosed channels without filling the microchannels for the injection molding of a cover layer over the plastic microchannel platform. In addition, the bond strength and seal performance were estimated in a comparison with those done by conventional bonding or welding processes.

Fractional Snow Cover Mapping by Artificial Neural Networks and Support Vector Machines

NASA Astrophysics Data System (ADS)

Çiftçi, B. B.; Kuter, S.; Akyürek, Z.; Weber, G.-W.

2017-11-01

Snow is an important land cover whose distribution over space and time plays a significant role in various environmental processes. Hence, snow cover mapping with high accuracy is necessary to have a real understanding for present and future climate, water cycle, and ecological changes. This study aims to investigate and compare the design and use of artificial neural networks (ANNs) and support vector machines (SVMs) algorithms for fractional snow cover (FSC) mapping from satellite data. ANN and SVM models with different model building settings are trained by using Moderate Resolution Imaging Spectroradiometer surface reflectance values of bands 1-7, normalized difference snow index and normalized difference vegetation index as predictor variables. Reference FSC maps are generated from higher spatial resolution Landsat ETM+ binary snow cover maps. Results on the independent test data set indicate that the developed ANN model with hyperbolic tangent transfer function in the output layer and the SVM model with radial basis function kernel produce high FSC mapping accuracies with the corresponding values of R = 0.93 and R = 0.92, respectively.

Automated image processing of LANDSAT 2 digital data for watershed runoff prediction

NASA Technical Reports Server (NTRS)

Sasso, R. R.; Jensen, J. R.; Estes, J. E.

1977-01-01

The U.S. Soil Conservation Service (SCS) model for watershed runoff prediction uses soil and land cover information as its major drivers. Kern County Water Agency is implementing the SCS model to predict runoff for 10,400 sq cm of mountainous watershed in Kern County, California. The Remote Sensing Unit, University of California, Santa Barbara, was commissioned by KCWA to conduct a 230 sq cm feasibility study in the Lake Isabella, California region to evaluate remote sensing methodologies which could be ultimately extrapolated to the entire 10,400 sq cm Kern County watershed. Digital results indicate that digital image processing of Landsat 2 data will provide usable land cover required by KCWA for input to the SCS runoff model.

Toward mechanistic models of action-oriented and detached cognition.

PubMed

Pezzulo, Giovanni

2016-01-01

To be successful, the research agenda for a novel control view of cognition should foresee more detailed, computationally specified process models of cognitive operations including higher cognition. These models should cover all domains of cognition, including those cognitive abilities that can be characterized as online interactive loops and detached forms of cognition that depend on internally generated neuronal processing.

Statistical design and analysis for plant cover studies with multiple sources of observation errors

USGS Publications Warehouse

Wright, Wilson; Irvine, Kathryn M.; Warren, Jeffrey M .; Barnett, Jenny K.

2017-01-01

Effective wildlife habitat management and conservation requires understanding the factors influencing distribution and abundance of plant species. Field studies, however, have documented observation errors in visually estimated plant cover including measurements which differ from the true value (measurement error) and not observing a species that is present within a plot (detection error). Unlike the rapid expansion of occupancy and N-mixture models for analysing wildlife surveys, development of statistical models accounting for observation error in plants has not progressed quickly. Our work informs development of a monitoring protocol for managed wetlands within the National Wildlife Refuge System.Zero-augmented beta (ZAB) regression is the most suitable method for analysing areal plant cover recorded as a continuous proportion but assumes no observation errors. We present a model extension that explicitly includes the observation process thereby accounting for both measurement and detection errors. Using simulations, we compare our approach to a ZAB regression that ignores observation errors (naïve model) and an “ad hoc” approach using a composite of multiple observations per plot within the naïve model. We explore how sample size and within-season revisit design affect the ability to detect a change in mean plant cover between 2 years using our model.Explicitly modelling the observation process within our framework produced unbiased estimates and nominal coverage of model parameters. The naïve and “ad hoc” approaches resulted in underestimation of occurrence and overestimation of mean cover. The degree of bias was primarily driven by imperfect detection and its relationship with cover within a plot. Conversely, measurement error had minimal impacts on inferences. We found >30 plots with at least three within-season revisits achieved reasonable posterior probabilities for assessing change in mean plant cover.For rapid adoption and application, code for Bayesian estimation of our single-species ZAB with errors model is included. Practitioners utilizing our R-based simulation code can explore trade-offs among different survey efforts and parameter values, as we did, but tuned to their own investigation. Less abundant plant species of high ecological interest may warrant the additional cost of gathering multiple independent observations in order to guard against erroneous conclusions.

Modelling the role of basement block rotation and strike-slip faulting on structural pattern in the cover units of fold-and-thrust belts

NASA Astrophysics Data System (ADS)

Koyi, Hemin; Nilfouroushan, Faramarz; Hessami, Khaled

2015-04-01

A series of scaled analogue models are run to study the degree of coupling between basement block kinematics and cover deformation. In these models, rigid basal blocks were rotated about vertical axis in a "bookshelf" fashion, which caused strike-slip faulting along the blocks and, to some degrees, in the overlying cover units of loose sand. Three different combinations of cover basement deformations are modeled; cover shortening prior to basement fault movement; basement fault movement prior to shortening of cover units; and simultaneous cover shortening with basement fault movement. Model results show that the effect of basement strike-slip faults depends on the timing of their reactivation during the orogenic process. Pre- and syn-orogen basement strike-slip faults have a significant impact on the structural pattern of the cover units, whereas post-orogenic basement strike-slip faults have less influence on the thickened hinterland of the overlying fold-and-thrust belt. The interaction of basement faulting and cover shortening results in formation of rhomb features. In models with pre- and syn-orogen basement strike-slip faults, rhomb-shaped cover blocks develop as a result of shortening of the overlying cover during basement strike-slip faulting. These rhombic blocks, which have resemblance to flower structures, differ in kinematics, genesis and structural extent. They are bounded by strike-slip faults on two opposite sides and thrusts on the other two sides. In the models, rhomb-shaped cover blocks develop as a result of shortening of the overlying cover during basement strke-slip faulting. Such rhomb features are recognized in the Alborz and Zagros fold-and-thrust belts where cover units are shortened simultaneously with strike-slip faulting in the basement. Model results are also compared with geodetic results obtained from combination of all available GPS velocities in the Zagros and Alborz FTBs. Geodetic results indicate domains of clockwise and anticlockwise rotation in these two FTBs. The typical pattern of structures and their spatial distributions are used to suggest clockwise block rotation of basement blocks about vertical axes and their associated strike-slip faulting in both west-central Alborz and the southeastern part of the Zagros fold-and-thrust belt.

Cloud cover models derived from satellite radiation measurements

NASA Technical Reports Server (NTRS)

Bean, S. J.; Somerville, P. N.

1979-01-01

Using daily measurement of day and night infrared and incoming and absorbed solar radiation obtained from a TIROS satellite over a period of approximately 45 months, and integrated over 2.5 degree latitude-longitude grids, the proportion of cloud cover over each grid each day was derived for the entire period. For each of four three-month periods, estimates a and b of the two parameters of the best-fit beta distribution were obtained for each grid location. The (a,b) plane was divided into a number of regions. All the geographical locations whose (a,b) estimates were in the same region in the (a,b) plane were said to have the same cloud cover type for that season. For each season, the world was thus divided into separate cloud cover types. Using estimates of mean cloud cover for each season, the world was again divided into separate cloud cover types. The process was repeated for standard deviations. Thus for each season, three separate cloud cover models were obtained using the criteria of shape of frequency distribution, mean cloud cover, and variability of cloud cover. The cloud cover statistics were derived from once-a-day, near-local-noon satellite radiation measurements.

Data sets for snow cover monitoring and modelling from the National Snow and Ice Data Center

NASA Astrophysics Data System (ADS)

Holm, M.; Daniels, K.; Scott, D.; McLean, B.; Weaver, R.

2003-04-01

A wide range of snow cover monitoring and modelling data sets are pending or are currently available from the National Snow and Ice Data Center (NSIDC). In-situ observations support validation experiments that enhance the accuracy of remote sensing data. In addition, remote sensing data are available in near-real time, providing coarse-resolution snow monitoring capability. Time series data beginning in 1966 are valuable for modelling efforts. NSIDC holdings include SMMR and SSM/I snow cover data, MODIS snow cover extent products, in-situ and satellite data collected for NASA's recent Cold Land Processes Experiment, and soon-to-be-released ASMR-E passive microwave products. The AMSR-E and MODIS sensors are part of NASA's Earth Observing System flying on the Terra and Aqua satellites Characteristics of these NSIDC-held data sets, appropriateness of products for specific applications, and data set access and availability will be presented.

Snow Physics and Meltwater Hydrology of the SSiB Model Employed for Climate Simulation Studies with GEOS 2 GCM

NASA Technical Reports Server (NTRS)

Mocko, David M.; Sud, Y. C.; Einaudi, Franco (Technical Monitor)

2000-01-01

Present-day climate models produce large climate drifts that interfere with the climate signals simulated in modelling studies. The simplifying assumptions of the physical parameterization of snow and ice processes lead to large biases in the annual cycles of surface temperature, evapotranspiration, and the water budget, which in turn causes erroneous land-atmosphere interactions. Since land processes are vital for climate prediction, and snow and snowmelt processes have been shown to affect Indian monsoons and North American rainfall and hydrology, special attention is now being given to cold land processes and their influence on the simulated annual cycle in GCMs. The snow model of the SSiB land-surface model being used at Goddard has evolved from a unified single snow-soil layer interacting with a deep soil layer through a force-restore procedure to a two-layer snow model atop a ground layer separated by a snow-ground interface. When the snow cover is deep, force-restore occurs within the snow layers. However, several other simplifying assumptions such as homogeneous snow cover, an empirical depth related surface albedo, snowmelt and melt-freeze in the diurnal cycles, and neglect of latent heat of soil freezing and thawing still remain as nagging problems. Several important influences of these assumptions will be discussed with the goal of improving them to better simulate the snowmelt and meltwater hydrology. Nevertheless, the current snow model (Mocko and Sud, 2000, submitted) better simulates cold land processes as compared to the original SSiB. This was confirmed against observations of soil moisture, runoff, and snow cover in global GSWP (Sud and Mocko, 1999) and point-scale Valdai simulations over seasonal snow regions. New results from the current snow model SSiB from the 10-year PILPS 2e intercomparison in northern Scandinavia will be presented.

Advances in land modeling of KIAPS based on the Noah Land Surface Model

NASA Astrophysics Data System (ADS)

Koo, Myung-Seo; Baek, Sunghye; Seol, Kyung-Hee; Cho, Kyoungmi

2017-08-01

As of 2013, the Noah Land Surface Model (LSM) version 2.7.1 was implemented in a new global model being developed at the Korea Institute of Atmospheric Prediction Systems (KIAPS). This land surface scheme is further refined in two aspects, by adding new physical processes and by updating surface input parameters. Thus, the treatment of glacier land, sea ice, and snow cover are addressed more realistically. Inconsistencies in the amount of absorbed solar flux at ground level by the land surface and radiative processes are rectified. In addition, new parameters are available by using 1-km land cover data, which had usually not been possible at a global scale. Land surface albedo/emissivity climatology is newly created using Moderate-Resolution Imaging Spectroradiometer (MODIS) satellitebased data and adjusted parameterization. These updates have been applied to the KIAPS-developed model and generally provide a positive impact on near-surface weather forecasting.

Land-atmosphere-aerosol coupling in North China during 2000­-2013

NASA Astrophysics Data System (ADS)

Wei, J.; Jin, Q.; Yang, Z. L.; Zhou, L.

2017-12-01

North China is one of the most densely populated regions in the world. To its west, north, and northwest, the world's largest afforestation project has been going on for decades. At the same time, North China has been suffering from air pollution because of its large fossil fuel consumption. Here we show that the changes in land cover and aerosol concentration are coupled with the variations of land surface temperature, cloud cover, and surface solar radiation during the summer 2000-2013. Model experiments show that the interannual variation of aerosol concentration in North China is mainly a result of the varying atmospheric circulation. The increasing vegetation cover due to afforestation has enhanced surface evapotranspiration (ET) and cooled the local surface, and precipitation is observed to be increasing with ET. The model with prescribed increasing vegetation cover can simulate the increasing ET but cannot reproduce the increasing precipitation. Although this may be caused by model biases, the lack of aerosol processes in the model could also be a potential cause.

Numerical modelling of methane oxidation efficiency and coupled water-gas-heat reactive transfer in a sloping landfill cover.

PubMed

Feng, S; Ng, C W W; Leung, A K; Liu, H W

2017-10-01

Microbial aerobic methane oxidation in unsaturated landfill cover involves coupled water, gas and heat reactive transfer. The coupled process is complex and its influence on methane oxidation efficiency is not clear, especially in steep covers where spatial variations of water, gas and heat are significant. In this study, two-dimensional finite element numerical simulations were carried out to evaluate the performance of unsaturated sloping cover. The numerical model was calibrated using a set of flume model test data, and was then subsequently used for parametric study. A new method that considers transient changes of methane concentration during the estimation of the methane oxidation efficiency was proposed and compared against existing methods. It was found that a steeper cover had a lower oxidation efficiency due to enhanced downslope water flow, during which desaturation of soil promoted gas transport and hence landfill gas emission. This effect was magnified as the cover angle and landfill gas generation rate at the bottom of the cover increased. Assuming the steady-state methane concentration in a cover would result in a non-conservative overestimation of oxidation efficiency, especially when a steep cover was subjected to rainfall infiltration. By considering the transient methane concentration, the newly-modified method can give a more accurate oxidation efficiency. Copyright © 2017. Published by Elsevier Ltd.

Evaluation of DGVMs in tropical areas: linking patterns of vegetation cover, climate and fire to ecological processes

NASA Astrophysics Data System (ADS)

D'Onofrio, Donatella; von Hardenberg, Jost; Baudena, Mara

2017-04-01

Many current Dynamic Global Vegetation Models (DGVMs), including those incorporated into Earth System Models (ESMs), are able to realistically reproduce the distribution of the most worldwide biomes. However, they display high uncertainty in predicting the forest, savanna and grassland distributions and the transitions between them in tropical areas. These biomes are the most productive terrestrial ecosystems, and owing to their different biogeophysical and biogeochemical characteristics, future changes in their distributions could have also impacts on climate states. In particular, expected increasing temperature and CO2, modified precipitation regimes, as well as increasing land-use intensity could have large impacts on global biogeochemical cycles and precipitation, affecting the land-climate interactions. The difficulty of the DGVMs in simulating tropical vegetation, especially savanna structure and occurrence, has been associated with the way they represent the ecological processes and feedbacks between biotic and abiotic conditions. The inclusion of appropriate ecological mechanisms under present climatic conditions is essential for obtaining reliable future projections of vegetation and climate states. In this work we analyse observed relationships of tree and grass cover with climate and fire, and the current ecological understanding of the mechanisms driving the forest-savanna-grassland transition in Africa to evaluate the outcomes of a current state-of-the-art DGVM and to assess which ecological processes need to be included or improved within the model. Specifically, we analyse patterns of woody and herbaceous cover and fire return times from MODIS satellite observations, rainfall annual average and seasonality from TRMM satellite measurements and tree phenology information from the ESA global land cover map, comparing them with the outcomes of the LPJ-GUESS DGVM, also used by the EC-Earth global climate model. The comparison analysis with the LPJ-GUESS simulations suggests possible improvements in the model representations of tree-grass competition for water and in the vegetation-fire interaction. The proposed method could be useful for evaluating DGVMs in tropical areas, especially in the phase of model setting-up, before the coupling with Earth System Models. This could help in improving the simulations of ecological processes and consequently of land-climate interactions.

A QUANTITATIVE ASSESSMENT OF A COMBINED SPECTRAL AND GIS RULE-BASED LAND-COVER CLASSIFICATION IN THE NEUSE RIVER BASIN OF NORTH CAROLINA

EPA Science Inventory

The 14,582 km2 Neuse River Basin in North Carolina was characterized based on a user defined land-cover (LC) classification system developed specifically to support spatially explicit, non-point source nitrogen allocation modeling studies. Data processing incorporated both spect...

The Impacts of Urbanization on Meteorology and Air Quality in the Los Angeles Basin

NASA Astrophysics Data System (ADS)

Li, Y.; Zhang, J.; Sailor, D.; Ban-Weiss, G. A.

2017-12-01

Urbanization has a profound influence on regional meteorology in mega cities like Los Angeles. This influence is driven by changes in land surface physical properties and urban processes, and their corresponding influence on surface-atmosphere coupling. Changes in meteorology from urbanization in turn influences air quality through weather-dependent chemical reaction, pollutant dispersion, etc. Hence, a real-world representation of the urban land surface properties and urban processes should be accurately resolved in regional climate-chemistry models for better understanding the role of urbanization on changing urban meteorology and associated pollutant dynamics. By incorporating high-resolution land surface data, previous research has improved model-observation comparisons of meteorology in urban areas including the Los Angeles basin, and indicated that historical urbanization has increased urban temperatures and altered wind flows significantly. However, the impact of urban expansion on air quality has been less studied. Thus, in this study, we aim to evaluate the effectiveness of resolving high-resolution heterogeneity in urban land surface properties and processes for regional weather and pollutant concentration predictions. We coupled the Weather Research and Forecasting model with Chemistry to the single-layer Urban Canopy Model to simulate a typical summer period in year 2012 for Southern California. Land cover type and urban fraction were determined from National Land Cover Data. MODIS observations were used to determine satellite-derived albedo, green vegetation fraction, and leaf area index. Urban morphology was determined from GIS datasets of 3D building geometries. An urban irrigation scheme was also implemented in the model. Our results show that the improved model captures the diurnal cycle of 2m air temperature (T2) and Ozone (O3) concentrations. However, it tends to overestimate wind speed and underestimate T2, which leads to an underestimation of O3 and fine particulate matter concentrations. By comparing simulations assuming current land cover of the Los Angeles basin versus pre-urbanization land cover, we find that land cover change through urbanization has led to important shifts in regional air pollution via the aforementioned physical and chemical mechanisms.

SWANN: The Snow Water Artificial Neural Network Modelling System

NASA Astrophysics Data System (ADS)

Broxton, P. D.; van Leeuwen, W.; Biederman, J. A.

2017-12-01

Snowmelt from mountain forests is important for water supply and ecosystem health. Along Arizona's Mogollon Rim, snowmelt contributes to rivers and streams that provide a significant water supply for hydro-electric power generation, agriculture, and human consumption in central Arizona. In this project, we are building a snow monitoring system for the Salt River Project (SRP), which supplies water and power to millions of customers in the Phoenix metropolitan area. We are using process-based hydrological models and artificial neural networks (ANNs) to generate information about both snow water equivalent (SWE) and snow cover. The snow-cover data is generated with ANNs that are applied to Landsat and MODIS satellite reflectance data. The SWE data is generated using a combination of gridded SWE estimates generated by process-based snow models and ANNs that account for variations in topography, forest cover, and solar radiation. The models are trained and evaluated with snow data from SNOTEL stations as well as from aerial LiDAR and field data that we collected this past winter in northern Arizona, as well as with similar data from other sites in the Southwest US. These snow data are produced in near-real time, and we have built a prototype decision support tool to deliver them to SRP. This tool is designed to provide daily-to annual operational monitoring of spatial and temporal changes in SWE and snow cover conditions over the entire Salt River Watershed (covering 17,000 km2), and features advanced web mapping capabilities and watershed analytics displayed as graphical data.

Impacts of Changing Climatic Drivers and Land use features on Future Stormwater Runoff in the Northwest Florida Basin: A Large-Scale Hydrologic Modeling Assessment

NASA Astrophysics Data System (ADS)

Khan, M.; Abdul-Aziz, O. I.

2017-12-01

Potential changes in climatic drivers and land cover features can significantly influence the stormwater budget in the Northwest Florida Basin. We investigated the hydro-climatic and land use sensitivities of stormwater runoff by developing a large-scale process-based rainfall-runoff model for the large basin by using the EPA Storm Water Management Model (SWMM 5.1). Climatic and hydrologic variables, as well as land use/cover features were incorporated into the model to account for the key processes of coastal hydrology and its dynamic interactions with groundwater and sea levels. We calibrated and validated the model by historical daily streamflow observations during 2009-2012 at four major rivers in the basin. Downscaled climatic drivers (precipitation, temperature, solar radiation) projected by twenty GCMs-RCMs under CMIP5, along with the projected future land use/cover features were also incorporated into the model. The basin storm runoff was then simulated for the historical (2000s = 1976-2005) and two future periods (2050s = 2030-2059, and 2080s = 2070-2099). Comparative evaluation of the historical and future scenarios leads to important guidelines for stormwater management in Northwest Florida and similar regions under a changing climate and environment.

Modeling and Analysis of Process Parameters for Evaluating Shrinkage Problems During Plastic Injection Molding of a DVD-ROM Cover

NASA Astrophysics Data System (ADS)

Öktem, H.

2012-01-01

Plastic injection molding plays a key role in the production of high-quality plastic parts. Shrinkage is one of the most significant problems of a plastic part in terms of quality in the plastic injection molding. This article focuses on the study of the modeling and analysis of the effects of process parameters on the shrinkage by evaluating the quality of the plastic part of a DVD-ROM cover made with Acrylonitrile Butadiene Styrene (ABS) polymer material. An effective regression model was developed to determine the mathematical relationship between the process parameters (mold temperature, melt temperature, injection pressure, injection time, and cooling time) and the volumetric shrinkage by utilizing the analysis data. Finite element (FE) analyses designed by Taguchi (L27) orthogonal arrays were run in the Moldflow simulation program. Analysis of variance (ANOVA) was then performed to check the adequacy of the regression model and to determine the effect of the process parameters on the shrinkage. Experiments were conducted to control the accuracy of the regression model with the FE analyses obtained from Moldflow. The results show that the regression model agrees very well with the FE analyses and the experiments. From this, it can be concluded that this study succeeded in modeling the shrinkage problem in our application.

Quantitative microbiological risk assessment in food industry: Theory and practical application.

PubMed

Membré, Jeanne-Marie; Boué, Géraldine

2018-04-01

The objective of this article is to bring scientific background as well as practical hints and tips to guide risk assessors and modelers who want to develop a quantitative Microbiological Risk Assessment (MRA) in an industrial context. MRA aims at determining the public health risk associated with biological hazards in a food. Its implementation in industry enables to compare the efficiency of different risk reduction measures, and more precisely different operational settings, by predicting their effect on the final model output. The first stage in MRA is to clearly define the purpose and scope with stakeholders, risk assessors and modelers. Then, a probabilistic model is developed; this includes schematically three important phases. Firstly, the model structure has to be defined, i.e. the connections between different operational processing steps. An important step in food industry is the thermal processing leading to microbial inactivation. Growth of heat-treated surviving microorganisms and/or post-process contamination during storage phase is also important to take into account. Secondly, mathematical equations are determined to estimate the change of microbial load after each processing step. This phase includes the construction of model inputs by collecting data or eliciting experts. Finally, the model outputs are obtained by simulation procedures, they have to be interpreted and communicated to targeted stakeholders. In this latter phase, tools such as what-if scenarios provide an essential added value. These different MRA phases are illustrated through two examples covering important issues in industry. The first one covers process optimization in a food safety context, the second one covers shelf-life determination in a food quality context. Although both contexts required the same methodology, they do not have the same endpoint: up to the human health in the foie gras case-study illustrating here a safety application, up to the food portion in the brioche case-study illustrating here a quality application. Copyright © 2017 Elsevier Ltd. All rights reserved.

Chemsheet as a Simulation Platform for Pyrometallurgical Processes

NASA Astrophysics Data System (ADS)

Penttilä, Karri; Salminen, Justin; Tripathi, Nagendra; Koukkari, Pertti

ChemSheet is a thermodynamic multi-phase multi-component simulation software, which is used as an Add-in in Microsoft Excel. In ChemSheet, the unique Constrained Gibbs free energy method can be used to include dynamic constraints and reaction rates of kinetically slow reactions, yet retaining full consistency of the multiphase thermodynamic model. With appropriate data, ChemSheet models can be used to simulate reactors and processes in all fields of thermochemistry. The presentation will cover off-line modeling of Cu-flash smelters and advanced thermochemical simulation coupled with on-line process control of Cu-Ni smelting. The presentation will describe an off-line model of Cu-smelter based on critically assessed properties of the Al-Ca-Cu-Fe-O-S-Si -system (slag, matte and liquid metal) by using the quasichemical model. A four-stage reactor model (shaft, settler, uptake and bath) is used for optimizing process parameters and feed particle distribution. As a second example, an advanced thermochemical model of a Ni-Cu sulphide smelting plant will be given. The on-line model covers the operation of treating Ni-Cu-S concentrate via roasters, electric furnace and converters, producing a high grade Bessemer matte product for further refining. The model integrates the thermochemistry of the roasters and electric furnace, and predicts important process parameters such as degree of sulphur elimination in the fluid-bed roasters, matte grade, iron metallization, slag losses and the iron to silica ratio in the electric furnace slag. Both models can be used to assist process engineers and operators in calculating the addition rates of coke, flux and air for different feed scenarios.

INTERCOMPARISON OF ALTERNATIVE VEGETATION DATABASES FOR REGIONAL AIR QUALITY MODELING

EPA Science Inventory

Vegetation cover data are used to characterize several regional air quality modeling processes, including the calculation of heat, moisture, and momentum fluxes with the Mesoscale Meteorological Model (MM5) and the estimate of biogenic volatile organic compound and nitric oxide...

Monitoring Areal Snow Cover Using NASA Satellite Imagery

NASA Technical Reports Server (NTRS)

Harshburger, Brian J.; Blandford, Troy; Moore, Brandon

2011-01-01

The objective of this project is to develop products and tools to assist in the hydrologic modeling process, including tools to help prepare inputs for hydrologic models and improved methods for the visualization of streamflow forecasts. In addition, this project will facilitate the use of NASA satellite imagery (primarily snow cover imagery) by other federal and state agencies with operational streamflow forecasting responsibilities. A GIS software toolkit for monitoring areal snow cover extent and producing streamflow forecasts is being developed. This toolkit will be packaged as multiple extensions for ArcGIS 9.x and an opensource GIS software package. The toolkit will provide users with a means for ingesting NASA EOS satellite imagery (snow cover analysis), preparing hydrologic model inputs, and visualizing streamflow forecasts. Primary products include a software tool for predicting the presence of snow under clouds in satellite images; a software tool for producing gridded temperature and precipitation forecasts; and a suite of tools for visualizing hydrologic model forecasting results. The toolkit will be an expert system designed for operational users that need to generate accurate streamflow forecasts in a timely manner. The Remote Sensing of Snow Cover Toolbar will ingest snow cover imagery from multiple sources, including the MODIS Operational Snowcover Data and convert them to gridded datasets that can be readily used. Statistical techniques will then be applied to the gridded snow cover data to predict the presence of snow under cloud cover. The toolbar has the ability to ingest both binary and fractional snow cover data. Binary mapping techniques use a set of thresholds to determine whether a pixel contains snow or no snow. Fractional mapping techniques provide information regarding the percentage of each pixel that is covered with snow. After the imagery has been ingested, physiographic data is attached to each cell in the snow cover image. This data can be obtained from a digital elevation model (DEM) for the area of interest.

Enterprise Pattern: integrating the business process into a unified enterprise model of modern service company

NASA Astrophysics Data System (ADS)

Li, Ying; Luo, Zhiling; Yin, Jianwei; Xu, Lida; Yin, Yuyu; Wu, Zhaohui

2017-01-01

Modern service company (MSC), the enterprise involving special domains, such as the financial industry, information service industry and technology development industry, depends heavily on information technology. Modelling of such enterprise has attracted much research attention because it promises to help enterprise managers to analyse basic business strategies (e.g. the pricing strategy) and even optimise the business process (BP) to gain benefits. While the existing models proposed by economists cover the economic elements, they fail to address the basic BP and its relationship with the economic characteristics. Those proposed in computer science regardless of achieving great success in BP modelling perform poorly in supporting the economic analysis. Therefore, the existing approaches fail to satisfy the requirement of enterprise modelling for MSC, which demands simultaneous consideration of both economic analysing and business processing. In this article, we provide a unified enterprise modelling approach named Enterprise Pattern (EP) which bridges the gap between the BP model and the enterprise economic model of MSC. Proposing a language named Enterprise Pattern Description Language (EPDL) covering all the basic language elements of EP, we formulate the language syntaxes and two basic extraction rules assisting economic analysis. Furthermore, we extend Business Process Model and Notation (BPMN) to support EPDL, named BPMN for Enterprise Pattern (BPMN4EP). The example of mobile application platform is studied in detail for a better understanding of EPDL.

Continuous Change Detection and Classification (CCDC) of Land Cover Using All Available Landsat Data

NASA Astrophysics Data System (ADS)

Zhu, Z.; Woodcock, C. E.

2012-12-01

A new algorithm for Continuous Change Detection and Classification (CCDC) of land cover using all available Landsat data is developed. This new algorithm is capable of detecting many kinds of land cover change as new images are collected and at the same time provide land cover maps for any given time. To better identify land cover change, a two step cloud, cloud shadow, and snow masking algorithm is used for eliminating "noisy" observations. Next, a time series model that has components of seasonality, trend, and break estimates the surface reflectance and temperature. The time series model is updated continuously with newly acquired observations. Due to the high variability in spectral response for different kinds of land cover change, the CCDC algorithm uses a data-driven threshold derived from all seven Landsat bands. When the difference between observed and predicted exceeds the thresholds three consecutive times, a pixel is identified as land cover change. Land cover classification is done after change detection. Coefficients from the time series models and the Root Mean Square Error (RMSE) from model fitting are used as classification inputs for the Random Forest Classifier (RFC). We applied this new algorithm for one Landsat scene (Path 12 Row 31) that includes all of Rhode Island as well as much of Eastern Massachusetts and parts of Connecticut. A total of 532 Landsat images acquired between 1982 and 2011 were processed. During this period, 619,924 pixels were detected to change once (91% of total changed pixels) and 60,199 pixels were detected to change twice (8% of total changed pixels). The most frequent land cover change category is from mixed forest to low density residential which occupies more than 8% of total land cover change pixels.

Spring floods prediction with the use of optical satellite data in Québec

NASA Astrophysics Data System (ADS)

Roy, A.; Royer, A.; Turcotte, R.

2009-04-01

The Centre d'expertise hydrique du Québec (CEHQ) operates a distributed hydrological model, which integrates a snow model, for the management of dams in the south of Québec. It appears that the estimation of the water quantity of snowmelt in spring remains a variable with a large uncertainty and induces generally to an important error in stream flow simulation. Therefore, the National snow and ice center (NSIDC) produces, from MODIS (Moderate Resolution Imaging Spectroradiometer) data, continuous and homogeneous spatial snow cover (snow/swow-free) data on the whole territory, but with a cloud contamination. This research aims to improve the prediction of spring floods and the estimation of the rate of discharge by integrating snow cover data in the CEHQ's snow model. The study is done on two watersheds: du Nord river watershed (45,8°N) and Aux Écorces river watershed (47,9°N). The snow model used in the study (SPH-AV) is an implementation developed by the CEHQ of the snowmelt model of HYDROLTEL in is hydrological forecast system to simulate the melted water. The melted water estimated is then used as input in the empirical hydrological model MOHYSE to simulate stream flow. MODIS data are considered valid only when the cloud cover on each pixel of the watersheds is less then 30%. A pixel by pixel correction is applied to the snow pack when there is a difference between satellite snow cover and modeled snow cover. In the case of model shows to much snow, a factor is applied on temperatures by iterative process (starting from the last valid MODIS data) to melt the snow. In the opposite case, the snow quantity added to the last valid MODIS data is found by iterative process so that the pixel's snow water equivalent is equal to the nonzero neighbor minimum value. The study shows, through the simulations done on the two watersheds, the interest of the use of snow/snow-free product for the operational update of snow water equivalent with the objective to improve spring snowmelt stream flow simulations. The binary aspect (snow/snowfree) of the data is however a limit. Alternatives are discussed (passive microwave data). Keywords : satellite snow cover data, MODIS, satellite data integration, snow model, hydrological model, stream flow simulation, flood.

Challenges in Educational Modelling: Expressiveness of IMS Learning Design

ERIC Educational Resources Information Center

Caeiro-Rodriguez, Manuel; Anido-Rifon, Luis; Llamas-Nistal, Martin

2010-01-01

Educational Modelling Languages (EMLs) have been proposed to enable the authoring of models of "learning units" (e.g., courses, lessons, lab practices, seminars) covering the broad variety of pedagogical approaches. In addition, some EMLs have been proposed as computational languages that support the processing of learning unit models by…

A service relation model for web-based land cover change detection

NASA Astrophysics Data System (ADS)

Xing, Huaqiao; Chen, Jun; Wu, Hao; Zhang, Jun; Li, Songnian; Liu, Boyu

2017-10-01

Change detection with remotely sensed imagery is a critical step in land cover monitoring and updating. Although a variety of algorithms or models have been developed, none of them can be universal for all cases. The selection of appropriate algorithms and construction of processing workflows depend largely on the expertise of experts about the "algorithm-data" relations among change detection algorithms and the imagery data used. This paper presents a service relation model for land cover change detection by integrating the experts' knowledge about the "algorithm-data" relations into the web-based geo-processing. The "algorithm-data" relations are mapped into a set of web service relations with the analysis of functional and non-functional service semantics. These service relations are further classified into three different levels, i.e., interface, behavior and execution levels. A service relation model is then established using the Object and Relation Diagram (ORD) approach to represent the multi-granularity services and their relations for change detection. A set of semantic matching rules are built and used for deriving on-demand change detection service chains from the service relation model. A web-based prototype system is developed in .NET development environment, which encapsulates nine change detection and pre-processing algorithms and represents their service relations as an ORD. Three test areas from Shandong and Hebei provinces, China with different imagery conditions are selected for online change detection experiments, and the results indicate that on-demand service chains can be generated according to different users' demands.

Mapping Land Use/Land Cover in the Ambos Nogales Study Area

USGS Publications Warehouse

Norman, Laura M.; Wallace, Cynthia S.A.

2008-01-01

The Ambos Nogales watershed, which surrounds the twin cities of Nogales, Arizona, United States and Nogales, Sonora, Mexico, has a history of problems related to flooding. This paper describes the process of creating a high-resolution, binational land-cover dataset to be used in modeling the Ambos Nogales watershed. The Automated Geospatial Watershed Assessment tool will be used to model the Ambos Nogales watershed to identify focal points for planning efforts and to anticipate ramifications of implementing detention reservoirs at certain watershed planes.

Cloud cover estimation: Use of GOES imagery in development of cloud cover data base for insolation assessment

NASA Technical Reports Server (NTRS)

Huning, J. R.; Logan, T. L.; Smith, J. H.

1982-01-01

The potential of using digital satellite data to establish a cloud cover data base for the United States, one that would provide detailed information on the temporal and spatial variability of cloud development are studied. Key elements include: (1) interfacing GOES data from the University of Wisconsin Meteorological Data Facility with the Jet Propulsion Laboratory's VICAR image processing system and IBIS geographic information system; (2) creation of a registered multitemporal GOES data base; (3) development of a simple normalization model to compensate for sun angle; (4) creation of a variable size georeference grid that provides detailed cloud information in selected areas and summarized information in other areas; and (5) development of a cloud/shadow model which details the percentage of each grid cell that is cloud and shadow covered, and the percentage of cloud or shadow opacity. In addition, comparison of model calculations of insolation with measured values at selected test sites was accomplished, as well as development of preliminary requirements for a large scale data base of cloud cover statistics.

USING CLASSIFICATION CONSISTENCY IN INTER-SCENE OVERLAP AREAS TO MODEL SPATIAL VARIATIONS IN LAND-COVER ACCURACY OVER LARGE GEOGRAPHIC REGIONS

EPA Science Inventory

During the last decade, a number of initiatives have been undertaken to create systematic national and global data sets of processed satellite imagery. An important application of these data is the derivation of large area (i.e. multi-scene) land cover products. Such products, ho...

Modeling erosion on steep sagebrush rangeland before and after prescribed fire

Treesearch

Corey A. Moffet; Frederick B. Pierson; Kenneth E. Spaeth

2007-01-01

Fire in sagebrush rangelands significantly alters canopy cover, ground cover, and soil properties that influence runoff and erosion processes. Runoff is generated more quickly and a larger volume of runoff is produced following prescribed fire. The result is increased risk of severe erosion and downstream flooding. The Water Erosion Prediction Project (WEPP), developed...

Monitoring tropical vegetation succession with LANDSAT data

NASA Technical Reports Server (NTRS)

Robinson, V. B. (Principal Investigator)

1983-01-01

The shadowing problem, which is endemic to the use of LANDSAT in tropical areas, and the ability to model changes over space and through time are problems to be addressed when monitoring tropical vegetation succession. Application of a trend surface analysis model to major land cover classes in a mountainous region of the Phillipines shows that the spatial modeling of radiance values can provide a useful approach to tropical rain forest succession monitoring. Results indicate shadowing effects may be due primarily to local variations in the spectral responses. These variations can be compensated for through the decomposition of the spatial variation in both elevation and MSS data. Using the model to estimate both elevation and spectral terrain surface as a posteriori inputs in the classification process leads to improved classification accuracy for vegetation of cover of this type. Spatial patterns depicted by the MSS data reflect the measurement of responses to spatial processes acting at several scales.

Deposition Of Thin-Film Sensors On Glass-Fiber/Epoxy Models

NASA Technical Reports Server (NTRS)

Tran, Sang Q.

1995-01-01

Direct-deposition process devised for fabrication of thin-film sensors on three-dimensional, curved surfaces of models made of stainless steel covered with glass-fiber/epoxy-matrix composite material. Models used under cryogenic conditions, and sensors used to detect on-line transitions between laminar and turbulent flows in wind tunnel environments. Sensors fabricated by process used at temperatures from minus 300 degrees F to 175 degrees F.

Rapid response tools and datasets for post-fire modeling: Linking Earth Observations and process-based hydrological models to support post-fire remediation

Treesearch

M. E. Miller; M. Billmire; W. J. Elliot; K. A. Endsley; P. R. Robichaud

2015-01-01

Preparation is key to utilizing Earth Observations and process-based models to support post-wildfire mitigation. Post-fire flooding and erosion can pose a serious threat to life, property and municipal water supplies. Increased runoff and sediment delivery due to the loss of surface cover and fire-induced changes in soil properties are of great concern. Remediation...

Framework for cascade size calculations on random networks

NASA Astrophysics Data System (ADS)

Burkholz, Rebekka; Schweitzer, Frank

2018-04-01

We present a framework to calculate the cascade size evolution for a large class of cascade models on random network ensembles in the limit of infinite network size. Our method is exact and applies to network ensembles with almost arbitrary degree distribution, degree-degree correlations, and, in case of threshold models, for arbitrary threshold distribution. With our approach, we shift the perspective from the known branching process approximations to the iterative update of suitable probability distributions. Such distributions are key to capture cascade dynamics that involve possibly continuous quantities and that depend on the cascade history, e.g., if load is accumulated over time. As a proof of concept, we provide two examples: (a) Constant load models that cover many of the analytically tractable casacade models, and, as a highlight, (b) a fiber bundle model that was not tractable by branching process approximations before. Our derivations cover the whole cascade dynamics, not only their steady state. This allows us to include interventions in time or further model complexity in the analysis.

Emissions model of waste treatment operations at the Idaho Chemical Processing Plant

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schindler, R.E.

1995-03-01

An integrated model of the waste treatment systems at the Idaho Chemical Processing Plant (ICPP) was developed using a commercially-available process simulation software (ASPEN Plus) to calculate atmospheric emissions of hazardous chemicals for use in an application for an environmental permit to operate (PTO). The processes covered by the model are the Process Equipment Waste evaporator, High Level Liquid Waste evaporator, New Waste Calcining Facility and Liquid Effluent Treatment and Disposal facility. The processes are described along with the model and its assumptions. The model calculates emissions of NO{sub x}, CO, volatile acids, hazardous metals, and organic chemicals. Some calculatedmore » relative emissions are summarized and insights on building simulations are discussed.« less

Functional correlation approach to operational risk in banking organizations

NASA Astrophysics Data System (ADS)

Kühn, Reimer; Neu, Peter

2003-05-01

A Value-at-Risk-based model is proposed to compute the adequate equity capital necessary to cover potential losses due to operational risks, such as human and system process failures, in banking organizations. Exploring the analogy to a lattice gas model from physics, correlations between sequential failures are modeled by as functionally defined, heterogeneous couplings between mutually supportive processes. In contrast to traditional risk models for market and credit risk, where correlations are described as equal-time-correlations by a covariance matrix, the dynamics of the model shows collective phenomena such as bursts and avalanches of process failures.

Evaluation of post fire changes in soil properties and influence on the hydrological and erosive dynamics in a Mediterranean watershed

NASA Astrophysics Data System (ADS)

Sanz, Inés; Aguilar, Cristina; Millares, Agustín

2013-04-01

In the last fifty years, forest fires and changes in land use and management practices have had a significant influenceon the evolution of soil loss processes in the Mediterranean area. Forest fires have immediate effects in hydrological processes mainly due to sudden changes in soil properties and vegetation cover. After a fire there is an increase in runoff processes and peak flows and thus in the amount and composition of the sediments produced. Silting in dams downstream is often reported so the description of the post-fire hydrological processes is crucial in order to optimize decision making. This study analyzes a micro-watershed of 25 ha in the south of Spain that suffered a fire in October 2010 burning around a 2 km2 area. As the erosive processes in this area are directly related to concentrated overland flow, an indirect assessment of soil loss is presented in this work based on evaluating changes in runoff in Mediterranean post-fire situations. For this, the study is divided into two main parts. Firstly, changes in soil properties and vegetation cover are evaluated. Secondly, the effects of these changes in the hydrological and erosive dynamics are assessed.The watershed had been monitored in previous studies so soil properties and the vegetation cover before the fire took place were already characterized. Besides, the hydrological response was also available through an already calibrated and validated physically-based distributed hydrological model. For the evaluation of soil properties, field measurement campaigns were designed. Philip Dunne's tests for the determination of saturated hydraulic conductivity, as well as moisture content and bulk density measurements were carried out in both unaltered and burned soil samples. Changes in the vegetation cover fraction were assessed through desktop analysis of Landsat-TM5 platform satellite images as well as through visual inspection in the field campaigns. The analysis of the hydraulic conductivity revealed a reduction in post-fire values of near 90 % over those previous to the fire. Regarding the vegetation cover, the recovery of the burned covers, mainly herbaceous with some bushes, turned out to quick due to the wet character of the year. Nevertheless, an apparent decrease in the cover fraction and thus in the vegetation storage capacity was reported. These changes were incorporated into a new hydrological model configuration and compared to the response previous to the fire. The results point out the rainfall pattern to be a determinant factor in post-fire situation with an increase in modeled runoff of up to 350% and even more in dry years. These results have direct implications in soil erodibility changes in hillslopes as well as a considerable increase in bedload processes in Mediterranean alluvial rivers.

Fragmentation and melting of the seasonal sea ice cover

NASA Astrophysics Data System (ADS)

Feltham, D. L.; Bateson, A.; Schroeder, D.; Ridley, J. K.; Aksenov, Y.

2017-12-01

Recent years have seen a rapid reduction in the summer extent of Arctic sea ice. This trend has implications for navigation, oil exploration, wildlife, and local communities. Furthermore the Arctic sea ice cover impacts the exchange of heat and momentum between the ocean and atmosphere with significant teleconnections across the climate system, particularly mid to low latitudes in the Northern Hemisphere. The treatment of melting and break-up processes of the seasonal sea ice cover within climate models is currently limited. In particular floes are assumed to have a uniform size which does not evolve with time. Observations suggest however that floe sizes can be modelled as truncated power law distributions, with different exponents for smaller and larger floes. This study aims to examine factors controlling the floe size distribution in the seasonal and marginal ice zone. This includes lateral melting, wave induced break-up of floes, and the feedback between floe size and the mixed ocean layer. These results are then used to quantify the proximate mechanisms of seasonal sea ice reduction in a sea ice—ocean mixed layer model. Observations are used to assess and calibrate the model. The impacts of introducing these processes to the model will be discussed and the preliminary results of sensitivity and feedback studies will also be presented.

Very High Resolution Tree Cover Mapping for Continental United States using Deep Convolutional Neural Networks

NASA Technical Reports Server (NTRS)

Ganguly, Sangram; Kalia, Subodh; Li, Shuang; Michaelis, Andrew; Nemani, Ramakrishna R.; Saatchi, Sassan A

2017-01-01

Uncertainties in input land cover estimates contribute to a significant bias in modeled above ground biomass (AGB) and carbon estimates from satellite-derived data. The resolution of most currently used passive remote sensing products is not sufficient to capture tree canopy cover of less than ca. 10-20 percent, limiting their utility to estimate canopy cover and AGB for trees outside of forest land. In our study, we created a first of its kind Continental United States (CONUS) tree cover map at a spatial resolution of 1-m for the 2010-2012 epoch using the USDA NAIP imagery to address the present uncertainties in AGB estimates. The process involves different tasks including data acquisition ingestion to pre-processing and running a state-of-art encoder-decoder based deep convolutional neural network (CNN) algorithm for automatically generating a tree non-tree map for almost a quarter million scenes. The entire processing chain including generation of the largest open source existing aerial satellite image training database was performed at the NEX supercomputing and storage facility. We believe the resulting forest cover product will substantially contribute to filling the gaps in ongoing carbon and ecological monitoring research and help quantifying the errors and uncertainties in derived products.

Very High Resolution Tree Cover Mapping for Continental United States using Deep Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Ganguly, S.; Kalia, S.; Li, S.; Michaelis, A.; Nemani, R. R.; Saatchi, S.

2017-12-01

Uncertainties in input land cover estimates contribute to a significant bias in modeled above gound biomass (AGB) and carbon estimates from satellite-derived data. The resolution of most currently used passive remote sensing products is not sufficient to capture tree canopy cover of less than ca. 10-20 percent, limiting their utility to estimate canopy cover and AGB for trees outside of forest land. In our study, we created a first of its kind Continental United States (CONUS) tree cover map at a spatial resolution of 1-m for the 2010-2012 epoch using the USDA NAIP imagery to address the present uncertainties in AGB estimates. The process involves different tasks including data acquisition/ingestion to pre-processing and running a state-of-art encoder-decoder based deep convolutional neural network (CNN) algorithm for automatically generating a tree/non-tree map for almost a quarter million scenes. The entire processing chain including generation of the largest open source existing aerial/satellite image training database was performed at the NEX supercomputing and storage facility. We believe the resulting forest cover product will substantially contribute to filling the gaps in ongoing carbon and ecological monitoring research and help quantifying the errors and uncertainties in derived products.

Do invasive corals alter coral reef processes? An empirical approach evaluating reef fish trophic interactions.

PubMed

Miranda, Ricardo J; Nunes, José de Anchieta C C; Mariano-Neto, Eduardo; Sippo, James Z; Barros, Francisco

2018-07-01

Understanding how invasive species affect key ecological interactions and ecosystem processes is imperative for the management of invasions. We evaluated the effects of invasive corals (Tubastraea spp.) on fish trophic interactions in an Atlantic coral reef. Remote underwater video cameras were used to examine fish foraging activity (bite rates and food preferences) on invasive cover levels. Using a model selection approach, we found that fish feeding rates declined with increased invasive cover. For Roving Herbivores (RH) and Sessile Invertivores (SI), an abrupt reduction of fish feeding rates corresponded with higher invasive cover, while feeding rates of Territorial Herbivores (TH) and Mobile Invertivores (MI) decreased linearly with cover increase. Additionally, some fish trophic groups, such as RH, SI and Omnivores (OM), had lower densities in reef sections with high invasive cover. These findings demonstrate that invasive corals negatively impact fish-benthic interactions, and could potentially alter existing trophic relationships in reef ecosystems. Copyright © 2018 Elsevier Ltd. All rights reserved.

Modeled historical land use and land cover for the conterminous United States

USGS Publications Warehouse

Sohl, Terry L.; Reker, Ryan R.; Bouchard, Michelle A.; Sayler, Kristi L.; Dornbierer, Jordan; Wika, Steve; Quenzer, Robert; Friesz, Aaron M.

2016-01-01

The landscape of the conterminous United States has changed dramatically over the last 200 years, with agricultural land use, urban expansion, forestry, and other anthropogenic activities altering land cover across vast swaths of the country. While land use and land cover (LULC) models have been developed to model potential future LULC change, few efforts have focused on recreating historical landscapes. Researchers at the US Geological Survey have used a wide range of historical data sources and a spatially explicit modeling framework to model spatially explicit historical LULC change in the conterminous United States from 1992 back to 1938. Annual LULC maps were produced at 250-m resolution, with 14 LULC classes. Assessment of model results showed good agreement with trends and spatial patterns in historical data sources such as the Census of Agriculture and historical housing density data, although comparison with historical data is complicated by definitional and methodological differences. The completion of this dataset allows researchers to assess historical LULC impacts on a range of ecological processes.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Seapan, M.; Crynes, B.L.; Dale, S.

The objectives of this study were to analyze alternate crudes kinetic hydrotreatment data in the literature, develop a mathematical model for interpretation of these data, develop an experimental procedure and apparatus to collect accurate kinetic data, and finally, to combine the model and experimental data to develop a general model which, with a few experimental parameters, could be used in design of future hydrotreatment processes. These objectives were to cover a four year program (1980 to 1984) and were subjective to sufficient funding. Only partial funding has been available thus far to cover activities for two years. A hydrotreatment datamore » base is developed which contains over 2000 citations, stored in a microcomputer. About 50% of these are reviewed, classified and can be identified by feedstock, catalyst, reactor type and other process characteristics. Tests of published hydrodesulfurization data indicate the problems with simple n-th order, global kinetic models, and point to the value of developing intrinsic reaction kinetic models to describe the reaction processes. A Langmuir-Hinshelwood kinetic model coupled with a plug flow reactor design equation has been developed and used for published data evaluation. An experimental system and procedure have been designed and constructed, which can be used for kinetic studies. 30 references, 4 tables.« less

The Impact of Detailed Snow Physics on the Simulation of Snow Cover and Subsurface Thermodynamics at Continental Scales

NASA Technical Reports Server (NTRS)

Stieglitz, Marc; Ducharne, Agnes; Koster, Randy; Suarez, Max; Busalacchi, Antonio J. (Technical Monitor)

2000-01-01

The three-layer snow model is coupled to the global catchment-based Land Surface Model (LSM) of the NASA Seasonal to Interannual Prediction Project (NSIPP) project, and the combined models are used to simulate the growth and ablation of snow cover over the North American continent for the period 1987-1988. The various snow processes included in the three-layer model, such as snow melting and re-freezing, dynamic changes in snow density, and snow insulating properties, are shown (through a comparison with the corresponding simulation using a much simpler snow model) to lead to an improved simulation of ground thermodynamics on the continental scale.

Application and Evaluation of an Explicit Prognostic Cloud-Cover Scheme in GRAPES Global Forecast System

NASA Astrophysics Data System (ADS)

Ma, Zhanshan; Liu, Qijun; Zhao, Chuanfeng; Shen, Xueshun; Wang, Yuan; Jiang, Jonathan H.; Li, Zhe; Yung, Yuk

2018-03-01

An explicit prognostic cloud-cover scheme (PROGCS) is implemented into the Global/Regional Assimilation and Prediction System (GRAPES) for global middle-range numerical weather predication system (GRAPES_GFS) to improve the model performance in simulating cloud cover and radiation. Unlike the previous diagnostic cloud-cover scheme (DIAGCS), PROGCS considers the formation and dissipation of cloud cover by physically connecting it to the cumulus convection and large-scale stratiform condensation processes. Our simulation results show that clouds in mid-high latitudes arise mainly from large-scale stratiform condensation processes, while cumulus convection and large-scale condensation processes jointly determine cloud cover in low latitudes. Compared with DIAGCS, PROGCS captures more consistent vertical distributions of cloud cover with the observations from Atmospheric Radiation Measurements (ARM) program at the Southern Great Plains (SGP) site and simulates more realistic diurnal cycle of marine stratocumulus with the ERA-Interim reanalysis data. The low, high, and total cloud covers that are determined via PROGCS appear to be more realistic than those simulated via DIAGCS when both are compared with satellite retrievals though the former maintains slight negative biases. In addition, the simulations of outgoing longwave radiation (OLR) at the top of the atmosphere (TOA) from PROGCS runs have been considerably improved as well, resulting in less biases in radiative heating rates at heights below 850 hPa and above 400 hPa of GRAPES_GFS. Our results indicate that a prognostic method of cloud-cover calculation has significant advantage over the conventional diagnostic one, and it should be adopted in both weather and climate simulation and forecast.

Comparing long-term geomorphic model outcomes with sediment archives highlights the need for high-resolution Holocene land cover reconstructions

NASA Astrophysics Data System (ADS)

De Brue, Hanne; Verstraeten, Gert

2013-04-01

During the last decade, several global land cover reconstructions have been produced that enable to quantify human impact on the landscape since the introduction of agriculture. Application of these land cover maps in geomorphic models potentially allows to estimate the anthropogenic impact on sediment fluxes and thus to reconstruct changes in landscape morphology through time. However, current land cover reconstructions face some drawbacks. First of all, their low spatial resolution (i.e. 5 arc-minutes at best) questions their use in geomorphic models, as sub-catchment vegetation patterns play an important role in sediment dynamics. Existing global land cover reconstructions also do not differentiate the typology of human impact (cropland, grazing land, disturbed forests), although the susceptibility of different anthropogenic land uses towards erosion varies greatly. Finally, the various land cover reconstructions differ significantly regarding the estimated intensity of human impact for the preindustrial period. In this study, we assessed the performance of a spatially distributed erosion and sediment redistribution model that operates at high resolution (100 m) to the quality and spatial resolution of input land cover maps. This was done through a comparison of two sets of model runs. Firstly, low-resolution land cover (expressed as percentage of non-natural vegetation) maps were resampled to a spatial resolution of 100 m without differentiation of non-natural vegetation types. For the second set of model runs, estimated non-natural vegetation was differentiated in areas of cropland and grassland, and spatially allocated to a high-resolution grid (100 m) using a logistic model that relates contemporary land cover classes to slope, soil characteristics, landforms and distance to rivers. For both land cover maps, different scenarios for the ratio between cropland and grassland were simulated. Analyses were performed for several time periods throughout the Holocene, for the Scheldt River Basin (19,000 km2) in Belgium and northern France. Results indicate that low-resolution land cover information, regardless of the considered cropland/grassland ratio, leads to largely overestimated sediment fluxes when compared to field-based sediment budgets. Allocation of land cover to a higher spatial resolution yields far better results. Variations in model outcomes are related to differences in landscape connectivity between allocated and non-allocated land cover. These results point towards the need for higher-resolution land cover maps that incorporate the patchiness of vegetation at relevant scales regarding geomorphic processes. Also, model results with allocated and non-allocated land cover maps differ greatly for different cropland/grassland ratios. This indicates that there is not only a need for land cover reconstructions at high spatial resolution, but also that differentiation between cropland and grassland is essential for accurate geomorphic modeling. Further improvements in land cover reconstructions are thus needed before reliable quantitative estimates of anthropogenic impact on soil profiles and sediment redistribution can be simulated at continental scales. Detailed historic sediment budgets can provide an important tool not only for validating but also for reconstructing land cover histories.

Introduction of Virtualization Technology to Multi-Process Model Checking

NASA Technical Reports Server (NTRS)

Leungwattanakit, Watcharin; Artho, Cyrille; Hagiya, Masami; Tanabe, Yoshinori; Yamamoto, Mitsuharu

2009-01-01

Model checkers find failures in software by exploring every possible execution schedule. Java PathFinder (JPF), a Java model checker, has been extended recently to cover networked applications by caching data transferred in a communication channel. A target process is executed by JPF, whereas its peer process runs on a regular virtual machine outside. However, non-deterministic target programs may produce different output data in each schedule, causing the cache to restart the peer process to handle the different set of data. Virtualization tools could help us restore previous states of peers, eliminating peer restart. This paper proposes the application of virtualization technology to networked model checking, concentrating on JPF.

Rainfall and sheet power model for interrill erosion in steep slope

NASA Astrophysics Data System (ADS)

Shin, Seung Sook; Deog Park, Sand; Nam, Myeong Jun

2015-04-01

The two-phase process of interrill erosion consist of the splash and detachment of individual particles from soil mass by impact of raindrops and the transport by erosive running water. Most experimental results showed that the effect of interaction between rainfall impact and surface runoff increases soil erosion in low or gentle slope. Especially, the combination of rain splash and sheet flow is the dominant runoff and erosion mechanism occurring on most steep hillslopes. In this study, a rainfall simulation was conducted to evaluate interrill erosion in steep slope with cover or non-cover. The kinetic energy of raindrops of rainfall simulator was measured by disdrometer used to measure the drop size distribution and velocity of falling raindrops and showed about 0.563 rate of that calculated from empirical equation between rainfall kinetic energy and rainfall intensity. Surface and subsurface runoff and sediment yield depended on rainfall intensity, gradient of slope, and existence of cover. Sediment from steep plots under rainfall simulator is greatly reduced by existence of the strip cover that the kinetic energy of raindrop approximates to zero. Soil erosion in steep slope with non-cover was nearly 4.93 times of that measured in plots with strip cover although runoff was only 1.82 times. The equation of a rainfall and sheet power was used to evaluate sediment yields in steep slope with cover or non-cover. The power model successfully explained physical processes for interrill erosion that combination of raindrop impact and sheet flow increases greatly soil erosion in steep slope. This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education, Science and Technology(No. 2013R1A1A3011962).

Monitoring landscape level processes using remote sensing of large plots

Treesearch

Raymond L. Czaplewski

1991-01-01

Global and regional assessaents require timely information on landscape level status (e.g., areal extent of different ecosystems) and processes (e.g., changes in land use and land cover). To measure and understand these processes at the regional level, and model their impacts, remote sensing is often necessary. However, processing massive volumes of remotely sensing...

Climate Impacts of Cover Crops

NASA Astrophysics Data System (ADS)

Lombardozzi, D.; Wieder, W. R.; Bonan, G. B.; Morris, C. K.; Grandy, S.

2016-12-01

Cover crops are planted in agricultural rotation with the intention of protecting soil rather than harvest. Cover crops have numerous environmental benefits that include preventing soil erosion, increasing soil fertility, and providing weed and pest control- among others. In addition to localized environmental benefits, cover crops can have important regional or global biogeochemical impacts by increasing soil organic carbon, changing emissions of greenhouse trace gases like nitrous oxide and methane, and reducing hydrologic nitrogen losses. Cover crops may additionally affect climate by changing biogeophysical processes, like albedo and latent heat flux, though these potential changes have not yet been evaluated. Here we use the coupled Community Atmosphere Model (CAM5) - Community Land Model (CLM4.5) to test how planting cover crops in the United States may change biogeophysical fluxes and climate. We present seasonal changes in albedo, heat fluxes, evaporative partitioning, radiation, and the resulting changes in temperature. Preliminary analyses show that during seasons when cover crops are planted, latent heat flux increases and albedo decreases, changing the evaporative fraction and surface temperatures. Understanding both the biogeophysical changes caused by planting cover crops in this study and the biogeochemical changes found in other studies will give a clearer picture of the overall impacts of cover crops on climate and atmospheric chemistry, informing how this land use strategy will impact climate in the future.

The Future of Pharmaceutical Manufacturing Sciences

PubMed Central

2015-01-01

The entire pharmaceutical sector is in an urgent need of both innovative technological solutions and fundamental scientific work, enabling the production of highly engineered drug products. Commercial‐scale manufacturing of complex drug delivery systems (DDSs) using the existing technologies is challenging. This review covers important elements of manufacturing sciences, beginning with risk management strategies and design of experiments (DoE) techniques. Experimental techniques should, where possible, be supported by computational approaches. With that regard, state‐of‐art mechanistic process modeling techniques are described in detail. Implementation of materials science tools paves the way to molecular‐based processing of future DDSs. A snapshot of some of the existing tools is presented. Additionally, general engineering principles are discussed covering process measurement and process control solutions. Last part of the review addresses future manufacturing solutions, covering continuous processing and, specifically, hot‐melt processing and printing‐based technologies. Finally, challenges related to implementing these technologies as a part of future health care systems are discussed. © 2015 The Authors. Journal of Pharmaceutical Sciences published by Wiley Periodicals, Inc. and the American Pharmacists Association J Pharm Sci 104:3612–3638, 2015 PMID:26280993

The Future of Pharmaceutical Manufacturing Sciences.

PubMed

Rantanen, Jukka; Khinast, Johannes

2015-11-01

The entire pharmaceutical sector is in an urgent need of both innovative technological solutions and fundamental scientific work, enabling the production of highly engineered drug products. Commercial-scale manufacturing of complex drug delivery systems (DDSs) using the existing technologies is challenging. This review covers important elements of manufacturing sciences, beginning with risk management strategies and design of experiments (DoE) techniques. Experimental techniques should, where possible, be supported by computational approaches. With that regard, state-of-art mechanistic process modeling techniques are described in detail. Implementation of materials science tools paves the way to molecular-based processing of future DDSs. A snapshot of some of the existing tools is presented. Additionally, general engineering principles are discussed covering process measurement and process control solutions. Last part of the review addresses future manufacturing solutions, covering continuous processing and, specifically, hot-melt processing and printing-based technologies. Finally, challenges related to implementing these technologies as a part of future health care systems are discussed. © 2015 The Authors. Journal of Pharmaceutical Sciences published by Wiley Periodicals, Inc. and the American Pharmacists Association.

Forecasting land cover change impacts on drinking water treatment costs in Minneapolis, Minnesota

NASA Astrophysics Data System (ADS)

Woznicki, S. A.; Wickham, J.

2017-12-01

Source protection is a critical aspect of drinking water treatment. The benefits of protecting source water quality in reducing drinking water treatment costs are clear. However, forecasting the impacts of environmental change on source water quality and its potential to influence future treatment processes is lacking. The drinking water treatment plant in Minneapolis, MN has recognized that land cover change threatens water quality in their source watershed, the Upper Mississippi River Basin (UMRB). Over 1,000 km2 of forests, wetlands, and grasslands in the UMRB were lost to agriculture from 2008-2013. This trend, coupled with a projected population increase of one million people in Minnesota by 2030, concerns drinking water treatment plant operators in Minneapolis with respect to meeting future demand for clean water in the UMRB. The objective of this study is to relate land cover change (forest and wetland loss, agricultural expansion, urbanization) to changes in treatment costs for the Minneapolis, MN drinking water utility. To do this, we first developed a framework to determine the relationship between land cover change and water quality in the context of recent historical changes and projected future changes in land cover. Next we coupled a watershed model, the Soil and Water Assessment Tool (SWAT) to projections of land cover change from the FOREcasting SCEnarios of Land-use Change (FORE-SCE) model for the mid-21st century. Using historical Minneapolis drinking water treatment data (chemical usage and costs), source water quality in the UMRB was linked to changes in treatment requirements as a function of projected future land cover change. These analyses will quantify the value of natural landscapes in protecting drinking water quality and future treatment processes requirements. In addition, our study provides the Minneapolis drinking water utility with information critical to their planning and capital improvement process.

Definition and documentation of engineering processes

DOE Office of Scientific and Technical Information (OSTI.GOV)

McDonald, G.W.

1997-11-01

This tutorial is an extract of a two-day workshop developed under the auspices of the Quality Engineering Department at Sandia National Laboratories. The presentation starts with basic definitions and addresses why processes should be defined and documented. It covers three primary topics: (1) process considerations and rationale, (2) approach to defining and documenting engineering processes, and (3) an IDEFO model of the process for defining engineering processes.

Land Use Change on Household Farms in the Ecuadorian Amazon: Design and Implementation of an Agent-Based Model.

PubMed

Mena, Carlos F; Walsh, Stephen J; Frizzelle, Brian G; Xiaozheng, Yao; Malanson, George P

2011-01-01

This paper describes the design and implementation of an Agent-Based Model (ABM) used to simulate land use change on household farms in the Northern Ecuadorian Amazon (NEA). The ABM simulates decision-making processes at the household level that is examined through a longitudinal, socio-economic and demographic survey that was conducted in 1990 and 1999. Geographic Information Systems (GIS) are used to establish spatial relationships between farms and their environment, while classified Landsat Thematic Mapper (TM) imagery is used to set initial land use/land cover conditions for the spatial simulation, assess from-to land use/land cover change patterns, and describe trajectories of land use change at the farm and landscape levels. Results from prior studies in the NEA provide insights into the key social and ecological variables, describe human behavioral functions, and examine population-environment interactions that are linked to deforestation and agricultural extensification, population migration, and demographic change. Within the architecture of the model, agents are classified as active or passive. The model comprises four modules, i.e., initialization, demography, agriculture, and migration that operate individually, but are linked through key household processes. The main outputs of the model include a spatially-explicit representation of the land use/land cover on survey and non-survey farms and at the landscape level for each annual time-step, as well as simulated socio-economic and demographic characteristics of households and communities. The work describes the design and implementation of the model and how population-environment interactions can be addressed in a frontier setting. The paper contributes to land change science by examining important pattern-process relations, advocating a spatial modeling approach that is capable of synthesizing fundamental relationships at the farm level, and links people and environment in complex ways.

Models of Personnel Needs Assessment.

ERIC Educational Resources Information Center

Mattson, Beverly

This report presents samples of models and strategies for determining professional development needs of special education personnel. The following areas are covered: definitions of needs and the needs assessment process; personnel needs assessment regulations under the Comprehensive System of Personnel Development, the Individuals with…

Fire modeling in the Brazilian arc of deforestation through nested coupling of atmosphere, dynamic vegetation, LUCC and fire spread models

NASA Astrophysics Data System (ADS)

Tourigny, E.; Nobre, C.; Cardoso, M. F.

2012-12-01

Deforestation of tropical forests for logging and agriculture, associated to slash-and-burn practices, is a major source of CO2 emissions, both immediate due to biomass burning and future due to the elimination of a potential CO2 sink. Feedbacks between climate change and LUCC (Land-Use and Land-Cover Change) can potentially increase the loss of tropical forests and increase the rate of CO2 emissions, through mechanisms such as land and soil degradation and the increase in wildfire occurrence and severity. However, current understanding of the processes of fires (including ignition, spread and consequences) in tropical forests and climatic feedbacks are poorly understood and need further research. As the processes of LUCC and associated fires occur at local scales, linking them to large-scale atmospheric processes requires a means of up-scaling higher resolutions processes to lower resolutions. Our approach is to couple models which operate at various spatial and temporal scales: a Global Climate Model (GCM), Dynamic Global Vegetation Model (DGVM) and local-scale LUCC and fire spread model. The climate model resolves large scale atmospheric processes and forcings, which are imposed on the surface DGVM and fed-back to climate. Higher-resolution processes such as deforestation, land use management and associated (as well as natural) fires are resolved at the local level. A dynamic tiling scheme allows to represent local-scale heterogeneity while maintaining computational efficiency of the land surface model, compared to traditional landscape models. Fire behavior is modeled at the regional scale (~500m) to represent the detailed landscape using a semi-empirical fire spread model. The relatively coarse scale (as compared to other fire spread models) is necessary due to the paucity of detailed land-cover information and fire history (particularly in the tropics and developing countries). This work presents initial results of a spatially-explicit fire spread model coupled to the IBIS DGVM model. Our area of study comprises selected regions in and near the Brazilian "arc of deforestation". For model training and evaluation, several areas have been mapped using high-resolution imagery from the Landsat TM/ETM+ sensors (Figure 1). This high resolution reference data is used for local-scale simulations and also to evaluate the accuracy of the global MCD45 burned area product, which will be used in future studies covering the entire "arc of deforestation".; Area of study along the arc of deforestation and cerrado: landsat scenes used and burned area (2010) from MCD45 product.

Land Covers Classification Based on Random Forest Method Using Features from Full-Waveform LIDAR Data

NASA Astrophysics Data System (ADS)

Ma, L.; Zhou, M.; Li, C.

2017-09-01

In this study, a Random Forest (RF) based land covers classification method is presented to predict the types of land covers in Miyun area. The returned full-waveforms which were acquired by a LiteMapper 5600 airborne LiDAR system were processed, including waveform filtering, waveform decomposition and features extraction. The commonly used features that were distance, intensity, Full Width at Half Maximum (FWHM), skewness and kurtosis were extracted. These waveform features were used as attributes of training data for generating the RF prediction model. The RF prediction model was applied to predict the types of land covers in Miyun area as trees, buildings, farmland and ground. The classification results of these four types of land covers were obtained according to the ground truth information acquired from CCD image data of the same region. The RF classification results were compared with that of SVM method and show better results. The RF classification accuracy reached 89.73% and the classification Kappa was 0.8631.

Supporting the operational use of process based hydrological models and NASA Earth Observations for use in land management and post-fire remediation through a Rapid Response Erosion Database (RRED).

NASA Astrophysics Data System (ADS)

Miller, M. E.; Elliot, W.; Billmire, M.; Robichaud, P. R.; Banach, D. M.

2017-12-01

We have built a Rapid Response Erosion Database (RRED, http://rred.mtri.org/rred/) for the continental United States to allow land managers to access properly formatted spatial model inputs for the Water Erosion Prediction Project (WEPP). Spatially-explicit process-based models like WEPP require spatial inputs that include digital elevation models (DEMs), soil, climate and land cover. The online database delivers either a 10m or 30m USGS DEM, land cover derived from the Landfire project, and soil data derived from SSURGO and STATSGO datasets. The spatial layers are projected into UTM coordinates and pre-registered for modeling. WEPP soil parameter files are also created along with linkage files to match both spatial land cover and soils data with the appropriate WEPP parameter files. Our goal is to make process-based models more accessible by preparing spatial inputs ahead of time allowing modelers to focus on addressing scenarios of concern. The database provides comprehensive support for post-fire hydrological modeling by allowing users to upload spatial soil burn severity maps, and within moments returns spatial model inputs. Rapid response is critical following natural disasters. After moderate and high severity wildfires, flooding, erosion, and debris flows are a major threat to life, property and municipal water supplies. Mitigation measures must be rapidly implemented if they are to be effective, but they are expensive and cannot be applied everywhere. Fire, runoff, and erosion risks also are highly heterogeneous in space, creating an urgent need for rapid, spatially-explicit assessment. The database has been used to help assess and plan remediation on over a dozen wildfires in the Western US. Future plans include expanding spatial coverage, improving model input data and supporting additional models. Our goal is to facilitate the use of the best possible datasets and models to support the conservation of soil and water.

A modified temporal criterion to meta-optimize the extended Kalman filter for land cover classification of remotely sensed time series

NASA Astrophysics Data System (ADS)

Salmon, B. P.; Kleynhans, W.; Olivier, J. C.; van den Bergh, F.; Wessels, K. J.

2018-05-01

Humans are transforming land cover at an ever-increasing rate. Accurate geographical maps on land cover, especially rural and urban settlements are essential to planning sustainable development. Time series extracted from MODerate resolution Imaging Spectroradiometer (MODIS) land surface reflectance products have been used to differentiate land cover classes by analyzing the seasonal patterns in reflectance values. The proper fitting of a parametric model to these time series usually requires several adjustments to the regression method. To reduce the workload, a global setting of parameters is done to the regression method for a geographical area. In this work we have modified a meta-optimization approach to setting a regression method to extract the parameters on a per time series basis. The standard deviation of the model parameters and magnitude of residuals are used as scoring function. We successfully fitted a triply modulated model to the seasonal patterns of our study area using a non-linear extended Kalman filter (EKF). The approach uses temporal information which significantly reduces the processing time and storage requirements to process each time series. It also derives reliability metrics for each time series individually. The features extracted using the proposed method are classified with a support vector machine and the performance of the method is compared to the original approach on our ground truth data.

Sensitivity of tsunami evacuation modeling to direction and land cover assumptions

USGS Publications Warehouse

Schmidtlein, Mathew C.; Wood, Nathan J.

2015-01-01

Although anisotropic least-cost-distance (LCD) modeling is becoming a common tool for estimating pedestrian-evacuation travel times out of tsunami hazard zones, there has been insufficient attention paid to understanding model sensitivity behind the estimates. To support tsunami risk-reduction planning, we explore two aspects of LCD modeling as it applies to pedestrian evacuations and use the coastal community of Seward, Alaska, as our case study. First, we explore the sensitivity of modeling to the direction of movement by comparing standard safety-to-hazard evacuation times to hazard-to-safety evacuation times for a sample of 3985 points in Seward's tsunami-hazard zone. Safety-to-hazard evacuation times slightly overestimated hazard-to-safety evacuation times but the strong relationship to the hazard-to-safety evacuation times, slightly conservative bias, and shorter processing times of the safety-to-hazard approach make it the preferred approach. Second, we explore how variations in land cover speed conservation values (SCVs) influence model performance using a Monte Carlo approach with one thousand sets of land cover SCVs. The LCD model was relatively robust to changes in land cover SCVs with the magnitude of local model sensitivity greatest in areas with higher evacuation times or with wetland or shore land cover types, where model results may slightly underestimate travel times. This study demonstrates that emergency managers should be concerned not only with populations in locations with evacuation times greater than wave arrival times, but also with populations with evacuation times lower than but close to expected wave arrival times, particularly if they are required to cross wetlands or beaches.

Integrating remotely sensed land cover observations and a biogeochemical model for estimating forest ecosystem carbon dynamics

USGS Publications Warehouse

Liu, J.; Liu, S.; Loveland, Thomas R.; Tieszen, L.L.

2008-01-01

Land cover change is one of the key driving forces for ecosystem carbon (C) dynamics. We present an approach for using sequential remotely sensed land cover observations and a biogeochemical model to estimate contemporary and future ecosystem carbon trends. We applied the General Ensemble Biogeochemical Modelling System (GEMS) for the Laurentian Plains and Hills ecoregion in the northeastern United States for the period of 1975-2025. The land cover changes, especially forest stand-replacing events, were detected on 30 randomly located 10-km by 10-km sample blocks, and were assimilated by GEMS for biogeochemical simulations. In GEMS, each unique combination of major controlling variables (including land cover change history) forms a geo-referenced simulation unit. For a forest simulation unit, a Monte Carlo process is used to determine forest type, forest age, forest biomass, and soil C, based on the Forest Inventory and Analysis (FIA) data and the U.S. General Soil Map (STATSGO) data. Ensemble simulations are performed for each simulation unit to incorporate input data uncertainty. Results show that on average forests of the Laurentian Plains and Hills ecoregion have been sequestrating 4.2 Tg C (1 teragram = 1012 gram) per year, including 1.9 Tg C removed from the ecosystem as the consequences of land cover change. ?? 2008 Elsevier B.V.

An Approach to Modeling the Water Balance Sensitivity to Landscape Vegetation Changes

NASA Astrophysics Data System (ADS)

Mohammed, I. N.; Tarboton, D. G.

2008-12-01

Watershed development and management require an understanding of how hydrological processes affect water balance components. The study of water resources management, especially in Western United States, is currently motivated by climate change, the impact of vegetation cover change on water production, and the need to manage water supplies. Vegetation management and its relation to runoff has been well documented, as reduction of forest cover, reducing evapotranspiration, increases water yield and in contrast the establishment of forest cover on sparsely vegetated land, increasing evapotranspiration, deceases water yield. This paper presents a water balance model developed to quantify the sensitivity of runoff production to changes in vegetation based on differences in evapotranspiration from different land cover types. The model is intended to provide a simple framework for estimating long term yield changes due to managed vegetation change. The model assumes that relative potential evapotranspiration from specific land cover can be quantified by a set of potential evapotranspiration coefficients for each land cover type. The model uses the Budyko curve to partition precipitation into evapotranspiration and runoff over the long term. Potential evapotranspiration is estimated from the Budyko curve for present conditions, then adjusted for land cover changes using the relative potential evapotranspiration coefficients for each land cover type. The adjusted potential evapotranspiration is then partitioned using the Budyko curve to provide estimates of long term runoff and evapotranspiration for the changed conditions. We found that the changes in runoff were in general close to being linearly proportional to the changes in land cover. In Utah study watersheds, reducing 50% of the present coniferous forests resulted in runoff increase that ranged from 0.5 to 38 mm/year, while the transition of 50% of area present as range/shrub/other to forest resulted in runoff decrease that ranged from 3.8 to 37 mm/year. The model helps to evaluate long term runoff production sensitivities to vegetation changes and answer, in a broad sense without requiring detailed information or modeling, how much runoff production could potentially be changed through vegetation management. The theoretical approach taken in this study is simple and general and could be applied to a wide range of watersheds.

Simple Process-Based Simulators for Generating Spatial Patterns of Habitat Loss and Fragmentation: A Review and Introduction to the G-RaFFe Model

PubMed Central

Pe'er, Guy; Zurita, Gustavo A.; Schober, Lucia; Bellocq, Maria I.; Strer, Maximilian; Müller, Michael; Pütz, Sandro

2013-01-01

Landscape simulators are widely applied in landscape ecology for generating landscape patterns. These models can be divided into two categories: pattern-based models that generate spatial patterns irrespective of the processes that shape them, and process-based models that attempt to generate patterns based on the processes that shape them. The latter often tend toward complexity in an attempt to obtain high predictive precision, but are rarely used for generic or theoretical purposes. Here we show that a simple process-based simulator can generate a variety of spatial patterns including realistic ones, typifying landscapes fragmented by anthropogenic activities. The model “G-RaFFe” generates roads and fields to reproduce the processes in which forests are converted into arable lands. For a selected level of habitat cover, three factors dominate its outcomes: the number of roads (accessibility), maximum field size (accounting for land ownership patterns), and maximum field disconnection (which enables field to be detached from roads). We compared the performance of G-RaFFe to three other models: Simmap (neutral model), Qrule (fractal-based) and Dinamica EGO (with 4 model versions differing in complexity). A PCA-based analysis indicated G-RaFFe and Dinamica version 4 (most complex) to perform best in matching realistic spatial patterns, but an alternative analysis which considers model variability identified G-RaFFe and Qrule as performing best. We also found model performance to be affected by habitat cover and the actual land-uses, the latter reflecting on land ownership patterns. We suggest that simple process-based generators such as G-RaFFe can be used to generate spatial patterns as templates for theoretical analyses, as well as for gaining better understanding of the relation between spatial processes and patterns. We suggest caution in applying neutral or fractal-based approaches, since spatial patterns that typify anthropogenic landscapes are often non-fractal in nature. PMID:23724108

Simple process-based simulators for generating spatial patterns of habitat loss and fragmentation: a review and introduction to the G-RaFFe model.

PubMed

Pe'er, Guy; Zurita, Gustavo A; Schober, Lucia; Bellocq, Maria I; Strer, Maximilian; Müller, Michael; Pütz, Sandro

2013-01-01

Landscape simulators are widely applied in landscape ecology for generating landscape patterns. These models can be divided into two categories: pattern-based models that generate spatial patterns irrespective of the processes that shape them, and process-based models that attempt to generate patterns based on the processes that shape them. The latter often tend toward complexity in an attempt to obtain high predictive precision, but are rarely used for generic or theoretical purposes. Here we show that a simple process-based simulator can generate a variety of spatial patterns including realistic ones, typifying landscapes fragmented by anthropogenic activities. The model "G-RaFFe" generates roads and fields to reproduce the processes in which forests are converted into arable lands. For a selected level of habitat cover, three factors dominate its outcomes: the number of roads (accessibility), maximum field size (accounting for land ownership patterns), and maximum field disconnection (which enables field to be detached from roads). We compared the performance of G-RaFFe to three other models: Simmap (neutral model), Qrule (fractal-based) and Dinamica EGO (with 4 model versions differing in complexity). A PCA-based analysis indicated G-RaFFe and Dinamica version 4 (most complex) to perform best in matching realistic spatial patterns, but an alternative analysis which considers model variability identified G-RaFFe and Qrule as performing best. We also found model performance to be affected by habitat cover and the actual land-uses, the latter reflecting on land ownership patterns. We suggest that simple process-based generators such as G-RaFFe can be used to generate spatial patterns as templates for theoretical analyses, as well as for gaining better understanding of the relation between spatial processes and patterns. We suggest caution in applying neutral or fractal-based approaches, since spatial patterns that typify anthropogenic landscapes are often non-fractal in nature.

Combustion Fundamentals Research

NASA Technical Reports Server (NTRS)

1984-01-01

The various physical processes that occur in the gas turbine combustor and the development of analytical models that accurately describe these processes are discussed. Aspects covered include fuel sprays; fluid mixing; combustion dynamics; radiation and chemistry and numeric techniques which can be applied to highly turbulent, recirculating, reacting flow fields.

Modeling temperature and humidity profiles within forest canopies

USDA-ARS?s Scientific Manuscript database

Physically-based models are a powerful tool to help understand interactions of vegetation, atmospheric dynamics, and hydrology, and to test hypotheses regarding the effects of land cover, management, hydrometeorology, and climate variability on ecosystem processes. The purpose of this paper is to f...

Scientific computations section monthly report, November 1993

DOE Office of Scientific and Technical Information (OSTI.GOV)

Buckner, M.R.

1993-12-30

This progress report from the Savannah River Technology Center contains abstracts from papers from the computational modeling, applied statistics, applied physics, experimental thermal hydraulics, and packaging and transportation groups. Specific topics covered include: engineering modeling and process simulation, criticality methods and analysis, plutonium disposition.

Development and testing of a physically based model of streambank erosion for coupling with a basin-scale hydrologic model SWAT

USDA-ARS?s Scientific Manuscript database

A comprehensive stream bank erosion model based on excess shear stress has been developed and incorporated in the hydrological model Soil and Water Assessment Tool (SWAT). It takes into account processes such as weathering, vegetative cover, and channel meanders to adjust critical and effective str...

Assessing the Impact of Land Use and Land Cover Change on Global Water Resources

NASA Astrophysics Data System (ADS)

Batra, N.; Yang, Y. E.; Choi, H. I.; Islam, A.; Charlotte, D. F.; Cai, X.; Kumar, P.

2007-12-01

Land use and land cover changes (LULCC) significantly modify the hydrological regime of the watersheds, affecting water resources and environment from regional to global scale. This study seeks to advance and integrate water and energy cycle observation, scientific understanding, and human impacts to assess future water availability. To achieve the research objective, we integrate and interpret past and current space based and in situ observations into a global hydrologic model (GHM). GHM is developed with enhanced spatial and temporal resolution, physical complexity, hydrologic theory and processes to quantify the impact of LULCC on physical variables: surface runoff, subsurface flow, groundwater, infiltration, ET, soil moisture, etc. Coupled with the common land model (CLM), a 3-dimensional volume averaged soil-moisture transport (VAST) model is expanded to incorporate the lateral flow and subgrid heterogeneity. The model consists of 11 soil-hydrology layers to predict lateral as well as vertical moisture flux transport based on Richard's equations. The primary surface boundary conditions (SBCs) include surface elevation and its derivatives, land cover category, sand and clay fraction profiles, bedrock depth and fractional vegetation cover. A consistent global GIS-based dataset is constructed for the SBCs of the model from existing observational datasets comprising of various resolutions, map projections and data formats. Global ECMWF data at 6-hour time steps for the period 1971 through 2000 is processed to get the forcing data which includes incoming longwave and shortwave radiation, precipitation, air temperature, pressure, wind components, boundary layer height and specific humidity. Land use land cover data, generated using IPCC scenarios for every 10 years from 2000 to 2100 is used for future assessment on water resources. Alterations due to LULCC on surface water balance components: ET, groundwater recharge and runoff are then addressed in the study. Land use change disrupts the hydrological cycle through increasing the water yield at some places leading to floods while diminishing, or even eliminating the low flow at other places.

42 CFR 82.18 - How will NIOSH calculate internal dose to the primary cancer site(s)?

Code of Federal Regulations, 2010 CFR

2010-10-01

... primary cancer site(s)? 82.18 Section 82.18 Public Health PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND... Dose Reconstruction Process § 82.18 How will NIOSH calculate internal dose to the primary cancer site(s... cancer covered by a claim is in a tissue not covered by existing ICRP models, NIOSH will use the ICRP...

42 CFR 82.18 - How will NIOSH calculate internal dose to the primary cancer site(s)?

Code of Federal Regulations, 2011 CFR

2011-10-01

... primary cancer site(s)? 82.18 Section 82.18 Public Health PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND... Dose Reconstruction Process § 82.18 How will NIOSH calculate internal dose to the primary cancer site(s... cancer covered by a claim is in a tissue not covered by existing ICRP models, NIOSH will use the ICRP...

Land-use and land-cover change carbon emissions between 1901 and 2012 constrained by biomass observations

Treesearch

Wei Li; Philippe Ciais; Shushi Peng; Chao Yue; Yilong Wang; Martin Thurner; Sassan S. Saatchi; Almut Arneth; Valerio Avitabile; Nuno Carvalhais; Anna B. Harper; Etsushi Kato; Charles Koven; Yi Y. Liu; Julia E. M. S. Nabel; Yude Pan; Julia Pongratz; Benjamin Poulter; Thomas A. M. Pugh; Maurizio Santoro; Stephen Sitch; Benjamin D. Stocker; Nicolas Viovy; Andy Wiltshire; Rasoul Yousefpour; Sönke Zaehle

2017-01-01

The use of dynamic global vegetation models (DGVMs) to estimate CO2 emissions from land-use and land-cover change (LULCC) offers a new window to account for spatial and temporal details of emissions and for ecosystem processes affected by LULCC. One drawback of LULCC emissions from DGVMs, however, is lack of observation constraint. Here, we...

Rapid-response tools and datasets for post-fire remediation: Linking remote sensing and process-based hydrological models

Treesearch

M. E. Miller; William Elliot; M. Billmire; Pete Robichaud; K. A. Endsley

2016-01-01

Post-wildfire flooding and erosion can threaten lives, property and natural resources. Increased peak flows and sediment delivery due to the loss of surface vegetation cover and fire-induced changes in soil properties are of great concern to public safety. Burn severity maps derived from remote sensing data reflect fire-induced changes in vegetative cover and soil...

42 CFR 82.18 - How will NIOSH calculate internal dose to the primary cancer site(s)?

Code of Federal Regulations, 2013 CFR

2013-10-01

... primary cancer site(s)? 82.18 Section 82.18 Public Health PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND... Dose Reconstruction Process § 82.18 How will NIOSH calculate internal dose to the primary cancer site(s... cancer covered by a claim is in a tissue not covered by existing ICRP models, NIOSH will use the ICRP...

42 CFR 82.18 - How will NIOSH calculate internal dose to the primary cancer site(s)?

Code of Federal Regulations, 2014 CFR

2014-10-01

... primary cancer site(s)? 82.18 Section 82.18 Public Health PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND... Dose Reconstruction Process § 82.18 How will NIOSH calculate internal dose to the primary cancer site(s... cancer covered by a claim is in a tissue not covered by existing ICRP models, NIOSH will use the ICRP...

42 CFR 82.18 - How will NIOSH calculate internal dose to the primary cancer site(s)?

Code of Federal Regulations, 2012 CFR

2012-10-01

... primary cancer site(s)? 82.18 Section 82.18 Public Health PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND... Dose Reconstruction Process § 82.18 How will NIOSH calculate internal dose to the primary cancer site(s... cancer covered by a claim is in a tissue not covered by existing ICRP models, NIOSH will use the ICRP...

Can we use Earth Observations to improve monthly water level forecasts?

NASA Astrophysics Data System (ADS)

Slater, L. J.; Villarini, G.

2017-12-01

Dynamical-statistical hydrologic forecasting approaches benefit from different strengths in comparison with traditional hydrologic forecasting systems: they are computationally efficient, can integrate and `learn' from a broad selection of input data (e.g., General Circulation Model (GCM) forecasts, Earth Observation time series, teleconnection patterns), and can take advantage of recent progress in machine learning (e.g. multi-model blending, post-processing and ensembling techniques). Recent efforts to develop a dynamical-statistical ensemble approach for forecasting seasonal streamflow using both GCM forecasts and changing land cover have shown promising results over the U.S. Midwest. Here, we use climate forecasts from several GCMs of the North American Multi Model Ensemble (NMME) alongside 15-minute stage time series from the National River Flow Archive (NRFA) and land cover classes extracted from the European Space Agency's Climate Change Initiative 300 m annual Global Land Cover time series. With these data, we conduct systematic long-range probabilistic forecasting of monthly water levels in UK catchments over timescales ranging from one to twelve months ahead. We evaluate the improvement in model fit and model forecasting skill that comes from using land cover classes as predictors in the models. This work opens up new possibilities for combining Earth Observation time series with GCM forecasts to predict a variety of hazards from space using data science techniques.

A model for the prediction of latent errors using data obtained during the development process

NASA Technical Reports Server (NTRS)

Gaffney, J. E., Jr.; Martello, S. J.

1984-01-01

A model implemented in a program that runs on the IBM PC for estimating the latent (or post ship) content of a body of software upon its initial release to the user is presented. The model employs the count of errors discovered at one or more of the error discovery processes during development, such as a design inspection, as the input data for a process which provides estimates of the total life-time (injected) error content and of the latent (or post ship) error content--the errors remaining a delivery. The model presented presumes that these activities cover all of the opportunities during the software development process for error discovery (and removal).

Global Impacts of Long-Term Land Cover Changes Within China's Densely Populated Rural Regions

NASA Astrophysics Data System (ADS)

Ellis, E. C.

2006-12-01

Long-term changes in land cover are usually investigated in terms of large-scale change processes such as urban expansion, deforestation and land conversion to agriculture. Yet China's densely populated agricultural regions, which cover more than 2 million square kilometers of Monsoon Asia, have been transformed profoundly over the past fifty years by fine-scale changes in land cover caused by unprecedented changes in population, technology and social conditions. Using a regional sampling and upscaling design coupled with high-resolution landscape change measurements at five field sites, we investigated long-term changes in land cover and ecological processes, circa 1945 to 2002, within and across China's densely populated agricultural regions. As expected, the construction of buildings and roads increased impervious surface area over time, but the total net increase was surprising, being similar in magnitude to the total current extent of China's cities. Agricultural land area declined over the same period, while tree cover increased, by about 10%, driven by tree planting and regrowth around new buildings, the introduction of perennial agriculture, improved forestry, and declines in annual crop cultivation. Though changes in impervious surface areas were closely related to changes in population density, long-term changes in agricultural land and tree cover were unrelated to populated density and required explanation by more complex models with strong regional and biophysical components. Moreover, most of these changes occurred primarily at fine spatial scales (< 30 m), under the threshold for conventional global and regional land cover change measurements. Given that these changes in built structures and vegetation cover have the potential to contribute substantially to regional and global changes in biogeochemistry, hydrology, and land-atmosphere interactions, future investigations of these changes and their impacts across Monsoon Asia would benefit from models that incorporate fine-scale landscape structure and its changes over time.

Streamflow response to future land-cover change at a headwaters catchment spanning the alpine-subalpine transition on the Colorado Front Range

NASA Astrophysics Data System (ADS)

Barnhart, T. B.; Vukomanovic, J.; Bourgeron, P.; Molotch, N. P.

2017-12-01

Land-cover change at the alpine-subalpine interface has the potential to change the water balance of mountainous, snow-dominated catchments due to the influence of vegetation on blowing snow, effective precipitation, evapotranspiration, and other processes. Understanding how land-cover change will impact water resources in snow-dominated regions is of critical importance as these locations produce a disproportionate amount of runoff relative to their land area. We coupled the LANdscape DIsturbance and Succession (LANDIS-II) model with a spatially explicit, physics-based, watershed process model, the Regional Hydro-Ecologic Simulation System (RHESSys), to simulate land-cover change and its impact on the water balance in a 6.6 km­2 headwater catchment that spans the alpine-subalpine transition on the Colorado Front Range. We simulated two potential futures of air temperature warming (+4 °C/century) to 2100: a) increased precipitation (+15%, MP) and b) decreased precipitation (-15%, LP). As the LANDIS-II model simulates forest succession in a stochastic manner, we use three LANDIS-II model runs each for the MP and LP future forcing conditions. For both MP and LP, the RHESSys forcing data set was updated to reflect the changes in precipitation and temperature used to generate the land-cover futures. Forest cover in the catchment increased from 72% in 2000 to 84% and 83% in 2050 and to 95% and 92% in 2100 for MP and LP, respectively. Somewhat surprisingly, this increase in forest cover led to mean increases in streamflow production of 9% for MP and 3% for LP in 2050. In 2100, mean streamflow production increased by 15% and 6% for the MP and LP scenarios, respectively. This is likely due to increases in effective precipitation as the catchment forested and blowing snow decreased. Indeed, catchment effective precipitation increased from 94% in 2000 to 97% and 99% in 2050 and 2100, respectively, for both MP and LP conditions. This result counters previous work as runoff production increased with forested area, highlighting the need to better understand the impacts of forest expansion on blowing snow and effective precipitation. Identifying the hydrologic response of mountainous areas to climate warming induced land-cover change is of critical importance due to the potential water resources impacts in downstream regions.

Snow cover distribution over elevation zones in a mountainous catchment

NASA Astrophysics Data System (ADS)

Panagoulia, D.; Panagopoulos, Y.

2009-04-01

A good understanding of the elevetional distribution of snow cover is necessary to predict the timing and volume of runoff. In a complex mountainous terrain the snow cover distribution within a watershed is highly variable in time and space and is dependent on elevation, slope, aspect, vegetation type, surface roughness, radiation load, and energy exchange at the snow-air interface. Decreases in snowpack due to climate change could disrupt the downstream urban and agricultural water supplies, while increases could lead to seasonal flooding. Solar and longwave radiation are dominant energy inputs driving the ablation process. Turbulent energy exchange at the snow cover surface is important during the snow season. The evaporation of blowing and drifting snow is strongly dependent upon wind speed. Much of the spatial heterogeneity of snow cover is the result of snow redistribution by wind. Elevation is important in determining temperature and precipitation gradients along hillslopes, while the temperature gradients determine where precipitation falls as rain and snow and contribute to variable melt rates within the hillslope. Under these premises, the snow accumulation and ablation (SAA) model of the US National Weather Service (US NWS) was applied to implement the snow cover extent over elevation zones of a mountainous catchment (the Mesochora catchment in Western-Central Greece), taking also into account the indirectly included processes of sublimation, interception, and snow redistribution. The catchment hydrology is controlled by snowfall and snowmelt and the simulated discharge was computed from the soil moisture accounting (SMA) model of the US NWS and compared to the measured discharge. The elevationally distributed snow cover extent presented different patterns with different time of maximization, extinction and return during the year, producing different timing of discharge that is a crucial factor for the control and management of water resources systems.

Man's impact on the troposphere: Lectures in tropospheric chemistry

NASA Technical Reports Server (NTRS)

Levine, J. S. (Editor); Schryer, D. R. (Editor)

1978-01-01

Lectures covering a broad spectrum of current research in tropospheric chemistry with particular emphasis on the interaction of measurements, modeling, and understanding of fundamental processes are presented.

A missing piece of the puzzle in climate change hotspots: Near-surface turbulent interactions controlling ET-soil moisture coupling in semiarid areas

NASA Astrophysics Data System (ADS)

Haghighi, Erfan; Gianotti, Daniel J.; Rigden, Angela J.; Salvucci, Guido D.; Kirchner, James W.; Entekhabi, Dara

2017-04-01

Being located in the transitional zone between dry and wet climate areas, semiarid ecosystems (and their associated ecohydrological processes) play a critical role in controlling climate change and global warming. Land evapotranspiration (ET), which is a central process in the climate system and a nexus of the water, energy and carbon cycles, typically accounts for up to 95% of the water budget in semiarid areas. Thus, the manner in which ET is partitioned into soil evaporation and plant transpiration in these settings is of practical importance for water and carbon cycling and their feedbacks to the climate system. ET (and its partitioning) in these regions is primarily controlled by surface soil moisture which varies episodically under stochastic precipitation inputs. Important as the ET-soil moisture relationship is, it remains empirical, and physical mechanisms governing its nature and dynamics are underexplored. Thus, the objective of this study is twofold: (1) to provide observational evidence for the influence of surface cover conditions on ET-soil moisture coupling in semiarid regions using soil moisture data from NASA's SMAP satellite mission combined with independent observationally based ET estimates, and (2) to develop a relatively simple mechanistic modeling platform improving our physical understanding of interactions between micro and macroscale processes controlling ET and its partitioning in partially vegetated areas. To this end, we invoked concepts from recent progress in mechanistic modeling of turbulent energy flux exchange in bluff-rough regions, and developed a physically based ET model that explicitly accounts for how vegetation-induced turbulence in the near-surface region influences soil drying and thus ET rates and dynamics. Model predictions revealed nonlinearities in the strength of the ET-soil moisture relationship (i.e., ∂ET/∂θ) as vegetation cover fraction increases, accounted for by the nonlinearity of surface-cover-dependent turbulent interactions. We identified a (predictable) critical vegetation cover fraction (as a function of vegetation stature and environmental conditions) that yields the strongest ET-soil moisture relationship under prescribed atmospheric conditions. Overall, the results suggest that ∂ET/ ∂θ varies more widely in regions with tall-stature woody vegetation that experience higher rates of change in turbulence intensity as the cover fraction increases. Our results facilitate a mathematically tractable description of ∂ET/ ∂θ, which is a core component of models that seek to predict hydrology-climate feedback processes in a changing climate.

Multi-scale, multi-model assessment of projected land allocation

NASA Astrophysics Data System (ADS)

Vernon, C. R.; Huang, M.; Chen, M.; Calvin, K. V.; Le Page, Y.; Kraucunas, I.

2017-12-01

Effects of land use and land cover change (LULCC) on climate are generally classified into two scale-dependent processes: biophysical and biogeochemical. An extensive amount of research has been conducted related to the impact of each process under alternative climate change futures. However, these studies are generally focused on the impacts of a single process and fail to bridge the gap between sector-driven scale dependencies and any associated dynamics. Studies have been conducted to better understand the relationship of these processes but their respective scale has not adequately captured overall interdependencies between land surface changes and changes in other human-earth systems (e.g., energy, water, economic, etc.). There has also been considerable uncertainty surrounding land use land cover downscaling approaches due to scale dependencies. Demeter, a land use land cover downscaling and change detection model, was created to address this science gap. Demeter is an open-source model written in Python that downscales zonal land allocation projections to the gridded resolution of a user-selected spatial base layer (e.g., MODIS, NLCD, EIA CCI, etc.). Demeter was designed to be fully extensible to allow for module inheritance and replacement for custom research needs, such as flexible IO design to facilitate the coupling of Earth system models (e.g., the Accelerated Climate Modeling for Energy (ACME) and the Community Earth System Model (CESM)) to integrated assessment models (e.g., the Global Change Assessment Model (GCAM)). In this study, we first assessed the sensitivity of downscaled LULCC scenarios at multiple resolutions from Demeter to its parameters by comparing them to historical LULC change data. "Optimal" values of key parameters for each region were identified and used to downscale GCAM-based future scenarios consistent with those in the Land Use Model Intercomparison Project (LUMIP). Demeter-downscaled land use scenarios were then compared to the default LUMIP scenarios to illustrate the uncertainties in projected LULC as a result of difference in downscaling algorithms. Our results show that such uncertainties could propagate to other components in ACME and CESM and lead to significant differences in simulated water and biogeochemical cycles.

Random covering of the circle: the configuration-space of the free deposition process

NASA Astrophysics Data System (ADS)

Huillet, Thierry

2003-12-01

Consider a circle of circumference 1. Throw at random n points, sequentially, on this circle and append clockwise an arc (or rod) of length s to each such point. The resulting random set (the free gas of rods) is a collection of a random number of clusters with random sizes. It models a free deposition process on a 1D substrate. For such processes, we shall consider the occurrence times (number of rods) and probabilities, as n grows, of the following configurations: those avoiding rod overlap (the hard-rod gas), those for which the largest gap is smaller than rod length s (the packing gas), those (parking configurations) for which hard rod and packing constraints are both fulfilled and covering configurations. Special attention is paid to the statistical properties of each such (rare) configuration in the asymptotic density domain when ns = rgr, for some finite density rgr of points. Using results from spacings in the random division of the circle, explicit large deviation rate functions can be computed in each case from state equations. Lastly, a process consisting in selecting at random one of these specific equilibrium configurations (called the observable) can be modelled. When particularized to the parking model, this system produces parking configurations differently from Rényi's random sequential adsorption model.

Pairing top-down and bottom-up approaches to analyze catchment scale management of water quality and quantity

NASA Astrophysics Data System (ADS)

Lovette, J. P.; Duncan, J. M.; Band, L. E.

2016-12-01

Watershed management requires information on the hydrologic impacts of local to regional land use, land cover and infrastructure conditions. Management of runoff volumes, storm flows, and water quality can benefit from large scale, "top-down" screening tools, using readily available information, as well as more detailed, "bottom-up" process-based models that explicitly track local runoff production and routing from sources to receiving water bodies. Regional scale data, available nationwide through the NHD+, and top-down models based on aggregated catchment information provide useful tools for estimating regional patterns of peak flows, volumes and nutrient loads at the catchment level. Management impacts can be estimated with these models, but have limited ability to resolve impacts beyond simple changes to land cover proportions. Alternatively, distributed process-based models provide more flexibility in modeling management impacts by resolving spatial patterns of nutrient source, runoff generation, and uptake. This bottom-up approach can incorporate explicit patterns of land cover, drainage connectivity, and vegetation extent, but are typically applied over smaller areas. Here, we first model peak flood flows and nitrogen loads across North Carolina's 70,000 NHD+ catchments using USGS regional streamflow regression equations and the SPARROW model. We also estimate management impact by altering aggregated sources in each of these models. To address the missing spatial implications of the top-down approach, we further explore the demand for riparian buffers as a management strategy, simulating the accumulation of nutrient sources along flow paths and the potential mitigation of these sources through forested buffers. We use the Regional Hydro-Ecological Simulation System (RHESSys) to model changes across several basins in North Carolina's Piedmont and Blue Ridge regions, ranging in size from 15 - 1,130 km2. The two approaches provide a complementary set of tools for large area screening, followed by smaller, more process based assessment and design tools.

A Distributed Snow Evolution Modeling System (SnowModel)

NASA Astrophysics Data System (ADS)

Liston, G. E.; Elder, K.

2004-12-01

A spatially distributed snow-evolution modeling system (SnowModel) has been specifically designed to be applicable over a wide range of snow landscapes, climates, and conditions. To reach this goal, SnowModel is composed of four sub-models: MicroMet defines the meteorological forcing conditions, EnBal calculates surface energy exchanges, SnowMass simulates snow depth and water-equivalent evolution, and SnowTran-3D accounts for snow redistribution by wind. While other distributed snow models exist, SnowModel is unique in that it includes a well-tested blowing-snow sub-model (SnowTran-3D) for application in windy arctic, alpine, and prairie environments where snowdrifts are common. These environments comprise 68% of the seasonally snow-covered Northern Hemisphere land surface. SnowModel also accounts for snow processes occurring in forested environments (e.g., canopy interception related processes). SnowModel is designed to simulate snow-related physical processes occurring at spatial scales of 5-m and greater, and temporal scales of 1-hour and greater. These include: accumulation from precipitation; wind redistribution and sublimation; loading, unloading, and sublimation within forest canopies; snow-density evolution; and snowpack ripening and melt. To enhance its wide applicability, SnowModel includes the physical calculations required to simulate snow evolution within each of the global snow classes defined by Sturm et al. (1995), e.g., tundra, taiga, alpine, prairie, maritime, and ephemeral snow covers. The three, 25-km by 25-km, Cold Land Processes Experiment (CLPX) mesoscale study areas (MSAs: Fraser, North Park, and Rabbit Ears) are used as SnowModel simulation examples to highlight model strengths, weaknesses, and features in forested, semi-forested, alpine, and shrubland environments.

Integrated evaluation of the vulnerability to thermokarst disturbance and its implications for the regional carbon balance in boreal Alaska

NASA Astrophysics Data System (ADS)

Helene, G.; Lara, M. J.; McGuire, A. D.; Euskirchen, E. S.; Bolton, W. R.; Romanovsky, V. E.

2017-12-01

Our capacity to project future ecosystem trajectories in northern permafrost regions depends on our ability to characterize complex interactions between climatic and ecological processes at play in the soil, the vegetation, and the atmosphere. We present a study that uses remote sensing analyses, field observations, and data synthesis to inform models for the prediction of ecosystem responses to climate change in the boreal zone of Alaska. Recent warming, altered precipitation and fire regimes are driving permafrost degradation, threatening to mobilize vast reservoirs of ancient carbon previously protected from decomposition. Although large scale, progressive, top-down permafrost thaw have been well studied and represented in high-latitude ecosystem models, the consequences of abrupt and local thermokarst disturbances (TK) are less well understood. To fill this gap, we conducted a detection analysis characterizing 60 years of land cover change in the Tanana Flats, a wetland complex subjected to TK disturbance in Interior Alaska, using aerial and satellite images. We observed a nonlinear loss of permafrost plateau forest associated with TK and driven by precipitation and forest fragmentation. The results of this analysis were integrated into the Alaska Thermokarst Model (ATM), a state-and-transition model that simulates land cover change associated with TK disturbance. Thermokarst-related land cover change was simulated from 2000 to 2100 across the Tanana Flats. By 2100, the model predicts a mean decrease of 7.4% (sd 1.8%) in permafrost plateau forests associated with an increase in TK fens and bogs. Transitions from permafrost plateau forests to TK wetlands are accompanied with changes in physical and biogeochemical processes affecting ecosystem carbon balance. We evaluated the consequences of TK disturbances on the regional carbon balance by coupling outputs from the ATM and from a process-based biogeochemical model. We used long-term field observations of vegetation and soil physical and biogeochemical attributes to develop new parameterizations for TK wetlands and permafrost plateau forest land cover types. Preliminary simulations from 2000 to 2100 estimate that the conversion of permafrost plateau forest to young TK wetlands would result in a 7.5% (sd 3.5%) decrease in Net Ecosystem Exchange.

Studies in astronomical time series analysis. IV - Modeling chaotic and random processes with linear filters

NASA Technical Reports Server (NTRS)

Scargle, Jeffrey D.

1990-01-01

While chaos arises only in nonlinear systems, standard linear time series models are nevertheless useful for analyzing data from chaotic processes. This paper introduces such a model, the chaotic moving average. This time-domain model is based on the theorem that any chaotic process can be represented as the convolution of a linear filter with an uncorrelated process called the chaotic innovation. A technique, minimum phase-volume deconvolution, is introduced to estimate the filter and innovation. The algorithm measures the quality of a model using the volume covered by the phase-portrait of the innovation process. Experiments on synthetic data demonstrate that the algorithm accurately recovers the parameters of simple chaotic processes. Though tailored for chaos, the algorithm can detect both chaos and randomness, distinguish them from each other, and separate them if both are present. It can also recover nonminimum-delay pulse shapes in non-Gaussian processes, both random and chaotic.

A data-based conservation planning tool for Florida panthers

USGS Publications Warehouse

Murrow, Jennifer L.; Thatcher, Cindy A.; Van Manen, Frank T.; Clark, Joseph D.

2013-01-01

Habitat loss and fragmentation are the greatest threats to the endangered Florida panther (Puma concolor coryi). We developed a data-based habitat model and user-friendly interface so that land managers can objectively evaluate Florida panther habitat. We used a geographic information system (GIS) and the Mahalanobis distance statistic (D2) to develop a model based on broad-scale landscape characteristics associated with panther home ranges. Variables in our model were Euclidean distance to natural land cover, road density, distance to major roads, human density, amount of natural land cover, amount of semi-natural land cover, amount of permanent or semi-permanent flooded area–open water, and a cost–distance variable. We then developed a Florida Panther Habitat Estimator tool, which automates and replicates the GIS processes used to apply the statistical habitat model. The estimator can be used by persons with moderate GIS skills to quantify effects of land-use changes on panther habitat at local and landscape scales. Example applications of the tool are presented.

Outdoor Recreation Management

ERIC Educational Resources Information Center

Jubenville, Alan

The complex problems facing the manager of an outdoor recreation area are outlined and discussed. Eighteen chapters cover the following primary concerns of the manager of such a facility: (1) an overview of the management process; (2) the basic outdoor recreation management model; (3) the problem-solving process; (4) involvement of the public in…

(Working) Memory and L2 Acquisition and Processing

ERIC Educational Resources Information Center

Rankin, Tom

2017-01-01

This review evaluates two recent anthologies that survey research at the intersection of cognitive psychological investigations of (working) memory and issues in second language (L2), and bilingual processing and acquisition. The volumes cover similar ground by outlining the theoretical underpinnings of models of (working) memory as well as…

Modelling debris transport within glaciers by advection in a full-Stokes ice flow model

NASA Astrophysics Data System (ADS)

Wirbel, Anna; Jarosch, Alexander H.; Nicholson, Lindsey

2018-01-01

Glaciers with extensive surface debris cover respond differently to climate forcing than those without supraglacial debris. In order to include debris-covered glaciers in projections of glaciogenic runoff and sea level rise and to understand the paleoclimate proxy recorded by such glaciers, it is necessary to understand the manner and timescales over which a supraglacial debris cover develops. Because debris is delivered to the glacier by processes that are heterogeneous in space and time, and these debris inclusions are altered during englacial transport through the glacier system, correctly determining where, when and how much debris is delivered to the glacier surface requires knowledge of englacial transport pathways and deformation. To achieve this, we present a model of englacial debris transport in which we couple an advection scheme to a full-Stokes ice flow model. The model performs well in numerical benchmark tests, and we present both 2-D and 3-D glacier test cases that, for a set of prescribed debris inputs, reproduce the englacial features, deformation thereof and patterns of surface emergence predicted by theory and observations of structural glaciology. In a future step, coupling this model to (i) a debris-aware surface mass balance scheme and (ii) a supraglacial debris transport scheme will enable the co-evolution of debris cover and glacier geometry to be modelled.

NASA-Chinese Aeronautical Establishment (CAE) Symposium

NASA Technical Reports Server (NTRS)

1986-01-01

Several topics relative to combustion research are discussed. A numerical study of combustion processes in afterburners; the modeling of turbulent, reactive flow; gas turbine research; modeling of dilution jet flow fields; and chemical shock tubes as tools for studying high-temperature chemical kinetics are among the topics covered.

Walking the Walk: Modeling Social Model and Universal Design in the Disabilities Office

ERIC Educational Resources Information Center

Thornton, Melanie; Downs, Sharon

2010-01-01

Making the shift from the medical model of disability to the social model requires postsecondary disabilities offices to carefully examine and revise policies and procedures to reflect this paradigm shift, which gives them the credibility to work toward such change on the campus level. The process followed by one university is covered in-depth, as…

Land Cover Land Use Change and Soil Organic Carbon under Climate Variability in the Semi-Arid West African Sahel (1960-2050)

ERIC Educational Resources Information Center

Dieye, Amadou M.

2016-01-01

Land Cover Land Use (LCLU) change affects land surface processes recognized to influence climate change at local, national and global levels. Soil organic carbon is a key component for the functioning of agro-ecosystems and has a direct effect on the physical, chemical and biological characteristics of the soil. The capacity to model and project…

Effects of Land Cover on the Movement of Frugivorous Birds in a Heterogeneous Landscape.

PubMed

Da Silveira, Natalia Stefanini; Niebuhr, Bernardo Brandão S; Muylaert, Renata de Lara; Ribeiro, Milton Cezar; Pizo, Marco Aurélio

2016-01-01

Movement is a key spatiotemporal process that enables interactions between animals and other elements of nature. The understanding of animal trajectories and the mechanisms that influence them at the landscape level can yield insight into ecological processes and potential solutions to specific ecological problems. Based upon optimal foraging models and empirical evidence, we hypothesized that movement by thrushes is highly tortuous (low average movement speeds and homogeneous distribution of turning angles) inside forests, moderately tortuous in urban areas, which present intermediary levels of resources, and minimally tortuous (high movement speeds and turning angles next to 0 radians) in open matrix types (e.g., crops and pasture). We used data on the trajectories of two common thrush species (Turdus rufiventris and Turdus leucomelas) collected by radio telemetry in a fragmented region in Brazil. Using a maximum likelihood model selection approach we fit four probability distribution models to average speed data, considering short-tailed, long-tailed, and scale-free distributions (to represent different regimes of movement variation), and one distribution to relative angle data. Models included land cover type and distance from forest-matrix edges as explanatory variables. Speed was greater farther away from forest edges and increased faster inside forest habitat compared to urban and open matrices. However, turning angle was not influenced by land cover. Thrushes presented a very tortuous trajectory, with many displacements followed by turns near 180 degrees. Thrush trajectories resembled habitat and edge dependent, tortuous random walks, with a well-defined movement scale inside each land cover type. Although thrushes are habitat generalists, they showed a greater preference for forest edges, and thus may be considered edge specialists. Our results reinforce the importance of studying animal movement patterns in order to understand ecological processes such as seed dispersal in fragmented areas, where the percentage of remaining habitat is dwindling.

Investigating the variation of terrestrial water storage under changing climate and land cover

NASA Astrophysics Data System (ADS)

Fang, Y.; Niu, G. Y.; Zhang, X.; Troch, P. A. A.

2015-12-01

Terrestrial water storage (TWS) consists of groundwater, soil moisture, snow and ice, lakes and rivers and water contained in biomass. The water storage, especially the subsurface storage, is an essential property of the catchment, which controls climate, hydrological and biogeochemical processes at different scales. During the past decades, climate and land cover change has been proved to exert significant influences on hydrological processes which in turn alters the TWS variation. In order to better understand the interaction and feedback mechanism between TWS and earth system, it is necessary to quantify the effects of climate and land cover change on TWS variation. Direct estimation of total TWS has been made possible by the Gravity Recovery And Climate Experiment (GRACE) satellites that measures the earth gravity field. At present, few efforts were made to explicitly investigate the TWS variation under changing climate and land cover. GRACE data has its own limitations. One is its temporal coverage is short, it's only available since 2002, which is not sufficient to reflect the trend due to climate and land cover change. The other reason is that it cannot distinguish different components contributing to TWS. The limitation of TWS observation data can be overcame by numerical models developed to reproduce or to predict different earth system processes. After calibration and validation, with limited observations, these models can be trusted to extend our knowledge to where observations are not available both in time and space. In this study, based on Noah-MP LSM and satellite and ground data, we aim to: (1) Investigate the variation of total TWS as well as its components over Upper Colorado River Basin from 1990 to 2014. (2) Identify the major factors that control the TWS variation. (3) Quantify how the changing climate and land cover affect TWS variation in the same period.

A landscape-scale assessment of plant communities, hydrologic processes, and state-and-transition theory in a western juniper dominated ecosystem

NASA Astrophysics Data System (ADS)

Petersen, Steven L.

Western juniper has rapidly expanded into sagebrush steppe communities in the Intermountain West during the past 120 years. This expansion has occurred across a wide range of soil types and topographic positions. These plant communities, however, are typically treated in current peer-reviewed literature generically. The focus of this research is to investigate watershed level response to Western juniper encroachment at multiple topographic positions. Data collected from plots used to measure vegetation, soil moisture, and infiltration rates show that intercanopy sites within encroached Western juniper communities generally exhibit a significant decrease in intercanopy plant density and cover, decreased infiltration rates, increased water sediment content, and lower soil moisture content. High-resolution remotely sensed imagery and Geographic Information Systems were used with these plot level measurements to characterize and model the landscape-scale response for both biotic and abiotic components of a Western juniper encroached ecosystem. These data and their analyses included an inventory of plant density, plant cover, bare ground, gap distance and cover, a plant community classification of intercanopy patches and juniper canopy cover, soil moisture estimation, solar insulation prediction, slope and aspect. From these data, models were built that accurately predicted shrub density and shrub cover throughout the watershed study area, differentiated by aspect. We propose a new model of process-based plant community dynamics associated with current state-and-transition theory. This model is developed from field measurements and spatially explicit information that characterize the relationship between the matrix mountain big sagebrush plant community and intercanopy plant community patterns occurring within a Western juniper dominated woodland at a landscape scale. Model parameters (states, transitions, and thresholds) are developed based on differences in shrub density and cover, steady-state infiltration rates, water sediment content, and percent bare ground in response to juniper competition and topographic position. Results from both analysis of variance and multivariate hierarchical cluster analysis indicate that states, transitions, and thresholds can be accurately predicted for intercanopy areas occurring within the study area. In theory, this model and the GIS-based layers produced from this research can be used together to predict states, transitions, and thresholds for any location within the extent of the study area. This is a valuable tool for assessing sites at risk and those that have exceeded the ability to self-repair.

Reproduction of influence of autumn snow cover anomalies on the following winter atmospheric dynamics in INMCM4.0 and INMCM5.0 data

NASA Astrophysics Data System (ADS)

Martynova, Yuliya

2015-04-01

There are different studies of the influence of autumn snow cover anomalies on atmospheric dynamics in the following winter (e.g. Allen R.J. and Zender C.S., 2011; Martynova Yu.V. and Krupchatnikov V.N., 2010). The mechanism of this effect is complex and largely affects stratospheric processes (Cohen J. et al., 2007). The snow cover rapidly increases exceeding normal values. Emerged diabatic cooling results in pressure increase over and temperature decrease under the normal value. Thus, in troposphere upward energy flux increases, and then it is absorbed in stratosphere. Strong convergence of wave activity flux causes geopotential heights increase, polar vortex slowdown and stratospheric temperature increase. Emerged geopotential and wind anomalies extend from stratosphere to troposphere up to surface. As a result, strong negative AO mode appears near the surface as surface air temperature increase. Siberia plays important role in this mechanism. Firstly, the most extensive snow cover is formed there. Secondly, according to NOAA satellite observations this cover is generally formed in October (Gong G. Et al., 2003). As a result, Siberia is very interesting for investigations of the autumn snow cover anomalies influence on the atmospheric dynamics in the following winter. This study is devoted to detection and estimation of described mechanism in INMCM4.0 and INMCM5.0 data. INMCM5.0 model represents further development of INMCM4.0 model (Volodin E.M. et al., 2010; Volodin E.M., 2014). They are different both from physical (various physical processes) and numerical (spatial resolution) points of view, thus giving different results representing various physical processes. An analysis of some parameters of atmospheric dynamics shows that top of atmosphere and vertical resolution set in INMCM models play important role in reproduction of influence of the Siberian autumn snow cover anomalies on the Northern Hemisphere atmospheric dynamics in the following winter. Acknowledgements Author acknowledges Dr. Volodin E.M. for providing INMCM data and valued advices. This work is partially supported by SB RAS project VIII.80.2.1, RFBR grant 13-05-12034, 13-05-00480, 14-05-00502 and grant of the President of the Russian Federation. References Allen R.J. and Zender C.S. Forcing of the Arctic Oscillation by Eurasian snow cover. // J. Climate. 2011. Volume 24. P. 6528-6539. Cohen J., Barlow M., Kushner P.J., Saito K. Stratosphere-troposphere coupling and links with Eurasian land-surface variability. // J. Climate. 2007. Volume 20. P. 5335-5343. Gong G., Entekhabi D., Cohen J. Modeled Northern Hemisphere winter climate response to realistic Siberian snow anomalies. // J. Climate, 2003. -- V. 16. -- P. 3917-3931. Martynova Yu.V. and Krupchatnikov V.N. A study of the sensitivity of the surface temperature in Eurasia in winter to snow-cover anomalies: The role of the stratosphere // Izvestiya, Atmospheric and Oceanic Physics. 2010. V 46, Issue 6, pp 757-769. Volodin E.M., Dianskii N.A., Gusev A.V. Simulating Present-Day Climate with the INMCM4.0 Coupled Model of the Atmospheric and Oceanic General Circulations // Izvestiya, Atmospheric and Oceanic Physics. 2010. V 46, No. 4, pp 414-431. Volodin E.M. Possible reasons for low climate-model sensitivity to increased carbon dioxide concentrations // Izvestiya, Atmospheric and Oceanic Physics. 2014. V 50, Issue 4 , pp 350-355.

A prototype for automation of land-cover products from Landsat Surface Reflectance Data Records

NASA Astrophysics Data System (ADS)

Rover, J.; Goldhaber, M. B.; Steinwand, D.; Nelson, K.; Coan, M.; Wylie, B. K.; Dahal, D.; Wika, S.; Quenzer, R.

2014-12-01

Landsat data records of surface reflectance provide a three-decade history of land surface processes. Due to the vast number of these archived records, development of innovative approaches for automated data mining and information retrieval were necessary. Recently, we created a prototype utilizing open source software libraries for automatically generating annual Anderson Level 1 land cover maps and information products from data acquired by the Landsat Mission for the years 1984 to 2013. The automated prototype was applied to two target areas in northwestern and east-central North Dakota, USA. The approach required the National Land Cover Database (NLCD) and two user-input target acquisition year-days. The Landsat archive was mined for scenes acquired within a 100-day window surrounding these target dates, and then cloud-free pixels where chosen closest to the specified target acquisition dates. The selected pixels were then composited before completing an unsupervised classification using the NLCD. Pixels unchanged in pairs of the NLCD were used for training decision tree models in an iterative process refined with model confidence measures. The decision tree models were applied to the Landsat composites to generate a yearly land cover map and related information products. Results for the target areas captured changes associated with the recent expansion of oil shale production and agriculture driven by economics and policy, such as the increase in biofuel production and reduction in Conservation Reserve Program. Changes in agriculture, grasslands, and surface water reflect the local hydrological conditions that occurred during the 29-year span. Future enhancements considered for this prototype include a web-based client, ancillary spatial datasets, trends and clustering algorithms, and the forecasting of future land cover.

Regional Climate Modeling over the Marmara Region, Turkey, with Improved Land Cover Data

NASA Astrophysics Data System (ADS)

Sertel, E.; Robock, A.

2007-12-01

Land surface controls the partitioning of available energy at the surface between sensible and latent heat,and controls partitioning of available water between evaporation and runoff. Current land cover data available within the regional climate models such as Regional Atmospheric Modeling System (RAMS), the Fifth-Generation NCAR/Penn State Mesoscale Model (MM5) and Weather Research and Forecasting (WRF) was obtained from 1- km Advanced Very High Resolution Radiometer satellite images spanning April 1992 through March 1993 with an unsupervised classification technique. These data are not up-to-date and are not accurate for all regions and some land cover types such as urban areas. Here we introduce new, up-to-date and accurate land cover data for the Marmara Region, Turkey derived from Landsat Enhanced Thematic Mapper images into the WRF regional climate model. We used several image processing techniques to create accurate land cover data from Landsat images obtained between 2001 and 2005. First, all images were atmospherically and radiometrically corrected to minimize contamination effects of atmospheric particles and systematic errors. Then, geometric correction was performed for each image to eliminate geometric distortions and define images in a common coordinate system. Finally, unsupervised and supervised classification techniques were utilized to form the most accurate land cover data yet for the study area. Accuracy assessments of the classifications were performed using error matrix and kappa statistics to find the best classification results. Maximum likelihood classification method gave the most accurate results over the study area. We compared the new land cover data with the default WRF land cover data. WRF land cover data cannot represent urban areas in the cities of Istanbul, Izmit, and Bursa. As an example, both original satellite images and new land cover data showed the expansion of urban areas into the Istanbul metropolitan area, but in the WRF land cover data only a limited area along the Bosporus is shown as urban. In addition, the new land cover data indicate that the northern part of Istanbul is covered by evergreen and deciduous forest (verified by ground truth data), but the WRF data indicate that most of this region is croplands. In the northern part of the Marmara Region, there is bare ground as a result of open mining activities and this class can be identified in our land cover data, whereas the WRF data indicated this region as woodland. We then used this new data set to conduct WRF simulations for one main and two nested domains, where the inner-most domain represents the Marmara Region with 3 km horizontal resolution. The vertical domain of both main and nested domains extends over 28 vertical levels. Initial and boundary conditions were obtained from National Centers for Environmental Prediction-Department of Energy Reanalysis II and the Noah model was selected as the land surface model. Two model simulations were conducted; one with available land cover data and one with the newly created land cover data. Using detailed meteorological station data within the study area, we find that the simulation with the new land cover data set produces better temperature and precipitation simulations for the region, showing the value of accurate land cover data and that changing land cover data can be an important influence on local climate change.

Understanding the Effect of Land Cover Classification on Model Estimates of Regional Carbon Cycling in the Boreal Forest Biome

NASA Technical Reports Server (NTRS)

Kimball, John; Kang, Sinkyu

2003-01-01

The original objectives of this proposed 3-year project were to: 1) quantify the respective contributions of land cover and disturbance (i.e., wild fire) to uncertainty associated with regional carbon source/sink estimates produced by a variety of boreal ecosystem models; 2) identify the model processes responsible for differences in simulated carbon source/sink patterns for the boreal forest; 3) validate model outputs using tower and field- based estimates of NEP and NPP; and 4) recommend/prioritize improvements to boreal ecosystem carbon models, which will better constrain regional source/sink estimates for atmospheric C02. These original objectives were subsequently distilled to fit within the constraints of a 1 -year study. This revised study involved a regional model intercomparison over the BOREAS study region involving Biome-BGC, and TEM (A.D. McGuire, UAF) ecosystem models. The major focus of these revised activities involved quantifying the sensitivity of regional model predictions associated with land cover classification uncertainties. We also evaluated the individual and combined effects of historical fire activity, historical atmospheric CO2 concentrations, and climate change on carbon and water flux simulations within the BOREAS study region.

Calibration and Validation of Tundra Plant Functional Type Fractional Cover Mapping

NASA Astrophysics Data System (ADS)

Macander, M. J.; Nelson, P.; Frost, G. V., Jr.

2017-12-01

Fractional cover maps are being developed for selected tundra plant functional types (PFTs) across >500,000 sq. km of arctic Alaska and adjacent Canada at 30 m resolution. Training and validation data include a field-based training dataset based on point-intercept sampling method at hundreds of plots spanning bioclimatic and geomorphic gradients. We also compiled 50 blocks of 1-5 cm resolution RGB image mosaics in Alaska (White Mountains, North Slope, and Yukon-Kuskokwim Delta) and the Yukon Territory. The mosaics and associated surface and canopy height models were developed using a consumer drone and structure from motion processing. We summarized both the in situ measurements and drone imagery to determine cover of two PFTs: Low and Tall Deciduous Shrub, and Light Fruticose/Foliose Lichen. We applied these data to train 2 m (limited extent) and 30 m (wall to wall) maps of PFT fractional cover for shrubs and lichen. Predictors for 2 m models were commercial satellite imagery such as WorldView-2 and Worldview-3, analyzed on the ABoVE Science Cloud. Predictors for 30 m models were primarily reflectance composites and spectral metrics developed from Landsat imagery, using Google Earth Engine. We compared the performance of models developed from the in situ and drone-derived training data and identify best practices to improve the performance and efficiency of arctic PFT fractional cover mapping.

A generic model for estimating biomass accumulation and greenhouse gas emissions from perennial crops

NASA Astrophysics Data System (ADS)

Ledo, Alicia; Heathcote, Richard; Hastings, Astley; Smith, Pete; Hillier, Jonathan

2017-04-01

Agriculture is essential to maintain humankind but is, at the same time, a substantial emitter of greenhouse gas (GHG) emissions. With a rising global population, the need for agriculture to provide secure food and energy supply is one of the main human challenges. At the same time, it is the only sector which has significant potential for negative emissions through the sequestration of carbon and offsetting via supply of feedstock for energy production. Perennial crops accumulate carbon during their lifetime and enhance organic soil carbon increase via root senescence and decomposition. However, inconsistency in accounting for this stored biomass undermines efforts to assess the benefits of such cropping systems when applied at scale. A consequence of this exclusion is that efforts to manage this important carbon stock are neglected. Detailed information on carbon balance is crucial to identify the main processes responsible for greenhouse gas emissions in order to develop strategic mitigation programs. Perennial crops systems represent 30% in area of total global crop systems, a considerable amount to be ignored. Furthermore, they have a major standing both in the bioenergy and global food industries. In this study, we first present a generic model to calculate the carbon balance and GHGs emissions from perennial crops, covering both food and bioenergy crops. The model is composed of two simple process-based sub-models, to cover perennial grasses and other perennial woody plants. The first is a generic individual based sub-model (IBM) covering crops in which the yield is the fruit and the plant biomass is an unharvested residue. Trees, shrubs and climbers fall into this category. The second model is a generic area based sub-model (ABM) covering perennial grasses, in which the harvested part includes some of the plant parts in which the carbon storage is accounted. Most second generation perennial bioenergy crops fall into this category. Both generic sub-models presented in this paper can be parametrized for different crops. Quantifying CO2 capture by plants and biomass accumulation and changes in soil carbon, are key in evaluating the impacts of perennial crops in life cycle analysis. We then use this model to illustrate the importance of biomass in the overall GHG estimation from four important perennial crops - sugarcane, Miscanthus, coffee, and apples - which were chosen to cover tropical and temperate regions, trees and grasses, and energy and food supply.

Climate Change for Agriculture, Forest Cover and 3d Urban Models

NASA Astrophysics Data System (ADS)

Kapoor, M.; Bassir, D.

2014-11-01

This research demonstrates the important role of the remote sensing in finding out the different parameters behind the agricultural crop change, forest cover and urban 3D models. Standalone software is developed to view and analysis the different factors effecting the change in crop productions. Open-source libraries from the Open Source Geospatial Foundation have been used for the development of the shape-file viewer. Software can be used to get the attribute information, scale, zoom in/out and pan the shapefiles. Environmental changes due to pollution and population that are increasing the urbanisation and decreasing the forest cover on the earth. Satellite imagery such as Landsat 5(1984) to Landsat TRIS/8 (2014), Landsat Data Continuity Mission (LDCM) and NDVI are used to analyse the different parameters that are effecting the agricultural crop production change and forest change. It is advisable for the development of good quality of NDVI and forest cover maps to use data collected from the same processing methods for the complete region. Management practices have been developed from the analysed data for the betterment of the crop and saving the forest cover

Chemometrics.

ERIC Educational Resources Information Center

Delaney, Michael F.

1984-01-01

This literature review on chemometrics (covering December 1981 to December 1983) is organized under these headings: personal supermicrocomputers; education and books; statistics; modeling and parameter estimation; resolution; calibration; signal processing; image analysis; factor analysis; pattern recognition; optimization; artificial…

Software Engineering Guidebook

NASA Technical Reports Server (NTRS)

Connell, John; Wenneson, Greg

1993-01-01

The Software Engineering Guidebook describes SEPG (Software Engineering Process Group) supported processes and techniques for engineering quality software in NASA environments. Three process models are supported: structured, object-oriented, and evolutionary rapid-prototyping. The guidebook covers software life-cycles, engineering, assurance, and configuration management. The guidebook is written for managers and engineers who manage, develop, enhance, and/or maintain software under the Computer Software Services Contract.

Land-use and land-cover scenarios and spatial modeling at the regional scale

USGS Publications Warehouse

Sohl, Terry L.; Sleeter, Benjamin M.

2012-01-01

Land-use and land-cover (LULC) change has altered a large part of the earth's surface. Scenarios of potential future LULC change are required in order to better manage potential impacts on biodiversity, carbon fluxes, climate change, hydrology, and many other ecological processes. The U.S. Geological Survey is analyzing potential future LULC change in the United States, using an approach based on scenario construction and spatially explicit modeling. Similar modeling techniques are being used to produce historical LULC maps from 1940 to present. With the combination of backcast and forecast LULC data, the USGS is providing consistent LULC data for historical, current, and future time frames to support a variety of research applications.

Cloud cover estimation optical package: New facility, algorithms and techniques

NASA Astrophysics Data System (ADS)

Krinitskiy, Mikhail

2017-02-01

Short- and long-wave radiation is an important component of surface heat budget over sea and land. For estimating them accurate observations of the cloud cover are needed. While massively observed visually, for building accurate parameterizations cloud cover needs also to be quantified using precise instrumental measurements. Major disadvantages of the most of existing cloud-cameras are associated with their complicated design and inaccuracy of post-processing algorithms which typically result in the uncertainties of 20% to 30% in the camera-based estimates of cloud cover. The accuracy of these types of algorithm in terms of true scoring compared to human-observed values is typically less than 10%. We developed new generation package for cloud cover estimating, which provides much more accurate results and also allows for measuring additional characteristics. New algorithm, namely SAIL GrIx, based on routine approach, also developed for this package. It uses the synthetic controlling index ("grayness rate index") which allows to suppress the background sunburn effect. This makes it possible to increase the reliability of the detection of the optically thin clouds. The accuracy of this algorithm in terms of true scoring became 30%. One more approach, namely SAIL GrIx ML, we have used to increase the cloud cover estimating accuracy is the algorithm that uses machine learning technique along with some other signal processing techniques. Sun disk condition appears to be a strong feature in this kind of models. Artificial Neural Networks type of model demonstrates the best quality. This model accuracy in terms of true scoring increases up to 95,5%. Application of a new algorithm lets us to modify the design of the optical sensing package and to avoid the use of the solar trackers. This made the design of the cloud camera much more compact. New cloud-camera has already been tested in several missions across Atlantic and Indian oceans on board of IORAS research vessels.

Pedagogical Interaction in High School, the Structural and Functional Model of Pedagogical Interaction

ERIC Educational Resources Information Center

Semenova, Larissa A.; Kazantseva, Anastassiya I.; Sergeyeva, Valeriya V.; Raklova, Yekaterina M.; Baiseitova, Zhanar B.

2016-01-01

The study covers the problems of pedagogical technologies and their experimental implementation in the learning process. The theoretical aspects of the "student-teacher" interaction are investigated. A structural and functional model of pedagogical interaction is offered, which determines the conditions for improving pedagogical…

Performance of complex snow cover descriptions in a distributed hydrological model system: A case study for the high Alpine terrain of the Berchtesgaden Alps.

PubMed

Warscher, M; Strasser, U; Kraller, G; Marke, T; Franz, H; Kunstmann, H

2013-05-01

[1] Runoff generation in Alpine regions is typically affected by snow processes. Snow accumulation, storage, redistribution, and ablation control the availability of water. In this study, several robust parameterizations describing snow processes in Alpine environments were implemented in a fully distributed, physically based hydrological model. Snow cover development is simulated using different methods from a simple temperature index approach, followed by an energy balance scheme, to additionally accounting for gravitational and wind-driven lateral snow redistribution. Test site for the study is the Berchtesgaden National Park (Bavarian Alps, Germany) which is characterized by extreme topography and climate conditions. The performance of the model system in reproducing snow cover dynamics and resulting discharge generation is analyzed and validated via measurements of snow water equivalent and snow depth, satellite-based remote sensing data, and runoff gauge data. Model efficiency (the Nash-Sutcliffe coefficient) for simulated runoff increases from 0.57 to 0.68 in a high Alpine headwater catchment and from 0.62 to 0.64 in total with increasing snow model complexity. In particular, the results show that the introduction of the energy balance scheme reproduces daily fluctuations in the snowmelt rates that trace down to the channel stream. These daily cycles measured in snowmelt and resulting runoff rates could not be reproduced by using the temperature index approach. In addition, accounting for lateral snow transport changes the seasonal distribution of modeled snowmelt amounts, which leads to a higher accuracy in modeling runoff characteristics.

Simulating vegetation cover dynamics with regards to long-term climatic variations in sub-arctic landscapes

NASA Astrophysics Data System (ADS)

Haraldsson, Hörður V.; Ólafsdóttir, Rannveig

2003-09-01

Iceland is facing severe land degradation in many parts of the country. This study aims to increase the understanding of the complex interactions and interconnectivity between the critical factors that help maintain the land degradation processes in sub-arctic environments. A holistic approach in the form of a causal loop diagram (CLD) is applied for diagnosing the influencing factors. To further study the relationship between vegetation cover and its degradation, a dynamic model that uses a long-term temperature data as the main indicator function is constructed to simulate potential vegetation cover during the Holocene. The results depict an oscillating vegetation cover. Gradual degradation in potential vegetation cover begins ca. 3000 BP and accelerates greatly after ca. 2500 BP. From the time of the Norse settlement in the latter halve of the 9th century to present time, the simulated vegetation cover retreats ca. 25% in relation to climatic cooling.

Business Process Reengineering in the Inventory Management to Improve Aircraft Maintenance Operations in the Indonesian Air Force

DTIC Science & Technology

2006-06-01

research will cover an overview of business process engineering (BPR) and operation management . The focus will be on the basic process of BPR, inventory...management and improvement of the process of business operation management to appropriately provide a basic model for the Indonesian Air Force in...discuss the operation management aspects of inventory management and process improvement, including Economic Order Quantity, Material Requirement

Generating land cover boundaries from remotely sensed data using object-based image analysis: overview and epidemiological application

PubMed Central

Maxwell, Susan K.

2010-01-01

Satellite imagery and aerial photography represent a vast resource to significantly enhance environmental mapping and modeling applications for use in understanding spatio-temporal relationships between environment and health. Deriving boundaries of land cover objects, such as trees, buildings, and crop fields, from image data has traditionally been performed manually using a very time consuming process of hand digitizing. Boundary detection algorithms are increasingly being applied using object-based image analysis (OBIA) technology to automate the process. The purpose of this paper is to present an overview and demonstrate the application of OBIA for delineating land cover features at multiple scales using a high resolution aerial photograph (1 m) and a medium resolution Landsat image (30 m) time series in the context of a pesticide spray drift exposure application. PMID:21135917

Integrating Land Cover Modeling and Adaptive Management to Conserve Endangered Species and Reduce Catastrophic Fire Risk

NASA Technical Reports Server (NTRS)

Breininger, David; Duncan, Brean; Eaton, Mitchell; Johnson, Fred; Nichols, James

2014-01-01

Land cover modeling is used to inform land management, but most often via a two-step process where science informs how management alternatives can influence resources and then decision makers can use this to make decisions. A more efficient process is to directly integrate science and decision making, where science allows us to learn to better accomplish management objectives and is developed to address specific decisions. Co-development of management and science is especially productive when decisions are complicated by multiple objectives and impeded by uncertainty. Multiple objectives can be met by specification of tradeoffs, and relevant uncertainty can be addressed through targeted science (i.e., models and monitoring). We describe how to integrate habitat and fuels monitoring with decision making focused on dual objectives of managing for endangered species and minimizing catastrophic fire risk. Under certain conditions, both objectives might be achieved by a similar management policy, but habitat trajectories suggest tradeoffs. Knowledge about system responses to actions can be informed by applying competing management actions to different land units in the same system state and by ideas about fire behavior. Monitoring and management integration is important to optimize state-specific management decisions and increase knowledge about system responses. We believe this approach has broad utility for and cover modeling programs intended to inform decision making.

MODSNOW-Tool: an operational tool for daily snow cover monitoring using MODIS data

NASA Astrophysics Data System (ADS)

Gafurov, Abror; Lüdtke, Stefan; Unger-Shayesteh, Katy; Vorogushyn, Sergiy; Schöne, Tilo; Schmidt, Sebastian; Kalashnikova, Olga; Merz, Bruno

2017-04-01

Spatially distributed snow cover information in mountain areas is extremely important for water storage estimations, seasonal water availability forecasting, or the assessment of snow-related hazards (e.g. enhanced snow-melt following intensive rains, or avalanche events). Moreover, spatially distributed snow cover information can be used to calibrate and/or validate hydrological models. We present the MODSNOW-Tool - an operational monitoring tool offers a user-friendly application which can be used for catchment-based operational snow cover monitoring. The application automatically downloads and processes freely available daily Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover data. The MODSNOW-Tool uses a step-wise approach for cloud removal and delivers cloud-free snow cover maps for the selected river basins including basin specific snow cover extent statistics. The accuracy of cloud-eliminated MODSNOW snow cover maps was validated for 84 almost cloud-free days in the Karadarya river basin in Central Asia, and an average accuracy of 94 % was achieved. The MODSNOW-Tool can be used in operational and non-operational mode. In the operational mode, the tool is set up as a scheduled task on a local computer allowing automatic execution without user interaction and delivers snow cover maps on a daily basis. In the non-operational mode, the tool can be used to process historical time series of snow cover maps. The MODSNOW-Tool is currently implemented and in use at the national hydrometeorological services of four Central Asian states - Kazakhstan, Kyrgyzstan, Uzbekistan and Turkmenistan and used for seasonal water availability forecast.

A program in global biology. [biota-environment interaction important to life

NASA Technical Reports Server (NTRS)

Mooneyhan, D. W.

1983-01-01

NASA's Global Biology Research Program and its goals for greater understanding of planetary biological processes are discussed. Consideration is given to assessing major pathways and rates of exchange of elements such as carbon and nitrogen, extrapolating local rates of anaerobic activities, determining exchange rates of ocean nutrients, and developing models for the global cycles of carbon, nitrogen, sulfur, and phosphorus. Satellites and sensors operating today are covered: the Nimbus, NOAA, and Landsat series. Block diagrams of the software and hardware for a typical ground data processing and analysis system are provided. Samples of the surface cover data achieved with the Advanced Very High Resolution Radiometer, the Multispectral Scanner, and the Thematic Mapper are presented, as well as a productive capacity model for coastal wetlands. Finally, attention is given to future goals, their engineering requirements, and the necessary data analysis system.

Dimensional comparability of psychosocial working conditions as covered in European monitoring questionnaires.

PubMed

Formazin, Maren; Burr, Hermann; Aagestad, Cecilie; Tynes, Tore; Thorsen, Sannie Vester; Perkio-Makela, Merja; Díaz Aramburu, Clara Isabel; Pinilla García, Francisco Javier; Galiana Blanco, Luz; Vermeylen, Greet; Parent-Thirion, Agnes; Hooftman, Wendela; Houtman, Irene

2014-12-09

In most countries in the EU, national surveys are used to monitor working conditions and health. Since the development processes behind the various surveys are not necessarily theoretical, but certainly practical and political, the extent of similarity among the dimensions covered in these surveys has been unclear. Another interesting question is whether prominent models from scientific research on work and health are present in the surveys--bearing in mind that the primary focus of these surveys is on monitoring status and trends, not on mapping scientific models. Moreover, it is relevant to know which other scales and concepts not stemming from these models have been included in the surveys. The purpose of this paper is to determine (1) the similarity of dimensions covered in the surveys included and (2) the congruence of dimensions of scientific research and of dimensions present in the monitoring systems. Items from surveys representing six European countries and one European wide survey were classified into the dimensions they cover, using a taxonomy agreed upon among all involved partners from the six countries. The classification reveals that there is a large overlap of dimensions, albeit not in the formulation of items, covered in the seven surveys. Among the available items, the two prominent work-stress-models--job-demand-control-support-model (DCS) and effort-reward-imbalance-model (ERI)--are covered in most surveys even though this has not been the primary aim in the compilation of these surveys. In addition, a large variety of items included in the surveillance systems are not part of these models and are--at least partly--used in nearly all surveys. These additional items reflect concepts such as "restructuring", "meaning of work", "emotional demands" and "offensive behaviour/violence & harassment". The overlap of the dimensions being covered in the various questionnaires indicates that the interests of the parties deciding on the questionnaires in the different countries overlap. The large number of dimensions measured in the questionnaires and not being part of the DCS and ERI models is striking. These "new" dimensions could inspire the research community to further investigate their possible health and labour market effects.

The Rangeland Hydrology and Erosion Model: A Dynamic Approach for Predicting Soil Loss on Rangelands

NASA Astrophysics Data System (ADS)

Hernandez, Mariano; Nearing, Mark A.; Al-Hamdan, Osama Z.; Pierson, Frederick B.; Armendariz, Gerardo; Weltz, Mark A.; Spaeth, Kenneth E.; Williams, C. Jason; Nouwakpo, Sayjro K.; Goodrich, David C.; Unkrich, Carl L.; Nichols, Mary H.; Holifield Collins, Chandra D.

2017-11-01

In this study, we present the improved Rangeland Hydrology and Erosion Model (RHEM V2.3), a process-based erosion prediction tool specific for rangeland application. The article provides the mathematical formulation of the model and parameter estimation equations. Model performance is assessed against data collected from 23 runoff and sediment events in a shrub-dominated semiarid watershed in Arizona, USA. To evaluate the model, two sets of primary model parameters were determined using the RHEM V2.3 and RHEM V1.0 parameter estimation equations. Testing of the parameters indicated that RHEM V2.3 parameter estimation equations provided a 76% improvement over RHEM V1.0 parameter estimation equations. Second, the RHEM V2.3 model was calibrated to measurements from the watershed. The parameters estimated by the new equations were within the lowest and highest values of the calibrated parameter set. These results suggest that the new parameter estimation equations can be applied for this environment to predict sediment yield at the hillslope scale. Furthermore, we also applied the RHEM V2.3 to demonstrate the response of the model as a function of foliar cover and ground cover for 124 data points across Arizona and New Mexico. The dependence of average sediment yield on surface ground cover was moderately stronger than that on foliar cover. These results demonstrate that RHEM V2.3 predicts runoff volume, peak runoff, and sediment yield with sufficient accuracy for broad application to assess and manage rangeland systems.

Land Use Change on Household Farms in the Ecuadorian Amazon: Design and Implementation of an Agent-Based Model

PubMed Central

Mena, Carlos F.; Walsh, Stephen J.; Frizzelle, Brian G.; Xiaozheng, Yao; Malanson, George P.

2010-01-01

This paper describes the design and implementation of an Agent-Based Model (ABM) used to simulate land use change on household farms in the Northern Ecuadorian Amazon (NEA). The ABM simulates decision-making processes at the household level that is examined through a longitudinal, socio-economic and demographic survey that was conducted in 1990 and 1999. Geographic Information Systems (GIS) are used to establish spatial relationships between farms and their environment, while classified Landsat Thematic Mapper (TM) imagery is used to set initial land use/land cover conditions for the spatial simulation, assess from-to land use/land cover change patterns, and describe trajectories of land use change at the farm and landscape levels. Results from prior studies in the NEA provide insights into the key social and ecological variables, describe human behavioral functions, and examine population-environment interactions that are linked to deforestation and agricultural extensification, population migration, and demographic change. Within the architecture of the model, agents are classified as active or passive. The model comprises four modules, i.e., initialization, demography, agriculture, and migration that operate individually, but are linked through key household processes. The main outputs of the model include a spatially-explicit representation of the land use/land cover on survey and non-survey farms and at the landscape level for each annual time-step, as well as simulated socio-economic and demographic characteristics of households and communities. The work describes the design and implementation of the model and how population-environment interactions can be addressed in a frontier setting. The paper contributes to land change science by examining important pattern-process relations, advocating a spatial modeling approach that is capable of synthesizing fundamental relationships at the farm level, and links people and environment in complex ways. PMID:24436501

Modelling the influence of elevation and snow regime on winter stream temperature in the rain-on-snow zone

NASA Astrophysics Data System (ADS)

Leach, J.; Moore, D.

2015-12-01

Winter stream temperature of coastal mountain catchments influences fish growth and development. Transient snow cover and advection associated with lateral throughflow inputs are dominant controls on stream thermal regimes in these regions. Existing stream temperature models lack the ability to properly simulate these processes. Therefore, we developed and evaluated a conceptual-parametric catchment-scale stream temperature model that includes the role of transient snow cover and lateral advection associated with throughflow. The model provided reasonable estimates of observed stream temperature at three test catchments. We used the model to simulate winter stream temperature for virtual catchments located at different elevations within the rain-on-snow zone. The modelling exercise examined stream temperature response associated with interactions between elevation, snow regime, and changes in air temperature. Modelling results highlight that the sensitivity of winter stream temperature response to changes in climate may be dependent on catchment elevation and landscape position.

A large-scale integrated karst-vegetation recharge model to understand the impact of climate and land cover change

NASA Astrophysics Data System (ADS)

Sarrazin, Fanny; Hartmann, Andreas; Pianosi, Francesca; Wagener, Thorsten

2017-04-01

Karst aquifers are an important source of drinking water in many regions of the world, but their resources are likely to be affected by changes in climate and land cover. Karst areas are highly permeable and produce large amounts of groundwater recharge, while surface runoff is typically negligible. As a result, recharge in karst systems may be particularly sensitive to environmental changes compared to other less permeable systems. However, current large-scale hydrological models poorly represent karst specificities. They tend to provide an erroneous water balance and to underestimate groundwater recharge over karst areas. A better understanding of karst hydrology and estimating karst groundwater resources at a large-scale is therefore needed for guiding water management in a changing world. The first objective of the present study is to introduce explicit vegetation processes into a previously developed karst recharge model (VarKarst) to better estimate evapotranspiration losses depending on the land cover characteristics. The novelty of the approach for large-scale modelling lies in the assessment of model output uncertainty, and parameter sensitivity to avoid over-parameterisation. We find that the model so modified is able to produce simulations consistent with observations of evapotranspiration and soil moisture at Fluxnet sites located in carbonate rock areas. Secondly, we aim to determine the model sensitivities to climate and land cover characteristics, and to assess the relative influence of changes in climate and land cover on aquifer recharge. We perform virtual experiments using synthetic climate inputs, and varying the value of land cover parameters. In this way, we can control for variations in climate input characteristics (e.g. precipitation intensity, precipitation frequency) and vegetation characteristics (e.g. canopy water storage capacity, rooting depth), and we can isolate the effect that each of these quantities has on recharge. Our results show that these factors are strongly interacting and are generating non-linear responses in recharge.

Applicability of mathematical modeling to problems of environmental physiology

NASA Technical Reports Server (NTRS)

White, Ronald J.; Lujan, Barbara F.; Leonard, Joel I.; Srinivasan, R. Srini

1988-01-01

The paper traces the evolution of mathematical modeling and systems analysis from terrestrial research to research related to space biomedicine and back again to terrestrial research. Topics covered include: power spectral analysis of physiological signals; pattern recognition models for detection of disease processes; and, computer-aided diagnosis programs used in conjunction with a special on-line biomedical computer library.

[Land use and land cover charnge (LUCC) and landscape service: Evaluation, mapping and modeling].

PubMed

Song, Zhang-jian; Cao, Yu; Tan, Yong-zhong; Chen, Xiao-dong; Chen, Xian-peng

2015-05-01

Studies on ecosystem service from landscape scale aspect have received increasing attention from researchers all over the world. Compared with ecosystem scale, it should be more suitable to explore the influence of human activities on land use and land cover change (LUCC), and to interpret the mechanisms and processes of sustainable landscape dynamics on landscape scale. Based on comprehensive and systematic analysis of researches on landscape service, this paper firstly discussed basic concepts and classification of landscape service. Then, methods of evaluation, mapping and modeling of landscape service were analyzed and concluded. Finally, future trends for the research on landscape service were proposed. It was put forward that, exploring further connotation and classification system of landscape service, improving methods and quantitative indicators for evaluation, mapping and modelling of landscape service, carrying out long-term integrated researches on landscape pattern-process-service-scale relationships and enhancing the applications of theories and methods on landscape economics and landscape ecology are very important fields of the research on landscape service in future.

Assessing, understanding, and conveying the state of the Arctic sea ice cover

NASA Astrophysics Data System (ADS)

Perovich, D. K.; Richter-Menge, J. A.; Rigor, I.; Parkinson, C. L.; Weatherly, J. W.; Nghiem, S. V.; Proshutinsky, A.; Overland, J. E.

2003-12-01

Recent studies indicate that the Arctic sea ice cover is undergoing significant climate-induced changes, affecting both its extent and thickness. Satellite-derived estimates of Arctic sea ice extent suggest a reduction of about 3% per decade since 1978. Ice thickness data from submarines suggest a net thinning of the sea ice cover since 1958. Changes (including oscillatory changes) in atmospheric circulation and the thermohaline properties of the upper ocean have also been observed. These changes impact not only the Arctic, but the global climate system and are likely accelerated by such processes as the ice-albedo feedback. It is important to continue and expand long-term observations of these changes to (a) improve the fundamental understanding of the role of the sea ice cover in the global climate system and (b) use the changes in the sea ice cover as an early indicator of climate change. This is a formidable task that spans a range of temporal and spatial scales. Fortunately, there are numerous tools that can be brought to bear on this task, including satellite remote sensing, autonomous buoys, ocean moorings, field campaigns and numerical models. We suggest the integrated and coordinated use of these tools during the International Polar Year to monitor the state of the Arctic sea ice cover and investigate its governing processes. For example, satellite remote sensing provides the large-scale snapshots of such basic parameters as ice distribution, melt zone, and cloud fraction at intervals of half a day to a week. Buoys and moorings can contribute high temporal resolution and can measure parameters currently unavailable from space including ice thickness, internal ice temperature, and ocean temperature and salinity. Field campaigns can be used to explore, in detail, the processes that govern the ice cover. Numerical models can be used to assess the character of the changes in the ice cover and predict their impacts on the rest of the climate system. This work affords extraordinary opportunities for outreach activities, because of the public interest in both the Arctic and climate change. Data can be streamed to public web sites in near real time, as can photographs and commentaries from field camps. The breadth of activities affords considerable opportunities to engage the next generation of researchers in such diverse fields as computer science, engineering, and geophysics.

Modeling and Analysis of Power Processing Systems (MAPPS). Volume 1: Technical report

NASA Technical Reports Server (NTRS)

Lee, F. C.; Rahman, S.; Carter, R. A.; Wu, C. H.; Yu, Y.; Chang, R.

1980-01-01

Computer aided design and analysis techniques were applied to power processing equipment. Topics covered include: (1) discrete time domain analysis of switching regulators for performance analysis; (2) design optimization of power converters using augmented Lagrangian penalty function technique; (3) investigation of current-injected multiloop controlled switching regulators; and (4) application of optimization for Navy VSTOL energy power system. The generation of the mathematical models and the development and application of computer aided design techniques to solve the different mathematical models are discussed. Recommendations are made for future work that would enhance the application of the computer aided design techniques for power processing systems.

Sensitivity study of a dynamic thermodynamic sea ice model

NASA Astrophysics Data System (ADS)

Holland, David M.; Mysak, Lawrence A.; Manak, Davinder K.; Oberhuber, Josef M.

1993-02-01

A numerical simulation of the seasonal sea ice cover in the Arctic Ocean and the Greenland, Iceland, and Norwegian seas is presented. The sea ice model is extracted from Oberhuber's (1990) coupled sea ice-mixed layer-isopycnal general circulation model and is written in spherical coordinates. The advantage of such a model over previous sea ice models is that it can be easily coupled to either global atmospheric or ocean general circulation models written in spherical coordinates. In this model, the thermodynamics are a modification of that of Parkinson and Washington (1979), while the dynamics use the full Hibler (1979) viscous-plastic rheology. Monthly thermodynamic and dynamic forcing fields for the atmosphere and ocean are specified. The simulations of the seasonal cycle of ice thickness, compactness, and velocity, for a control set of parameters, compare favorably with the known seasonal characteristics of these fields. A sensitivity study of the control simulation of the seasonal sea ice cover is presented. The sensitivity runs are carried out under three different themes, namely, numerical conditions, parameter values, and physical processes. This last theme refers to experiments in which physical processes are either newly added or completely removed from the model. Approximately 80 sensitivity runs have been performed in which a change from the control run environment has been implemented. Comparisons have been made between the control run and a particular sensitivity run based on time series of the seasonal cycle of the domain-averaged ice thickness, compactness, areal coverage, and kinetic energy. In addition, spatially varying fields of ice thickness, compactness, velocity, and surface temperature for each season are presented for selected experiments. A brief description and discussion of the more interesting experiments are presented. The simulation of the seasonal cycle of Arctic sea ice cover is shown to be robust.

Using a basin-scale hydrological model to estimate crop transpiration and soil evaporation

NASA Astrophysics Data System (ADS)

Kite, G.

2000-03-01

Increasing populations and expectations, declining crop yields and the resulting increased competition for water necesitate improvements in irrigation management and productivity. A key factor in defining agricultural productivity is to be able to simulate soil evaporation and crop transpiration. In agribusiness terms, crop transpiration is a useful process while soil and open-water evaporations are wasteful processes. In this study a distributed hydrological model was used to compute daily evaporation and transpiration for a variety of crops and other land covers within the 17,200 km 2 Gediz Basin in western Turkey. The model, SLURP, describes the complete hydrological cycle for each land cover within a series of sub-basins including all dams, reservoirs, regulators and irrigation schemes in the basin. The sub-basins and land covers are defined by analysing a digital elevation model and NOAA AVHRR satellite data. In this study, the model uses the FAO implementation of the Penman-Monteith equation to simulate soil evaporation and crop transpiration. The results of the model runs provide time series of data on streamflow at many points along the river system, abstractions and return flows from crops within the irrigation schemes and areally distributed soil evaporation and crop transpiration across the entire basin on each day of an 11 year period. The results show that evaporation and transpiration vary widely across the basin on any one day and over the irrigation season and can be used to evaluate the effectiveness of the various irrigation strategies used in the basin. The advantages of using such a model as compared to deriving evapotranspiration from satellite data are that the model obtains results for each day of an indefinitely long period, as opposed to occasional snapshots, and can also be used to simulate alternate scenarios.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Knudsen, J.K.; Smith, C.L.

The steps involved to incorporate parameter uncertainty into the Nuclear Regulatory Commission (NRC) accident sequence precursor (ASP) models is covered in this paper. Three different uncertainty distributions (i.e., lognormal, beta, gamma) were evaluated to Determine the most appropriate distribution. From the evaluation, it was Determined that the lognormal distribution will be used for the ASP models uncertainty parameters. Selection of the uncertainty parameters for the basic events is also discussed. This paper covers the process of determining uncertainty parameters for the supercomponent basic events (i.e., basic events that are comprised of more than one component which can have more thanmore » one failure mode) that are utilized in the ASP models. Once this is completed, the ASP model is ready to be utilized to propagate parameter uncertainty for event assessments.« less

Land Cover Applications, Landscape Dynamics, and Global Change

USGS Publications Warehouse

Tieszen, Larry L.

2007-01-01

The Land Cover Applications, Landscape Dynamics, and Global Change project at U.S. Geological Survey (USGS) Center for Earth Resources Observation and Science (EROS) seeks to integrate remote sensing and simulation models to better understand and seek solutions to national and global issues. Modeling processes related to population impacts, natural resource management, climate change, invasive species, land use changes, energy development, and climate mitigation all pose significant scientific opportunities. The project activities use remotely sensed data to support spatial monitoring, provide sensitivity analyses across landscapes and large regions, and make the data and results available on the Internet with data access and distribution, decision support systems, and on-line modeling. Applications support sustainable natural resource use, carbon cycle science, biodiversity conservation, climate change mitigation, and robust simulation modeling approaches that evaluate ecosystem and landscape dynamics.

A web-based land cover classification system based on ontology model of different classification systems

NASA Astrophysics Data System (ADS)

Lin, Y.; Chen, X.

2016-12-01

Land cover classification systems used in remote sensing image data have been developed to meet the needs for depicting land covers in scientific investigations and policy decisions. However, accuracy assessments of a spate of data sets demonstrate that compared with the real physiognomy, each of the thematic map of specific land cover classification system contains some unavoidable flaws and unintended deviation. This work proposes a web-based land cover classification system, an integrated prototype, based on an ontology model of various classification systems, each of which is assigned the same weight in the final determination of land cover type. Ontology, a formal explication of specific concepts and relations, is employed in this prototype to build up the connections among different systems to resolve the naming conflicts. The process is initialized by measuring semantic similarity between terminologies in the systems and the search key to produce certain set of satisfied classifications, and carries on through searching the predefined relations in concepts of all classification systems to generate classification maps with user-specified land cover type highlighted, based on probability calculated by votes from data sets with different classification system adopted. The present system is verified and validated by comparing the classification results with those most common systems. Due to full consideration and meaningful expression of each classification system using ontology and the convenience that the web brings with itself, this system, as a preliminary model, proposes a flexible and extensible architecture for classification system integration and data fusion, thereby providing a strong foundation for the future work.

Multidecadal Rates of Disturbance- and Climate Change-Induced Land Cover Change in Arctic and Boreal Ecosystems over Western Canada and Alaska Inferred from Dense Landsat Time Series

NASA Astrophysics Data System (ADS)

Wang, J.; Sulla-menashe, D. J.; Woodcock, C. E.; Sonnentag, O.; Friedl, M. A.

2017-12-01

Rapid climate change in arctic and boreal ecosystems is driving changes to land cover composition, including woody expansion in the arctic tundra, successional shifts following boreal fires, and thaw-induced wetland expansion and forest collapse along the southern limit of permafrost. The impacts of these land cover transformations on the physical climate and the carbon cycle are increasingly well-documented from field and model studies, but there have been few attempts to empirically estimate rates of land cover change at decadal time scale and continental spatial scale. Previous studies have used too coarse spatial resolution or have been too limited in temporal range to enable broad multi-decadal assessment of land cover change. As part of NASA's Arctic Boreal Vulnerability Experiment (ABoVE), we are using dense time series of Landsat remote sensing data to map disturbances and classify land cover types across the ABoVE extended domain (spanning western Canada and Alaska) over the last three decades (1982-2014) at 30 m resolution. We utilize regionally-complete and repeated acquisition high-resolution (<2 m) DigitalGlobe imagery to generate training data from across the region that follows a nested, hierarchical classification scheme encompassing plant functional type and cover density, understory type, wetland status, and land use. Additionally, we crosswalk plot-level field data into our scheme for additional high quality training sites. We use the Continuous Change Detection and Classification algorithm to estimate land cover change dates and temporal-spectral features in the Landsat data. These features are used to train random forest classification models and map land cover and analyze land cover change processes, focusing primarily on tundra "shrubification", post-fire succession, and boreal wetland expansion. We will analyze the high resolution data based on stratified random sampling of our change maps to validate and assess the accuracy of our model predictions. In this paper, we present initial results from this effort, including sub-regional analyses focused on several key areas, such as the Taiga Plains and the Southern Arctic ecozones, to calibrate our random forest models and assess results.

Hydrologic models for land-atmosphere retrospective studies of the use of LANDSAT and AVHRR data

NASA Technical Reports Server (NTRS)

Duchon, Claude E.; Williams, T. H. Lee; Nicks, Arlin D.

1988-01-01

The use of a Geographic Information System (GIS) and LANDSAT analysis in conjunction with the Simulator for Water Resources on a Rural Basin (SWRRB) hydrologic model to examine the water balance on the Little Washita River basin is discussed. LANDSAT analysis was used to divide the basin into eight non-contiguous land covers or subareas: rangeland, grazed range, winter wheat, alfalfa/pasture, bare soil, water, woodland, and impervious land (roads, quarry). The use of a geographic information system allowed for the calculation of SWRRB model parameters in each subarea. Four data sets were constructed in order to compare SWRRB estimates of hydrologic processes using two methods of maximum LAI and two methods of watershed subdivision. Maximum LAI was determined from a continental scale map, which provided a value of 4.5 for the entire basin, and from its association with the type of land-cover (eight values). The two methods of watershed subdivision were determined according to drainage subbasin (four) and the eight land-covers. These data sets were used with the SWRRB model to obtain daily hydrologic estimates for 1985. The results of the one year analysis lead to the conclusion that the greater homogeneity of a land-cover subdivision provides better water yield estimates than those based on a drainage properties subdivision.

Comparative Synthesis of Current and Future Urban Stormwater Runoff Scenarios in Tampa Bay Basin under a Changing Climate

NASA Astrophysics Data System (ADS)

Khan, M.; Abdul-Aziz, O. I.

2016-12-01

Changes in climatic regimes and basin characteristics such as imperviousness, roughness and land use types would lead to potential changes in stormwater budget. In this study we quantified reference sensitivities of stormwater runoff to the potential climatic and land use/cover changes by developing a large-scale, mechanistic rainfall-runoff model for the Tampa Bay Basin of Florida using the US EPA Storm Water Management Model (SWMM 5.1). Key processes of urban hydrology, its dynamic interactions with groundwater and sea level, hydro-climatic variables and land use/cover characteristics were incorporated within the model. The model was calibrated and validated with historical streamflow data. We then computed the historical (1970-2000) and potential 2050s stormwater budgets for the Tampa Bay Basin. Climatic scenario projected by the global climate models (GCMs) and the regional climate models (RCMs), along with sea level and land use/cover projections, were utilized to anticipate the future stormwater budget. The comparative assessment of current and future stormwater scenario will aid a proactive management of stormwater runoff under a changing climate in the Tampa Bay Basin and similar urban basins around the world.

Sensitivity of single column model simulations of Arctic springtime clouds to different cloud cover and mixed phase cloud parameterizations

NASA Astrophysics Data System (ADS)

Zhang, Junhua; Lohmann, Ulrike

2003-08-01

The single column model of the Canadian Centre for Climate Modeling and Analysis (CCCma) climate model is used to simulate Arctic spring cloud properties observed during the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment. The model is driven by the rawinsonde observations constrained European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis data. Five cloud parameterizations, including three statistical and two explicit schemes, are compared and the sensitivity to mixed phase cloud parameterizations is studied. Using the original mixed phase cloud parameterization of the model, the statistical cloud schemes produce more cloud cover, cloud water, and precipitation than the explicit schemes and in general agree better with observations. The mixed phase cloud parameterization from ECMWF decreases the initial saturation specific humidity threshold of cloud formation. This improves the simulated cloud cover in the explicit schemes and reduces the difference between the different cloud schemes. On the other hand, because the ECMWF mixed phase cloud scheme does not consider the Bergeron-Findeisen process, less ice crystals are formed. This leads to a higher liquid water path and less precipitation than what was observed.

Applications of Location Similarity Measures and Conceptual Spaces to Event Coreference and Classification

ERIC Educational Resources Information Center

McConky, Katie Theresa

2013-01-01

This work covers topics in event coreference and event classification from spoken conversation. Event coreference is the process of identifying descriptions of the same event across sentences, documents, or structured databases. Existing event coreference work focuses on sentence similarity models or feature based similarity models requiring slot…

REMOTE SENSING AND SPATIALLY EXPLICIT LANDSCAPE-BASED NITROGEN MODELING METHODS DEVELOPMENT IN THE NEUSE RIVER BASIN, NC

EPA Science Inventory

The objective of this research was to model and map the spatial patterns of excess nitrogen (N) sources across the landscape within the Neuse River Basin (NRB) of North
Carolina. The process included an initial land cover characterization effort to map landscape "patches" at ...

Secondary emission from dust grains: Comparison of experimental and model results

NASA Astrophysics Data System (ADS)

Richterova, I.; Pavlu, J.; Nemecek, Z.; Safrankova, J.; Zilavy, P.

The motion, coalescence, and other processes in dust clouds are determined by the dust charge. Since dust grains in the space are bombarded by energetic electrons, the secondary emission is an important process contributing to their charge. It is generally expected that the secondary emission yield is related to surface properties of the bombarded body. However, it is well known that secondary emission from small bodies is determined not only by their composition but an effect of dimension can be very important when the penetration depth of primary electrons is comparable with the grain size. It implies that the secondary emission yield can be influenced by the substrate material if the surface layer is thin enough. We have developed a simple Monte Carlo model of secondary emission that was successfully applied on the dust simulants from glass and melanine formaldehyd (MF) resin and matched very well experimental results. In order to check the influence of surface layers, we have modified the model for spheres covered by a layer with different material properties. The results of model simulations are compared with measurements on MF spheres covered by different metals.

Evaluating differences in forest fragmentation and restoration between western natural forests and southeastern plantation forests in the United States.

PubMed

Ren, Xinyu; Lv, Yingying; Li, Mingshi

2017-03-01

Changes in forest ecosystem structure and functions are considered some of the research issues in landscape ecology. In this study, advancing Forman's theory, we considered five spatially explicit processes associated with fragmentation, including perforation, dissection, subdivision, shrinkage, and attrition, and two processes associated with restoration, i.e., increment and expansion processes. Following this theory, a forest fragmentation and restoration process model that can detect the spatially explicit processes and ecological consequences of forest landscape change was developed and tested in the current analysis. Using the National Land Cover Databases (2001, 2006 and 2011), the forest fragmentation and restoration process model was applied to US western natural forests and southeastern plantation forests to quantify and classify forest patch losses into one of the four fragmentation processes (the dissection process was merged into the subdivision process) and to classify the newly gained forest patches based on the two restoration processes. At the same time, the spatio-temporal differences in fragmentation and restoration patterns and trends between natural forests and plantations were further compared. Then, through overlaying the forest fragmentation/restoration processes maps with targeting year land cover data and land ownership vectors, the results from forest fragmentation and the contributors to forest restoration in federal and nonfederal lands were identified. Results showed that, in natural forests, the forest change patches concentrated around the urban/forest, cultivated/forest, and shrubland/forest interfaces, while the patterns of plantation change patches were scattered sparsely and irregularly. The shrinkage process was the most common type in forest fragmentation, and the average size was the smallest. Expansion, the most common restoration process, was observed in both natural forests and plantations and often occurred around the previous expansion or covered the previous subdivision or shrinkage processes. The overall temporal fragmentation pattern of natural forests had a "perforation-subdivision/shrinkage-attrition" pathway, which corresponded to Forman's landscape fragmentation rule, while the plantation forests did not follow the rule strictly. The main land cover types resulted from forest fragmentation in natural forests and plantation forests were shrubland and herbaceous, mainly through subdivision and shrinkages process. The processes and effects of restoration of plantation forests were more diverse and efficient, compared to the natural forest, which were simpler with a lower regrowth rate. The fragmentation mostly occurred in nonfederal lands. In natural forests, forest fragmentation pattern differed in different land tenures, yet plantations remained the same in federal and nonfederal lands. Copyright © 2016 Elsevier Ltd. All rights reserved.

Multisensor earth observations to characterize wetlands and malaria epidemiology in Ethiopia

NASA Astrophysics Data System (ADS)

Midekisa, Alemayehu; Senay, Gabriel B.; Wimberly, Michael C.

2014-11-01

Malaria is a major global public health problem, particularly in Sub-Saharan Africa. The spatial heterogeneity of malaria can be affected by factors such as hydrological processes, physiography, and land cover patterns. Tropical wetlands, for example, are important hydrological features that can serve as mosquito breeding habitats. Mapping and monitoring of wetlands using satellite remote sensing can thus help to target interventions aimed at reducing malaria transmission. The objective of this study was to map wetlands and other major land cover types in the Amhara region of Ethiopia and to analyze district-level associations of malaria and wetlands across the region. We evaluated three random forests classification models using remotely sensed topographic and spectral data based on Shuttle Radar Topographic Mission (SRTM) and Landsat TM/ETM+ imagery, respectively. The model that integrated data from both sensors yielded more accurate land cover classification than single-sensor models. The resulting map of wetlands and other major land cover classes had an overall accuracy of 93.5%. Topographic indices and subpixel level fractional cover indices contributed most strongly to the land cover classification. Further, we found strong spatial associations of percent area of wetlands with malaria cases at the district level across the dry, wet, and fall seasons. Overall, our study provided the most extensive map of wetlands for the Amhara region and documented spatiotemporal associations of wetlands and malaria risk at a broad regional level. These findings can assist public health personnel in developing strategies to effectively control and eliminate malaria in the region.

Multisensor earth observations to characterize wetlands and malaria epidemiology in Ethiopia

USGS Publications Warehouse

Midekisa, Alemayehu; Senay, Gabriel; Wimberly, Michael C.

2014-01-01

Malaria is a major global public health problem, particularly in Sub-Saharan Africa. The spatial heterogeneity of malaria can be affected by factors such as hydrological processes, physiography, and land cover patterns. Tropical wetlands, for example, are important hydrological features that can serve as mosquito breeding habitats. Mapping and monitoring of wetlands using satellite remote sensing can thus help to target interventions aimed at reducing malaria transmission. The objective of this study was to map wetlands and other major land cover types in the Amhara region of Ethiopia and to analyze district-level associations of malaria and wetlands across the region. We evaluated three random forests classification models using remotely sensed topographic and spectral data based on Shuttle Radar Topographic Mission (SRTM) and Landsat TM/ETM+ imagery, respectively. The model that integrated data from both sensors yielded more accurate land cover classification than single-sensor models. The resulting map of wetlands and other major land cover classes had an overall accuracy of 93.5%. Topographic indices and subpixel level fractional cover indices contributed most strongly to the land cover classification. Further, we found strong spatial associations of percent area of wetlands with malaria cases at the district level across the dry, wet, and fall seasons. Overall, our study provided the most extensive map of wetlands for the Amhara region and documented spatiotemporal associations of wetlands and malaria risk at a broad regional level. These findings can assist public health personnel in developing strategies to effectively control and eliminate malaria in the region.

Potential of remotely-sensed data for mapping sediment connectivity pathways and their seasonal changes in dryland environments

NASA Astrophysics Data System (ADS)

Foerster, Saskia; Wilczok, Charlotte; Brosinsky, Arlena; Kroll, Anja; Segl, Karl; Francke, Till

2014-05-01

Many drylands are characterized by strong erosion in headwater catchments, where connectivity processes play an important role in the redistribution of water and sediments. Sediment connectivity relates to the physical transfer of sediment through a drainage basin (Bracken and Croke 2007). The identification of sediment source areas and the way they connect to the channel network are essential to environmental management (Reid et al. 2007), especially where high erosion and sediment delivery rates occur. Vegetation cover and its spatial and temporal pattern is one of the main factors affecting sediment connectivity. This is particularly true for patchy vegetation covers typical for dryland environments. While many connectivity studies are based on field-derived data, the potential of remotely-sensed data for sediment connectivity analyses has not yet been fully exploited. Recent advances in remote sensing allow for quantitative, spatially explicit, catchment-wide derivation of surface information to be used in connectivity analyses. These advances include a continuous increase in spatial image resolution to comprise processes at the plot to hillslope to catchment scale, an increase in the temporal resolution to cover seasonal and long-term changes and an increase in the spectral resolution enabling the discrimination of dry and green vegetation fractions from soil surfaces in heterogeneous dryland landscapes. The utilization of remotely-sensed data for connectivity studies raises questions on what type of information is required, how scale of sediment flux and image resolution match, how the connectivity information can be incorporated into water and sediment transport models and how this improves model predictions. The objective of this study is to demonstrate the potential of remotely-sensed data for mapping sediment connectivity pathways and their seasonal change at the example of a mesoscale dryland catchment in the Spanish Pyrenees. Here, sediment connectivity pathways have been mapped for two adjacent sub-catchments (approx. 70 km²) of the Isábena River in different seasons using a quantitative connectivity index based on fractional vegetation cover and topography data. Fractional cover of green and dry vegetation, bare soil and rock were derived by applying a Multiple Endmember Spectral Mixture Analysis approach applied to a hyperspectral image dataset. Sediment connectivity was mapped using the Index of Connectivity (Borselli et al. 2008), in which the effect of land cover on runoff and sediment fluxes is expressed by a spatially distributed weighing factor (in this study, the cover and management factor of the RUSLE). The resulting connectivity maps show that areas behave very differently with regard to connectivity, depending on the land cover but also on the spatial distribution of vegetation abundances and topographic barriers. Most parts of the catchment show higher connectivity values in summer than in spring. The studied sub-catchments show a slightly different connectivity behaviour reflecting the different land cover proportions and their spatial configuration. Future work includes the incorporation of sediment connectivity information into a hydrological model (WASA-SED, Mueller et al. 2010) to better reflect connectivity processes and testing the sensitivity of the model to different input data.

Refreezing on the Greenland ice sheet: a model comparison

NASA Astrophysics Data System (ADS)

Steger, Christian; Reijmer, Carleen; van den Broeke, Michiel; Ligtenberg, Stefan; Kuipers Munneke, Peter; Noël, Brice

2016-04-01

Mass loss of the Greenland ice sheet (GrIS) is an important contributor to global sea level rise. Besides calving, surface melt is the dominant source of mass loss. However, only part of the surface melt leaves the ice sheet as runoff whereas the other part percolates into the snow cover and refreezes. Due to this process, part of the meltwater is (intermediately) stored. Refreezing thus impacts the surface mass balance of the ice sheet but it also affects the vertical structure of the snow cover due to transport of mass and energy. Due to the sparse availability of in situ data and the demand of future projections, it is inevitable to use numerical models to simulate refreezing and related processes. Currently, the magnitude of refrozen mass is neither well constrained nor well validated. In this study, we model the snow and firn layer, and compare refreezing on the GrIS as modelled with two different numerical models. Both models are forced with meteorological data from the regional climate model RACMO 2 that has been shown to simulate realistic conditions for Greenland. One model is the UU/IMAU firn densification model (FDM) that can be used both in an on- and offline mode with RACMO 2. The other model is SNOWPACK; a model originally designed to simulate seasonal snow cover in alpine conditions. In contrast to FDM, SNOWPACK accounts for snow metamorphism and microstructure and contains a more physically based snow densification scheme. A first comparison of the models indicates that both seem to be able to capture the general spatial and temporal pattern of refreezing. Spatially, refreezing occurs mostly in the ablation zone and decreases in the accumulation zone towards the interior of the ice sheet. Below the equilibrium line altitude (ELA) where refreezing occurs in seasonal snow cover on bare ice, the storage effect is only intermediate. Temporal patterns on a seasonal range indicate two peaks in refreezing; one at the beginning of the melt season where water infiltrates the cold snow pack and one in early winter where the penetration of the cold surface temperature refreezes the retained liquid water. However, the model comparison reveals differences especially close to the equilibrium line where refreezing and runoff seem to be highly sensitive to the exact model formulation and fresh snow density initialization. Furthermore, SNOWPACK's densification scheme generally underestimates densification rates in case of high overburden pressure.

A Multitemporal, Multisensor Approach to Mapping the Canadian Boreal Forest

NASA Astrophysics Data System (ADS)

Reith, Ernest

The main anthropogenic source of CO2 emissions is the combustion of fossil fuels, while the clearing and burning of forests contribute significant amounts as well. Vegetation represents a major reservoir for terrestrial carbon stocks, and improving our ability to inventory vegetation will enhance our understanding of the impacts of land cover and climate change on carbon stocks and fluxes. These relationships may be an indication of a series of troubling biosphere-atmospheric feedback mechanisms that need to be better understood and modeled. Valuable land cover information can be provided to the global climate change modeling community using advanced remote sensing capabilities such as Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Airborne Synthetic Aperture Radar (AIRSAR). Individually and synergistically, data were successfully used to characterize the complex nature of the Canadian boreal forest land cover types. The multiple endmember spectral mixture analysis process was applied against seasonal AVIRIS data to produce species-level vegetated land cover maps of two study sites in the Canadian boreal forest: Old Black Spruce (OBS) and Old Jack Pine (OJP). The highest overall accuracy was assessed to be at least 66% accurate to the available reference map, providing evidence that high-quality, species-level land cover mapping of the Canadian boreal forest is achievable at accuracy levels greater than other previous research efforts in the region. Backscatter information from multichannel, polarimetric SAR utilizing a binary decision tree-based classification technique methodology was moderately successfully applied to AIRSAR to produce maps of the boreal land cover types at both sites, with overall accuracies at least 59%. A process, centered around noise whitening and principal component analysis features of the minimum noise fraction transform, was implemented to leverage synergies contained within spatially coregistered multitemporal and multisensor AVIRIS and AIRSAR data sets to successfully produce high-accuracy boreal forest land cover maps. Overall land cover map accuracies of 78% and 72% were assessed for OJP and OBS sites, respectively, for either seasonal or multitemporal data sets. High individual land cover accuracies appeared to be independent of site, season, or multisensor combination in the minimum-noise fraction-based approach.

Modelling and Analysis of Hydrodynamics and Water Quality for Rivers in the Northern Cold Region of China

PubMed Central

Tang, Gula; Zhu, Yunqiang; Wu, Guozheng; Li, Jing; Li, Zhao-Liang; Sun, Jiulin

2016-01-01

In this study, the Mudan River, which is the most typical river in the northern cold region of China was selected as the research object; Environmental Fluid Dynamics Code (EFDC) was adopted to construct a new two-dimensional water quality model for the urban sections of the Mudan River, and concentrations of CODCr and NH3N during ice-covered and open-water periods were simulated and analyzed. Results indicated that roughness coefficient and comprehensive pollutant decay rate were significantly different in those periods. To be specific, the roughness coefficient in the ice-covered period was larger than that of the open-water period, while the decay rate within the former period was smaller than that in the latter. In addition, according to the analysis of the simulated results, the main reasons for the decay rate reduction during the ice-covered period are temperature drop, upstream inflow decrease and ice layer cover; among them, ice sheet is the major contributor of roughness increase. These aspects were discussed in more detail in this work. The model could be generalized to hydrodynamic water quality process simulation researches on rivers in other cold regions as well. PMID:27070631

Generating land cover boundaries from remotely sensed data using object-based image analysis: overview and epidemiological application.

PubMed

Maxwell, Susan K

2010-12-01

Satellite imagery and aerial photography represent a vast resource to significantly enhance environmental mapping and modeling applications for use in understanding spatio-temporal relationships between environment and health. Deriving boundaries of land cover objects, such as trees, buildings, and crop fields, from image data has traditionally been performed manually using a very time consuming process of hand digitizing. Boundary detection algorithms are increasingly being applied using object-based image analysis (OBIA) technology to automate the process. The purpose of this paper is to present an overview and demonstrate the application of OBIA for delineating land cover features at multiple scales using a high resolution aerial photograph (1 m) and a medium resolution Landsat image (30 m) time series in the context of a pesticide spray drift exposure application. Copyright © 2010. Published by Elsevier Ltd.

Comparison of effects of cold-region soil/snow processes and the uncertainties from model forcing data on permafrost physical characteristics

DOE PAGES

Barman, Rahul; Jain, Atul K.

2016-03-28

Here, we used a land surface model to (1) evaluate the influence of recent improvements in modeling cold-region soil/snow physics on near-surface permafrost physical characteristics (within 0–3 m soil column) in the northern high latitudes (NHL) and (2) compare them with uncertainties from climate and land-cover data sets. Specifically, four soil/snow processes are investigated: deep soil energetics, soil organic carbon (SOC) effects on soil properties, wind compaction of snow, and depth hoar formation. In the model, together they increased the contemporary NHL permafrost area by 9.2 × 10 6 km 2 (from 2.9 to 12.3—without and with these processes, respectively)more » and reduced historical degradation rates. In comparison, permafrost area using different climate data sets (with annual air temperature difference of ~0.5°C) differed by up to 2.3 × 10 6 km 2, with minimal contribution of up to 0.7 × 10 6 km 2 from substantial land-cover differences. Individually, the strongest role in permafrost increase was from deep soil energetics, followed by contributions from SOC and wind compaction, while depth hoar decreased permafrost. The respective contribution on 0–3 m permafrost stability also followed a similar pattern. However, soil temperature and moisture within vegetation root zone (~0–1 m), which strongly influence soil biogeochemistry, were only affected by the latter three processes. The ecosystem energy and water fluxes were impacted the least due to these soil/snow processes. While it is evident that simulated permafrost physical characteristics benefit from detailed treatment of cold-region biogeophysical processes, we argue that these should also lead to integrated improvements in modeling of biogeochemistry.« less

Hydrologic impacts of land cover variability and change at seasonal to decadal time scales over North America, 1992-2016

NASA Astrophysics Data System (ADS)

Bohn, T. J.; Vivoni, E. R.

2017-12-01

Land cover variability and change have been shown to influence the terrestrial hydrologic cycle by altering the partitioning of moisture and energy fluxes. However, the magnitude and directionality of the relationship between land cover and surface hydrology has been shown to vary substantially across regions. Here, we provide an assessment of the impacts of land cover change on hydrologic processes at seasonal (vegetation phenology) to decadal scales (land cover conversion) in the United States and Mexico. To this end, we combine time series of remotely-sensed land surface characteristics with land cover maps for different decades as input to the Variable Infiltration Capacity hydrologic model. Land surface characteristics (leaf area index, surface albedo, and canopy fraction derived from normalized difference vegetation index) were obtained from the Moderate Resolution Imaging Spectrometer (MODIS) at 8-day intervals over the period 2000-2016. Land cover maps representing conditions in 1992, 2001, and 2011 were derived by homogenizing the National Land Cover Database over the US and the INEGI Series I through V maps over Mexico. An additional map covering all of North America was derived from the most frequent land cover class observed in each pixel of the MODIS MOD12Q1 product during 2001-2013. Land surface characteristics were summarized over land cover fractions at 1/16 degree (6 km) resolution. For each land cover map, hydrologic simulations were conducted that covered the period 1980-2013, using the best-available, hourly meteorological forcings at a similar spatial resolution. Based on these simulations, we present a comparison of the contributions of land cover change and climate variability at seasonal to decadal scales on the hydrologic and energy budgets, identifying the dominant components through time and space. This work also offers a valuable dataset on land cover variability and its hydrologic response for continental-scale assessments and modeling.

A Tool for Creating Regionally Calibrated High-Resolution Land Cover Data Sets for the West African Sahel: Using Machine Learning to Scale Up Hand-Classified Maps in a Data-Sparse Environment

NASA Astrophysics Data System (ADS)

Van Gordon, M.; Van Gordon, S.; Min, A.; Sullivan, J.; Weiner, Z.; Tappan, G. G.

2017-12-01

Using support vector machine (SVM) learning and high-accuracy hand-classified maps, we have developed a publicly available land cover classification tool for the West African Sahel. Our classifier produces high-resolution and regionally calibrated land cover maps for the Sahel, representing a significant contribution to the data available for this region. Global land cover products are unreliable for the Sahel, and accurate land cover data for the region are sparse. To address this gap, the U.S. Geological Survey and the Regional Center for Agriculture, Hydrology and Meteorology (AGRHYMET) in Niger produced high-quality land cover maps for the region via hand-classification of Landsat images. This method produces highly accurate maps, but the time and labor required constrain the spatial and temporal resolution of the data products. By using these hand-classified maps alongside SVM techniques, we successfully increase the resolution of the land cover maps by 1-2 orders of magnitude, from 2km-decadal resolution to 30m-annual resolution. These high-resolution regionally calibrated land cover datasets, along with the classifier we developed to produce them, lay the foundation for major advances in studies of land surface processes in the region. These datasets will provide more accurate inputs for food security modeling, hydrologic modeling, analyses of land cover change and climate change adaptation efforts. The land cover classification tool we have developed will be publicly available for use in creating additional West Africa land cover datasets with future remote sensing data and can be adapted for use in other parts of the world.

Land cover change impact on urban flood modeling (case study: Upper Citarum watershed)

NASA Astrophysics Data System (ADS)

Siregar, R. I.

2018-03-01

The upper Citarum River watershed utilizes remote sensing technology in Geographic Information System to provide information on land coverage by interpretation of objects in the image. Rivers that pass through urban areas will cause flooding problems causing disadvantages, and it disrupts community activities in the urban area. Increased development in a city is related to an increase in the number of population growth that added by increasing quality and quantity of life necessities. Improved urban lifestyle changes have an impact on land cover. The impact in over time will be difficult to control. This study aims to analyze the condition of flooding in urban areas caused by upper Citarum watershed land-use change in 2001 with the land cover change in 2010. This modeling analyzes with the help of HEC-RAS to describe flooded inundation urban areas. Land cover change in upper Citarum watershed is not very significant; it based on the results of data processing of land cover has the difference of area that changed is not enormous. Land cover changes for the floods increased dramatically to a flow coefficient for 2001 is 0.65 and in 2010 at 0.69. In 2001, the inundation area about 105,468 hectares and it were about 92,289 hectares in 2010.

Evaluation of the AnnAGNPS Model for Predicting Runoff and Nutrient Export in a Typical Small Watershed in the Hilly Region of Taihu Lake.

PubMed

Luo, Chuan; Li, Zhaofu; Li, Hengpeng; Chen, Xiaomin

2015-09-02

The application of hydrological and water quality models is an efficient approach to better understand the processes of environmental deterioration. This study evaluated the ability of the Annualized Agricultural Non-Point Source (AnnAGNPS) model to predict runoff, total nitrogen (TN) and total phosphorus (TP) loading in a typical small watershed of a hilly region near Taihu Lake, China. Runoff was calibrated and validated at both an annual and monthly scale, and parameter sensitivity analysis was performed for TN and TP before the two water quality components were calibrated. The results showed that the model satisfactorily simulated runoff at annual and monthly scales, both during calibration and validation processes. Additionally, results of parameter sensitivity analysis showed that the parameters Fertilizer rate, Fertilizer organic, Canopy cover and Fertilizer inorganic were more sensitive to TN output. In terms of TP, the parameters Residue mass ratio, Fertilizer rate, Fertilizer inorganic and Canopy cover were the most sensitive. Based on these sensitive parameters, calibration was performed. TN loading produced satisfactory results for both the calibration and validation processes, whereas the performance of TP loading was slightly poor. The simulation results showed that AnnAGNPS has the potential to be used as a valuable tool for the planning and management of watersheds.

Pine invasions in treeless environments: dispersal overruns microsite heterogeneity.

PubMed

Pauchard, Aníbal; Escudero, Adrián; García, Rafael A; de la Cruz, Marcelino; Langdon, Bárbara; Cavieres, Lohengrin A; Esquivel, Jocelyn

2016-01-01

Understanding biological invasions patterns and mechanisms is highly needed for forecasting and managing these processes and their negative impacts. At small scales, ecological processes driving plant invasions are expected to produce a spatially explicit pattern driven by propagule pressure and local ground heterogeneity. Our aim was to determine the interplay between the intensity of seed rain, using distance to a mature plantation as a proxy, and microsite heterogeneity in the spreading of Pinus contorta in the treeless Patagonian steppe. Three one-hectare plots were located under different degrees of P. contorta invasion (Coyhaique Alto, 45° 30'S and 71° 42'W). We fitted three types of inhomogeneous Poisson models to each pine plot in an attempt for describing the observed pattern as accurately as possible: the "dispersal" models, "local ground heterogeneity" models, and "combined" models, using both types of covariates. To include the temporal axis in the invasion process, we analyzed both the pattern of young and old recruits and also of all recruits together. As hypothesized, the spatial patterns of recruited pines showed coarse scale heterogeneity. Early pine invasion spatial patterns in our Patagonian steppe site is not different from expectations of inhomogeneous Poisson processes taking into consideration a linear and negative dependency of pine recruit intensity on the distance to afforestations. Models including ground-cover predictors were able to describe the point pattern process only in a couple of cases but never better than dispersal models. This finding concurs with the idea that early invasions depend more on seed pressure than on the biotic and abiotic relationships seed and seedlings establish at the microsite scale. Our results show that without a timely and active management, P. contorta will invade the Patagonian steppe independently of the local ground-cover conditions.

An Automated Algorithm for Producing Land Cover Information from Landsat Surface Reflectance Data Acquired Between 1984 and Present

NASA Astrophysics Data System (ADS)

Rover, J.; Goldhaber, M. B.; Holen, C.; Dittmeier, R.; Wika, S.; Steinwand, D.; Dahal, D.; Tolk, B.; Quenzer, R.; Nelson, K.; Wylie, B. K.; Coan, M.

2015-12-01

Multi-year land cover mapping from remotely sensed data poses challenges. Producing land cover products at spatial and temporal scales required for assessing longer-term trends in land cover change are typically a resource-limited process. A recently developed approach utilizes open source software libraries to automatically generate datasets, decision tree classifications, and data products while requiring minimal user interaction. Users are only required to supply coordinates for an area of interest, land cover from an existing source such as National Land Cover Database and percent slope from a digital terrain model for the same area of interest, two target acquisition year-day windows, and the years of interest between 1984 and present. The algorithm queries the Landsat archive for Landsat data intersecting the area and dates of interest. Cloud-free pixels meeting the user's criteria are mosaicked to create composite images for training the classifiers and applying the classifiers. Stratification of training data is determined by the user and redefined during an iterative process of reviewing classifiers and resulting predictions. The algorithm outputs include yearly land cover raster format data, graphics, and supporting databases for further analysis. Additional analytical tools are also incorporated into the automated land cover system and enable statistical analysis after data are generated. Applications tested include the impact of land cover change and water permanence. For example, land cover conversions in areas where shrubland and grassland were replaced by shale oil pads during hydrofracking of the Bakken Formation were quantified. Analytical analysis of spatial and temporal changes in surface water included identifying wetlands in the Prairie Pothole Region of North Dakota with potential connectivity to ground water, indicating subsurface permeability and geochemistry.

BOREAS AFM-12 1-km AVHRR Seasonal Land Cover Classification

NASA Technical Reports Server (NTRS)

Steyaert, Lou; Hall, Forrest G.; Newcomer, Jeffrey A. (Editor); Knapp, David E. (Editor); Loveland, Thomas R.; Smith, David E. (Technical Monitor)

2000-01-01

The Boreal Ecosystem-Atmosphere Study (BOREAS) Airborne Fluxes and Meteorology (AFM)-12 team's efforts focused on regional scale Surface Vegetation and Atmosphere (SVAT) modeling to improve parameterization of the heterogeneous BOREAS landscape for use in larger scale Global Circulation Models (GCMs). This regional land cover data set was developed as part of a multitemporal one-kilometer Advanced Very High Resolution Radiometer (AVHRR) land cover analysis approach that was used as the basis for regional land cover mapping, fire disturbance-regeneration, and multiresolution land cover scaling studies in the boreal forest ecosystem of central Canada. This land cover classification was derived by using regional field observations from ground and low-level aircraft transits to analyze spectral-temporal clusters that were derived from an unsupervised cluster analysis of monthly Normalized Difference Vegetation Index (NDVI) image composites (April-September 1992). This regional data set was developed for use by BOREAS investigators, especially those involved in simulation modeling, remote sensing algorithm development, and aircraft flux studies. Based on regional field data verification, this multitemporal one-kilometer AVHRR land cover mapping approach was effective in characterizing the biome-level land cover structure, embedded spatially heterogeneous landscape patterns, and other types of key land cover information of interest to BOREAS modelers.The land cover mosaics in this classification include: (1) wet conifer mosaic (low, medium, and high tree stand density), (2) mixed coniferous-deciduous forest (80% coniferous, codominant, and 80% deciduous), (3) recent visible bum, vegetation regeneration, or rock outcrops-bare ground-sparsely vegetated slow regeneration bum (four classes), (4) open water and grassland marshes, and (5) general agricultural land use/ grasslands (three classes). This land cover mapping approach did not detect small subpixel-scale landscape features such as fens, bogs, and small water bodies. Field observations and comparisons with Landsat Thematic Mapper (TM) suggest a minimum effective resolution of these land cover classes in the range of three to four kilometers, in part, because of the daily to monthly compositing process. In general, potential accuracy limitations are mitigated by the use of conservative parameterization rules such as aggregation of predominant land cover classes within minimum horizontal grid cell sizes of ten kilometers. The AFM-12 one-kilometer AVHRR seasonal land cover classification data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

Quantification of the inevitable: the influence of soil macrofauna on soil water movement in rehabilitated open-cut mine land

NASA Astrophysics Data System (ADS)

Arnold, S.; Williams, E. R.

2015-08-01

Recolonisation of soil by macrofauna (especially ants and termites) in rehabilitated open-cut mine sites is inevitable. In these highly disturbed landscapes, soil invertebrates play a major role in soil development (macropore configuration, nutrient cycling, bioturbation, etc.) and can influence hydrological processes such as infiltration and seepage. Understanding and quantifying these ecosystem processes is important in rehabilitation design, establishment and subsequent management to ensure progress to the desired end-goal, especially in waste cover systems designed to prevent water reaching and transporting underlying hazardous waste materials. However, soil macrofauna are typically overlooked during hydrological modelling, possibly due to uncertainties on the extent of their influence, which can lead to failure of waste cover systems or rehabilitation activities. We propose that scientific experiments under controlled conditions are required to quantify (i) macrofauna - soil structure interactions, (ii) functional dynamics of macrofauna taxa, and (iii) their effects on macrofauna and soil development over time. Such knowledge would provide crucial information for soil water models, which would increase confidence in mine waste cover design recommendations and eventually lead to higher likelihood of rehabilitation success of open-cut mining land.

Atmospheric Profiles, Clouds, and the Evolution of Sea Ice Cover in the Beaufort and Chukchi Seas: Atmospheric Observations and Modeling as Part of the SeasonalIce Zone Reconnaissance Surveys

DTIC Science & Technology

2015-09-30

hired to conduct WRF model experiments. • We conducted Weather Research and Forecast ( WRF ) model simulations for the summer of 2014 and compared with... WRF simulations under different synoptic conditions will help to more 10 clearly identify the deficiencies in the representation of these processes

Towards simplification of hydrologic modeling: Identification of dominant processes

USGS Publications Warehouse

Markstrom, Steven; Hay, Lauren E.; Clark, Martyn P.

2016-01-01

The Precipitation–Runoff Modeling System (PRMS), a distributed-parameter hydrologic model, has been applied to the conterminous US (CONUS). Parameter sensitivity analysis was used to identify: (1) the sensitive input parameters and (2) particular model output variables that could be associated with the dominant hydrologic process(es). Sensitivity values of 35 PRMS calibration parameters were computed using the Fourier amplitude sensitivity test procedure on 110 000 independent hydrologically based spatial modeling units covering the CONUS and then summarized to process (snowmelt, surface runoff, infiltration, soil moisture, evapotranspiration, interflow, baseflow, and runoff) and model performance statistic (mean, coefficient of variation, and autoregressive lag 1). Identified parameters and processes provide insight into model performance at the location of each unit and allow the modeler to identify the most dominant process on the basis of which processes are associated with the most sensitive parameters. The results of this study indicate that: (1) the choice of performance statistic and output variables has a strong influence on parameter sensitivity, (2) the apparent model complexity to the modeler can be reduced by focusing on those processes that are associated with sensitive parameters and disregarding those that are not, (3) different processes require different numbers of parameters for simulation, and (4) some sensitive parameters influence only one hydrologic process, while others may influence many

Computational provenance in hydrologic science: a snow mapping example.

PubMed

Dozier, Jeff; Frew, James

2009-03-13

Computational provenance--a record of the antecedents and processing history of digital information--is key to properly documenting computer-based scientific research. To support investigations in hydrologic science, we produce the daily fractional snow-covered area from NASA's moderate-resolution imaging spectroradiometer (MODIS). From the MODIS reflectance data in seven wavelengths, we estimate the fraction of each 500 m pixel that snow covers. The daily products have data gaps and errors because of cloud cover and sensor viewing geometry, so we interpolate and smooth to produce our best estimate of the daily snow cover. To manage the data, we have developed the Earth System Science Server (ES3), a software environment for data-intensive Earth science, with unique capabilities for automatically and transparently capturing and managing the provenance of arbitrary computations. Transparent acquisition avoids the scientists having to express their computations in specific languages or schemas in order for provenance to be acquired and maintained. ES3 models provenance as relationships between processes and their input and output files. It is particularly suited to capturing the provenance of an evolving algorithm whose components span multiple languages and execution environments.

Preliminary development of digital signal processing in microwave radiometers

NASA Technical Reports Server (NTRS)

Stanley, W. D.

1980-01-01

Topics covered involve a number of closely related tasks including: the development of several control loop and dynamic noise model computer programs for simulating microwave radiometer measurements; computer modeling of an existing stepped frequency radiometer in an effort to determine its optimum operational characteristics; investigation of the classical second order analog control loop to determine its ability to reduce the estimation error in a microwave radiometer; investigation of several digital signal processing unit designs; initiation of efforts to develop required hardware and software for implementation of the digital signal processing unit; and investigation of the general characteristics and peculiarities of digital processing noiselike microwave radiometer signals.

An analysis of IGBP global land-cover characterization process

USGS Publications Warehouse

Loveland, Thomas R.; Zhu, Zhiliang; Ohlen, Donald O.; Brown, Jesslyn F.; Reed, Bradley C.; Yang, Limin

1999-01-01

The international Geosphere Biosphere Programme (IGBP) has called for the development of improved global land-cover data for use in increasingly sophisticated global environmental models. To meet this need, the staff of the U.S. Geological Survey and the University of Nebraska-Lincoln developed and applied a global land-cover characterization methodology using 1992-1993 1-km resolution Advanced Very High Resolution Radiometer (AVHRR) and other spatial data. The methodology, based on unsupervised classification with extensive postclassification refinement, yielded a multi-layer database consisting of eight land-cover data sets, descriptive attributes, and source data. An independent IGBP accuracy assessment reports a global accuracy of 73.5 percent, and continental results vary from 63 percent to 83 percent. Although data quality, methodology, interpreter performance, and logistics affected the results, significant problems were associated with the relationship between AVHRR data and fine-scale, spectrally similar land-cover patterns in complex natural or disturbed landscapes.

Commentary: A cautionary tale regarding use of the National Land Cover Dataset 1992

USGS Publications Warehouse

Thogmartin, Wayne E.; Gallant, Alisa L.; Knutson, Melinda G.; Fox, Timothy J.; Suarez, Manuel J.

2004-01-01

Digital land-cover data are among the most popular data sources used in ecological research and natural resource management. However, processes for accurate land-cover classification over large regions are still evolving. We identified inconsistencies in the National Land Cover Dataset 1992, the most current and available representation of land cover for the conterminous United States. We also report means to address these inconsistencies in a bird-habitat model. We used a Geographic Information System (GIS) to position a regular grid (or lattice) over the upper midwestern United States and summarized the proportion of individual land covers in each cell within the lattice. These proportions were then mapped back onto the lattice, and the resultant lattice was compared to satellite paths, state borders, and regional map classification units. We observed mapping inconsistencies at the borders between mapping regions, states, and Thematic Mapper (TM) mapping paths in the upper midwestern United States, particularly related to grass I and-herbaceous, emergent-herbaceous wetland, and small-grain land covers. We attributed these discrepancies to differences in image dates between mapping regions, suboptimal image dates for distinguishing certain land-cover types, lack of suitable ancillary data for improving discrimination for rare land covers, and possibly differences among image interpreters. To overcome these inconsistencies for the purpose of modeling regional populations of birds, we combined grassland-herbaceous and pasture-hay land-cover classes and excluded the use of emergent-herbaceous and small-grain land covers. We recommend that users of digital land-cover data conduct similar assessments for other regions before using these data for habitat evaluation. Further, caution is advised in using these data in the analysis of regional land-cover change because it is not likely that future digital land-cover maps will repeat the same problems, thus resulting in biased estimates of change.

Development of a generic auto-calibration package for regional ecological modeling and application in the Central Plains of the United States

USGS Publications Warehouse

Wu, Yiping; Liu, Shuguang; Li, Zhengpeng; Dahal, Devendra; Young, Claudia J.; Schmidt, Gail L.; Liu, Jinxun; Davis, Brian; Sohl, Terry L.; Werner, Jeremy M.; Oeding, Jennifer

2014-01-01

Process-oriented ecological models are frequently used for predicting potential impacts of global changes such as climate and land-cover changes, which can be useful for policy making. It is critical but challenging to automatically derive optimal parameter values at different scales, especially at regional scale, and validate the model performance. In this study, we developed an automatic calibration (auto-calibration) function for a well-established biogeochemical model—the General Ensemble Biogeochemical Modeling System (GEMS)-Erosion Deposition Carbon Model (EDCM)—using data assimilation technique: the Shuffled Complex Evolution algorithm and a model-inversion R package—Flexible Modeling Environment (FME). The new functionality can support multi-parameter and multi-objective auto-calibration of EDCM at the both pixel and regional levels. We also developed a post-processing procedure for GEMS to provide options to save the pixel-based or aggregated county-land cover specific parameter values for subsequent simulations. In our case study, we successfully applied the updated model (EDCM-Auto) for a single crop pixel with a corn–wheat rotation and a large ecological region (Level II)—Central USA Plains. The evaluation results indicate that EDCM-Auto is applicable at multiple scales and is capable to handle land cover changes (e.g., crop rotations). The model also performs well in capturing the spatial pattern of grain yield production for crops and net primary production (NPP) for other ecosystems across the region, which is a good example for implementing calibration and validation of ecological models with readily available survey data (grain yield) and remote sensing data (NPP) at regional and national levels. The developed platform for auto-calibration can be readily expanded to incorporate other model inversion algorithms and potential R packages, and also be applied to other ecological models.

Integrating land cover modeling and adaptive management to conserve endangered species and reduce catastrophic fire risk

USGS Publications Warehouse

Breininger, David; Duncan, Brean; Eaton, Mitchell J.; Johnson, Fred; Nichols, James

2014-01-01

Land cover modeling is used to inform land management, but most often via a two-step process, where science informs how management alternatives can influence resources, and then, decision makers can use this information to make decisions. A more efficient process is to directly integrate science and decision-making, where science allows us to learn in order to better accomplish management objectives and is developed to address specific decisions. Co-development of management and science is especially productive when decisions are complicated by multiple objectives and impeded by uncertainty. Multiple objectives can be met by the specification of tradeoffs, and relevant uncertainty can be addressed through targeted science (i.e., models and monitoring). We describe how to integrate habitat and fuel monitoring with decision-making focused on the dual objectives of managing for endangered species and minimizing catastrophic fire risk. Under certain conditions, both objectives might be achieved by a similar management policy; other conditions require tradeoffs between objectives. Knowledge about system responses to actions can be informed by developing hypotheses based on ideas about fire behavior and then applying competing management actions to different land units in the same system state. Monitoring and management integration is important to optimize state-specific management decisions and to increase knowledge about system responses. We believe this approach has broad utility and identifies a clear role for land cover modeling programs intended to inform decision-making.

Modeling of Thermal Performance of Multiphase Nuclear Fuel Cell Under Variable Gravity Conditions

NASA Technical Reports Server (NTRS)

Ding, Z.; Anghaie, S.

1996-01-01

A unique numerical method has been developed to model the dynamic processes of bulk evaporation and condensation processes, associated with internal heat generation and natural convection under different gravity levels. The internal energy formulation, for the bulk liquid-vapor phase change problems in an encapsulated container, was employed. The equations, governing the conservation of mass, momentum and energy for both phases involved in phase change, were solved. The thermal performance of a multiphase uranium tetra-fluoride fuel element under zero gravity, micro-gravity and normal gravity conditions has been investigated. The modeling yielded results including the evolution of the bulk liquid-vapor phase change process, the evolution of the liquid-vapor interface, the formation and development of the liquid film covering the side wall surface, the temperature distribution and the convection flow field in the fuel element. The strong dependence of the thermal performance of such multiphase nuclear fuel cell on the gravity condition has been revealed. Under all three gravity conditions, 0-g, 10(exp -3)-g, and 1-g, the liquid film is formed and covers the entire side wall. The liquid film covering the side wall is more isothermalized at the wall surface, which can prevent the side wall from being over-heated. As the gravity increases, the liquid film is thinner, the temperature gradient is larger across the liquid film and smaller across the vapor phase. This investigation provides valuable information about the thermal performance of multi-phase nuclear fuel element for the potential space and ground applications.

Integrating statistical and process-based models to produce probabilistic landslide hazard at regional scale

NASA Astrophysics Data System (ADS)

Strauch, R. L.; Istanbulluoglu, E.

2017-12-01

We develop a landslide hazard modeling approach that integrates a data-driven statistical model and a probabilistic process-based shallow landslide model for mapping probability of landslide initiation, transport, and deposition at regional scales. The empirical model integrates the influence of seven site attribute (SA) classes: elevation, slope, curvature, aspect, land use-land cover, lithology, and topographic wetness index, on over 1,600 observed landslides using a frequency ratio (FR) approach. A susceptibility index is calculated by adding FRs for each SA on a grid-cell basis. Using landslide observations we relate susceptibility index to an empirically-derived probability of landslide impact. This probability is combined with results from a physically-based model to produce an integrated probabilistic map. Slope was key in landslide initiation while deposition was linked to lithology and elevation. Vegetation transition from forest to alpine vegetation and barren land cover with lower root cohesion leads to higher frequency of initiation. Aspect effects are likely linked to differences in root cohesion and moisture controlled by solar insulation and snow. We demonstrate the model in the North Cascades of Washington, USA and identify locations of high and low probability of landslide impacts that can be used by land managers in their design, planning, and maintenance.

Tropical and Subtropical Cloud Transitions in Weather and Climate Prediction Models: The GCSS/WGNE Pacific Cross-Section Intercomparison (GPCI)

NASA Technical Reports Server (NTRS)

Teixeira, J.; Cardoso, S.; Bonazzola, M.; Cole, J.; DeGenio, A.; DeMott, C.; Franklin, C.; Hannay, C.; Jakob, C.; Jiao, Y.;

Carotene Degradation and Isomerization during Thermal Processing: A Review on the Kinetic Aspects.

PubMed

Colle, Ines J P; Lemmens, Lien; Knockaert, Griet; Van Loey, Ann; Hendrickx, Marc

2016-08-17

Kinetic models are important tools for process design and optimization to balance desired and undesired reactions taking place in complex food systems during food processing and preservation. This review covers the state of the art on kinetic models available to describe heat-induced conversion of carotenoids, in particular lycopene and β-carotene. First, relevant properties of these carotenoids are discussed. Second, some general aspects of kinetic modeling are introduced, including both empirical single-response modeling and mechanism-based multi-response modeling. The merits of multi-response modeling to simultaneously describe carotene degradation and isomerization are demonstrated. The future challenge in this research field lies in the extension of the current multi-response models to better approach the real reaction pathway and in the integration of kinetic models with mass transfer models in case of reaction in multi-phase food systems.

Identification and delineation of areas flood hazard using high accuracy of DEM data

NASA Astrophysics Data System (ADS)

Riadi, B.; Barus, B.; Widiatmaka; Yanuar, M. J. P.; Pramudya, B.

2018-05-01

Flood incidents that often occur in Karawang regency need to be mitigated. These expectations exist on technologies that can predict, anticipate and reduce disaster risks. Flood modeling techniques using Digital Elevation Model (DEM) data can be applied in mitigation activities. High accuracy DEM data used in modeling, will result in better flooding flood models. The result of high accuracy DEM data processing will yield information about surface morphology which can be used to identify indication of flood hazard area. The purpose of this study was to identify and describe flood hazard areas by identifying wetland areas using DEM data and Landsat-8 images. TerraSAR-X high-resolution data is used to detect wetlands from landscapes, while land cover is identified by Landsat image data. The Topography Wetness Index (TWI) method is used to detect and identify wetland areas with basic DEM data, while for land cover analysis using Tasseled Cap Transformation (TCT) method. The result of TWI modeling yields information about potential land of flood. Overlay TWI map with land cover map that produces information that in Karawang regency the most vulnerable areas occur flooding in rice fields. The spatial accuracy of the flood hazard area in this study was 87%.

Separating snow, clean and debris covered ice in the Upper Indus Basin, Hindukush-Karakoram-Himalayas, using Landsat images between 1998 and 2002

NASA Astrophysics Data System (ADS)

Khan, Asif; Naz, Bibi S.; Bowling, Laura C.

2015-02-01

The Hindukush Karakoram Himalayan mountains contain some of the largest glaciers of the world, and supply melt water from perennial snow and glaciers to the Upper Indus Basin (UIB) upstream of Tarbela dam, which constitutes greater than 80% of the annual flows, and caters to the needs of millions of people in the Indus Basin. It is therefore important to study the response of perennial snow and glaciers in the UIB under changing climatic conditions, using improved hydrological modeling, glacier mass balance, and observations of glacier responses. However, the available glacier inventories and datasets only provide total perennial-snow and glacier cover areas, despite the fact that snow, clean ice and debris covered ice have different melt rates and densities. This distinction is vital for improved hydrological modeling and mass balance studies. This study, therefore, presents a separated perennial snow and glacier inventory (perennial snow-cover on steep slopes, perennial snow-covered ice, clean and debris covered ice) based on a semi-automated method that combines Landsat images and surface slope information in a supervised maximum likelihood classification to map distinct glacier zones, followed by manual post processing. The accuracy of the presented inventory falls well within the accuracy limits of available snow and glacier inventory products. For the entire UIB, estimates of perennial and/or seasonal snow on steep slopes, snow-covered ice, clean and debris covered ice zones are 7238 ± 724, 5226 ± 522, 4695 ± 469 and 2126 ± 212 km2 respectively. Thus total snow and glacier cover is 19,285 ± 1928 km2, out of which 12,075 ± 1207 km2 is glacier cover (excluding steep slope snow-cover). Equilibrium Line Altitude (ELA) estimates based on the Snow Line Elevation (SLE) in various watersheds range between 4800 and 5500 m, while the Accumulation Area Ratio (AAR) ranges between 7% and 80%. 0 °C isotherms during peak ablation months (July and August) range between ∼ 5500 and 6200 m in various watersheds. These outputs can be used as input to hydrological models, to estimate spatially-variable degree day factors for hydrological modeling, to separate glacier and snow-melt contributions in river flows, and to study glacier mass balance, and glacier responses to changing climate.

Influence of dynamic coupled hydro-bio-mechanical processes on response of municipal solid waste and liner system in bioreactor landfills.

PubMed

Reddy, Krishna R; Kumar, Girish; Giri, Rajiv K

2017-05-01

A two-dimensional (2-D) mathematical model is presented to predict the response of municipal solid waste (MSW) of conventional as well as bioreactor landfills undergoing coupled hydro-bio-mechanical processes. The newly developed and validated 2-D coupled mathematical modeling framework combines and simultaneously solves a two-phase flow model based on the unsaturated Richard's equation, a plain-strain formulation of Mohr-Coulomb mechanical model and first-order decay kinetics biodegradation model. The performance of both conventional and bioreactor landfill was investigated holistically, by evaluating the mechanical settlement, extent of waste degradation with subsequent changes in geotechnical properties, landfill slope stability, and in-plane shear behavior (shear stress-displacement) of composite liner system and final cover system. It is concluded that for the given specific conditions considered, bioreactor landfill attained an overall stabilization after a continuous leachate injection of 16years, whereas the stabilization was observed after around 50years of post-closure in conventional landfills, with a total vertical strain of 36% and 37% for bioreactor and conventional landfills, respectively. The significant changes in landfill settlement, the extent of MSW degradation, MSW geotechnical properties, along with their influence on the in-plane shear response of composite liner and final cover system, between the conventional and bioreactor landfills, observed using the mathematical model proposed in this study, corroborates the importance of considering coupled hydro-bio-mechanical processes while designing and predicting the performance of engineered bioreactor landfills. The study underscores the importance of considering the effect of coupled processes while examining the stability and integrity of the liner and cover systems, which form the integral components of a landfill. Moreover, the spatial and temporal variations in the landfill settlement, the stability of landfill slope under pressurized leachate injection conditions and the rapid changes in the MSW properties with degradation emphasizes the complexity of the bioreactor landfill system and the need for understanding the interrelated processes to design and operate stable and effective bioreactor landfills. A detailed discussion on the results obtained from the numerical simulations along with limitations and key challenges in this study are also presented. Copyright © 2016 Elsevier Ltd. All rights reserved.

Soil detachment by overland flow under different vegetation restoration models in the loess plateau of China

USDA-ARS?s Scientific Manuscript database

Land use change has significant effects on soil properties and vegetation cover and thus probably affects soil detachment by overland flow. Few studies were conducted to evaluate the effect of restoration models on the soil detachment process in the Loess Plateau in the past decade during which a Gr...

Computational Nanotechnology of Molecular Materials, Electronics and Machines

NASA Technical Reports Server (NTRS)

Srivastava, D.; Biegel, Bryan A. (Technical Monitor)

2002-01-01

This viewgraph presentation covers carbon nanotubes, their characteristics, and their potential future applications. The presentation include predictions on the development of nanostructures and their applications, the thermal characteristics of carbon nanotubes, mechano-chemical effects upon carbon nanotubes, molecular electronics, and models for possible future nanostructure devices. The presentation also proposes a neural model for signal processing.

Energy Dispersive Spectrometry and Quantitative Analysis Short Course. Introduction to X-ray Energy Dispersive Spectrometry and Quantitative Analysis

NASA Technical Reports Server (NTRS)

Carpenter, Paul; Curreri, Peter A. (Technical Monitor)

2002-01-01

This course will cover practical applications of the energy-dispersive spectrometer (EDS) to x-ray microanalysis. Topics covered will include detector technology, advances in pulse processing, resolution and performance monitoring, detector modeling, peak deconvolution and fitting, qualitative and quantitative analysis, compositional mapping, and standards. An emphasis will be placed on use of the EDS for quantitative analysis, with discussion of typical problems encountered in the analysis of a wide range of materials and sample geometries.

Controlled Ecological Life Support System: Regenerative Life Support Systems in Space

NASA Technical Reports Server (NTRS)

Macelroy, Robert D.; Smernoff, David T.

1987-01-01

A wide range of topics related to the extended support of humans in space are covered. Overviews of research conducted in Japan, Europe, and the U.S. are presented. The methods and technologies required to recycle materials, especially respiratory gases, within a closed system are examined. Also presented are issues related to plant and algal productivity, efficiency, and processing methods. Computer simulation of closed systems, discussions of radiation effects on systems stability, and modeling of a computer bioregenerative system are also covered.

Analysis of MODIS snow cover time series over the alpine regions as input for hydrological modeling

NASA Astrophysics Data System (ADS)

Notarnicola, Claudia; Rastner, Philipp; Irsara, Luca; Moelg, Nico; Bertoldi, Giacomo; Dalla Chiesa, Stefano; Endrizzi, Stefano; Zebisch, Marc

2010-05-01

Snow extent and relative physical properties are key parameters in hydrology, weather forecast and hazard warning as well as in climatological models. Satellite sensors offer a unique advantage in monitoring snow cover due to their temporal and spatial synoptic view. The Moderate Resolution Imaging Spectrometer (MODIS) from NASA is especially useful for this purpose due to its high frequency. However, in order to evaluate the role of snow on the water cycle of a catchment such as runoff generation due to snowmelt, remote sensing data need to be assimilated in hydrological models. This study presents a comparison on a multi-temporal basis between snow cover data derived from (1) MODIS images, (2) LANDSAT images, and (3) predictions by the hydrological model GEOtop [1,3]. The test area is located in the catchment of the Matscher Valley (South Tyrol, Northern Italy). The snow cover maps derived from MODIS-images are obtained using a newly developed algorithm taking into account the specific requirements of mountain regions with a focus on the Alps [2]. This algorithm requires the standard MODIS-products MOD09 and MOD02 as input data and generates snow cover maps at a spatial resolution of 250 m. The final output is a combination of MODIS AQUA and MODIS TERRA snow cover maps, thus reducing the presence of cloudy pixels and no-data-values due to topography. By using these maps, daily time series starting from the winter season (November - May) 2002 till 2008/2009 have been created. Along with snow maps from MODIS images, also some snow cover maps derived from LANDSAT images have been used. Due to their high resolution (< 30 m) they have been considered as an evaluation tool. The snow cover maps are then compared with the hydrological GEOtop model outputs. The main objectives of this work are: 1. Evaluation of the MODIS snow cover algorithm using LANDSAT data 2. Investigation of snow cover, and snow cover duration for the area of interest for South Tyrol 3. Derivation and interpretation of the snow line for the seven winter seasons 4. An evaluation of the model outputs in order to determine the situations in which the remotely sensed data can be used to improve the model prediction of snow coverage and related variables References [1] Rigon R., Bertoldi G. and Over T.M. 2006. GEOtop: A Distributed Hydrological Model with Coupled Water and Energy Budgets, Journal of Hydrometeorology, 7: 371-388. [2] Rastner P., Irsara L., Schellenberger T., Della Chiesa S., Bertoldi G., Endrizzi S., Notarnicola C., Steurer C., Zebisch M. 2009. Monitoraggio del manto nevoso in aree alpine con dati MODIS multi-temporali e modelli idrologici, 13th ASITA National Conference, 1-4.12.2009, Bari, Italy. [3] Zanotti F., Endrizzi S., Bertoldi G. and Rigon R. 2004. The GEOtop snow module. Hydrological Processes, 18: 3667-3679. DOI:10.1002/hyp.5794.

Three-Dimensional Computer Simulation as an Important Competence Based Aspect of a Modern Mining Professional

NASA Astrophysics Data System (ADS)

Aksenova, Olesya; Pachkina, Anna

2017-11-01

The article deals with the problem of necessity of educational process transformation to meet the requirements of modern miming industry; cooperative developing of new educational programs and implementation of educational process taking into account modern manufacturability. The paper proves the idea of introduction into mining professionals learning process studying of three-dimensional models of surface technological complex, ore reserves and underground digging complex as well as creating these models in different graphic editors and working with the information analysis model obtained on the basis of these three-dimensional models. The technological process of manless coal mining at the premises of the mine Polysaevskaya controlled by the information analysis models built on the basis of three-dimensional models of individual objects and technological process as a whole, and at the same time requiring the staff able to use the programs of three-dimensional positioning in the miners and equipment global frame of reference is covered.

Relationships between lower tropospheric stability, low cloud cover, and water vapor isotopic composition in the subtropical Pacific

NASA Astrophysics Data System (ADS)

Galewsky, J.

2017-12-01

Understanding the processes that govern the relationships between lower tropospheric stability and low-cloud cover is crucial for improved constraints on low-cloud feedbacks and for improving the parameterizations of low-cloud cover used in climate models. The stable isotopic composition of atmospheric water vapor is a sensitive recorder of the balance of moistening and drying processes that set the humidity of the lower troposphere and may thus provide a useful framework for improving our understanding low-cloud processes. In-situ measurements of water vapor isotopic composition collected at the NOAA Mauna Loa Observatory in Hawaii, along with twice-daily soundings from Hilo and remote sensing of cloud cover, show a clear inverse relationship between the estimated inversion strength (EIS) and the mixing ratios and water vapor δ -values, and a positive relationship between EIS, deuterium excess, and Δ δ D, defined as the difference between an observation and a reference Rayleigh distillation curve. These relationships are consistent with reduced moistening and an enhanced upper-tropospheric contribution above the trade inversion under high EIS conditions and stronger moistening under weaker EIS conditions. The cloud fraction, cloud liquid water path, and cloud-top pressure were all found to be higher under low EIS conditions. Inverse modeling of the isotopic data for the highest and lowest terciles of EIS conditions provide quantitative constraints on the cold-point temperatures and mixing fractions that govern the humidity above the trade inversion. The modeling shows the moistening fraction between moist boundary layer air and dry middle tropospheric air 24±1.5% under low EIS conditions is and 6±1.5% under high EIS conditions. A cold-point (last-saturation) temperature of -30C can match the observations for both low and high EIS conditions. The isotopic composition of the moistening source as derived from the inversion (-114±10‰ ) requires moderate fractionation from a pure marine source, indicating a link between inversion strength and moistening of the lower troposphere from the outflow of shallow convection. This approach can be applied in other settings and the results can be used to test parameterizations in climate models.

Improved cloud parameterization for Arctic climate simulations based on satellite data

NASA Astrophysics Data System (ADS)

Klaus, Daniel; Dethloff, Klaus; Dorn, Wolfgang; Rinke, Annette

2015-04-01

The defective representation of Arctic cloud processes and properties remains a crucial problem in climate modelling and in reanalysis products. Satellite-based cloud observations (MODIS and CPR/CALIOP) and single-column model simulations (HIRHAM5-SCM) were exploited to evaluate and improve the simulated Arctic cloud cover of the atmospheric regional climate model HIRHAM5. The ECMWF reanalysis dataset 'ERA-Interim' (ERAint) was used for the model initialization, the lateral boundary forcing as well as the dynamical relaxation inside the pan-Arctic domain. HIRHAM5 has a horizontal resolution of 0.25° and uses 40 pressure-based and terrain-following vertical levels. In comparison with the satellite observations, the HIRHAM5 control run (HH5ctrl) systematically overestimates total cloud cover, but to a lesser extent than ERAint. The underestimation of high- and mid-level clouds is strongly outweighed by the overestimation of low-level clouds. Numerous sensitivity studies with HIRHAM5-SCM suggest (1) the parameter tuning, enabling a more efficient Bergeron-Findeisen process, combined with (2) an extension of the prognostic-statistical (PS) cloud scheme, enabling the use of negatively skewed beta distributions. This improved model setup was then used in a corresponding HIRHAM5 sensitivity run (HH5sens). While the simulated high- and mid-level cloud cover is improved only to a limited extent, the large overestimation of low-level clouds can be systematically and significantly reduced, especially over sea ice. Consequently, the multi-year annual mean area average of total cloud cover with respect to sea ice is almost 14% lower than in HH5ctrl. Overall, HH5sens slightly underestimates the observed total cloud cover but shows a halved multi-year annual mean bias of 2.2% relative to CPR/CALIOP at all latitudes north of 60° N. Importantly, HH5sens produces a more realistic ratio between the cloud water and ice content. The considerably improved cloud simulation manifests in a more correct radiative transfer and better energy budget in the atmospheric boundary layer and results also in a more realistic surface energy budget associated with more reasonable turbulent fluxes. All this mitigates the positive temperature, relative humidity and horizontal wind speed biases in the lower model levels.

Generation of 2D Land Cover Maps for Urban Areas Using Decision Tree Classification

NASA Astrophysics Data System (ADS)

Höhle, J.

2014-09-01

A 2D land cover map can automatically and efficiently be generated from high-resolution multispectral aerial images. First, a digital surface model is produced and each cell of the elevation model is then supplemented with attributes. A decision tree classification is applied to extract map objects like buildings, roads, grassland, trees, hedges, and walls from such an "intelligent" point cloud. The decision tree is derived from training areas which borders are digitized on top of a false-colour orthoimage. The produced 2D land cover map with six classes is then subsequently refined by using image analysis techniques. The proposed methodology is described step by step. The classification, assessment, and refinement is carried out by the open source software "R"; the generation of the dense and accurate digital surface model by the "Match-T DSM" program of the Trimble Company. A practical example of a 2D land cover map generation is carried out. Images of a multispectral medium-format aerial camera covering an urban area in Switzerland are used. The assessment of the produced land cover map is based on class-wise stratified sampling where reference values of samples are determined by means of stereo-observations of false-colour stereopairs. The stratified statistical assessment of the produced land cover map with six classes and based on 91 points per class reveals a high thematic accuracy for classes "building" (99 %, 95 % CI: 95 %-100 %) and "road and parking lot" (90 %, 95 % CI: 83 %-95 %). Some other accuracy measures (overall accuracy, kappa value) and their 95 % confidence intervals are derived as well. The proposed methodology has a high potential for automation and fast processing and may be applied to other scenes and sensors.

3D modeling of the laterites on top of the Koniambo Massif, New Caledonia: refinement of the per descensum lateritic model for nickel mineralization

NASA Astrophysics Data System (ADS)

Quesnel, Benoît; de Veslud, Christian Le Carlier; Boulvais, Philippe; Gautier, Pierre; Cathelineau, Michel; Drouillet, Maxime

2017-10-01

Resulting from the weathering of the Peridotite Nappe, laterites are abundant in New Caledonia and host one of the largest nickel deposits worldwide. This work presents a 3D model of the Koniambo nickel laterite ore deposit. It shows that the laterites are located along the ridges of the massif and organized as hectometric-sized patches obliquely cut by the topography and distributed at various elevations. Three kinds of geometry were observed: (i) a thick laterite cover (between 20 and 40 m) overlying saprolite and mainly localized on topographic highs, (ii) a thin laterite cover (from a few meters to 20 m) mainly localized on areas with gentle slopes, and (iii) exposure of saprolite without laterite cover. Our data show that Ni-rich and Ni-poor areas are organized as hectometric-sized patches which broadly correlate with the distribution of the laterite thickness. The highest Ni areas are localized on slopes where laterite cover is thin or absent. The areas with lowest Ni are located in topographic highs under the thickest laterite cover. The vertical Ni mass balance for each borehole shows that, in areas with thick laterite cover, Ni is sub-equilibrated to slightly depleted whereas in areas with thin laterite cover, Ni is enriched. This suggests the existence of lateral infiltration of water rich in dissolved Ni, from areas such as topographic highs to downstream slope areas, in a process leading to enrichment of saprolite in Ni in slope areas. Mechanical transport and leaching of laterite material on slopes, including Ni-bearing material, could also contribute to local enrichment of Ni in the saprolite.

Landsat 8 Multispectral and Pansharpened Imagery Processing on the Study of Civil Engineering Issues

NASA Astrophysics Data System (ADS)

Lazaridou, M. A.; Karagianni, A. Ch.

2016-06-01

Scientific and professional interests of civil engineering mainly include structures, hydraulics, geotechnical engineering, environment, and transportation issues. Topics included in the context of the above may concern urban environment issues, urban planning, hydrological modelling, study of hazards and road construction. Land cover information contributes significantly on the study of the above subjects. Land cover information can be acquired effectively by visual image interpretation of satellite imagery or after applying enhancement routines and also by imagery classification. The Landsat Data Continuity Mission (LDCM - Landsat 8) is the latest satellite in Landsat series, launched in February 2013. Landsat 8 medium spatial resolution multispectral imagery presents particular interest in extracting land cover, because of the fine spectral resolution, the radiometric quantization of 12bits, the capability of merging the high resolution panchromatic band of 15 meters with multispectral imagery of 30 meters as well as the policy of free data. In this paper, Landsat 8 multispectral and panchromatic imageries are being used, concerning surroundings of a lake in north-western Greece. Land cover information is extracted, using suitable digital image processing software. The rich spectral context of the multispectral image is combined with the high spatial resolution of the panchromatic image, applying image fusion - pansharpening, facilitating in this way visual image interpretation to delineate land cover. Further processing concerns supervised image classification. The classification of pansharpened image preceded multispectral image classification. Corresponding comparative considerations are also presented.

Accelerating Drug Development: Antiviral Therapies for Emerging Viruses as a Model.

PubMed

Everts, Maaike; Cihlar, Tomas; Bostwick, J Robert; Whitley, Richard J

2017-01-06

Drug discovery and development is a lengthy and expensive process. Although no one, simple, single solution can significantly accelerate this process, steps can be taken to avoid unnecessary delays. Using the development of antiviral therapies as a model, we describe options for acceleration that cover target selection, assay development and high-throughput screening, hit confirmation, lead identification and development, animal model evaluations, toxicity studies, regulatory issues, and the general drug discovery and development infrastructure. Together, these steps could result in accelerated timelines for bringing antiviral therapies to market so they can treat emerging infections and reduce human suffering.

Sensitivity of global terrestrial carbon cycle dynamics to variability in satellite-observed burned area

NASA Astrophysics Data System (ADS)

Poulter, Benjamin; Cadule, Patricia; Cheiney, Audrey; Ciais, Philippe; Hodson, Elke; Peylin, Philippe; Plummer, Stephen; Spessa, Allan; Saatchi, Sassan; Yue, Chao; Zimmermann, Niklaus E.

2015-02-01

Fire plays an important role in terrestrial ecosystems by regulating biogeochemistry, biogeography, and energy budgets, yet despite the importance of fire as an integral ecosystem process, significant advances remain to improve its prognostic representation in carbon cycle models. To recommend and to help prioritize model improvements, this study investigates the sensitivity of a coupled global biogeography and biogeochemistry model, LPJ, to observed burned area measured by three independent satellite-derived products, GFED v3.1, L3JRC, and GlobCarbon. Model variables are compared with benchmarks that include pantropical aboveground biomass, global tree cover, and CO2 and CO trace gas concentrations. Depending on prescribed burned area product, global aboveground carbon stocks varied by 300 Pg C, and woody cover ranged from 50 to 73 Mkm2. Tree cover and biomass were both reduced linearly with increasing burned area, i.e., at regional scales, a 10% reduction in tree cover per 1000 km2, and 0.04-to-0.40 Mg C reduction per 1000 km2. In boreal regions, satellite burned area improved simulated tree cover and biomass distributions, but in savanna regions, model-data correlations decreased. Global net biome production was relatively insensitive to burned area, and the long-term land carbon sink was robust, 2.5 Pg C yr-1, suggesting that feedbacks from ecosystem respiration compensated for reductions in fuel consumption via fire. CO2 transport provided further evidence that heterotrophic respiration compensated any emission reductions in the absence of fire, with minor differences in modeled CO2 fluxes among burned area products. CO was a more sensitive indicator for evaluating fire emissions, with MODIS-GFED burned area producing CO concentrations largely in agreement with independent observations in high latitudes. This study illustrates how ensembles of burned area data sets can be used to diagnose model structures and parameters for further improvement and also highlights the importance in considering uncertainties and variability in observed burned area data products for model applications.

Impact of wave mixing on the sea ice cover

NASA Astrophysics Data System (ADS)

Rynders, Stefanie; Aksenov, Yevgeny; Madec, Gurvan; Nurser, George; Feltham, Daniel

2017-04-01

As information on surface waves in ice-covered regions becomes available in ice-ocean models, there is an opportunity to model wave-related processes more accurate. Breaking waves cause mixing of the upper water column and present mixing schemes in ocean models take this into account through surface roughness. A commonly used approach is to calculate surface roughness from significant wave height, parameterised from wind speed. We present results from simulations using modelled significant wave height instead, which accounts for the presence of sea ice and the effect of swell. The simulations use the NEMO ocean model coupled to the CICE sea ice model, with wave information from the ECWAM model of the European Centre for Medium-Range Weather Forecasts (ECMWF). The new waves-in-ice module allows waves to propagate in sea ice and attenuates waves according to multiple scattering and non-elastic losses. It is found that in the simulations with wave mixing the mixed layer depth (MLD) under ice cover is reduced, since the parameterisation from wind speed overestimates wave height in the ice-covered regions. The MLD change, in turn, affects sea ice concentration and ice thickness. In the Arctic, reduced MLD in winter translates into increased ice thicknesses overall, with higher increases in the Western Arctic and decreases along the Siberian coast. In summer, shallowing of the mixed layer results in more heat accumulating in the surface ocean, increasing ice melting. In the Southern Ocean the meridional gradient in ice thickness and concentration is increased. We argue that coupling waves with sea ice - ocean models can reduce negative biases in sea ice cover, affecting the distribution of nutrients and, thus, biological productivity and ecosystems. This coupling will become more important in the future, when wave heights in a large part of the Arctic are expected to increase due to sea ice retreat and a larger wave fetch. Therefore, wave mixing constitutes a possible positive feedback mechanism.

Monitoring, analyzing and simulating of spatial-temporal changes of landscape pattern over mining area

NASA Astrophysics Data System (ADS)

Liu, Pei; Han, Ruimei; Wang, Shuangting

2014-11-01

According to the merits of remotely sensed data in depicting regional land cover and Land changes, multi- objective information processing is employed to remote sensing images to analyze and simulate land cover in mining areas. In this paper, multi-temporal remotely sensed data were selected to monitor the pattern, distri- bution and trend of LUCC and predict its impacts on ecological environment and human settlement in mining area. The monitor, analysis and simulation of LUCC in this coal mining areas are divided into five steps. The are information integration of optical and SAR data, LULC types extraction with SVM classifier, LULC trends simulation with CA Markov model, landscape temporal changes monitoring and analysis with confusion matrixes and landscape indices. The results demonstrate that the improved data fusion algorithm could make full use of information extracted from optical and SAR data; SVM classifier has an efficient and stable ability to obtain land cover maps, which could provide a good basis for both land cover change analysis and trend simulation; CA Markov model is able to predict LULC trends with good performance, and it is an effective way to integrate remotely sensed data with spatial-temporal model for analysis of land use / cover change and corresponding environmental impacts in mining area. Confusion matrixes are combined with landscape indices to evaluation and analysis show that, there was a sustained downward trend in agricultural land and bare land, but a continues growth trend tendency in water body, forest and other lands, and building area showing a wave like change, first increased and then decreased; mining landscape has undergone a from small to large and large to small process of fragmentation, agricultural land is the strongest influenced landscape type in this area, and human activities are the primary cause, so the problem should be pay more attentions by government and other organizations.

A land cover change detection and classification protocol for updating Alaska NLCD 2001 to 2011

USGS Publications Warehouse

Jin, Suming; Yang, Limin; Zhu, Zhe; Homer, Collin G.

2017-01-01

Monitoring and mapping land cover changes are important ways to support evaluation of the status and transition of ecosystems. The Alaska National Land Cover Database (NLCD) 2001 was the first 30-m resolution baseline land cover product of the entire state derived from circa 2001 Landsat imagery and geospatial ancillary data. We developed a comprehensive approach named AKUP11 to update Alaska NLCD from 2001 to 2011 and provide a 10-year cyclical update of the state's land cover and land cover changes. Our method is designed to characterize the main land cover changes associated with different drivers, including the conversion of forests to shrub and grassland primarily as a result of wildland fire and forest harvest, the vegetation successional processes after disturbance, and changes of surface water extent and glacier ice/snow associated with weather and climate changes. For natural vegetated areas, a component named AKUP11-VEG was developed for updating the land cover that involves four major steps: 1) identify the disturbed and successional areas using Landsat images and ancillary datasets; 2) update the land cover status for these areas using a SKILL model (System of Knowledge-based Integrated-trajectory Land cover Labeling); 3) perform decision tree classification; and 4) develop a final land cover and land cover change product through the postprocessing modeling. For water and ice/snow areas, another component named AKUP11-WIS was developed for initial land cover change detection, removal of the terrain shadow effects, and exclusion of ephemeral snow changes using a 3-year MODIS snow extent dataset from 2010 to 2012. The overall approach was tested in three pilot study areas in Alaska, with each area consisting of four Landsat image footprints. The results from the pilot study show that the overall accuracy in detecting change and no-change is 90% and the overall accuracy of the updated land cover label for 2011 is 86%. The method provided a robust, consistent, and efficient means for capturing major disturbance events and updating land cover for Alaska. The method has subsequently been applied to generate the land cover and land cover change products for the entire state of Alaska.

PREDICTING THE RELATIVE IMPACTS OF URBAN DEVELOPMENT POLICIES AND ON-ROAD VEHICLE TECHNOLOGIES ON AIR QUALITY IN THE UNITED STATES: MODELING AND ANALYSIS OF A CASE STUDY IN AUSTIN, TEXAS

EPA Science Inventory

Urban development results in changes to land use and land cover and, consequently, to biogenic and anthropogenic emissions, meteorological processes, and processes such as dry deposition that influence future predictions of air quality. This study examines the impacts of alter...

Hydrometric, Hydrochemical, and Hydrogeophysical Runoff Characterization Across Multiple Land Covers in the Agua Salud Project, Panama

NASA Astrophysics Data System (ADS)

Litt, Guy Finley

As the Panama Canal Authority faces sensitivity to water shortages, managing water resources becomes crucial for the global shipping industry's security. These studies address knowledge gaps in tropical water resources to aid hydrological model development and validation. Field-based hydrological investigations in the Agua Salud Project within the Panama Canal Watershed employed multiple tools across a variety of land covers to investigate hydrological processes. Geochemical tracers informed where storm runoff in a stream comes from and identified electrical conductivity (EC) as an economical, high sample frequency tracer during small storms. EC-based hydrograph separation coupled with hydrograph recession rate analyses identified shallow and deep groundwater storage-discharge relationships that varied by season and land cover. A series of plot-scale electrical resistivity imaging geophysical experiments coupled with rainfall simulation characterized subsurface flow pathway behavior and quantified respectively increasing infiltration rates across pasture, 10 year old secondary succession forest, teak (tectona grandis), and 30 year old secondary succession forest land covers. Additional soil water, groundwater, and geochemical studies informed conceptual model development in subsurface flow pathways and groundwater, and identified future research needs.

Advanced hierarchical distance sampling

USGS Publications Warehouse

Royle, Andy

2016-01-01

In this chapter, we cover a number of important extensions of the basic hierarchical distance-sampling (HDS) framework from Chapter 8. First, we discuss the inclusion of “individual covariates,” such as group size, in the HDS model. This is important in many surveys where animals form natural groups that are the primary observation unit, with the size of the group expected to have some influence on detectability. We also discuss HDS integrated with time-removal and double-observer or capture-recapture sampling. These “combined protocols” can be formulated as HDS models with individual covariates, and thus they have a commonality with HDS models involving group structure (group size being just another individual covariate). We cover several varieties of open-population HDS models that accommodate population dynamics. On one end of the spectrum, we cover models that allow replicate distance sampling surveys within a year, which estimate abundance relative to availability and temporary emigration through time. We consider a robust design version of that model. We then consider models with explicit dynamics based on the Dail and Madsen (2011) model and the work of Sollmann et al. (2015). The final major theme of this chapter is relatively newly developed spatial distance sampling models that accommodate explicit models describing the spatial distribution of individuals known as Point Process models. We provide novel formulations of spatial DS and HDS models in this chapter, including implementations of those models in the unmarked package using a hack of the pcount function for N-mixture models.

The invasive species Ulex europaeus (Fabaceae) shows high dynamism in a fragmented landscape of south-central Chile.

PubMed

Altamirano, Adison; Cely, Jenny Paola; Etter, Andrés; Miranda, Alejandro; Fuentes-Ramirez, Andres; Acevedo, Patricio; Salas, Christian; Vargas, Rodrigo

2016-08-01

Ulex europaeus (gorse) is an invasive shrub deemed as one of the most invasive species in the world. U. europaeus is widely distributed in the south-central area of Chile, which is considered a world hotspot for biodiversity conservation. In addition to its negative effects on the biodiversity of natural ecosystems, U. europaeus is one of the most severe pests for agriculture and forestry. Despite its importance as an invasive species, U. europaeus has been little studied. Although information exists on the potential distribution of the species, the interaction of the invasion process with the spatial dynamic of the landscape and the landscape-scale factors that control the presence or absence of the species is still lacking. We studied the spatial and temporal dynamics of the landscape and how these relate to U. europaeus invasion in south-central Chile. We used supervised classification of satellite images to determine the spatial distribution of the species and other land covers for the years 1986 and 2003, analysing the transitions between the different land covers. We used logistic regression for modelling the increase, decrease and permanence of U. europaeus invasion considering landscape variables. Results showed that the species covers only around 1 % of the study area and showed a 42 % reduction in area for the studied period. However, U. europaeus was the cover type which presented the greatest dynamism in the landscape. We found a strong relationship between changes in land cover and the invasion process, especially connected with forest plantations of exotic species, which promotes the displacement of U. europaeus. The model of gorse cover increase presented the best performance, and the most important predictors were distance to seed source and landscape complexity index. Our model predicted high spread potential of U. europaeus in areas of high conservation value. We conclude that proper management for this invasive species must take into account the spatial dynamics of the landscape within the invaded area in order to address containment, control or mitigation of the invasion.

How cells engulf: a review of theoretical approaches to phagocytosis

NASA Astrophysics Data System (ADS)

Richards, David M.; Endres, Robert G.

2017-12-01

Phagocytosis is a fascinating process whereby a cell surrounds and engulfs particles such as bacteria and dead cells. This is crucial both for single-cell organisms (as a way of acquiring nutrients) and as part of the immune system (to destroy foreign invaders). This whole process is hugely complex and involves multiple coordinated events such as membrane remodelling, receptor motion, cytoskeleton reorganisation and intracellular signalling. Because of this, phagocytosis is an excellent system for theoretical study, benefiting from biophysical approaches combined with mathematical modelling. Here, we review these theoretical approaches and discuss the recent mathematical and computational models, including models based on receptors, models focusing on the forces involved, and models employing energetic considerations. Along the way, we highlight a beautiful connection to the physics of phase transitions, consider the role of stochasticity, and examine links between phagocytosis and other types of endocytosis. We cover the recently discovered multistage nature of phagocytosis, showing that the size of the phagocytic cup grows in distinct stages, with an initial slow stage followed by a much quicker second stage starting around half engulfment. We also address the issue of target shape dependence, which is relevant to both pathogen infection and drug delivery, covering both one-dimensional and two-dimensional results. Throughout, we pay particular attention to recent experimental techniques that continue to inform the theoretical studies and provide a means to test model predictions. Finally, we discuss population models, connections to other biological processes, and how physics and modelling will continue to play a key role in future work in this area.

Early-warning signals for catastrophic soil degradation

NASA Astrophysics Data System (ADS)

Karssenberg, Derek

2010-05-01

Many earth systems have critical thresholds at which the system shifts abruptly from one state to another. Such critical transitions have been described, among others, for climate, vegetation, animal populations, and geomorphology. Predicting the timing of critical transitions before they are reached is of importance because of the large impact on nature and society associated with the transition. However, it is notably difficult to predict the timing of a transition. This is because the state variables of the system show little change before the threshold is reached. As a result, the precision of field observations is often too low to provide predictions of the timing of a transition. A possible solution is the use of spatio-temporal patterns in state variables as leading indicators of a transition. It is becoming clear that the critically slowing down of a system causes spatio-temporal autocorrelation and variance to increase before the transition. Thus, spatio-temporal patterns are important candidates for early-warning signals. In this research we will show that these early-warning signals also exist in geomorphological systems. We consider a modelled vegetation-soil system under a gradually increasing grazing pressure causing an abrupt shift towards extensive soil degradation. It is shown that changes in spatio-temporal patterns occur well ahead of this catastrophic transition. A distributed model describing the coupled processes of vegetation growth and geomorphological denudation is adapted. The model uses well-studied simple process representations for vegetation and geomorphology. A logistic growth model calculates vegetation cover as a function of grazing pressure and vegetation growth rate. Evolution of the soil thickness is modelled by soil creep and wash processes, as a function of net rain reaching the surface. The vegetation and soil system are coupled by 1) decreasing vegetation growth with decreasing soil thickness and 2) increasing soil wash with decreasing vegetation cover. The model describes a critical, catastrophic transition of an underexploited system with low grazing pressure towards an overexploited system. The underexploited state has high vegetation cover and well developed soils, while the overexploited state has low vegetation cover and largely degraded soils. We first show why spatio-temporal patterns in vegetation cover, morphology, erosion rate, and sediment load should be expected to change well before the critical transition towards the overexploited state. Subsequently, spatio-temporal patterns are quantified by calculating statistics, in particular first order statistics and autocorrelation in space and time. It is shown that these statistics gradually change before the transition is reached. This indicates that the statistics may serve as early-warning signals in real-world applications. We also discuss the potential use of remote sensing to predict the critical transition in real-world landscapes.

User Generated Spatial Content Sources for Land Use/Land Cover Validation Purposes: Suitability Analysis and Integration Model

NASA Astrophysics Data System (ADS)

Estima, Jacinto Paulo Simoes

Traditional geographic information has been produced by mapping agencies and corporations, using high skilled people as well as expensive precision equipment and procedures, in a very costly approach. The production of land use and land cover databases are just one example of such traditional approach. On the other side, The amount of Geographic Information created and shared by citizens through the Web has been increasing exponentially during the last decade, resulting from the emergence and popularization of technologies such as the Web 2.0, cloud computing, GPS, smart phones, among others. Such comprehensive amount of free geographic data might have valuable information to extract and thus opening great possibilities to improve significantly the production of land use and land cover databases. In this thesis we explored the feasibility of using geographic data from different user generated spatial content initiatives in the process of land use and land cover database production. Data from Panoramio, Flickr and OpenStreetMap were explored in terms of their spatial and temporal distribution, and their distribution over the different land use and land cover classes. We then proposed a conceptual model to integrate data from suitable user generated spatial content initiatives based on identified dissimilarities among a comprehensive list of initiatives. Finally we developed a prototype implementing the proposed integration model, which was then validated by using the prototype to solve four identified use cases. We concluded that data from user generated spatial content initiatives has great value but should be integrated to increase their potential. The possibility of integrating data from such initiatives in an integration model was proved. Using the developed prototype, the relevance of the integration model was also demonstrated for different use cases. None None None

The Resource, Spring 2002

DTIC Science & Technology

2002-01-01

wrappers to other widely used languages, namely TCL/TK, Java, and Python . VTK is very powerful and covers polygonal models and image processing classes and...follows: � Large Data Visualization and Rendering � Information Visualization for Beginners � Rendering and Visualization in Parallel Environments

Mathematics and Information Retrieval.

ERIC Educational Resources Information Center

Salton, Gerald

1979-01-01

Examines the main mathematical approaches to information retrieval, including both algebraic and probabilistic models, and describes difficulties which impede formalization of information retrieval processes. A number of developments are covered where new theoretical understandings have directly led to improved retrieval techniques and operations.…

The potential for machine learning algorithms to improve and reduce the cost of 3-dimensional printing for surgical planning.

PubMed

Huff, Trevor J; Ludwig, Parker E; Zuniga, Jorge M

2018-05-01

3D-printed anatomical models play an important role in medical and research settings. The recent successes of 3D anatomical models in healthcare have led many institutions to adopt the technology. However, there remain several issues that must be addressed before it can become more wide-spread. Of importance are the problems of cost and time of manufacturing. Machine learning (ML) could be utilized to solve these issues by streamlining the 3D modeling process through rapid medical image segmentation and improved patient selection and image acquisition. The current challenges, potential solutions, and future directions for ML and 3D anatomical modeling in healthcare are discussed. Areas covered: This review covers research articles in the field of machine learning as related to 3D anatomical modeling. Topics discussed include automated image segmentation, cost reduction, and related time constraints. Expert commentary: ML-based segmentation of medical images could potentially improve the process of 3D anatomical modeling. However, until more research is done to validate these technologies in clinical practice, their impact on patient outcomes will remain unknown. We have the necessary computational tools to tackle the problems discussed. The difficulty now lies in our ability to collect sufficient data.

Urey prize lecture - Water on Mars

NASA Technical Reports Server (NTRS)

Squyres, Steven W.

1989-01-01

Taking the heat-transport physics of ice-covered lakes in the Dry Valleys of Antarctica as a model, it is presently suggested that liquid water lakes could have persisted for significant periods under protective ice covers in the Valles Marineris depressions of Mars. Calculations of ground ice thermodynamic stability in a Martian setting indicate that they may exist close to the surface at high latitudes, but are able to persist near the equator only at substantial depths. Such Martian landforms as terrain-softening are attributable to the creep of the Martian regolith under the influence of ground-ice deformation; FEM modeling of the flow process implies terrain-softening to be a near-surface phenomenon.

Facilitation drives 65 years of vegetation change in the Sonoran Desert

USGS Publications Warehouse

Butterfield, Bradley J.; Betancourt, Julio L.; Turner, Raymond M.; Briggs, John M.

2010-01-01

Ecological processes of low-productivity ecosystems have long been considered to be driven by abiotic controls with biotic interactions playing an insignificant role. However, existing studies present conflicting evidence concerning the roles of these factors, in part due to the short temporal extent of most data sets and inability to test indirect effects of environmental variables modulated by biotic interactions. Using structural equation modeling to analyze 65 years of perennial vegetation change in the Sonoran Desert, we found that precipitation had a stronger positive effect on recruitment beneath existing canopies than in open microsites due to reduced evaporation rates. Variation in perennial canopy cover had additional facilitative effects on juvenile recruitment, which was indirectly driven by effects of density and precipitation on cover. Mortality was strongly influenced by competition as indicated by negative density-dependence, whereas precipitation had no effect. The combined direct, indirect, and interactive facilitative effects of precipitation and cover on recruitment were substantial, as was the effect of competition on mortality, providing strong evidence for dual control of community dynamics by climate and biotic interactions. Through an empirically derived simulation model, we also found that the positive feedback of density on cover produces unique temporal abundance patterns, buffering changes in abundance from high frequency variation in precipitation, amplifying effects of low frequency variation, and decoupling community abundance from precipitation patterns at high abundance. Such dynamics should be generally applicable to low-productivity systems in which facilitation is important and can only be understood within the context of long-term variation in climatic patterns. This predictive model can be applied to better manage low-productivity ecosystems, in which variation in biogeochemical processes and trophic dynamics may be driven by positive density-dependent feedbacks that influence temporal abundance and productivity patterns.

Up-scaling Stream Ecosystem Processes to Predict the Effects of Land Cover Change at a Watershed Scale in the Atlantic Tropical Rainforest.

NASA Astrophysics Data System (ADS)

Tromboni, F.; Feijó de Lima, R.; Silva-Júnior, E. F.; Lourenço-Amorim, C.; Zandoná, E.; Moulton, T. P.; Da Silva, B. S.; Silva-Araújo, M.; Thomas, S. A.

2015-12-01

Riparian land-cover change (LCC) causes a cascade of subsequent hierarchical effects that propagate through abiotic compartments until reaching the biota, altering stream ecosystem functioning. Due to the movement of water downstream, these lateral effects co-occur with longitudinal influences. We investigated both the lateral and longitudinal effects of deforestation in four streams in the Atlantic tropical rainforest of Brazil. We collected physical-chemical, geomorphic, hydrological data and samples of macroinvertebrates assemblages. We then categorized land cover at different scales (from different riparian and reach buffer sizes to sub and total watershed) using a SPOT-5 satellite image and ArcGIS. We also carried out a series of experiments along the streams to understand: 1) the mechanisms by which LCC affects periphyton and how these changes alter metabolism and nutrient uptake rates; 2) the downstream distance at which periphyton and the associated variables change in the transitions from one riparian category to the other. We used (i) a path analysis to test if our hypothesized land-cover cascade model described our data and (ii) non-linear models to describe the longitudinal effect on each variable. Our results showed that deforestation produced a range of physical changes at different spatial scale, longitudinally altering periphyton taxonomic composition (taxa depending on light), stoichiometry (nutritionally richer with increasing deforestation) and growth rates (greater in deforested). Macroinvertebrate assemblages behaved similarly to chlorophyll a in response to forest loss. Respiration rate increased with deforestation probably due to higher nutrient concentrations but primary production did not increase. Models were used to upscale LCC impacts on ecosystem processes from local scale experiments to landscape and our work has important implications for socio-economic decisions concerning ecosystem management and conservation.

The importance of parameterization when simulating the hydrologic response of vegetative land-cover change

NASA Astrophysics Data System (ADS)

White, Jeremy; Stengel, Victoria; Rendon, Samuel; Banta, John

2017-08-01

Computer models of hydrologic systems are frequently used to investigate the hydrologic response of land-cover change. If the modeling results are used to inform resource-management decisions, then providing robust estimates of uncertainty in the simulated response is an important consideration. Here we examine the importance of parameterization, a necessarily subjective process, on uncertainty estimates of the simulated hydrologic response of land-cover change. Specifically, we applied the soil water assessment tool (SWAT) model to a 1.4 km2 watershed in southern Texas to investigate the simulated hydrologic response of brush management (the mechanical removal of woody plants), a discrete land-cover change. The watershed was instrumented before and after brush-management activities were undertaken, and estimates of precipitation, streamflow, and evapotranspiration (ET) are available; these data were used to condition and verify the model. The role of parameterization in brush-management simulation was evaluated by constructing two models, one with 12 adjustable parameters (reduced parameterization) and one with 1305 adjustable parameters (full parameterization). Both models were subjected to global sensitivity analysis as well as Monte Carlo and generalized likelihood uncertainty estimation (GLUE) conditioning to identify important model inputs and to estimate uncertainty in several quantities of interest related to brush management. Many realizations from both parameterizations were identified as behavioral in that they reproduce daily mean streamflow acceptably well according to Nash-Sutcliffe model efficiency coefficient, percent bias, and coefficient of determination. However, the total volumetric ET difference resulting from simulated brush management remains highly uncertain after conditioning to daily mean streamflow, indicating that streamflow data alone are not sufficient to inform the model inputs that influence the simulated outcomes of brush management the most. Additionally, the reduced-parameterization model grossly underestimates uncertainty in the total volumetric ET difference compared to the full-parameterization model; total volumetric ET difference is a primary metric for evaluating the outcomes of brush management. The failure of the reduced-parameterization model to provide robust uncertainty estimates demonstrates the importance of parameterization when attempting to quantify uncertainty in land-cover change simulations.

The importance of parameterization when simulating the hydrologic response of vegetative land-cover change

USGS Publications Warehouse

White, Jeremy; Stengel, Victoria G.; Rendon, Samuel H.; Banta, John

2017-01-01

Computer models of hydrologic systems are frequently used to investigate the hydrologic response of land-cover change. If the modeling results are used to inform resource-management decisions, then providing robust estimates of uncertainty in the simulated response is an important consideration. Here we examine the importance of parameterization, a necessarily subjective process, on uncertainty estimates of the simulated hydrologic response of land-cover change. Specifically, we applied the soil water assessment tool (SWAT) model to a 1.4 km2 watershed in southern Texas to investigate the simulated hydrologic response of brush management (the mechanical removal of woody plants), a discrete land-cover change. The watershed was instrumented before and after brush-management activities were undertaken, and estimates of precipitation, streamflow, and evapotranspiration (ET) are available; these data were used to condition and verify the model. The role of parameterization in brush-management simulation was evaluated by constructing two models, one with 12 adjustable parameters (reduced parameterization) and one with 1305 adjustable parameters (full parameterization). Both models were subjected to global sensitivity analysis as well as Monte Carlo and generalized likelihood uncertainty estimation (GLUE) conditioning to identify important model inputs and to estimate uncertainty in several quantities of interest related to brush management. Many realizations from both parameterizations were identified as behavioral in that they reproduce daily mean streamflow acceptably well according to Nash–Sutcliffe model efficiency coefficient, percent bias, and coefficient of determination. However, the total volumetric ET difference resulting from simulated brush management remains highly uncertain after conditioning to daily mean streamflow, indicating that streamflow data alone are not sufficient to inform the model inputs that influence the simulated outcomes of brush management the most. Additionally, the reduced-parameterization model grossly underestimates uncertainty in the total volumetric ET difference compared to the full-parameterization model; total volumetric ET difference is a primary metric for evaluating the outcomes of brush management. The failure of the reduced-parameterization model to provide robust uncertainty estimates demonstrates the importance of parameterization when attempting to quantify uncertainty in land-cover change simulations.

Assessing winter cover crop nutrient uptake efficiency using a water quality simulation model

NASA Astrophysics Data System (ADS)

Yeo, I.-Y.; Lee, S.; Sadeghi, A. M.; Beeson, P. C.; Hively, W. D.; McCarty, G. W.; Lang, M. W.

2013-11-01

Winter cover crops are an effective conservation management practice with potential to improve water quality. Throughout the Chesapeake Bay Watershed (CBW), which is located in the Mid-Atlantic US, winter cover crop use has been emphasized and federal and state cost-share programs are available to farmers to subsidize the cost of winter cover crop establishment. The objective of this study was to assess the long-term effect of planting winter cover crops at the watershed scale and to identify critical source areas of high nitrate export. A physically-based watershed simulation model, Soil and Water Assessment Tool (SWAT), was calibrated and validated using water quality monitoring data and satellite-based estimates of winter cover crop species performance to simulate hydrological processes and nutrient cycling over the period of 1991-2000. Multiple scenarios were developed to obtain baseline information on nitrate loading without winter cover crops planted and to investigate how nitrate loading could change with different winter cover crop planting scenarios, including different species, planting times, and implementation areas. The results indicate that winter cover crops had a negligible impact on water budget, but significantly reduced nitrate leaching to groundwater and delivery to the waterways. Without winter cover crops, annual nitrate loading was approximately 14 kg ha-1, but it decreased to 4.6-10.1 kg ha-1 with winter cover crops resulting in a reduction rate of 27-67% at the watershed scale. Rye was most effective, with a potential to reduce nitrate leaching by up to 93% with early planting at the field scale. Early planting of winter cover crops (~30 days of additional growing days) was crucial, as it lowered nitrate export by an additional ~2 kg ha-1 when compared to late planting scenarios. The effectiveness of cover cropping increased with increasing extent of winter cover crop implementation. Agricultural fields with well-drained soils and those that were more frequently used to grow corn had a higher potential for nitrate leaching and export to the waterways. This study supports the effective implement of winter cover crop programs, in part by helping to target critical pollution source areas for winter cover crop implementation.

Potential and limitations of webcam images for snow cover monitoring in the Swiss Alps

NASA Astrophysics Data System (ADS)

Dizerens, Céline; Hüsler, Fabia; Wunderle, Stefan

2017-04-01

In Switzerland, several thousands of outdoor webcams are currently connected to the Internet. They deliver freely available images that can be used to analyze snow cover variability on a high spatio-temporal resolution. To make use of this big data source, we have implemented a webcam-based snow cover mapping procedure, which allows to almost automatically derive snow cover maps from such webcam images. As there is mostly no information about the webcams and its parameters available, our registration approach automatically resolves these parameters (camera orientation, principal point, field of view) by using an estimate of the webcams position, the mountain silhouette, and a high-resolution digital elevation model (DEM). Combined with an automatic snow classification and an image alignment using SIFT features, our procedure can be applied to arbitrary images to generate snow cover maps with a minimum of effort. Resulting snow cover maps have the same resolution as the digital elevation model and indicate whether each grid cell is snow-covered, snow-free, or hidden from webcams' positions. Up to now, we processed images of about 290 webcams from our archive, and evaluated images of 20 webcams using manually selected ground control points (GCPs) to evaluate the mapping accuracy of our procedure. We present methodological limitations and ongoing improvements, show some applications of our snow cover maps, and demonstrate that webcams not only offer a great opportunity to complement satellite-derived snow retrieval under cloudy conditions, but also serve as a reference for improved validation of satellite-based approaches.

Annual grass invasion in sagebrush-steppe: The relative importance of climate, soil properties and biotic interactions

USGS Publications Warehouse

Bansal, Sheel; Sheley, Roger L.

2016-01-01

The invasion by winter-annual grasses (AGs) such as Bromus tectorum into sagebrush steppe throughout the western USA is a classic example of a biological invasion with multiple, interacting climate, soil and biotic factors driving the invasion, although few studies have examined all components together. Across a 6000-km2 area of the northern Great Basin, we conducted a field assessment of 100 climate, soil, and biotic (functional group abundances, diversity) factors at each of 90 sites that spanned an invasion gradient ranging from 0 to 100 % AG cover. We first determined which biotic and abiotic factors had the strongest correlative relationships with AGs and each resident functional group. We then used regression and structural equation modeling to explore how multiple ecological factors interact to influence AG abundance. Among biotic interactions, we observed negative relationships between AGs and biodiversity, perennial grass cover, resident species richness, biological soil crust cover and shrub density, whereas perennial and annual forb cover, tree cover and soil microbial biomass had no direct linkage to AG. Among abiotic factors, AG cover was strongly related to climate (increasing cover with increasing temperature and aridity), but had weak relationships with soil factors. Our structural equation model showed negative effects of perennial grasses and biodiversity on AG cover while integrating the negative effects of warmer climate and positive influence of belowground processes on resident functional groups. Our findings illustrate the relative importance of biotic interactions and climate on invasive abundance, while soil properties appear to have stronger relationships with resident biota than with invasives.

General form of a cooperative gradual maximal covering location problem

NASA Astrophysics Data System (ADS)

Bagherinejad, Jafar; Bashiri, Mahdi; Nikzad, Hamideh

2018-07-01

Cooperative and gradual covering are two new methods for developing covering location models. In this paper, a cooperative maximal covering location-allocation model is developed (CMCLAP). In addition, both cooperative and gradual covering concepts are applied to the maximal covering location simultaneously (CGMCLP). Then, we develop an integrated form of a cooperative gradual maximal covering location problem, which is called a general CGMCLP. By setting the model parameters, the proposed general model can easily be transformed into other existing models, facilitating general comparisons. The proposed models are developed without allocation for physical signals and with allocation for non-physical signals in discrete location space. Comparison of the previously introduced gradual maximal covering location problem (GMCLP) and cooperative maximal covering location problem (CMCLP) models with our proposed CGMCLP model in similar data sets shows that the proposed model can cover more demands and acts more efficiently. Sensitivity analyses are performed to show the effect of related parameters and the model's validity. Simulated annealing (SA) and a tabu search (TS) are proposed as solution algorithms for the developed models for large-sized instances. The results show that the proposed algorithms are efficient solution approaches, considering solution quality and running time.

Casemix funding for acute hospital inpatient services in Australia.

PubMed

Duckett, S J

1998-10-19

Casemix funding was introduced first in Victoria in 1993-94, and since then most States have moved towards either casemix funding or using casemix to inform the budget setting process. The five States implementing casemix have adopted some common funding elements: all use AN-DRG-3; all have introduced capping, msot commonly at the hospital level; and all ensure accuracy of diagnosis and procedure coding through coding audits. Two funding models have been developed. The fixed and variable model involves a fixed grant for hospital overhead costs and a payment for each patient treated, covering only variable costs. The integrated model provides an integrated payment to hospitals for each patient treated, covering both the fixed and variable costs. There are different weight setting processes and base prices between the States, which result in marked differences in the price paid for the same type of case treated in similar hospitals. Learning across State boundaries should be encouraged, with knowledge of what is effective and what is ineffective in casemix funding arrangements being used to develop Australian best practice in this area.

Arcjet space thrusters

NASA Astrophysics Data System (ADS)

Keefer, Dennis; Rhodes, Robert

1993-05-01

Electrically powered arc jets which produce thrust at high specific impulse could provide a substantial cost reduction for orbital transfer and station keeping missions. There is currently a limited understanding of the complex, nonlinear interactions in the plasma propellant which has hindered the development of high efficiency arc jet thrusters by making it difficult to predict the effect of design changes and to interpret experimental results. A computational model developed at the University of Tennessee Space Institute (UTSI) to study laser powered thrusters and radio frequency gas heaters has been adapted to provide a tool to help understand the physical processes in arc jet thrusters. The approach is to include in the model those physical and chemical processes which appear to be important, and then to evaluate our judgement by the comparison of numerical simulations with experimental data. The results of this study have been presented at four technical conferences. The details of the work accomplished in this project are covered in the individual papers included in the appendix of this report. We present a brief description of the model covering its most important features followed by a summary of the effort.

Operational monitoring of land-cover change using multitemporal remote sensing data

NASA Astrophysics Data System (ADS)

Rogan, John

2005-11-01

Land-cover change, manifested as either land-cover modification and/or conversion, can occur at all spatial scales, and changes at local scales can have profound, cumulative impacts at broader scales. The implication of operational land-cover monitoring is that researchers have access to a continuous stream of remote sensing data, with the long term goal of providing for consistent and repetitive mapping. Effective large area monitoring of land-cover (i.e., >1000 km2) can only be accomplished by using remotely sensed images as an indirect data source in land-cover change mapping and as a source for land-cover change model projections. Large area monitoring programs face several challenges: (1) choice of appropriate classification scheme/map legend over large, topographically and phenologically diverse areas; (2) issues concerning data consistency and map accuracy (i.e., calibration and validation); (3) very large data volumes; (4) time consuming data processing and interpretation. Therefore, this dissertation research broadly addresses these challenges in the context of examining state-of-the-art image pre-processing, spectral enhancement, classification, and accuracy assessment techniques to assist the California Land-cover Mapping and Monitoring Program (LCMMP). The results of this dissertation revealed that spatially varying haze can be effectively corrected from Landsat data for the purposes of change detection. The Multitemporal Spectral Mixture Analysis (MSMA) spectral enhancement technique produced more accurate land-cover maps than those derived from the Multitemporal Kauth Thomas (MKT) transformation in northern and southern California study areas. A comparison of machine learning classifiers showed that Fuzzy ARTMAP outperformed two classification tree algorithms, based on map accuracy and algorithm robustness. Variation in spatial data error (positional and thematic) was explored in relation to environmental variables using geostatistical interpolation techniques. Finally, the land-cover modification maps generated for three time intervals (1985--1990--1996--2000), with nine change-classes revealed important variations in land-cover gain and loss between northern and southern California study areas.

A simple ecohydrological model captures essentials of seasonal leaf dynamics in semi-arid tropical grasslands

NASA Astrophysics Data System (ADS)

Choler, P.; Sea, W.; Briggs, P.; Raupach, M.; Leuning, R.

2009-09-01

Modelling leaf phenology in water-controlled ecosystems remains a difficult task because of high spatial and temporal variability in the interaction of plant growth and soil moisture. Here, we move beyond widely used linear models to examine the performance of low-dimensional, nonlinear ecohydrological models that couple the dynamics of plant cover and soil moisture. The study area encompasses 400 000 km2 of semi-arid perennial tropical grasslands, dominated by C4 grasses, in the Northern Territory and Queensland (Australia). We prepared 8 yr time series (2001-2008) of climatic variables and estimates of fractional vegetation cover derived from MODIS Normalized Difference Vegetation Index (NDVI) for 400 randomly chosen sites, of which 25% were used for model calibration and 75% for model validation. We found that the mean absolute error of linear and nonlinear models did not markedly differ. However, nonlinear models presented key advantages: (1) they exhibited far less systematic error than their linear counterparts; (2) their error magnitude was consistent throughout a precipitation gradient while the performance of linear models deteriorated at the driest sites, and (3) they better captured the sharp transitions in leaf cover that are observed under high seasonality of precipitation. Our results showed that low-dimensional models including feedbacks between soil water balance and plant growth adequately predict leaf dynamics in semi-arid perennial grasslands. Because these models attempt to capture fundamental ecohydrological processes, they should be the favoured approach for prognostic models of phenology.

A simple ecohydrological model captures essentials of seasonal leaf dynamics in semi-arid tropical grasslands

NASA Astrophysics Data System (ADS)

Choler, P.; Sea, W.; Briggs, P.; Raupach, M.; Leuning, R.

2010-03-01

Modelling leaf phenology in water-controlled ecosystems remains a difficult task because of high spatial and temporal variability in the interaction of plant growth and soil moisture. Here, we move beyond widely used linear models to examine the performance of low-dimensional, nonlinear ecohydrological models that couple the dynamics of plant cover and soil moisture. The study area encompasses 400 000 km2 of semi-arid perennial tropical grasslands, dominated by C4 grasses, in the Northern Territory and Queensland (Australia). We prepared 8-year time series (2001-2008) of climatic variables and estimates of fractional vegetation cover derived from MODIS Normalized Difference Vegetation Index (NDVI) for 400 randomly chosen sites, of which 25% were used for model calibration and 75% for model validation. We found that the mean absolute error of linear and nonlinear models did not markedly differ. However, nonlinear models presented key advantages: (1) they exhibited far less systematic error than their linear counterparts; (2) their error magnitude was consistent throughout a precipitation gradient while the performance of linear models deteriorated at the driest sites, and (3) they better captured the sharp transitions in leaf cover that are observed under high seasonality of precipitation. Our results showed that low-dimensional models including feedbacks between soil water balance and plant growth adequately predict leaf dynamics in semi-arid perennial grasslands. Because these models attempt to capture fundamental ecohydrological processes, they should be the favoured approach for prognostic models of phenology.

Effects of Land Cover / Land Use, Soil Texture, and Vegetation on the Water Balance of Lake Chad Basin

NASA Astrophysics Data System (ADS)

Babamaaji, R. A.; Lee, J.

2013-12-01

Lake Chad Basin (LCB) has experienced drastic changes of land cover and poor water management practices during the last 50 years. The successive droughts in the 1970s and 1980s resulted in the shortage of surface water and groundwater resources. This problem of drought has a devastating implication on the natural resources of the Basin with great consequence on food security, poverty reduction and quality of life of the inhabitants in the LCB. Therefore, understanding the effects of land use / land cover must be a first step to find how they disturb cycle especially the groundwater in the LCB. The abundance of groundwater is affected by the climate change through the interaction with surface water, such as lakes and rivers, and disuse recharge through an infiltration process. Quantifying the impact of climate change on the groundwater resource requires reliable forecasting of changes in the major climatic variables and other spatial variations including the land use/land cover, soil texture, topographic slope, and vegetation. In this study, we employed a spatially distributed water balance model WetSpass to simulate a long-term average change of groundwater recharge in the LCB of Africa. WetSpass is a water balance-based model to estimate seasonal and spatial distribution of surface runoff, interception, evapotranspiration, and groundwater recharge. The model is especially suitable for studying the effect of land use/land cover change on the water regime in the LCB. The present study describes the concept of the model and its application to the development of recharge map of the LCB. The study shows that major role in the water balance of LCB. The mean yearly actual evapotranspiration (ET) from the basin range from 60mm - 400 mm, which is 90 % (69mm - 430) of the annual precipitation from 2003 - 2010. It is striking that about 50 - 60 % of the total runoff is produced on build-up (impervious surfaces), while much smaller contributions are obtained from vegetated, bare soil and open water surfaces. The result of this study also shows that runoff is high in the clay, clay loam and sandy-clay loam due to the lack of infiltration process in clay soil from capping or crusting or sealing of the soil pores, therefore this situation will aid runoff. The application of the WetSpass model shows that precipitation, soil texture and land use / land cover are three controlling factors affecting the water balance in the LCB. Key words: Groundwater recharge, surface runoff, evapotranspiration, water balance, meteorological, draught, Landuse changes, climate changes, WetSpass, GIS.

Human impacts drive a global topographic signature in tree cover.

PubMed

Sandel, Brody; Svenning, Jens-Christian

2013-01-01

The Anthropocene is a geological epoch marked by major human influences on processes in the atmosphere, biosphere, hydrosphere and geosphere. One of the most dramatic features of the Anthropocene is the massive alteration of the Earth's vegetation, including forests. Here we investigate the role of topography in shaping human impacts on tree cover from local to global scales. We show that human impacts have resulted in a global tendency for tree cover to be constrained to sloped terrain and losses to be concentrated on flat terrain. This effect increases in strength with increasing human pressure and is most pronounced in countries with rapidly growing economies, limited human population stress and highly effective governments. These patterns likely reflect the relative inaccessibility of sloped topography and have important implications for conservation and modelling of future tree cover.

Air-Sea Interaction Processes in Low and High-Resolution Coupled Climate Model Simulations for the Southeast Pacific

NASA Astrophysics Data System (ADS)

Porto da Silveira, I.; Zuidema, P.; Kirtman, B. P.

2017-12-01

The rugged topography of the Andes Cordillera along with strong coastal upwelling, strong sea surface temperatures (SST) gradients and extensive but geometrically-thin stratocumulus decks turns the Southeast Pacific (SEP) into a challenge for numerical modeling. In this study, hindcast simulations using the Community Climate System Model (CCSM4) at two resolutions were analyzed to examine the importance of resolution alone, with the parameterizations otherwise left unchanged. The hindcasts were initialized on January 1 with the real-time oceanic and atmospheric reanalysis (CFSR) from 1982 to 2003, forming a 10-member ensemble. The two resolutions are (0.1o oceanic and 0.5o atmospheric) and (1.125o oceanic and 0.9o atmospheric). The SST error growth in the first six days of integration (fast errors) and those resulted from model drift (saturated errors) are assessed and compared towards evaluating the model processes responsible for the SST error growth. For the high-resolution simulation, SST fast errors are positive (+0.3oC) near the continental borders and negative offshore (-0.1oC). Both are associated with a decrease in cloud cover, a weakening of the prevailing southwesterly winds and a reduction of latent heat flux. The saturated errors possess a similar spatial pattern, but are larger and are more spatially concentrated. This suggests that the processes driving the errors already become established within the first week, in contrast to the low-resolution simulations. These, instead, manifest too-warm SSTs related to too-weak upwelling, driven by too-strong winds and Ekman pumping. Nevertheless, the ocean surface tends to be cooler in the low-resolution simulation than the high-resolution due to a higher cloud cover. Throughout the integration, saturated SST errors become positive and could reach values up to +4oC. These are accompanied by upwelling dumping and a decrease in cloud cover. High and low resolution models presented notable differences in how SST errors variability drove atmospheric changes, especially because the high resolution is sensitive to resurgence regions. This allows the model to resolve cloud heights and establish different radiative feedbacks.

Sensitivity of modelled snow cover to turbulent flux parameterization and forcing data: a case study in a high altitude basin of the dry Andes, northern Chile

NASA Astrophysics Data System (ADS)

Kinnard, C.; Irarrazaval, I.; Campos, C.; Gascoin, S.; MacDonell, S.; Macdonell, S.; Herrero, J.

2016-12-01

Snow cover in the central-northern Andes of Chile is the main runoff source, providing water for the irrigation of cultures in the fertile valleys downstream. The prospect of adverse climate warming impacts on the hydrological cycle calls for a better understanding of the snow cover dynamics in response to climate, an aspect that has been little studied in the dry Andes. The heterogeneous and often thin snow cover, as well as the paucity of long-term hydrometeorological data makes snow modelling a challenging task in these regions. In this work we applied a physically-based, spatially-distributed snow model (Wimmed) to the La Laguna headwater catchment in the dry Andes (30°S, 70°W) during three hydrological years (2010-2013) when forcing data was available. Model testing at the point scale revealed a large sensitivity of simulated snow depths to the choice of snow roughness parameter (z0), which controls turbulent fluxes, while wind-induced snow erosion at the station in 2010 and 2011 complicated model validation. The inclusion of a mean wind speed map from a previous simulation with the WRF atmospheric model was found to improve the simulation results, while excluding the highest mountain ridge weather station had detrimental effects on the results. A snow roughness (z0) of 1 mm yielded the best comparison between the simulated and observed snow depth at the reference weather station, and between the simulated and MODIS-derived snow cover at the catchment scale. The simulation resulted in large sublimation losses (up to 4 mm day-1), corresponding to more than 80% of snow ablation in the catchment. While such high sublimation rates have been reported before in this region, remaining uncertainties in precipitation data and snow compaction processes call for more detailed studies and increased instrumentation in order to improve future modelling efforts.

Evaluation of the AnnAGNPS Model for Predicting Runoff and Nutrient Export in a Typical Small Watershed in the Hilly Region of Taihu Lake

PubMed Central

Luo, Chuan; Li, Zhaofu; Li, Hengpeng; Chen, Xiaomin

2015-01-01

The application of hydrological and water quality models is an efficient approach to better understand the processes of environmental deterioration. This study evaluated the ability of the Annualized Agricultural Non-Point Source (AnnAGNPS) model to predict runoff, total nitrogen (TN) and total phosphorus (TP) loading in a typical small watershed of a hilly region near Taihu Lake, China. Runoff was calibrated and validated at both an annual and monthly scale, and parameter sensitivity analysis was performed for TN and TP before the two water quality components were calibrated. The results showed that the model satisfactorily simulated runoff at annual and monthly scales, both during calibration and validation processes. Additionally, results of parameter sensitivity analysis showed that the parameters Fertilizer rate, Fertilizer organic, Canopy cover and Fertilizer inorganic were more sensitive to TN output. In terms of TP, the parameters Residue mass ratio, Fertilizer rate, Fertilizer inorganic and Canopy cover were the most sensitive. Based on these sensitive parameters, calibration was performed. TN loading produced satisfactory results for both the calibration and validation processes, whereas the performance of TP loading was slightly poor. The simulation results showed that AnnAGNPS has the potential to be used as a valuable tool for the planning and management of watersheds. PMID:26364642

A higher order conditional random field model for simultaneous classification of land cover and land use

NASA Astrophysics Data System (ADS)

Albert, Lena; Rottensteiner, Franz; Heipke, Christian

2017-08-01

We propose a new approach for the simultaneous classification of land cover and land use considering spatial as well as semantic context. We apply a Conditional Random Fields (CRF) consisting of a land cover and a land use layer. In the land cover layer of the CRF, the nodes represent super-pixels; in the land use layer, the nodes correspond to objects from a geospatial database. Intra-layer edges of the CRF model spatial dependencies between neighbouring image sites. All spatially overlapping sites in both layers are connected by inter-layer edges, which leads to higher order cliques modelling the semantic relation between all land cover and land use sites in the clique. A generic formulation of the higher order potential is proposed. In order to enable efficient inference in the two-layer higher order CRF, we propose an iterative inference procedure in which the two classification tasks mutually influence each other. We integrate contextual relations between land cover and land use in the classification process by using contextual features describing the complex dependencies of all nodes in a higher order clique. These features are incorporated in a discriminative classifier, which approximates the higher order potentials during the inference procedure. The approach is designed for input data based on aerial images. Experiments are carried out on two test sites to evaluate the performance of the proposed method. The experiments show that the classification results are improved compared to the results of a non-contextual classifier. For land cover classification, the result is much more homogeneous and the delineation of land cover segments is improved. For the land use classification, an improvement is mainly achieved for land use objects showing non-typical characteristics or similarities to other land use classes. Furthermore, we have shown that the size of the super-pixels has an influence on the level of detail of the classification result, but also on the degree of smoothing induced by the segmentation method, which is especially beneficial for land cover classes covering large, homogeneous areas.

Comparison of DNDC and RZWQM2 for simulating hydrology and nitrogen dynamics in a corn-soybean system with a winter cover crop

NASA Astrophysics Data System (ADS)

Desjardins, R.; Smith, W.; Qi, Z.; Grant, B.; VanderZaag, A.

2017-12-01

Biophysical models are needed for assessing science-based mitigation options to improve the efficiency and sustainability of agricultural cropping systems. In order to account for trade-offs between environmental indicators such as GHG emissions, soil C change, and water quality it is important that models can encapsulate the complex array of interrelated biogeochemical processes controlling water, nutrient and energy flows in the agroecosystem. The Denitrification Decomposition (DNDC) model is one of the most widely used process-based models, and is arguably the most sophisticated for estimating GHG emissions and soil C&N cycling, however, the model simulates only simple cascade water flow. The purpose of this study was to compare the performance of DNDC to a comprehensive water flow model, the Root Zone Water Quality Model (RZWQM2), to determine which processes in DNDC may be limiting and recommend improvements. Both models were calibrated and validated for simulating crop biomass, soil hydrology, and nitrogen loss to tile drains using detailed observations from a corn-soybean rotation in Iowa, with and without cover crops. Results indicated that crop yields, biomass and the annual estimation of nitrogen and water loss to tiles drains were well simulated by both models (NSE > 0.6 in all cases); however, RZWQM2 performed much better for simulating soil water content, and the dynamics of daily water flow (DNDC: NSE -0.32 to 0.28; RZWQM2: NSE 0.34 to 0.70) to tile drains. DNDC overestimated soil water content near the soil surface and underestimated it deeper in the profile which was presumably caused by the lack of a root distribution algorithm, the inability to simulate a heterogeneous profile and lack of a water table. We recommend these improvements along with the inclusion of enhanced water flow and a mechanistic tile drainage sub-model. The accurate temporal simulation of water and N strongly impacts several biogeochemical processes.

Regional Arctic System Model (RASM): A Tool to Advance Understanding and Prediction of Arctic Climate Change at Process Scales

NASA Astrophysics Data System (ADS)

Maslowski, W.; Roberts, A.; Osinski, R.; Brunke, M.; Cassano, J. J.; Clement Kinney, J. L.; Craig, A.; Duvivier, A.; Fisel, B. J.; Gutowski, W. J., Jr.; Hamman, J.; Hughes, M.; Nijssen, B.; Zeng, X.

2014-12-01

The Arctic is undergoing rapid climatic changes, which are some of the most coordinated changes currently occurring anywhere on Earth. They are exemplified by the retreat of the perennial sea ice cover, which integrates forcing by, exchanges with and feedbacks between atmosphere, ocean and land. While historical reconstructions from Global Climate and Global Earth System Models (GC/ESMs) are in broad agreement with these changes, the rate of change in the GC/ESMs remains outpaced by observations. Reasons for that stem from a combination of coarse model resolution, inadequate parameterizations, unrepresented processes and a limited knowledge of physical and other real world interactions. We demonstrate the capability of the Regional Arctic System Model (RASM) in addressing some of the GC/ESM limitations in simulating observed seasonal to decadal variability and trends in the sea ice cover and climate. RASM is a high resolution, fully coupled, pan-Arctic climate model that uses the Community Earth System Model (CESM) framework. It uses the Los Alamos Sea Ice Model (CICE) and Parallel Ocean Program (POP) configured at an eddy-permitting resolution of 1/12° as well as the Weather Research and Forecasting (WRF) and Variable Infiltration Capacity (VIC) models at 50 km resolution. All RASM components are coupled via the CESM flux coupler (CPL7) at 20-minute intervals. RASM is an example of limited-area, process-resolving, fully coupled earth system model, which due to the additional constraints from lateral boundary conditions and nudging within a regional model domain facilitates detailed comparisons with observational statistics that are not possible with GC/ESMs. In this talk, we will emphasize the utility of RASM to understand sensitivity to variable parameter space, importance of critical processes, coupled feedbacks and ultimately to reduce uncertainty in arctic climate change projections.

Current and Future Urban Stormwater Flooding Scenarios in the Southeast Florida Coasts

NASA Astrophysics Data System (ADS)

Huq, E.; Abdul-Aziz, O. I.

2016-12-01

This study computed rainfall-fed stormwater flooding under the historical and future reference scenarios for the Southeast Coasts Basin of Florida. A large-scale, mechanistic rainfall-runoff model was developed using the U.S. E.P.A. Storm Water Management Model (SWMM 5.1). The model parameterized important processes of urban hydrology, groundwater, and sea level, while including hydroclimatological variables and land use features. The model was calibrated and validated with historical streamflow data. It was then used to estimate the sensitivity of stormwater runoff to the reference changes in hydroclimatological variables (rainfall and evapotranspiration) and different land use/land cover features (imperviousness, roughness). Furthermore, historical (1970-2000) and potential 2050s stormwater budgets were also estimated for the Florida Southeast Coasts Basin by incorporating climatic projections from different GCMs and RCMs, as well as by using relevant projections of sea level and land use/cover. Comparative synthesis of the historical and future scenarios along with the results of sensitivity analysis can aid in efficient management of stormwater flooding for the southeast Florida coasts and similar urban centers under a changing regime of climate, sea level, land use/cover and hydrology.

A neural network model of metaphor understanding with dynamic interaction based on a statistical language analysis: targeting a human-like model.

PubMed

Terai, Asuka; Nakagawa, Masanori

2007-08-01

The purpose of this paper is to construct a model that represents the human process of understanding metaphors, focusing specifically on similes of the form an "A like B". Generally speaking, human beings are able to generate and understand many sorts of metaphors. This study constructs the model based on a probabilistic knowledge structure for concepts which is computed from a statistical analysis of a large-scale corpus. Consequently, this model is able to cover the many kinds of metaphors that human beings can generate. Moreover, the model implements the dynamic process of metaphor understanding by using a neural network with dynamic interactions. Finally, the validity of the model is confirmed by comparing model simulations with the results from a psychological experiment.

Semiconductor technology program. Progress briefs

NASA Technical Reports Server (NTRS)

Bullis, W. M. (Editor)

1979-01-01

The current status of NBS work on measurement technology for semiconductor materials, process control, and devices is reported. Results of both in-house and contract research are covered. Highlighted activities include modeling of diffusion processes, analysis of model spreading resistance data, and studies of resonance ionization spectroscopy, resistivity-dopant density relationships in p-type silicon, deep level measurements, photoresist sensitometry, random fault measurements, power MOSFET thermal characteristics, power transistor switching characteristics, and gross leak testing. New and selected on-going projects are described. Compilations of recent publications and publications in press are included.

Application of evolutionary games to modeling carcinogenesis.

PubMed

Swierniak, Andrzej; Krzeslak, Michal

2013-06-01

We review a quite large volume of literature concerning mathematical modelling of processes related to carcinogenesis and the growth of cancer cell populations based on the theory of evolutionary games. This review, although partly idiosyncratic, covers such major areas of cancer-related phenomena as production of cytotoxins, avoidance of apoptosis, production of growth factors, motility and invasion, and intra- and extracellular signaling. We discuss the results of other authors and append to them some additional results of our own simulations dealing with the possible dynamics and/or spatial distribution of the processes discussed.

Stochastic Adaptive Estimation and Control.

DTIC Science & Technology

1994-10-26

Marcus, "Language Stability and Stabilizability of Discrete Event Dynamical Systems ," SIAM Journal on Control and Optimization, 31, September 1993...in the hierarchical control of flexible manufacturing systems ; in this problem, the model involves a hybrid process in continuous time whose state is...of the average cost control problem for discrete- time Markov processes. Our exposition covers from finite to Borel state and action spaces and

Influence of Elevation Data Resolution on Spatial Prediction of Colluvial Soils in a Luvisol Region

PubMed Central

Penížek, Vít; Zádorová, Tereza; Kodešová, Radka; Vaněk, Aleš

2016-01-01

The development of a soil cover is a dynamic process. Soil cover can be altered within a few decades, which requires updating of the legacy soil maps. Soil erosion is one of the most important processes quickly altering soil cover on agriculture land. Colluvial soils develop in concave parts of the landscape as a consequence of sedimentation of eroded material. Colluvial soils are recognised as important soil units because they are a vast sink of soil organic carbon. Terrain derivatives became an important tool in digital soil mapping and are among the most popular auxiliary data used for quantitative spatial prediction. Prediction success rates are often directly dependent on raster resolution. In our study, we tested how raster resolution (1, 2, 3, 5, 10, 20 and 30 meters) influences spatial prediction of colluvial soils. Terrain derivatives (altitude, slope, plane curvature, topographic position index, LS factor and convergence index) were calculated for the given raster resolutions. Four models were applied (boosted tree, neural network, random forest and Classification/Regression Tree) to spatially predict the soil cover over a 77 ha large study plot. Models training and validation was based on 111 soil profiles surveyed on a regular sampling grid. Moreover, the predicted real extent and shape of the colluvial soil area was examined. In general, no clear trend in the accuracy prediction was found without the given raster resolution range. Higher maximum prediction accuracy for colluvial soil, compared to prediction accuracy of total soil cover of the study plot, can be explained by the choice of terrain derivatives that were best for Colluvial soils differentiation from other soil units. Regarding the character of the predicted Colluvial soils area, maps of 2 to 10 m resolution provided reasonable delineation of the colluvial soil as part of the cover over the study area. PMID:27846230

Mapping fractional woody cover in semi-arid savannahs using multi-seasonal composites from Landsat data

NASA Astrophysics Data System (ADS)

Higginbottom, Thomas P.; Symeonakis, Elias; Meyer, Hanna; van der Linden, Sebastian

2018-05-01

Increasing attention is being directed at mapping the fractional woody cover of savannahs using Earth-observation data. In this study, we test the utility of Landsat TM/ ETM-based spectral-temporal variability metrics for mapping regional-scale woody cover in the Limpopo Province of South Africa, for 2010. We employ a machine learning framework to compare the accuracies of Random Forest models derived using metrics calculated from different seasons. We compare these results to those from fused Landsat-PALSAR data to establish if seasonal metrics can compensate for structural information from the PALSAR signal. Furthermore, we test the applicability of a statistical variable selection method, the recursive feature elimination (RFE), in the automation of the model building process in order to reduce model complexity and processing time. All of our tests were repeated at four scales (30, 60, 90, and 120 m-pixels) to investigate the role of spatial resolution on modelled accuracies. Our results show that multi-seasonal composites combining imagery from both the dry and wet seasons produced the highest accuracies (R2 = 0.77, RMSE = 9.4, at the 120 m scale). When using a single season of observations, dry season imagery performed best (R2 = 0.74, RMSE = 9.9, at the 120 m resolution). Combining Landsat and radar imagery was only marginally beneficial, offering a mean relative improvement of 1% in accuracy at the 120 m scale. However, this improvement was concentrated in areas with lower densities of woody coverage (<30%), which are areas of concern for environmental monitoring. At finer spatial resolutions, the inclusion of SAR data actually reduced accuracies. Overall, the RFE was able to produce the most accurate model (R2 = 0.8, RMSE = 8.9, at the 120 m pixel scale). For mapping savannah woody cover at the 30 m pixel scale, we suggest that monitoring methodologies continue to exploit the Landsat archive, but should aim to use multi-seasonal derived information. When the coarser 120 m pixel scale is adequate, integration of Landsat and SAR data should be considered, especially in areas with lower woody cover densities. The use of multiple seasonal compositing periods offers promise for large-area mapping of savannahs, even in regions with a limited historical Landsat coverage.

A functional-dynamic reflection on participatory processes in modeling projects.

PubMed

Seidl, Roman

2015-12-01

The participation of nonscientists in modeling projects/studies is increasingly employed to fulfill different functions. However, it is not well investigated if and how explicitly these functions and the dynamics of a participatory process are reflected by modeling projects in particular. In this review study, I explore participatory modeling projects from a functional-dynamic process perspective. The main differences among projects relate to the functions of participation-most often, more than one per project can be identified, along with the degree of explicit reflection (i.e., awareness and anticipation) on the dynamic process perspective. Moreover, two main approaches are revealed: participatory modeling covering diverse approaches and companion modeling. It becomes apparent that the degree of reflection on the participatory process itself is not always explicit and perfectly visible in the descriptions of the modeling projects. Thus, the use of common protocols or templates is discussed to facilitate project planning, as well as the publication of project results. A generic template may help, not in providing details of a project or model development, but in explicitly reflecting on the participatory process. It can serve to systematize the particular project's approach to stakeholder collaboration, and thus quality management.

S stars in the Gaia era: stellar parameters and nucleosynthesis

NASA Astrophysics Data System (ADS)

van Eck, Sophie; Karinkuzhi, Drisya; Shetye, Shreeya; Jorissen, Alain; Goriely, Stéphane; Siess, Lionel; Merle, Thibault; Plez, Bertrand

2018-04-01

S stars are s-process and C-enriched (0.5

Mechanics of aeolian processes: Soil erosion and dust production

NASA Technical Reports Server (NTRS)

Mehrabadi, M. M.

1989-01-01

Aeolian (wind) processes occur as a result of atmosphere/land-surface system interactions. A thorough understanding of these processes and their physical/mechanical characterization on a global scale is essential to monitoring global change and, hence, is imperative to the fundamental goal of the Earth observing system (Eos) program. Soil erosion and dust production by wind are of consequence mainly in arid and semi arid regions which cover 36 percent of the Earth's land surface. Some recent models of dust production due to wind erosion of agricultural soils and the mechanics of wind erosion in deserts are reviewed and the difficulties of modeling the aeolian transport are discussed.

A dataset mapping the potential biophysical effects of vegetation cover change

NASA Astrophysics Data System (ADS)

Duveiller, Gregory; Hooker, Josh; Cescatti, Alessandro

2018-02-01

Changing the vegetation cover of the Earth has impacts on the biophysical properties of the surface and ultimately on the local climate. Depending on the specific type of vegetation change and on the background climate, the resulting competing biophysical processes can have a net warming or cooling effect, which can further vary both spatially and seasonally. Due to uncertain climate impacts and the lack of robust observations, biophysical effects are not yet considered in land-based climate policies. Here we present a dataset based on satellite remote sensing observations that provides the potential changes i) of the full surface energy balance, ii) at global scale, and iii) for multiple vegetation transitions, as would now be required for the comprehensive evaluation of land based mitigation plans. We anticipate that this dataset will provide valuable information to benchmark Earth system models, to assess future scenarios of land cover change and to develop the monitoring, reporting and verification guidelines required for the implementation of mitigation plans that account for biophysical land processes.

A dataset mapping the potential biophysical effects of vegetation cover change

PubMed Central

Duveiller, Gregory; Hooker, Josh; Cescatti, Alessandro

2018-01-01

Changing the vegetation cover of the Earth has impacts on the biophysical properties of the surface and ultimately on the local climate. Depending on the specific type of vegetation change and on the background climate, the resulting competing biophysical processes can have a net warming or cooling effect, which can further vary both spatially and seasonally. Due to uncertain climate impacts and the lack of robust observations, biophysical effects are not yet considered in land-based climate policies. Here we present a dataset based on satellite remote sensing observations that provides the potential changes i) of the full surface energy balance, ii) at global scale, and iii) for multiple vegetation transitions, as would now be required for the comprehensive evaluation of land based mitigation plans. We anticipate that this dataset will provide valuable information to benchmark Earth system models, to assess future scenarios of land cover change and to develop the monitoring, reporting and verification guidelines required for the implementation of mitigation plans that account for biophysical land processes. PMID:29461538

Chemical mass transport between fluid fine tailings and the overlying water cover of an oil sands end pit lake

NASA Astrophysics Data System (ADS)

Dompierre, Kathryn A.; Barbour, S. Lee; North, Rebecca L.; Carey, Sean K.; Lindsay, Matthew B. J.

2017-06-01

Fluid fine tailings (FFT) are a principal by-product of the bitumen extraction process at oil sands mines. Base Mine Lake (BML)—the first full-scale demonstration oil sands end pit lake (EPL)—contains approximately 1.9 × 108 m3 of FFT stored under a water cover within a decommissioned mine pit. Chemical mass transfer from the FFT to the water cover can occur via two key processes: (1) advection-dispersion driven by tailings settlement; and (2) FFT disturbance due to fluid movement in the water cover. Dissolved chloride (Cl) was used to evaluate the water cover mass balance and to track mass transport within the underlying FFT based on field sampling and numerical modeling. Results indicated that FFT was the dominant Cl source to the water cover and that the FFT is exhibiting a transient advection-dispersion mass transport regime with intermittent disturbance near the FFT-water interface. The advective pore water flux was estimated by the mass balance to be 0.002 m3 m-2 d-1, which represents 0.73 m of FFT settlement per year. However, the FFT pore water Cl concentrations and corresponding mass transport simulations indicated that advection rates and disturbance depths vary between sample locations. The disturbance depth was estimated to vary with location between 0.75 and 0.95 m. This investigation provides valuable insight for assessing the geochemical evolution of the water cover and performance of EPLs as an oil sands reclamation strategy.

Assimilation of sea ice concentration data in the Arctic via DART/CICE5 in the CESM1

NASA Astrophysics Data System (ADS)

Zhang, Y.; Bitz, C. M.; Anderson, J. L.; Collins, N.; Hendricks, J.; Hoar, T. J.; Raeder, K.

2016-12-01

Arctic sea ice cover has been experiencing significant reduction in the past few decades. Climate models predict that the Arctic Ocean may be ice-free in late summer within a few decades. Better sea ice prediction is crucial for regional and global climate prediction that are vital to human activities such as maritime shipping and subsistence hunting, as well as wildlife protection as animals face habitat loss. The physical processes involved with the persistence and re-emergence of sea ice cover are found to extend the predictability of sea ice concentration (SIC) and thickness at the regional scale up to several years. This motivates us to investigate sea ice predictability stemming from initial values of the sea ice cover. Data assimilation is a useful technique to combine observations and model forecasts to reconstruct the states of sea ice in the past and provide more accurate initial conditions for sea ice prediction. This work links the most recent version of the Los Alamos sea ice model (CICE5) within the Community Earth System Model version 1.5 (CESM1.5) and the Data Assimilation Research Testbed (DART). The linked DART/CICE5 is ideal to assimilate multi-scale and multivariate sea ice observations using an ensemble Kalman filter (EnKF). The study is focused on the assimilation of SIC data that impact SIC, sea ice thickness, and snow thickness. The ensemble sea ice model states are constructed by introducing uncertainties in atmospheric forcing and key model parameters. The ensemble atmospheric forcing is a reanalysis product generated with DART and the Community Atmosphere Model (CAM). We also perturb two model parameters that are found to contribute significantly to the model uncertainty in previous studies. This study applies perfect model observing system simulation experiments (OSSEs) to investigate data assimilation algorithms and post-processing methods. One of the ensemble members of a CICE5 free run is chosen as the truth. Daily synthetic observations are obtained by adding 15% random noise to the truth. Experiments assimilating the synthetic observations are then conducted to test the effectiveness of different data assimilation algorithms (e.g., localization and inflation) and post-processing methods (e.g., how to distribute the total increment of SIC into each ice thickness category).

Hydrological system dynamics of glaciated Karnali River Basin Nepal Himalaya using J2000 Hydrological model

NASA Astrophysics Data System (ADS)

Khatiwada, K. R.; Nepal, S.; Panthi, J., Sr.; Shrestha, M.

2015-12-01

Hydrological modelling plays an important role in understanding hydrological processes of a catchment. In the context of climate change, the understanding of hydrological characteristic of the catchment is very vital to understand how the climate change will affect the hydrological regime. This research facilitates in better understanding of the hydrological system dynamics of a himalayan mountainous catchment in western Nepal. The Karnali River, longest river flowing inside Nepal, is one of the three major basins of Nepal, having the area of 45269 sq. km. is unique. The basin has steep topography and high mountains to the northern side. The 40% of the basin is dominated by forest land while other land cover are: grass land, bare rocky land etc. About 2% of the areas in basin is covered by permanent glacier apart from that about 12% of basin has the snow and ice cover. There are 34 meteorological stations distributed across the basin. A process oriented distributed J2000 hydrologial model has been applied to understand the hydrological system dynamics. The model application provides distributed output of various hydrological components. The J2000 model applies Hydrological Response Unit (HRU) as a modelling entity. With 6861 HRU and 1010 reaches, the model was calibrated (1981-1999) and validated (2000-2004) at a daily scale using split-sample test. The model is able to capture the overall hydrological dynamics well. The rising limbs and recession limbs are simulated equally and with satisfactory ground water conditions. Based on the graphical and statistical evaluation of the model performance the model is able to simulate hydrological processes fairly well. Calibration shows that Nash Sutcliffe efficiency is 0.91, coefficient of determination is 0.92 Initial observation shows that during the pre-monsoon season(March to May) the glacial runoff is 25% of the total discharge while in the monsoon(June to September) season it is only 13%. The surface runoff contributed about 40%, 20% in subsurface while there is about 13% in the base flow. For better understanding and interpretation of the area there is still need of further coherent research and analysis for land use change and future climate change impact in the glaciered alpine catchment of Himalayan region.

Quantification of the inevitable: the influence of soil macrofauna on soil water movement in rehabilitated open-cut mined lands

NASA Astrophysics Data System (ADS)

Arnold, S.; Williams, E. R.

2016-01-01

Recolonisation of soil by macrofauna (especially ants, termites and earthworms) in rehabilitated open-cut mine sites is inevitable and, in terms of habitat restoration and function, typically of great value. In these highly disturbed landscapes, soil invertebrates play a major role in soil development (macropore configuration, nutrient cycling, bioturbation, etc.) and can influence hydrological processes such as infiltration, seepage, runoff generation and soil erosion. Understanding and quantifying these ecosystem processes is important in rehabilitation design, establishment and subsequent management to ensure progress to the desired end goal, especially in waste cover systems designed to prevent water reaching and transporting underlying hazardous waste materials. However, the soil macrofauna is typically overlooked during hydrological modelling, possibly due to uncertainties on the extent of their influence, which can lead to failure of waste cover systems or rehabilitation activities. We propose that scientific experiments under controlled conditions and field trials on post-mining lands are required to quantify (i) macrofauna-soil structure interactions, (ii) functional dynamics of macrofauna taxa, and (iii) their effects on macrofauna and soil development over time. Such knowledge would provide crucial information for soil water models, which would increase confidence in mine waste cover design recommendations and eventually lead to higher likelihood of rehabilitation success of open-cut mining land.

Quantifying the Spatial Distribution of Evapotranspiration over Canada With a Process Model Using Remote Sensing, Meteorological, and Soil Data

NASA Astrophysics Data System (ADS)

Liu, J.; Chen, J.; Cihlar, J.

2004-12-01

The evapotranspiration (ET) from all Canadian landmass is estimated at daily steps and 1 km resolution using a process model named Boreal Ecosystem Productivity Simulator (BEPS). The model is driven by remotely sensed leaf area index and land cover maps, as well as soil water holding capacity and daily meteorological data. All the major ET components are considered: transpiration from vegetation, evaporation of canopy-intercepted rainfall, evaporation from soil, sublimation of snow in winter and in permafrost and glacier areas, and sublimation of canopy-intercepted snow. In forested areas, the transpiration from both the overstory and understory vegetation is modelled separately. The Penman-Monteith method was applied to sunlit and shaded leaf groups individually in modelling the canopy-level transpiration, a methodological improvement necessary for forest canopies with considerable foliage clumping. The modelled ET map displays pronounced east-west and north-south gradients as well as detailed variations with cover types and vegetation density. It is estimated that, for a relative wet year of 1996, the total ET from all Canada's landmass (excluding inland waters) was 2037 km3. If compared with the total precipitation of 5351 km3 based on the data from a medium range meteorological forecast model, the ratio of ET to precipitation was 38 %. The ET averaged over Canadian land surface was 228 mm/yr in 1996, partitioned into transpiration of 102 mm/yr and evaporation and sublimation of 126 mm/yr. Forested areas contributed the largest fraction of the total national ET at 59 %. Averaged for all cover types, transpiration accounted for 45 % of the total ET, while in forested areas, transpiration was contributed 51 % of ET. Modelled results of daily ET are compared with eddy covariance measurements at three forested sites with a r2 value of 0.61 and a root mean square error of 0.7 mm/day.

Biospheric Monitoring and Ecological Forecasting using EOS/MODIS data, ecosystem modeling, planning and scheduling technologies

NASA Astrophysics Data System (ADS)

Nemani, R. R.; Votava, P.; Golden, K.; Hashimoto, H.; Jolly, M.; White, M.; Running, S.; Coughlan, J.

2003-12-01

The latest generation of NASA Earth Observing System satellites has brought a new dimension to continuous monitoring of the living part of the Earth System, the Biosphere. EOS data can now provide weekly global measures of vegetation productivity and ocean chlorophyll, and many related biophysical factors such as land cover changes or snowmelt rates. However, information with the highest economic value would be forecasting impending conditions of the biosphere that would allow advanced decision-making to mitigate dangers, or exploit positive trends. We have developed a software system called the Terrestrial Observation and Prediction System (TOPS) to facilitate rapid analysis of ecosystem states/functions by integrating EOS data with ecosystem models, surface weather observations and weather/climate forecasts. Land products from MODIS (Moderate Resolution Imaging Spectroradiometer) including land cover, albedo, snow, surface temperature, leaf area index are ingested into TOPS for parameterization of models and for verifying model outputs such as snow cover and vegetation phenology. TOPS is programmed to gather data from observing networks such as USDA soil moisture, AMERIFLUX, SNOWTEL to further enhance model predictions. Key technologies enabling TOPS implementation include the ability to understand and process heterogeneous-distributed data sets, automated planning and execution of ecosystem models, causation analysis for understanding model outputs. Current TOPS implementations at local (vineyard) to global scales (global net primary production) can be found at http://www.ntsg.umt.edu/tops.

A model for the evolution of CO2 on Mars

NASA Technical Reports Server (NTRS)

Haberle, Robert M.; Tyler, D.; Mckay, C. P.; Davis, W. L.

1993-01-01

Our MSATT work has focused on the evolution of CO2 on Mars. We have constructed a model that predicts the evolution of CO2 on Mars from a specified initial amount at the end of the heavy bombardment to the present. The model draws on published estimates of the main process believed to affect the fate of CO2 during this period: chemical weathering, regolith uptake, polar cap formation, and atmospheric escape. Except for escape, the rate at which these processes act is controlled by surface temperatures that we calculate using a modified version of the Gierasch and Toon energy balance model. Various aspects of this work are covered.

Land cover variation and West Nile virus prevalence: Patterns, processes, and implications for disease control

USGS Publications Warehouse

Ezenwa, V.O.; Milheim, L.E.; Coffey, M.F.; Godsey, M.S.; King, R.J.; Guptill, S.C.

2007-01-01

Identifying links between environmental variables and infectious disease risk is essential to understanding how human-induced environmental changes will effect the dynamics of human and wildlife diseases. Although land cover change has often been tied to spatial variation in disease occurrence, the underlying factors driving the correlations are often unknown, limiting the applicability of these results for disease prevention and control. In this study, we described associations between land cover composition and West Nile virus (WNV) infection prevalence, and investigated three potential processes accounting for observed patterns: (1) variation in vector density; (2) variation in amplification host abundance; and (3) variation in host community composition. Interestingly, we found that WNV infection rates among Culex mosquitoes declined with increasing wetland cover, but wetland area was not significantly associated with either vector density or amplification host abundance. By contrast, wetland area was strongly correlated with host community composition, and model comparisons suggested that this factor accounted, at least partially, for the observed effect of wetland area on WNV infection risk. Our results suggest that preserving large wetland areas, and by extension, intact wetland bird communities, may represent a valuable ecosystem-based approach for controlling WNV outbreaks. ?? Mary Ann Liebert, Inc.

Flow structure at an ice-covered river confluence

NASA Astrophysics Data System (ADS)

Martel, Nancy; Biron, Pascale; Buffin-Bélanger, Thomas

2017-04-01

River confluences are known to exhibit complex relationships between flow structure, sediment transport and bed-form development. Flow structure at these sites is influenced by the junction angle, the momentum flux ratio (Mr) and bed morphology. In cold regions where an ice cover is present for most of the winter period, the flow structure is also likely affected by the roughness effect of the ice. However, very few studies have examined the impact of an ice cover on the flow structure at a confluence. The aims of this study are (1) to describe the evolution of an ice cover at a river confluence and (2) to characterize and compare the flow structure at a river confluence with and without an ice cover. The field site is a medium-sized confluence (around 40 m wide) between the Mit is and Neigette Rivers in the Bas-Saint-Laurent region, Quebec (Canada). The confluence was selected because a thick ice cover is present for most of the winter allowing for safe field work. Two winter field campaigns were conducted in 2015 and 2016 to obtain ice cover measurements in addition to hydraulic and morphological measurements. Daily monitoring of the evolution of the ice cover was made with a Reconyx camera. Velocity profiles were collected with an acoustic Doppler current profiler (ADCP) to reconstruct the three-dimensional flow structure. Time series of photographs allow the evolution of the ice cover to be mapped, linking the processes leading to the formation of the primary ice cover for each year. The time series suggests that these processes are closely related with both confluence flow zones and hydro-climatic conditions. Results on the thickness of the ice cover from in situ measurements reveal that the ice thickness tends to be thinner at the center of the confluence where high turbulent exchanges take place. Velocity measurements reveal that the ice cover affects velocity profiles by moving the highest velocities towards the center of the profiles. A spatio-temporal conceptual model is presented to illustrate the main differences on the three-dimensional flow structure at the river confluence with and without the ice cover.

Tropical cloud feedbacks and natural variability of climate

NASA Technical Reports Server (NTRS)

Miller, R. L.; Del Genio, A. D.

1994-01-01

Simulations of natural variability by two general circulation models (GCMs) are examined. One GCM is a sector model, allowing relatively rapid integration without simplification of the model physics, which would potentially exclude mechanisms of variability. Two mechanisms are found in which tropical surface temperature and sea surface temperature (SST) vary on interannual and longer timescales. Both are related to changes in cloud cover that modulate SST through the surface radiative flux. Over the equatorial ocean, SST and surface temperature vary on an interannual timescale, which is determined by the magnitude of the associated cloud cover anomalies. Over the subtropical ocean, variations in low cloud cover drive SST variations. In the sector model, the variability has no preferred timescale, but instead is characterized by a 'red' spectrum with increasing power at longer periods. In the terrestrial GCM, SST variability associated with low cloud anomalies has a decadal timescale and is the dominant form of global temperature variability. Both GCMs are coupled to a mixed layer ocean model, where dynamical heat transports are prescribed, thus filtering out El Nino-Southern Oscillation (ENSO) and thermohaline circulation variability. The occurrence of variability in the absence of dynamical ocean feedbacks suggests that climatic variability on long timescales can arise from atmospheric processes alone.

Thermal processes of thermokarst lakes in the continuous permafrost zone of northern Siberia - observations and modeling (Lena River Delta, Siberia)

NASA Astrophysics Data System (ADS)

Boike, J.; Georgi, C.; Kirilin, G.; Muster, S.; Abramova, K.; Fedorova, I.; Chetverova, A.; Grigoriev, M.; Bornemann, N.; Langer, M.

2015-10-01

Thermokarst lakes are typical features of the northern permafrost ecosystems, and play an important role in the thermal exchange between atmosphere and subsurface. The objective of this study is to describe the main thermal processes of the lakes and to quantify the heat exchange with the underlying sediments. The thermal regimes of five lakes located within the continuous permafrost zone of northern Siberia (Lena River Delta) were investigated using hourly water temperature and water level records covering a 3-year period (2009-2012), together with bathymetric survey data. The lakes included thermokarst lakes located on Holocene river terraces that may be connected to Lena River water during spring flooding, and a thermokarst lake located on deposits of the Pleistocene Ice Complex. Lakes were covered by ice up to 2 m thick that persisted for more than 7 months of the year, from October until about mid-June. Lake-bottom temperatures increased at the start of the ice-covered period due to upward-directed heat flux from the underlying thawed sediment. Prior to ice break-up, solar radiation effectively warmed the water beneath the ice cover and induced convective mixing. Ice break-up started at the beginning of June and lasted until the middle or end of June. Mixing occurred within the entire water column from the start of ice break-up and continued during the ice-free periods, as confirmed by the Wedderburn numbers, a quantitative measure of the balance between wind mixing and stratification that is important for describing the biogeochemical cycles of lakes. The lake thermal regime was modeled numerically using the FLake model. The model demonstrated good agreement with observations with regard to the mean lake temperature, with a good reproduction of the summer stratification during the ice-free period, but poor agreement during the ice-covered period. Modeled sensitivity to lake depth demonstrated that lakes in this climatic zone with mean depths > 5 m develop continuous stratification in summer for at least 1 month. The modeled vertical heat flux across the bottom sediment tends towards an annual mean of zero, with maximum downward fluxes of about 5 W m-2 in summer and with heat released back into the water column at a rate of less than 1 W m-2 during the ice-covered period. The lakes are shown to be efficient heat absorbers and effectively distribute the heat through mixing. Monthly bottom water temperatures during the ice-free period range up to 15 °C and are therefore higher than the associated monthly air or ground temperatures in the surrounding frozen permafrost landscape. The investigated lakes remain unfrozen at depth, with mean annual lake-bottom temperatures of between 2.7 and 4 °C.

Computer Applications in Social Studies.

ERIC Educational Resources Information Center

White, Charles S.

1988-01-01

Examines "Decisions, Decisions-Revolutionary Wars: Choosing Sides," an Apple II software package that emphasizes student decision-making about the nature of revolutions. Targeted at grades 5-12, the product covers a broad range of issues. Concludes that "Decisions, Decisions" models an effective decision-making process and has…

Practice Parameter for Psychiatric Consultation to Schools

ERIC Educational Resources Information Center

Journal of the American Academy of Child and Adolescent Psychiatry, 2005

2005-01-01

This practice parameter reviews the topic of psychiatric consultation to schools. The review covers the history of school consultation and current consultative models; the process of developing a consultative relationship; school administrative procedures, personnel, and milieu; legal protections for students with mental disabilities; and issues…

Fundamental Phenomena on Fuel Decomposition and Boundary-Layer Combustion Precesses with Applications to Hybrid Rocket Motors. Part 1; Experimental Investigation

NASA Technical Reports Server (NTRS)

Kuo, Kenneth K.; Lu, Yeu-Cherng; Chiaverini, Martin J.; Johnson, David K.; Serin, Nadir; Risha, Grant A.; Merkle, Charles L.; Venkateswaran, Sankaran

1996-01-01

This final report summarizes the major findings on the subject of 'Fundamental Phenomena on Fuel Decomposition and Boundary-Layer Combustion Processes with Applications to Hybrid Rocket Motors', performed from 1 April 1994 to 30 June 1996. Both experimental results from Task 1 and theoretical/numerical results from Task 2 are reported here in two parts. Part 1 covers the experimental work performed and describes the test facility setup, data reduction techniques employed, and results of the test firings, including effects of operating conditions and fuel additives on solid fuel regression rate and thermal profiles of the condensed phase. Part 2 concerns the theoretical/numerical work. It covers physical modeling of the combustion processes including gas/surface coupling, and radiation effect on regression rate. The numerical solution of the flowfield structure and condensed phase regression behavior are presented. Experimental data from the test firings were used for numerical model validation.

Observation and integrated Earth-system science: A roadmap for 2016-2025

NASA Astrophysics Data System (ADS)

Simmons, Adrian; Fellous, Jean-Louis; Ramaswamy, Venkatachalam; Trenberth, Kevin; Asrar, Ghassem; Balmaseda, Magdalena; Burrows, John P.; Ciais, Philippe; Drinkwater, Mark; Friedlingstein, Pierre; Gobron, Nadine; Guilyardi, Eric; Halpern, David; Heimann, Martin; Johannessen, Johnny; Levelt, Pieternel F.; Lopez-Baeza, Ernesto; Penner, Joyce; Scholes, Robert; Shepherd, Ted

2016-05-01

This report is the response to a request by the Committee on Space Research of the International Council for Science to prepare a roadmap on observation and integrated Earth-system science for the coming ten years. Its focus is on the combined use of observations and modelling to address the functioning, predictability and projected evolution of interacting components of the Earth system on timescales out to a century or so. It discusses how observations support integrated Earth-system science and its applications, and identifies planned enhancements to the contributing observing systems and other requirements for observations and their processing. All types of observation are considered, but emphasis is placed on those made from space. The origins and development of the integrated view of the Earth system are outlined, noting the interactions between the main components that lead to requirements for integrated science and modelling, and for the observations that guide and support them. What constitutes an Earth-system model is discussed. Summaries are given of key cycles within the Earth system. The nature of Earth observation and the arrangements for international coordination essential for effective operation of global observing systems are introduced. Instances are given of present types of observation, what is already on the roadmap for 2016-2025 and some of the issues to be faced. Observations that are organised on a systematic basis and observations that are made for process understanding and model development, or other research or demonstration purposes, are covered. Specific accounts are given for many of the variables of the Earth system. The current status and prospects for Earth-system modelling are summarized. The evolution towards applying Earth-system models for environmental monitoring and prediction as well as for climate simulation and projection is outlined. General aspects of the improvement of models, whether through refining the representations of processes that are already incorporated or through adding new processes or components, are discussed. Some important elements of Earth-system models are considered more fully. Data assimilation is discussed not only because it uses observations and models to generate datasets for monitoring the Earth system and for initiating and evaluating predictions, in particular through reanalysis, but also because of the feedback it provides on the quality of both the observations and the models employed. Inverse methods for surface-flux or model-parameter estimation are also covered. Reviews are given of the way observations and the processed datasets based on them are used for evaluating models, and of the combined use of observations and models for monitoring and interpreting the behaviour of the Earth system and for predicting and projecting its future. A set of concluding discussions covers general developmental needs, requirements for continuity of space-based observing systems, further long-term requirements for observations and other data, technological advances and data challenges, and the importance of enhanced international co-operation.

Observation and integrated Earth-system science: A roadmap for 2016–2025

DOE Office of Scientific and Technical Information (OSTI.GOV)

Simmons, Adrian; Fellous, Jean-Louis; Ramaswamy, V.

This report is the response to a request by the Committee on Space Research of the International Council for Science to prepare a roadmap on observation and integrated Earth-system science for the coming ten years. Its focus is on the combined use of observations and modelling to address the functioning, predictability and projected evolution of interacting components of the Earth system on timescales out to a century or so. It discusses how observations support integrated Earth-system science and its applications, and identifies planned enhancements to the contributing observing systems and other requirements for observations and their processing. All types ofmore » observation are considered, but emphasis is placed on those made from space. The origins and development of the integrated view of the Earth system are outlined, noting the interactions between the main components that lead to requirements for integrated science and modelling, and for the observations that guide and support them. What constitutes an Earth-system model is discussed. Summaries are given of key cycles within the Earth system. The nature of Earth observation and the arrangements for international coordination essential for effective operation of global observing systems are introduced. Instances are given of present types of observation, what is already on the roadmap for 2016–2025 and some of the issues to be faced. Observations that are organized on a systematic basis and observations that are made for process understanding and model development, or other research or demonstration purposes, are covered. Specific accounts are given for many of the variables of the Earth system. The current status and prospects for Earth-system modelling are summarized. The evolution towards applying Earth-system models for environmental monitoring and prediction as well as for climate simulation and projection is outlined. General aspects of the improvement of models, whether through refining the representations of processes that are already incorporated or through adding new processes or components, are discussed. Some important elements of Earth-system models are considered more fully. Data assimilation is discussed not only because it uses observations and models to generate datasets for monitoring the Earth system and for initiating and evaluating predictions, in particular through reanalysis, but also because of the feedback it provides on the quality of both the observations and the models employed. Inverse methods for surface-flux or model-parameter estimation are also covered. Reviews are given of the way observations and the processed datasets based on them are used for evaluating models, and of the combined use of observations and models for monitoring and interpreting the behaviour of the Earth system and for predicting and projecting its future. A set of concluding discussions covers general developmental needs, requirements for continuity of space-based observing systems, further long-term requirements for observations and other data, technological advances and data challenges, and the importance of enhanced international co-operation.« less

Preservation of Earth Science Data History with Digital Content Repository Technology

NASA Astrophysics Data System (ADS)

Wei, Y.; Pan, J.; Shrestha, B.; Cook, R. B.

2011-12-01

An increasing need for derived and on-demand data product in Earth Science research makes the digital content more difficult for providers to manage and preserve and for users to locate, understand, and consume. Specifically, this increasing need presents additional challenges in managing data processing history information and delivering such information to end users. For example, the North American Carbon Program (NACP) Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) chose a modified SYNMAP land cover data as one of the input driver data for participating terrestrial biospheric models. The global 1km resolution SYNMAP data was created by harmonizing 3 remote sensing-based land cover products: GLCC, GLC2000, and the MODIS land cover product. The original SYNMAP land cover data was aggregated into half and quarter degree resolution. It was then enhanced with more detailed grassland and cropland types. Currently, there lacks an effective mechanism to convey this data processing information to different modeling teams for them to determine if a data product meets their needs. It still highly relies on offline human interaction. The NASA-sponsored ORNL DAAC has leveraged the contemporary digital object repository technology to promote the representation, management, and delivery of data processing history and provenance information. Within digital object repository, different data products are managed as objects, with metadata as attributes and content delivery and management services as dissemination methods. Derivation relationships among data products can be semantically referenced between digital objects. Within the repository, data users can easily track a derived data product back to its origin, explorer metadata and documents about each intermediate data product, and discover processing details involved in each derivation step. Coupled with Drupal Web Content Management System, the digital repository interface was enhanced to provide intuitive graphic representation of the data processing history. Each data product is also associated with a formal metadata record in FGDC standards, and the main fields of the FGDC record are indexed for search, and are displayed as attributes of the data product. These features enable data users to better understand and consume a data product. The representation of data processing history in digital repository can further promote long-term data preservation. Lineage information is a major aspect to make digital data understandable and usable long time into the future. Derivation references can be setup between digital objects not only within a single digital repository, but also across multiple distributed digital repositories. Along with emerging identification mechanisms, such as Digital Object Identifier (DOI), a flexible distributed digital repository network can be setup to better preserve digital content. In this presentation, we describe how digital content repository technology can be used to manage, preserve, and deliver digital data processing history information in Earth Science research domain, with selected data archived in ORNL DAAC and Model and Synthesis Thematic Data Center (MAST-DC) as testing targets.

Multisensor earth observations to characterize wetlands and malaria epidemiology in Ethiopia

PubMed Central

Midekisa, Alemayehu; Senay, Gabriel B; Wimberly, Michael C

2014-01-01

Malaria is a major global public health problem, particularly in Sub-Saharan Africa. The spatial heterogeneity of malaria can be affected by factors such as hydrological processes, physiography, and land cover patterns. Tropical wetlands, for example, are important hydrological features that can serve as mosquito breeding habitats. Mapping and monitoring of wetlands using satellite remote sensing can thus help to target interventions aimed at reducing malaria transmission. The objective of this study was to map wetlands and other major land cover types in the Amhara region of Ethiopia and to analyze district-level associations of malaria and wetlands across the region. We evaluated three random forests classification models using remotely sensed topographic and spectral data based on Shuttle Radar Topographic Mission (SRTM) and Landsat TM/ETM+ imagery, respectively. The model that integrated data from both sensors yielded more accurate land cover classification than single-sensor models. The resulting map of wetlands and other major land cover classes had an overall accuracy of 93.5%. Topographic indices and subpixel level fractional cover indices contributed most strongly to the land cover classification. Further, we found strong spatial associations of percent area of wetlands with malaria cases at the district level across the dry, wet, and fall seasons. Overall, our study provided the most extensive map of wetlands for the Amhara region and documented spatiotemporal associations of wetlands and malaria risk at a broad regional level. These findings can assist public health personnel in developing strategies to effectively control and eliminate malaria in the region. Key Points Remote sensing produced an accurate wetland map for the Ethiopian highlands Wetlands were associated with spatial variability in malaria risk Mapping and monitoring wetlands can improve malaria spatial decision support PMID:25653462

Impact of vegetation dynamics on hydrological processes in a semi-arid basin by using a land surface-hydrology coupled model

NASA Astrophysics Data System (ADS)

Jiao, Yang; Lei, Huimin; Yang, Dawen; Huang, Maoyi; Liu, Dengfeng; Yuan, Xing

2017-08-01

Land surface models (LSMs) are widely used to understand the interactions between hydrological processes and vegetation dynamics, which is important for the attribution and prediction of regional hydrological variations. However, most LSMs have large uncertainties in their representations of eco-hydrological processes due to deficiencies in hydrological parameterizations. In this study, the Community Land Model version 4 (CLM4) LSM was modified with an advanced runoff generation and flow routing scheme, resulting in a new land surface-hydrology coupled model, CLM-GBHM. Both models were implemented in the Wudinghe River Basin (WRB), which is a semi-arid basin located in the middle reaches of the Yellow River, China. Compared with CLM, CLM-GBHM increased the Nash Sutcliffe efficiency for daily river discharge simulation (1965-1969) from -0.03 to 0.23 and reduced the relative bias in water table depth simulations (2010-2012) from 32.4% to 13.4%. The CLM-GBHM simulations with static, remotely sensed and model-predicted vegetation conditions showed that the vegetation in the WRB began to recover in the 2000s due to the Grain for Green Program but had not reached the same level of vegetation cover as regions in natural eco-hydrological equilibrium. Compared with a simulation using remotely sensed vegetation cover, the simulation with a dynamic vegetation model that considers only climate-induced change showed a 10.3% increase in evapotranspiration, a 47.8% decrease in runoff, and a 62.7% and 71.3% deceleration in changing trend of the outlet river discharge before and after the year 2000, respectively. This result suggests that both natural and anthropogenic factors should be incorporated in dynamic vegetation models to better simulate the eco-hydrological cycle.

Impact of vegetation dynamics on hydrological processes in a semi-arid basin by using a land surface-hydrology coupled model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiao, Yang; Lei, Huimin; Yang, Dawen

Land surface models (LSMs) are widely used to understand the interactions between hydrological processes and vegetation dynamics, which is important for the attribution and prediction of regional hydrological variations. However, most LSMs have large uncertainties in their representations of ecohydrological processes due to deficiencies in hydrological parameterizations. In this study, the Community Land Model version 4 (CLM4) LSM was modified with an advanced runoff generation and flow routing scheme, resulting in a new land surface-hydrology coupled model, CLM-GBHM. Both models were implemented in the Wudinghe River Basin (WRB), which is a semi-arid basin located in the middle reaches of themore » Yellow River, China. Compared with CLM, CLM-GBHM increased the Nash Sutcliffe efficiency for daily river discharge simulation (1965–1969) from 0.03 to 0.23 and reduced the relative bias in water table depth simulations (2010–2012) from 32.4% to 13.4%. The CLM-GBHM simulations with static, remotely sensed and model-predicted vegetation conditions showed that the vegetation in the WRB began to recover in the 2000s due to the Grain for Green Program but had not reached the same level of vegetation cover as regions in natural eco-hydrological equilibrium. Compared with a simulation using remotely sensed vegetation cover, the simulation with a dynamic vegetation model that considers only climate-induced change showed a 10.3% increase in evapotranspiration, a 47.8% decrease in runoff, and a 62.7% and 71.3% deceleration in changing trend of the outlet river discharge before and after the year 2000, respectively. This result suggests that both natural and anthropogenic factors should be incorporated in dynamic vegetation models to better simulate the eco-hydrological cycle.« less

Dual-Use Space Technology Transfer Conference and Exhibition. Volume 1

NASA Technical Reports Server (NTRS)

Krishen, Kumar (Compiler)

1994-01-01

This document contains papers presented at the Dual-Use Space Technology Transfer Conference and Exhibition held at the Johnson Space Center February 1-3, 1994. Possible technology transfers covered during the conference were in the areas of information access; innovative microwave and optical applications; materials and structures; marketing and barriers; intelligent systems; human factors and habitation; communications and data systems; business process and technology transfer; software engineering; biotechnology and advanced bioinstrumentation; communications signal processing and analysis; new ways of doing business; medical care; applications derived from control center data systems; human performance evaluation; technology transfer methods; mathematics, modeling, and simulation; propulsion; software analysis and decision tools systems/processes in human support technology; networks, control centers, and distributed systems; power; rapid development perception and vision technologies; integrated vehicle health management; automation technologies; advanced avionics; ans robotics technologies. More than 77 papers, 20 presentations, and 20 exhibits covering various disciplines were presented b experts from NASA, universities, and industry.

Effects of wildfire on catchment runoff response: a modeling approach to detect changes in snow-dominated forested catchments

Treesearch

Jan Seibert; Jeffrey J. McDonnell; Richard D. Woodsmith

2010-01-01

Wildfire is an important disturbance affecting hydrological processes through alteration of vegetation cover and soil characteristics. The effects of fire on hydrological systems at the catchment scale are not well known, largely because site specific data from both before and after wildfire are rare. In this study a modelling approach was employed for change detection...

Short Range Acoustic Propagation Under Arctic Ice Cover During Icex 16

DTIC Science & Technology

2016-09-01

There is no immediately apparent pattern to the discontinuity between modeled and observed transmission loss . In some cases, the modeled values are...Reeder THIS PAGE INTENTIONALLY LEFT BLANK i REPORT DOCUMENTATION PAGE Form Approved OMB No . 0704–0188 Public reporting burden for this...transmission loss in the observed frequency, range, and depth combinations. The received signals were processed and analyzed to determine observed

Climate and land use controls over terrestrial water use efficiency in monsoon Asia.

Treesearch

Hanqin Tian; Chaoqun Lu; Guangsheng Chen; Xiaofeng Xu; Mingliang Liu; et al

2011-01-01

Much concern has been raised regarding how and to what extent climate change and intensive human activities have altered water use efficiency (WUE, amount of carbon uptake per unit of water use) in monsoon Asia. By using a process-based ecosystem model [dynamic land ecosystem model (DLEM)], we examined effects of climate change, land use/cover change, and land...

Breaking New Ground: Teaching Skills of Intelligence. Lethbridge Catholic Separate School District No. 9.

ERIC Educational Resources Information Center

Lethbridge Catholic Separate School District #9 (Alberta).

The objectives of the 2-year Thinking Skills Project were to provide teachers and students with a set of thinking skills, to develop and validate a model of cognition for teachers, to devise a Measure of Questioning Skills, and to establish a normative base for this instrument. The model of essential thinking skills covers the basic processes: (1)…

The M-type stars

NASA Technical Reports Server (NTRS)

Johnson, Hollis Ralph; Querci, Francois R.; Jordan, Stuart (Editor); Thomas, Richard (Editor); Goldberg, Leo; Pecker, Jean-Claude

1987-01-01

The papers in this volume cover the following topics: (1) basic properties and photometric variability of M and related stars; (2) spectroscopy and nonthermal processes; (3) circumstellar radio molecular lines; (4) circumstellar shells, the formation of grains, and radiation transfer; (5) mass loss; (6) circumstellar chemistry; (7) thermal atmospheric models; (8) quasi-thermal models; (9) observations on the atmospheres of M dwarfs; and (1) theoretical work on M dwarfs.

Age, origin and evolution of Antarctic debris-covered glaciers: Implications for landscape evolution and long-term climate change

NASA Astrophysics Data System (ADS)

Mackay, Sean Leland

Antarctic debris-covered glaciers are potential archives of long-term climate change. However, the geomorphic response of these systems to climate forcing is not well understood. To address this concern, I conducted a series of field-based and numerical modeling studies in the McMurdo Dry Valleys of Antarctica (MDV), with a focus on Mullins and Friedman glaciers. I used data and results from geophysical surveys, ice-core collection and analysis, geomorphic mapping, micro-meteorological stations, and numerical-process models to (1) determine the precise origin and distribution of englacial and supraglacial debris within these buried-ice systems, (2) quantify the fundamental processes and feedbacks that govern interactions among englacial and supraglacial debris, (3) establish a process-based model to quantify the inventory of cosmogenic nuclides within englacial and supraglacial debris, and (4) isolate the governing relationships between the evolution of englacial /supraglacial debris and regional climate forcing. Results from 93 field excavations, 21 ice cores, and 24 km of ground-penetrating radar data show that Mullins and Friedman glaciers contain vast areas of clean glacier ice interspersed with inclined layers of concentrated debris. The similarity in the pattern of englacial debris bands across both glaciers, along with model results that call for negligible basal entrainment, is best explained by episodic environmental change at valley headwalls. To constrain better the timing of debris-band formation, I developed a modeling framework that tracks the accumulation of cosmogenic 3He in englacial and supraglacial debris. Results imply that ice within Mullins Glacier increases in age non-linearly from 12 ka to ˜220 ka in areas of active flow (up to >> 1.6 Ma in areas of slow-moving-to-stagnant ice) and that englacial debris bands originate with a periodicity of ˜41 ka. Modeling studies suggest that debris bands originate in synchronicity with changes in obliquity-paced, total integrated summer insolation. The implication is that the englacial structure and surface morphology of some cold-based, debris-covered glaciers can preserve high-resolution climate archives that exceed the typical resolution of Antarctic terrestrial deposits and moraine records.

A pattern-based analysis of clinical computer-interpretable guideline modeling languages.

PubMed

Mulyar, Nataliya; van der Aalst, Wil M P; Peleg, Mor

2007-01-01

Languages used to specify computer-interpretable guidelines (CIGs) differ in their approaches to addressing particular modeling challenges. The main goals of this article are: (1) to examine the expressive power of CIG modeling languages, and (2) to define the differences, from the control-flow perspective, between process languages in workflow management systems and modeling languages used to design clinical guidelines. The pattern-based analysis was applied to guideline modeling languages Asbru, EON, GLIF, and PROforma. We focused on control-flow and left other perspectives out of consideration. We evaluated the selected CIG modeling languages and identified their degree of support of 43 control-flow patterns. We used a set of explicitly defined evaluation criteria to determine whether each pattern is supported directly, indirectly, or not at all. PROforma offers direct support for 22 of 43 patterns, Asbru 20, GLIF 17, and EON 11. All four directly support basic control-flow patterns, cancellation patterns, and some advance branching and synchronization patterns. None support multiple instances patterns. They offer varying levels of support for synchronizing merge patterns and state-based patterns. Some support a few scenarios not covered by the 43 control-flow patterns. CIG modeling languages are remarkably close to traditional workflow languages from the control-flow perspective, but cover many fewer workflow patterns. CIG languages offer some flexibility that supports modeling of complex decisions and provide ways for modeling some decisions not covered by workflow management systems. Workflow management systems may be suitable for clinical guideline applications.

Simulating the hydrological impacts of inter-annual and seasonal variability in land use land cover change on streamflow

NASA Astrophysics Data System (ADS)

Taxak, A. K.; Ojha, C. S. P.

2017-12-01

Land use and land cover (LULC) changes within a watershed are recognised as an important factor affecting hydrological processes and water resources. LULC changes continuously not only in long term but also on the inter-annual and season level. Changes in LULC affects the interception, storage and moisture. A widely used approach in rainfall-runoff modelling through Land surface models (LSM)/ hydrological models is to keep LULC same throughout the model running period. In long term simulations where land use change take place during the run period, using a single LULC does not represent a true picture of ground conditions could result in stationarity of model responses. The present work presents a case study in which changes in LULC are incorporated by using multiple LULC layers. LULC for the study period were created using imageries from Landsat series, Sentinal, EO-1 ALI. Distributed, physically based Variable Infiltration Capacity (VIC) model was modified to allow inclusion of LULC as a time varying variable just like climate. The Narayani basin was simulated with LULC, leaf area index (LAI), albedo and climate data for 1992-2015. The results showed that the model simulation with varied parametrization approach has a large improvement over the conventional fixed parametrization approach in terms of long-term water balance. The proposed modelling approach could improve hydrological modelling for applications like land cover change studies, water budget studies etc.

Ionospheres of the terrestrial planets

NASA Astrophysics Data System (ADS)

Schunk, R. W.; Nagy, A. F.

1980-11-01

The theory and observations relating to the ionospheres of the terrestrial planets Venus, the earth, and Mars are reviewed. Emphasis is placed on comparing the basic differences and similarities between the planetary ionospheres. The review covers the plasma and electric-magnetic field environments that surround the planets, the theory leading to the creation and transport of ionization in the ionospheres, the relevant observations, and the most recent model calculations. The theory section includes a discussion of ambipolar diffusion in a partially ionized plasma, diffusion in a fully ionized plasma, supersonic plasma flow, photochemistry, and heating and cooling processes. The sections on observations and model calculations cover the neutral atmosphere composition, the ion composition, the electron density, and the electron, ion, and neutral temperatures.

Are stock market returns related to the weather effects? Empirical evidence from Taiwan

NASA Astrophysics Data System (ADS)

Chang, Tsangyao; Nieh, Chien-Chung; Yang, Ming Jing; Yang, Tse-Yu

2006-05-01

In this study, we employ a recently developed econometric technique of the threshold model with the GJR-GARCH process on error terms to investigate the relationships between weather factors and stock market returns in Taiwan using daily data for the period of 1 July 1997-22 October 2003. The major weather factors studied include temperature, humidity, and cloud cover. Our empirical evidence shows that temperature and cloud cover are two important weather factors that affect the stock returns in Taiwan. Our empirical findings further support the previous arguments that advocate the inclusion of economically neutral behavioral variables in asset pricing models. These results also have significant implications for individual investors and financial institutions planning to invest in the Taiwan stock market.

Modelling the feedbacks between mass balance, ice flow and debris transport to predict the response to climate change of debris-covered glaciers in the Himalaya

NASA Astrophysics Data System (ADS)

Rowan, Ann V.; Egholm, David L.; Quincey, Duncan J.; Glasser, Neil F.

2015-11-01

Many Himalayan glaciers are characterised in their lower reaches by a rock debris layer. This debris insulates the glacier surface from atmospheric warming and complicates the response to climate change compared to glaciers with clean-ice surfaces. Debris-covered glaciers can persist well below the altitude that would be sustainable for clean-ice glaciers, resulting in much longer timescales of mass loss and meltwater production. The properties and evolution of supraglacial debris present a considerable challenge to understanding future glacier change. Existing approaches to predicting variations in glacier volume and meltwater production rely on numerical models that represent the processes governing glaciers with clean-ice surfaces, and yield conflicting results. We developed a numerical model that couples the flow of ice and debris and includes important feedbacks between debris accumulation and glacier mass balance. To investigate the impact of debris transport on the response of a glacier to recent and future climate change, we applied this model to a large debris-covered Himalayan glacier-Khumbu Glacier in Nepal. Our results demonstrate that supraglacial debris prolongs the response of the glacier to warming and causes lowering of the glacier surface in situ, concealing the magnitude of mass loss when compared with estimates based on glacierised area. Since the Little Ice Age, Khumbu Glacier has lost 34% of its volume while its area has reduced by only 6%. We predict a decrease in glacier volume of 8-10% by AD2100, accompanied by dynamic and physical detachment of the debris-covered tongue from the active glacier within the next 150 yr. This detachment will accelerate rates of glacier decay, and similar changes are likely for other debris-covered glaciers in the Himalaya.

Remotely Sensed Thermal Anomalies in Western Colorado

DOE Data Explorer

Khalid Hussein

2012-02-01

This layer contains the areas identified as areas of anomalous surface temperature from Landsat satellite imagery in Western Colorado. Data was obtained for two different dates. The digital numbers of each Landsat scene were converted to radiance and the temperature was calculated in degrees Kelvin and then converted to degrees Celsius for each land cover type using the emissivity of that cover type. And this process was repeated for each of the land cover types (open water, barren, deciduous forest and evergreen forest, mixed forest, shrub/scrub, grassland/herbaceous, pasture hay, and cultivated crops). The temperature of each pixel within each scene was calculated using the thermal band. In order to calculate the temperature an average emissivity value was used for each land cover type within each scene. The NLCD 2001 land cover classification raster data of the zones that cover Colorado were downloaded from USGS site and used to identify the land cover types within each scene. Areas that had temperature residual greater than 2o, and areas with temperature equal to 1o to 2o, were considered Landsat modeled very warm and warm surface exposures (thermal anomalies), respectively. Note: 'o' is used in this description to represent lowercase sigma.

Impacts of land use/cover change on ecosystem services for Xiamen

NASA Astrophysics Data System (ADS)

Shi, L.; Cui, S.

2009-12-01

Based on remote sensing images of Xiamen in 1987, 1997 and 2007, the process of ecosystem service alteration resulting from land use/cover change was quantitatively analyzed through RS and GIS techniques. Consulting relative researches, an integrated assessment model was built to evaluating regional ecosystem services of Xiamen. The results showed that the total ecosystem service value of Xiamen was increased by 14.67%, from 3271.5 million to 3751.39 RMB. The relative change rate of supplying service, regulation service, cultural service and supporting service were 97.8%, -25.1%, 165.0% and -44.7% respectively, which indicated that land use/ cover change had positive effects on supplying and cultural service, whereas it had negatively affected both regulation service and supporting service. Land use/cover types of Xiamen in 1987, 1997 and 2007 Ecosystem values of Xiamen in 1987, 1997 and 2007 10 thousand RMB

Runoff sensitivity to snowmelt process representation for the conterminous United States

NASA Astrophysics Data System (ADS)

Driscoll, J. M.; Sexstone, G. A.

2017-12-01

Watershed-scale hydrologic models that operate at a continental extent must balance detailed descriptions of spatiotemporal variability against simplified process representations across a diverse range of physiographic and climatic regimes. Some of these models describe the sub-grid variability of snow-cover extent and snowmelt processes using snow depletion curves (SDCs), which relate the snow covered area to the snow water equivalent (SWE). The U.S. Geological Survey's National Hydrologic Modeling (NHM) system run with the daily-timestep Precipitation Runoff Modeling System (PRMS), or NHM-PRMS, originally used two default SDCs to describe snowmelt processes: one for hydrologic response units with elevations above treeline and one for hydrologic response units with elevations below treeline. Seeking to improve upon this approach, spatially-distributed SWE, derived from Snow Data Assimilation System (SNODAS) over eleven years, was used to develop new, site-specific SDCs for each hydrologic response unit in the NHM-PRMS. This study investigates the sensitivity of NHM-PRMS to changes in SDCs for a 30-year historical period by first running the NHM-PRMS with the default binary SDCs and then with the site-specific SDCs. Comparison of simulated snowmelt and streamflow response during the snowmelt season allows for spatial analysis and grouping of the sensitivity of streamflow to changes in snowmelt dynamics. Site-specific SDCs allow for the identification and categorization of areas where faster or slower snowmelt could have a greater impact to water resources. These new SDCs can be used to identify locations where increased SWE observation density would be most useful for seasonal water availability assessments.

Exobiology site selection for future Mars missions: Martian paleolake sediments and terrestrial analogs

NASA Technical Reports Server (NTRS)

Wharton, Robert A., Jr.

1989-01-01

This research was conducted to establish the scientific framework for the exobiological study of sediments on Mars and to encourage the selection of these sedimentary deposits as sampling sites for future Mars missions. A study was completed on the Antarctic Dry Valley Lakes (terrestrial analogs of the purported Martian paleolakes) and their sediments that allowed the development of quantitative models relating environmental factors to the nature of the biological community and sediment forming processes. The publications presented include: (1) Diversity of micro-fungi isolated in an Antarctic dry valley; (2) Lake Hoare, Antarctica--sedimentation through a thick perennial ice cover; (3) The possibility of life on Mars during a water-rich past; (4) An Antarctic research outpost as a model for planetary exploration; (5) Early Martian environments--the Antarctic and other terrestrial analogs; (6) Lipophilic pigments from the benthos of a perennially ice-covered Antarctic lake; and (7) Perennially ice-covered Lake Hoare, Antarctica--physical environment, biology, and sedimentation.

Vegetation Continuous Fields--Transitioning from MODIS to VIIRS

NASA Astrophysics Data System (ADS)

DiMiceli, C.; Townshend, J. R.; Sohlberg, R. A.; Kim, D. H.; Kelly, M.

2015-12-01

Measurements of fractional vegetation cover are critical for accurate and consistent monitoring of global deforestation rates. They also provide important parameters for land surface, climate and carbon models and vital background data for research into fire, hydrological and ecosystem processes. MODIS Vegetation Continuous Fields (VCF) products provide four complementary layers of fractional cover: tree cover, non-tree vegetation, bare ground, and surface water. MODIS VCF products are currently produced globally and annually at 250m resolution for 2000 to the present. Additionally, annual VCF products at 1/20° resolution derived from AVHRR and MODIS Long-Term Data Records are in development to provide Earth System Data Records of fractional vegetation cover for 1982 to the present. In order to provide continuity of these valuable products, we are extending the VCF algorithms to create Suomi NPP/VIIRS VCF products. This presentation will highlight the first VIIRS fractional cover product: global percent tree cover at 1 km resolution. To create this product, phenological and physiological metrics were derived from each complete year of VIIRS 8-day surface reflectance products. A supervised regression tree method was applied to the metrics, using training derived from Landsat data supplemented by high-resolution data from Ikonos, RapidEye and QuickBird. The regression tree model was then applied globally to produce fractional tree cover. In our presentation we will detail our methods for creating the VIIRS VCF product. We will compare the new VIIRS VCF product to our current MODIS VCF products and demonstrate continuity between instruments. Finally, we will outline future VIIRS VCF development plans.

Effects of Varying Cloud Cover on Springtime Runoff in California's Sierra Nevada

NASA Astrophysics Data System (ADS)

Sumargo, E.; Cayan, D. R.

2017-12-01

This study investigates how cloud cover modifies snowmelt-runoff processes in Sierra Nevada watersheds during dry and wet periods. We use two of the California Department of Water Resources' (DWR's) quasi-operational models of the Tuolumne and Merced River basins developed from the USGS Precipitation-Runoff Modeling System (PRMS) hydrologic modeling system. Model simulations are conducted after a validated optimization of model performance in simulating recent (1996-2014) historical variability in the Tuolumne and Merced basins using solar radiation (Qsi) derived from Geostationary Operational Environmental Satellite (GOES) remote sensing. Specifically, the questions we address are: 1) how sensitive are snowmelt and runoff in the Tuolumne and Merced River basins to Qsi variability associated with cloud cover variations?, and 2) does this sensitivity change in dry vs. wet years? To address these question, we conduct two experiments, where: E1) theoretical clear-sky Qsi is used as an input to PRMS, and E2) the annual harmonic cycle of Qsi is used as an input to PRMS. The resulting hydrographs from these experiments exhibit changes in peak streamflow timing by several days to a few weeks and smaller streamflow variability when compared to the actual flows and the original simulations. For E1, despite some variations, this pattern persists when the result is evaluated for dry-year and wet-year subsets, reflecting the consistently higher Qsi input available. For E2, the hydrograph shows a later spring-summer streamflow peak in the dry-year subset when compared to the original simulations, indicating the relative importance of the modulating effect of cloud cover on snowmelt-runoff in drier years.

One NASA: Sharing Knowledge Through an Agency-wide Process Asset Library (PAL)

NASA Technical Reports Server (NTRS)

Truss, Baraka J.

2006-01-01

This poster session will cover the key purpose and components behind implementing the NASA PAL website. This session will present the current results, describing the process used to create the website, the current usage measure, and will demonstrate how NASA is truly becoming ONE. The target audience for the poster session includes those currently implementing the CMMI model and looking for PAL adoption techniques. To continue to be the leader in space, science and technology, NASA is using this agency-wide PAL to share knowledge, work products and lessons learned through this website. Many organizations have failed to recognize how the efforts of process improvement fit into overall organizational effort. However, NASA as an agency has adopted the benefits of process improvement by the creation of this website to foster communication between its ten centers. The poster session will cover the following, topics outlined below: 1) Website purpose; 2) Characteristics of the website; 3) User accounts status; 4) Website content size; and 5) Usage percentages.

Using fuzzy rule-based knowledge model for optimum plating conditions search

NASA Astrophysics Data System (ADS)

Solovjev, D. S.; Solovjeva, I. A.; Litovka, Yu V.; Arzamastsev, A. A.; Glazkov, V. P.; L’vov, A. A.

2018-03-01

The paper discusses existing approaches to plating process modeling in order to decrease the distribution thickness of plating surface cover. However, these approaches do not take into account the experience, knowledge, and intuition of the decision-makers when searching the optimal conditions of electroplating technological process. The original approach to optimal conditions search for applying the electroplating coatings, which uses the rule-based model of knowledge and allows one to reduce the uneven product thickness distribution, is proposed. The block diagrams of a conventional control system of a galvanic process as well as the system based on the production model of knowledge are considered. It is shown that the fuzzy production model of knowledge in the control system makes it possible to obtain galvanic coatings of a given thickness unevenness with a high degree of adequacy to the experimental data. The described experimental results confirm the theoretical conclusions.

[Mathematic concept model of accumulation of functional disorders associated with environmental factors].

PubMed

Zaĭtseva, N V; Trusov, P V; Kir'ianov, D A

2012-01-01

The mathematic concept model presented describes accumulation of functional disorders associated with environmental factors, plays predictive role and is designed for assessments of possible effects caused by heterogenous factors with variable exposures. Considering exposure changes with self-restoration process opens prospects of using the model to evaluate, analyse and manage occupational risks. To develop current theoretic approaches, the authors suggested a model considering age-related body peculiarities, systemic interactions of organs, including neuro-humoral regulation, accumulation of functional disorders due to external factors, rehabilitation of functions during treatment. General objective setting covers defining over a hundred unknow coefficients that characterize speed of various processes within the body. To solve this problem, the authors used iteration approach, successive identification, that starts from the certain primary approximation of the model parameters and processes subsequent updating on the basis of new theoretic and empirical knowledge.

Climate Model Tests of the Early Anthropogenic Hypothesis

NASA Astrophysics Data System (ADS)

Vavrus, S.; Kutzbach, J.; Philippon, G.

2008-12-01

We test the hypothesis that greenhouse gas emissions produced by the combination of early and recent human activities, augmented by additional rises in greenhouse gases through ocean feedbacks, have kept the climate warmer than its natural level and offset an incipient glaciation. We use four different configurations of NCAR's Community Climate System Model to investigate the natural climate that should exist today if CO2 and CH4 concentrations had fallen to their average levels reached during previous interglaciations. The model simulations consist of three using a coupled atmosphere-slab ocean configuration---fixed land cover at moderate (T42) and high (T85) model resolution and interactive vegetation composition at T42 resolution--and one employing a coupled atmosphere-dynamical ocean configuration and fixed land cover at T42 resolution. With greenhouse gas concentrations lowered to their estimated natural levels, global mean temperature falls by 2.5-3.0 K in all four experiments. Of the total global cooling with fixed land cover and moderate model resolution, 38% (62%) is attributable to early agricultural activities (industrialization), while early agriculture accounts for approximately half of the expanded permanent snow cover area. The greenhouse cooling triggers widespread glacial inception in the Northern Hemisphere, where permanent snow cover expands by at least 80% and even more with the addition of enhanced model processes: 130% with the dynamical ocean, 150% with high (T85) model resolution, and 200% with vegetation feedbacks included. The regional pattern of incipient glaciation is strongly influenced by atmospheric and circulation changes, sea ice feedbacks, and model resolution. The simulation with a dynamical ocean produces a decrease in vertically integrated global ocean temperature of 1.25 K, a 20% weakening of the Atlantic meridional overturning cell, and an expansion of sea ice and reduced upwelling in the Southern Ocean. Viewed from the perspective of explaining the unusual late-Holocene increases of CO2 that occurred prior to the Industrial Revolution, these simulated changes in ocean temperature, sea ice cover, and circulation (with sign reversed) support the hypothesis that early agriculture played a role in initiating anomalous warming that thwarted incipient glaciation beginning several thousand years ago. Decreased ocean solubility globally and positive ocean/sea-ice feedbacks in the Southern Hemisphere probably augmented the initial CO2 increase and caused additional warming.

Medical Writing Competency Model - Section 1: Functions, Tasks, and Activities.

PubMed

Clemow, David B; Wagner, Bertil; Marshallsay, Christopher; Benau, Dan; L'Heureux, Darryl; Brown, David H; Dasgupta, Devjani Ghosh; Girten, Eileen; Hubbard, Frank; Gawrylewski, Helle-Mai; Ebina, Hiroko; Stoltenborg, Janet; York, J P; Green, Kim; Wood, Linda Fossati; Toth, Lisa; Mihm, Michael; Katz, Nancy R; Vasconcelos, Nina-Maria; Sakiyama, Norihisa; Whitsell, Robin; Gopalakrishnan, Shobha; Bairnsfather, Susan; Wanderer, Tatyana; Schindler, Thomas M; Mikyas, Yeshi; Aoyama, Yumiko

2018-01-01

This article provides Section 1 of the 2017 Edition 2 Medical Writing Competency Model that describes the core work functions and associated tasks and activities related to professional medical writing within the life sciences industry. The functions in the Model are scientific communication strategy; document preparation, development, and finalization; document project management; document template, standard, format, and style development and maintenance; outsourcing, alliance partner, and client management; knowledge, skill, ability, and behavior development and sharing; and process improvement. The full Model also includes Section 2, which covers the knowledge, skills, abilities, and behaviors needed for medical writers to be effective in their roles; Section 2 is presented in a companion article. Regulatory, publication, and other scientific writing as well as management of writing activities are covered. The Model was developed to aid medical writers and managers within the life sciences industry regarding medical writing hiring, training, expectation and goal setting, performance evaluation, career development, retention, and role value sharing to cross-functional partners.

Integrated firn elevation change model for glaciers and ice caps

NASA Astrophysics Data System (ADS)

Saß, Björn; Sauter, Tobias; Braun, Matthias

2016-04-01

We present the development of a firn compaction model in order to improve the volume to mass conversion of geodetic glacier mass balance measurements. The model is applied on the Arctic ice cap Vestfonna. Vestfonna is located on the island Nordaustlandet in the north east of Svalbard. Vestfonna covers about 2400 km² and has a dome like shape with well-defined outlet glaciers. Elevation and volume changes measured by e.g. satellite techniques are becoming more and more popular. They are carried out over observation periods of variable length and often covering different meteorological and snow hydrological regimes. The elevation change measurements compose of various components including dynamic adjustments, firn compaction and mass loss by downwasting. Currently, geodetic glacier mass balances are frequently converted from elevation change measurements using a constant conversion factor of 850 kg m-³ or the density of ice (917 kg m-³) for entire glacier basins. However, the natural conditions are rarely that static. Other studies used constant densities for the ablation (900 kg m-³) and accumulation (600 kg m-³) areas, whereby density variations with varying meteorological and climate conditions are not considered. Hence, each approach bears additional uncertainties from the volume to mass conversion that are strongly affected by the type and timing of the repeat measurements. We link and adapt existing models of surface energy balance, accumulation and snow and firn processes in order to improve the volume to mass conversion by considering the firn compaction component. Energy exchange at the surface is computed by a surface energy balance approach and driven by meteorological variables like incoming short-wave radiation, air temperature, relative humidity, air pressure, wind speed, all-phase precipitation, and cloud cover fraction. Snow and firn processes are addressed by a coupled subsurface model, implemented with a non-equidistant layer discretisation. On our poster we present a general view on the model structure, the input data (model forcing) and finally, an exemplary test case with basic approaches of validation.

RCRA, Superfund and EPCRA hotline training module. Introduction to: Superfund accelerated cleanup model (updated February 1998); Directive

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

1998-06-01

This module presents the primary aspects of SACM compared to the traditional Superfund response process. In addition, this module discusses presumptive remedies by covering what they are, and providing an overview of the guidance EPA has developed.

Deforestation Impacts on Bat Functional Diversity in Tropical Landscapes

PubMed Central

García-Morales, Rodrigo; Badano, Ernesto I.; Zuria, Iriana; Galindo-González, Jorge; Rojas-Martínez, Alberto E.; Ávila-Gómez, Eva S.

2016-01-01

Functional diversity is the variability in the functional roles carried out by species within ecosystems. Changes in the environment can affect this component of biodiversity and can, in turn, affect different processes, including some ecosystem services. This study aimed to determine the effect of forest loss on species richness, abundance and functional diversity of Neotropical bats. To this end, we identified six landscapes with increasing loss of forest cover in the Huasteca region of the state of Hidalgo, Mexico. We captured bats in each landscape using mist nets, and calculated functional diversity indices (functional richness and functional evenness) along with species richness and abundance. We analyzed these measures in terms of percent forest cover. We captured 906 bats (Phyllostomidae and Mormoopidae), including 10 genera and 12 species. Species richness, abundance and functional richness per night are positively related with forest cover. Generalized linear models show that species richness, abundance and functional richness per night are significantly related with forest cover, while seasonality had an effect on abundance and functional richness. Neither forest cover nor season had a significant effect on functional evenness. All these findings were consistent across three spatial scales (1, 3 and 5 km radius around sampling sites). The decrease in species, abundance and functional richness of bats with forest loss may have implications for the ecological processes they carry out such as seed dispersal, pollination and insect predation, among others. PMID:27926923

Remote Sensing and Imaging Physics

DTIC Science & Technology

2012-03-07

Model Analysis Process Wire-frame Shape Model a s s u m e d a p rio ri k n o w le d g e No material BRDF library employed in retrieval...a collection of information if it does not display a currently valid OMB control number. 1. REPORT DATE 07 MAR 2012 2. REPORT TYPE 3. DATES COVERED...imaging estimation problems Allows properties of local maxima to be derived from the Kolmogorov model of atmospheric turbulence: Each speckle

Computational models of music perception and cognition I: The perceptual and cognitive processing chain

NASA Astrophysics Data System (ADS)

Purwins, Hendrik; Herrera, Perfecto; Grachten, Maarten; Hazan, Amaury; Marxer, Ricard; Serra, Xavier

2008-09-01

We present a review on perception and cognition models designed for or applicable to music. An emphasis is put on computational implementations. We include findings from different disciplines: neuroscience, psychology, cognitive science, artificial intelligence, and musicology. The article summarizes the methodology that these disciplines use to approach the phenomena of music understanding, the localization of musical processes in the brain, and the flow of cognitive operations involved in turning physical signals into musical symbols, going from the transducers to the memory systems of the brain. We discuss formal models developed to emulate, explain and predict phenomena involved in early auditory processing, pitch processing, grouping, source separation, and music structure computation. We cover generic computational architectures of attention, memory, and expectation that can be instantiated and tuned to deal with specific musical phenomena. Criteria for the evaluation of such models are presented and discussed. Thereby, we lay out the general framework that provides the basis for the discussion of domain-specific music models in Part II.

The effects of psammophilous plants on sand dune dynamics

NASA Astrophysics Data System (ADS)

Bel, Golan; Ashkenazy, Yosef

2014-07-01

Mathematical models of sand dune dynamics have considered different types of sand dune cover. However, despite the important role of psammophilous plants (plants that flourish in moving-sand environments) in dune dynamics, the incorporation of their effects into mathematical models of sand dunes remains a challenging task. Here we propose a nonlinear physical model for the role of psammophilous plants in the stabilization and destabilization of sand dunes. There are two main mechanisms by which the wind affects these plants: (i) sand drift results in the burial and exposure of plants, a process that is known to result in an enhanced growth rate, and (ii) strong winds remove shoots and rhizomes and seed them in nearby locations, enhancing their growth rate. Our model describes the temporal evolution of the fractions of surface cover of regular vegetation, biogenic soil crust, and psammophilous plants. The latter reach their optimal growth under either (i) specific sand drift or (ii) specific wind power. The model exhibits complex bifurcation diagrams and dynamics, which explain observed phenomena, and it predicts new dune stabilization scenarios. Depending on the climatological conditions, it is possible to obtain one, two, or, predicted here for the first time, three stable dune states. Our model shows that the development of the different cover types depends on the precipitation rate and the wind power and that the psammophilous plants are not always the first to grow and stabilize the dunes.

Impacts of regional land-grab on regional hydroclimate in southeastern Africa via modeling and remote sensing

NASA Astrophysics Data System (ADS)

Maksimowicz, M.; Masarik, M. T.; Brandt, J.; Flores, A. N.

2017-12-01

Land use/land cover (LULC) change directly impacts the partitioning of surface mass and energy fluxes. Regional-scale weather and climate are potentially altered by LULC if the resultant changes in partitioning of surface energy fluxes are significant enough to induce changes in the evolution of the planetary boundary layer and its interaction with the atmosphere above. Dynamics of land use, particularly those related to the social dimensions of the Earth System, are often simplified or not represented in regional land-atmosphere models or Earth System Models. This study explores the role of LULC change on a regional hydroclimate system, focusing on potential hydroclimate changes arising from timber harvesting due to a land grab boom in Mozambique. We also focus more narrowly at quantifying regional impacts on Gorongosa National Park, a nationally important economic and biodiversity resource in southeastern Africa. After nationalizing all land in 1975 after Mozambique gained independence, complex social processes, including an extended low intensity conflict civil war and economic hardships, led to an escalation of land use rights grants to foreign governments. Between 2004 and 2009, large tracts of land were requested for timber. Here we use existing tree cover loss datasets to more accurately represent land cover within a regional weather model. LULC in a region encompassing Gorongosa is updated at three instances between 2001 and 2014 using a tree cover loss dataset. We use these derived LULC datasets to inform lower boundary conditions in the Weather Research and Forecasting (WRF) model. To quantify potential hydrometeorological changes arising from land use change, we performed a factorial-like experiment by mixing input LULC maps and atmospheric forcing data from before, during, and after the land grab. Results suggest that the land grab has impacted microclimate parameters in a significant way via direct and indirect impacts on land-atmosphere interactions. Results of this study suggest that LULC change arising from regional social dynamics are a potentially understudied, yet important human process to capture in both regional reanalyses and climate change projections.

Model for the alpha and beta shear-mechanical properties of supercooled liquids and its comparison to squalane data

NASA Astrophysics Data System (ADS)

Hecksher, Tina; Olsen, Niels Boye; Dyre, Jeppe C.

2017-04-01

This paper presents data for supercooled squalane's frequency-dependent shear modulus covering frequencies from 10 mHz to 30 kHz and temperatures from 168 K to 190 K; measurements are also reported for the glass phase down to 146 K. The data reveal a strong mechanical beta process. A model is proposed for the shear response of the metastable equilibrium liquid phase of supercooled liquids. The model is an electrical equivalent-circuit characterized by additivity of the dynamic shear compliances of the alpha and beta processes. The nontrivial parts of the alpha and beta processes are each represented by a "Cole-Cole retardation element" defined as a series connection of a capacitor and a constant-phase element, resulting in the Cole-Cole compliance function well-known from dielectrics. The model, which assumes that the high-frequency decay of the alpha shear compliance loss varies with the angular frequency as ω-1 /2, has seven parameters. Assuming time-temperature superposition for the alpha and beta processes separately, the number of parameters varying with temperature is reduced to four. The model provides a better fit to the data than an equally parametrized Havriliak-Negami type model. From the temperature dependence of the best-fit model parameters, the following conclusions are drawn: (1) the alpha relaxation time conforms to the shoving model; (2) the beta relaxation loss-peak frequency is almost temperature independent; (3) the alpha compliance magnitude, which in the model equals the inverse of the instantaneous shear modulus, is only weakly temperature dependent; (4) the beta compliance magnitude decreases by a factor of three upon cooling in the temperature range studied. The final part of the paper briefly presents measurements of the dynamic adiabatic bulk modulus covering frequencies from 10 mHz to 10 kHz in the temperature range from 172 K to 200 K. The data are qualitatively similar to the shear modulus data by having a significant beta process. A single-order-parameter framework is suggested to rationalize these similarities.

Model for the alpha and beta shear-mechanical properties of supercooled liquids and its comparison to squalane data.

PubMed

Hecksher, Tina; Olsen, Niels Boye; Dyre, Jeppe C

2017-04-21

This paper presents data for supercooled squalane's frequency-dependent shear modulus covering frequencies from 10 mHz to 30 kHz and temperatures from 168 K to 190 K; measurements are also reported for the glass phase down to 146 K. The data reveal a strong mechanical beta process. A model is proposed for the shear response of the metastable equilibrium liquid phase of supercooled liquids. The model is an electrical equivalent-circuit characterized by additivity of the dynamic shear compliances of the alpha and beta processes. The nontrivial parts of the alpha and beta processes are each represented by a "Cole-Cole retardation element" defined as a series connection of a capacitor and a constant-phase element, resulting in the Cole-Cole compliance function well-known from dielectrics. The model, which assumes that the high-frequency decay of the alpha shear compliance loss varies with the angular frequency as ω -1/2 , has seven parameters. Assuming time-temperature superposition for the alpha and beta processes separately, the number of parameters varying with temperature is reduced to four. The model provides a better fit to the data than an equally parametrized Havriliak-Negami type model. From the temperature dependence of the best-fit model parameters, the following conclusions are drawn: (1) the alpha relaxation time conforms to the shoving model; (2) the beta relaxation loss-peak frequency is almost temperature independent; (3) the alpha compliance magnitude, which in the model equals the inverse of the instantaneous shear modulus, is only weakly temperature dependent; (4) the beta compliance magnitude decreases by a factor of three upon cooling in the temperature range studied. The final part of the paper briefly presents measurements of the dynamic adiabatic bulk modulus covering frequencies from 10 mHz to 10 kHz in the temperature range from 172 K to 200 K. The data are qualitatively similar to the shear modulus data by having a significant beta process. A single-order-parameter framework is suggested to rationalize these similarities.

Clarity versus complexity: land-use modeling as a practical tool for decision-makers

USGS Publications Warehouse

Sohl, Terry L.; Claggett, Peter

2013-01-01

The last decade has seen a remarkable increase in the number of modeling tools available to examine future land-use and land-cover (LULC) change. Integrated modeling frameworks, agent-based models, cellular automata approaches, and other modeling techniques have substantially improved the representation of complex LULC systems, with each method using a different strategy to address complexity. However, despite the development of new and better modeling tools, the use of these tools is limited for actual planning, decision-making, or policy-making purposes. LULC modelers have become very adept at creating tools for modeling LULC change, but complicated models and lack of transparency limit their utility for decision-makers. The complicated nature of many LULC models also makes it impractical or even impossible to perform a rigorous analysis of modeling uncertainty. This paper provides a review of land-cover modeling approaches and the issues causes by the complicated nature of models, and provides suggestions to facilitate the increased use of LULC models by decision-makers and other stakeholders. The utility of LULC models themselves can be improved by 1) providing model code and documentation, 2) through the use of scenario frameworks to frame overall uncertainties, 3) improving methods for generalizing key LULC processes most important to stakeholders, and 4) adopting more rigorous standards for validating models and quantifying uncertainty. Communication with decision-makers and other stakeholders can be improved by increasing stakeholder participation in all stages of the modeling process, increasing the transparency of model structure and uncertainties, and developing user-friendly decision-support systems to bridge the link between LULC science and policy. By considering these options, LULC science will be better positioned to support decision-makers and increase real-world application of LULC modeling results.

Environmental and climatic variables as potential drivers of post-fire cover of cheatgrass (Bromus tectorum) in seeded and unseeded semiarid ecosystems

USGS Publications Warehouse

Shinneman, D.J.; Baker, W.L.

2009-01-01

Cheatgrass, a non-native annual grass, dominates millions of hectares in semiarid ecosystems of the Intermountain West (USA). Post-fire invasions can reduce native species diversity and alter ecological processes. To curb cheatgrass invasion, land managers often seed recently burned areas with perennial competitor species. We sampled vegetation within burned (19 years post-fire) and nearby unburned (representing pre-fire) pionjuniper (Pinus edulisJuniperus osteosperma) woodland and sagebrush (Artemisia sp.) in western Colorado to analyze variables that might explain cheatgrass cover after fire. A multiple regression model suggests higher cheatgrass cover after fire with: (1) sagebrush v. pionjuniper; (2) higher pre-fire cover of annual forbs; (3) increased time since fire; (4) lower pre-fire cover of biological soil crust; and (5) lower precipitation the year before fire. Time since fire, which coincided with higher precipitation, accounts for most of the variability in cheatgrass cover. No significant difference was found in mean cheatgrass cover between seeded and unseeded plots over time. However, negative relationships with pre-fire biological soil crust cover and native species richness suggest livestock-degraded areas are more susceptible to post-fire invasion. Proactive strategies for combating cheatgrass should include finding effective native competitors and restoring livestock-degraded areas. ?? 2009 IAWF.

Using Landsat imagery to detect, monitor, and project net landscape change

USGS Publications Warehouse

Reker, Ryan R.; Sohl, Terry L.; Gallant, Alisa L.

2015-01-01

Detailed landscape information is a necessary component to bird habitat conservation planning. The U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center has been providing information on the Earth’s surface for over 40 years via the continuous series of Landsat satellites. In addition to operating, processing, and disseminating satellite images, EROS is the home to nationwide and global landscape mapping, monitoring, and projection products, including:National Land Cover Database (NLCD) – the definitive land cover dataset for the U.S., with updates occurring at five-year intervals;Global Land Cover Monitoring – producing 30m resolution global land cover;LANDFIRE – Landscape Fire and Resource Management Planning Tools–EROS is a partner in this joint program between U.S. Department of Agriculture and Department of Interior that produces consistent, comprehensive, geospatial data and databases that describe vegetation, wildland fuel, and fire regimes across the U.S.;Land Cover Trends – a landscape monitoring and assessment effort to understand the rates, trends, causes, and consequences of contemporary U.S. land use and land cover change; andLand Use and Land Cover (LULC) Modeling – a project extending contemporary databases of landscape change forward and backward in time through moderate-resolution land cover projections.

Consequences of land-cover misclassification in models of impervious surface

USGS Publications Warehouse

McMahon, G.

2007-01-01

Model estimates of impervious area as a function of landcover area may be biased and imprecise because of errors in the land-cover classification. This investigation of the effects of land-cover misclassification on impervious surface models that use National Land Cover Data (NLCD) evaluates the consequences of adjusting land-cover within a watershed to reflect uncertainty assessment information. Model validation results indicate that using error-matrix information to adjust land-cover values used in impervious surface models does not substantially improve impervious surface predictions. Validation results indicate that the resolution of the landcover data (Level I and Level II) is more important in predicting impervious surface accurately than whether the land-cover data have been adjusted using information in the error matrix. Level I NLCD, adjusted for land-cover misclassification, is preferable to the other land-cover options for use in models of impervious surface. This result is tied to the lower classification error rates for the Level I NLCD. ?? 2007 American Society for Photogrammetry and Remote Sensing.

76 FR 22648 - Resolution Plans and Credit Exposure Reports Required

Federal Register 2010, 2011, 2012, 2013, 2014

2011-04-22

..., including associated services, functions and support that, in the view of the Covered Company or as jointly...-based Covered Company's overall contingency planning process, and information regarding the.... operations be linked to the contingency planning process of the foreign-based Covered Company? Process 1. Are...

Scale and processes dominating soil erosion and sediment transport: case studies from Indonesia and Australia

NASA Astrophysics Data System (ADS)

van Dijk, A. I. J. M.; Bruijnzeel, L. A.

2009-04-01

Soil erosion and sediment transport at different scales of space and time are dominated by a variable set of landscape properties and processes. Research results from West Java (Indonesia) and southeast Australia are presented, taking a natural resources management perspective. The dominant role of vegetation and soil health, rainfall infiltration, and connectivity between hillslope and stream are elaborated on. In humid volcanic upland West Java, vegetative cover and associated infiltration capacity are the dominant control on surface runoff and sediment generation, with additional variation attributed to slope and soil surface structure. Use of process models to replicate and upscale field measurements highlighted that a predictive theory to link vegetative cover and infiltration capacity is lacking, and that full knowledge of the covariance between terrain attributes that promote sediment generation is needed for process based modelling. At the hillslope to catchment scale, slope gradient and a less erodible substrate became additional constraints on sediment yield. A conceptual framework relating processes, scale and sediment delivery ratio was developed. In water-limited southeast Australia, measures to reduce erosion and sediment production generally aim to intercept surface runoff, allowing runoff to infiltrate and sediment to settle on vegetated buffer strips or roadsides or in leaky dams. It is illustrated how remote sensing can help to assess the sources of sediment and hydrological connectivity at different scales and to identify opportunities for mitigation.

Solution processable and optically switchable 1D photonic structures.

PubMed

Paternò, Giuseppe M; Iseppon, Chiara; D'Altri, Alessia; Fasanotti, Carlo; Merati, Giulia; Randi, Mattia; Desii, Andrea; Pogna, Eva A A; Viola, Daniele; Cerullo, Giulio; Scotognella, Francesco; Kriegel, Ilka

2018-02-23

We report the first demonstration of a solution processable, optically switchable 1D photonic crystal which incorporates phototunable doped metal oxide nanocrystals. The resulting device structure shows a dual optical response with the photonic bandgap covering the visible spectral range and the plasmon resonance of the doped metal oxide the near infrared. By means of a facile photodoping process, we tuned the plasmonic response and switched effectively the optical properties of the photonic crystal, translating the effect from the near infrared to the visible. The ultrafast bandgap pumping induces a signal change in the region of the photonic stopband, with recovery times of several picoseconds, providing a step toward the ultrafast optical switching. Optical modeling uncovers the importance of a complete modeling of the variations of the dielectric function of the photodoped material, including the high frequency region of the Drude response which is responsible for the strong switching in the visible after photodoping. Our device configuration offers unprecedented tunability due to flexibility in device design, covering a wavelength range from the visible to the near infrared. Our findings indicate a new protocol to modify the optical response of photonic devices by optical triggers only.

The FORE-SCE model: a practical approach for projecting land cover change using scenario-based modeling

USGS Publications Warehouse

Sohl, Terry L.; Sayler, Kristi L.; Drummond, Mark A.; Loveland, Thomas R.

2007-01-01

A wide variety of ecological applications require spatially explicit, historic, current, and projected land use and land cover data. The U.S. Land Cover Trends project is analyzing contemporary (1973–2000) land-cover change in the conterminous United States. The newly developed FORE-SCE model used Land Cover Trends data and theoretical, statistical, and deterministic modeling techniques to project future land cover change through 2020 for multiple plausible scenarios. Projected proportions of future land use were initially developed, and then sited on the lands with the highest potential for supporting that land use and land cover using a statistically based stochastic allocation procedure. Three scenarios of 2020 land cover were mapped for the western Great Plains in the US. The model provided realistic, high-resolution, scenario-based land-cover products suitable for multiple applications, including studies of climate and weather variability, carbon dynamics, and regional hydrology.

[Optimization of application parameters of soil seed bank in vegetation recovery via response surface methodology].

PubMed

He, Meng-Xuan; Li, Hong-Yuan; Mo, Xun-Qiang; Meng, Wei-Qing; Yang, Jia-Nan

2014-08-01

The thickness of surface soil, the covering thickness and the number of adding arbor seeds are all important factors to be considered in the application of soil seed bank (SSB) for vegetation recovery. To determine the optimal conditions, the Box-Behnken central composite design with three parameters and three levels was conducted and Design-Expert was used for response surface optimization. Finally, the optimal model and optimal level of each parameter were selected. The quadratic model was more suitable for response surface optimization (P < 0.0001), indicating the model had good statistical significance which could express ideal relations between all the independent variable and dependent variable. For the optimum condition, the thickness of surface soil was 4.3 cm, the covering thickness was 2 cm, and the number of adding arbor seeds was 224 ind x m(-2), under which the number of germinated seedlings could be reached up to 6222 plants x m(-2). During the process of seed germination, significant interactions between the thickness of surface soil and the covering thickness, as well as the thickness of surface soil and the number of adding arbor seeds were found, but the relationship between the covering thickness and the number of adding arbor seeds was relatively unremarkable. Among all the parameters, the thickness of surface soil was the most important one, which had the steepest curve and the largest standardized coefficient.

Analysis of ecosystem controls on soil carbon source-sink relationships in the northwest Great Plains

USGS Publications Warehouse

Tan, Z.; Liu, S.; Johnston, C.A.; Liu, J.; Tieszen, L.L.

2006-01-01

Our ability to forecast the role of ecosystem processes in mitigating global greenhouse effects relies on understanding the driving forces on terrestrial C dynamics. This study evaluated the controls on soil organic C (SOC) changes from 1973 to 2000 in the northwest Great Plains. SOC source-sink relationships were quantified using the General Ensemble Biogeochemical Modeling System (GEMS) based on 40 randomly located 10 × 10 km2 sample blocks. These sample blocks were aggregated into cropland, grassland, and forestland groups based on land cover composition within each sample block. Canonical correlation analysis indicated that SOC source-sink relationship from 1973 to 2000 was significantly related to the land cover type while the change rates mainly depended on the baseline SOC level and annual precipitation. Of all selected driving factors, the baseline SOC and nitrogen levels controlled the SOC change rates for the forestland and cropland groups, while annual precipitation determined the C source-sink relationship for the grassland group in which noticeable SOC sink strength was attributed to the conversion from cropped area to grass cover. Canonical correlation analysis also showed that grassland ecosystems are more complicated than others in the ecoregion, which may be difficult to identify on a field scale. Current model simulations need further adjustments to the model input variables for the grass cover-dominated ecosystems in the ecoregion.

Assessing winter cover crop nutrient uptake efficiency using a water quality simulation model

USGS Publications Warehouse

Yeo, In-Young; Lee, Sangchui; Sadeghi, Ali M.; Beeson, Peter C.; Hively, W. Dean; McCarty, Greg W.; Lang, Megan W.

2013-01-01

Winter cover crops are an effective conservation management practice with potential to improve water quality. Throughout the Chesapeake Bay Watershed (CBW), which is located in the Mid-Atlantic US, winter cover crop use has been emphasized and federal and state cost-share programs are available to farmers to subsidize the cost of winter cover crop establishment. The objective of this study was to assess the long-term effect of planting winter cover crops at the watershed scale and to identify critical source areas of high nitrate export. A physically-based watershed simulation model, Soil and Water Assessment Tool (SWAT), was calibrated and validated using water quality monitoring data and satellite-based estimates of winter cover crop species performance to simulate hydrological processes and nutrient cycling over the period of 1991–2000. Multiple scenarios were developed to obtain baseline information on nitrate loading without winter cover crops planted and to investigate how nitrate loading could change with different winter cover crop planting scenarios, including different species, planting times, and implementation areas. The results indicate that winter cover crops had a negligible impact on water budget, but significantly reduced nitrate leaching to groundwater and delivery to the waterways. Without winter cover crops, annual nitrate loading was approximately 14 kg ha−1, but it decreased to 4.6–10.1 kg ha−1 with winter cover crops resulting in a reduction rate of 27–67% at the watershed scale. Rye was most effective, with a potential to reduce nitrate leaching by up to 93% with early planting at the field scale. Early planting of winter cover crops (~30 days of additional growing days) was crucial, as it lowered nitrate export by an additional ~2 kg ha−1 when compared to late planting scenarios. The effectiveness of cover cropping increased with increasing extent of winter cover crop implementation. Agricultural fields with well-drained soils and those that were more frequently used to grow corn had a higher potential for nitrate leaching and export to the waterways. This study supports the effective implement of winter cover crop programs, in part by helping to target critical pollution source areas for winter cover crop implementation.

Snow cover monitoring model and change over both time and space in pastoral area of northern China

NASA Astrophysics Data System (ADS)

Cui, Yan; Li, Suju; Wang, Ping; Zhang, Wei; Nie, Juan; Wen, Qi

2014-11-01

Snow disaster is a natural phenomenon owning to widespread snowfall for a long time and usually affect people's life, property and economic. During the whole disaster management circle, snow disaster in pastoral area of northern china which including Xinjiang, Inner Mongolia, Qinghai, Tibet has been paid more attention. Thus do a good job in snow cover monitoring then found snow disaster in time can help the people in disaster area to take effective rescue measures, which always been the central and local government great important work. Remote sensing has been used widely in snow cover monitoring for its wide range, high efficiency, less conditions, more methods and large information. NOAA/AVHRR data has been used for wide range, plenty bands information and timely acquired and act as an import data of Snow Cover Monitoring Model (SCMM). SCMM including functions list below: First after NOAA/AVHRR data has been acquired, geometric calibration, radiometric calibration and other pre-processing work has been operated. Second after band operation, four threshold conditions are used to extract snow spectrum information among water, cloud and other features in NOAA/AVHRR image. Third snow cover information has been analyzed one by one and the maximum snow cover from about twenty images in a week has been selected. Then selected image has been mosaic which covered the pastoral area of China. At last both time and space analysis has been carried out through this operational model ,such as analysis on the difference between this week and the same period of last year , this week and last week in three level regional. SCMM have been run successfully for three years, and the results have been take into account as one of the three factors which led to risk warning of snow disaster and analysis results from it always play an important role in disaster reduction and relief.

The Cycles of Snow Cover in Pyrenees Mountain and Mont Lebanon Analyzed Using the Global Modeling Technique.

NASA Astrophysics Data System (ADS)

Drapeau, L.; Mangiarotti, S.; Le Jean, F.; Gascoin, S.; Jarlan, L.

2014-12-01

The global modeling technique provides a way to obtain ordinary differential equations from single time series1. This technique, initiated in the 1990s, could be applied successfully to numerous theoretic and experimental systems. More recently it could be applied to environmental systems2,3. Here this technique is applied to seasonal snow cover area in the Pyrenees mountain (Europe) and Mont Lebanon (Mediterranean region). The snowpack evolution is complex because it results from combination of processes driven by physiography (elevation, slope, land cover...) and meteorological variables (precipitation, temperature, wind speed...), which are highly heterogeneous in such regions. Satellite observations in visible bands offer a powerful tool to monitor snow cover areas at global scale, with large resolutions range. Although this observable does not directly inform about snow water equivalent, its dynamical behavior strongly relies on it. Therefore, snow cover area is likely to be a good proxy of the global dynamics and global modeling technique a well adapted approach. The MOD10A2 product (500m) generated from MODIS by the NASA is used after a pretreatment is applied to minimize clouds effect. The global modeling technique is then applied using two packages4,5. The analysis is performed with two time series for the whole period (2000-2012) and year by year. Low-dimensional chaotic models are obtained in many cases. Such models provide a strong argument for chaos since involving the two necessary conditions in a synthetic way: determinism and strong sensitivity to initial conditions. The models comparison suggests important non-stationnarities at interannual scale which prevent from detecting long term changes. 1: Letellier et al 2009. Frequently asked questions about global modeling, Chaos, 19, 023103. 2: Maquet et al 2007. Global models from the Canadian lynx cycles as a direct evidence for chaos in real ecosystems. J. of Mathematical Biology, 55 (1), 21-39 3: Mangiarotti et al 2014. Two chaotic global models for cereal crops cycles observed from satellite in Northern Morocco. Chaos, 24, 023130. 4 : Mangiarotti et al 2012. Polynomial search and Global modelling: two algorithms for modeling chaos. Physical Review E, 86(4), 046205. 5: http://cran.r-project.org/web/packages/PoMoS/index.html.

PICUS v1.6 - enhancing the water cycle within a hybrid ecosystem model to assess the provision of drinking water in a changing climate

NASA Astrophysics Data System (ADS)

Schimmel, A.; Rammer, W.; Lexer, M. J.

2012-04-01

The PICUS model is a hybrid ecosystem model which is based on a 3D patch model and a physiological stand level production model. The model includes, among others, a submodel of bark beetle disturbances in Norway spruce and a management module allowing any silvicultural treatment to be mimicked realistically. It has been tested intensively for its ability to realistically reproduce tree growth and stand dynamics in complex structured mixed and mono-species temperate forest ecosystems. In several applications the models capacity to generate relevant forest related attributes which were subsequently fed into indicator systems to assess sustainable forest management under current and future climatic conditions has been proven. However, the relatively coarse monthly temporal resolution of the driving climate data as well as the process resolution of the major water relations within the simulated ecosystem hampered the inclusion of more detailed physiologically based assessments of drought conditions and water provisioning ecosystem services. In this contribution we present the improved model version PICUS v1.6 focusing on the newly implemented logic for the water cycle calculations. Transpiration, evaporation from leave surfaces and the forest floor, snow cover and snow melt as well as soil water dynamics in several soil horizons are covered. In enhancing the model overarching goal was to retain the large-scale applicability by keeping the input requirements to a minimum while improving the physiological foundation of water related ecosystem processes. The new model version is tested against empirical time series data. Future model applications are outlined.

Career Development Theory and Its Application. Career Knowledge Series

ERIC Educational Resources Information Center

National Career Development Association, 2015

2015-01-01

Covers career development theory, models, and techniques and how to apply them; understand the steps in the career development process and why career choice and development theory is important as well as limitations. Presents the assumptions that underlie four different types of theories; trait and factor, learning, developmental, and transition…

Classroom Success Stories: Exposing Students to Time Bonding.

ERIC Educational Resources Information Center

Papaleo, Ralph J.

1996-01-01

Recommends using time bonding (finding a role model and researching the process and story behind that individual's accomplishments) as a means to interest students in history. Outlines the instructions covering the objectives of the writing assignments. Students researched a variety of biographies including Jackie Robinson and Lyndon Johnson. (MJP)

Ray-traced tropospheric total slant delays for GNSS processing

NASA Astrophysics Data System (ADS)

Hobiger, T.; Ichikawa, R.; Hatanaka, Y.; Yutsudo, T.; Iwashita, C.; Miyahara, B.; Koyama, Y.; Kondo, T.

2007-12-01

Numerical weather models have undergone an improvement of spatial and temporal resolution in the recent years, which made their use for GNSS applications feasible. Ray-tracing through such models permits the computation of total troposphere delays and ray-bending angles. At the National Institute of Information and Communications Technology (NICT), Japan the so-called KAshima RAy-tracing Tools (KARAT) have been developed which allow to obtain troposphere delay corrections in real-time. Together with fine-mesh weather models from the Japanese Meteorological Agency (JMA) huge parts of the East Asian region, including Japan, Korea, Taiwan and East China, can be covered. The Japanese GEONET with its more than 1300 GNSS receivers represent an ideal test-bed for the evaluation of the performance of KARAT. In cooperation with the Geographical Survey Institute (GSI), Japan more than 1.6 billion observations, covering measurements from July 1st until August 31st, 2006, were processed and the corresponding troposphere delays were used to modify the original RINEX files by subtraction of code- and phase delays. These modified observations were processed by a dedicated analysis run of the GEONET operation center, taking advantage of the computer cluster at GSI. First results from this study, together with an in-depth discussion about the assets and drawbacks of the reduction of troposphere total slant delays will be given in this presentation. Additionally an overview about KARAT, the treatment of observational data and the impact of future refined numerical weather models on GNSS analysis will be included in this contribution.

Thermokinetic Modeling of Phase Transformation in the Laser Powder Deposition Process

NASA Astrophysics Data System (ADS)

Foroozmehr, Ehsan; Kovacevic, Radovan

2009-08-01

A finite element model coupled with a thermokinetic model is developed to predict the phase transformation of the laser deposition of AISI 4140 on a substrate with the same material. Four different deposition patterns, long-bead, short-bead, spiral-in, and spiral-out, are used to cover a similar area. Using a finite element model, the temperature history of the laser powder deposition (LPD) process is determined. The martensite transformation as well as martensite tempering is considered to calculate the final fraction of martensite, ferrite, cementite, ɛ-carbide, and retained austenite. Comparing the surface hardness topography of different patterns reveals that path planning is a critical parameter in laser surface modification. The predicted results are in a close agreement with the experimental results.

On-line identification of fermentation processes for ethanol production.

PubMed

Câmara, M M; Soares, R M; Feital, T; Naomi, P; Oki, S; Thevelein, J M; Amaral, M; Pinto, J C

2017-07-01

A strategy for monitoring fermentation processes, specifically, simultaneous saccharification and fermentation (SSF) of corn mash, was developed. The strategy covered the development and use of first principles, semimechanistic and unstructured process model based on major kinetic phenomena, along with mass and energy balances. The model was then used as a reference model within an identification procedure capable of running on-line. The on-line identification procedure consists on updating the reference model through the estimation of corrective parameters for certain reaction rates using the most recent process measurements. The strategy makes use of standard laboratory measurements for sugars quantification and in situ temperature and liquid level data. The model, along with the on-line identification procedure, has been tested against real industrial data and have been able to accurately predict the main variables of operational interest, i.e., state variables and its dynamics, and key process indicators. The results demonstrate that the strategy is capable of monitoring, in real time, this complex industrial biomass fermentation. This new tool provides a great support for decision-making and opens a new range of opportunities for industrial optimization.

An Interactive Design Space Supporting Development of Vehicle Architecture Concept Models

DTIC Science & Technology

2011-01-01

Denver, Colorado, USA IMECE2011-64510 AN INTERACTIVE DESIGN SPACE SUPPORTING DEVELOPMENT OF VEHICLE ARCHITECTURE CONCEPT MODELS Gary Osborne...early in the development cycle. Optimization taking place later in the cycle usually occurs at the detail design level, and tends to result in...architecture changes may be imposed, but such modifications are equivalent to a huge optimization cycle covering almost the entire design process, and

Modeling percent tree canopy cover: a pilot study

Treesearch

John W. Coulston; Gretchen G. Moisen; Barry T. Wilson; Mark V. Finco; Warren B. Cohen; C. Kenneth Brewer

2012-01-01

Tree canopy cover is a fundamental component of the landscape, and the amount of cover influences fire behavior, air pollution mitigation, and carbon storage. As such, efforts to empirically model percent tree canopy cover across the United States are a critical area of research. The 2001 national-scale canopy cover modeling and mapping effort was completed in 2006,...

Spatially-explicit modeling of multi-scale drivers of aboveground forest biomass and water yield in watersheds of the Southeastern United States.

PubMed

Ajaz Ahmed, Mukhtar Ahmed; Abd-Elrahman, Amr; Escobedo, Francisco J; Cropper, Wendell P; Martin, Timothy A; Timilsina, Nilesh

2017-09-01

Understanding ecosystem processes and the influence of regional scale drivers can provide useful information for managing forest ecosystems. Examining more local scale drivers of forest biomass and water yield can also provide insights for identifying and better understanding the effects of climate change and management on forests. We used diverse multi-scale datasets, functional models and Geographically Weighted Regression (GWR) to model ecosystem processes at the watershed scale and to interpret the influence of ecological drivers across the Southeastern United States (SE US). Aboveground forest biomass (AGB) was determined from available geospatial datasets and water yield was estimated using the Water Supply and Stress Index (WaSSI) model at the watershed level. Our geostatistical model examined the spatial variation in these relationships between ecosystem processes, climate, biophysical, and forest management variables at the watershed level across the SE US. Ecological and management drivers at the watershed level were analyzed locally to identify whether drivers contribute positively or negatively to aboveground forest biomass and water yield ecosystem processes and thus identifying potential synergies and tradeoffs across the SE US region. Although AGB and water yield drivers varied geographically across the study area, they were generally significantly influenced by climate (rainfall and temperature), land-cover factor1 (Water and barren), land-cover factor2 (wetland and forest), organic matter content high, rock depth, available water content, stand age, elevation, and LAI drivers. These drivers were positively or negatively associated with biomass or water yield which significantly contributes to ecosystem interactions or tradeoff/synergies. Our study introduced a spatially-explicit modelling framework to analyze the effect of ecosystem drivers on forest ecosystem structure, function and provision of services. This integrated model approach facilitates multi-scale analyses of drivers and interactions at the local to regional scale. Copyright © 2017 Elsevier Ltd. All rights reserved.

Temporal trend of the snow-related variables in Sierra Nevada in the last years: An analysis combining Earth Observation and hydrological modelling

NASA Astrophysics Data System (ADS)

Pérez-Luque, Antonio J.; Herrero, Javier; Bonet, Francisco J.; Pérez-Pérez, Ramón

2016-04-01

Climate change is causing declines in snow-cover extent and duration in European mountain ranges. This is especially important in Mediterranean mountain ranges where the observed trends towards precipitation and higher temperatures can provoke problems of water scarcity. In this work, we analyzed temporal trends (2000 to 2014) of snow-related variables obtained from satellite and modelling data in Sierra Nevada, a Mediterranean high-mountain range located in Southern Spain, at 37°N. Snow cover indicators (snow-cover duration, snow-cover onset dates and snow-cover melting dates) were obtained by processing images of MOD10A2 MODIS product using an automated workflow. Precipitation data were obtained using WiMMed, a complete and fully distributed hydrological model that is used to map the annual rainfall and snowfall with a resolution of 30x30 m over the whole study area. It uses expert algorithms to interpolate precipitation and temperature at an hourly scale, and simulates partition of precipitation into snowfall with several methods. For each snow-related indicator (snow-covers and snowfall), a trend analysis was applied at the MODIS pixel scale during the study period (2000-2014). We applied Mann-Kendall test and Theil-Sen slope estimation in each of the pixels comprising Sierra Nevada. The trend analysis assesses the intensity, magnitude and degree of statistical significance during the period analysed. The spatial pattern of these trends was explored according to elevation ranges. Finally, we explored the relationship between trends of snow-cover related indicators and precipitation trends. Our results show that snow-cover has undergone significant changes in the last 14 years. 80 % of the pixels covering Sierra Nevada showed a negative trend in the duration of snow-cover. We also observed a delay in the snow-cover onset date (68.03 % pixels showing a positive trend in the snow-cover onset date) and an advance in the melt date (80.72 % of pixels followed a negative trend for the snow-cover melting date). Precipitation does not show a significant trend for these years, even though its inter-annual variability has been outstanding. The maximum mean annual precipitation of 906 mm/year doubles the mean precipitation, which somehow compensates for the occurrence of a sequence of dry years with a minimum of 250 mm/year. The assessment of the spatial pattern of snow cover duration shows that both the trend and the slope of the trend becomes more pronounced with elevation. At higher elevations the snow-cover duration decreased an average of 3 days from 2000-2014. This research has been funded by ECOPOTENTIAL (Improving future ecosystem benefits through Earth Observations) Horizon 2020 EU project, and Sierra Nevada Global Change Observatory (LTER-site)

Modeling of Passive Forces of Machine Tool Covers

NASA Astrophysics Data System (ADS)

Kolar, Petr; Hudec, Jan; Sulitka, Matej

The passive forces acting against the drive force are phenomena that influence dynamical properties and precision of linear axes equipped with feed drives. Covers are one of important sources of passive forces in machine tools. The paper describes virtual evaluation of cover passive forces using the cover complex model. The model is able to compute interaction between flexible cover segments and sealing wiper. The result is deformation of cover segments and wipers which is used together with measured friction coefficient for computation of cover total passive force. This resulting passive force is dependent on cover position. Comparison of computational results and measurement on the real cover is presented in the paper.

Boosted Regression Tree Models to Explain Watershed ...

EPA Pesticide Factsheets

Boosted regression tree (BRT) models were developed to quantify the nonlinear relationships between landscape variables and nutrient concentrations in a mesoscale mixed land cover watershed during base-flow conditions. Factors that affect instream biological components, based on the Index of Biotic Integrity (IBI), were also analyzed. Seasonal BRT models at two spatial scales (watershed and riparian buffered area [RBA]) for nitrite-nitrate (NO2-NO3), total Kjeldahl nitrogen, and total phosphorus (TP) and annual models for the IBI score were developed. Two primary factors — location within the watershed (i.e., geographic position, stream order, and distance to a downstream confluence) and percentage of urban land cover (both scales) — emerged as important predictor variables. Latitude and longitude interacted with other factors to explain the variability in summer NO2-NO3 concentrations and IBI scores. BRT results also suggested that location might be associated with indicators of sources (e.g., land cover), runoff potential (e.g., soil and topographic factors), and processes not easily represented by spatial data indicators. Runoff indicators (e.g., Hydrological Soil Group D and Topographic Wetness Indices) explained a substantial portion of the variability in nutrient concentrations as did point sources for TP in the summer months. The results from our BRT approach can help prioritize areas for nutrient management in mixed-use and heavily impacted watershed

Defense Waste Processing Facility Nitric- Glycolic Flowsheet Chemical Process Cell Chemistry: Part 2

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zamecnik, J.; Edwards, T.

The conversions of nitrite to nitrate, the destruction of glycolate, and the conversion of glycolate to formate and oxalate were modeled for the Nitric-Glycolic flowsheet using data from Chemical Process Cell (CPC) simulant runs conducted by Savannah River National Laboratory (SRNL) from 2011 to 2016. The goal of this work was to develop empirical correlation models to predict these values from measureable variables from the chemical process so that these quantities could be predicted a-priori from the sludge or simulant composition and measurable processing variables. The need for these predictions arises from the need to predict the REDuction/OXidation (REDOX) statemore » of the glass from the Defense Waste Processing Facility (DWPF) melter. This report summarizes the work on these correlations based on the aforementioned data. Previous work on these correlations was documented in a technical report covering data from 2011-2015. This current report supersedes this previous report. Further refinement of the models as additional data are collected is recommended.« less

Recent Advances in Transferable Coarse-Grained Modeling of Proteins

PubMed Central

Kar, Parimal; Feig, Michael

2017-01-01

Computer simulations are indispensable tools for studying the structure and dynamics of biological macromolecules. Biochemical processes occur on different scales of length and time. Atomistic simulations cannot cover the relevant spatiotemporal scales at which the cellular processes occur. To address this challenge, coarse-grained (CG) modeling of the biological systems are employed. Over the last few years, many CG models for proteins continue to be developed. However, many of them are not transferable with respect to different systems and different environments. In this review, we discuss those CG protein models that are transferable and that retain chemical specificity. We restrict ourselves to CG models of soluble proteins only. We also briefly review recent progress made in the multi-scale hybrid all-atom/coarse-grained simulations of proteins. PMID:25443957

Determining Distributed Ablation over Dirty Ice Areas of Debris-covered Glaciers Using a UAV-SfM Approach

NASA Astrophysics Data System (ADS)

Woodget, A.; Fyffe, C. L.; Kirkbride, M. P.; Deline, P.; Westoby, M.; Brock, B. W.

2017-12-01

Dirty ice areas (where debris cover is discontinuous) are often found on debris-covered glaciers above the limit of continuous debris and are important because they are areas of high melt and have been recognized as the locus of the identified upglacier increase in debris cover. The modelling of glacial ablation in areas of dirty ice is in its infancy and is currently restricted to theoretical studies. Glacial ablation is traditionally determined at point locations using stakes drilled into the ice. However, in areas of dirty ice, ablation is highly spatially variable, since debris a few centimetres thick is near the threshold between enhancing and reducing ablation. As a result, it is very difficult to ascertain if point ablation measurements are representative of ablation of the area surrounding the stake - making these measurements unsuitable for the validation of models of dirty ice ablation. This paper aims to quantify distributed ablation and its relationship to essential dirty ice characteristics with a view to informing the construction of dirty ice melt models. A novel approach to determine distributed ablation is presented which uses repeat aerial imagery acquired from a UAV (Unmanned Aerial Vehicle), processed using SfM (Structure from Motion) techniques, on an area of dirty ice on Miage Glacier, Italian Alps. A spatially continuous ablation map is presented, along with a correlation to the local debris characteristics. Furthermore, methods are developed which link ground truth data on the percentage debris cover, albedo and clast depth to the UAV imagery, allowing these characteristics to be determined for the entire study area, and used as model inputs. For example, debris thickness is determined through a field relationship with clast size, which is then correlated with image texture and point cloud roughness metrics derived from the UAV imagery. Finally, we evaluate the potential of our novel approach to lead to improved modelling of dirty ice ablation.

Distributed Hydrologic Modeling of Semiarid Basins in Arizona: A Platform for Land Cover and Climate Change Assessments

NASA Astrophysics Data System (ADS)

Hawkins, G. A.; Vivoni, E. R.

2011-12-01

Watershed management is challenged by rising concerns over climate change and its potential to interact with land cover alterations to impact regional water supplies and hydrologic processes. The inability to conduct experimental manipulations that address climate and land cover change at watershed scales limits the capacity of water managers to make decisions to protect future supplies. As a result, spatially-explicit, physically-based models possess value for predicting the possible consequences on watershed hydrology. In this study, we apply a distributed watershed model, the Triangulated Irregular Network (TIN)-based Real-time Integrated Basin Simulator (tRIBS), to the Beaver Creek basin in Arizona. This sub-basin of the Verde River is representative of the regional topography, land cover, soils distribution and availability of hydrologic data in forested regions of northern Arizona. As such, it can serve as a demonstration study in the broader region to illustrate the utility of distributed models for change assessment studies. Through a model application to summertime conditions, we compare the hydrologic response from three sources of meteorological input: (1) an available network of ground-based stations, (2) weather radar rainfall estimates, and (3) the North American Land Data Assimilation System (NLDAS). Comparisons focus on analysis of spatiotemporal distributions of precipitation, soil moisture, runoff generation, evapotranspiration and recharge from the root zone at high resolution for an assessment of sustainable water supplies for agricultural and domestic purposes. We also present a preliminary analysis of the impact of vegetation change arising from historical treatments in the Beaver Creek to inform the hydrologic consequences in the form of soil moisture and evapotranspiration patterns with differing degrees of proposed forest thinning. Our results are discussed in the context of improved hydrologic predictions for sustainability and decision-making under the uncertainties induced by combined climate and land cover change.

Using Gridded Snow Covered Area and Snow-Water Equivalence Spatial Data Sets to Improve Snow-Pack Depletion Simulation in a Continental Scale Hydrologic Model

NASA Astrophysics Data System (ADS)

Risley, J. C.; Tracey, J. A.; Markstrom, S. L.; Hay, L.

2014-12-01

Snow cover areal depletion curves were used in a continuous daily hydrologic model to simulate seasonal spring snowmelt during the period between maximum snowpack accumulation and total melt. The curves are defined as the ratio of snow-water equivalence (SWE) divided by the seasonal maximum snow-water equivalence (Ai) (Y axis) versus the percent snow cover area (SCA) (X axis). The slope of the curve can vary depending on local watershed conditions. Windy sparsely vegetated high elevation watersheds, for example, can have a steeper slope than lower elevation forested watersheds. To improve the accuracy of simulated runoff at ungaged watersheds, individual snow cover areal depletion curves were created for over 100,000 hydrologic response units (HRU) in the continental scale U.S. Geological Survey (USGS) National Hydrologic Model (NHM). NHM includes the same components of the USGS Precipitation-Runoff-Modeling System (PRMS), except it uses consistent land surface characterization and model parameterization across the U.S. continent. Weighted-mean daily time series of 1-kilometer gridded SWE, from Snow Data Assimilation System (SNODAS), and 500-meter gridded SCA, from Moderate Resolution Imaging Spectroradiometer (MODIS), for 2003-2014 were computed for each HRU using the USGS Geo Data Portal. Using a screening process, pairs of SWE/Ai and SCA from the snowmelt period of each year were selected. SCA values derived from imagery that did not have any cloud cover and were >0 and <100 percent were selected. Unrealistically low and high SCA values that were paired with high and low SWE/Ai ratios, respectively, were removed. Second order polynomial equations were then fit to the remaining pairs of SWE/Ai and SCA to create a unique curve for each HRU. Simulations comparing these new curves with an existing single default curve in NHM will be made to determine if there are significant improvements in runoff.

Multi-Temporal Land Cover Classification with Long Short-Term Memory Neural Networks

NASA Astrophysics Data System (ADS)

Rußwurm, M.; Körner, M.

2017-05-01

Land cover classification (LCC) is a central and wide field of research in earth observation and has already put forth a variety of classification techniques. Many approaches are based on classification techniques considering observation at certain points in time. However, some land cover classes, such as crops, change their spectral characteristics due to environmental influences and can thus not be monitored effectively with classical mono-temporal approaches. Nevertheless, these temporal observations should be utilized to benefit the classification process. After extensive research has been conducted on modeling temporal dynamics by spectro-temporal profiles using vegetation indices, we propose a deep learning approach to utilize these temporal characteristics for classification tasks. In this work, we show how long short-term memory (LSTM) neural networks can be employed for crop identification purposes with SENTINEL 2A observations from large study areas and label information provided by local authorities. We compare these temporal neural network models, i.e., LSTM and recurrent neural network (RNN), with a classical non-temporal convolutional neural network (CNN) model and an additional support vector machine (SVM) baseline. With our rather straightforward LSTM variant, we exceeded state-of-the-art classification performance, thus opening promising potential for further research.

The Mica Creek Experimental Watershed: An Outdoor Laboratory for the Investigation of Hydrologic Processes in a Continental/Maritime Mountainous Environment

NASA Astrophysics Data System (ADS)

Link, T. E.; Gravelle, J.; Hubbart, J.; Warnsing, A.; Du, E.; Boll, J.; Brooks, E.; Cundy, T.

2004-12-01

Experimental catchments have proven to be extremely useful for investigations focused on fundamental hydrologic processes and on the impacts of land cover change on hydrologic regimes and water quality. Recent studies have illustrated how watershed responses to experimental treatments vary greatly between watersheds with differing physical, ecological and hydroclimatic characteristics. Meteorological and hydrological data within catchments are needed to help identify how hydrologic mechanisms may be altered by land cover alterations, and to both constrain and develop spatially-distributed physically based models. Existing instrumentation at the Mica Creek Experimental Watershed (MCEW) in northern Idaho is a fourth-order catchment that is undergoing expansion to produce a comprehensive dataset for model development and testing. The experimental catchments encompass a 28 km2 area spanning elevations from 975 to 1725 m msl. Snow processes dominate the hydrology of the catchment and climate conditions in the winter alternate between cold, dry continental and warm, moist maritime weather systems. Landcover is dominated by 80 year old second growth conifer forests, with partially cut (thinned) and clear-cut sub-catchments. Climate and precipitation data are collected at a SNOTEL site, three primary, and seven supplemental meteorological stations stratified by elevation and canopy cover. Manual snow depth measurements are recorded every 1-2 weeks during snowmelt, stratified by aspect, elevation and canopy cover. An air temperature transect spans three second-order sub-catchments to track air temperature lapse rate dynamics. Precipitation gauge arrays are installed within thinned and closed-canopy stands to track throughfall and interception loss. Nine paired and nested sub-catchments are monitored for flow, temperature, sediment, and nutrients. Hydroclimatic data are augmented by LiDAR and hyperspectral imagery for determination of canopy and topographic structure. Results will serve as a key dataset to assess how canopy conditions affect surface hydrology in complex snow-dominated catchments in the intermountain western U.S.

Integrating landscape ecology and geoinformatics to decipher landscape dynamics for regional planning.

PubMed

Dikou, Angela; Papapanagiotou, Evangelos; Troumbis, Andreas

2011-09-01

We used remote sensing and GIS in conjunction with multivariate statistical methods to: (i) quantify landscape composition (land cover types) and configuration (patch density, diversity, fractal dimension, contagion) for five coastal watersheds of Kalloni gulf, Lesvos Island, Greece, in 1945, 1960, 1971, 1990 and 2002/2003, (ii) evaluate the relative importance of physical (slope, geologic substrate, stream order) and human (road network, population density) variables on landscape composition and configuration, and (iii) characterize processes that led to land cover changes through land cover transitions between these five successive periods in time. Distributions of land cover types did not differ among the five time periods at the five watersheds studied because the largest cumulative changes between 1945 and 2002/2003 did not take place at dominant land cover types. Landscape composition related primarily to the physical attributes of the landscape. Nevertheless, increase in population density and the road network were found to increase heterogeneity of the landscape mosaic (patchiness), complexity of patch shape (fractal dimension), and patch disaggregation (contagion). Increase in road network was also found to increase landscape diversity due to the creation of new patches. The main processes involved in land cover changes were plough-land abandonment and ecological succession. Landscape dynamics during the last 50 years corroborate the ecotouristic-agrotouristic model for regional development to reverse trends in agricultural land abandonment and human population decline and when combined with hypothetical regulatory approaches could predict how this landscape could develop in the future, thus, providing a valuable tool to regional planning.

Integrated Spatial Models of Non Native Plant Invasion, Fire Risk, and Wildlife Habitat to Support Conservation of Military and Adjacent Lands in the Arid Southwest

DTIC Science & Technology

2015-12-01

FINAL REPORT Integrated spatial models of non-native plant invasion, fire risk, and wildlife habitat to support conservation of military and...as reflecting the official policy or position of the Department of Defense. Reference herein to any specific commercial product, process, or service...2. REPORT TYPE Final 3. DATES COVERED (From - To) 26/4/2010 – 25/10/2015 4. TITLE AND SUBTITLE Integrated Spatial Models of Non-Native Plant

Potential solar radiation and land cover contributions to digital climate surface modeling

NASA Astrophysics Data System (ADS)

Puig, Pol; Batalla, Meritxell; Pesquer, Lluís; Ninyerola, Miquel

2016-04-01

Overview: We have designed a series of ad-hoc experiments to study the role of factors that a priori have a strong weight in developing digital models of temperature and precipitation, such as solar radiation and land cover. Empirical test beds have been designed to improve climate (mean air temperature and total precipitation) digital models using statistical general techniques (multiple regression) with residual correction (interpolated with inverse weighting distance). Aim: Understand what roles these two factors (solar radiation and land cover) play to incorporate them into the process of generating mapping of temperature and rainfall. Study area: The Iberian Peninsula and supported in this, Catalonia and the Catalan Pyrenees. Data: The dependent variables used in all experiments relate to data from meteorological stations precipitation (PL), mean temperature (MT), average temperature minimum (MN) and maximum average temperature (MX). These data were obtained monthly from the AEMET (Agencia Estatal de Meteorología). Data series of stations covers the period between 1950 to 2010. Methodology: The idea is to design ad hoc, based on a sample of more equitable space statistician, to detect the role of radiation. Based on the influence of solar radiation on the temperature of the air from a quantitative point of view, the difficulty in answering this lies in the fact that there are lots of weather stations located in areas where solar radiation is similar. This suggests that the role of the radiation variable remains "off" when, instead, we intuitively think that would strongly influence the temperature. We have developed a multiple regression analysis between these meteorological variables as the dependent ones (Temperature and rainfall), and some geographical variables: altitude (ALT), latitude (LAT), continentality (CON) and solar radiation (RAD) as the independent ones. In case of the experiment with land covers, we have used the NDVI index as a proxy of land covers and added this variable in to the independents to improve the models. Results: The role of solar radiation does not improve models only under certain conditions and areas, especially in the Pyrennes. The vegetation index NDVI and therefore the land cover on which the station is located, helps improve rainfall and temperature patterns, obtaining various degrees of improvement in terms of molded variables and months.

How sensitive are estimates of carbon fixation in agricultural models to input data?

PubMed Central

2012-01-01

Background Process based vegetation models are central to understand the hydrological and carbon cycle. To achieve useful results at regional to global scales, such models require various input data from a wide range of earth observations. Since the geographical extent of these datasets varies from local to global scale, data quality and validity is of major interest when they are chosen for use. It is important to assess the effect of different input datasets in terms of quality to model outputs. In this article, we reflect on both: the uncertainty in input data and the reliability of model results. For our case study analysis we selected the Marchfeld region in Austria. We used independent meteorological datasets from the Central Institute for Meteorology and Geodynamics and the European Centre for Medium-Range Weather Forecasts (ECMWF). Land cover / land use information was taken from the GLC2000 and the CORINE 2000 products. Results For our case study analysis we selected two different process based models: the Environmental Policy Integrated Climate (EPIC) and the Biosphere Energy Transfer Hydrology (BETHY/DLR) model. Both process models show a congruent pattern to changes in input data. The annual variability of NPP reaches 36% for BETHY/DLR and 39% for EPIC when changing major input datasets. However, EPIC is less sensitive to meteorological input data than BETHY/DLR. The ECMWF maximum temperatures show a systematic pattern. Temperatures above 20°C are overestimated, whereas temperatures below 20°C are underestimated, resulting in an overall underestimation of NPP in both models. Besides, BETHY/DLR is sensitive to the choice and accuracy of the land cover product. Discussion This study shows that the impact of input data uncertainty on modelling results need to be assessed: whenever the models are applied under new conditions, local data should be used for both input and result comparison. PMID:22296931

Nitrogen deposition, land cover conversion, climate, and contemporary carbon balance of Europe (Invited)

NASA Astrophysics Data System (ADS)

Churkina, G.; Zahle, S.; Hughes, J.; Viovy, N.; Chen, Y.; Jung, M.; Ramankutty, N.; Roedenbeck, C.; Heimann, M.; Jones, C.

2009-12-01

In Europe, atmospheric nitrogen deposition has more than doubled, air temperature was rising, forest cover was steadily increasing, while agricultural area was declining over the last 50 years. What effect have these changes had on the European carbon balance? In this study we estimate responses of the European land ecosystems to nitrogen deposition, rising CO2, land cover conversion and climate change. We use results from three ecosystem process models such as BIOME-BGC, JULES, and ORCHIDEE (-CN) to address this question. We discuss to which degree carbon balance of Europe has been altered by nitrogen deposition in comparison to other drivers and identify areas which carbon balance has been affected by anthropogenic changes the most. We also analyze ecosystems carbon pools which were affected by the abovementioned environmental changes.

20 CFR 1010.300 - What processes are to be implemented to identify covered persons?

Code of Federal Regulations, 2010 CFR

2010-04-01

... 20 Employees' Benefits 3 2010-04-01 2010-04-01 false What processes are to be implemented to identify covered persons? 1010.300 Section 1010.300 Employees' Benefits OFFICE OF THE ASSISTANT SECRETARY... processes to identify covered persons who physically access service delivery points or who access virtual...

Machine learning based cloud mask algorithm driven by radiative transfer modeling

NASA Astrophysics Data System (ADS)

Chen, N.; Li, W.; Tanikawa, T.; Hori, M.; Shimada, R.; Stamnes, K. H.

2017-12-01

Cloud detection is a critically important first step required to derive many satellite data products. Traditional threshold based cloud mask algorithms require a complicated design process and fine tuning for each sensor, and have difficulty over snow/ice covered areas. With the advance of computational power and machine learning techniques, we have developed a new algorithm based on a neural network classifier driven by extensive radiative transfer modeling. Statistical validation results obtained by using collocated CALIOP and MODIS data show that its performance is consistent over different ecosystems and significantly better than the MODIS Cloud Mask (MOD35 C6) during the winter seasons over mid-latitude snow covered areas. Simulations using a reduced number of satellite channels also show satisfactory results, indicating its flexibility to be configured for different sensors.

On the nature of the sea ice albedo feedback in simple models.

PubMed

Moon, W; Wettlaufer, J S

2014-08-01

We examine the nature of the ice-albedo feedback in a long-standing approach used in the dynamic-thermodynamic modeling of sea ice. The central issue examined is how the evolution of the ice area is treated when modeling a partial ice cover using a two-category-thickness scheme; thin sea ice and open water in one category and "thick" sea ice in the second. The problem with the scheme is that the area evolution is handled in a manner that violates the basic rules of calculus, which leads to a neglected area evolution term that is equivalent to neglecting a leading-order latent heat flux. We demonstrate the consequences by constructing energy balance models with a fractional ice cover and studying them under the influence of increased radiative forcing. It is shown that the neglected flux is particularly important in a decaying ice cover approaching the transitions to seasonal or ice-free conditions. Clearly, a mishandling of the evolution of the ice area has leading-order effects on the ice-albedo feedback. Accordingly, it may be of considerable importance to reexamine the relevant climate model schemes and to begin the process of converting them to fully resolve the sea ice thickness distribution in a manner such as remapping, which does not in principle suffer from the pathology we describe.

On the nature of the sea ice albedo feedback in simple models

PubMed Central

Moon, W; Wettlaufer, J S

2014-01-01

We examine the nature of the ice-albedo feedback in a long-standing approach used in the dynamic-thermodynamic modeling of sea ice. The central issue examined is how the evolution of the ice area is treated when modeling a partial ice cover using a two-category-thickness scheme; thin sea ice and open water in one category and “thick” sea ice in the second. The problem with the scheme is that the area evolution is handled in a manner that violates the basic rules of calculus, which leads to a neglected area evolution term that is equivalent to neglecting a leading-order latent heat flux. We demonstrate the consequences by constructing energy balance models with a fractional ice cover and studying them under the influence of increased radiative forcing. It is shown that the neglected flux is particularly important in a decaying ice cover approaching the transitions to seasonal or ice-free conditions. Clearly, a mishandling of the evolution of the ice area has leading-order effects on the ice-albedo feedback. Accordingly, it may be of considerable importance to reexamine the relevant climate model schemes and to begin the process of converting them to fully resolve the sea ice thickness distribution in a manner such as remapping, which does not in principle suffer from the pathology we describe. PMID:26213674

Modelling The Energy And Mass Balance Of A Black Glacier

NASA Astrophysics Data System (ADS)

Grossi, G.; Taschner, S.; Ranzi, R.

A distributed energy balance hydrologic model has been implemented to simulate the melting season of the Belvedere glacier, situated in the Anza river basin (North- Western Italy) for a few years. The Belvedere Glacier is an example of SblackS glacier, ´ since the ablation zone is covered by a significant debris layer. The glacierSs termi- nus has an altitude of 1785 m asl which is very unusual for the Southern side of the European Alps. The model accounts for the energy exchange processes at the inter- face between the atmospheric boundary layer and the snow/ice/debris layer. To run the model hydrometeorological and physiographic data were collected, including the depth of the debris cover and the tritium (3H) concentration in the glacial river. Mea- surements of the soil thermal conductivity were carried out during a field campaign organised within the glaciers monitoring GLIMS project, at the time of the passage of the Landsat and the Terra satellites last 15 August 2001. A comparison of the different energy terms simulated by the model assigns a dominant role to the shortwave radia- tion, which provides the highest positive contribution to the energy available for snow- and ice-melt, while the sensible heat turns out to be the second major source of heat. Longwave radiation balance and latent heat seem to be less relevant and often nega- tive. The role of the debris cover is not negligible, since its thermal insulation causes, on average, a decrease in the ice melt volume. One of the model variables is the tem- perature of the debris cover, which can be a useful information when a black glacier is to be monitored through remote sensing techniques. The visible and near infrared radi- ation data do not always provide sufficient information to detect the glaciers' margins beneath the debris layer. For this reason the information of the different thermal sur- face characteristics (pure ice, debris covered ice, rock), proved by the energy balance model results was applied for the glacierSs classification with a Landsat-TM image. Taking into account also the thermal infrared band leads to an improved classification result.

Soil Moisture and Snow Cover: Active or Passive Elements of Climate?

NASA Technical Reports Server (NTRS)

Oglesby, Robert J.; Marshall, Susan; Robertson, Franklin R.; Roads, John O.; Arnold, James E. (Technical Monitor)

2001-01-01

A key question in the study of the hydrologic cycle is the extent to which surface effects such as soil moisture and snow cover are simply passive elements or whether they can affect the evolution of climate on seasonal and longer time scales. We have constructed ensembles of predictability studies using the NCAR CCM3 in which we compared the relative roles of initial surface and atmospheric conditions over the central and western U.S. GAPP region in determining the subsequent evolution of soil moisture and of snow cover. We have also made sensitivity studies with exaggerated soil moisture and snow cover anomalies in order to determine the physical processes that may be important. Results from simulations with realistic soil moisture anomalies indicate that internal climate variability may be the strongest factor, with some indication that the initial atmospheric state is also important. The initial state of soil moisture does not appear important, a result that held whether simulations were started in late winter or late spring. Model runs with exaggerated soil moisture reductions (near-desert conditions) showed a much larger effect, with warmer surface temperatures, reduced precipitation, and lower surface pressures; the latter indicating a response of the atmospheric circulation. These results suggest the possibility of a threshold effect in soil moisture, whereby an anomaly must be of a sufficient size before it can have a significant impact on the atmospheric circulation and hence climate. Results from simulations with realistic snow cover anomalies indicate that the time of year can be crucial. When introduced in late winter, these anomalies strongly affected the subsequent evolution of snow cover. When introduced in early winter, however, little or no effect is seen on the subsequent snow cover. Runs with greatly exaggerated initial snow cover indicate that the high reflectivity of snow is the most important process by which snow cover can impact climate, through lower surface temperatures and increased surface pressures. In early winter, the amount of solar radiation is very small and so this albedo, effect is inconsequential while in late winter, with the sun higher in the sky and period of daylight longer, the effect is much stronger. The results to date were obtained for model runs with present-day conditions. We are currently analyzing runs made with projected forcings for the 21st century to see if these results are modified in any way under likely scenarios of future climate change.

Multi-temporal high resolution monitoring of debris-covered glaciers using unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Kraaijenbrink, Philip; Immerzeel, Walter; de Jong, Steven; Shea, Joseph; Pellicciotti, Francesca; Meijer, Sander; Shresta, Arun

2016-04-01

Debris-covered glaciers in the Himalayas are relatively unstudied due to the difficulties in fieldwork caused by the inaccessible terrain and the presence of debris layers, which complicate in situ measurements. To overcome these difficulties an unmanned aerial vehicle (UAV) has been deployed multiple times over two debris covered glaciers in the Langtang catchment, located in the Nepalese Himalayas. Using differential GPS measurements and the Structure for Motion algorithm the UAV imagery was processed into accurate high-resolution digital elevation models and orthomosaics for both pre- and post-monsoon periods. These data were successfully used to estimate seasonal surface flow and mass wasting by using cross-correlation feature tracking and DEM differencing techniques. The results reveal large heterogeneity in mass loss and surface flow over the glacier surfaces, which are primarily caused by the presence of surface features such as ice cliffs and supra-glacial lakes. Accordingly, we systematically analyze those features using an object-based approach and relate their characteristics to the observed dynamics. We show that ice cliffs and supra-glacial lakes are contributing to a significant portion of the melt water of debris covered glaciers and we conclude that UAVs have great potential in understanding the key surface processes that remain largely undetected by using satellite remote sensing.

Assessing Landscape Change and Processes of Recurrence, Replacement, and Recovery in the Southeastern Coastal Plains, USA

NASA Astrophysics Data System (ADS)

Drummond, Mark A.; Stier, Michael P.; Auch, Roger F.; Taylor, Janis L.; Griffith, Glenn E.; Riegle, Jodi L.; Hester, David J.; Soulard, Christopher E.; McBeth, Jamie L.

2015-11-01

The processes of landscape change are complex, exhibiting spatial variability as well as linear, cyclical, and reversible characteristics. To better understand the various processes that cause transformation, a data aggregation, validation, and attribution approach was developed and applied to an analysis of the Southeastern Coastal Plains (SECP). The approach integrates information from available national land-use, natural disturbance, and land-cover data to efficiently assess spatially-specific changes and causes. Between 2001 and 2006, the processes of change affected 7.8 % of the SECP but varied across small-scale ecoregions. Processes were placed into a simple conceptual framework to explicitly identify the type and direction of change based on three general characteristics: replacement, recurrence, and recovery. Replacement processes, whereby a land use or cover is supplanted by a new land use, including urbanization and agricultural expansion, accounted for approximately 15 % of the extent of change. Recurrent processes that contribute to cyclical changes in land cover, including forest harvest/replanting and fire, accounted for 83 %. Most forest cover changes were recurrent, while the extents of recurrent silviculture and forest replacement processes such as urbanization far exceeded forest recovery processes. The total extent of landscape recovery, from prior land use to natural or semi-natural vegetation cover, accounted for less than 3 % of change. In a region of complex change, increases in transitory grassland and shrubland covers were caused by large-scale intensive plantation silviculture and small-scale activities including mining reclamation. Explicit identification of the process types and dynamics presented here may improve the understanding of land-cover change and landscape trajectory.

Assessing landscape change and processes of recurrence, replacement, and recovery in the Southeastern Coastal Plains, USA

USGS Publications Warehouse

Drummond, Mark A.; Stier, Michael P.; Auch, Roger F.; Taylor, Janis L.; Griffith, Glenn E.; Hester, David J.; Riegle, Jodi L.; Soulard, Christopher E.; McBeth, Jamie L.

2015-01-01

The processes of landscape change are complex, exhibiting spatial variability as well as linear, cyclical, and reversible characteristics. To better understand the various processes that cause transformation, a data aggregation, validation, and attribution approach was developed and applied to an analysis of the Southeastern Coastal Plains (SECP). The approach integrates information from available national land-use, natural disturbance, and land-cover data to efficiently assess spatially-specific changes and causes. Between 2001 and 2006, the processes of change affected 7.8 % of the SECP but varied across small-scale ecoregions. Processes were placed into a simple conceptual framework to explicitly identify the type and direction of change based on three general characteristics: replacement, recurrence, and recovery. Replacement processes, whereby a land use or cover is supplanted by a new land use, including urbanization and agricultural expansion, accounted for approximately 15 % of the extent of change. Recurrent processes that contribute to cyclical changes in land cover, including forest harvest/replanting and fire, accounted for 83 %. Most forest cover changes were recurrent, while the extents of recurrent silviculture and forest replacement processes such as urbanization far exceeded forest recovery processes. The total extent of landscape recovery, from prior land use to natural or semi-natural vegetation cover, accounted for less than 3 % of change. In a region of complex change, increases in transitory grassland and shrubland covers were caused by large-scale intensive plantation silviculture and small-scale activities including mining reclamation. Explicit identification of the process types and dynamics presented here may improve the understanding of land-cover change and landscape trajectory.

Assessing Landscape Change and Processes of Recurrence, Replacement, and Recovery in the Southeastern Coastal Plains, USA.

PubMed

Drummond, Mark A; Stier, Michael P; Auch, Roger F; Taylor, Janis L; Griffith, Glenn E; Riegle, Jodi L; Hester, David J; Soulard, Christopher E; McBeth, Jamie L

2015-11-01

The processes of landscape change are complex, exhibiting spatial variability as well as linear, cyclical, and reversible characteristics. To better understand the various processes that cause transformation, a data aggregation, validation, and attribution approach was developed and applied to an analysis of the Southeastern Coastal Plains (SECP). The approach integrates information from available national land-use, natural disturbance, and land-cover data to efficiently assess spatially-specific changes and causes. Between 2001 and 2006, the processes of change affected 7.8% of the SECP but varied across small-scale ecoregions. Processes were placed into a simple conceptual framework to explicitly identify the type and direction of change based on three general characteristics: replacement, recurrence, and recovery. Replacement processes, whereby a land use or cover is supplanted by a new land use, including urbanization and agricultural expansion, accounted for approximately 15% of the extent of change. Recurrent processes that contribute to cyclical changes in land cover, including forest harvest/replanting and fire, accounted for 83%. Most forest cover changes were recurrent, while the extents of recurrent silviculture and forest replacement processes such as urbanization far exceeded forest recovery processes. The total extent of landscape recovery, from prior land use to natural or semi-natural vegetation cover, accounted for less than 3% of change. In a region of complex change, increases in transitory grassland and shrubland covers were caused by large-scale intensive plantation silviculture and small-scale activities including mining reclamation. Explicit identification of the process types and dynamics presented here may improve the understanding of land-cover change and landscape trajectory.

Sensitivity properties of a biosphere model based on BATS and a statistical-dynamical climate model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, T.

A biosphere model based on the Biosphere-Atmosphere Transfer Scheme (BATS) and the Saltzman-Vernekar (SV) statistical-dynamical climate model is developed. Some equations of BATS are adopted either intact or with modifications, some are conceptually modified, and still others are replaced with equations of the SV model. The model is designed so that it can be run independently as long as the parameters related to the physiology and physiognomy of the vegetation, the atmospheric conditions, solar radiation, and soil conditions are given. With this stand-alone biosphere model, a series of sensitivity investigations, particularly the model sensitivity to fractional area of vegetation cover,more » soil surface water availability, and solar radiation for different types of vegetation, were conducted as a first step. These numerical experiments indicate that the presence of a vegetation cover greatly enhances the exchanges of momentum, water vapor, and energy between the atmosphere and the surface of the earth. An interesting result is that a dense and thick vegetation cover tends to serve as an environment conditioner or, more specifically, a thermostat and a humidistat, since the soil surface temperature, foliage temperature, and temperature and vapor pressure of air within the foliage are practically insensitive to variation of soil surface water availability and even solar radiation within a wide range. An attempt is also made to simulate the gradual deterioration of environment accompanying gradual degradation of a tropical forest to grasslands. Comparison with field data shows that this model can realistically simulate the land surface processes involving biospheric variations. 46 refs., 10 figs., 6 tabs.« less

Sensitivity properties of a biosphere model based on BATS and a statistical-dynamical climate model

NASA Technical Reports Server (NTRS)

Zhang, Taiping

1994-01-01

A biosphere model based on the Biosphere-Atmosphere Transfer Scheme (BATS) and the Saltzman-Vernekar (SV) statistical-dynamical climate model is developed. Some equations of BATS are adopted either intact or with modifications, some are conceptually modified, and still others are replaced with equations of the SV model. The model is designed so that it can be run independently as long as the parameters related to the physiology and physiognomy of the vegetation, the atmospheric conditions, solar radiation, and soil conditions are given. With this stand-alone biosphere model, a series of sensitivity investigations, particularly the model sensitivity to fractional area of vegetation cover, soil surface water availability, and solar radiation for different types of vegetation, were conducted as a first step. These numerical experiments indicate that the presence of a vegetation cover greatly enhances the exchanges of momentum, water vapor, and energy between the atmosphere and the surface of the earth. An interesting result is that a dense and thick vegetation cover tends to serve as an environment conditioner or, more specifically, a thermostat and a humidistat, since the soil surface temperature, foliage temperature, and temperature and vapor pressure of air within the foliage are practically insensitive to variation of soil surface water availability and even solar radiation within a wide range. An attempt is also made to simulate the gradual deterioration of environment accompanying gradual degradation of a tropical forest to grasslands. Comparison with field data shows that this model can realistically simulate the land surface processes involving biospheric variations.

User's Guide for the Agricultural Non-Point Source (AGNPS) Pollution Model Data Generator

USGS Publications Warehouse

Finn, Michael P.; Scheidt, Douglas J.; Jaromack, Gregory M.

2003-01-01

BACKGROUND Throughout this user guide, we refer to datasets that we used in conjunction with developing of this software for supporting cartographic research and producing the datasets to conduct research. However, this software can be used with these datasets or with more 'generic' versions of data of the appropriate type. For example, throughout the guide, we refer to national land cover data (NLCD) and digital elevation model (DEM) data from the U.S. Geological Survey (USGS) at a 30-m resolution, but any digital terrain model or land cover data at any appropriate resolution will produce results. Another key point to keep in mind is to use a consistent data resolution for all the datasets per model run. The U.S. Department of Agriculture (USDA) developed the Agricultural Nonpoint Source (AGNPS) pollution model of watershed hydrology in response to the complex problem of managing nonpoint sources of pollution. AGNPS simulates the behavior of runoff, sediment, and nutrient transport from watersheds that have agriculture as their prime use. The model operates on a cell basis and is a distributed parameter, event-based model. The model requires 22 input parameters. Output parameters are grouped primarily by hydrology, sediment, and chemical output (Young and others, 1995.) Elevation, land cover, and soil are the base data from which to extract the 22 input parameters required by the AGNPS. For automatic parameter extraction, follow the general process described in this guide of extraction from the geospatial data through the AGNPS Data Generator to generate input parameters required by the pollution model (Finn and others, 2002.)

Comparing cropland net primary production estimates from inventory, a satellite-based model, and a process-based model in the Midwest of the United States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Zhengpeng; Liu, Shuguang; Tan, Zhengxi

2014-04-01

Accurately quantifying the spatial and temporal variability of net primary production (NPP) for croplands is essential to understand regional cropland carbon dynamics. We compared three NPP estimates for croplands in the Midwestern United States: inventory-based estimates using crop yield data from the U.S. Department of Agriculture (USDA) National Agricultural Statistics Service (NASS); estimates from the satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) NPP product; and estimates from the General Ensemble biogeochemical Modeling System (GEMS) process-based model. The three methods estimated mean NPP in the range of 469–687 g C m -2 yr -1 and total NPP in the range of 318–490more » Tg C yr -1 for croplands in the Midwest in 2007 and 2008. The NPP estimates from crop yield data and the GEMS model showed the mean NPP for croplands was over 650 g C m -2 yr -1 while the MODIS NPP product estimated the mean NPP was less than 500 g C m -2 yr -1. MODIS NPP also showed very different spatial variability of the cropland NPP from the other two methods. We found these differences were mainly caused by the difference in the land cover data and the crop specific information used in the methods. Our study demonstrated that the detailed mapping of the temporal and spatial change of crop species is critical for estimating the spatial and temporal variability of cropland NPP. Finally, we suggest that high resolution land cover data with species–specific crop information should be used in satellite-based and process-based models to improve carbon estimates for croplands.« less

Comparing cropland net primary production estimates from inventory, a satellite-based model, and a process-based model in the Midwest of the United States

USGS Publications Warehouse

Li, Zhengpeng; Liu, Shuguang; Tan, Zhengxi; Bliss, Norman B.; Young, Claudia J.; West, Tristram O.; Ogle, Stephen M.

2014-01-01

Accurately quantifying the spatial and temporal variability of net primary production (NPP) for croplands is essential to understand regional cropland carbon dynamics. We compared three NPP estimates for croplands in the Midwestern United States: inventory-based estimates using crop yield data from the U.S. Department of Agriculture (USDA) National Agricultural Statistics Service (NASS); estimates from the satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) NPP product; and estimates from the General Ensemble biogeochemical Modeling System (GEMS) process-based model. The three methods estimated mean NPP in the range of 469–687 g C m−2 yr−1and total NPP in the range of 318–490 Tg C yr−1 for croplands in the Midwest in 2007 and 2008. The NPP estimates from crop yield data and the GEMS model showed the mean NPP for croplands was over 650 g C m−2 yr−1 while the MODIS NPP product estimated the mean NPP was less than 500 g C m−2 yr−1. MODIS NPP also showed very different spatial variability of the cropland NPP from the other two methods. We found these differences were mainly caused by the difference in the land cover data and the crop specific information used in the methods. Our study demonstrated that the detailed mapping of the temporal and spatial change of crop species is critical for estimating the spatial and temporal variability of cropland NPP. We suggest that high resolution land cover data with species–specific crop information should be used in satellite-based and process-based models to improve carbon estimates for croplands.

Uncertainty in Land Cover observations and its impact on near surface climate

NASA Astrophysics Data System (ADS)

Georgievski, Goran; Hagemann, Stefan

2017-04-01

Land Cover (LC) and its bio-geo-physical feedbacks are important for the understanding of climate and its vulnerability to changes on the surface of the Earth. Recently ESA has published a new LC map derived by combining remotely sensed surface reflectance and ground-truth observations. For each grid-box at 300m resolution, an estimate of confidence is provided. This LC data set can be used in climate modelling to derive land surface boundary parameters for the respective Land Surface Model (LSM). However, the ESA LC classes are not directly suitable for LSMs, therefore they need to be converted into the model specific surface presentations. Due to different design and processes implemented in various climate models they might differ in the treatment of artificial, water bodies, ice, bare or vegetated surfaces. Nevertheless, usually vegetation distribution in models is presented by means of plant functional types (PFT), which is a classification system used to simplify vegetation representation and group different vegetation types according to their biophysical characteristics. The method of LC conversion into PFT is also called "cross-walking" (CW) procedure. The CW procedure is another source of uncertainty, since it depends on model design and processes implemented and resolved by LSMs. These two sources of uncertainty, (i) due to surface reflectance conversion into LC classes, (ii) due to CW procedure, have been studied by Hartley et al (2016) to investigate their impact on LSM state variables (albedo, evapotranspiration (ET) and primary productivity) by using three standalone LSMs. The present study is a follow up to that work and aims at quantifying the impact of these two uncertainties on climate simulations performed with the Max Planck Institute for Meteorology Earth System Model (MPI-ESM) using prescribed sea surface temperature and sea ice. The main focus is on the terrestrial water cycle, but the impacts on surface albedo, wind patterns, 2m temperatures, as well as plant productivity are also examined. The analysis of vegetation covered area indicates that the range of uncertainty might be about the same order of magnitude as the estimated historical anthropogenic LC change. For example, the area covered with managed grasses (crops and pasture in MPI-ESM PFT classification) varies from 17 to 26 million km2, and area covered with trees ranges from 15 million km2 up to 51 million km2. These uncertainties in vegetation distribution lead to noticeable variations in atmospheric temperature, humidity, cloud cover, circulation, and precipitation as well as local, regional and global climate forcing. For example, the amount of terrestrial ET ranges from 73 to 77 × 103 km3yr-1in MPI-ESM simulations and this range has about the same order of magnitude as the current estimate of the reduction of annual ET due to recent anthropogenic LC change. This and more impacts of LC uncertainty on the near surface climate will be presented and discussed in the context of LC change. Hartley, A.J., MacBean, N., Georgievski, G., Bontemps, S.: Uncertainty in plant functional type distributions and its impact on land surface models (in review with Remote Sensing of Environment Special Issue)

How well do we characterize the biophysical effects of vegetation cover change? Benchmarking land surface models against satellite observations.

NASA Astrophysics Data System (ADS)

Duveiller, Gregory; Forzieri, Giovanni; Robertson, Eddy; Georgievski, Goran; Li, Wei; Lawrence, Peter; Ciais, Philippe; Pongratz, Julia; Sitch, Stephen; Wiltshire, Andy; Arneth, Almut; Cescatti, Alessandro

2017-04-01

Changes in vegetation cover can affect the climate by altering the carbon, water and energy cycles. The main tools to characterize such land-climate interactions for both the past and future are land surface models (LSMs) that can be embedded in larger Earth System models (ESMs). While such models have long been used to characterize the biogeochemical effects of vegetation cover change, their capacity to model biophysical effects accurately across the globe remains unclear due to the complexity of the phenomena. The result of competing biophysical processes on the surface energy balance varies spatially and seasonally, and can lead to warming or cooling depending on the specific vegetation change and on the background climate (e.g. presence of snow or soil moisture). Here we present a global scale benchmarking exercise of four of the most commonly used LSMs (JULES, ORCHIDEE, JSBACH and CLM) against a dedicated dataset of satellite observations. To facilitate the understanding of the causes that lead to discrepancies between simulated and observed data, we focus on pure transitions amongst major plant functional types (PFTs): from different tree types (evergreen broadleaf trees, deciduous broadleaf trees and needleleaf trees) to either grasslands or crops. From the modelling perspective, this entails generating a separate simulation for each PFT in which all 1° by 1° grid cells are uniformly covered with that PFT, and then analysing the differences amongst them in terms of resulting biophysical variables (e.g net radiation, latent and sensible heat). From the satellite perspective, the effect of pure transitions is obtained by unmixing the signal of different 0.05° spatial resolution MODIS products (albedo, latent heat, upwelling longwave radiation) over a local moving window using PFT maps derived from the ESA Climate Change Initiative land cover map. After aggregating to a common spatial support, the observation and model-driven datasets are confronted and analysed across different climate zones. Results indicate that models tend to catch better radiative than non-radiative energy fluxes. However, for various vegetation transitions, models do not agree amongst themselves on the magnitude nor the sign of the change. In particular, predicting the impact of land cover change on the partitioning of the available energy between latent and sensible heat proves to be a challenging task for vegetation models. We expect that this benchmarking exercise will shed a light on where to prioritize the efforts in model development as well as inform where consensus between model and observations is already met. Improving the robustness and consistency of land-model is essential to develop and inform land-based mitigation and adaptation policies that account for both biogeochemical and biophysical vegetation impacts on climate.

Integration of geological remote-sensing techniques in subsurface analysis

USGS Publications Warehouse

Taranik, James V.; Trautwein, Charles M.

1976-01-01

Geological remote sensing is defined as the study of the Earth utilizing electromagnetic radiation which is either reflected or emitted from its surface in wavelengths ranging from 0.3 micrometre to 3 metres. The natural surface of the Earth is composed of a diversified combination of surface cover types, and geologists must understand the characteristics of surface cover types to successfully evaluate remotely-sensed data. In some areas landscape surface cover changes throughout the year, and analysis of imagery acquired at different times of year can yield additional geological information. Integration of different scales of analysis allows landscape features to be effectively interpreted. Interpretation of the static elements displayed on imagery is referred to as an image interpretation. Image interpretation is dependent upon: (1) the geologist's understanding of the fundamental aspects of image formation, and (2.) his ability to detect, delineate, and classify image radiometric data; recognize radiometric patterns; and identify landscape surface characteristics as expressed on imagery. A geologic interpretation integrates surface characteristics of the landscape with subsurface geologic relationships. Development of a geologic interpretation from imagery is dependent upon: (1) the geologist's ability to interpret geomorphic processes from their static surface expression as landscape characteristics on imagery, (2) his ability to conceptualize the dynamic processes responsible for the evolution 6f interpreted geologic relationships (his ability to develop geologic models). The integration of geologic remote-sensing techniques in subsurface analysis is illustrated by development of an exploration model for ground water in the Tucson area of Arizona, and by the development of an exploration model for mineralization in southwest Idaho.

The mark of vegetation change on Earth's surface energy balance: data-driven diagnostics and model validation

NASA Astrophysics Data System (ADS)

Cescatti, A.; Duveiller, G.; Hooker, J.

2017-12-01

Changing vegetation cover not only affects the atmospheric concentration of greenhouse gases but also alters the radiative and non-radiative properties of the surface. The result of competing biophysical processes on Earth's surface energy balance varies spatially and seasonally, and can lead to warming or cooling depending on the specific vegetation change and on the background climate. To date these effects are not accounted for in land-based climate policies because of the complexity of the phenomena, contrasting model predictions and the lack of global data-driven assessments. To overcome the limitations of available observation-based diagnostics and of the on-going model inter-comparison, here we present a new benchmarking dataset derived from satellite remote sensing. This global dataset provides the potential changes induced by multiple vegetation transitions on the single terms of the surface energy balance. We used this dataset for two major goals: 1) Quantify the impact of actual vegetation changes that occurred during the decade 2000-2010, showing the overwhelming role of tropical deforestation in warming the surface by reducing evapotranspiration despite the concurrent brightening of the Earth. 2) Benchmark a series of ESMs against data-driven metrics of the land cover change impacts on the various terms of the surface energy budget and on the surface temperature. We anticipate that the dataset could be also used to evaluate future scenarios of land cover change and to develop the monitoring, reporting and verification guidelines required for the implementation of mitigation plans that account for biophysical land processes.

Impact of the snow cover scheme on snow distribution and energy budget modeling over the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Xie, Zhipeng; Hu, Zeyong; Xie, Zhenghui; Jia, Binghao; Sun, Genhou; Du, Yizhen; Song, Haiqing

2018-02-01

This paper presents the impact of two snow cover schemes (NY07 and SL12) in the Community Land Model version 4.5 (CLM4.5) on the snow distribution and surface energy budget over the Tibetan Plateau. The simulated snow cover fraction (SCF), snow depth, and snow cover days were evaluated against in situ snow depth observations and a satellite-based snow cover product and snow depth dataset. The results show that the SL12 scheme, which considers snow accumulation and snowmelt processes separately, has a higher overall accuracy (81.8%) than the NY07 (75.8%). The newer scheme performs better in the prediction of overall accuracy compared with the NY07; however, SL12 yields a 15.1% underestimation rate while NY07 overestimated the SCF with a 15.2% overestimation rate. Both two schemes capture the distribution of the maximum snow depth well but show large positive biases in the average value through all periods (3.37, 3.15, and 1.48 cm for NY07; 3.91, 3.52, and 1.17 cm for SL12) and overestimate snow cover days compared with the satellite-based product and in situ observations. Higher altitudes show larger root-mean-square errors (RMSEs) in the simulations of snow depth and snow cover days during the snow-free period. Moreover, the surface energy flux estimations from the SL12 scheme are generally superior to the simulation from NY07 when evaluated against ground-based observations, in particular for net radiation and sensible heat flux. This study has great implications for further improvement of the subgrid-scale snow variations over the Tibetan Plateau.

The origin of high and low flows in the river Rhine: particle tracing and water quality calculations in a distributed hydrological model

NASA Astrophysics Data System (ADS)

Schellekens, Jaap; van Gils, Jos; Christophe, Christophe; Sperna-Weiland, Frederiek; Winsemius, Hessel

2013-04-01

The ability to quickly link a complete water quality model to any distributed hydrological model can be of great value. It provides the hydrological modeller with more information on the performance of the model by being able to add particle tracing and independent mass balance calculations to an existing distributed hydrological model. It also allows for full catchment water quality calculations forced by emissions to different hydrological compartments, taking into account the relevant processes in the different compartments of the hydrological model. A combined distributed hydrological model and hydrochemical model (Delwaq) have been combined within the modeling framework OpenStreams to model large scale hydrological processes in the Rhine basin upstream of the Dutch border at Lobith. Several models have been setup to evaluate (1) the origin of high and low flows in the Rhine basin based on subcatchment contribution and (2) the contribution of different land covers to the total flow with special reference to urban land cover. In addition (3) the relative share of fast and slow runoff components in the total river discharge has been quantified, as well as the age of these two fractions, both as a function of time. Finally (4) the transmission of a pollutant released in infiltrating water and undergoing sorption has been simulated, as a first test for implementing full water quality modelling. The results of a thirty-five year run using daily time steps for 1975 to 2010 were analysed for monthly average contribution to the total flow of each subcatchment and the different land cover types both for average flow conditions and for the top ten and bottom ten flow percentiles. Furthermore, a number of high and low flow events have been analysed in detail. They reveal the large contribution of the basin area upstream of Basel to the dry season flow, especially during the driest summers. Flood conditions in the basin have a more varied origin with the Moselle being the main contributor. The amount of urban land cover (6.7%) generated a fairly large amount of (quick) runoff. In times up to 21 % of the flow at Lobith is generated in urban areas. The location of urban areas (in general close to the river) in combination with the associated impermeable surfaces most probably cause the relatively large contribution of urban areas. The fast runoff fraction at Lobith has an average age between 5 and 25 days, depending on the hydrology within the year, while the slow runoff fraction shows an average age between 300 and 600 days, again depending on the hydrology within the year. The time needed to flush out 90% of the total volume of water from the basin is about 20 years.

Modelling the future impacts of climate and land-use change on suspended sediment transport in the River Thames (UK)

NASA Astrophysics Data System (ADS)

Bussi, Gianbattista; Dadson, Simon J.; Prudhomme, Christel; Whitehead, Paul G.

2016-11-01

The effects of climate change and variability on river flows have been widely studied. However the impacts of such changes on sediment transport have received comparatively little attention. In part this is because modelling sediment production and transport processes introduces additional uncertainty, but it also results from the fact that, alongside the climate change signal, there have been and are projected to be significant changes in land cover which strongly affect sediment-related processes. Here we assess the impact of a range of climatic variations and land covers on the River Thames catchment (UK). We first calculate a response of the system to climatic stressors (average precipitation, average temperature and increase in extreme precipitation) and land-cover stressors (change in the extent of arable land). To do this we use an ensemble of INCA hydrological and sediment behavioural models. The resulting system response, which reveals the nature of interactions between the driving factors, is then compared with climate projections originating from the UKCP09 assessment (UK Climate Projections 2009) to evaluate the likelihood of the range of projected outcomes. The results show that climate and land cover each exert an individual control on sediment transport. Their effects vary depending on the land use and on the level of projected climate change. The suspended sediment yield of the River Thames in its lowermost reach is expected to change by -4% (-16% to +13%, confidence interval, p = 0.95) under the A1FI emission scenario for the 2030s, although these figures could be substantially altered by an increase in extreme precipitation, which could raise the suspended sediment yield up to an additional +10%. A 70% increase in the extension of the arable land is projected to increase sediment yield by around 12% in the lowland reaches. A 50% reduction is projected to decrease sediment yield by around 13%.

Numerical Modeling of High-Temperature Corrosion Processes

NASA Technical Reports Server (NTRS)

Nesbitt, James A.

1995-01-01

Numerical modeling of the diffusional transport associated with high-temperature corrosion processes is reviewed. These corrosion processes include external scale formation and internal subscale formation during oxidation, coating degradation by oxidation and substrate interdiffusion, carburization, sulfidation and nitridation. The studies that are reviewed cover such complexities as concentration-dependent diffusivities, cross-term effects in ternary alloys, and internal precipitation where several compounds of the same element form (e.g., carbides of Cr) or several compounds exist simultaneously (e.g., carbides containing varying amounts of Ni, Cr, Fe or Mo). In addition, the studies involve a variety of boundary conditions that vary with time and temperature. Finite-difference (F-D) techniques have been applied almost exclusively to model either the solute or corrodant transport in each of these studies. Hence, the paper first reviews the use of F-D techniques to develop solutions to the diffusion equations with various boundary conditions appropriate to high-temperature corrosion processes. The bulk of the paper then reviews various F-D modeling studies of diffusional transport associated with high-temperature corrosion.

Indices for estimating fractional snow cover in the western Tibetan Plateau

NASA Astrophysics Data System (ADS)

Shreve, Cheney M.; Okin, Gregory S.; Painter, Thomas H.

Snow cover in the Tibetan Plateau is highly variable in space and time and plays a key role in ecological processes of this cold-desert ecosystem. Resolution of passive microwave data is too low for regional-scale estimates of snow cover on the Tibetan Plateau, requiring an alternate data source. Optically derived snow indices allow for more accurate quantification of snow cover using higher-resolution datasets subject to the constraint of cloud cover. This paper introduces a new optical snow index and assesses four optically derived MODIS snow indices using Landsat-based validation scenes: MODIS Snow-Covered Area and Grain Size (MODSCAG), Relative Multiple Endmember Spectral Mixture Analysis (RMESMA), Relative Spectral Mixture Analysis (RSMA) and the normalized-difference snow index (NDSI). Pearson correlation coefficients were positively correlated with the validation datasets for all four optical snow indices, suggesting each provides a good measure of total snow extent. At the 95% confidence level, linear least-squares regression showed that MODSCAG and RMESMA had accuracy comparable to validation scenes. Fusion of optical snow indices with passive microwave products, which provide snow depth and snow water equivalent, has the potential to contribute to hydrologic and energy-balance modeling in the Tibetan Plateau.

Geophysical imaging and thermal modeling of subsurface morphology and thaw evolution of discontinuous permafrost

NASA Astrophysics Data System (ADS)

McClymont, Alastair F.; Hayashi, Masaki; Bentley, Laurence R.; Christensen, Brendan S.

2013-09-01

our current understanding of permafrost thaw in subarctic regions in response to rising air temperatures, little is known about the subsurface geometry and distribution of discontinuous permafrost bodies in peat-covered, wetland-dominated terrains and their responses to rising temperature. Using electrical resistivity tomography, ground-penetrating radar profiling, and thermal-conduction modeling, we show how the land cover distributions influence thawing of discontinuous permafrost at a study site in the Northwest Territories, Canada. Permafrost bodies in this region occur under forested peat plateaus and have thicknesses of 5-13 m. Our geophysical data reveal different stages of thaw resulting from disturbances within the active layer: from widening and deepening of differential thaw features under small frost-table depressions to complete thaw of permafrost under an isolated bog. By using two-dimensional geometric constraints derived from our geophysics profiles and meteorological data, we model seasonal and interannual changes to permafrost distribution in response to contemporary climatic conditions and changes in land cover. Modeling results show that in this environment (1) differences in land cover have a strong influence on subsurface thermal gradients such that lateral thaw dominates over vertical thaw and (2) in accordance with field observations, thaw-induced subsidence and flooding at the lateral margins of peat plateaus represents a positive feedback that leads to enhanced warming along the margins of peat plateaus and subsequent lateral heat conduction. Based on our analysis, we suggest that subsurface energy transfer processes (and feedbacks) at scales of 1-100 m have a strong influence on overall permafrost degradation rates at much larger scales.

COVER: A user's guide to the CANOPY and SHRUBS extension of the Stand Prognosis Model

Treesearch

Melinda Moeur

1985-01-01

The COVER model predicts vertical and horizontal tree canopy closure, tree foliage biomass, and the probability of occurrence, height, and cover of shrubs in forest stands. This paper documents use of the COVER program, an adjunct to the Stand Prognosis Model. Preparation of input, interpretation of output, program control, model characteristics, and example...

20 CFR 1010.300 - What processes are to be implemented to identify covered persons?

Code of Federal Regulations, 2014 CFR

2014-04-01

... 20 Employees' Benefits 4 2014-04-01 2014-04-01 false What processes are to be implemented to identify covered persons? 1010.300 Section 1010.300 Employees' Benefits OFFICE OF THE ASSISTANT SECRETARY... FOR COVERED PERSONS Applying Priority of Service § 1010.300 What processes are to be implemented to...

Graphene growth process modeling: a physical-statistical approach

NASA Astrophysics Data System (ADS)

Wu, Jian; Huang, Qiang

2014-09-01

As a zero-band semiconductor, graphene is an attractive material for a wide variety of applications such as optoelectronics. Among various techniques developed for graphene synthesis, chemical vapor deposition on copper foils shows high potential for producing few-layer and large-area graphene. Since fabrication of high-quality graphene sheets requires the understanding of growth mechanisms, and methods of characterization and control of grain size of graphene flakes, analytical modeling of graphene growth process is therefore essential for controlled fabrication. The graphene growth process starts with randomly nucleated islands that gradually develop into complex shapes, grow in size, and eventually connect together to cover the copper foil. To model this complex process, we develop a physical-statistical approach under the assumption of self-similarity during graphene growth. The growth kinetics is uncovered by separating island shapes from area growth rate. We propose to characterize the area growth velocity using a confined exponential model, which not only has clear physical explanation, but also fits the real data well. For the shape modeling, we develop a parametric shape model which can be well explained by the angular-dependent growth rate. This work can provide useful information for the control and optimization of graphene growth process on Cu foil.

Towards a community Earth System Model

NASA Astrophysics Data System (ADS)

Blackmon, M.

2003-04-01

The Community Climate System Model, version 2 (CCSM2), was released in June 2002. CCSM2 has several new components and features, which I will discuss briefly. I will also show a few results from a multi-century equilibrium run with this model, emphasizing the improvements over the earlier simulation using the original CSM. A few flaws and inadequacies in CCSM2 have been identified. I will also discuss briefly work underway to improve the model and present results, if available. CCSM2, with improvements, will be the basis for the development of a Community Earth System Model (CESM). The highest priority for expansion of the model involves incorporation of biogeosciences into the coupled model system, with emphasis given to the carbon, nitrogen and iron cycles. The overall goal of the biogeosciences project within CESM is to understand the regulation of planetary energetics, planetary ecology, and planetary metabolism through exchanges of energy, momentum, and materials among atmosphere, land, and ocean, and the response of the climate system through these processes to changes in land cover and land use. In particular, this research addresses how biogeochemical coupling of carbon, nitrogen, and iron cycles affects climate and how human perturbations of these cycles alter climate. To accomplish these goals, the Community Land Model, the land component of CCSM2, is being developed to include river routing, carbon and nitrogen cycles, emissions of mineral aerosols and biogenic volatile organic compounds, dry deposition of various gases, and vegetation dynamics. The carbon and nitrogen cycles are being implemented using parameterizations developed as part of a state-of-the-art ecosystem biogeochemistry model. The primary goal of this research is to provide an accurate net flux of CO2 between the land and the atmosphere so that CESM can be used to study the dynamics of the coupled climate-carbon system. Emissions of biogenic volatile organic compounds are also based on a state-of-the-art emissions model and depend on plant type, leaf area index, photosynthetically active radiation, and leaf temperature. Dust emissions and deposition are being developed to implement a fully coupled dust cycle in CCSM, including the radiative effects of dust and carbon feedbacks related to fertilization of ocean and terrestrial ecosystems. Dust mobilization depends on surface wind speed, soil moisture, plant cover, and soil texture. Dust dry deposition processes include sedimentation and turbulent mix-out. A major research focus is how natural and human-mediated changes in land cover and ecosystem functions alter surface energy fluxes, the hydrological cycle, and biogeochemical cycles. Human land uses include conversion of natural vegetation to cropland, soil degradation, and urbanization. Climate feedbacks associated with natural changes in land cover are being assessed by developing and implementing a model of natural vegetation dynamics for use with the Community Land Model. Development of a marine ecosystem model is also underway. The ecosystem model is based on the global, mixed-layer marine ecosystem model of Moore et al., which includes parameterizations for such things as iron limitation and scavenging, zooplankton grazing, nitrogen fixation, calcification, and ballast-based remineralization. A series of experiments is being planned to assess the coupling of the ecology to the biogeochemistry, to adequately tune some of the model parameters that are poorly constrained by data, to explore new parameterizations and processes (e.g., riverine and atmospheric inputs of nutrients), and to conduct uncoupled application studies (e.g., deliberate carbon sequestration, retrospective historical simulations, iron-dust deposition response). Longer term plans include investigating biogeochemical processes in the coastal zone and how to incorporate these processes into a global ocean model, either through subgrid-scale parameterizations or model nesting. A Whole Atmosphere Community Climate Model(WACCM) is being developed. The vertical extent of the model is 150 km at present, but extension to 500 km is eventually expected. Interactive chemistry is being incorporated. This model will be used as the atmospheric component of CESM for some experiments. One expected application is the study of solar variability and its impact on climate variability in the troposphere and at the atmosphere, ocean, land interface. Preliminary results using some of these model components will be shown. A timeline for development and use of the models will be given.

The challenges associated with applying global models in heterogeneous landscapes: A case study using MOD17 GPP estimates in Hawaii

NASA Astrophysics Data System (ADS)

Kimball, H.; Selmants, P. C.; Running, S. W.; Moreno, A.; Giardina, C. P.

2016-12-01

In this study we evaluate the influence of spatial data product accuracy and resolution on the application of global models for smaller scale heterogeneous landscapes. In particular, we assess the influence of locally specific land cover and high-resolution climate data products on estimates of Gross Primary Production (GPP) for the Hawaiian Islands using the MOD17 model. The MOD17 GPP algorithm uses a measure of the fraction of absorbed photosynthetically active radiation from the National Aeronautics and Space Administration's Earth Observation System. This direct measurement is combined with global land cover (500-m resolution) and climate models ( 1/2-degree resolution) to estimate GPP. We first compared the alignment between the global land cover model used in MOD17 with a Hawaii specific land cover data product. We found that there was a 51.6% overall agreement between the two land cover products. We then compared four MOD17 GPP models: A global model that used the global land cover and low-resolution global climate data products, a model produced using the Hawaii specific land cover and low-resolution global climate data products, a model with global land cover and high-resolution climate data products, and finally, a model using both Hawaii specific land cover and high-resolution climate data products. We found that including either the Hawaii specific land cover or the high-resolution Hawaii climate data products with MOD17 reduced overall estimates of GPP by 8%. When both were used, GPP estimates were reduced by 16%. The reduction associated with land cover is explained by a reduction of the total area designated as evergreen broad leaf forest and an increase in the area designated as barren or sparsely vegetated in the Hawaii land cover product as compared to the global product. The climate based reduction is explained primarily by the spatial resolution and distribution of solar radiation in the Hawaiian Islands. This study highlights the importance of accuracy and resolution when applying global models to highly variable landscapes and provides an estimate of the influence of land cover and climate data products on estimates of GPP using MOD17.

Analysis of spatio-temporal land cover changes for hydrological impact assessment within the Nyando River Basin of Kenya.

PubMed

Olang, Luke Omondi; Kundu, Peter; Bauer, Thomas; Fürst, Josef

2011-08-01

The spatio-temporal changes in the land cover states of the Nyando Basin were investigated for auxiliary hydrological impact assessment. The predominant land cover types whose conversions could influence the hydrological response of the region were selected. Six Landsat images for 1973, 1986, and 2000 were processed to discern the changes based on a methodology that employs a hybrid of supervised and unsupervised classification schemes. The accuracy of the classifications were assessed using reference datasets processed in a GIS with the help of ground-based information obtained through participatory mapping techniques. To assess the possible hydrological effect of the detected changes during storm events, a physically based lumped approach for infiltration loss estimation was employed within five selected sub-basins. The results obtained indicated that forests in the basin declined by 20% while agricultural fields expanded by 16% during the entire period of study. Apparent from the land cover conversion matrices was that the majority of the forest decline was a consequence of agricultural expansion. The model results revealed decreased infiltration amounts by between 6% and 15%. The headwater regions with the vast deforestation were noted to be more vulnerable to the land cover change effects. Despite the haphazard land use patterns and uncertainties related to poor data quality for environmental monitoring and assessment, the study exposed the vast degradation and hence the need for sustainable land use planning for enhanced catchment management purposes.

Assessing winter cover crop nutrient uptake efficiency using a water quality simulation model

NASA Astrophysics Data System (ADS)

Yeo, I.-Y.; Lee, S.; Sadeghi, A. M.; Beeson, P. C.; Hively, W. D.; McCarty, G. W.; Lang, M. W.

2014-12-01

Winter cover crops are an effective conservation management practice with potential to improve water quality. Throughout the Chesapeake Bay watershed (CBW), which is located in the mid-Atlantic US, winter cover crop use has been emphasized, and federal and state cost-share programs are available to farmers to subsidize the cost of cover crop establishment. The objective of this study was to assess the long-term effect of planting winter cover crops to improve water quality at the watershed scale (~ 50 km2) and to identify critical source areas of high nitrate export. A physically based watershed simulation model, Soil and Water Assessment Tool (SWAT), was calibrated and validated using water quality monitoring data to simulate hydrological processes and agricultural nutrient cycling over the period of 1990-2000. To accurately simulate winter cover crop biomass in relation to growing conditions, a new approach was developed to further calibrate plant growth parameters that control the leaf area development curve using multitemporal satellite-based measurements of species-specific winter cover crop performance. Multiple SWAT scenarios were developed to obtain baseline information on nitrate loading without winter cover crops and to investigate how nitrate loading could change under different winter cover crop planting scenarios, including different species, planting dates, and implementation areas. The simulation results indicate that winter cover crops have a negligible impact on the water budget but significantly reduce nitrate leaching to groundwater and delivery to the waterways. Without winter cover crops, annual nitrate loading from agricultural lands was approximately 14 kg ha-1, but decreased to 4.6-10.1 kg ha-1 with cover crops resulting in a reduction rate of 27-67% at the watershed scale. Rye was the most effective species, with a potential to reduce nitrate leaching by up to 93% with early planting at the field scale. Early planting of cover crops (~ 30 days of additional growing days) was crucial, as it lowered nitrate export by an additional ~ 2 kg ha-1 when compared to late planting scenarios. The effectiveness of cover cropping increased with increasing extent of cover crop implementation. Agricultural fields with well-drained soils and those that were more frequently used to grow corn had a higher potential for nitrate leaching and export to the waterways. This study supports the effective implementation of cover crop programs, in part by helping to target critical pollution source areas for cover crop implementation.

Towards realistic Holocene land cover scenarios: integration of archaeological, palynological and geomorphological records and comparison to global land cover scenarios.

NASA Astrophysics Data System (ADS)

De Brue, Hanne; Verstraeten, Gert; Broothaerts, Nils; Notebaert, Bastiaan

2016-04-01

Accurate and spatially explicit landscape reconstructions for distinct time periods in human history are essential for the quantification of the effect of anthropogenic land cover changes on, e.g., global biogeochemical cycles, ecology, and geomorphic processes, and to improve our understanding of interaction between humans and the environment in general. A long-term perspective covering Mid and Late Holocene land use changes is recommended in this context, as it provides a baseline to evaluate human impact in more recent periods. Previous efforts to assess the evolution and intensity of agricultural land cover in past centuries or millennia have predominantly focused on palynological records. An increasing number of quantitative techniques has been developed during the last two decades to transfer palynological data to land cover estimates. However, these techniques have to deal with equifinality issues and, furthermore, do not sufficiently allow to reconstruct spatial patterns of past land cover. On the other hand, several continental and global databases of historical anthropogenic land cover changes based on estimates of global population and the required agricultural land per capita have been developed in the past decennium. However, at such long temporal and spatial scales, reconstruction of past anthropogenic land cover intensities and spatial patterns necessarily involves many uncertainties and assumptions as well. Here, we present a novel approach that combines archaeological, palynological and geomorphological data for the Dijle catchment in the central Belgium Loess Belt in order to arrive at more realistic Holocene land cover histories. Multiple land cover scenarios (> 60.000) are constructed using probabilistic rules and used as input into a sediment delivery model (WaTEM/SEDEM). Model outcomes are confronted with a detailed geomorphic dataset on Holocene sediment fluxes and with REVEALS based estimates of vegetation cover using palynological data from six alluvial sites. This comparison drastically reduces the number of realistic land cover scenarios for various cultural periods. REVEALS based land cover histories provide more accurate estimates of Holocene sediment fluxes compared to global land cover scenarios (KK10 and HYDE 3.1). Both global land cover scenarios produce erroneous results when applied at their original coarse scale resolution. However, spatially allocating KK10 land cover data to a finer spatial resolution increases its performance, whereas this is not the case for HYDE 3.1. Results suggest that KK10 also offers a more realistic history of human impact than HYDE 3.1 although it overestimates human impact in the Belgian Loess Belt prior to the Roman Age, whereas it underestimates human impact from the Medieval Period onwards.

Do Clouds Save the Great Barrier Reef? Satellite Imagery Elucidates the Cloud-SST Relationship at the Local Scale

PubMed Central

Leahy, Susannah M.; Kingsford, Michael J.; Steinberg, Craig R.

2013-01-01

Evidence of global climate change and rising sea surface temperatures (SSTs) is now well documented in the scientific literature. With corals already living close to their thermal maxima, increases in SSTs are of great concern for the survival of coral reefs. Cloud feedback processes may have the potential to constrain SSTs, serving to enforce an “ocean thermostat” and promoting the survival of coral reefs. In this study, it was hypothesized that cloud cover can affect summer SSTs in the tropics. Detailed direct and lagged relationships between cloud cover and SST across the central Great Barrier Reef (GBR) shelf were investigated using data from satellite imagery and in situ temperature and light loggers during two relatively hot summers (2005 and 2006) and two relatively cool summers (2007 and 2008). Across all study summers and shelf positions, SSTs exhibited distinct drops during periods of high cloud cover, and conversely, SST increases during periods of low cloud cover, with a three-day temporal lag between a change in cloud cover and a subsequent change in SST. Cloud cover alone was responsible for up to 32.1% of the variation in SSTs three days later. The relationship was strongest in both El Niño (2005) and La Niña (2008) study summers and at the inner-shelf position in those summers. SST effects on subsequent cloud cover were weaker and more variable among study summers, with rising SSTs explaining up to 21.6% of the increase in cloud cover three days later. This work quantifies the often observed cloud cooling effect on coral reefs. It highlights the importance of incorporating local-scale processes into bleaching forecasting models, and encourages the use of remote sensing imagery to value-add to coral bleaching field studies and to more accurately predict risks to coral reefs. PMID:23894649

75 FR 67689 - Stainless Steel Bar From Brazil: Preliminary Results of Antidumping Duty Administrative Review

Federal Register 2010, 2011, 2012, 2013, 2014

2010-11-03

... from Brazil. The review covers one producer/ exporter of the subject merchandise, Villares Metals S.A... have indentations, ribs, grooves, or other deformations produced during the rolling process. Except as..., we used the following methodology. If an identical comparison-market model was reported, we made...

Vocational English as a Second Language: A Partnership with Industry.

ERIC Educational Resources Information Center

Wilde, Cindy

This monograph offers a process model developed by the Fremont Union High School District (California) for the implementation of Vocational English as a Second Language (VESL) at industry sites for minority employees who have limited English proficiency and are unable to continue classes in a traditional manner. The following areas are covered:…

Making Nutrition Education Count: A Guide for Nutrition Education K-6. Grade 3.

ERIC Educational Resources Information Center

Kratky, Patricia; Haigh, Lois

This curriculum guide for nutrition education grade 3, was designed to incorporate knowledge of thirteen concepts into the child's decision-making processes as a food consumer. These concepts, as covered by the guide, are: affecting bodily well-being through nutrition; affecting dental health through nutrition; models for diet selection;…

Making Nutrition Education Count: A Guide for Nutrition Education K-6. Grade 1.

ERIC Educational Resources Information Center

Kratky, Patricia; Haigh, Lois

This curriculum guide for nutrition education grade 1, was designed to incorporate knowledge of thirteen concepts into the child's decision-making processes as a food consumer. These concepts, as covered by the guide, are: affecting bodily well-being through nutrition; affecting dental health through nutrition; models for diet selection;…

Making Nutrition Education Count: A Guide for Nutrition Education K-6. Grade 2.

ERIC Educational Resources Information Center

Kratky, Patricia; Haigh, Lois

This curriculum guide for nutrition education grade 2, was designed to incorporate knowledge of thirteen concepts into the child's decision-making processes as a food consumer. These concepts, as covered by the guide, are: affecting bodily well-being through nutrition; affecting dental health through nutrition; models for diet selection;…

Making Nutrition Education Count: A Guide for Nutrition Education K-6. Grade 4.

ERIC Educational Resources Information Center

Kratky, Patricia; Haigh, Lois

This curriculum guide for nutrition education grade 4, was designed to incorporate knowledge of thirteen concepts into the child's decision-making processes as a food consumer. These concepts, as covered by the guide, are: affecting bodily well-being through nutrition; affecting dental health through nutrition; models for diet selection;…

Making Nutrition Education Count: A Guide for Nutrition Education K-6. Grade 6.

ERIC Educational Resources Information Center

Kratky, Patricia; Haigh, Lois

This curriculum guide for nutrition education grade 6, was designed to incorporate knowledge of thirteen concepts into the child's decision-making processes as a food consumer. These concepts, as covered by the guide, are: affecting bodily well-being through nutrition; affecting dental health through nutrition; models for diet selection;…

Making Nutrition Education Count: A Guide for Nutrition Education K-6. Grade 5.

ERIC Educational Resources Information Center

Kratky, Patricia; Haigh, Lois

This curriculum guide for nutrition education grade 5, was designed to incorporate knowledge of thirteen concepts into the child's decision-making processes as a food consumer. These concepts, as covered by the guide, are: affecting bodily well-being through nutrition; affecting dental health through nutrition; models for diet selection;…

Modelling of auroral electrodynamical processes: Magnetosphere to mesosphere

NASA Technical Reports Server (NTRS)

Chiu, Y. T.; Gorney, D. J.; Kishi, A. M.; Newman, A. L.; Schulz, M.; Walterscheid, R. L.; CORNWALL; Prasad, S. S.

1982-01-01

Research conducted on auroral electrodynamic coupling between the magnetosphere and ionosphere-atmosphere in support of the development of a global scale kinetic plasma theory is reviewed. Topics covered include electric potential structure in the evening sector; morning and dayside auroras; auroral plasma formation; electrodynamic coupling with the thermosphere; and auroral electron interaction with the atmosphere.

Curricular Implications of Transition: Life Skills Instruction as an Integral Part of Transition Education.

ERIC Educational Resources Information Center

Patton, James R.; Cronin, Mary E.; Jairrels, Veda

1997-01-01

Discusses life skills instruction in the transition education of adolescents with disabilities. The relationship of life skills instruction to the transition process, curricular issues related to students with special needs, models for teaching life skills, options for covering life skills in the curriculum, and cultural considerations are…

Perspective of Lecturers in Implementing PISMP Science Curriculum in Malaysia's IPG

ERIC Educational Resources Information Center

Yahya, Fauziah Hj; Bin Hamdan, Abdul Rahim; Jantan, Hafsah Binti; Saleh, Halimatussadiah Binti

2015-01-01

The article aims to identify lecturers' perspectives in implementing PISMP science curriculum in IPG Malaysia based on teaching experience with KIPP model. The respondents consisted of 105 lecturers from 20 IPG Malaysia. The study used a questionnaire consisting of 74 items covering the four dimensions (Context, Input, Process and Product). Data…

Stochastic chemical kinetics : A review of the modelling and simulation approaches.

PubMed

Lecca, Paola

2013-12-01

A review of the physical principles that are the ground of the stochastic formulation of chemical kinetics is presented along with a survey of the algorithms currently used to simulate it. This review covers the main literature of the last decade and focuses on the mathematical models describing the characteristics and the behavior of systems of chemical reactions at the nano- and micro-scale. Advantages and limitations of the models are also discussed in the light of the more and more frequent use of these models and algorithms in modeling and simulating biochemical and even biological processes.

What Role for Humans in Global Land Cover Change over the Holocene? Insights from Models and Data

NASA Astrophysics Data System (ADS)

Kaplan, J. O.; Krumhardt, K. M.; Davis, B. A. S.; Zanon, M.

2014-12-01

Did humans affect global climate over the before the Industrial Era? While this question is hotly debated, the co-evolution of humans and the natural environment over the last 11,700 years had an undisputed role in influencing the development and present state of terrestrial ecosystems, many of which are highly valued today as economic, cultural, and ecological resources. Yet we still have a very incomplete picture of human-environment interactions over the Holocene. In order to address this, we combined a global dynamic vegetation model with a new model of preindustrial anthropogenic land cover change. We drive this integrated model a new synthesis of demographic, technological, and economic development over preindustrial time, and a database of historical urbanization covering the last 8000 years. We simulate natural vegetation and anthropogenic land use from 11,700 years before present to AD 1850 and compare these results with regional syntheses of pollen-based reconstructions of land cover. Our model results show that climate and tectonics controlled global land cover in the early Holocene. Shifts in forest biomes on the northern continents show an expansion of temperate tree types far to the north of their present day limits. By the early Iron Age (1000 BC), however, humans in Europe, East Asia, and Mesoamerica had a larger influence than natural processes on the landscape. Anthropogenic deforestation was widespread with most areas of temperate Europe and southwest Asia, east-central China, northern India, and Mesoamerica occupied by a matrix of natural vegetation, cropland and pastures. While we simulate fluctuations in human impact on the landscape, including periods of widespread land abandonment, e.g., during the Migration Period in Europe that following the end of the Western Roman Empire, approaching the Industrial Revolution nearly all of the landmasses of Europe and south and East Asia are dominated by anthropogenic activities. In contrast, the collapse of the aboriginal populations of the Americas following 15th century European contact leads to a period of ecosystem recovery. Initial comparisons with pollen-based land cover reconstructions in Europe suggest that the model is too late in simulating the first period of widespread deforestation, which occurs already during the Bronze Age (~2500 BC).

Coupling Processes between Atmospheric Chemistry and Climate

NASA Technical Reports Server (NTRS)

Ko, M. K. W.; Weisenstein, Debra; Shia, Run-Lie; Sze, N. D.

1998-01-01

This is the third semi-annual report for NAS5-97039, covering January through June 1998. The overall objective of this project is to improve the understanding of coupling processes between atmospheric chemistry and climate. Model predictions of the future distributions of trace gases in the atmosphere constitute an important component of the input necessary for quantitative assessments of global change. We will concentrate on the changes in ozone and stratospheric sulfate aerosol, with emphasis on how ozone in the lower stratosphere would respond to natural or anthropogenic changes. The key modeling for this work are the AER 2-dimensional chemistry-transport model, the AER 2-dimensional stratospheric sulfate model, and the AER three-wave interactive model with full chemistry. We will continue developing our three-wave model so that we can help NASA determine the strengths and weaknesses of the next generation assessment models.

Plasma Processes for Semiconductor Fabrication

NASA Astrophysics Data System (ADS)

Hitchon, W. N. G.

1999-01-01

Plasma processing is a central technique in the fabrication of semiconductor devices. This self-contained book provides an up-to-date description of plasma etching and deposition in semiconductor fabrication. It presents the basic physics and chemistry of these processes, and shows how they can be accurately modeled. The author begins with an overview of plasma reactors and discusses the various models for understanding plasma processes. He then covers plasma chemistry, addressing the effects of different chemicals on the features being etched. Having presented the relevant background material, he then describes in detail the modeling of complex plasma systems, with reference to experimental results. The book closes with a useful glossary of technical terms. No prior knowledge of plasma physics is assumed in the book. It contains many homework exercises and serves as an ideal introduction to plasma processing and technology for graduate students of electrical engineering and materials science. It will also be a useful reference for practicing engineers in the semiconductor industry.

The dominant role of climate change in determining changes in evapotranspiration in Xinjiang, China from 2001 to 2012

PubMed Central

Bai, Jie; Li, Longhui

2017-01-01

The Xinjiang Uyghur Autonomous Region of China has experienced significant land cover and climate change since the beginning of the 21st century. However, a reasonable simulation of evapotranspiration (ET) and its response to environmental factors are still unclear. For this study, to simulate ET and its response to climate and land cover change in Xinjiang, China from 2001 to 2012, we used the Common Land Model (CoLM) by adding irrigation effects for cropland and modifying root distributions and the root water uptake process for shrubland. Our results indicate that mean annual ET from 2001 to 2012 was 131.22 (±21.78) mm/year and demonstrated no significant trend (p = 0.12). The model simulation also indicates that climate change was capable of explaining 99% of inter-annual ET variability; land cover change only explained 1%. Land cover change caused by the expansion of croplands increased annual ET by 1.11 mm while climate change, mainly resulting from both decreased temperature and precipitation, reduced ET by 21.90 mm. Our results imply that climate change plays a dominant role in determining changes in ET, and also highlight the need for appropriate land-use strategies for managing water sources in dryland ecosystems within Xinjiang. PMID:28841645

The dominant role of climate change in determining changes in evapotranspiration in Xinjiang, China from 2001 to 2012.

PubMed

Yuan, Xiuliang; Bai, Jie; Li, Longhui; Kurban, Alishir; De Maeyer, Philippe

2017-01-01

The Xinjiang Uyghur Autonomous Region of China has experienced significant land cover and climate change since the beginning of the 21st century. However, a reasonable simulation of evapotranspiration (ET) and its response to environmental factors are still unclear. For this study, to simulate ET and its response to climate and land cover change in Xinjiang, China from 2001 to 2012, we used the Common Land Model (CoLM) by adding irrigation effects for cropland and modifying root distributions and the root water uptake process for shrubland. Our results indicate that mean annual ET from 2001 to 2012 was 131.22 (±21.78) mm/year and demonstrated no significant trend (p = 0.12). The model simulation also indicates that climate change was capable of explaining 99% of inter-annual ET variability; land cover change only explained 1%. Land cover change caused by the expansion of croplands increased annual ET by 1.11 mm while climate change, mainly resulting from both decreased temperature and precipitation, reduced ET by 21.90 mm. Our results imply that climate change plays a dominant role in determining changes in ET, and also highlight the need for appropriate land-use strategies for managing water sources in dryland ecosystems within Xinjiang.

Human-induced shifts in geomorphic process rates: An example of landslide activity following forest cover change.

NASA Astrophysics Data System (ADS)

Guns, Marie; Balthazar, Vincent; Vanacker, Veerle

2013-04-01

Mountain regions present unique challenges and opportunities to land use change research. Very few, if any, mountain ecosystems remain unaffected by human impact. Based on the exemplary evidence from local case studies, it is not yet possible to have an overall assessment of the extent and impact of human activities on mountain erosion as mountain regions are typically characterized by rapid changes in geomorphic, cryospheric, climatic, hydrologic, ecological and socio-economic conditions over relatively short distances. Here, we present a conceptual model that allows evaluating human-induced shifts in geomorphic process rates. The basic idea behind this model is that the magnitude-frequency distribution of geomorphic processes is dependent on the intensity of human disturbance. The conceptual model is here applied for characterising landslide activity following forest cover change. We selected a tropical Andean catchment with a deforestation rate of 1.4% over the last 45 years. Landslide inventories were established based on historical aerial photographs (1963, 1977, and 1989) and very high-resolution satellite images (2010). Statistical analyses show that the total number of landslides is rising, and that they are increasingly associated with human disturbances (deforestation, road construction). This is particularly the case for shallow landslides that become more frequent after clearcutting. As the human-induced shifts in landslide activity are significant for the low-magnitude events only, the total impact on geomorphic process rates is rather limited in this particular area. This work shows that including information on the magnitude-frequency of geomorphic events before, during and after human disturbances offers new possibilities to quantify the complex response of geomorphic processes to human disturbances.

Reconstruction of fire regimes through integrated paleoecological proxy data and ecological modeling.

PubMed

Iglesias, Virginia; Yospin, Gabriel I; Whitlock, Cathy

2014-01-01

Fire is a key ecological process affecting vegetation dynamics and land cover. The characteristic frequency, size, and intensity of fire are driven by interactions between top-down climate-driven and bottom-up fuel-related processes. Disentangling climatic from non-climatic drivers of past fire regimes is a grand challenge in Earth systems science, and a topic where both paleoecology and ecological modeling have made substantial contributions. In this manuscript, we (1) review the use of sedimentary charcoal as a fire proxy and the methods used in charcoal-based fire history reconstructions; (2) identify existing techniques for paleoecological modeling; and (3) evaluate opportunities for coupling of paleoecological and ecological modeling approaches to better understand the causes and consequences of past, present, and future fire activity.

Reconstruction of fire regimes through integrated paleoecological proxy data and ecological modeling

PubMed Central

Iglesias, Virginia; Yospin, Gabriel I.; Whitlock, Cathy

2015-01-01

Fire is a key ecological process affecting vegetation dynamics and land cover. The characteristic frequency, size, and intensity of fire are driven by interactions between top-down climate-driven and bottom-up fuel-related processes. Disentangling climatic from non-climatic drivers of past fire regimes is a grand challenge in Earth systems science, and a topic where both paleoecology and ecological modeling have made substantial contributions. In this manuscript, we (1) review the use of sedimentary charcoal as a fire proxy and the methods used in charcoal-based fire history reconstructions; (2) identify existing techniques for paleoecological modeling; and (3) evaluate opportunities for coupling of paleoecological and ecological modeling approaches to better understand the causes and consequences of past, present, and future fire activity. PMID:25657652

Modeling runoff and erosion risk in a~small steep cultivated watershed using different data sources: from on-site measurements to farmers' perceptions

NASA Astrophysics Data System (ADS)

Auvet, B.; Lidon, B.; Kartiwa, B.; Le Bissonnais, Y.; Poussin, J.-C.

2015-09-01

This paper presents an approach to model runoff and erosion risk in a context of data scarcity, whereas the majority of available models require large quantities of physical data that are frequently not accessible. To overcome this problem, our approach uses different sources of data, particularly on agricultural practices (tillage and land cover) and farmers' perceptions of runoff and erosion. The model was developed on a small (5 ha) cultivated watershed characterized by extreme conditions (slopes of up to 55 %, extreme rainfall events) on the Merapi volcano in Indonesia. Runoff was modelled using two versions of STREAM. First, a lumped version was used to determine the global parameters of the watershed. Second, a distributed version used three parameters for the production of runoff (slope, land cover and roughness), a precise DEM, and the position of waterways for runoff distribution. This information was derived from field observations and interviews with farmers. Both surface runoff models accurately reproduced runoff at the outlet. However, the distributed model (Nash-Sutcliffe = 0.94) was more accurate than the adjusted lumped model (N-S = 0.85), especially for the smallest and biggest runoff events, and produced accurate spatial distribution of runoff production and concentration. Different types of erosion processes (landslides, linear inter-ridge erosion, linear erosion in main waterways) were modelled as a combination of a hazard map (the spatial distribution of runoff/infiltration volume provided by the distributed model), and a susceptibility map combining slope, land cover and tillage, derived from in situ observations and interviews with farmers. Each erosion risk map gives a spatial representation of the different erosion processes including risk intensities and frequencies that were validated by the farmers and by in situ observations. Maps of erosion risk confirmed the impact of the concentration of runoff, the high susceptibility of long steep slopes, and revealed the critical role of tillage direction. Calibrating and validating models using in situ measurements, observations and farmers' perceptions made it possible to represent runoff and erosion risk despite the initial scarcity of hydrological data. Even if the models mainly provided orders of magnitude and qualitative information, they significantly improved our understanding of the watershed dynamics. In addition, the information produced by such models is easy for farmers to use to manage runoff and erosion by using appropriate agricultural practices.

Evaluation of the satellite derived snow cover area - Runoff forecasting models for the inaccessible basins of western Himalayas

NASA Technical Reports Server (NTRS)

Dey, B.

1985-01-01

In this study, the existing seasonal snow cover area runoff forecasting models of the Indus, Kabul, Sutlej and Chenab basins were evaluated with the concurrent flow correlation model for the period 1975-79. In all the basins under study, correlation of concurrent flow model explained the variability in flow better than by the snow cover area runoff models. Actually, the concurrent flow correlation model explained more than 90 percent of the variability in the flow of these rivers. Compared to this model, the snow cover area runoff models explained less of the variability in flow. In the Himalayan river basins under study and at least for the period under observation, the concurrent flow correlation model provided a set of results with which to compare the estimates from the snow cover area runoff models.

The Role of Laboratory-Based Studies of the Physical and Biological Properties of Sea Ice in Supporting the Observation and Modeling of Ice Covered Seas

NASA Astrophysics Data System (ADS)

Light, B.; Krembs, C.

2003-12-01

Laboratory-based studies of the physical and biological properties of sea ice are an essential link between high latitude field observations and existing numerical models. Such studies promote improved understanding of climatic variability and its impact on sea ice and the structure of ice-dependent marine ecosystems. Controlled laboratory experiments can help identify feedback mechanisms between physical and biological processes and their response to climate fluctuations. Climatically sensitive processes occurring between sea ice and the atmosphere and sea ice and the ocean determine surface radiative energy fluxes and the transfer of nutrients and mass across these boundaries. High temporally and spatially resolved analyses of sea ice under controlled environmental conditions lend insight to the physics that drive these transfer processes. Techniques such as optical probing, thin section photography, and microscopy can be used to conduct experiments on natural sea ice core samples and laboratory-grown ice. Such experiments yield insight on small scale processes from the microscopic to the meter scale and can be powerful interdisciplinary tools for education and model parameterization development. Examples of laboratory investigations by the authors include observation of the response of sea ice microstructure to changes in temperature, assessment of the relationships between ice structure and the partitioning of solar radiation by first-year sea ice covers, observation of pore evolution and interfacial structure, and quantification of the production and impact of microbial metabolic products on the mechanical, optical, and textural characteristics of sea ice.

Numerical Prediction of Dust. Chapter 10

NASA Technical Reports Server (NTRS)

Benedetti, Angela; Baldasano, J. M.; Basart, S.; Benincasa, F.; Boucher, O.; Brooks, M.; Chen, J. P.; Colarco, P. R.; Gong, S.; Huneeus, N.;

Satellite based assessment of recent permafrost extent and active layer trends over Alaska and Northwest Canada

NASA Astrophysics Data System (ADS)

Kim, Y.; Kimball, J. S.; PARK, H.; Yi, Y.

2017-12-01

Climate change in the Boreal-Arctic region has experienced greater surface air temperature (SAT) warming than the global average in recent decades, which is promoting permafrost thawing and active layer deepening. Permafrost extent (PE) and active layer thickness (ALT) are key environmental indicators of recent climate change, and strongly impact other eco-hydrological processes including land-atmosphere carbon exchange. We developed a new approach for regional estimation and monitoring of PE using daily landscape freeze-thaw (FT) records derived from satellite microwave (37 GHz) brightness temperature (Tb) observations. ALT was estimated within the PE domain using empirical modeling of land cover dependent edaphic factors and an annual thawing index derived from MODIS land surface temperature (LST) observations and reanalysis based surface air temperatures (SAT). The PE and ALT estimates were derived over the 1980-2016 satellite record and NASA ABoVE (Arctic Boreal Vulnerability Experiment) domain encompassing Alaska and Northwest Canada. The baseline model estimates were derived at 25-km resolution consistent with the satellite FT global record. Our results show recent widespread PE decline and deepening ALT trends, with larger spatial variability and model uncertainty along the southern PE boundary. Larger PE and ALT variability occurs over heterogeneous permafrost subzones characterized by dense vegetation, and variable snow cover and organic layer conditions. We also tested alternative PE and ALT estimates derived using finer (6-km) scale satellite Tb (36.5 GHz) and FT retrievals from a calibrated AMSR-E and AMSR2 sensor record. The PE and ALT results were compared against other independent observations, including process model simulations, in situ measurements, and permafrost inventory records. A model sensitivity analysis was conducted to evaluate snow cover, soil organic layer, and vegetation composition impacts to ALT. The finer delineation of permafrost and active layer conditions provides enhanced regional monitoring of PE and ALT changes over the ABoVE domain, including heterogeneous permafrost subzones.

Predicting Deforestation Patterns in Loreto, Peru from 2000-2010 Using a Nested GLM Approach

NASA Astrophysics Data System (ADS)

Vijay, V.; Jenkins, C.; Finer, M.; Pimm, S.

2013-12-01

Loreto is the largest province in Peru, covering about 370,000 km2. Because of its remote location in the Amazonian rainforest, it is also one of the most sparsely populated. Though a majority of the region remains covered by forest, deforestation is being driven by human encroachment through industrial activities and the spread of colonization and agriculture. The importance of accurate predictive modeling of deforestation has spawned an extensive body of literature on the topic. We present a nested GLM approach based on predictions of deforestation from 2000-2010 and using variables representing the expected drivers of deforestation. Models were constructed using 2000 to 2005 changes and tested against data for 2005 to 2010. The most complex model, which included transportation variables (roads and navigable rivers), spatial contagion processes, population centers and industrial activities, performed better in predicting the 2005 to 2010 changes (75.8% accurate) than did a simpler model using only transportation variables (69.2% accurate). Finally we contrast the GLM approach with a more complex spatially articulated model.

Processes driving rapid morphological changes observed on the Khumbu Glacier, Nepal

NASA Astrophysics Data System (ADS)

Quincey, Duncan; Rowan, Ann; Gibson, Morgan; Irvine-Fynn, Tristram; King, Owen; Watson, Scott

2016-04-01

The response of many Himalayan glaciers to climatic change is complicated by the presence of a supraglacial debris cover, which leads to a suite of processes controlling mass loss that are not commonly found where glaciers are debris-free. Here, we present a range of field, surface topographic and ice-dynamical observations acquired from Khumbu Glacier in Nepal, to describe and quantify these processes in fine spatial and temporal resolution. Like many other debris-covered glaciers in the Himalaya, the debris-covered tongue of the Khumbu Glacier is heavily in recession. For at least two decades, the lower ablation area has been stagnant as surface lowering in the mid-ablation zone has led to ever decreasing driving stresses. Contemporary velocity data derived from TerraSAR-X imagery confirms that the active-inactive ice boundary can now be found 5 km from the glacier terminus and that the maximum velocity, immediately below the icefall, is around 70 m per year. These data show that in this upper part of the ablation zone, the glacier velocity has not changed during the last 20 years, suggesting that at least above the icefall the glacier remains healthy. Across the stagnant debris-covered tongue there have been marked surface morphological changes. Mapping from 2004 shows relatively few surface ponds, a homogeneous debris-covered surface, and a small area towards the terminus supporting soil formation and low vegetation. Mapping from field observations in 2014 shows an abundance of surface meltwater, a more heterogeneous surface texture associated with many exposed ice cliffs, and a long (3 km) zone of stable terrain where soils are developing and, in places, low scrub can be found. Most dramatically, a string of surface ponds occupying the true-left lowermost 2 km of ice have expanded and coalesced, suggesting the glacier has crossed a threshold leading towards large glacial lake development. Two fine-resolution DEMs derived from Structure-from-Motion in spring 2014 and autumn 2015 elucidate the processes driving mass loss across the debris-covered area. Recession is greatest around surface meltwater ponds and in the upper part of the ablation area where debris cover is thinnest. Comparison with an historic DEM from 1984 shows the evolution of the glacier surface topography, which has become increasingly irregular because of the development of surface ponds and associated ice cliffs. These observations suggest a continuous cycle of relief inversion drives surface lowering across large areas of the debris-covered surface, and we propose a conceptual model to illustrate this cycle that is applicable to all receding debris-covered glaciers in the region.

Next generation of global land cover characterization, mapping, and monitoring

USGS Publications Warehouse

Giri, Chandra; Pengra, Bruce; Long, J.; Loveland, Thomas R.

2013-01-01

Land cover change is increasingly affecting the biophysics, biogeochemistry, and biogeography of the Earth's surface and the atmosphere, with far-reaching consequences to human well-being. However, our scientific understanding of the distribution and dynamics of land cover and land cover change (LCLCC) is limited. Previous global land cover assessments performed using coarse spatial resolution (300 m–1 km) satellite data did not provide enough thematic detail or change information for global change studies and for resource management. High resolution (∼30 m) land cover characterization and monitoring is needed that permits detection of land change at the scale of most human activity and offers the increased flexibility of environmental model parameterization needed for global change studies. However, there are a number of challenges to overcome before producing such data sets including unavailability of consistent global coverage of satellite data, sheer volume of data, unavailability of timely and accurate training and validation data, difficulties in preparing image mosaics, and high performance computing requirements. Integration of remote sensing and information technology is needed for process automation and high-performance computing needs. Recent developments in these areas have created an opportunity for operational high resolution land cover mapping, and monitoring of the world. Here, we report and discuss these advancements and opportunities in producing the next generations of global land cover characterization, mapping, and monitoring at 30-m spatial resolution primarily in the context of United States, Group on Earth Observations Global 30 m land cover initiative (UGLC).

Site-level model intercomparison of high latitude and high altitude soil thermal dynamics in tundra and barren landscapes

NASA Astrophysics Data System (ADS)

Ekici, A.; Chadburn, S.; Chaudhary, N.; Hajdu, L. H.; Marmy, A.; Peng, S.; Boike, J.; Burke, E.; Friend, A. D.; Hauck, C.; Krinner, G.; Langer, M.; Miller, P. A.; Beer, C.

2015-07-01

Modeling soil thermal dynamics at high latitudes and altitudes requires representations of physical processes such as snow insulation, soil freezing and thawing and subsurface conditions like soil water/ice content and soil texture. We have compared six different land models: JSBACH, ORCHIDEE, JULES, COUP, HYBRID8 and LPJ-GUESS, at four different sites with distinct cold region landscape types, to identify the importance of physical processes in capturing observed temperature dynamics in soils. The sites include alpine, high Arctic, wet polygonal tundra and non-permafrost Arctic, thus showing how a range of models can represent distinct soil temperature regimes. For all sites, snow insulation is of major importance for estimating topsoil conditions. However, soil physics is essential for the subsoil temperature dynamics and thus the active layer thicknesses. This analysis shows that land models need more realistic surface processes, such as detailed snow dynamics and moss cover with changing thickness and wetness, along with better representations of subsoil thermal dynamics.

LACO-Wiki: A land cover validation tool and a new, innovative teaching resource for remote sensing and the geosciences

NASA Astrophysics Data System (ADS)

See, Linda; Perger, Christoph; Dresel, Christopher; Hofer, Martin; Weichselbaum, Juergen; Mondel, Thomas; Steffen, Fritz

2016-04-01

The validation of land cover products is an important step in the workflow of generating a land cover map from remotely-sensed imagery. Many students of remote sensing will be given exercises on classifying a land cover map followed by the validation process. Many algorithms exist for classification, embedded within proprietary image processing software or increasingly as open source tools. However, there is little standardization for land cover validation, nor a set of open tools available for implementing this process. The LACO-Wiki tool was developed as a way of filling this gap, bringing together standardized land cover validation methods and workflows into a single portal. This includes the storage and management of land cover maps and validation data; step-by-step instructions to guide users through the validation process; sound sampling designs; an easy-to-use environment for validation sample interpretation; and the generation of accuracy reports based on the validation process. The tool was developed for a range of users including producers of land cover maps, researchers, teachers and students. The use of such a tool could be embedded within the curriculum of remote sensing courses at a university level but is simple enough for use by students aged 13-18. A beta version of the tool is available for testing at: http://www.laco-wiki.net.

Improving satellite-based PM2.5 estimates in China using Gaussian processes modeling in a Bayesian hierarchical setting.

PubMed

Yu, Wenxi; Liu, Yang; Ma, Zongwei; Bi, Jun

2017-08-01

Using satellite-based aerosol optical depth (AOD) measurements and statistical models to estimate ground-level PM 2.5 is a promising way to fill the areas that are not covered by ground PM 2.5 monitors. The statistical models used in previous studies are primarily Linear Mixed Effects (LME) and Geographically Weighted Regression (GWR) models. In this study, we developed a new regression model between PM 2.5 and AOD using Gaussian processes in a Bayesian hierarchical setting. Gaussian processes model the stochastic nature of the spatial random effects, where the mean surface and the covariance function is specified. The spatial stochastic process is incorporated under the Bayesian hierarchical framework to explain the variation of PM 2.5 concentrations together with other factors, such as AOD, spatial and non-spatial random effects. We evaluate the results of our model and compare them with those of other, conventional statistical models (GWR and LME) by within-sample model fitting and out-of-sample validation (cross validation, CV). The results show that our model possesses a CV result (R 2  = 0.81) that reflects higher accuracy than that of GWR and LME (0.74 and 0.48, respectively). Our results indicate that Gaussian process models have the potential to improve the accuracy of satellite-based PM 2.5 estimates.

Impact of wildfire-induced land cover modification on local meteorology: A sensitivity study of the 2003 wildfires in Portugal

NASA Astrophysics Data System (ADS)

Hernandez, Charles; Drobinski, Philippe; Turquety, Solène

2015-10-01

Wildfires alter land cover creating changes in dynamic, vegetative, radiative, thermal and hydrological properties of the surface. However, how so drastic changes induced by wildfires and how the age of the burnt scar affect the small and meso-scale atmospheric boundary layer dynamics are largely unknown. These questions are relevant for process analysis, meteorological and air quality forecast but also for regional climate analysis. Such questions are addressed numerically in this study on the case of the Portugal wildfires in 2003 as a testbed. In order to study the effects of burnt scars, an ensemble of numerical simulations using the Weather Research and Forecasting modeling system (WRF) have been performed with different surface properties mimicking the surface state immediately after the fire, few days after the fire and few months after the fire. In order to investigate such issue in a seamless approach, the same modelling framework has been used with various horizontal resolutions of the model grid and land use, ranging from 3.5 km, which can be considered as the typical resolution of state-of-the art regional numerical weather prediction models to 14 km which is now the typical target resolution of regional climate models. The study shows that the combination of high surface heat fluxes over the burnt area, large differential heating with respect to the preserved surroundings and lower surface roughness produces very intense frontogenesis with vertical velocity reaching few meters per second. This powerful meso-scale circulation can pump more humid air from the surroundings not impacted by the wildfire and produce more cloudiness over the burnt area. The influence of soil temperature immediately after the wildfire ceases is mainly seen at night as the boundary-layer remains unstably stratified and lasts only few days. So the intensity of the induced meso-scale circulation decreases with time, even though it remains until full recovery of the vegetation. Finally all these effects are simulated whatever the land cover and model resolution and there are thus robust processes in both regional climate simulations and process studies or short-time forecast. However, the impact of burnt scars on the precipitation signal remains very uncertain, especially because low precipitation is at stake.

The influences of land use and land cover on climate; an analysis of the Washington-Baltimore area that couples remote sensing with numerical simulation

USGS Publications Warehouse

Pease, R.W.; Jenner, C.B.; Lewis, J.E.

1980-01-01

The Sun drives the atmospheric heat engine by warming the terrestrial surface which in turn warms the atmosphere above. Climate, therefore, is significantly controlled by complex interaction of energy flows near and at the terrestrial surface. When man alters this delicate energy balance by his use of the land, he may alter his climatic environment as well. Land use climatology has emerged as a discipline in which these energy interactions are studied; first, by viewing the spatial distributions of their surface manifestations, and second, by analyzing the energy exchange processes involved. Two new tools for accomplishing this study are presented: one that can interpret surface energy exchange processes from space, and another that can simulate the complex of energy transfers by a numerical simulation model. Use of a satellite-borne multispectral scanner as an imaging radiometer was made feasible by devising a gray-window model that corrects measurements made in space for the effects of the atmosphere in the optical path. The simulation model is a combination of mathematical models of energy transfer processes at or near the surface. Integration of these two analytical approaches was applied to the Washington-Baltimore area to coincide with the August 5, 1973, Skylab 3 overpass which provided data for constructing maps of the energy characteristics of the Earth's surface. The use of the two techniques provides insights into the relationship of climate to land use and land cover and in predicting alterations of climate that may result from alterations of the land surface.

Snow-atmosphere coupling and its impact on temperature variability and extremes over North America

NASA Astrophysics Data System (ADS)

Diro, G. T.; Sushama, L.; Huziy, O.

2018-04-01

The impact of snow-atmosphere coupling on climate variability and extremes over North America is investigated using modeling experiments with the fifth generation Canadian Regional Climate Model (CRCM5). To this end, two CRCM5 simulations driven by ERA-Interim reanalysis for the 1981-2010 period are performed, where snow cover and depth are prescribed (uncoupled) in one simulation while they evolve interactively (coupled) during model integration in the second one. Results indicate systematic influence of snow cover and snow depth variability on the inter-annual variability of soil and air temperatures during winter and spring seasons. Inter-annual variability of air temperature is larger in the coupled simulation, with snow cover and depth variability accounting for 40-60% of winter temperature variability over the Mid-west, Northern Great Plains and over the Canadian Prairies. The contribution of snow variability reaches even more than 70% during spring and the regions of high snow-temperature coupling extend north of the boreal forests. The dominant process contributing to the snow-atmosphere coupling is the albedo effect in winter, while the hydrological effect controls the coupling in spring. Snow cover/depth variability at different locations is also found to affect extremes. For instance, variability of cold-spell characteristics is sensitive to snow cover/depth variation over the Mid-west and Northern Great Plains, whereas, warm-spell variability is sensitive to snow variation primarily in regions with climatologically extensive snow cover such as northeast Canada and the Rockies. Furthermore, snow-atmosphere interactions appear to have contributed to enhancing the number of cold spell days during the 2002 spring, which is the coldest recorded during the study period, by over 50%, over western North America. Additional results also provide useful information on the importance of the interactions of snow with large-scale mode of variability in modulating temperature extreme characteristics.

Quantitative assessment of desertification in south of Iran using MEDALUS method.

PubMed

Sepehr, A; Hassanli, A M; Ekhtesasi, M R; Jamali, J B

2007-11-01

The main aim of this study was the quantitative assessment of desertification process in the case study area of the Fidoye-Garmosht plain (Southern Iran). Based on the MEDALUS approach and the characteristics of study area a regional model developed using GIS. Six main factors or indicators of desertification including: soil, climate, erosion, plant cover, groundwater and management were considered for evaluation. Then several sub-indicators affecting the quality of each main indicator were identified. Based on the MEDALUS approach, each sub-indicator was quantified according to its quality and given a weighting of between 1.0 and 2.0. ArcGIS 9 was used to analyze and prepare the layers of quality maps using the geometric mean to integrate the individual sub-indicator maps. In turn the geometric mean of all six quality maps was used to generate a single desertification status map. Results showed that 12% of the area is classified as very severe, 81% as severe and 7% as moderately affected by desertification. In addition the plant cover and groundwater indicators were the most important factors affecting desertification process in the study area. The model developed may be used to assess desertification process and distinguish the areas sensitive to desertification in the study region and in regions with the similar characteristics.

Effects of Urbanization and Climate Change on Hydrological Processes over the San Antonio River Basin, Texas

NASA Astrophysics Data System (ADS)

Zhao, G.; Gao, H.; Cuo, L.

2014-12-01

With the rapid population growth and economic development in the State of Texas, a fast urbanization process has occurred over the past several decades. The direct consequences of the increased impervious area are greater surface runoff and higher flood peaks. Meanwhile, climate change has led to more frequent extreme events. Therefore, a thorough understanding of the hydrological processes under urbanization and climate change is indispensable for sustainable water management. In this investigation, a case study was conducted by applying the Distributed Hydrology Soil Vegetation Model (DHSVM) to the San Antonio River Basin (SARB), Texas. Hosting the seventh largest city in the U.S. (i.e., City of San Antonio), the SARB is vulnerable to both floods and droughts. A set of historical and future land cover maps were assembled to represent the urbanization process. Two forcing datasets were employed to drive the DHSVM model. The first is a long-term observation based dataset (1915-2011), which was used as inputs for calibrating and validating DHSVM, as well as evaluating the urbanization effect. The second is the statistically downscaled climate simulations (1950-2099) from the Coupled Model Intercomparison Project Phase 5 (CMIP5), which were applied for understanding impacts related to climate change. Results show that urbanization exerts a much larger influence on streamflow than climate change does. Under the same observed forcings, annual average streamflow increased from 993.0 cfs (with 1929 land cover) to 1777.7 cfs (with 2011 land cover). As for climate change, results suggest that it will exacerbate the drought severity — with reduced evapotranspiration and soil moisture caused by decreased precipitation. However, the projected future streamflow does not show a clear increasing or decreasing trend. Regarding the combined effect from urbanization and climate change, the results indicate that the seasonal streamflow pattern will be notably changed (i.e., streamflow in October will be significantly increased, which makes it a second flow peak in addition to May). Furthermore, with significantly decreased evapotranspiration and slightly increased soil moisture, more water will be available for streamflow, increasing the possibility of flood risk in the region.

The influence of multi-season imagery on models of canopy cover: A case study

Treesearch

John W. Coulston; Dennis M. Jacobs; Chris R. King; Ivey C. Elmore

2013-01-01

Quantifying tree canopy cover in a spatially explicit fashion is important for broad-scale monitoring of ecosystems and for management of natural resources. Researchers have developed empirical models of tree canopy cover to produce geospatial products. For subpixel models, percent tree canopy cover estimates (derived from fine-scale imagery) serve as the response...

Mapping and measuring land-cover characteristics of New River Basin, Tennessee, using Landsat digital tapes

USGS Publications Warehouse

Hollyday, E.F.; Sauer, S.P.

1976-01-01

Land-cover information is needed to select subbasins within the New River basin, Tennessee, for the study of hydrologic processes and also is needed to transfer study results to other sites affected by coal mining. It was believed that data recorded by the first Earth Resources Technology Satellite (Landsat-1) could be processed to yield the needed land-cover information. This study demonstrates that digital computer processing of the spectral information contained in each picture element (pixel) of 1.1 acres (4,500 m2) can produce maps and tables of the areal extent of selected land-cover categories.The distribution of water, rock, agricultural areas, evergreens, bare earth, hardwoods, and uncategorized areas, is portrayed on a map of the entire New River basin (1:62,500 scale) and on 15 quadrangles (1:24,000 scale). Although some categories are a mixture of land-cover types, they portray the predominant component named. Tables quantify the area of each category and indicate that agriculture covers 5 percent of the basin, evergreens cover 7 percent, bare earth covers 6 percent, three categories of hardwoods cover 81 percent, and water, rock, and uncategorized areas each cover less than 1 percent of the basin.

Modelling of temperature effects on removal efficiency and dissolved oxygen concentrations in stormwater ponds.

PubMed

German, J; Svensson, G; Gustafsson, L G; Vikström, M

2003-01-01

The performance of stormwater ponds, operated under winter conditions, was modelled using the commercial software Mike21 and MOUSE. Direct and indirect effects of changing temperature were investigated. The most important effect of winter conditions is the changed hydrology, characterised by long periods with no runoff followed by snowmelt events with large runoff volumes during several days. This gives lower removal efficiencies than during a period with the same precipitation but without winter conditions. For the concentration of dissolved oxygen, wind is an important factor. Consequently the most important effect of an ice cover on the pond is that it prevents the oxygenation effects of the wind. The direct temperature effects on the removal processes are negligible compared to the indirect effects in changed hydrology and forming of ice cover.

Supercritical fluid extraction. Principles and practice

DOE Office of Scientific and Technical Information (OSTI.GOV)

McHugh, M.A.; Krukonis, V.J.

This book is a presentation of the fundamentals and application of super-critical fluid solvents (SCF). The authors cover virtually every facet of SCF technology: the history of SCF extraction, its underlying thermodynamic principles, process principles, industrial applications, and analysis of SCF research and development efforts. The thermodynamic principles governing SCF extraction are covered in depth. The often complex three-dimensional pressure-temperature composition (PTx) phase diagrams for SCF-solute mixtures are constructed in a coherent step-by-step manner using the more familiar two-dimensional Px diagrams. The experimental techniques used to obtain high pressure phase behavior information are described in detail and the advantages andmore » disadvantages of each technique are explained. Finally, the equations used to model SCF-solute mixtures are developed, and modeling results are presented to highlight the correlational strengths of a cubic equation of state.« less

The Antarctic dry valley lakes: Relevance to Mars

NASA Technical Reports Server (NTRS)

Wharton, R. A., Jr.; Mckay, Christopher P.; Mancinelli, Rocco L.; Clow, G. D.; Simmons, G. M., Jr.

1989-01-01

The similarity of the early environments of Mars and Earth, and the biological evolution which occurred on early Earth, motivates exobiologists to seriously consider the possiblity of an early Martian biota. Environments are being identified which could contain Martian life and areas which may presently contain evidence of this former life. Sediments which were thought to be deposited in large ice-covered lakes are present on Mars. Such localities were identified within some of the canyons of the Valles Marineris and more recently in the ancient terrain in the Southern Hemisphere. Perennially ice-covered Antarctic lakes are being studied in order to develop quantitative models that relate environmental factors to the nature of the biological community and sediment forming processes. These models will be applied to the Martian paleolakes to establish the scientific rationale for the exobiological study of ancient Martian sediments.

Soil cover by natural trees in agroforestry systems

NASA Astrophysics Data System (ADS)

Diaz-Ambrona, C. G. H.; Almoguera Millán, C.; Tarquis Alfonso, A.

2009-04-01

The dehesa is common agroforestry system in the Iberian Peninsula. These open oak parklands with silvo-pastoral use cover about two million hectares. Traditionally annual pastures have been grazed by cows, sheep and also goats while acorns feed Iberian pig diet. Evergreen oak (Quercus ilex L.) has other uses as fuelwood collection and folder after tree pruning. The hypothesis of this work is that tree density and canopy depend on soil types. We using the spanish GIS called SIGPAC to download the images of dehesa in areas with different soil types. True colour images were restoring to a binary code, previously canopy colour range was selected. Soil cover by tree canopy was calculated and number of trees. Processing result was comparable to real data. With these data we have applied a dynamic simulation model Dehesa to determine evergreen oak acorn and annual pasture production. The model Dehesa is divided into five submodels: Climate, Soil, Evergreen oak, Pasture and Grazing. The first three require the inputs: (i) daily weather data (maximum and minimum temperatures, precipitation and solar radiation); (ii) the soil input parameters for three horizons (thickness, field capacity, permanent wilting point, and bulk density); and (iii) the tree characterization of the dehesa (tree density, canopy diameter and height, and diameter of the trunk). The influence of tree on pasture potential production is inversely proportional to the canopy cover. Acorn production increase with tree canopy cover until stabilizing itself, and will decrease if density becomes too high (more than 80% soil tree cover) at that point there is competition between the trees. Main driving force for dehesa productivity is soil type for pasture, and tree cover for acorn production. Highest pasture productivity was obtained on soil Dystric Planosol (Alfisol), Dystric Cambisol and Chromo-calcic-luvisol, these soils only cover 22.4% of southwest of the Iberian peninssula. Lowest productivity was obtained on Dystric Lithosol.

Soil Moisture and Snow Cover: Active or Passive Elements of Climate

NASA Technical Reports Server (NTRS)

Oglesby, Robert J.; Marshall, Susan; Erickson, David J., III; Robertson, Franklin R.; Roads, John O.; Arnold, James E. (Technical Monitor)

2002-01-01

A key question is the extent to which surface effects such as soil moisture and snow cover are simply passive elements or whether they can affect the evolution of climate on seasonal and longer time scales. We have constructed ensembles of predictability studies using the NCAR CCM3 in which we compared the relative roles of initial surface and atmospheric conditions over the central and western U.S. in determining the subsequent evolution of soil moisture and of snow cover. Results from simulations with realistic soil moisture anomalies indicate that internal climate variability may be the strongest factor, with some indication that the initial atmospheric state is also important. Model runs with exaggerated soil moisture reductions (near-desert conditions) showed a much larger effect, with warmer surface temperatures, reduced precipitation, and lower surface pressures; the latter indicating a response of the atmospheric circulation. These results suggest the possibility of a threshold effect in soil moisture, whereby an anomaly must be of a sufficient size before it can have a significant impact on the atmospheric circulation and climate. Results from simulations with realistic snow cover anomalies indicate that the time of year can be crucial. When introduced in late winter, these anomalies strongly affected the subsequent evolution of snow cover. When introduced in early winter, however, little or no effect is seen on the subsequent snow cover. Runs with greatly exaggerated initial snow cover indicate that the high reflectivity of snow is the most important process by which snow cover can impact climate, through lower surface temperatures and increased surface pressures. The results to date were obtained for model runs with present-day conditions. We are currently analyzing runs made with projected forcings for the 21st century to see if these results are modified in any way under likely scenarios of future climate change. An intriguing new statistical technique involving 'clustering' is developed to assist in this analysis.

Minimum forest cover required for sustainable water flow regulation of a watershed: a case study in Jambi Province, Indonesia

NASA Astrophysics Data System (ADS)

Tarigan, Suria; Wiegand, Kerstin; Sunarti; Slamet, Bejo

2018-01-01

In many tropical regions, the rapid expansion of monoculture plantations has led to a sharp decline in forest cover, potentially degrading the ability of watersheds to regulate water flow. Therefore, regional planners need to determine the minimum proportion of forest cover that is required to support adequate ecosystem services in these watersheds. However, to date, there has been little research on this issue, particularly in tropical areas where monoculture plantations are expanding at an alarming rate. Therefore, in this study, we investigated the influence of forest cover and oil palm (Elaeis guineensis) and rubber (Hevea brasiliensis) plantations on the partitioning of rainfall into direct runoff and subsurface flow in a humid, tropical watershed in Jambi Province, Indonesia. To do this, we simulated streamflow with a calibrated Soil and Water Assessment Tool (SWAT) model and observed several watersheds to derive the direct runoff coefficient (C) and baseflow index (BFI). The model had a strong performance, with Nash-Sutcliffe efficiency values of 0.80-0.88 (calibration) and 0.80-0.85 (validation) and percent bias values of -2.9-1.2 (calibration) and 7.0-11.9 (validation). We found that the percentage of forest cover in a watershed was significantly negatively correlated with C and significantly positively correlated with BFI, whereas the rubber and oil palm plantation cover showed the opposite pattern. Our findings also suggested that at least 30 % of the forest cover was required in the study area for sustainable ecosystem services. This study provides new adjusted crop parameter values for monoculture plantations, particularly those that control surface runoff and baseflow processes, and it also describes the quantitative association between forest cover and flow indicators in a watershed, which will help regional planners in determining the minimum proportion of forest and the maximum proportion of plantation to ensure that a watershed can provide adequate ecosystem services.

Linking laser scanning to snowpack modeling: Data processing and visualization

NASA Astrophysics Data System (ADS)

Teufelsbauer, H.

2009-07-01

SnowSim is a newly developed physical snowpack model that can use three-dimensional terrestrial laser scanning data to generate model domains. This greatly simplifies the input and numerical simulation of snow covers in complex terrains. The program can model two-dimensional cross sections of general slopes, with complicated snow distributions. The model predicts temperature distributions and snow settlements in this cross section. Thus, the model can be used for a wide range of problems in snow science and engineering, including numerical investigations of avalanche formation. The governing partial differential equations are solved by means of the finite element method, using triangular elements. All essential data for defining the boundary conditions and evaluating the simulation results are gathered by automatic weather and snow measurement sites. This work focuses on the treatment of these measurements and the simulation results, and presents a pre- and post-processing graphical user interface (GUI) programmed in Matlab.

Defining landscape resistance values in least-cost connectivity models for the invasive grey squirrel: a comparison of approaches using expert-opinion and habitat suitability modelling.

PubMed

Stevenson-Holt, Claire D; Watts, Kevin; Bellamy, Chloe C; Nevin, Owen T; Ramsey, Andrew D

2014-01-01

Least-cost models are widely used to study the functional connectivity of habitat within a varied landscape matrix. A critical step in the process is identifying resistance values for each land cover based upon the facilitating or impeding impact on species movement. Ideally resistance values would be parameterised with empirical data, but due to a shortage of such information, expert-opinion is often used. However, the use of expert-opinion is seen as subjective, human-centric and unreliable. This study derived resistance values from grey squirrel habitat suitability models (HSM) in order to compare the utility and validity of this approach with more traditional, expert-led methods. Models were built and tested with MaxEnt, using squirrel presence records and a categorical land cover map for Cumbria, UK. Predictions on the likelihood of squirrel occurrence within each land cover type were inverted, providing resistance values which were used to parameterise a least-cost model. The resulting habitat networks were measured and compared to those derived from a least-cost model built with previously collated information from experts. The expert-derived and HSM-inferred least-cost networks differ in precision. The HSM-informed networks were smaller and more fragmented because of the higher resistance values attributed to most habitats. These results are discussed in relation to the applicability of both approaches for conservation and management objectives, providing guidance to researchers and practitioners attempting to apply and interpret a least-cost approach to mapping ecological networks.

Effects of Land Use Land Cover (LULC) and Climate on Simulation of Phosphorus loading in the Southeast United States Region

NASA Astrophysics Data System (ADS)

Jima, T. G.; Roberts, A.

2013-12-01

Quality of coastal and freshwater resources in the Southeastern United States is threatened due to Eutrophication as a result of excessive nutrients, and phosphorus is acknowledged as one of the major limiting nutrients. In areas with much non-point source (NPS) pollution, land use land cover and climate have been found to have significant impact on water quality. Landscape metrics applied in catchment and riparian stream based nutrient export models are known to significantly improve nutrient prediction. The regional SPARROW (Spatially Referenced Regression On Watershed attributes), which predicts Total Phosphorus has been developed by the Southeastern United States regions USGS, as part of the National Water Quality Assessment (NAWQA) program and the model accuracy was found to be 67%. However, landscape composition and configuration metrics which play a significant role in the source, transport and delivery of the nutrient have not been incorporated in the model. Including these matrices in the models parameterization will improve the models accuracy and improve decision making process for mitigating and managing NPS phosphorus in the region. The National Land Cover Data 2001 raster data will be used (since the base line is 2002) for the region (with 8321 watersheds ) with fragstats 4.1 and ArcGIS Desktop 10.1 for the analysis of landscape matrices, buffers and creating map layers. The result will be imported to the Southeast SPARROW model and will be analyzed. Resulting statistical significance and model accuracy will be assessed and predictions for those areas with no water quality monitoring station will be made.

A Dynamic Simulation Model of Land-Use, Population, and Rural Livelihoods in the Central Rift Valley of Ethiopia

NASA Astrophysics Data System (ADS)

Garedew, Efrem; Sandewall, Mats; Soderberg, Ulf

2012-01-01

The dynamic interactions between society and land resources have to be taken into account when planning and managing natural resources. A computer model, using STELLA software, was developed through active participation of purposively selected farm households from different wealth groups, age groups and gender within a rural community and some members of Kebelle council. The aim of the modeling was to study the perceived changes in land-use, population and livelihoods over the next 30 years and to improve our understanding of the interactions among them. The modeling output is characterized by rapid population growth, declining farm size and household incomes, deteriorating woody vegetation cover and worsening land degradation if current conditions remain. However, through integrated intervention strategies (including forest increase, micro-finance, family planning, health and education) the woody vegetation cover is likely to increase in the landscape, population growth is likely to slow down and households' income is likely to improve. A validation assessment of the simulation model based on historical data on land-use and population from 1973 to 2006 showed that the model is relatively robust. We conclude that as a supporting tool, the simulation model can contribute to the decision making process.

Incorporation of the Mass Concentration and the New Snow Albedo Schemes into the Global Forecasting Model, GEOS-5 and the Impact of the New Schemes over Himalayan Glaciers

NASA Technical Reports Server (NTRS)

Yasunari, Teppei

2012-01-01

Recently the issue on glacier retreats comes up and many factors should be relevant to the issue. The absorbing aerosols such as dust and black carbon (BC) are considered to be one of the factors. After they deposited onto the snow surface, it will reduce snow albedo (called snow darkening effect) and probably contribute to further melting of glacier. The Goddard Earth Observing System version 5 (GEOS-5) has developed at NASA/GSFC. However, the original snowpack model used in the land surface model in the GEOS-5 did not consider the snow darkening effect. Here we developed the new snow albedo scheme which can consider the snow darkening effect. In addition, another scheme on calculating mass concentrations on the absorbing aerosols in snowpack was also developed, in which the direct aerosol depositions from the chemical transport model in the GEOS-5 were used. The scheme has been validated with the observed data obtained at backyard of the Institute of Low Temperature Science, Hokkaido University, by Dr. Teruo Aoki (Meteorological Research Institute) et aL including me. The observed data was obtained when I was Ph.D. candidate. The original GEOS-5during 2007-2009 over the Himalayas and Tibetan Plateau region showed more reductions of snow than that of the new GEOS-5 because the original one used lower albedo settings. On snow cover fraction, the new GEOS-5 simulated more realistic snow-covered area comparing to the MODIS snow cover fraction. The reductions on snow albedo, snow cover fraction, and snow water equivalent were seen with statistically significance if we consider the snow darkening effect comparing to the results without the snow darkening effect. In the real world, debris cover, inside refreezing process, surface flow of glacier, etc. affect glacier mass balance and the simulated results immediately do not affect whole glacier retreating. However, our results indicate that some surface melting over non debris covered parts of the glacier would be explained by the snow darkening effect. Further discussion and observations are necessary to assess the glacier issue.

Temporal expansion of annual crop classification layers for the CONUS using the C5 decision tree classifier

USGS Publications Warehouse

Friesz, Aaron M.; Wylie, Bruce K.; Howard, Daniel M.

2017-01-01

Crop cover maps have become widely used in a range of research applications. Multiple crop cover maps have been developed to suite particular research interests. The National Agricultural Statistics Service (NASS) Cropland Data Layers (CDL) are a series of commonly used crop cover maps for the conterminous United States (CONUS) that span from 2008 to 2013. In this investigation, we sought to contribute to the availability of consistent CONUS crop cover maps by extending temporal coverage of the NASS CDL archive back eight additional years to 2000 by creating annual NASS CDL-like crop cover maps derived from a classification tree model algorithm. We used over 11 million records to train a classification tree algorithm and develop a crop classification model (CCM). The model was used to create crop cover maps for the CONUS for years 2000–2013 at 250 m spatial resolution. The CCM and the maps for years 2008–2013 were assessed for accuracy relative to resampled NASS CDLs. The CCM performed well against a withheld test data set with a model prediction accuracy of over 90%. The assessment of the crop cover maps indicated that the model performed well spatially, placing crop cover pixels within their known domains; however, the model did show a bias towards the ‘Other’ crop cover class, which caused frequent misclassifications of pixels around the periphery of large crop cover patch clusters and of pixels that form small, sparsely dispersed crop cover patches.

Performance of a process-based hydrodynamic model in predicting shoreline change

NASA Astrophysics Data System (ADS)

Safak, I.; Warner, J. C.; List, J. H.

2012-12-01

Shoreline change is controlled by a complex combination of processes that include waves, currents, sediment characteristics and availability, geologic framework, human interventions, and sea level rise. A comprehensive data set of shoreline position (14 shorelines between 1978-2002) along the continuous and relatively non-interrupted North Carolina Coast from Oregon Inlet to Cape Hatteras (65 km) reveals a spatial pattern of alternating erosion and accretion, with an erosional average shoreline change rate of -1.6 m/yr and up to -8 m/yr in some locations. This data set gives a unique opportunity to study long-term shoreline change in an area hit by frequent storm events while relatively uninfluenced by human interventions and the effects of tidal inlets. Accurate predictions of long-term shoreline change may require a model that accurately resolves surf zone processes and sediment transport patterns. Conventional methods for predicting shoreline change such as one-line models and regression of shoreline positions have been designed for computational efficiency. These methods, however, not only have several underlying restrictions (validity for small angle of wave approach, assuming bottom contours and shoreline to be parallel, depth of closure, etc.) but also their empirical estimates of sediment transport rates in the surf zone have been shown to vary greatly from the calculations of process-based hydrodynamic models. We focus on hind-casting long-term shoreline change using components of the process-based, three-dimensional coupled-ocean-atmosphere-wave-sediment transport modeling system (COAWST). COAWST is forced with historical predictions of atmospheric and oceanographic data from public-domain global models. Through a method of coupled concurrent grid-refinement approach in COAWST, the finest grid with resolution of O(10 m) that covers the surf zone along the section of interest is forced at its spatial boundaries with waves and currents computed on the grids that cover the U.S. East Coast with resolutions as low as O(1 km). The computed patterns of the gradients of surf-zone integrated longshore sediment transport rates are compared with the observed shoreline change.

Comprehensive data set of global land cover change for land surface model applications

NASA Astrophysics Data System (ADS)

Sterling, Shannon; Ducharne, AgnèS.

2008-09-01

To increase our understanding of how humans have altered the Earth's surface and to facilitate land surface modeling experiments aimed to elucidate the direct impact of land cover change on the Earth system, we create and analyze a database of global land use/cover change (LUCC). From a combination of sources including satellite imagery and other remote sensing, ecological modeling, and country surveys, we adapt and synthesize existing maps of potential land cover and layers of the major anthropogenic land covers, including a layer of wetland loss, that are then tailored for land surface modeling studies. Our map database shows that anthropogenic land cover totals to approximately 40% of the Earth's surface, consistent with literature estimates. Almost all (92%) of the natural grassland on the Earth has been converted to human use, mostly grazing land, and the natural temperate savanna with mixed C3/C4 is almost completely lost (˜90%), due mostly to conversion to cropland. Yet the resultant change in functioning, in terms of plant functional types, of the Earth system from land cover change is dominated by a loss of tree cover. Finally, we identify need for standardization of percent bare soil for global land covers and for a global map of tree plantations. Estimates of land cover change are inherently uncertain, and these uncertainties propagate into modeling studies of the impact of land cover change on the Earth system; to begin to address this problem, modelers need to document fully areas of land cover change used in their studies.

Integration of UAV and ground-based Structure from Motion with Multi-View Stereo photogrammetry and hydrological data to quantify hillslope gully erosion processes in tropical savanna

NASA Astrophysics Data System (ADS)

Koci, J.; Jarihani, B.; Sidle, R. C.; Wilkinson, S. N.; Bartley, R.

2017-12-01

Structure from Motion with Multi-View Stereo (SfM-MVS) photogrammetry provides a cost-effective method of rapidly acquiring high resolution (sub-meter) topographic data, but is rarely used in hydrogeomorphic investigations of gully erosion. This study integrates high resolution topographic and land cover data derived from an unmanned aerial vehicle (UAV) and ground-based SfM-MVS photogrammetry, with rainfall and gully discharge data, to elucidate hydrogeomorphic processes driving hillslope gully erosion. The study is located within a small (13 km2) dry-tropical savanna catchment within the Burdekin River Basin, northeast Australia, which is a major contributor sediments and nutrients to the Great Barrier Reef World Heritage Area. A pre-wet season UAV survey covered an entire hillslope gully system (0.715 km2), and is used to derive topography, ground cover and hydrological flow pathways in the gully contributing area. Ground-based surveys of a single active gully (650 m2) within the broader hillslope are compared between pre- and post-wet season conditions to quantify gully geomorphic change. Rainfall, recorded near to the head of the gully, is related to gully discharge during sporadic storm events. The study provides valuable insights into the relationships among hydrological flow pathways, ground cover, rainfall and runoff, and spatial patterns of gully morphologic change. We demonstrate how UAV and ground-based SfM-MVS photogrammetry can be used to improve hydrogeomorphic process understanding and aid in the modelling and management of hillslope gully systems.

Characterizing soil moisture and snow cover effects on boreal-arctic soil freeze/thaw dynamics and cold-season carbon emissions

NASA Astrophysics Data System (ADS)

Yi, Y.; Kimball, J. S.; Moghaddam, M.; Chen, R. H.; Reichle, R. H.; Oechel, W. C.; Zona, D.

2017-12-01

The contribution of cold season respiration to boreal-arctic carbon cycle and its potential feedbacks to climate change remain poorly quantified. Here, we developed an integrated modeling framework combining airborne low frequency (L+P-band) airborne radar retrievals and landscape level (≥1km) environmental observations from satellite optical and microwave sensors with a detailed permafrost carbon model to investigate underlying processes controlling soil freeze/thaw (FT) dynamics and cold season carbon emissions. The permafrost carbon model simulates the snow and soil thermal dynamics with soil water phase change included and accounts for soil carbon decomposition up to 3m below surface. Local-scale ( 50m) radar retrievals of active layer thickness (ALT), soil moisture and freeze/thaw (FT) status from NASA airborne UAVSAR and AirMOSS sensors are used to inform the model parameterizations of soil moisture effects on soil FT dynamics, and scaling properties of active layer processes. Both tower observed land-atmosphere fluxes and atmospheric CO2 measurements are used to evaluate the model processes controlling cold season carbon respiration, particularly the effects of snow cover and soil moisture on deep soil carbon emissions during the early cold season. Initial comparisons showed that the model can well capture the seasonality of cold season respiration in both tundra and boreal forest areas, with large emissions in late fall and early winter and gradually diminishing throughout the winter. Model sensitivity analyses are used to clarify how changes in soil thermodynamics at depth control the magnitude and seasonality of cold season respiration, and how a deeper unfrozen active layer with warming may contribute to changes in cold season respiration. Model outputs include ALT and regional carbon fluxes at 1-km resolution spanning recent satellite era (2001-present) across Alaska. These results will be used to quantify cold season respiration contributions to the annual carbon cycle and help close the boreal-arctic annual carbon budget.

The Leadership Philosophy Model

DTIC Science & Technology

1989-03-31

34 leadership philosophy"? One writer states that it is a "distillation of experience and theory , arrived at through a long and somewhat tenuous process of... LEADERSHIP PHILOSOPHY MfODEL .11.9BY .IELJTEN 1NT CO)LONEL CLAYTON E. MELTO.; DIST-. jUTION STATEMIS.T A’ Approved for publiC relea~se; distributicrn...CATALOG NUMBER 4 TITLE (-d Subtitle) T YPE OF REPORT & PERIOD COvERE3 The Leadership Philosophy Model Study Project 6. PERFORMING ORG. REPORT N,.MBER 7

System-Wide Water Resources Program Nutrient Sub-Model (SWWRP-NSM) Version 1.1

DTIC Science & Technology

2008-09-01

species including crops, native grasses, and trees . The process descriptions utilize a single plant growth model to simulate all types of land covers...characteristics: • Multi- species , multi-phase, and multi-reaction system • Fast (equilibrium-based) and slow (non-equilibrium-based or rate- based...Transformation and loading of N and P species in the overland flow • Simulation of the N and P cycle in the water column (both overland and

Modeling pollution potential input from the drainage basin into Barra Bonita reservoir, São Paulo - Brazil.

PubMed

Prado, R B; Novo, E M L M

2015-05-01

In this study multi-criteria modeling tools are applied to map the spatial distribution of drainage basin potential to pollute Barra Bonita Reservoir, São Paulo State, Brasil. Barra Bonita Reservoir Basin had undergone intense land use/land cover changes in the last decades, including the fast conversion from pasture into sugarcane. In this respect, this study answers to the lack of information about the variables (criteria) which affect the pollution potential of the drainage basin by building a Geographic Information System which provides their spatial distribution at sub-basin level. The GIS was fed by several data (geomorphology, pedology, geology, drainage network and rainfall) provided by public agencies. Landsat satellite images provided land use/land cover map for 2002. Ratings and weights of each criterion defined by specialists supported the modeling process. The results showed a wide variability in the pollution potential of different sub-basins according to the application of different criterion. If only land use is analyzed, for instance, less than 50% of the basin is classified as highly threatening to water quality and include sub basins located near the reservoir, indicating the importance of protection areas at the margins. Despite the subjectivity involved in the weighing processes, the multi-criteria analysis model allowed the simulation of scenarios which support rational land use polices at sub-basin level regarding the protection of water resources.

Model estimation of land-use effects on water levels of northern Prairie wetlands

USGS Publications Warehouse

Voldseth, R.A.; Johnson, W.C.; Gilmanov, T.; Guntenspergen, G.R.; Millett, B.V.

2007-01-01

Wetlands of the Prairie Pothole Region exist in a matrix of grassland dominated by intensive pastoral and cultivation agriculture. Recent conservation management has emphasized the conversion of cultivated farmland and degraded pastures to intact grassland to improve upland nesting habitat. The consequences of changes in land-use cover that alter watershed processes have not been evaluated relative to their effect on the water budgets and vegetation dynamics of associated wetlands. We simulated the effect of upland agricultural practices on the water budget and vegetation of a semipermanent prairie wetland by modifying a previously published mathematical model (WETSIM). Watershed cover/land-use practices were categorized as unmanaged grassland (native grass, smooth brome), managed grassland (moderately heavily grazed, prescribed burned), cultivated crops (row crop, small grain), and alfalfa hayland. Model simulations showed that differing rates of evapotranspiration and runoff associated with different upland plant-cover categories in the surrounding catchment produced differences in wetland water budgets and linked ecological dynamics. Wetland water levels were highest and vegetation the most dynamic under the managed-grassland simulations, while water levels were the lowest and vegetation the least dynamic under the unmanaged-grassland simulations. The modeling results suggest that unmanaged grassland, often planted for waterfowl nesting, may produce the least favorable wetland conditions for birds, especially in drier regions of the Prairie Pothole Region. These results stand as hypotheses that urgently need to be verified with empirical data.

Operational applications of satellite snowcover observations in Rio Grande drainage of Colorado

NASA Technical Reports Server (NTRS)

Washicheck, J. N.; Mikesell, T.

1975-01-01

Various mapping techniques were tried and evaluated. There were many problems encountered such as distinquishing clouds from snow and snow under trees. A partial solution to some of the problems involves ground reconnaissance and low air flights. Snow areas, cloud cover, and total areas were planimetered after transferring imagery by use of zoom transfer scope. These determinations were then compared to areas determined by use of a density slicer. Considerable adjustment is required for these two values to compare. NOAA pictures were also utilized in the evaluation. Forest cover is one of the parameters used in the modeling process. The determination of this percentage is being explored.

Quantifying the indirect impacts of climate on agriculture: an inter-method comparison

DOE PAGES

Calvin, Kate; Fisher-Vanden, Karen

2017-10-27

Climate change and increases in CO2 concentration affect the productivity of land, with implications for land use, land cover, and agricultural production. Much of the literature on the effect of climate on agriculture has focused on linking projections of changes in climate to process-based or statistical crop models. However, the changes in productivity have broader economic implications that cannot be quantified in crop models alone. How important are these socio-economic feedbacks to a comprehensive assessment of the impacts of climate change on agriculture? In this paper, we attempt to measure the importance of these interaction effects through an inter-method comparisonmore » between process models, statistical models, and integrated assessment model (IAMs). We find the impacts on crop yields vary widely between these three modeling approaches. Yield impacts generated by the IAMs are 20%-40% higher than the yield impacts generated by process-based or statistical crop models, with indirect climate effects adjusting yields by between - 12% and + 15% (e.g. input substitution and crop switching). The remaining effects are due to technological change.« less

Quantifying the indirect impacts of climate on agriculture: an inter-method comparison

NASA Astrophysics Data System (ADS)

Calvin, Kate; Fisher-Vanden, Karen

2017-11-01

Climate change and increases in CO2 concentration affect the productivity of land, with implications for land use, land cover, and agricultural production. Much of the literature on the effect of climate on agriculture has focused on linking projections of changes in climate to process-based or statistical crop models. However, the changes in productivity have broader economic implications that cannot be quantified in crop models alone. How important are these socio-economic feedbacks to a comprehensive assessment of the impacts of climate change on agriculture? In this paper, we attempt to measure the importance of these interaction effects through an inter-method comparison between process models, statistical models, and integrated assessment model (IAMs). We find the impacts on crop yields vary widely between these three modeling approaches. Yield impacts generated by the IAMs are 20%-40% higher than the yield impacts generated by process-based or statistical crop models, with indirect climate effects adjusting yields by between -12% and +15% (e.g. input substitution and crop switching). The remaining effects are due to technological change.

Quantifying the indirect impacts of climate on agriculture: an inter-method comparison

DOE Office of Scientific and Technical Information (OSTI.GOV)

Calvin, Kate; Fisher-Vanden, Karen

Climate change and increases in CO2 concentration affect the productivity of land, with implications for land use, land cover, and agricultural production. Much of the literature on the effect of climate on agriculture has focused on linking projections of changes in climate to process-based or statistical crop models. However, the changes in productivity have broader economic implications that cannot be quantified in crop models alone. How important are these socio-economic feedbacks to a comprehensive assessment of the impacts of climate change on agriculture? In this paper, we attempt to measure the importance of these interaction effects through an inter-method comparisonmore » between process models, statistical models, and integrated assessment model (IAMs). We find the impacts on crop yields vary widely between these three modeling approaches. Yield impacts generated by the IAMs are 20%-40% higher than the yield impacts generated by process-based or statistical crop models, with indirect climate effects adjusting yields by between - 12% and + 15% (e.g. input substitution and crop switching). The remaining effects are due to technological change.« less

A Tutorial for Building CMMI Process Performance Models

DTIC Science & Technology

2010-04-26

70 90 120 1 0~-----0~----~ 2 Arch itecture/ Design All New Code M ajor Reuse of Code 55 70 90 8 10 15 2 0~-----0~----~ 3 Code All New Code M ajor...Robert Stoddard and Dave Zubrow © 2010 Carnegie Mellon University t "’ ·=··=· "’ •• ,. ...... ,. .... ~ .00 1 Arch [’ <si!JI ~h~;,...o ’ .. CodeChoice...Carnegie Mellon University : • Fit Model It; b][g~ El Model Select Columns 41111Delivered0efect; 411111nspection0 efect ..ollllnspectionCover

A National Disturbance Modeling System to Support Ecological Carbon Sequestration Assessments

NASA Astrophysics Data System (ADS)

Hawbaker, T. J.; Rollins, M. G.; Volegmann, J. E.; Shi, H.; Sohl, T. L.

2009-12-01

The U.S. Geological Survey (USGS) is prototyping a methodology to fulfill requirements of Section 712 of the Energy Independence and Security Act (EISA) of 2007. At the core of the EISA requirements is the development of a methodology to complete a two-year assessment of current carbon stocks and other greenhouse gas (GHG) fluxes, and potential increases for ecological carbon sequestration under a range of future climate changes, land-use / land-cover configurations, and policy, economic and management scenarios. Disturbances, especially fire, affect vegetation dynamics and ecosystem processes, and can also introduce substantial uncertainty and risk to the efficacy of long-term carbon sequestration strategies. Thus, the potential impacts of disturbances need to be considered under different scenarios. As part of USGS efforts to meet EISA requirements, we developed the National Disturbance Modeling System (NDMS) using a series of statistical and process-based simulation models. NDMS produces spatially-explicit forecasts of future disturbance locations and severity, and the resulting effects on vegetation dynamics. NDMS is embedded within the Forecasting Scenarios of Future Land Cover (FORE-SCE) model and informs the General Ensemble Biogeochemical Modeling System (GEMS) for quantifying carbon stocks and GHG fluxes. For fires, NDMS relies on existing disturbance histories, such as the Landsat derived Monitoring Trends in Burn Severity (MTBS) and Vegetation Change Tracker (VCT) data being used to update LANDFIRE fuels data. The MTBS and VCT data are used to parameterize models predicting the number and size of fires in relation to climate, land-use/land-cover change, and socioeconomic variables. The locations of individual fire ignitions are determined by an ignition probability surface and then FARSITE is used to simulate fire spread in response to weather, fuels, and topography. Following the fire spread simulations, a burn severity model is used to determine annual changes in biomass pools. Vegetation succession among LANDFIRE vegetation types is initiated using burn perimeter and severity data at the end of each annual simulation. Results from NDMS are used to update land-use/land-cover layers used by FORE-SCE and also transferred to GEMS for quantifying and updating carbon stocks and greenhouse gas fluxes. In this presentation, we present: 1) an overview of NDMS and its role in USGS's national ecological carbon sequestration assessment; 2) validation of NDMS using historic data; and 3) initial forecasts of disturbances for the southeastern United States and their impacts on greenhouse gas emissions, and post-fire carbon stocks and fluxes.

Soil cover patterns and SOC dynamics impacts on the soil processes, land management and ecosystem services in Central Region of Russia

NASA Astrophysics Data System (ADS)

Vasenev, Ivan; Chernikov, Vladimir; Yashin, Ivan; Geraskin, Mikhail; Morev, Dmitriy

2014-05-01

In the Central Region of Russia (CRR) the soil cover patterns usually play the very important role in the soil forming and degradation processes (SFP & SDP) potential and current rates, soil organic carbon (SOC) dynamics and pools, greenhouse gases (GHG) emissions and soluble SOC fluxes that we need take into attention for better assessment of the natural and especially man-changed ecosystems' services and for best land-use practices development. Central Region of Russia is the biggest one in RF according to its population and role in the economy. CRR is characterized by high spatial variability of soil cover due to as original landscape heterogeneity as complicated history of land-use practices during last 700 years. Our long-term researches include the wide zonal-provincial set of representative ecosystems and soil cover patterns with different types and history of land-use (forest, meadow-steppe and agricultural ones) from middle-taiga to steppe zones with different level of continentality. The carried out more than 30-years region- and local-scale researches of representative natural and rural landscapes in Tver', Yaroslavl', Kaluga, Moscow, Vladimir, Saransk (Mordovia), Kursk, Orel, Tambov, Voronezh and Saratov oblasts give us the interregional multi-factorial matrix of elementary soil cover patterns (ESCP) with different soil forming and degradation processes rates and soil organic carbon dynamics due to regionally specific soil-geomorphologic features, environmental and dominated microclimate conditions, land-use current practices and history. The validation and ranging of the limiting factors of SFP and SDP develop¬ment, soil carbon dynamics and sequestration potential, ecosystem (agroecosystem) principal services, land functional qualities and agroecological state have been done for dominating and most dynamical components of ESCP regional-typological forms - with application of SOC structure analysis, regional and local GIS, soil spatial patterns detail mapping, traditional regression kriging, correlation tree models and DSS adapted to concrete region and agrolandscape conditions. The outcomes of statistical process modeling show the essential amplification of erosion, dehumification, CO2, CH4 and N2O emission, soluble SOC fluxes, acidification or alkalization, disaggregation and overcompaction processes due to violation of environmentally sound land-use systems and traditional balances of organic matter, nutrients, Ca and Na in agrolandscapes. Due to long-term intensive and out-of-balance land-use practices the most zonal soils and soil cover pattern essentially lost not only their unique natural features (humus horizons depth till 1 m and more in case of Chernozems, 2-6 % of SOC and favorable agrophysical features), but ecosystem services and ecological functions including terrestrial ecosystem carbon balance and the GHG fluxes control. Key-site monitoring results and regional generalized data showed 1-1.5% SOC lost during last 50 years period and active processes of CO2 emission and humus profile eluvial-illuvial redistribution too. A drop of Corg content below threshold "humus limiting content" values (for different soils they vary from 1 to 3-4% of SOC) considerably reduces effectiveness of used fertilizers and possibility of sustai¬nable agronomy here. Forest-steppe Chernozems are usually characterized by higher stability than steppe ones. The ratio between erosive and biological losses in humus supplies can be ten-tatively estimated as fifty-fifty with strong spatial variability due to slope and land-use parameters. These processes have essentially different sets of environmental consequences and ecosystem services that we need to understand in frame of environmental and agroecological problems development prediction.

Modelling multi-rotor UAVs swarm deployment using virtual pheromones

PubMed Central

Pujol, Mar; Rizo, Ramón; Rizo, Carlos

2018-01-01

In this work, a swarm behaviour for multi-rotor Unmanned Aerial Vehicles (UAVs) deployment will be presented. The main contribution of this behaviour is the use of a virtual device for quantitative sematectonic stigmergy providing more adaptable behaviours in complex environments. It is a fault tolerant highly robust behaviour that does not require prior information of the area to be covered, or to assume the existence of any kind of information signals (GPS, mobile communication networks …), taking into account the specific features of UAVs. This behaviour will be oriented towards emergency tasks. Their main goal will be to cover an area of the environment for later creating an ad-hoc communication network, that can be used to establish communications inside this zone. Although there are several papers on robotic deployment it is more difficult to find applications with UAV systems, mainly because of the existence of various problems that must be overcome including limitations in available sensory and on-board processing capabilities and low flight endurance. In addition, those behaviours designed for UAVs often have significant limitations on their ability to be used in real tasks, because they assume specific features, not easily applicable in a general way. Firstly, in this article the characteristics of the simulation environment will be presented. Secondly, a microscopic model for deployment and creation of ad-hoc networks, that implicitly includes stigmergy features, will be shown. Then, the overall swarm behaviour will be modeled, providing a macroscopic model of this behaviour. This model can accurately predict the number of agents needed to cover an area as well as the time required for the deployment process. An experimental analysis through simulation will be carried out in order to verify our models. In this analysis the influence of both the complexity of the environment and the stigmergy system will be discussed, given the data obtained in the simulation. In addition, the macroscopic and microscopic models will be compared verifying the number of predicted individuals for each state regarding the simulation. PMID:29370203

Towards a high resolution, integrated hydrology model of North America.

NASA Astrophysics Data System (ADS)

Maxwell, R. M.; Condon, L. E.

2015-12-01

Recent studies demonstrate feedbacks between groundwater dynamics, overland flow, land surface and vegetation processes, and atmospheric boundary layer development that significantly affect local and regional climate across a range of climatic conditions. Furthermore, the type and distribution of vegetation cover alters land-atmosphere water and energy fluxes, as well as runoff generation and overland flow processes. These interactions can result in significant feedbacks on local and regional climate. In mountainous regions, recent research has shown that spatial and temporal variability in annual evapotranspiration, and thus water budgets, is strongly dependent on lateral groundwater flow; however, the full effects of these feedbacks across varied terrain (e.g. from plains to mountains) are not well understood. Here, we present a high-resolution, integrated hydrology model that covers much of continental North America and encompasses the Mississippi and Colorado watersheds. The model is run in a fully-transient manner at hourly temporal resolution incorporating fully-coupled land energy states and fluxes with integrated surface and subsurface hydrology. Connections are seen between hydrologic variables (such as water table depth) and land energy fluxes (such as latent heat) and spatial and temporal scaling is shown to span many orders of magnitude. Using these transient simulations as a proof of concept, we present a vision for future integrated simulation capabilities.

IDSE Version 1 User's Manual

NASA Technical Reports Server (NTRS)

Mayer, Richard

1988-01-01

The integrated development support environment (IDSE) is a suite of integrated software tools that provide intelligent support for information modelling. These tools assist in function, information, and process modeling. Additional tools exist to assist in gathering and analyzing information to be modeled. This is a user's guide to application of the IDSE. Sections covering the requirements and design of each of the tools are presented. There are currently three integrated computer aided manufacturing definition (IDEF) modeling methodologies: IDEF0, IDEF1, and IDEF2. Also, four appendices exist to describe hardware and software requirements, installation procedures, and basic hardware usage.

Modelling and control of a diffusion/LPCVD furnace

NASA Astrophysics Data System (ADS)

Dewaard, H.; Dekoning, W. L.

1988-12-01

Heat transfer inside a cylindrical resistance diffusion/Low Pressure Chemical Vapor Deposition (LPCVD) furnace is studied with the aim of developing an improved temperature controller. A model of the thermal behavior is derived, which covers the important class of furnaces equipped with semitransparent quartz process tubes. The model takes into account the thermal behavior of the thermocouples. Currently used temperature controllers are shown to be highly inefficient for very large scale integration applications. Based on the model an alternative temperature controller of the LQG (linear quadratic Gaussian) type is proposed which features direct wafer temperature control. Some simulation results are given.

A combined disease management and process modeling approach for assessing and improving care processes: a fall management case-study.

PubMed

Askari, Marjan; Westerhof, Richard; Eslami, Saied; Medlock, Stephanie; de Rooij, Sophia E; Abu-Hanna, Ameen

2013-10-01

To propose a combined disease management and process modeling approach for evaluating and improving care processes, and demonstrate its usability and usefulness in a real-world fall management case study. We identified essential disease management related concepts and mapped them into explicit questions meant to expose areas for improvement in the respective care processes. We applied the disease management oriented questions to a process model of a comprehensive real world fall prevention and treatment program covering primary and secondary care. We relied on interviews and observations to complete the process models, which were captured in UML activity diagrams. A preliminary evaluation of the usability of our approach by gauging the experience of the modeler and an external validator was conducted, and the usefulness of the method was evaluated by gathering feedback from stakeholders at an invitational conference of 75 attendees. The process model of the fall management program was organized around the clinical tasks of case finding, risk profiling, decision making, coordination and interventions. Applying the disease management questions to the process models exposed weaknesses in the process including: absence of program ownership, under-detection of falls in primary care, and lack of efficient communication among stakeholders due to missing awareness about other stakeholders' workflow. The modelers experienced the approach as usable and the attendees of the invitational conference found the analysis results to be valid. The proposed disease management view of process modeling was usable and useful for systematically identifying areas of improvement in a fall management program. Although specifically applied to fall management, we believe our case study is characteristic of various disease management settings, suggesting the wider applicability of the approach. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Simulating the influence of snow surface processes on soil moisture dynamics and streamflow generation in an alpine catchment

NASA Astrophysics Data System (ADS)

Wever, Nander; Comola, Francesco; Bavay, Mathias; Lehning, Michael

2017-08-01

The assessment of flood risks in alpine, snow-covered catchments requires an understanding of the linkage between the snow cover, soil and discharge in the stream network. Here, we apply the comprehensive, distributed model Alpine3D to investigate the role of soil moisture in the predisposition of the Dischma catchment in Switzerland to high flows from rainfall and snowmelt. The recently updated soil module of the physics-based multilayer snow cover model SNOWPACK, which solves the surface energy and mass balance in Alpine3D, is verified against soil moisture measurements at seven sites and various depths inside and in close proximity to the Dischma catchment. Measurements and simulations in such terrain are difficult and consequently, soil moisture was simulated with varying degrees of success. Differences between simulated and measured soil moisture mainly arise from an overestimation of soil freezing and an absence of a groundwater description in the Alpine3D model. Both were found to have an influence in the soil moisture measurements. Using the Alpine3D simulation as the surface scheme for a spatially explicit hydrologic response model using a travel time distribution approach for interflow and baseflow, streamflow simulations were performed for the discharge from the catchment. The streamflow simulations provided a closer agreement with observed streamflow when driving the hydrologic response model with soil water fluxes at 30 cm depth in the Alpine3D model. Performance decreased when using the 2 cm soil water flux, thereby mostly ignoring soil processes. This illustrates that the role of soil moisture is important to take into account when understanding the relationship between both snowpack runoff and rainfall and catchment discharge in high alpine terrain. However, using the soil water flux at 60 cm depth to drive the hydrologic response model also decreased its performance, indicating that an optimal soil depth to include in surface simulations exists and that the runoff dynamics are controlled by only a shallow soil layer. Runoff coefficients (i.e. ratio of rainfall over discharge) based on measurements for high rainfall and snowmelt events were found to be dependent on the simulated initial soil moisture state at the onset of an event, further illustrating the important role of soil moisture for the hydrological processes in the catchment. The runoff coefficients using simulated discharge were found to reproduce this dependency, which shows that the Alpine3D model framework can be successfully applied to assess the predisposition of the catchment to flood risks from both snowmelt and rainfall events.

Soil Moisture and Snow Cover: Active or Passive Elements of Climate?

NASA Technical Reports Server (NTRS)

Oglesby, Robert J.; Marshall, Susan; Erickson, David J., III; Robertson, Franklin R.; Roads, John O.; Arnold, James E. (Technical Monitor)

2002-01-01

A key question in the study of the hydrologic cycle is the extent to which surface effects such as soil moisture and snow cover are simply passive elements or whether they can affect the evolution of climate on seasonal and longer time scales. We have constructed ensembles of predictability studies using the NCAR CCM3 in which we compared the relative roles of initial surface and atmospheric conditions over the central and western U.S. in determining the subsequent evolution of soil moisture and of snow cover. We have also made sensitivity studies with exaggerated soil moisture and snow cover anomalies in order to determine the physical processes that may be important. Results from simulations with realistic soil moisture anomalies indicate that internal climate variability may be the strongest factor, with some indication that the initial atmospheric state is also important. The initial state of soil moisture does not appear important, a result that held whether simulations were started in late winter or late spring. Model runs with exaggerated soil moisture reductions (near-desert conditions) showed a much larger effect, with warmer surface temperatures, reduced precipitation, and lower surface pressures; the latter indicating a response of the atmospheric circulation. These results suggest the possibility of a threshold effect in soil moisture, whereby an anomaly must be of a sufficient size before it can have a significant impact on the atmospheric circulation and hence climate. Results from simulations with realistic snow cover anomalies indicate that the time of year can be crucial. When introduced in late winter, these anomalies strongly affected the subsequent evolution of snow cover. When introduced in early winter, however, little or no effect is seen on the subsequent snow cover. Runs with greatly exaggerated initial snow cover indicate that the high reflectively of snow is the most important process by which snow cover cart impact climate, through lower surface temperatures and increased surface pressures. In early winter, the amount of solar radiation is very small and so this albedo effect is inconsequential while in late winter, with the sun higher in the sky and period of daylight longer, the effect is much stronger.

Forest cover of North America in the 1970s mapped using Landsat MSS data

NASA Astrophysics Data System (ADS)

Feng, M.; Sexton, J. O.; Channan, S.; Townshend, J. R.

2015-12-01

The distribution and changes in Earth's forests impact hydrological, biogeochemical, and energy fluxes, as well as ecosystems' capacity to support biodiversity and human economies. Long-term records of forest cover are needed across a broad range of investigation, including climate and carbon-cycle modeling, hydrological studies, habitat analyzes, biological conservation, and land-use planning. Satellite-based observations enable mapping and monitoring of forests at ecologically and economically relevant resolutions and continental or even global extents. Following early forest-mapping efforts using coarser resolution remote sensing data such as the Advanced Very High Resolution Radiometer (AVHRR) and MODerate-resolution Imaging Spectroradiometer (MODIS), forests have been mapped regionally at < 100-m resolution using Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+). These "Landsat-class" sensors offer precise calibration, but they provide observations only over the past three decades—a relatively short period for delineating the long-term changes of forests. Starting in 1971, the Multispectral Scanner (MSS) was the first generation of sensors aboard the Landsat satellites. MSS thus provides a unique resource to extend observations by at least a decade longer in history than records based on Landsat TM and ETM+. Leveraging more recent Landsat-based forest-cover products developed by the Global Land Cover Facility (GLCF) as reference, we developed an automated approach to detect forests using MSS data by leveraging the multispectral and phenological characteristics of forests observed in MSS time-series. The forest-cover map is produced with layers representing the year of observation, detection of forest-cover change relative to 1990, and the uncertainty of forest-cover and -change layers. The approach has been implemented with open-source libraries to facilitate processing large volumes of Landsat MSS images on high-performance computing machines. As the first result of our global mapping effort, we present the forest cover for North America. More than 25,000 Landsat MSS scenes were processed to provide a 120-meter resolution forest cover for North America, which will be made publicly available on the GLCF website (http://www.landcover.org).

Effects of future climate conditions on terrestrial export from coastal southern California

NASA Astrophysics Data System (ADS)

Feng, D.; Zhao, Y.; Raoufi, R.; Beighley, E.; Melack, J. M.

2015-12-01

The Santa Barbara Coastal - Long Term Ecological Research Project (SBC-LTER) is focused on investigating the relative importance of land and ocean processes in structuring giant kelp forest ecosystems. Understanding how current and future climate conditions influence terrestrial export is a central theme for the project. Here we combine the Hillslope River Routing (HRR) model and daily precipitation and temperature downscaled using statistical downscaling based on localized constructed Analogs (LOCA) to estimate recent streamflow dynamics (2000 to 2014) and future conditions (2015 to 2100). The HRR model covers the SBC-LTER watersheds from just west of the Ventura River to Point Conception; a land area of roughly 800 km2 with 179 watersheds ranging from 0.1 to 123 km2. The downscaled climate conditions have a spatial resolution of 6 km by 6 km. Here, we use the Penman-Monteith method with the Food and Agriculture Organization of the United Nations (FAO) limited climate data approximations and land surface conditions (albedo, leaf area index, land cover) measured from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua satellites to estimate potential evapotranspiration (PET). The HRR model is calibrated for the period 2000 to 2014 using USGS and LTER streamflow. An automated calibration technique is used. For future climate scenarios, we use mean 8-day land cover conditions. Future streamflow, ET and soil moisture statistics are presented and based on downscaled P and T from ten climate model projections from the Coupled Model Intercomparison Project Phase 5 (CMIP5).

Modeled change in carbon balance between 1970-2100 of a polygonal arctic tundra ecosystem near Barrow, Alaska

NASA Astrophysics Data System (ADS)

Lara, M. J.; McGuire, A. D.; Euskirchen, E. S.; Sloan, V. L.; Iversen, C. M.; Norby, R. J.; Genet, H.; Zhang, Y.; Yuan, F.

2013-12-01

Northern permafrost regions are estimated to cover 16% of the global soil area and account for approximately 50% of the global belowground organic carbon pool. However, there are considerable uncertainties regarding the fate of this soil carbon pool with projected climate warming over the next century. In northern Alaska, nearly 65% of the terrestrial surface is composed of polygonal tundra, where microtopographic position (i.e. high center, low center, trough) varies surface hydrology, plant community composition, and biogeochemical cycling, over small (<5m) spatial scales. Due to large spatial heterogeneity and other non-linear responses of soil carbon to altered thermal regime, it is difficult to accurately estimate the fate of terrestrial carbon balance over decadal time-scales without explicitly considering the dynamically coupled processes driving permafrost dynamics, community structure, and ecosystem function. We use a new version of the terrestrial ecosystem model (TEM), which couples a dynamic vegetation and dynamic organic soil model (DVM-DOS-TEM). This large-scale ecosystem model is designed to study interactions among carbon and nitrogen cycling, vegetation composition, and soil physical properties, including permafrost and active layer dynamics. The model is parameterized and calibrated using data specific to the local climate, vegetation, and soils within various polygon land cover types (i.e. high center & rim, low center, trough) collected from sites (71.28°N 156.60° W) on the arctic coastal plain near Barrow, Alaska to estimate the likely change in carbon balance between 1970 and 2100 in this landscape. Model outputs are scaled across the Barrow Peninsula using the distribution of polygonal tundra land cover types, described by a land cover classification of 26.9 km2, using a 2008 multi-spectral QuickBird satellite image. The polygonal tundra land cover classification found high center & rims to represent 37.5% of the study area, low centers 19.7%, troughs 9.9%, water bodies (i.e. lakes, ponds, rivers) 17.8%, and non-polygonal tundra (i.e. drainage terraces & graminoid meadows) 15.1%, respectively. The overall accuracy of the map was 86%, based on 250 ground control points, and the Kappa coefficient was 0.77. Preliminary model runs for this region indicated variability in response to specific polygonal tundra land cover type through time. Overall, results suggest that it is important to consider discrete polygonal tundra features in regional estimates of carbon balance in northern Alaska.

Exploring dust emission responses to land cover change using an ecological land classification

NASA Astrophysics Data System (ADS)

Galloza, Magda S.; Webb, Nicholas P.; Bleiweiss, Max P.; Winters, Craig; Herrick, Jeffrey E.; Ayers, Eldon

2018-06-01

Despite efforts to quantify the impacts of land cover change on wind erosion, assessment uncertainty remains large. We address this uncertainty by evaluating the application of ecological site concepts and state-and-transition models (STMs) for detecting and quantitatively describing the impacts of land cover change on wind erosion. We apply a dust emission model over a rangeland study area in the northern Chihuahuan Desert, New Mexico, USA, and evaluate spatiotemporal patterns of modelled horizontal sediment mass flux and dust emission in the context of ecological sites and their vegetation states; representing a diversity of land cover types. Our results demonstrate how the impacts of land cover change on dust emission can be quantified, compared across land cover classes, and interpreted in the context of an ecological model that encapsulates land management intensity and change. Results also reveal the importance of established weaknesses in the dust model soil characterisation and drag partition scheme, which appeared generally insensitive to the impacts of land cover change. New models that address these weaknesses, coupled with ecological site concepts and field measurements across land cover types, could significantly reduce assessment uncertainties and provide opportunities for identifying land management options.

Vegetation canopy cover effects on sediment erosion processes in the upper Colorado River Basin mancos shale formation, Price, Utah

USDA-ARS?s Scientific Manuscript database

This study provides new parameterizations for applying the Rangeland Hydrology and Erosion Model (RHEM) on the highly erosive, rangeland saline soils of the Mancos Shale formation in the Price-San Rafael River Basin in east central Utah. Calibrated hydrologic parameters (Kss and K') values are gener...

Exploring a New Model for Preprint Server: A Case Study of CSPO

ERIC Educational Resources Information Center

Hu, Changping; Zhang, Yaokun; Chen, Guo

2010-01-01

This paper describes the introduction of an open-access preprint server in China covering 43 disciplines. The system includes mandatory deposit for state-funded research and reports on the repository and its effectiveness and outlines a novel process of peer-review of preprints in the repository, which can be incorporated into the established…

Role of Individual Learning Pathways in Non-Threatening Teaching and Learning Environment Development

ERIC Educational Resources Information Center

Makarova, Elena A.

2014-01-01

The paper covers a diverse range of topics, the areas of interest for this particular paper include (a) knowledge structures and mental models, (b) problem solving processes, (c) metacognition, (d) skill acquisition, (e) individual learning styles, and (f) transfer of learning. The following brief synopsis of the paper serves to illustrate the…

A Data Warehouse Model for Micro-Level Decision Making in Higher Education

ERIC Educational Resources Information Center

van Dyk, Liezl

2008-01-01

An abundance of research, by educational researchers and scholars of teaching and learning alike, can be found on the use of ICT to plan design and deliver learning activities and assessment activities. The first steps of the instructional design process are covered quite thoroughly by this. However, the use of ICT and quantitative methods to…

Anopheles fauna of coastal Cayenne, French Guiana: modelling and mapping of species presence using remotely sensed land cover data.

PubMed

Adde, Antoine; Dusfour, Isabelle; Roux, Emmanuel; Girod, Romain; Briolant, Sébastien

2016-12-01

Little is known about the Anopheles species of the coastal areas of French Guiana, or their spatiotemporal distribution or environmental determinants. The present study aimed to (1) document the distribution of Anopheles fauna in the coastal area around Cayenne, and (2) investigate the use of remotely sensed land cover data as proxies of Anopheles presence. To characterise the Anopheles fauna, we combined the findings of two entomological surveys that were conducted during the period 2007-2009 and in 2014 at 37 sites. Satellite imagery data were processed to extract land cover variables potentially related to Anopheles ecology. Based on these data, a methodology was formed to estimate a statistical predictive model of the spatial-seasonal variations in the presence of Anopheles in the Cayenne region. Two Anopheles species, known as main malaria vectors in South America, were identified, including the more dominant An. aquasalis near town and rural sites, and An. darlingi only found in inland sites. Furthermore, a cross-validated model of An. aquasalis presence that integrated marsh and forest surface area was extrapolated to generate predictive maps. The present study supports the use of satellite imagery by health authorities for the surveillance of malaria vectors and planning of control strategies.

Investigating the impact of land cover change on peak river flow in UK upland peat catchments, based on modelled scenarios

NASA Astrophysics Data System (ADS)

Gao, Jihui; Holden, Joseph; Kirkby, Mike

2014-05-01

Changes to land cover can influence the velocity of overland flow. In headwater peatlands, saturation means that overland flow is a dominant source of runoff, particularly during heavy rainfall events. Human modifications in headwater peatlands may include removal of vegetation (e.g. by erosion processes, fire, pollution, overgrazing) or pro-active revegetation of peat with sedges such as Eriophorum or mosses such as Sphagnum. How these modifications affect the river flow, and in particular the flood peak, in headwater peatlands is a key problem for land management. In particular, the impact of the spatial distribution of land cover change (e.g. different locations and sizes of land cover change area) on river flow is not clear. In this presentation a new fully distributed version of TOPMODEL, which represents the effects of distributed land cover change on river discharge, was employed to investigate land cover change impacts in three UK upland peat catchments (Trout Beck in the North Pennines, the Wye in mid-Wales and the East Dart in southwest England). Land cover scenarios with three typical land covers (i.e. Eriophorum, Sphagnum and bare peat) having different surface roughness in upland peatlands were designed for these catchments to investigate land cover impacts on river flow through simulation runs of the distributed model. As a result of hypothesis testing three land cover principles emerged from the work as follows: Principle (1): Well vegetated buffer strips are important for reducing flow peaks. A wider bare peat strip nearer to the river channel gives a higher flow peak and reduces the delay to peak; conversely, a wider buffer strip with higher density vegetation (e.g. Sphagnum) leads to a lower peak and postpones the peak. In both cases, a narrower buffer strip surrounding upstream and downstream channels has a greater effect than a thicker buffer strip just based around the downstream river network. Principle (2): When the area of change is equal, the size of land cover change patches has no effect on river flow for patch sizes up to 40000m2. Principle (3): Bare peat on gentle slopes gives a faster flow response and higher peak value at the catchment outlet, while high density vegetation or re-vegetation on a gentle slope area has larger positive impact on peak river flow delay when compared with the same practices on steeper slopes. These simple principles should be useful to planners who wish to determine resource efficiency and optimisation for peatland protection and restoration works in headwater systems. If practitioners require further detail on impacts of specific spatial changes to land cover in a catchment then this modelling approach can be applied to new catchments of concern.

Assessing uncertainties in land cover projections.

PubMed

Alexander, Peter; Prestele, Reinhard; Verburg, Peter H; Arneth, Almut; Baranzelli, Claudia; Batista E Silva, Filipe; Brown, Calum; Butler, Adam; Calvin, Katherine; Dendoncker, Nicolas; Doelman, Jonathan C; Dunford, Robert; Engström, Kerstin; Eitelberg, David; Fujimori, Shinichiro; Harrison, Paula A; Hasegawa, Tomoko; Havlik, Petr; Holzhauer, Sascha; Humpenöder, Florian; Jacobs-Crisioni, Chris; Jain, Atul K; Krisztin, Tamás; Kyle, Page; Lavalle, Carlo; Lenton, Tim; Liu, Jiayi; Meiyappan, Prasanth; Popp, Alexander; Powell, Tom; Sands, Ronald D; Schaldach, Rüdiger; Stehfest, Elke; Steinbuks, Jevgenijs; Tabeau, Andrzej; van Meijl, Hans; Wise, Marshall A; Rounsevell, Mark D A

2017-02-01

Understanding uncertainties in land cover projections is critical to investigating land-based climate mitigation policies, assessing the potential of climate adaptation strategies and quantifying the impacts of land cover change on the climate system. Here, we identify and quantify uncertainties in global and European land cover projections over a diverse range of model types and scenarios, extending the analysis beyond the agro-economic models included in previous comparisons. The results from 75 simulations over 18 models are analysed and show a large range in land cover area projections, with the highest variability occurring in future cropland areas. We demonstrate systematic differences in land cover areas associated with the characteristics of the modelling approach, which is at least as great as the differences attributed to the scenario variations. The results lead us to conclude that a higher degree of uncertainty exists in land use projections than currently included in climate or earth system projections. To account for land use uncertainty, it is recommended to use a diverse set of models and approaches when assessing the potential impacts of land cover change on future climate. Additionally, further work is needed to better understand the assumptions driving land use model results and reveal the causes of uncertainty in more depth, to help reduce model uncertainty and improve the projections of land cover. © 2016 John Wiley & Sons Ltd.

Exploring Land Use and Land Cover Change and Feedbacks in the Global Change Assessment Model

NASA Astrophysics Data System (ADS)

Chen, M.; Vernon, C. R.; Huang, M.; Calvin, K. V.; Le Page, Y.; Kraucunas, I.

2017-12-01

Land Use and Land Cover Change (LULCC) is a major driver of global and regional environmental change. Projections of land use change are thus an essential component in Integrated Assessment Models (IAMs) to study feedbacks between transformation of energy systems and land productivity under the context of climate change. However, the spatial scale of IAMs, e.g., the Global Change Assessment Model (GCAM), is typically larger than the scale of terrestrial processes in the human-Earth system, LULCC downscaling therefore becomes a critical linkage among these multi-scale and multi-sector processes. Parametric uncertainties in LULCC downscaling algorithms, however, have been under explored, especially in the context of how such uncertainties could propagate to affect energy systems in a changing climate. In this study, we use a LULCC downscaling model, Demeter, to downscale GCAM-based future land use scenarios into fine spatial scales, and explore the sensitivity of downscaled land allocations to key parameters. Land productivity estimates (e.g., biomass production and crop yield) based on the downscaled LULCC scenarios are then fed to GCAM to evaluate how energy systems might change due to altered water and carbon cycle dynamics and their interactions with the human system, , which would in turn affect future land use projections. We demonstrate that uncertainties in LULCC downscaling can result in significant differences in simulated scenarios, indicating the importance of quantifying parametric uncertainties in LULCC downscaling models for integrated assessment studies.

Meteorological Modeling of Wintertime Cold Air Pool Stagnation Episodes in the Uintah and Salt Lake Basins

NASA Astrophysics Data System (ADS)

Crosman, E.; Horel, J.; Blaylock, B. K.; Foster, C.

2014-12-01

High wintertime ozone concentrations in rural areas associated with oil and gas development and high particulate concentrations in urban areas have become topics of increasing concern in the Western United States, as both primary and secondary pollutants become trapped within stable wintertime boundary layers. While persistent cold air pools that enable such poor wintertime air quality are typically associated with high pressure aloft and light winds, the complex physical processes that contribute to the formation, maintenance, and decay of persistent wintertime temperature inversions are only partially understood. In addition, obtaining sufficiently accurate numerical weather forecasts and meteorological simulations of cold air pools for input into chemical models remains a challenge. This study examines the meteorological processes associated with several wintertime pollution episodes in Utah's Uintah and Salt Lake Basins using numerical Weather Research and Forecasting model simulations and observations collected from the Persistent Cold Air Pool and Uintah Basin Ozone Studies. The temperature, vertical structure, and winds within these cold air pools was found to vary as a function of snow cover, snow albedo, land use, cloud cover, large-scale synoptic flow, and episode duration. We evaluate the sensitivity of key atmospheric features such as stability, planetary boundary layer depth, local wind flow patterns and transport mechanisms to variations in surface forcing, clouds, and synoptic flow. Finally, noted deficiencies in the meteorological models of cold air pools and modifications to the model snow and microphysics treatment that have resulted in improved cold pool simulations will be presented.

Assessing Climatic Impacts due to Land Use Change over Southeast Asian Maritime Continent base on Mesoscale Model Simulations

NASA Astrophysics Data System (ADS)

Feng, N.; Christopher, S. A.; Nair, U. S.

2014-12-01

Due to increasing urbanization, deforestation, and agriculture, land use change over Southeast Asia has dramatically risen during the last decades. Large areas of peat swamp forests over the Southeast Asian Maritime Continent region (10°S~20°N and 90°E~135°E) have been cleared for agricultural purposes. The Center for Remote Imaging, Sensing and Processing (CRISP) Moderate Resolution Imaging Spectroradiometer (MODIS) derived land cover classification data show that changes in land use are dominated by conversion of peat swamp forests to oil palm plantation, open lowland or lowland mosaic categories. Nested grid simulations based on Weather Research Forecasting Version 3.6 modelling system (WRFV3.6) over the central region of the Sarawak coast are used to investigate the climatic impacts of land use change over Maritime Continent. Numerical simulations were conducted for August of 2009 for satellite derived land cover scenarios for years 2000 and 2010. The variations in cloud formation, precipitation, and regional radiative and non-radiative parameters on climate results from land use change have been assessed based on numerical simulation results. Modelling studies demonstrate that land use change such as extensive deforestation processes can produce a negative radiative forcing due to the surface albedo increase and evapotranspiration decrease, while also largely caused reduced rainfall and cloud formation, and enhanced shortwave radiative forcing and temperature over the study area. Land use and land cover changes, similar to the domain in this study, has also occurred over other regions in Southeast Asia including Indonesia and could also impact cloud and precipitation formation in these regions.

Sojourning with the Homogeneous Poisson Process.

PubMed

Liu, Piaomu; Peña, Edsel A

2016-01-01

In this pedagogical article, distributional properties, some surprising, pertaining to the homogeneous Poisson process (HPP), when observed over a possibly random window, are presented. Properties of the gap-time that covered the termination time and the correlations among gap-times of the observed events are obtained. Inference procedures, such as estimation and model validation, based on event occurrence data over the observation window, are also presented. We envision that through the results in this paper, a better appreciation of the subtleties involved in the modeling and analysis of recurrent events data will ensue, since the HPP is arguably one of the simplest among recurrent event models. In addition, the use of the theorem of total probability, Bayes theorem, the iterated rules of expectation, variance and covariance, and the renewal equation could be illustrative when teaching distribution theory, mathematical statistics, and stochastic processes at both the undergraduate and graduate levels. This article is targeted towards both instructors and students.