Orion Crew Member Injury Predictions during Land and Water Landings

NASA Technical Reports Server (NTRS)

Lawrence, Charles; Littell, Justin D.; Fasanella, Edwin L.; Tabiei, Ala

2008-01-01

A review of astronaut whole body impact tolerance is discussed for land or water landings of the next generation manned space capsule named Orion. LS-DYNA simulations of Orion capsule landings are performed to produce a low, moderate, and high probability of injury. The paper evaluates finite element (FE) seat and occupant simulations for assessing injury risk for the Orion crew and compares these simulations to whole body injury models commonly referred to as the Brinkley criteria. The FE seat and crash dummy models allow for varying the occupant restraint systems, cushion materials, side constraints, flailing of limbs, and detailed seat/occupant interactions to minimize landing injuries to the crew. The FE crash test dummies used in conjunction with the Brinkley criteria provides a useful set of tools for predicting potential crew injuries during vehicle landings.

RCP4.5: A Pathway for Stabilization of Radiative Forcing by 2100

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

Thomson, Allison M.; Calvin, Katherine V.; Smith, Steven J.

2011-07-29

Representative Concentration Pathway (RCP) 4.5 is a scenario that stabilizes radiative forcing at 4.5 W m{sup -2} in the year 2100 without ever exceeding that value. Simulated with the Global Change Assessment Model (GCAM), RCP4.5 includes long-term, global emissions of greenhouse gases, short-lived species, and land-use-land-cover in a global economic framework. RCP4.5 was updated from earlier GCAM scenarios to incorporate historical emissions and land cover information common to the RCP process and follows a cost-minimizing pathway to reach the target radiative forcing. The imperative to limit emissions in order to reach this target drives changes in the energy system, includingmore » shifts to electricity, to lower emissions energy technologies and to the deployment of carbon capture and geologic storage technology. In addition, the RCP4.5 emissions price also applies to land use emissions; as a result, forest lands expand from their present day extent. The simulated future emissions and land use were downscaled from the regional simulation to a grid to facilitate transfer to climate models. While there are many alternative pathways to achieve a radiative forcing level of 4.5 W m{sup -2}, the application of the RCP4.5 provides a common platform for climate models to explore the climate system response to stabilizing the anthropogenic components of radiative forcing.« less

An economic and life cycle analysis of regional land use and transportation plans [research brief].

DOT National Transportation Integrated Search

2012-06-01

Travel and emissions models are commonly applied to evaluate the change in passenger and commercial travel and associated greenhouse gas (GHG) emissions from land use and transportation plans. Analyses conducted by the Sacramento Area Council of Gove...

Model Meets Data: Challenges and Opportunities to Implement Land Management in Earth System Models

NASA Astrophysics Data System (ADS)

Pongratz, J.; Dolman, A. J.; Don, A.; Erb, K. H.; Fuchs, R.; Herold, M.; Jones, C.; Luyssaert, S.; Kuemmerle, T.; Meyfroidt, P.

2016-12-01

Land-based demand for food and fibre is projected to increase in the future. In light of global sustainability challenges only part of this increase will be met by expansion of land use into relatively untouched regions. Additional demand will have to be fulfilled by intensification and other adjustments in management of land that already is under agricultural and forestry use. Such land management today occurs on about half of the ice-free land surface, as compared to only about one quarter that has undergone a change in land cover. As the number of studies revealing substantial biogeophysical and biogeochemical effects of land management is increasing, moving beyond land cover change towards including land management has become a key focus for Earth system modeling. However, a basis for prioritizing land management activities for implementation in models is lacking. We lay this basis for prioritization in a collaborative project across the disciplines of Earth system modeling, land system science, and Earth observation. We first assess the status and plans of implementing land management in Earth system and dynamic global vegetation models. A clear trend towards higher complexity of land use representation is visible. We then assess five criteria for prioritizing the implementation of land management activities: (1) spatial extent, (2) evidence for substantial effects on the Earth system, (3) process understanding, (4) possibility to link the management activity to existing concepts and structures of models, (5) availability of data required as model input. While the first three criteria have been assessed by an earlier study for ten common management activities, we review strategies for implementation in models and the availability of required datasets. We can thus evaluate the management activities for their performance in terms of importance for the Earth system, possibility of technical implementation in models, and data availability. This synthesis reveals some "low-hanging" fruits for model implementation, but also challenges for the assessment of land management effects by modeling. The identified gaps can guide prioritization within the data community from the Earth system and Earth system modeling perspective.

Model meets data: Challenges and opportunities to implement land management in Earth System Models

NASA Astrophysics Data System (ADS)

Pongratz, Julia; Dolman, Han; Don, Axel; Erb, Karl-Heinz; Fuchs, Richard; Herold, Martin; Jones, Chris; Luyssaert, Sebastiaan; Kuemmerle, Tobias; Meyfroidt, Patrick; Naudts, Kim

2017-04-01

Land-based demand for food and fibre is projected to increase in the future. In light of global sustainability challenges only part of this increase will be met by expansion of land use into relatively untouched regions. Additional demand will have to be fulfilled by intensification and other adjustments in management of land that already is under agricultural and forestry use. Such land management today occurs on about half of the ice-free land surface, as compared to only about one quarter that has undergone a change in land cover. As the number of studies revealing substantial biogeophysical and biogeochemical effects of land management is increasing, moving beyond land cover change towards including land management has become a key focus for Earth system modeling. However, a basis for prioritizing land management activities for implementation in models is lacking. We lay this basis for prioritization in a collaborative project across the disciplines of Earth system modeling, land system science, and Earth observation. We first assess the status and plans of implementing land management in Earth system and dynamic global vegetation models. A clear trend towards higher complexity of land use representation is visible. We then assess five criteria for prioritizing the implementation of land management activities: (1) spatial extent, (2) evidence for substantial effects on the Earth system, (3) process understanding, (4) possibility to link the management activity to existing concepts and structures of models, (5) availability of data required as model input. While the first three criteria have been assessed by an earlier study for ten common management activities, we review strategies for implementation in models and the availability of required datasets. We can thus evaluate the management activities for their performance in terms of importance for the Earth system, possibility of technical implementation in models, and data availability. This synthesis reveals some "low-hanging" fruits for model implementation, but also challenges for the assessment of land management effects by modeling. The identified gaps can guide prioritization within the data community from the Earth system and Earth system modeling perspective.

Validation of landsurface processes in the AMIP models

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

Phillips, T J

The Atmospheric Model Intercomparison Project (AMIP) is a commonly accepted protocol for testing the performance of the world's atmospheric general circulation models (AGCMs) under common specifications of radiative forcings (in solar constant and carbon dioxide concentration) and observed ocean boundary conditions (Gates 1992, Gates et al. 1999). From the standpoint of landsurface specialists, the AMIP affords an opportunity to investigate the behaviors of a wide variety of land-surface schemes (LSS) that are coupled to their ''native'' AGCMs (Phillips et al. 1995, Phillips 1999). In principle, therefore, the AMIP permits consideration of an overarching question: ''To what extent does an AGCM'smore » performance in simulating continental climate depend on the representations of land-surface processes by the embedded LSS?'' There are, of course, some formidable obstacles to satisfactorily addressing this question. First, there is the dilemna of how to effectively validate simulation performance, given the present dearth of global land-surface data sets. Even if this data problem were to be alleviated, some inherent methodological difficulties would remain: in the context of the AMIP, it is not possible to validate a given LSS per se, since the associated land-surface climate simulation is a product of the coupled AGCM/LSS system. Moreover, aside from the intrinsic differences in LSS across the AMIP models, the varied representations of land-surface characteristics (e.g. vegetation properties, surface albedos and roughnesses, etc.) and related variations in land-surface forcings further complicate such an attribution process. Nevertheless, it may be possible to develop validation methodologies/statistics that are sufficiently penetrating to reveal ''signatures'' of particular ISS representations (e.g. ''bucket'' vs more complex parameterizations of hydrology) in the AMIP land-surface simulations.« less

Effects of land use on lake nutrients: The importance of scale, hydrologic connectivity, and region

USGS Publications Warehouse

Soranno, Patricia A.; Cheruvelil, Kendra Spence; Wagner, Tyler; Webster, Katherine E.; Bremigan, Mary Tate

2015-01-01

Catchment land uses, particularly agriculture and urban uses, have long been recognized as major drivers of nutrient concentrations in surface waters. However, few simple models have been developed that relate the amount of catchment land use to downstream freshwater nutrients. Nor are existing models applicable to large numbers of freshwaters across broad spatial extents such as regions or continents. This research aims to increase model performance by exploring three factors that affect the relationship between land use and downstream nutrients in freshwater: the spatial extent for measuring land use, hydrologic connectivity, and the regional differences in both the amount of nutrients and effects of land use on them. We quantified the effects of these three factors that relate land use to lake total phosphorus (TP) and total nitrogen (TN) in 346 north temperate lakes in 7 regions in Michigan, USA. We used a linear mixed modeling framework to examine the importance of spatial extent, lake hydrologic class, and region on models with individual lake nutrients as the response variable, and individual land use types as the predictor variables. Our modeling approach was chosen to avoid problems of multi-collinearity among predictor variables and a lack of independence of lakes within regions, both of which are common problems in broad-scale analyses of freshwaters. We found that all three factors influence land use-lake nutrient relationships. The strongest evidence was for the effect of lake hydrologic connectivity, followed by region, and finally, the spatial extent of land use measurements. Incorporating these three factors into relatively simple models of land use effects on lake nutrients should help to improve predictions and understanding of land use-lake nutrient interactions at broad scales.

Effects of Land Use on Lake Nutrients: The Importance of Scale, Hydrologic Connectivity, and Region

PubMed Central

Soranno, Patricia A.; Cheruvelil, Kendra Spence; Wagner, Tyler; Webster, Katherine E.; Bremigan, Mary Tate

2015-01-01

Catchment land uses, particularly agriculture and urban uses, have long been recognized as major drivers of nutrient concentrations in surface waters. However, few simple models have been developed that relate the amount of catchment land use to downstream freshwater nutrients. Nor are existing models applicable to large numbers of freshwaters across broad spatial extents such as regions or continents. This research aims to increase model performance by exploring three factors that affect the relationship between land use and downstream nutrients in freshwater: the spatial extent for measuring land use, hydrologic connectivity, and the regional differences in both the amount of nutrients and effects of land use on them. We quantified the effects of these three factors that relate land use to lake total phosphorus (TP) and total nitrogen (TN) in 346 north temperate lakes in 7 regions in Michigan, USA. We used a linear mixed modeling framework to examine the importance of spatial extent, lake hydrologic class, and region on models with individual lake nutrients as the response variable, and individual land use types as the predictor variables. Our modeling approach was chosen to avoid problems of multi-collinearity among predictor variables and a lack of independence of lakes within regions, both of which are common problems in broad-scale analyses of freshwaters. We found that all three factors influence land use-lake nutrient relationships. The strongest evidence was for the effect of lake hydrologic connectivity, followed by region, and finally, the spatial extent of land use measurements. Incorporating these three factors into relatively simple models of land use effects on lake nutrients should help to improve predictions and understanding of land use-lake nutrient interactions at broad scales. PMID:26267813

The importance of defining focal assemblages when evaluating amphibian and reptile responses to land use.

PubMed

Thompson, Michelle E; Nowakowski, A Justin; Donnelly, Maureen A

2016-04-01

Habitat loss and degradation are primary threats to amphibians and reptiles, but the relative effects of common land uses on assemblages and the mechanisms that underlie faunal responses are poorly studied. We reviewed the effects of four prevalent types of habitat alteration (urbanization, agriculture, livestock grazing, and silviculture) on amphibian and reptile species richness and abundance by summarizing reported responses in the literature and by estimating effect sizes across studies for species richness in each land-use type. We then used a multinomial model to classify species as natural habitat specialists, generalists, and disturbed habitat specialists and examined variation in effect sizes for each land-use type according to habitat specialization categories. There were mixed conclusions from individual studies, some reporting negative, neutral, or positive effects of land use on species richness and total abundance. A large proportion of studies reported species-specific effects of individual species abundance. However, in our analysis of effect sizes, we found a general trend of negative effects of land use on species richness. We also demonstrate that habitat associations of common species and species turnover can explain variation in the effect of land use on herpetofauna. Our review highlights the pervasive negative effects of common land uses on amphibians and reptiles, the importance of identifying groups vulnerable to land-use change (e.g., forest-associated species) in conservation studies, and the potential influence of disturbance-associated species on whole assemblage analyses. © 2015 Society for Conservation Biology.

Implementation ambiguity: The fifth element long lost in uncertainty budgets for land biogeochemical modeling

NASA Astrophysics Data System (ADS)

Tang, J.; Riley, W. J.

2015-12-01

Previous studies have identified four major sources of predictive uncertainty in modeling land biogeochemical (BGC) processes: (1) imperfect initial conditions (e.g., assumption of preindustrial equilibrium); (2) imperfect boundary conditions (e.g., climate forcing data); (3) parameterization (type I equifinality); and (4) model structure (type II equifinality). As if that were not enough to cause substantial sleep loss in modelers, we propose here a fifth element of uncertainty that results from implementation ambiguity that occurs when the model's mathematical description is translated into computational code. We demonstrate the implementation ambiguity using the example of nitrogen down regulation, a necessary process in modeling carbon-climate feedbacks. We show that, depending on common land BGC model interpretations of the governing equations for mineral nitrogen, there are three different implementations of nitrogen down regulation. We coded these three implementations in the ACME land model (ALM), and explored how they lead to different preindustrial and contemporary land biogeochemical states and fluxes. We also show how this implementation ambiguity can lead to different carbon-climate feedback estimates across the RCP scenarios. We conclude by suggesting how to avoid such implementation ambiguity in ESM BGC models.

Impacts of land use/cover classification accuracy on regional climate simulations

NASA Astrophysics Data System (ADS)

Ge, Jianjun; Qi, Jiaguo; Lofgren, Brent M.; Moore, Nathan; Torbick, Nathan; Olson, Jennifer M.

2007-03-01

Land use/cover change has been recognized as a key component in global change. Various land cover data sets, including historically reconstructed, recently observed, and future projected, have been used in numerous climate modeling studies at regional to global scales. However, little attention has been paid to the effect of land cover classification accuracy on climate simulations, though accuracy assessment has become a routine procedure in land cover production community. In this study, we analyzed the behavior of simulated precipitation in the Regional Atmospheric Modeling System (RAMS) over a range of simulated classification accuracies over a 3 month period. This study found that land cover accuracy under 80% had a strong effect on precipitation especially when the land surface had a greater control of the atmosphere. This effect became stronger as the accuracy decreased. As shown in three follow-on experiments, the effect was further influenced by model parameterizations such as convection schemes and interior nudging, which can mitigate the strength of surface boundary forcings. In reality, land cover accuracy rarely obtains the commonly recommended 85% target. Its effect on climate simulations should therefore be considered, especially when historically reconstructed and future projected land covers are employed.

Dynamics of land use and common-resource pressures in terrestrial-aquatic environments

NASA Astrophysics Data System (ADS)

Lazarus, E.; Bell, K. P.

2010-12-01

Common-pool resource problems can arise in aquatic systems such as lakes, rivers, and open coastlines where individual land-use decisions produce collective, emergent effects at the watershed scale. A body of highly generalized modeling experiments has illustrated ways in which simple, opposing tendencies among individuals—imitative versus self-initiated actions, for example—can result in richly complex behaviors. If the dynamics of those opposing tendencies are translated into different land uses (development, extraction, working land, conservation), each entailing a different environmental consequence, then feedbacks between land-use decisions and resulting changes to the physical environment (which in turn influence subsequent land-use decisions) cause the environmental and social systems of the watershed to become coupled. We present the early results of an exploratory, spatially-extended model that couples a simplified riparian system to a hypothetical group of landowners, each of whom can choose between property development, placing property under a conservation easement, or taking no action and effectively maintaining the property's status quo. As in the generalized experiments, landowner behavior depends on two sets of opposing tendencies, one of which is imitation versus self-initiation. The other is a preference for property consolidation or subdivision; large property holdings can be subdivided into smaller parcels, and small parcels can be bought up by an owner to amass a larger property. Land-use decisions taken by landowners in the model affect the riparian system in process-based ways (sedimentation, eutrophication, water quality) that then inform subsequent social interactions and decisions. Isolating the basic dynamics of this kind of socio-environmental system allows us to pursue a number of questions relevant to resource management. What social and environmental circumstances in this framework result in continuous conservation corridors as opposed to patchworks of easements? How do different kinds of easements, such as those that permit private development and subdivision, affect the integrity of the commons? More broadly, how do changing, heterogeneous patterns of mixed land uses (with different inherent time scales) affect environmental resilience? Dynamical insights from the idealized model dovetail with empirical economic analyses of aquatic-system conservation currently underway in the State of Maine, where opportunities for case studies of specific coupled human/aquatic systems and cross-case comparisons are abundant. This investigation is part of an interdisciplinary project under the auspices of the Sustainability Solutions Initiative at the University of Maine.

State-and-transition simulation models: a framework for forecasting landscape change

USGS Publications Warehouse

Daniel, Colin; Frid, Leonardo; Sleeter, Benjamin M.; Fortin, Marie-Josée

2016-01-01

SummaryA wide range of spatially explicit simulation models have been developed to forecast landscape dynamics, including models for projecting changes in both vegetation and land use. While these models have generally been developed as separate applications, each with a separate purpose and audience, they share many common features.We present a general framework, called a state-and-transition simulation model (STSM), which captures a number of these common features, accompanied by a software product, called ST-Sim, to build and run such models. The STSM method divides a landscape into a set of discrete spatial units and simulates the discrete state of each cell forward as a discrete-time-inhomogeneous stochastic process. The method differs from a spatially interacting Markov chain in several important ways, including the ability to add discrete counters such as age and time-since-transition as state variables, to specify one-step transition rates as either probabilities or target areas, and to represent multiple types of transitions between pairs of states.We demonstrate the STSM method using a model of land-use/land-cover (LULC) change for the state of Hawai'i, USA. Processes represented in this example include expansion/contraction of agricultural lands, urbanization, wildfire, shrub encroachment into grassland and harvest of tree plantations; the model also projects shifts in moisture zones due to climate change. Key model output includes projections of the future spatial and temporal distribution of LULC classes and moisture zones across the landscape over the next 50 years.State-and-transition simulation models can be applied to a wide range of landscapes, including questions of both land-use change and vegetation dynamics. Because the method is inherently stochastic, it is well suited for characterizing uncertainty in model projections. When combined with the ST-Sim software, STSMs offer a simple yet powerful means for developing a wide range of models of landscape dynamics.

The ISLSCP initiative I global datasets: Surface boundary conditions and atmospheric forcings for land-atmosphere studies

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

Sellers, P.J.; Collatz, J.; Koster, R.

1996-09-01

A comprehensive series of global datasets for land-atmosphere models has been collected, formatted to a common grid, and released on a set of CD-ROMs. This paper describes the motivation for and the contents of the dataset. In June of 1992, an interdisciplinary earth science workshop was convened in Columbia, Maryland, to assess progress in land-atmosphere research, specifically in the areas of models, satellite data algorithms, and field experiments. At the workshop, representatives of the land-atmosphere modeling community defined a need for global datasets to prescribe boundary conditions, initialize state variables, and provide near-surface meteorological and radiative forcings for their models.more » The International Satellite Land Surface Climatology Project (ISLSCP), a part of the Global Energy and Water Cycle Experiment, worked with the Distributed Active Archive Center of the National Aeronautics and Space Administration Goddard Space Flight Center to bring the required datasets together in a usable format. The data have since been released on a collection of CD-ROMs. The datasets on the CD-ROMs are grouped under the following headings: vegetation; hydrology and soils; snow, ice, and oceans; radiation and clouds; and near-surface meteorology. All datasets cover the period 1987-88, and all but a few are spatially continuous over the earth`s land surface. All have been mapped to a common 1{degree} x 1{degree} equal-angle grid. The temporal frequency for most of the datasets is monthly. A few of the near-surface meteorological parameters are available both as six-hourly values and as monthly means. 26 refs., 8 figs., 2 tabs.« less

Immediate effects of modified landing pattern on a probabilistic tibial stress fracture model in runners.

PubMed

Chen, T L; An, W W; Chan, Z Y S; Au, I P H; Zhang, Z H; Cheung, R T H

2016-03-01

Tibial stress fracture is a common injury in runners. This condition has been associated with increased impact loading. Since vertical loading rates are related to the landing pattern, many heelstrike runners attempt to modify their footfalls for a lower risk of tibial stress fracture. Such effect of modified landing pattern remains unknown. This study examined the immediate effects of landing pattern modification on the probability of tibial stress fracture. Fourteen experienced heelstrike runners ran on an instrumented treadmill and they were given augmented feedback for landing pattern switch. We measured their running kinematics and kinetics during different landing patterns. Ankle joint contact force and peak tibial strains were estimated using computational models. We used an established mathematical model to determine the effect of landing pattern on stress fracture probability. Heelstrike runners experienced greater impact loading immediately after landing pattern switch (P<0.004). There was an increase in the longitudinal ankle joint contact force when they landed with forefoot (P=0.003). However, there was no significant difference in both peak tibial strains and the risk of tibial stress fracture in runners with different landing patterns (P>0.986). Immediate transitioning of the landing pattern in heelstrike runners may not offer timely protection against tibial stress fracture, despite a reduction of impact loading. Long-term effects of landing pattern switch remains unknown. Copyright © 2016 Elsevier Ltd. All rights reserved.

GLACE: The Global Land-Atmosphere Coupling Experiment Part 2: Analysis

NASA Technical Reports Server (NTRS)

Guo, Zhichang; Dirmeyer, Paul A.; Koster, Randal D.; Bonan, Gordon; Chan, Edmond; Cox, Peter; Gordon, C. T.; Kanae, Shinjiro; Kowalczyk, Eva; Lawrence, David

2005-01-01

The twelve weather and climate models participating in the Global Land-Atmosphere Coupling Experiment (GLACE) show both a wide variation in the strength of land-atmosphere coupling and some intriguing commonalities. In this paper, we address the causes of variations in coupling strength - both the geographic variations within a given model and the model-to-model differences. The ability of soil moisture to affect precipitation is examined in two stages, namely, the ability of the soil moisture to affect evaporation, and the ability of evaporation to affect precipitation. Most of the differences between the models and within a given model are found to be associated with the first stage - an evaporation rate that varies strongly and consistently with soil moisture tends to lead to a higher coupling strength. The first stage differences reflect identifiable differences in model parameterization and model climate. Intermodel differences in the evaporation-precipitation connection, however, also play a key role.

Water resources planning and modelling tools for the assessment of land use change in the Luvuvhu Catchment, South Africa

NASA Astrophysics Data System (ADS)

Jewitt, G. P. W.; Garratt, J. A.; Calder, I. R.; Fuller, L.

In arid and semi-arid areas, total evaporation is a major component of the hydrological cycle and seasonal water shortages and drought are common. In these areas, the role of land use and land use change is particularly important and it is imperative that land and water resources are well managed. To aid efficient water management, it is useful to demonstrate how changing land use affects water resources. A convenient framework to consider this is through the use of the ‘blue-water’ and ‘green-water’ classification of Falkenmark, where green-water represents water use by land and blue-water represents runoff. In this study the hydrological response of nine land-use scenarios were simulated for the upper reaches of the Mutale River, an important tributary of the Luvuvhu River in S. Africa. The ACRU and HYLUC land use sensitive hydrological models, were used to investigate the change in blue and green water under the various land-use scenarios. The GIS software ArcGIS(8.3) was used to analyse available spatial data to generate inputs required by the hydrological models. The scenarios investigated included the current land use in the catchment, an increase or decrease in forest cover, and an increase or decrease in the area irrigated. Both models predict that increasing either forestry or irrigation significantly reduces the proportion of blue water in the catchment. The predictions from the models were combined with maps of catchment land use, to illustrate the changes in distribution of green and blue water in a user-friendly manner. The use of GIS in this way is designed to enable policy-makers and managers to quickly assimilate the water resource implication of the land use change.

Moving across scales: Challenges and opportunities in upscaling carbon fluxes

NASA Astrophysics Data System (ADS)

Naithani, K. J.

2016-12-01

Light use efficiency (LUE) type models are commonly used to upscale terrestrial C fluxes and estimate regional and global C budgets. Model parameters are often estimated for each land cover type (LCT) using flux observations from one or more eddy covariance towers, and then spatially extrapolated by integrating land cover, meteorological, and remotely sensed data. Decisions regarding the type of input data (spatial resolution of land cover data, spatial and temporal length of flux data), representation of landscape structure (land use vs. disturbance regime), and the type of modeling framework (common risk vs. hierarchical) all influence the estimates CO2 fluxes and the associated uncertainties, but are rarely considered together. This work presents a synthesis of past and present efforts for upscaling CO2 fluxes and associated uncertainties in the ChEAS (Chequamegon Ecosystem Atmosphere Study) region in northern Wisconsin and the Upper Peninsula of Michigan. This work highlights two key future research needs. First, the characterization of uncertainties due to all of the abovementioned factors reflects only a (hopefully relevant) subset the overall uncertainties. Second, interactions among these factors are likely critical, but are poorly represented by the tower network at landscape scales. Yet, results indicate significant spatial and temporal heterogeneity of uncertainty in CO2 fluxes which can inform carbon management efforts and prioritize data needs.

Simulating forest landscape disturbances as coupled human and natural systems

USGS Publications Warehouse

Wimberly, Michael; Sohl, Terry L.; Liu, Zhihua; Lamsal, Aashis

2015-01-01

Anthropogenic disturbances resulting from human land use affect forest landscapes over a range of spatial and temporal scales, with diverse influences on vegetation patterns and dynamics. These processes fall within the scope of the coupled human and natural systems (CHANS) concept, which has emerged as an important framework for understanding the reciprocal interactions and feedbacks that connect human activities and ecosystem responses. Spatial simulation modeling of forest landscape change is an important technique for exploring the dynamics of CHANS over large areas and long time periods. Landscape models for simulating interactions between human activities and forest landscape dynamics can be grouped into two main categories. Forest landscape models (FLMs) focus on landscapes where forests are the dominant land cover and simulate succession and natural disturbances along with forest management activities. In contrast, land change models (LCMs) simulate mosaics of different land cover and land use classes that include forests in addition to other land uses such as developed areas and agricultural lands. There are also several examples of coupled models that combine elements of FLMs and LCMs. These integrated models are particularly useful for simulating human–natural interactions in landscapes where human settlement and agriculture are expanding into forested areas. Despite important differences in spatial scale and disciplinary scope, FLMs and LCMs have many commonalities in conceptual design and technical implementation that can facilitate continued integration. The ultimate goal will be to implement forest landscape disturbance modeling in a CHANS framework that recognizes the contextual effects of regional land use and other human activities on the forest ecosystem while capturing the reciprocal influences of forests and their disturbances on the broader land use mosaic.

Land Suitability Modeling using a Geographic Socio-Environmental Niche-Based Approach: A Case Study from Northeastern Thailand

PubMed Central

Heumann, Benjamin W.; Walsh, Stephen J.; Verdery, Ashton M.; McDaniel, Phillip M.; Rindfuss, Ronald R.

2012-01-01

Understanding the pattern-process relations of land use/land cover change is an important area of research that provides key insights into human-environment interactions. The suitability or likelihood of occurrence of land use such as agricultural crop types across a human-managed landscape is a central consideration. Recent advances in niche-based, geographic species distribution modeling (SDM) offer a novel approach to understanding land suitability and land use decisions. SDM links species presence-location data with geospatial information and uses machine learning algorithms to develop non-linear and discontinuous species-environment relationships. Here, we apply the MaxEnt (Maximum Entropy) model for land suitability modeling by adapting niche theory to a human-managed landscape. In this article, we use data from an agricultural district in Northeastern Thailand as a case study for examining the relationships between the natural, built, and social environments and the likelihood of crop choice for the commonly grown crops that occur in the Nang Rong District – cassava, heavy rice, and jasmine rice, as well as an emerging crop, fruit trees. Our results indicate that while the natural environment (e.g., elevation and soils) is often the dominant factor in crop likelihood, the likelihood is also influenced by household characteristics, such as household assets and conditions of the neighborhood or built environment. Furthermore, the shape of the land use-environment curves illustrates the non-continuous and non-linear nature of these relationships. This approach demonstrates a novel method of understanding non-linear relationships between land and people. The article concludes with a proposed method for integrating the niche-based rules of land use allocation into a dynamic land use model that can address both allocation and quantity of agricultural crops. PMID:24187378

Improving land surface emissivty parameter for land surface models using portable FTIR and remote sensing observation in Taklimakan Desert

NASA Astrophysics Data System (ADS)

Liu, Yongqiang; Mamtimin, Ali; He, Qing

2014-05-01

Because land surface emissivity (ɛ) has not been reliably measured, global climate model (GCM) land surface schemes conventionally set this parameter as simply assumption, for example, 1 as in the National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Prediction (NCEP) model, 0.96 for soil and wetland in the Global and Regional Assimilation and Prediction System (GRAPES) Common Land Model (CoLM). This is the so-called emissivity assumption. Accurate broadband emissivity data are needed as model inputs to better simulate the land surface climate. It is demonstrated in this paper that the assumption of the emissivity induces errors in modeling the surface energy budget over Taklimakan Desert where ɛ is far smaller than original value. One feasible solution to this problem is to apply the accurate broadband emissivity into land surface models. The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument has routinely measured spectral emissivities in six thermal infrared bands. The empirical regression equations have been developed in this study to convert these spectral emissivities to broadband emissivity required by land surface models. In order to calibrate the regression equations, using a portable Fourier Transform infrared (FTIR) spectrometer instrument, crossing Taklimakan Desert along with highway from north to south, to measure the accurate broadband emissivity. The observed emissivity data show broadband ɛ around 0.89-0.92. To examine the impact of improved ɛ to radiative energy redistribution, simulation studies were conducted using offline CoLM. The results illustrate that large impacts of surface ɛ occur over desert, with changes up in surface skin temperature, as well as evident changes in sensible heat fluxes. Keywords: Taklimakan Desert, surface broadband emissivity, Fourier Transform infrared spectrometer, MODIS, CoLM

EFFECT OF GEOMORPHOLOGIC RESOLUTION ON MODELING OF RUNOFF HYDROGRAPH AND SEDIMENTOGRAPH OVER SMALL WATERSHEDS

EPA Science Inventory

In hydrologic models GIS interfaces are commonly used for extracting the channel network, and delineating the watershed. By overlaying soil and land use maps onto the extracted channel network, input files required by the model are prepared. However, the nature of the extracted c...

Treatment of systematic errors in land data assimilation systems

NASA Astrophysics Data System (ADS)

Crow, W. T.; Yilmaz, M.

2012-12-01

Data assimilation systems are generally designed to minimize the influence of random error on the estimation of system states. Yet, experience with land data assimilation systems has also revealed the presence of large systematic differences between model-derived and remotely-sensed estimates of land surface states. Such differences are commonly resolved prior to data assimilation through implementation of a pre-processing rescaling step whereby observations are scaled (or non-linearly transformed) to somehow "match" comparable predictions made by an assimilation model. While the rationale for removing systematic differences in means (i.e., bias) between models and observations is well-established, relatively little theoretical guidance is currently available to determine the appropriate treatment of higher-order moments during rescaling. This talk presents a simple analytical argument to define an optimal linear-rescaling strategy for observations prior to their assimilation into a land surface model. While a technique based on triple collocation theory is shown to replicate this optimal strategy, commonly-applied rescaling techniques (e.g., so called "least-squares regression" and "variance matching" approaches) are shown to represent only sub-optimal approximations to it. Since the triple collocation approach is likely infeasible in many real-world circumstances, general advice for deciding between various feasible (yet sub-optimal) rescaling approaches will be presented with an emphasis of the implications of this work for the case of directly assimilating satellite radiances. While the bulk of the analysis will deal with linear rescaling techniques, its extension to nonlinear cases will also be discussed.

Combined analysis of KamLAND and Borexino neutrino signals from Th and U decays in the Earth's interior

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

Fogli, G. L.; Rotunno, A. M.; INFN, Sezione di Bari, Via Orabona 4, 70126, Bari

2010-11-01

The KamLAND and Borexino experiments have detected electron antineutrinos produced in the decay chains of natural thorium and uranium (Th and U geoneutrinos). We analyze the energy spectra of current geoneutrino data in combination with solar and long-baseline reactor neutrino data, with marginalized three-neutrino oscillation parameters. We consider the case with unconstrained Th and U event rates in KamLAND and Borexino, as well as cases with fewer degrees of freedom, as obtained by successively assuming for both experiments a common Th/U ratio, a common scaling of Th+U event rates, and a chondritic Th/U value. In combination, KamLAND and Borexino canmore » reject the null hypothesis (no geoneutrino signal) at 5{sigma}. Interesting bounds or indications emerge on the Th+U geoneutrino rates and on the Th/U ratio, in broad agreement with typical Earth model expectations. Conversely, the results disfavor the hypothesis of a georeactor in the Earth's core, if its power exceeds a few TW. The interplay of KamLAND and Borexino geoneutrino data is highlighted.« less

Carbon factors and models for forest carbon estimates for the 2005-2011 National Greenhouse Gas Inventories of the United States

Treesearch

James E. Smith; Linda S. Heath; Coeli M. Hoover

2013-01-01

Most nations have ratified the United Nations Framework Convention on Climate Change, and are mandated to report National Greenhouse Gas Inventories, including the land use, land use change and forestry sector when it is significant. Participating countries commonly use data from national forest inventories as a basis for their forest-related emissions estimates. The...

Data model for the collaboration between land administration systems and agricultural land parcel identification systems.

PubMed

Inan, Halil Ibrahim; Sagris, Valentina; Devos, Wim; Milenov, Pavel; van Oosterom, Peter; Zevenbergen, Jaap

2010-12-01

The Common Agricultural Policy (CAP) of the European Union (EU) has dramatically changed after 1992, and from then on the CAP focused on the management of direct income subsidies instead of production-based subsidies. For this focus, Member States (MS) are expected to establish Integrated Administration and Control System (IACS), including a Land Parcel Identification System (LPIS) as the spatial part of IACS. Different MS have chosen different solutions for their LPIS. Currently, some MS based their IACS/LPIS on data from their Land Administration Systems (LAS), and many others use purpose built special systems for their IACS/LPIS. The issue with these different IACS/LPIS is that they do not have standardized structures; rather, each represents a unique design in each MS, both in the case of LAS based or special systems. In this study, we aim at designing a core data model for those IACS/LPIS based on LAS. For this purpose, we make use of the ongoing standardization initiatives for LAS (Land Administration Domain Model: LADM) and IACS/LPIS (LPIS Core Model: LCM). The data model we propose in this study implies the collaboration between LADM and LCM and includes some extensions. Some basic issues with the collaboration model are discussed within this study: registration of farmers, land use rights and farming limitations, geometry/topology, temporal data management etc. For further explanation of the model structure, sample instance level diagrams illustrating some typical situations are also included. Copyright © 2010 Elsevier Ltd. All rights reserved.

Participatory, Multi-Criteria Evaluation Methods as a Means to Increase the Legitimacy and Sustainability of Land Use Planning Processes. The Case of the Chaco Region in Salta, Argentina.

PubMed

Seghezzo, Lucas; Venencia, Cristian; Buliubasich, E Catalina; Iribarnegaray, Martín A; Volante, José N

2017-02-01

Conflicts over land use and ownership are common in South America and generate frequent confrontations among indigenous peoples, small-scale farmers, and large-scale agricultural producers. We argue in this paper that an accurate identification of these conflicts, together with a participatory evaluation of their importance, will increase the social legitimacy of land use planning processes, rendering decision-making more sustainable in the long term. We describe here a participatory, multi-criteria conflict assessment model developed to identify, locate, and categorize land tenure and use conflicts. The model was applied to the case of the "Chaco" region of the province of Salta, in northwestern Argentina. Basic geographic, cadastral, and social information needed to apply the model was made spatially explicit on a Geographic Information System. Results illustrate the contrasting perceptions of different stakeholders (government officials, social and environmental non-governmental organizations, large-scale agricultural producers, and scholars) on the intensity of land use conflicts in the study area. These results can help better understand and address land tenure conflicts in areas with different cultures and conflicting social and enviornmental interests.

Participatory, Multi-Criteria Evaluation Methods as a Means to Increase the Legitimacy and Sustainability of Land Use Planning Processes. The Case of the Chaco Region in Salta, Argentina

NASA Astrophysics Data System (ADS)

Seghezzo, Lucas; Venencia, Cristian; Buliubasich, E. Catalina; Iribarnegaray, Martín A.; Volante, José N.

2017-02-01

Conflicts over land use and ownership are common in South America and generate frequent confrontations among indigenous peoples, small-scale farmers, and large-scale agricultural producers. We argue in this paper that an accurate identification of these conflicts, together with a participatory evaluation of their importance, will increase the social legitimacy of land use planning processes, rendering decision-making more sustainable in the long term. We describe here a participatory, multi-criteria conflict assessment model developed to identify, locate, and categorize land tenure and use conflicts. The model was applied to the case of the "Chaco" region of the province of Salta, in northwestern Argentina. Basic geographic, cadastral, and social information needed to apply the model was made spatially explicit on a Geographic Information System. Results illustrate the contrasting perceptions of different stakeholders (government officials, social and environmental non-governmental organizations, large-scale agricultural producers, and scholars) on the intensity of land use conflicts in the study area. These results can help better understand and address land tenure conflicts in areas with different cultures and conflicting social and enviornmental interests.

Comparison of watershed disturbance predictive models for stream benthic macroinvertebrates for three distinct ecoregions in western US

USGS Publications Warehouse

Waite, Ian R.; Brown, Larry R.; Kennen, Jonathan G.; May, Jason T.; Cuffney, Thomas F.; Orlando, James L.; Jones, Kimberly A.

2010-01-01

The successful use of macroinvertebrates as indicators of stream condition in bioassessments has led to heightened interest throughout the scientific community in the prediction of stream condition. For example, predictive models are increasingly being developed that use measures of watershed disturbance, including urban and agricultural land-use, as explanatory variables to predict various metrics of biological condition such as richness, tolerance, percent predators, index of biotic integrity, functional species traits, or even ordination axes scores. Our primary intent was to determine if effective models could be developed using watershed characteristics of disturbance to predict macroinvertebrate metrics among disparate and widely separated ecoregions. We aggregated macroinvertebrate data from universities and state and federal agencies in order to assemble stream data sets of high enough density appropriate for modeling in three distinct ecoregions in Oregon and California. Extensive review and quality assurance of macroinvertebrate sampling protocols, laboratory subsample counts and taxonomic resolution was completed to assure data comparability. We used widely available digital coverages of land-use and land-cover data summarized at the watershed and riparian scale as explanatory variables to predict macroinvertebrate metrics commonly used by state resource managers to assess stream condition. The “best” multiple linear regression models from each region required only two or three explanatory variables to model macroinvertebrate metrics and explained 41–74% of the variation. In each region the best model contained some measure of urban and/or agricultural land-use, yet often the model was improved by including a natural explanatory variable such as mean annual precipitation or mean watershed slope. Two macroinvertebrate metrics were common among all three regions, the metric that summarizes the richness of tolerant macroinvertebrates (RICHTOL) and some form of EPT (Ephemeroptera, Plecoptera, and Trichoptera) richness. Best models were developed for the same two invertebrate metrics even though the geographic regions reflect distinct differences in precipitation, geology, elevation, slope, population density, and land-use. With further development, models like these can be used to elicit better causal linkages to stream biological attributes or condition and can be used by researchers or managers to predict biological indicators of stream condition at unsampled sites.

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.

The Plumbing of Land Surface Models: Is Poor Performance a Result of Methodology or Data Quality?

NASA Technical Reports Server (NTRS)

Haughton, Ned; Abramowitz, Gab; Pitman, Andy J.; Or, Dani; Best, Martin J.; Johnson, Helen R.; Balsamo, Gianpaolo; Boone, Aaron; Cuntz, Matthais; Decharme, Bertrand;

Hydrogeomorphic features mediate the effects of land use/cover on reservoir productivity and food webs

USGS Publications Warehouse

Bremigan, M.T.; Soranno, P.A.; Gonzalez, M.J.; Bunnell, D.B.; Arend, K.K.; Renwick, W.H.; Stein, R.A.; Vanni, M.J.

2008-01-01

Although effects of land use/cover on nutrient concentrations in aquatic systems are well known, half or more of the variation in nutrient concentration remains unexplained by land use/cover alone. Hydrogeomorphic (HGM) landscape features can explain much remaining variation and influence food web interactions. To explore complex linkages among land use/cover, HGM features, reservoir productivity, and food webs, we sampled 11 Ohio reservoirs, ranging broadly in agricultural catchment land use/cover, for 3 years. We hypothesized that HGM features mediate the bottom-up effects of land use/cover on reservoir productivity, chlorophyll a, zooplankton, and recruitment of gizzard shad, an omnivorous fish species common throughout southeastern U.S. reservoirs and capable of exerting strong effects on food web and nutrient dynamics. We tested specific hypotheses using a model selection approach. Percent variation explained was highest for total nitrogen (R2 = 0.92), moderately high for total phosphorus, chlorophyll a, and rotifer biomass (R2 = 0.57 to 0.67), relatively low for crustacean zooplankton biomass and larval gizzard shad hatch abundance (R2 = 0.43 and 0.42), and high for larval gizzard shad survivor abundance (R2 = 0.79). The trophic status models included agricultural land use/cover and an HGM predictor, whereas the zooplankton models had few HGM predictors. The larval gizzard shad models had the highest complexity, including more than one HGM feature and food web components. We demonstrate the importance of integrating land use/cover, HGM features, and food web interactions to investigate critical interactions and feedbacks among physical, chemical, and biological components of linked land-water ecosystems.

What is the role of historical anthropogenically-induced land-cover change on the surface climate of West Africa? Results from the LUCID intercomparison project

NASA Astrophysics Data System (ADS)

Souleymane, S.

2015-12-01

West Africa has been highlighted as a hot spot of land surface-atmosphere interactions. This study analyses the outputs of the project Land-Use and Climate, IDentification of Robust Impacts (LUCID) over West Africa. LUCID used seven atmosphere-land models with a common experimental design to explore the impacts of Land Use induced Land Cover Change (LULCC) that are robust and consistent across the climate models. Focusing the analysis on Sahel and Guinea, this study shows that, even though the seven climate models use the same atmospheric and land cover forcing, there are significant differences of West African Monsoon variability across the climate models. The magnitude of that variability differs significantly from model to model resulting two major "features": (1) atmosphere dynamics models; (2) how the land-surface functioning is parameterized in the Land surface Model, in particular regarding the evapotranspiration partitioning within the different land-cover types, as well as the role of leaf area index (LAI) in the flux calculations and how strongly the surface is coupled to the atmosphere. The major role that the models'sensitivity to land-cover perturbations plays in the resulting climate impacts of LULCC has been analysed in this study. The climate models show, however, significant differences in the magnitude and the seasonal partitioning of the temperature change. The LULCC induced cooling is directed by decreases in net shortwave radiation that reduced the available energy (QA) (related to changes in land-cover properties other than albedo, such as LAI and surface roughness), which decreases during most part of the year. The biophysical impacts of LULCC were compared to the impact of elevated greenhouse gases resulting changes in sea surface temperatures and sea ice extent (CO2SST). The results show that the surface cooling (related a decrease in QA) induced by the biophysical effects of LULCC are insignificant compared to surface warming (related an increase in QA), which is induced by the regional significance effect of CO2SST due to a small LULCC imposed. In contrast, the decrease of surface water balance resulting from LULCC effect is a similar sign to those resulting from CO2SST but the signal resulting of the biophysical effects of LULCC is stronger than the regional CO2SST impact.

Modelling the Relationship Between Land Surface Temperature and Landscape Patterns of Land Use Land Cover Classification Using Multi Linear Regression Models

NASA Astrophysics Data System (ADS)

Bernales, A. M.; Antolihao, J. A.; Samonte, C.; Campomanes, F.; Rojas, R. J.; dela Serna, A. M.; Silapan, J.

2016-06-01

The threat of the ailments related to urbanization like heat stress is very prevalent. There are a lot of things that can be done to lessen the effect of urbanization to the surface temperature of the area like using green roofs or planting trees in the area. So land use really matters in both increasing and decreasing surface temperature. It is known that there is a relationship between land use land cover (LULC) and land surface temperature (LST). Quantifying this relationship in terms of a mathematical model is very important so as to provide a way to predict LST based on the LULC alone. This study aims to examine the relationship between LST and LULC as well as to create a model that can predict LST using class-level spatial metrics from LULC. LST was derived from a Landsat 8 image and LULC classification was derived from LiDAR and Orthophoto datasets. Class-level spatial metrics were created in FRAGSTATS with the LULC and LST as inputs and these metrics were analysed using a statistical framework. Multi linear regression was done to create models that would predict LST for each class and it was found that the spatial metric "Effective mesh size" was a top predictor for LST in 6 out of 7 classes. The model created can still be refined by adding a temporal aspect by analysing the LST of another farming period (for rural areas) and looking for common predictors between LSTs of these two different farming periods.

Use of multi-temporal SPOT-5 satellite images for land degradation assessment in Cameron Highlands, Malaysia using Geospatial techniques

NASA Astrophysics Data System (ADS)

Nampak, Haleh; Pradhan, Biswajeet

2016-07-01

Soil erosion is the common land degradation problem worldwide because of its economic and environmental impacts. Therefore, land-use change detection has become one of the major concern to geomorphologists, environmentalists, and land use planners due to its impact on natural ecosystems. The objective of this paper is to evaluate the relationship between land use/cover changes and land degradation in the Cameron highlands (Malaysia) through multi-temporal remotely sensed satellite images and ancillary data. Land clearing in the study area has resulted increased soil erosion due to rainfall events. Also unsustainable development and agriculture, mismanagement and lacking policies contribute to increasing soil erosion rates. The LULC distribution of the study area was mapped for 2005, 2010, and 2015 through SPOT-5 satellite imagery data which were classified based on object-based classification. A soil erosion model was also used within a GIS in order to study the susceptibility of the areas affected by changes to overland flow and rain splash erosion. The model consists of four parameters, namely soil erodibility, slope, vegetation cover and overland flow. The results of this research will be used in the selection of the areas that require mitigation processes which will reduce their degrading potential. Key words: Land degradation, Geospatial, LULC change, Soil erosion modelling, Cameron highlands.

Modelling soil erosion at European scale: the importance of management practices and the future climate and land use scenarios

NASA Astrophysics Data System (ADS)

Panagos, Panos; Ballabio, Cristiano; Meusburger, Katrin; Poesen, Jean; Lugato, Emanuele; Montanarella, Luca; Alewell, Christine; Borrelli, Pasquale

2017-04-01

The implementation of RUSLE2015 for modelling soil loss by water erosion at European scale has introduced important aspects related to management practices. The policy measurements such as reduced tillage, crop residues, cover crops, grass margins, stone walls and contouring have been incorporated in the RUSLE2015 modelling platform. The recent policy interventions introduced in Good Agricultural Environmental Conditions of Common Agricultural Policy have reduced the rate of soil loss in the EU by an average of 9.5% overall, and by 20% for arable lands (NATURE, 526, 195). However, further economic and political action should rebrand the value of soil as part of ecosystem services, increase the income of rural land owners, involve young farmers and organize regional services for licensing land use changes (Land Degradation and Development, 27 (6): 1547-1551). RUSLE2015 is combining the future policy scenarios and land use changes introduced by predictions of LUISA Territorial Modelling Platform. Latest developments in RUSLE2015 allow also incorporating the climate change scenarios and the forthcoming intensification of rainfall in North and Central Europe contrary to mixed trends in Mediterranean basin. The rainfall erosivity predictions estimate a mean increase by 18% in European Union by 2050. Recently, a module of CENTURY model was coupled with the RUSLE2015 for estimating the effect of erosion in current carbon balance in European agricultural lands (Global Change Biology, 22(5), 1976-1984; 2016). Finally, the monthly erosivity datasets (Science of the Total Environment, 579: 1298-1315) introduce a dynamic component in RUSLE2015 and it is a step towards spatio-temporal soil erosion mapping at continental scale. The monthly mapping of rainfall erosivity permits to identify the months and the areas with highest risk of soil loss where conservation measures should apply in different seasons of the year. In the future, the soil erosion-modelling platform will incorporate the land use intra-annual variability, sediment transport and economic assessments of land degradation. Panagos, P., Borrelli, P., Robinson, D.A. 2015. Common Agricultural Policy: Tackling soil loss across Europe. Nature 526: 195 Panagos, P., Imeson, A., Meusburger, K., Borrelli, P., Poesen, J., Alewell, C. 2016. Soil Conservation in Europe: Wish or Reality? Land Degradation and Development, 27(6): 1547-1551 Lugato, E., Paustian, K., Panagos, P. et al. 2016. Quantifying the erosion effect on current carbon budget of European agricultural soils at high spatial resolution. Global Change Biology. 22(5): 1976-1984 Ballabio, C., Borrelli, P. et al. 2017. Mapping monthly rainfall erosivity in Europe. Science of the Total Environment, 579: 1298-1315

Prediction of cadmium enrichment in reclaimed coastal soils by classification and regression tree

NASA Astrophysics Data System (ADS)

Ru, Feng; Yin, Aijing; Jin, Jiaxin; Zhang, Xiuying; Yang, Xiaohui; Zhang, Ming; Gao, Chao

2016-08-01

Reclamation of coastal land is one of the most common ways to obtain land resources in China. However, it has long been acknowledged that the artificial interference with coastal land has disadvantageous effects, such as heavy metal contamination. This study aimed to develop a prediction model for cadmium enrichment levels and assess the importance of affecting factors in typical reclaimed land in Eastern China (DFCL: Dafeng Coastal Land). Two hundred and twenty seven surficial soil/sediment samples were collected and analyzed to identify the enrichment levels of cadmium and the possible affecting factors in soils and sediments. The classification and regression tree (CART) model was applied in this study to predict cadmium enrichment levels. The prediction results showed that cadmium enrichment levels assessed by the CART model had an accuracy of 78.0%. The CART model could extract more information on factors affecting the environmental behavior of cadmium than correlation analysis. The integration of correlation analysis and the CART model showed that fertilizer application and organic carbon accumulation were the most important factors affecting soil/sediment cadmium enrichment levels, followed by particle size effects (Al2O3, TFe2O3 and SiO2), contents of Cl and S, surrounding construction areas and reclamation history.

Efficiently modelling urban heat storage: an interface conduction scheme in an urban land surface model (aTEB v2.0)

NASA Astrophysics Data System (ADS)

Lipson, Mathew J.; Hart, Melissa A.; Thatcher, Marcus

2017-03-01

Intercomparison studies of models simulating the partitioning of energy over urban land surfaces have shown that the heat storage term is often poorly represented. In this study, two implicit discrete schemes representing heat conduction through urban materials are compared. We show that a well-established method of representing conduction systematically underestimates the magnitude of heat storage compared with exact solutions of one-dimensional heat transfer. We propose an alternative method of similar complexity that is better able to match exact solutions at typically employed resolutions. The proposed interface conduction scheme is implemented in an urban land surface model and its impact assessed over a 15-month observation period for a site in Melbourne, Australia, resulting in improved overall model performance for a variety of common material parameter choices and aerodynamic heat transfer parameterisations. The proposed scheme has the potential to benefit land surface models where computational constraints require a high level of discretisation in time and space, for example at neighbourhood/city scales, and where realistic material properties are preferred, for example in studies investigating impacts of urban planning changes.

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.

DasPy – Open Source Multivariate Land Data Assimilation Framework with High Performance Computing

NASA Astrophysics Data System (ADS)

Han, Xujun; Li, Xin; Montzka, Carsten; Kollet, Stefan; Vereecken, Harry; Hendricks Franssen, Harrie-Jan

2015-04-01

Data assimilation has become a popular method to integrate observations from multiple sources with land surface models to improve predictions of the water and energy cycles of the soil-vegetation-atmosphere continuum. In recent years, several land data assimilation systems have been developed in different research agencies. Because of the software availability or adaptability, these systems are not easy to apply for the purpose of multivariate land data assimilation research. Multivariate data assimilation refers to the simultaneous assimilation of observation data for multiple model state variables into a simulation model. Our main motivation was to develop an open source multivariate land data assimilation framework (DasPy) which is implemented using the Python script language mixed with C++ and Fortran language. This system has been evaluated in several soil moisture, L-band brightness temperature and land surface temperature assimilation studies. The implementation allows also parameter estimation (soil properties and/or leaf area index) on the basis of the joint state and parameter estimation approach. LETKF (Local Ensemble Transform Kalman Filter) is implemented as the main data assimilation algorithm, and uncertainties in the data assimilation can be represented by perturbed atmospheric forcings, perturbed soil and vegetation properties and model initial conditions. The CLM4.5 (Community Land Model) was integrated as the model operator. The CMEM (Community Microwave Emission Modelling Platform), COSMIC (COsmic-ray Soil Moisture Interaction Code) and the two source formulation were integrated as observation operators for assimilation of L-band passive microwave, cosmic-ray soil moisture probe and land surface temperature measurements, respectively. DasPy is parallelized using the hybrid MPI (Message Passing Interface) and OpenMP (Open Multi-Processing) techniques. All the input and output data flow is organized efficiently using the commonly used NetCDF file format. Online 1D and 2D visualization of data assimilation results is also implemented to facilitate the post simulation analysis. In summary, DasPy is a ready to use open source parallel multivariate land data assimilation framework.

Modeling crop residue burning experiments to evaluate smoke emissions and plume transport

EPA Science Inventory

Crop residue burning is a common land management practice that results in emissions of a variety of pollutants with negative health impacts. Modeling systems are used to estimate air quality impacts of crop residue burning to support retrospective regulatory assessments and also ...

Similarity Assessment of Land Surface Model Outputs in the North American Land Data Assimilation System

NASA Astrophysics Data System (ADS)

Kumar, Sujay V.; Wang, Shugong; Mocko, David M.; Peters-Lidard, Christa D.; Xia, Youlong

2017-11-01

Multimodel ensembles are often used to produce ensemble mean estimates that tend to have increased simulation skill over any individual model output. If multimodel outputs are too similar, an individual LSM would add little additional information to the multimodel ensemble, whereas if the models are too dissimilar, it may be indicative of systematic errors in their formulations or configurations. The article presents a formal similarity assessment of the North American Land Data Assimilation System (NLDAS) multimodel ensemble outputs to assess their utility to the ensemble, using a confirmatory factor analysis. Outputs from four NLDAS Phase 2 models currently running in operations at NOAA/NCEP and four new/upgraded models that are under consideration for the next phase of NLDAS are employed in this study. The results show that the runoff estimates from the LSMs were most dissimilar whereas the models showed greater similarity for root zone soil moisture, snow water equivalent, and terrestrial water storage. Generally, the NLDAS operational models showed weaker association with the common factor of the ensemble and the newer versions of the LSMs showed stronger association with the common factor, with the model similarity increasing at longer time scales. Trade-offs between the similarity metrics and accuracy measures indicated that the NLDAS operational models demonstrate a larger span in the similarity-accuracy space compared to the new LSMs. The results of the article indicate that simultaneous consideration of model similarity and accuracy at the relevant time scales is necessary in the development of multimodel ensemble.

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.

Microwave landing system modeling with application to air traffic control

NASA Technical Reports Server (NTRS)

Poulose, M. M.

1991-01-01

Compared to the current instrument landing system, the microwave landing system (MLS), which is in the advanced stage of implementation, can potentially provide significant fuel and time savings as well as more flexibility in approach and landing functions. However, the expanded coverage and increased accuracy requirements of the MLS make it more susceptible to the features of the site in which it is located. An analytical approach is presented for evaluating the multipath effects of scatterers that are commonly found in airport environments. The approach combines a multiplane model with a ray-tracing technique and a formulation for estimating the electromagnetic fields caused by the antenna array in the presence of scatterers. The model is applied to several airport scenarios. The reduced computational burden enables the scattering effects on MLS position information to be evaluated in near real time. Evaluation in near real time would permit the incorporation of the modeling scheme into air traffic control automation; it would adaptively delineate zones of reduced accuracy within the MLS coverage volume, and help establish safe approach and takeoff trajectories in the presence of uneven terrain and other scatterers.

DasPy 1.0 - the Open Source Multivariate Land Data Assimilation Framework in combination with the Community Land Model 4.5

NASA Astrophysics Data System (ADS)

Han, X.; Li, X.; He, G.; Kumbhar, P.; Montzka, C.; Kollet, S.; Miyoshi, T.; Rosolem, R.; Zhang, Y.; Vereecken, H.; Franssen, H.-J. H.

2015-08-01

Data assimilation has become a popular method to integrate observations from multiple sources with land surface models to improve predictions of the water and energy cycles of the soil-vegetation-atmosphere continuum. Multivariate data assimilation refers to the simultaneous assimilation of observation data from multiple model state variables into a simulation model. In recent years, several land data assimilation systems have been developed in different research agencies. Because of the software availability or adaptability, these systems are not easy to apply for the purpose of multivariate land data assimilation research. We developed an open source multivariate land data assimilation framework (DasPy) which is implemented using the Python script language mixed with the C++ and Fortran programming languages. LETKF (Local Ensemble Transform Kalman Filter) is implemented as the main data assimilation algorithm, and uncertainties in the data assimilation can be introduced by perturbed atmospheric forcing data, and represented by perturbed soil and vegetation parameters and model initial conditions. The Community Land Model (CLM) was integrated as the model operator. The implementation allows also parameter estimation (soil properties and/or leaf area index) on the basis of the joint state and parameter estimation approach. The Community Microwave Emission Modelling platform (CMEM), COsmic-ray Soil Moisture Interaction Code (COSMIC) and the Two-Source Formulation (TSF) were integrated as observation operators for the assimilation of L-band passive microwave, cosmic-ray soil moisture probe and land surface temperature measurements, respectively. DasPy has been evaluated in several assimilation studies of neutron count intensity (soil moisture), L-band brightness temperature and land surface temperature. DasPy is parallelized using the hybrid Message Passing Interface and Open Multi-Processing techniques. All the input and output data flows are organized efficiently using the commonly used NetCDF file format. Online 1-D and 2-D visualization of data assimilation results is also implemented to facilitate the post simulation analysis. In summary, DasPy is a ready to use open source parallel multivariate land data assimilation framework.

Comparison of multinomial logistic regression and logistic regression: which is more efficient in allocating land use?

NASA Astrophysics Data System (ADS)

Lin, Yingzhi; Deng, Xiangzheng; Li, Xing; Ma, Enjun

2014-12-01

Spatially explicit simulation of land use change is the basis for estimating the effects of land use and cover change on energy fluxes, ecology and the environment. At the pixel level, logistic regression is one of the most common approaches used in spatially explicit land use allocation models to determine the relationship between land use and its causal factors in driving land use change, and thereby to evaluate land use suitability. However, these models have a drawback in that they do not determine/allocate land use based on the direct relationship between land use change and its driving factors. Consequently, a multinomial logistic regression method was introduced to address this flaw, and thereby, judge the suitability of a type of land use in any given pixel in a case study area of the Jiangxi Province, China. A comparison of the two regression methods indicated that the proportion of correctly allocated pixels using multinomial logistic regression was 92.98%, which was 8.47% higher than that obtained using logistic regression. Paired t-test results also showed that pixels were more clearly distinguished by multinomial logistic regression than by logistic regression. In conclusion, multinomial logistic regression is a more efficient and accurate method for the spatial allocation of land use changes. The application of this method in future land use change studies may improve the accuracy of predicting the effects of land use and cover change on energy fluxes, ecology, and environment.

The dynamics of latifundia formation.

PubMed

Chaves, Luis Fernando

2013-01-01

Land tenure inequity is a major social problem in developing nations worldwide. In societies, where land is a commodity, inequities in land tenure are associated with gaps in income distribution, poverty and biodiversity loss. A common pattern of land tenure inequities through the history of civilization has been the formation of latifundia [Zhuāngyuán in chinese], i.e., a pattern where land ownership is concentrated by a small fraction of the whole population. Here, we use simple Markov chain models to study the dynamics of latifundia formation in a heterogeneous landscape where land can transition between forest, agriculture and recovering land. We systematically study the likelihood of latifundia formation under the assumption of pre-capitalist trade, where trade is based on the average utility of land parcels belonging to each individual landowner during a discrete time step. By restricting land trade to that under recovery, we found the likelihood of latifundia formation to increase with the size of the system, i.e., the amount of land and individuals in the society. We found that an increase of the transition rate for land use changes, i.e., how quickly land use changes, promotes more equitable patterns of land ownership. Disease introduction in the system, which reduced land profitability for infected individual landowners, promoted the formation of latifundia, with an increased likelihood for latifundia formation when there were heterogeneities in the susceptibility to infection. Finally, our model suggests that land ownership reforms need to guarantee an equitative distribution of land among individuals in a society to avoid the formation of latifundia.

The Dynamics of Latifundia Formation

PubMed Central

Chaves, Luis Fernando

2013-01-01

Land tenure inequity is a major social problem in developing nations worldwide. In societies, where land is a commodity, inequities in land tenure are associated with gaps in income distribution, poverty and biodiversity loss. A common pattern of land tenure inequities through the history of civilization has been the formation of latifundia [Zhuāngyuán in chinese], i.e., a pattern where land ownership is concentrated by a small fraction of the whole population. Here, we use simple Markov chain models to study the dynamics of latifundia formation in a heterogeneous landscape where land can transition between forest, agriculture and recovering land. We systematically study the likelihood of latifundia formation under the assumption of pre-capitalist trade, where trade is based on the average utility of land parcels belonging to each individual landowner during a discrete time step. By restricting land trade to that under recovery, we found the likelihood of latifundia formation to increase with the size of the system, i.e., the amount of land and individuals in the society. We found that an increase of the transition rate for land use changes, i.e., how quickly land use changes, promotes more equitable patterns of land ownership. Disease introduction in the system, which reduced land profitability for infected individual landowners, promoted the formation of latifundia, with an increased likelihood for latifundia formation when there were heterogeneities in the susceptibility to infection. Finally, our model suggests that land ownership reforms need to guarantee an equitative distribution of land among individuals in a society to avoid the formation of latifundia. PMID:24376597

Modeling crop residue burning experiments and assessing the fire impacts on air quality

EPA Science Inventory

Prescribed burning is a common land management practice that results in ambient emissions of a variety of primary and secondary pollutants with negative health impacts. The community Multiscale Air Quality (CMAQ) model is used to conduct 2 km grid resolution simulations of prescr...

From plot to regional scales: Effect of land use and soil type on soil erosion in the southern Amazon

NASA Astrophysics Data System (ADS)

Schindewolf, Marcus; Schultze, Nico; Amorim, Ricardo S. S.; Schmidt, Jürgen

2015-04-01

The corridor along the Brazilian Highway 163 in the Southern Amazon is affected by radical changes in land use patterns. In order to enable a model based assessment of erosion risks on different land use and soil types a transportable disc type rainfall simulator is applied to identify the most important infiltration and erosion parameters of the EROSION 3D model. Since particle detachment highly depends on experimental plot length, a combined runoff supply is used for the virtually extension of the plot length to more than 20 m. Simulations were conducted on the most common regional land use, soil management and soil types for dry and wet runs. The experiments are characterized by high final infiltration rates (0.3 - 2.5 mm*min^-1), low sediment concentrations (0.2-6.5 g*L^-1) and accordingly low soil loss rates (0.002-50 Kg*m^-2), strongly related to land use, applied management and soil type. Ploughed pastures and clear cuts reveal highest soil losses whereas croplands are less affected. Due to higher aggregate stabilities Ferrasols are less endangered than Acrisols. Derived model parameters are plausible, comparable to existing data bases and reproduce the effects of land use and soil management on soil loss. Thus it is possible to apply the EROSION 3D soil loss model in Southern Amazonia for erosion risk assessment and scenario simulation under changing climate and land use conditions.

Modeling landscape evapotranspiration by integrating land surface phenology and a water balance algorithm

USGS Publications Warehouse

Senay, Gabriel B.

2008-01-01

The main objective of this study is to present an improved modeling technique called Vegetation ET (VegET) that integrates commonly used water balance algorithms with remotely sensed Land Surface Phenology (LSP) parameter to conduct operational vegetation water balance modeling of rainfed systems at the LSP’s spatial scale using readily available global data sets. Evaluation of the VegET model was conducted using Flux Tower data and two-year simulation for the conterminous US. The VegET model is capable of estimating actual evapotranspiration (ETa) of rainfed crops and other vegetation types at the spatial resolution of the LSP on a daily basis, replacing the need to estimate crop- and region-specific crop coefficients.

GIS and remote sensing techniques for the assessment of land use changes impact on flood hydrology: the case study of Yialias Basin in Cyprus

NASA Astrophysics Data System (ADS)

Alexakis, D. D.; Gryllakis, M. G.; Koutroulis, A. G.; Agapiou, A.; Themistocleous, K.; Tsanis, I. K.; Michaelides, S.; Pashiardis, S.; Demetriou, C.; Aristeidou, K.; Retalis, A.; Tymvios, F.; Hadjimitsis, D. G.

2013-09-01

Flooding is one of the most common natural disasters worldwide, leading to economic losses and loss of human lives. This paper highlights the hydrological effects of multi-temporal land use changes in flood hazard within the Yialias catchment area, located in central Cyprus. Calibrated hydrological and hydraulic models were used to describe the hydrological processes and internal basin dynamics of the three major sub-basins, in order to study the diachronic effects of land use changes. For the implementation of the hydrological model, land use, soil and hydrometeorological data were incorporated. The climatic and stream flow data were derived from rain and flow gauge stations located in the wider area of the watershed basin. In addition, the land use and soil data were extracted after the application of object oriented nearest neighbor algorithms of ASTER satellite images. Subsequently, the CA-Markov chain analysis was implemented to predict the 2020 Land use/Land cover (LULC) map and incorporate it to the hydrological impact assessment. The results denoted the increase of runoff in the catchment area due to the recorded extensive urban sprawl phenomenon of the last decade.

GIS and remote sensing techniques for the assessment of land use change impact on flood hydrology: the case study of Yialias basin in Cyprus

NASA Astrophysics Data System (ADS)

Alexakis, D. D.; Grillakis, M. G.; Koutroulis, A. G.; Agapiou, A.; Themistocleous, K.; Tsanis, I. K.; Michaelides, S.; Pashiardis, S.; Demetriou, C.; Aristeidou, K.; Retalis, A.; Tymvios, F.; Hadjimitsis, D. G.

2014-02-01

Floods are one of the most common natural disasters worldwide, leading to economic losses and loss of human lives. This paper highlights the hydrological effects of multi-temporal land use changes in flood hazard within the Yialias catchment area, located in central Cyprus. A calibrated hydrological model was firstly developed to describe the hydrological processes and internal basin dynamics of the three major subbasins, in order to study the diachronic effects of land use changes. For the implementation of the hydrological model, land use, soil and hydrometeorological data were incorporated. The climatic and stream flow data were derived from rain and flow gauge stations located in the wider area of the watershed basin. In addition, the land use and soil data were extracted after the application of object-oriented nearest neighbor algorithms of ASTER satellite images. Subsequently, the cellular automata (CA)-Markov chain analysis was implemented to predict the 2020 land use/land cover (LULC) map and incorporate it to the hydrological impact assessment. The results denoted the increase of runoff in the catchment area due to the recorded extensive urban sprawl phenomenon of the last decade.

Effect of Variable Manning Coefficients on Tsunami Inundation

NASA Astrophysics Data System (ADS)

Barberopoulou, A.; Rees, D.

2017-12-01

Numerical simulations are commonly used to help estimate tsunami hazard, improve evacuation plans, issue or cancel tsunami warnings, inform forecasting and hazard assessments and have therefore become an integral part of hazard mitigation among the tsunami community. Many numerical codes exist for simulating tsunamis, most of which have undergone extensive benchmarking and testing. Tsunami hazard or risk assessments employ these codes following a deterministic or probabilistic approach. Depending on the scope these studies may or may not consider uncertainty in the numerical simulations, the effects of tides, variable friction or estimate financial losses, none of which are necessarily trivial. Distributed manning coefficients, the roughness coefficients used in hydraulic modeling, are commonly used in simulating both riverine and pluvial flood events however, their use in tsunami hazard assessments is primarily part of limited scope studies and for the most part, not a standard practice. For this work, we investigate variations in manning coefficients and their effects on tsunami inundation extent, pattern and financial loss. To assign manning coefficients we use land use maps that come from the New Zealand Land Cover Database (LCDB) and more recent data from the Ministry of the Environment. More than 40 classes covering different types of land use are combined into major classes such as cropland, grassland and wetland representing common types of land use in New Zealand, each of which is assigned a unique manning coefficient. By utilizing different data sources for variable manning coefficients, we examine the impact of data sources and classification methodology on the accuracy of model outputs.

Regional biases in absolute sea-level estimates from tide gauge data due to residual unmodeled vertical land movement

NASA Astrophysics Data System (ADS)

King, Matt A.; Keshin, Maxim; Whitehouse, Pippa L.; Thomas, Ian D.; Milne, Glenn; Riva, Riccardo E. M.

2012-07-01

The only vertical land movement signal routinely corrected for when estimating absolute sea-level change from tide gauge data is that due to glacial isostatic adjustment (GIA). We compare modeled GIA uplift (ICE-5G + VM2) with vertical land movement at ˜300 GPS stations located near to a global set of tide gauges, and find regionally coherent differences of commonly ±0.5-2 mm/yr. Reference frame differences and signal due to present-day mass trends cannot reconcile these differences. We examine sensitivity to the GIA Earth model by fitting to a subset of the GPS velocities and find substantial regional sensitivity, but no single Earth model is able to reduce the disagreement in all regions. We suggest errors in ice history and neglected lateral Earth structure dominate model-data differences, and urge caution in the use of modeled GIA uplift alone when interpreting regional- and global- scale absolute (geocentric) sea level from tide gauge data.

Through a glass, darkly—comparing VDDT and FVS

Treesearch

Donald C.E. Robinson; Sarah J. Beukema

2012-01-01

Land managers commonly use FVS and VDDT as planning aids. Although complementary, the models differ in their approach to projection, spatial and temporal resolution, simulation units and required input. When both are used, comparison of the model projections helps to identify differences in the assumptions of the two models and hopefully will result in more consistent...

Scenarios of land use and land cover change in the conterminous United States: Utilizing the special report on emission scenarios at ecoregional scales

USGS Publications Warehouse

Sleeter, Benjamin M.; Sohl, Terry L.; Bouchard, Michelle A.; Reker, Ryan R.; Soulard, Christopher E.; Acevedo, William; Griffith, Glenn E.; Sleeter, Rachel R.; Auch, Roger F.; Sayler, Kristi L.; Prisley, Stephen; Zhu, Zhi-Liang

2012-01-01

Global environmental change scenarios have typically provided projections of land use and land cover for a relatively small number of regions or using a relatively coarse resolution spatial grid, and for only a few major sectors. The coarseness of global projections, in both spatial and thematic dimensions, often limits their direct utility at scales useful for environmental management. This paper describes methods to downscale projections of land-use and land-cover change from the Intergovernmental Panel on Climate Change's Special Report on Emission Scenarios to ecological regions of the conterminous United States, using an integrated assessment model, land-use histories, and expert knowledge. Downscaled projections span a wide range of future potential conditions across sixteen land use/land cover sectors and 84 ecological regions, and are logically consistent with both historical measurements and SRES characteristics. Results appear to provide a credible solution for connecting regionalized projections of land use and land cover with existing downscaled climate scenarios, under a common set of scenario-based socioeconomic assumptions.

The Impact of Parametric Uncertainties on Biogeochemistry in the E3SM Land Model

NASA Astrophysics Data System (ADS)

Ricciuto, Daniel; Sargsyan, Khachik; Thornton, Peter

2018-02-01

We conduct a global sensitivity analysis (GSA) of the Energy Exascale Earth System Model (E3SM), land model (ELM) to calculate the sensitivity of five key carbon cycle outputs to 68 model parameters. This GSA is conducted by first constructing a Polynomial Chaos (PC) surrogate via new Weighted Iterative Bayesian Compressive Sensing (WIBCS) algorithm for adaptive basis growth leading to a sparse, high-dimensional PC surrogate with 3,000 model evaluations. The PC surrogate allows efficient extraction of GSA information leading to further dimensionality reduction. The GSA is performed at 96 FLUXNET sites covering multiple plant functional types (PFTs) and climate conditions. About 20 of the model parameters are identified as sensitive with the rest being relatively insensitive across all outputs and PFTs. These sensitivities are dependent on PFT, and are relatively consistent among sites within the same PFT. The five model outputs have a majority of their highly sensitive parameters in common. A common subset of sensitive parameters is also shared among PFTs, but some parameters are specific to certain types (e.g., deciduous phenology). The relative importance of these parameters shifts significantly among PFTs and with climatic variables such as mean annual temperature.

DRAINMOD-FOREST: Integrated modeling of hydrology, soil carbon and nitrogen dynamics, and plant growth for drained forests

Treesearch

Shiying Tian; Mohamed A. Youssef; R. Wayne Skaggs; Devendra M. Amatya; G.M. Chescheir

2012-01-01

We present a hybrid and stand-level forest ecosystem model, DRAINMOD-FOREST, for simulating the hydrology, carbon (C) and nitrogen (N) dynamics, and tree growth for drained forest lands under common silvicultural practices. The model was developed by linking DRAINMOD, the hydrological model, and DRAINMOD-N II, the soil C and N dynamics model, to a forest growth model,...

Assessing the effect of land use change on catchment runoff by combined use of statistical tests and hydrological modelling: Case studies from Zimbabwe

NASA Astrophysics Data System (ADS)

Lørup, Jens Kristian; Refsgaard, Jens Christian; Mazvimavi, Dominic

1998-03-01

The purpose of this study was to identify and assess long-term impacts of land use change on catchment runoff in semi-arid Zimbabwe, based on analyses of long hydrological time series (25-50 years) from six medium-sized (200-1000 km 2) non-experimental rural catchments. A methodology combining common statistical methods with hydrological modelling was adopted in order to distinguish between the effects of climate variability and the effects of land use change. The hydrological model (NAM) was in general able to simulate the observed hydrographs very well during the reference period, thus providing a means to account for the effects of climate variability and hence strengthening the power of the subsequent statistical tests. In the test period the validated model was used to provide the runoff record which would have occurred in the absence of land use change. The analyses indicated a decrease in the annual runoff for most of the six catchments, with the largest changes occurring for catchments located within communal land, where large increases in population and agricultural intensity have taken place. However, the decrease was only statistically significant at the 5% level for one of the catchments.

Assessment of Irrigation Physics in a Land Surface Modeling Framework Using Non-Traditional and Human-Practice Datasets

NASA Technical Reports Server (NTRS)

Lawston, Patricia M.; Santanello, Joseph A.; Rodell, Matthew; Franz, Trenton E.

2017-01-01

Irrigation increases soil moisture, which in turn controls water and energy fluxes from the land surface to the10 planetary boundary layer and determines plant stress and productivity. Therefore, developing a realistic representation of irrigation is critical to understanding land-atmosphere interactions in agricultural areas. Irrigation parameterizations are becoming more common in land surface models and are growing in sophistication, but there is difficulty in assessing the realism of these schemes, due to limited observations (e.g., soil moisture, evapotranspiration) and scant reporting of irrigation timing and quantity. This study uses the Noah land surface model run at high resolution within NASAs Land15 Information System to assess the physics of a sprinkler irrigation simulation scheme and model sensitivity to choice of irrigation intensity and greenness fraction datasets over a small, high resolution domain in Nebraska. Differences between experiments are small at the interannual scale but become more apparent at seasonal and daily time scales. In addition, this study uses point and gridded soil moisture observations from fixed and roving Cosmic Ray Neutron Probes and co-located human practice data to evaluate the realism of irrigation amounts and soil moisture impacts simulated by the model. Results20 show that field-scale heterogeneity resulting from the individual actions of farmers is not captured by the model and the amount of irrigation applied by the model exceeds that applied at the two irrigated fields. However, the seasonal timing of irrigation and soil moisture contrasts between irrigated and non-irrigated areas are simulated well by the model. Overall, the results underscore the necessity of both high-quality meteorological forcing data and proper representation of irrigation foraccurate simulation of water and energy states and fluxes over cropland.

Topographic variables improve climate models of forage species abundance in the northeastern United States

USDA-ARS?s Scientific Manuscript database

Species distribution modeling has most commonly been applied to presence-only data and to woody species, but detailed predicted abundance maps for forage species would be of great value for agricultural management and land use planning. We used field data from 107 farms across the northeastern Unite...

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.

Modeling Land Use Change in the Chesapeake Bay Watershed

NASA Astrophysics Data System (ADS)

Claire, J. A.; Goetz, S. J.; Bockstael, N.

2003-12-01

Low density, decentralized residential and commercial development is increasingly the dominant pattern of exurban land use in many developed countries, particularly the United States. The term "sprawl" is now commonly used to describe this form of development, the environmental and quality-of-life impacts of which are becoming central to debates over land use in urban and suburban areas. Continued poor health of the Chesapeake Bay, located in the Mid-Atlantic region of the United States, is due in part to disruptions in the hydrological system caused by urban and suburban development throughout the 167,000 square kilometer watershed. We present results of a spatial predictive model of land use change based on cellular automata (SLEUTH), which was calibrated using high resolution (30m cell size) maps of the built environment derived from Landsat ETM+ imagery for the period 1986-2000. The model was applied to a 23,740 square kilometer area centered on Washington DC - Baltimore MD, and predictions were made out to 2030 assuming three different policy scenarios (current trends, managed growth, and "sustainable"). Accuracy of the model was assessed at three scales (pixel, watershed and county) and overall strengths and weaknesses of the model are presented, particularly in comparison to other econometric modeling approaches.

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.

Variability and Predictability of Land-Atmosphere Interactions: Observational and Modeling Studies

NASA Technical Reports Server (NTRS)

Roads, John; Oglesby, Robert; Marshall, Susan; Robertson, Franklin R.

2002-01-01

The overall goal of this project is to increase our understanding of seasonal to interannual variability and predictability of atmosphere-land interactions. The project objectives are to: 1. Document the low frequency variability in land surface features and associated water and energy cycles from general circulation models (GCMs), observations and reanalysis products. 2. Determine what relatively wet and dry years have in common on a region-by-region basis and then examine the physical mechanisms that may account for a significant portion of the variability. 3. Develop GCM experiments to examine the hypothesis that better knowledge of the land surface enhances long range predictability. This investigation is aimed at evaluating and predicting seasonal to interannual variability for selected regions emphasizing the role of land-atmosphere interactions. Of particular interest are the relationships between large, regional and local scales and how they interact to account for seasonal and interannual variability, including extreme events such as droughts and floods. North and South America, including the Global Energy and Water Cycle Experiment Continental International Project (GEWEX GCIP), MacKenzie, and LBA basins, are currently being emphasized. We plan to ultimately generalize and synthesize to other land regions across the globe, especially those pertinent to other GEWEX projects.

Can Geoengineering Effectively Reduce the Land Warming?

NASA Astrophysics Data System (ADS)

Wang, W.; MacMartin, D.; Moore, J. C.; Ji, D.

2017-12-01

Permafrost, defined as ground that remains at or below 0 C for two or more consecutive years, underlies 24% of the land in the Northern Hemisphere. Under recent climate warming, permafrost has begun to thaw, causing changes in ecosystems and impacting northern communities. Using the multiple land model output from the Permafrost Carbon Network and applying 5 commonly used permafrost diagnostic methods, we assess the projected Northern Hemisphere permafrost area under RCP 8.5 scenario. Both the air and soil relative warming change is compared to highlight the soil warming pattern and intensity. Using the multiple Earth System Models output under abrupt 4×CO2, G1, PI-control, G3, G4, and RCP4.5 experiments, a preliminary attempt is also performed to examine the effectiveness of geoengineering schemes on reducing the land warming. Although there is uncertainty in the projected results due to model and method difference, the soil temperature based methods derived permafrost all present an intense decrease by 48% - 68% until 2100. The projected soil temperature by the more physically complicated model shows a different warming pattern compared with the air, which indicates that some potential land process intervene with the land response to atmospheric change. The simulated soil temperature can be effectively cooled down by 2 - 9 degree under G1 compared with abrupt 4×CO2, and by less than 4 degree under G3 and G4 compared with RCP4.5.

Life cycle assessment needs predictive spatial modelling for biodiversity and ecosystem services

PubMed Central

Chaplin-Kramer, Rebecca; Sim, Sarah; Hamel, Perrine; Bryant, Benjamin; Noe, Ryan; Mueller, Carina; Rigarlsford, Giles; Kulak, Michal; Kowal, Virginia; Sharp, Richard; Clavreul, Julie; Price, Edward; Polasky, Stephen; Ruckelshaus, Mary; Daily, Gretchen

2017-01-01

International corporations in an increasingly globalized economy exert a major influence on the planet's land use and resources through their product design and material sourcing decisions. Many companies use life cycle assessment (LCA) to evaluate their sustainability, yet commonly-used LCA methodologies lack the spatial resolution and predictive ecological information to reveal key impacts on climate, water and biodiversity. We present advances for LCA that integrate spatially explicit modelling of land change and ecosystem services in a Land-Use Change Improved (LUCI)-LCA. Comparing increased demand for bioplastics derived from two alternative feedstock-location scenarios for maize and sugarcane, we find that the LUCI-LCA approach yields results opposite to those of standard LCA for greenhouse gas emissions and water consumption, and of different magnitudes for soil erosion and biodiversity. This approach highlights the importance of including information about where and how land-use change and related impacts will occur in supply chain and innovation decisions. PMID:28429710

Life cycle assessment needs predictive spatial modelling for biodiversity and ecosystem services

NASA Astrophysics Data System (ADS)

Chaplin-Kramer, Rebecca; Sim, Sarah; Hamel, Perrine; Bryant, Benjamin; Noe, Ryan; Mueller, Carina; Rigarlsford, Giles; Kulak, Michal; Kowal, Virginia; Sharp, Richard; Clavreul, Julie; Price, Edward; Polasky, Stephen; Ruckelshaus, Mary; Daily, Gretchen

2017-04-01

International corporations in an increasingly globalized economy exert a major influence on the planet's land use and resources through their product design and material sourcing decisions. Many companies use life cycle assessment (LCA) to evaluate their sustainability, yet commonly-used LCA methodologies lack the spatial resolution and predictive ecological information to reveal key impacts on climate, water and biodiversity. We present advances for LCA that integrate spatially explicit modelling of land change and ecosystem services in a Land-Use Change Improved (LUCI)-LCA. Comparing increased demand for bioplastics derived from two alternative feedstock-location scenarios for maize and sugarcane, we find that the LUCI-LCA approach yields results opposite to those of standard LCA for greenhouse gas emissions and water consumption, and of different magnitudes for soil erosion and biodiversity. This approach highlights the importance of including information about where and how land-use change and related impacts will occur in supply chain and innovation decisions.

Digital terrain modeling

NASA Astrophysics Data System (ADS)

Wilson, John P.

2012-01-01

This article examines how the methods and data sources used to generate DEMs and calculate land surface parameters have changed over the past 25 years. The primary goal is to describe the state-of-the-art for a typical digital terrain modeling workflow that starts with data capture, continues with data preprocessing and DEM generation, and concludes with the calculation of one or more primary and secondary land surface parameters. The article first describes some of ways in which LiDAR and RADAR remote sensing technologies have transformed the sources and methods for capturing elevation data. It next discusses the need for and various methods that are currently used to preprocess DEMs along with some of the challenges that confront those who tackle these tasks. The bulk of the article describes some of the subtleties involved in calculating the primary land surface parameters that are derived directly from DEMs without additional inputs and the two sets of secondary land surface parameters that are commonly used to model solar radiation and the accompanying interactions between the land surface and the atmosphere on the one hand and water flow and related surface processes on the other. It concludes with a discussion of the various kinds of errors that are embedded in DEMs, how these may be propagated and carried forward in calculating various land surface parameters, and the consequences of this state-of-affairs for the modern terrain analyst.

Climatic effects of large-scale deforestation in Earth System Models

NASA Astrophysics Data System (ADS)

Brovkin, V.; Boysen, L.; Pongratz, J.

2017-12-01

Processes in terrestrial ecosystems, to a large extent, are controlled by climate and CO2 concentration. In turn, geographical distribution of vegetation cover strongly affects heat, moisture, and momentum fluxes between land surface and atmosphere (biogeophysical effects). Anthropogenic land use and land cover changes (LULCC) are now included into Earth System Models (ESMs) in the form of historical and hypothetical future scenarios as a forcing in the Coupled Model Intercomparison project, phase 6 (CMIP6). A propagation of climatic effects from land to the ocean in ESMs allows to investigate a global climate response to LULCC in addition to analysis of local effects over deforested land. One complication in the analysis of global climatic effects of historical and future LULCC scenarios is their relatively small amplitude. To increase the signal-to-noise ratio, the Land Use Model Intercomparison Project (LUMIP) suggested an idealized deforestation simulation following a prototype of 1%-CO2 increase experiment commonly used in CMIPs. The idealized experiment allows to investigate - in a harmonized way across models - a response of land surface biophysics and climate to a large-scale deforestation of 20 million km2 distributed over the most forested parts of globe. The forest is removed linearly over a period of 50 years, with an additional 30 years with no specified change in forest cover. Boundary conditions such as CO2 concentration and other forcings are kept at the pre-industrial level. We will present results of idealized deforestation experiments and other sensitivity runs with the CMIP6-version of MPI-ESM, which will be part of the later multi-model comparison. A special focus will be put on less well investigated aspects of LULCC that the idealized setup is particularly well suited for studying, such as non-linearities of the model response to the deforestation forcing and detectability of the signal over time.

FARSITE: a fire area simulator for fire managers

Treesearch

Mark A. Finney

1995-01-01

A fire growth model (FARSITE) has been developed for use on personal computers (PC’s). Because PC’s are commonly used by land and fire managers, this portable platform would be an accustomed means to bring fire growth modeling technology to management applications. The FARSITE model is intended for use in projecting the growth of prescribed natural fires for wilderness...

78 FR 12651 - Airworthiness Directives; Agusta S.p.A. Helicopters

Federal Register 2010, 2011, 2012, 2013, 2014

2013-02-25

.... Discussion On June 12, 2002, a T/R blade on an Agusta Model 119 helicopter failed and resulted in an autorotative landing. As a result of this failure, based on the commonality of the T/R blades on the model 109E... applies to Agusta Model 109E helicopters with tail rotor (T/R) hub and blade assembly, part number (P/N...

Can private land conservation reduce wildfire risk to homes? A case study in San Diego County, California, USA

USGS Publications Warehouse

Butsic, Van; Syphard, Alexandra D.; Keeley, Jon E.; Bar-Massada, Avi

2017-01-01

The purchase of private land for conservation purposes is a common way to prevent the exploitation of sensitive ecological areas. However, private land conservation can also provide other benefits, one of these being natural hazard reduction. Here, we investigated the impacts of private land conservation on fire risk to homes in San Diego County, California. We coupled an econometric land use change model with a model that estimates the probability of house loss due to fire in order to compare fire risk at the county and municipality scale under alternative private land purchasing schemes and over a 20 year time horizon. We found that conservation purchases could reduce fire risk on this landscape, and the amount of risk reduction was related to the targeting approach used to choose which parcels were conserved. Conservation land purchases that targeted parcels designated as high fire hazard resulted in lower fire risk to homes than purchases that targeted low costs or high likelihood to subdivide. This result was driven by (1) preventing home placement in fire prone areas and (2) taking land off the market, and hence increasing development densities in other areas. These results raise the possibility that resource conservation and fire hazard reduction may benefit from combining efforts. With adequate planning, future conservation purchases could have synergistic effects beyond just protecting ecologically sensitive areas.

Modeling crop residue burning experiments to evaluate smoke emissions and plume transport

Treesearch

Luxi Zhou; Kirk R. Baker; Sergey L. Napelenok; George Pouliot; Robert Elleman; Susan M. O' Neill; Shawn P. Urbanski; David C. Wong

2018-01-01

Crop residue burning is a common land management practice that results in emissions of a variety of pollutants with negative health impacts. Modeling systems are used to estimate air quality impacts of crop residue burning to support retrospective regulatory assessments and also for forecasting purposes. Ground and airborne measurements from a recent field experiment...

Collective decision making in cohesive flocks

NASA Astrophysics Data System (ADS)

Bhattacharya, K.; Vicsek, Tamás

2010-09-01

Most of us must have been fascinated by the eye-catching displays of collectively moving animals. Schools of fish can move in a rather orderly fashion and then change direction amazingly abruptly. There are a large number of further examples both from the living and the non-living world for phenomena during which the many interacting, permanently moving units seem to arrive at a common behavioural pattern taking place in a short time. As a paradigm of this type of phenomena we consider the problem of how birds arrive at a decision resulting in their synchronized landing. We introduce a simple model to interpret this process. Collective motion prior to landing is modelled using a simple self-propelled particle (SPP) system with a new kind of boundary condition, while the tendency and the sudden propagation of the intention of landing are introduced through rules analogous to the random field Ising model in an external field. We show that our approach is capable of capturing the most relevant features of collective decision making in a system of units with variance of individual intentions and being under an increasing level of pressure to switch states. We find that as a function of the few parameters of our model the collective switching from the flying to the landing state is indeed much sharper than the distribution of individual landing intentions. The transition is accompanied by a number of interesting features discussed in this paper.

SUMMA and Model Mimicry: Understanding Differences Among Land Models

NASA Astrophysics Data System (ADS)

Nijssen, B.; Nearing, G. S.; Ou, G.; Clark, M. P.

2016-12-01

Model inter-comparison and model ensemble experiments suffer from an inability to explain the mechanisms behind differences in model outcomes. We can clearly demonstrate that the models are different, but we cannot necessarily identify the reasons why, because most models exhibit myriad differences in process representations, model parameterizations, model parameters and numerical solution methods. This inability to identify the reasons for differences in model performance hampers our understanding and limits model improvement, because we cannot easily identify the most promising paths forward. We have developed the Structure for Unifying Multiple Modeling Alternatives (SUMMA) to allow for controlled experimentation with model construction, numerical techniques, and parameter values and therefore isolate differences in model outcomes to specific choices during the model development process. In developing SUMMA, we recognized that hydrologic models can be thought of as individual instantiations of a master modeling template that is based on a common set of conservation equations for energy and water. Given this perspective, SUMMA provides a unified approach to hydrologic modeling that integrates different modeling methods into a consistent structure with the ability to instantiate alternative hydrologic models at runtime. Here we employ SUMMA to revisit a previous multi-model experiment and demonstrate its use for understanding differences in model performance. Specifically, we implement SUMMA to mimic the spread of behaviors exhibited by the land models that participated in the Protocol for the Analysis of Land Surface Models (PALS) Land Surface Model Benchmarking Evaluation Project (PLUMBER) and draw conclusions about the relative performance of specific model parameterizations for water and energy fluxes through the soil-vegetation continuum. SUMMA's ability to mimic the spread of model ensembles and the behavior of individual models can be an important tool in focusing model development and improvement efforts.

The Impact of Parametric Uncertainties on Biogeochemistry in the E3SM Land Model

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

Ricciuto, Daniel; Sargsyan, Khachik; Thornton, Peter

We conduct a global sensitivity analysis (GSA) of the Energy Exascale Earth System Model (E3SM), land model (ELM) to calculate the sensitivity of five key carbon cycle outputs to 68 model parameters. This GSA is conducted by first constructing a Polynomial Chaos (PC) surrogate via new Weighted Iterative Bayesian Compressive Sensing (WIBCS) algorithm for adaptive basis growth leading to a sparse, high-dimensional PC surrogate with 3,000 model evaluations. The PC surrogate allows efficient extraction of GSA information leading to further dimensionality reduction. The GSA is performed at 96 FLUXNET sites covering multiple plant functional types (PFTs) and climate conditions. Aboutmore » 20 of the model parameters are identified as sensitive with the rest being relatively insensitive across all outputs and PFTs. These sensitivities are dependent on PFT, and are relatively consistent among sites within the same PFT. The five model outputs have a majority of their highly sensitive parameters in common. A common subset of sensitive parameters is also shared among PFTs, but some parameters are specific to certain types (e.g., deciduous phenology). In conclusion, the relative importance of these parameters shifts significantly among PFTs and with climatic variables such as mean annual temperature.« less

The Impact of Parametric Uncertainties on Biogeochemistry in the E3SM Land Model

DOE PAGES

Ricciuto, Daniel; Sargsyan, Khachik; Thornton, Peter

2018-02-27

We conduct a global sensitivity analysis (GSA) of the Energy Exascale Earth System Model (E3SM), land model (ELM) to calculate the sensitivity of five key carbon cycle outputs to 68 model parameters. This GSA is conducted by first constructing a Polynomial Chaos (PC) surrogate via new Weighted Iterative Bayesian Compressive Sensing (WIBCS) algorithm for adaptive basis growth leading to a sparse, high-dimensional PC surrogate with 3,000 model evaluations. The PC surrogate allows efficient extraction of GSA information leading to further dimensionality reduction. The GSA is performed at 96 FLUXNET sites covering multiple plant functional types (PFTs) and climate conditions. Aboutmore » 20 of the model parameters are identified as sensitive with the rest being relatively insensitive across all outputs and PFTs. These sensitivities are dependent on PFT, and are relatively consistent among sites within the same PFT. The five model outputs have a majority of their highly sensitive parameters in common. A common subset of sensitive parameters is also shared among PFTs, but some parameters are specific to certain types (e.g., deciduous phenology). In conclusion, the relative importance of these parameters shifts significantly among PFTs and with climatic variables such as mean annual temperature.« less

Integrating spatially explicit representations of landscape perceptions into land change research

USGS Publications Warehouse

Dorning, Monica; Van Berkel, Derek B.; Semmens, Darius J.

2017-01-01

Purpose of ReviewHuman perceptions of the landscape can influence land-use and land-management decisions. Recognizing the diversity of landscape perceptions across space and time is essential to understanding land change processes and emergent landscape patterns. We summarize the role of landscape perceptions in the land change process, demonstrate advances in quantifying and mapping landscape perceptions, and describe how these spatially explicit techniques have and may benefit land change research.Recent FindingsMapping landscape perceptions is becoming increasingly common, particularly in research focused on quantifying ecosystem services provision. Spatial representations of landscape perceptions, often measured in terms of landscape values and functions, provide an avenue for matching social and environmental data in land change studies. Integrating these data can provide new insights into land change processes, contribute to landscape planning strategies, and guide the design and implementation of land change models.SummaryChallenges remain in creating spatial representations of human perceptions. Maps must be accompanied by descriptions of whose perceptions are being represented and the validity and uncertainty of those representations across space. With these considerations, rapid advancements in mapping landscape perceptions hold great promise for improving representation of human dimensions in landscape ecology and land change research.

Sand Impact Tests of a Half-Scale Crew Module Boilerplate Test Article

NASA Technical Reports Server (NTRS)

Vassilakos, Gregory J.; Hardy, Robin C.

2012-01-01

Although the Orion Multi-Purpose Crew Vehicle (MPCV) is being designed primarily for water landings, a further investigation of launch abort scenarios reveals the possibility of an onshore landing at Kennedy Space Center (KSC). To gather data for correlation against simulations of beach landing impacts, a series of sand impact tests were conducted at NASA Langley Research Center (LaRC). Both vertical drop tests and swing tests with combined vertical and horizontal velocity were performed onto beds of common construction-grade sand using a geometrically scaled crew module boilerplate test article. The tests were simulated using the explicit, nonlinear, transient dynamic finite element code LS-DYNA. The material models for the sand utilized in the simulations were based on tests of sand specimens. Although the LSDYNA models provided reasonable predictions for peak accelerations, they were not always able to track the response through the duration of the impact. Further improvements to the material model used for the sand were identified based on results from the sand specimen tests.

Developing and Testing a 3d Cadastral Data Model a Case Study in Australia

NASA Astrophysics Data System (ADS)

Aien, A.; Kalantari, M.; Rajabifard, A.; Williamson, I. P.; Shojaei, D.

2012-07-01

Population growth, urbanization and industrialization place more pressure on land use with the need for increased space. To extend the use and functionality of the land, complex infrastructures are being built, both vertically and horizontally, layered and stacked. These three-dimensional (3D) developments affect the interests (Rights, Restrictions, and Responsibilities (RRRs)) attached to the underlying land. A 3D cadastre will assist in managing the effects of 3D development on a particular extent of land. There are many elements that contribute to developing a 3D cadastre, such as existing of 3D property legislations, 3D DBMS, 3D visualization. However, data modelling is one of the most important elements of a successful 3D cadastre. As architectural models of houses and high rise buildings help their users visualize the final product, 3D cadastre data model supports 3D cadastre users to understand the structure or behavior of the system and has a template that guides them to construct and implement the 3D cadastre. Many jurisdictions, organizations and software developers have built their own cadastral data model. Land Administration Domain Model (DIS-ISO 19152, The Netherlands) and ePlan (Intergovernmental Committee on Surveying and Mapping, Australia) are examples of existing data models. The variation between these data models is the result of different attitudes towards cadastres. However, there is a basic common thread among them all. Current cadastral data models use a 2D land-parcel concept and extend it to support 3D requirements. These data models cannot adequately manage and represent the spatial extent of 3D RRRs. Most of the current cadastral data models have been influenced by a very broad understanding of 3D cadastral concepts because better clarity in what needs to be represented and analysed in the cadastre needs to be established. This paper presents the first version of a 3D Cadastral Data Model (3DCDM_Version 1.0). 3DCDM models both the legal and physical extent of 3D properties and associated interests. The data model extends the traditional cadastral requirements to cover other applications such as urban planning and land valuation and taxation. A demonstration of a test system on the proposed data model is also presented. The test is based on a case study in Victoria, Australia to evaluate the effectiveness of the data model.

Spatial Modeling of Agricultural Land-Use Change at Global Scale

NASA Astrophysics Data System (ADS)

Meiyappan, Prasanth; Dalton, Michael; O'Neill, Brian C.; Jain, Atul K.

2013-12-01

Land use is both a source and consequence of climate change. Long-term modeling of land use is central in global scale assessments using Integrated Assessment Models (IAMs) to explore policy alternatives; especially because adaptation and mitigation of climate change requires long-term commitment. We present a land-use change modeling framework that can reproduce the past 100 years of evolution of global cropland and pastureland patterns to a reasonable accuracy. The novelty of our approach underlies in integrating knowledge from both the observed behavior and economic rationale behind land-use decisions, thereby making up for the intrinsic deficits in both the disciplines. The underlying economic rationale is profit maximization of individual landowners that implicitly reflects local-level decisions-making process at a larger scale. Observed behavior based on examining the relationships between contemporary land-use patterns and its socioeconomic and biophysical drivers, enters as an explicit factor into the economic framework. The land-use allocation is modified by autonomous developments and competition between land-use types. The framework accounts for spatial heterogeneity in the nature of driving factors across geographic regions. The model is currently configured to downscale continental-scale aggregate land-use information to region specific changes in land-use patterns (0.5-deg spatial resolution). The temporal resolution is one year. The historical validation experiment is facilitated by synthesizing gridded maps of a wide range of potential biophysical and socioeconomic driving factors for the 20th century. To our knowledge, this is the first retrospective analysis that has been successful in reproducing the historical experience at a global scale. We apply the method to gain useful insights on two questions: (1) what are the dominant socioeconomic and biophysical driving factors of contemporary cropland and pastureland patterns, across geographic regions, and (2) the impacts of various driving factors on shaping the cropland and pastureland patterns over the 20th century. Specifically, we focus on the causes of changes in land-use patterns in certain key regions of the world, such as the abandonment of cropland in the eastern US and a subsequent expansion to the mid-west US. This presentation will focus on the scientific basis behind the developed framework and motivations behind selecting specific statistical techniques to implement the scientific theory. Specifically, we will highlight the application of recently developed statistical techniques that are highly efficient in dealing with problems such as spatial autocorrelation and multicollinearity that are common in land-change studies. However, these statistical techniques have largely been confined to medical literature. We will present the validation results and an example application of the developed framework within an IAM. The presented framework provides a benchmark for long-term spatial modeling of land use that will benefit the IAM, land use and the Earth system modeling communities.

Antagonist muscle co-contraction during a double-leg landing maneuver at two heights.

PubMed

Mokhtarzadeh, Hossein; Yeow, Chen Hua; Goh, James Cho Hong; Oetomo, Denny; Ewing, Katie; Lee, Peter Vee Sin

2017-10-01

Knee injuries are common during landing activities. Greater landing height increases peak ground reaction forces (GRFs) and loading at the knee joint. As major muscles to stabilize the knee joint, Quadriceps and Hamstring muscles provide internal forces to attenuate the excessive GRF. Despite the number of investigations on the importance of muscle function during landing, the role of landing height on these muscles forces using modeling during landing is not fully investigated. Participant-specific musculoskeletal models were developed using experimental motion analysis data consisting of anatomic joint motions and GRF from eight male participants performing double-leg drop landing from 30 and 60 cm. Muscle forces were calculated in OpenSim and their differences were analyzed at the instances of high risk during landing i.e. peak GRF for both heights. The maximum knee flexion angle and moments were found significantly higher from a double-leg landing at 60 cm compared to 30 cm. The results showed elevated GRF, and mean muscle forces during landing. At peak GRF, only quadriceps showed significantly greater forces at 60 cm. Hamstring muscle forces did not significantly change at 60 cm compared to 30 cm. Quadriceps and hamstring muscle forces changed at different heights. Since hamstring forces were similar in both landing heights, this could lead to an imbalance between the antagonist muscles, potentially placing the knee at risk of injury if combined with small flexion angles that was not observed at peak GRF in our study. Thus, enhanced neuromuscular training programs strengthening the hamstrings may be required to address this imbalance. These findings may contribute to enhance neuromuscular training programs to prevent knee injuries during landing.

Hydrological excitation of polar motion by different variables of the GLDAS models

NASA Astrophysics Data System (ADS)

Wińska, Małgorzata; Nastula, Jolanta

Continental hydrological loading, by land water, snow, and ice, is an element that is strongly needed for a full understanding of the excitation of polar motion. In this study we compute different estimations of hydrological excitation functions of polar motion (Hydrological Angular Momentum - HAM) using various variables from the Global Land Data Assimilation System (GLDAS) models of land hydrosphere. The main aim of this study is to show the influence of different variables for example: total evapotranspiration, runoff, snowmelt, soil moisture to polar motion excitations in annual and short term scale. In our consideration we employ several realizations of the GLDAS model as: GLDAS Common Land Model (CLM), GLDAS Mosaic Model, GLDAS National Centers for Environmental Prediction/Oregon State University/Air Force/Hydrologic Research Lab Model (Noah), GLDAS Variable Infiltration Capacity (VIC) Model. Hydrological excitation functions of polar motion, both global and regional, are determined by using selected variables of these GLDAS realizations. First we compare a timing, spectra and phase diagrams of different regional and global HAMs with each other. Next, we estimate, the hydrological signal in geodetically observed polar motion excitation by subtracting the atmospheric -- AAM (pressure + wind) and oceanic -- OAM (bottom pressure + currents) contributions. Finally, the hydrological excitations are compared to these hydrological signal in observed polar motion excitation series. The results help us understand which variables of considered hydrological models are the most important for the polar motion excitation and how well we can close polar motion excitation budget in the seasonal and inter-annual spectral ranges.

Global Land Use Regression Model for Nitrogen Dioxide Air Pollution.

PubMed

Larkin, Andrew; Geddes, Jeffrey A; Martin, Randall V; Xiao, Qingyang; Liu, Yang; Marshall, Julian D; Brauer, Michael; Hystad, Perry

2017-06-20

Nitrogen dioxide is a common air pollutant with growing evidence of health impacts independent of other common pollutants such as ozone and particulate matter. However, the worldwide distribution of NO 2 exposure and associated impacts on health is still largely uncertain. To advance global exposure estimates we created a global nitrogen dioxide (NO 2 ) land use regression model for 2011 using annual measurements from 5,220 air monitors in 58 countries. The model captured 54% of global NO 2 variation, with a mean absolute error of 3.7 ppb. Regional performance varied from R 2 = 0.42 (Africa) to 0.67 (South America). Repeated 10% cross-validation using bootstrap sampling (n = 10,000) demonstrated a robust performance with respect to air monitor sampling in North America, Europe, and Asia (adjusted R 2 within 2%) but not for Africa and Oceania (adjusted R 2 within 11%) where NO 2 monitoring data are sparse. The final model included 10 variables that captured both between and within-city spatial gradients in NO 2 concentrations. Variable contributions differed between continental regions, but major roads within 100 m and satellite-derived NO 2 were consistently the strongest predictors. The resulting model can be used for global risk assessments and health studies, particularly in countries without existing NO 2 monitoring data or models.

Evaluating the Impact of Land Use Change on Submerged Aquatic Vegetation Stressors in Mobile Bay

NASA Technical Reports Server (NTRS)

Al-Hamdan, Mohammad; Estes, Maurice G., Jr.; Quattrochi, Dale; Thom, Ronald; Woodruff, Dana; Judd, Chaeli; Ellis, Jean; Watson, Brian; Rodriquez, Hugo; Johnson, Hoyt

2009-01-01

Alabama coastal systems have been subjected to increasing pressure from a variety of activities including urban and rural development, shoreline modifications, industrial activities, and dredging of shipping and navigation channels. The impacts on coastal ecosystems are often observed through the use of indicator species. One such indicator species for aquatic ecosystem health is submerged aquatic vegetation (SAV). Watershed and hydrodynamic modeling has been performed to evaluate the impact of land use change in Mobile and Baldwin counties on SAV stressors and controlling factors (temperature, salinity, and sediment) in Mobile Bay. Watershed modeling using the Loading Simulation Package in C++ (LSPC) was performed for all watersheds contiguous to Mobile Bay for land use scenarios in 1948, 1992, 2001, and 2030. Landsat-derived National Land Cover Data (NLCD) were used in the 1992 and 2001 simulations after having been reclassified to a common classification scheme. The Prescott Spatial Growth Model was used to project the 2030 land use scenario based on current trends. The LSPC model simulations provided output on changes in flow, temperature, and sediment for 22 discharge points into the Bay. Theses results were inputted in the Environmental Fluid Dynamics Computer Code (EFDC) hydrodynamic model to generate data on changes in temperature, salinity, and sediment on a grid with four vertical profiles throughout Mobile Bay. The changes in the aquatic ecosystem were used to perform an ecological analysis to evaluate the impact on SAV habitat suitability. This is the key product benefiting the Mobile Bay coastal environmental managers that integrates the influences of temperature, salinity, and sediment due to land use driven flow changes with the restoration potential of SAVs.

Divergent projections of future land use in the United States arising from different models and scenarios

USGS Publications Warehouse

Sohl, Terry L.; Wimberly, Michael; Radeloff, Volker C.; Theobald, David M.; Sleeter, Benjamin M.

2016-01-01

A variety of land-use and land-cover (LULC) models operating at scales from local to global have been developed in recent years, including a number of models that provide spatially explicit, multi-class LULC projections for the conterminous United States. This diversity of modeling approaches raises the question: how consistent are their projections of future land use? We compared projections from six LULC modeling applications for the United States and assessed quantitative, spatial, and conceptual inconsistencies. Each set of projections provided multiple scenarios covering a period from roughly 2000 to 2050. Given the unique spatial, thematic, and temporal characteristics of each set of projections, individual projections were aggregated to a common set of basic, generalized LULC classes (i.e., cropland, pasture, forest, range, and urban) and summarized at the county level across the conterminous United States. We found very little agreement in projected future LULC trends and patterns among the different models. Variability among scenarios for a given model was generally lower than variability among different models, in terms of both trends in the amounts of basic LULC classes and their projected spatial patterns. Even when different models assessed the same purported scenario, model projections varied substantially. Projections of agricultural trends were often far above the maximum historical amounts, raising concerns about the realism of the projections. Comparisons among models were hindered by major discrepancies in categorical definitions, and suggest a need for standardization of historical LULC data sources. To capture a broader range of uncertainties, ensemble modeling approaches are also recommended. However, the vast inconsistencies among LULC models raise questions about the theoretical and conceptual underpinnings of current modeling approaches. Given the substantial effects that land-use change can have on ecological and societal processes, there is a need for improvement in LULC theory and modeling capabilities to improve acceptance and use of regional- to national-scale LULC projections for the United States and elsewhere.

Matrix approach to uncertainty assessment and reduction for modeling terrestrial carbon cycle

NASA Astrophysics Data System (ADS)

Luo, Y.; Xia, J.; Ahlström, A.; Zhou, S.; Huang, Y.; Shi, Z.; Wang, Y.; Du, Z.; Lu, X.

2017-12-01

Terrestrial ecosystems absorb approximately 30% of the anthropogenic carbon dioxide emissions. This estimate has been deduced indirectly: combining analyses of atmospheric carbon dioxide concentrations with ocean observations to infer the net terrestrial carbon flux. In contrast, when knowledge about the terrestrial carbon cycle is integrated into different terrestrial carbon models they make widely different predictions. To improve the terrestrial carbon models, we have recently developed a matrix approach to uncertainty assessment and reduction. Specifically, the terrestrial carbon cycle has been commonly represented by a series of carbon balance equations to track carbon influxes into and effluxes out of individual pools in earth system models. This representation matches our understanding of carbon cycle processes well and can be reorganized into one matrix equation without changing any modeled carbon cycle processes and mechanisms. We have developed matrix equations of several global land C cycle models, including CLM3.5, 4.0 and 4.5, CABLE, LPJ-GUESS, and ORCHIDEE. Indeed, the matrix equation is generic and can be applied to other land carbon models. This matrix approach offers a suite of new diagnostic tools, such as the 3-dimensional (3-D) parameter space, traceability analysis, and variance decomposition, for uncertainty analysis. For example, predictions of carbon dynamics with complex land models can be placed in a 3-D parameter space (carbon input, residence time, and storage potential) as a common metric to measure how much model predictions are different. The latter can be traced to its source components by decomposing model predictions to a hierarchy of traceable components. Then, variance decomposition can help attribute the spread in predictions among multiple models to precisely identify sources of uncertainty. The highly uncertain components can be constrained by data as the matrix equation makes data assimilation computationally possible. We will illustrate various applications of this matrix approach to uncertainty assessment and reduction for terrestrial carbon cycle models.

Spatial Predictive Modeling and Remote Sensing of Land Use Change in the Chesapeake Bay Watershed

NASA Technical Reports Server (NTRS)

Goetz, Scott J.; Bockstael, Nancy E.; Jantz, Claire A.

2005-01-01

This project was focused on modeling the processes by which increasing demand for developed land uses, brought about by changes in the regional economy and the socio-demographics of the region, are translated into a changing spatial pattern of land use. Our study focused on a portion of the Chesapeake Bay Watershed where the spatial patterns of sprawl represent a set of conditions generally prevalent in much of the U.S. Working in the region permitted us access to (i) a time-series of multi-scale and multi-temporal (including historical) satellite imagery and (ii) an established network of collaborating partners and agencies willing to share resources and to utilize developed techniques and model results. In addition, a unique parcel-level tax assessment database and linked parcel boundary maps exists for two counties in the Maryland portion of this region that made it possible to establish a historical cross-section time-series database of parcel level development decisions. Scenario analyses of future land use dynamics provided critical quantitative insight into the impact of alternative land management and policy decisions. These also have been specifically aimed at addressing growth control policies aimed at curbing exurban (sprawl) development. Our initial technical approach included three components: (i) spatial econometric modeling of the development decision, (ii) remote sensing of suburban change and residential land use density, including comparisons of past change from Landsat analyses and more traditional sources, and (iii) linkages between the two through variable initialization and supplementation of parcel level data. To these we added a fourth component, (iv) cellular automata modeling of urbanization, which proved to be a valuable addition to the project. This project has generated both remote sensing and spatially explicit socio-economic data to estimate and calibrate the parameters for two different types of land use change models and has undertaken analyses of these models. One (the CA model) is driven largely by observations on past patterns of land use change, while the other (the EC model) is driven by mechanisms of the land use change decision at the parcel level. Our project may be the first serious attempt at developing both types of models for the same area, using as much common data as possible. We have identified the strengths and weaknesses of the two approaches and plan to continue to revise each model in the light of new data and new lessons learned through continued collaboration. Questions, approaches, findings, publication and presentation lists concerning the research are also presented.

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.

A Comparison of Land Surface Model Soil Hydraulic Properties Estimated by Inverse Modeling and Pedotransfer Functions

NASA Technical Reports Server (NTRS)

Gutmann, Ethan D.; Small, Eric E.

2007-01-01

Soil hydraulic properties (SHPs) regulate the movement of water in the soil. This in turn plays an important role in the water and energy cycles at the land surface. At present, SHPS are commonly defined by a simple pedotransfer function from soil texture class, but SHPs vary more within a texture class than between classes. To examine the impact of using soil texture class to predict SHPS, we run the Noah land surface model for a wide variety of measured SHPs. We find that across a range of vegetation cover (5 - 80% cover) and climates (250 - 900 mm mean annual precipitation), soil texture class only explains 5% of the variance expected from the real distribution of SHPs. We then show that modifying SHPs can drastically improve model performance. We compare two methods of estimating SHPs: (1) inverse method, and (2) soil texture class. Compared to texture class, inverse modeling reduces errors between measured and modeled latent heat flux from 88 to 28 w/m(exp 2). Additionally we find that with increasing vegetation cover the importance of SHPs decreases and that the van Genuchten m parameter becomes less important, while the saturated conductivity becomes more important.

Extratropical Respones to Amazon Deforestation

NASA Astrophysics Data System (ADS)

Badger, A.; Dirmeyer, P.

2014-12-01

Land-use change (LUC) is known to impact local climate conditions through modifications of land-atmosphere interactions. Large-scale LUC, such as Amazon deforestation, could have a significant effect on the local and regional climates. The question remains as to what the global impact of large-scale LUC could be, as previous modeling studies have shown non-local responses due to Amazon deforestation. A common shortcoming in many previous modeling studies is the use of prescribed ocean conditions, which can act as a boundary condition to dampen the global response with respect to changes in the mean and variability. Using fully coupled modeling simulations with the Community Earth System Model version 1.2.0, the Amazon rainforest has been replaced with a distribution of representative tropical crops. Through the modifications of local land-atmosphere interactions, a significant change in the region, both at the surface and throughout the atmosphere, can be quantified. Accompanying these local changes are significant changes to the atmospheric circulation across all scales, thus modifying regional climates in other locales. Notable impacts include significant changes in precipitation, surface fluxes, basin-wide sea surface temperatures and ENSO behavior.

Refraction traveltime tomography based on damped wave equation for irregular topographic model

NASA Astrophysics Data System (ADS)

Park, Yunhui; Pyun, Sukjoon

2018-03-01

Land seismic data generally have time-static issues due to irregular topography and weathered layers at shallow depths. Unless the time static is handled appropriately, interpretation of the subsurface structures can be easily distorted. Therefore, static corrections are commonly applied to land seismic data. The near-surface velocity, which is required for static corrections, can be inferred from first-arrival traveltime tomography, which must consider the irregular topography, as the land seismic data are generally obtained in irregular topography. This paper proposes a refraction traveltime tomography technique that is applicable to an irregular topographic model. This technique uses unstructured meshes to express an irregular topography, and traveltimes calculated from the frequency-domain damped wavefields using the finite element method. The diagonal elements of the approximate Hessian matrix were adopted for preconditioning, and the principle of reciprocity was introduced to efficiently calculate the Fréchet derivative. We also included regularization to resolve the ill-posed inverse problem, and used the nonlinear conjugate gradient method to solve the inverse problem. As the damped wavefields were used, there were no issues associated with artificial reflections caused by unstructured meshes. In addition, the shadow zone problem could be circumvented because this method is based on the exact wave equation, which does not require a high-frequency assumption. Furthermore, the proposed method was both robust to an initial velocity model and efficient compared to full wavefield inversions. Through synthetic and field data examples, our method was shown to successfully reconstruct shallow velocity structures. To verify our method, static corrections were roughly applied to the field data using the estimated near-surface velocity. By comparing common shot gathers and stack sections with and without static corrections, we confirmed that the proposed tomography algorithm can be used to correct the statics of land seismic data.

Reducing uncertainty in dust monitoring to detect aeolian sediment transport responses to land cover change

NASA Astrophysics Data System (ADS)

Webb, N.; Chappell, A.; Van Zee, J.; Toledo, D.; Duniway, M.; Billings, B.; Tedela, N.

2017-12-01

Anthropogenic land use and land cover change (LULCC) influence global rates of wind erosion and dust emission, yet our understanding of the magnitude of the responses remains poor. Field measurements and monitoring provide essential data to resolve aeolian sediment transport patterns and assess the impacts of human land use and management intensity. Data collected in the field are also required for dust model calibration and testing, as models have become the primary tool for assessing LULCC-dust cycle interactions. However, there is considerable uncertainty in estimates of dust emission due to the spatial variability of sediment transport. Field sampling designs are currently rudimentary and considerable opportunities are available to reduce the uncertainty. Establishing the minimum detectable change is critical for measuring spatial and temporal patterns of sediment transport, detecting potential impacts of LULCC and land management, and for quantifying the uncertainty of dust model estimates. Here, we evaluate the effectiveness of common sampling designs (e.g., simple random sampling, systematic sampling) used to measure and monitor aeolian sediment transport rates. Using data from the US National Wind Erosion Research Network across diverse rangeland and cropland cover types, we demonstrate how only large changes in sediment mass flux (of the order 200% to 800%) can be detected when small sample sizes are used, crude sampling designs are implemented, or when the spatial variation is large. We then show how statistical rigour and the straightforward application of a sampling design can reduce the uncertainty and detect change in sediment transport over time and between land use and land cover types.

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.

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.

Are our dynamic water quality models too complex? A comparison of a new parsimonious phosphorus model, SimplyP, and INCA-P

NASA Astrophysics Data System (ADS)

Jackson-Blake, L. A.; Sample, J. E.; Wade, A. J.; Helliwell, R. C.; Skeffington, R. A.

2017-07-01

Catchment-scale water quality models are increasingly popular tools for exploring the potential effects of land management, land use change and climate change on water quality. However, the dynamic, catchment-scale nutrient models in common usage are complex, with many uncertain parameters requiring calibration, limiting their usability and robustness. A key question is whether this complexity is justified. To explore this, we developed a parsimonious phosphorus model, SimplyP, incorporating a rainfall-runoff model and a biogeochemical model able to simulate daily streamflow, suspended sediment, and particulate and dissolved phosphorus dynamics. The model's complexity was compared to one popular nutrient model, INCA-P, and the performance of the two models was compared in a small rural catchment in northeast Scotland. For three land use classes, less than six SimplyP parameters must be determined through calibration, the rest may be based on measurements, while INCA-P has around 40 unmeasurable parameters. Despite substantially simpler process-representation, SimplyP performed comparably to INCA-P in both calibration and validation and produced similar long-term projections in response to changes in land management. Results support the hypothesis that INCA-P is overly complex for the study catchment. We hope our findings will help prompt wider model comparison exercises, as well as debate among the water quality modeling community as to whether today's models are fit for purpose. Simpler models such as SimplyP have the potential to be useful management and research tools, building blocks for future model development (prototype code is freely available), or benchmarks against which more complex models could be evaluated.

Mapping moderate-scale land-cover over very large geographic areas within a collaborative framework: A case study of the Southwest Regional Gap Analysis Project (SWReGAP)

USGS Publications Warehouse

Lowry, J.; Ramsey, R.D.; Thomas, K.; Schrupp, D.; Sajwaj, T.; Kirby, J.; Waller, E.; Schrader, S.; Falzarano, S.; Langs, L.; Manis, G.; Wallace, C.; Schulz, K.; Comer, P.; Pohs, K.; Rieth, W.; Velasquez, C.; Wolk, B.; Kepner, W.; Boykin, K.; O'Brien, L.; Bradford, D.; Thompson, B.; Prior-Magee, J.

2007-01-01

Land-cover mapping efforts within the USGS Gap Analysis Program have traditionally been state-centered; each state having the responsibility of implementing a project design for the geographic area within their state boundaries. The Southwest Regional Gap Analysis Project (SWReGAP) was the first formal GAP project designed at a regional, multi-state scale. The project area comprises the southwestern states of Arizona, Colorado, Nevada, New Mexico, and Utah. The land-cover map/dataset was generated using regionally consistent geospatial data (Landsat ETM+ imagery (1999-2001) and DEM derivatives), similar field data collection protocols, a standardized land-cover legend, and a common modeling approach (decision tree classifier). Partitioning of mapping responsibilities amongst the five collaborating states was organized around ecoregion-based "mapping zones". Over the course of 21/2 field seasons approximately 93,000 reference samples were collected directly, or obtained from other contemporary projects, for the land-cover modeling effort. The final map was made public in 2004 and contains 125 land-cover classes. An internal validation of 85 of the classes, representing 91% of the land area was performed. Agreement between withheld samples and the validated dataset was 61% (KHAT = .60, n = 17,030). This paper presents an overview of the methodologies used to create the regional land-cover dataset and highlights issues associated with large-area mapping within a coordinated, multi-institutional management framework. ?? 2006 Elsevier Inc. All rights reserved.

Impacts of crop rotations on soil organic carbon sequestration

NASA Astrophysics Data System (ADS)

Gobin, Anne; Vos, Johan; Joris, Ingeborg; Van De Vreken, Philippe

2013-04-01

Agricultural land use and crop rotations can greatly affect the amount of carbon sequestered in the soil. We developed a framework for modelling the impacts of crop rotations on soil carbon sequestration at the field scale with test case Flanders. A crop rotation geo-database was constructed covering 10 years of crop rotation in Flanders using the IACS parcel registration (Integrated Administration and Control System) to elicit the most common crop rotation on major soil types in Flanders. In order to simulate the impact of crop cover on carbon sequestration, the Roth-C model was adapted to Flanders' environment and coupled to common crop rotations extracted from the IACS geodatabases and statistical databases on crop yield. Crop allometric models were used to calculate crop residues from common crops in Flanders and subsequently derive stable organic matter fluxes to the soil (REGSOM). The REGSOM model was coupled to Roth-C model was run for 30 years and for all combinations of seven main arable crops, two common catch crops and two common dosages of organic manure. The common crops are winter wheat, winter barley, sugar beet, potato, grain maize, silage maize and winter rapeseed; the catch crops are yellow mustard and Italian ryegrass; the manure dosages are 35 ton/ha cattle slurry and 22 ton/ha pig slurry. Four common soils were simulated: sand, loam, sandy loam and clay. In total more than 2.4 million simulations were made with monthly output of carbon content for 30 years. Results demonstrate that crop cover dynamics influence carbon sequestration for a very large percentage. For the same rotations carbon sequestration is highest on clay soils and lowest on sandy soils. Crop residues of grain maize and winter wheat followed by catch crops contribute largely to the total carbon sequestered. This implies that agricultural policies that impact on agricultural land management influence soil carbon sequestration for a large percentage. The framework is therefore suited for further scenario analysis and impact assessment in order to support agri-environmental policy decisions.

Development of multi-year land cover data to assess wildfire impacts to coastal watersheds and the nearshore environment

NASA Astrophysics Data System (ADS)

Morrison, Katherine D.

In the Mediterranean ecosystems of coastal California, wildfire is a common disturbance that can significantly alter vegetation in watersheds that transport sediment and nutrients to the adjacent nearshore oceanic environment. We assess the impact of two wildfires that burned in 2008 on land cover and to the nearshore environment along the Big Sur coast in central California. We created a multi-year land cover dataset to assess changes to coastal watersheds as a result of fire. This land cover dataset was then used to model changes in nonpoint source pollutants transported to the nearshore environment. Results indicate post-fire increases in percent export compared to pre-fire years and also link wildfire severity to the specific land cover changes that subsequently increase exports of pollutants and sediment to the nearshore environment. This approach is a replicable across watersheds and also provides a framework for including the nearshore environment as a value at risk terrestrial land management revolving around wildfire, including suppression, thinning, and other activities that change land cover at a landscape scale.

Microbial Source Module (MSM): Documenting the Science and Software for Discovery, Evaluation, and Integration

EPA Science Inventory

The Microbial Source Module (MSM) estimates microbial loading rates to land surfaces from non-point sources, and to streams from point sources for each subwatershed within a watershed. A subwatershed, the smallest modeling unit, represents the common basis for information consume...

Simulating the Interactions Among Land Use, Transportation ...

EPA Pesticide Factsheets

In most transportation studies, computer models that forecast travel behavior statistics for a future year use static projections of the spatial distribution of future population and employment growth as inputs. As a result, they are unable to account for the temporally dynamic and non-linear interactions among transportation, land use, and socioeconomic systems. System dynamics (SD) provides a common framework for modeling the complex interactions among transportation and other related systems. This study uses a SD model to simulate the cascading impacts of a proposed light rail transit (LRT) system in central North Carolina, USA. The Durham-Orange Light Rail Project (D-O LRP) SD model incorporates relationships among the land use, transportation, and economy sectors to simulate the complex feedbacks that give rise to the travel behavior changes forecasted by the region’s transportation model. This paper demonstrates the sensitivity of changes in travel behavior to the proposed LRT system and the assumptions that went into the transportation modeling, and compares those results to the impacts of an alternative fare-free transit system. SD models such as the D-O LRP SD model can complement transportation studies by providing valuable insight into the interdependent community systems that collectively contribute to travel behavior changes. Presented at the 35th International Conference of the System Dynamics Society in Cambridge, MA, July 18th, 2017

Watershed and Hydrodynamic Modeling for Evaluating the Impact of Land Use Change on Submerged Aquatic Vegetation and Seagrasses in Mobile Bay

NASA Technical Reports Server (NTRS)

Estes, Maurice G.; Al-Hamdan, Mohammed; Thom, Ron; Quattrochi, Dale; Woodruff, Dana; Judd, Chaeli; Ellism Jean; Watson, Brian; Rodriguez, Hugo; Johnson, Hoyt

2009-01-01

There is a continued need to understand how human activities along the northern Gulf of Mexico coast are impacting the natural ecosystems. The gulf coast is experiencing rapid population growth and associated land cover/land use change. Mobile Bay, AL is a designated pilot region of the Gulf of Mexico Alliance (GOMA) and is the focus area of many current NASA and NOAA studies, for example. This is a critical region, both ecologically and economically to the entire United States because it has the fourth largest freshwater inflow in the continental USA, is a vital nursery habitat for commercially and recreational important fisheries, and houses a working waterfront and port that is expanding. Watershed and hydrodynamic modeling has been performed for Mobile Bay to evaluate the impact of land use change in Mobile and Baldwin counties on the aquatic ecosystem. Watershed modeling using the Loading Simulation Package in C++ (LSPC) was performed for all watersheds contiguous to Mobile Bay for land use Scenarios in 1948, 1992, 2001, and 2030. The Prescott Spatial Growth Model was used to project the 2030 land use scenario based on observed trends. All land use scenarios were developed to a common land classification system developed by merging the 1992 and 2001 National Land Cover Data (NLCD). The LSPC model output provides changes in flow, temperature, sediments and general water quality for 22 discharge points into the Bay. These results were inputted in the Environmental Fluid Dynamics Computer Code (EFDC) hydrodynamic model to generate data on changes in temperature, salinity, and sediment concentrations on a grid with four vertical profiles throughout the Bay s aquatic ecosystems. The models were calibrated using in-situ data collected at sampling stations in and around Mobile bay. This phase of the project has focused on sediment modeling because of its significant influence on light attenuation which is a critical factor in the health of submerged aquatic vegetation. The impact of land use change on sediment concentrations was evaluated by analyzing the LSPC and EFDC sediment simulations for the four land use scenarios. Such analysis was also performed for storm and non-storm periods. In- situ data of total suspended sediments (TSS) and light attenuation were used to develop a regression model to estimate light attenuation from TSS. This regression model was used to derive marine light attenuation estimates throughout Mobile bay using the EFDC TSS outputs. The changes in sediment concentrations and associated impact on light attenuation in the aquatic ecosystem were used to perform an ecological analysis to evaluate the impact on seagreasses and Submerged Aquatic Vegetation (SAV) habitat. This is the key product benefiting the Mobile Bay coastal environmental managers that integrates the influences of sediments due to land use driven flow changes with the restoration potential of SAVs.

The managed clearing: An overlooked land-cover type in urbanizing regions?

PubMed Central

Madden, Marguerite; Gray, Josh; Meentemeyer, Ross K.

2018-01-01

Urban ecosystem assessments increasingly rely on widely available map products, such as the U.S. Geological Service (USGS) National Land Cover Database (NLCD), and datasets that use generic classification schemes to detect and model large-scale impacts of land-cover change. However, utilizing existing map products or schemes without identifying relevant urban class types such as semi-natural, yet managed land areas that account for differences in ecological functions due to their pervious surfaces may severely constrain assessments. To address this gap, we introduce the managed clearings land-cover type–semi-natural, vegetated land surfaces with varying degrees of management practices–for urbanizing landscapes. We explore the extent to which managed clearings are common and spatially distributed in three rapidly urbanizing areas of the Charlanta megaregion, USA. We visually interpreted and mapped fine-scale land cover with special attention to managed clearings using 2012 U.S. Department of Agriculture (USDA) National Agriculture Imagery Program (NAIP) images within 150 randomly selected 1-km2 blocks in the cities of Atlanta, Charlotte, and Raleigh, and compared our maps with National Land Cover Database (NLCD) data. We estimated the abundance of managed clearings relative to other land use and land cover types, and the proportion of land-cover types in the NLCD that are similar to managed clearings. Our study reveals that managed clearings are the most common land cover type in these cities, covering 28% of the total sampled land area– 6.2% higher than the total area of impervious surfaces. Managed clearings, when combined with forest cover, constitutes 69% of pervious surfaces in the sampled region. We observed variability in area estimates of managed clearings between the NAIP-derived and NLCD data. This suggests using high-resolution remote sensing imagery (e.g., NAIP) instead of modifying NLCD data for improved representation of spatial heterogeneity and mapping of managed clearings in urbanizing landscapes. Our findings also demonstrate the need to more carefully consider managed clearings and their critical ecological functions in landscape- to regional-scale studies of urbanizing ecosystems. PMID:29432442

The managed clearing: An overlooked land-cover type in urbanizing regions?

PubMed

Singh, Kunwar K; Madden, Marguerite; Gray, Josh; Meentemeyer, Ross K

2018-01-01

Urban ecosystem assessments increasingly rely on widely available map products, such as the U.S. Geological Service (USGS) National Land Cover Database (NLCD), and datasets that use generic classification schemes to detect and model large-scale impacts of land-cover change. However, utilizing existing map products or schemes without identifying relevant urban class types such as semi-natural, yet managed land areas that account for differences in ecological functions due to their pervious surfaces may severely constrain assessments. To address this gap, we introduce the managed clearings land-cover type-semi-natural, vegetated land surfaces with varying degrees of management practices-for urbanizing landscapes. We explore the extent to which managed clearings are common and spatially distributed in three rapidly urbanizing areas of the Charlanta megaregion, USA. We visually interpreted and mapped fine-scale land cover with special attention to managed clearings using 2012 U.S. Department of Agriculture (USDA) National Agriculture Imagery Program (NAIP) images within 150 randomly selected 1-km2 blocks in the cities of Atlanta, Charlotte, and Raleigh, and compared our maps with National Land Cover Database (NLCD) data. We estimated the abundance of managed clearings relative to other land use and land cover types, and the proportion of land-cover types in the NLCD that are similar to managed clearings. Our study reveals that managed clearings are the most common land cover type in these cities, covering 28% of the total sampled land area- 6.2% higher than the total area of impervious surfaces. Managed clearings, when combined with forest cover, constitutes 69% of pervious surfaces in the sampled region. We observed variability in area estimates of managed clearings between the NAIP-derived and NLCD data. This suggests using high-resolution remote sensing imagery (e.g., NAIP) instead of modifying NLCD data for improved representation of spatial heterogeneity and mapping of managed clearings in urbanizing landscapes. Our findings also demonstrate the need to more carefully consider managed clearings and their critical ecological functions in landscape- to regional-scale studies of urbanizing ecosystems.

TRADITIONAL USES OF PLANTS OF COMMONLAND HABITATS IN WESTERN CHITWAN, NEPAL

PubMed Central

Dangol, D.R.

2012-01-01

This paper is based on the flora data gathered from 138 common land plots as part of a multi-method longitudinal study of the reciprocal relations between population and environment in western Chitwan, Nepal. The paper also describes the uses and availability of different species drawing upon both field data and knowledge of indigenous and local residents in the study area. Land use in western Chitwan is changing rapidly and common land areas have been under much stress due to population increase, whereas the common land areas are valuable to local residents. Both indigenous and new migrant residents in this area use the available plant resources for different purposes which bring economic benefit to the households. Plant species provide valuable food, vegetable and medicinal products that maintain human health and general wellbeing of the household. These plants are also economically valuable to farmers with high quality forage value as well as useful for crop management (e.g., pesticide, compost, green manure). Moreover, some plant species are used as fish poison to harvest fish from rivers and streams. Likewise, the common land areas provide materials for use in house construction (e.g., thatch) and making tools with the potential and viable sites as communal grazing land. It is evident that access and utilization of common land resources are important for many households, especially those in remote and poor agricultural areas such as western Chitwan. PMID:22945971

Event-based rainfall-runoff modelling of the Kelantan River Basin

NASA Astrophysics Data System (ADS)

Basarudin, Z.; Adnan, N. A.; Latif, A. R. A.; Tahir, W.; Syafiqah, N.

2014-02-01

Flood is one of the most common natural disasters in Malaysia. According to hydrologists there are many causes that contribute to flood events. The two most dominant factors are the meteorology factor (i.e climate change) and change in land use. These two factors contributed to floods in recent decade especially in the monsoonal catchment such as Malaysia. This paper intends to quantify the influence of rainfall during extreme rainfall events on the hydrological model in the Kelantan River catchment. Therefore, two dynamic inputs were used in the study: rainfall and river discharge. The extreme flood events in 2008 and 2004 were compared based on rainfall data for both years. The events were modeled via a semi-distributed HEC-HMS hydrological model. Land use change was not incorporated in the study because the study only tries to quantify rainfall changes during these two events to simulate the discharge and runoff value. Therefore, the land use data representing the year 2004 were used as inputs in the 2008 runoff model. The study managed to demonstrate that rainfall change has a significant impact to determine the peak discharge and runoff depth for the study area.

Assessment of the water and energy budget simulation of three land surface models: CLM4.5, CoLM2014, and CoLM2005

NASA Astrophysics Data System (ADS)

Li, C.; Lu, H.; Wen, X.

2015-12-01

Land surface model (LSM), which simulates energy, water and momentum exchanges between land and atmosphere, is an important component of Earth System Models (ESM). As shown in CMIP5, different ESMs usually use different LSMs and represent various land surface status. In order to select a land surface model which could be embedded into the ESM developed in Tsinghua University, we firstly evaluate the performance of three LSMs: Community Land Model (CLM4.5) and two different versions of Common Land Model (CoLM2005 and CoLM2014). All of three models were driven by CRUNCEP data and simulation results from 1980 to 2010 were used in this study. Diagnostic data provided by NCAR, global latent and sensible heat flux map estimated by Jung, net radiation from SRB, and in situ observation collected from FluxNet were used as reference data. Two variables, surface runoff and snow depth, were used for evaluating the model performance in water budget simulation, while three variables including net radiation, sensible heat, and latent heat were used for assessing energy budget simulation. For 30 years averaged runoff, global average value of Colm2014 is 0.44mm/day and close to the diagnostic value of 0.75 mm/day, while that of Colm2005 is 0.44mm/day and that of CLM is 0.20mm/day. For snow depth simulation, three models all have overestimation in the Northern Hemisphere and underestimation in the Southern Hemisphere compare to diagnostic data. For 30 years energy budget simulation, at global scale, CoLM2005 performs best in latent heat estimation, CoLM2014 performs best in sensible heat simulation, and CoLM2005 and CoLM2014 make similar performance in net radiation estimation but is still better than CLM. At regional and local scale, comparing to the four years average of flux tower observation, RMSE of CoLM2005 is the smallest for latent heat (9.717 W/m2) , and for sensible heat simulation, RMSE of CoLM2005 (13.048 W/m2) is slightly greater than CLM(10.767 W/m2) but still better than CoLM2014(30.085 W/m2). Our analysis shows that both CoLM 2005 and CoLM 2014 are able to reproduce comparable land surface water and energy fluxes. It implies that the ESM developed in Tsinghua University may use CoLM, a LSM developed and maintained in China, as the land surface component. .

Evaluating soil moisture constraints on surface fluxes in land surface models globally

NASA Astrophysics Data System (ADS)

Harris, Phil; Gallego-Elvira, Belen; Taylor, Christopher; Folwell, Sonja; Ghent, Darren; Veal, Karen; Hagemann, Stefan

2016-04-01

Soil moisture availability exerts a strong control over land evaporation in many regions. However, global climate models (GCMs) disagree on when and where evaporation is limited by soil moisture. Evaluation of the relevant modelled processes has suffered from a lack of reliable, global observations of land evaporation at the GCM grid box scale. Satellite observations of land surface temperature (LST) offer spatially extensive but indirect information about the surface energy partition and, under certain conditions, about soil moisture availability on evaporation. Specifically, as soil moisture decreases during rain-free dry spells, evaporation may become limited leading to increases in LST and sensible heat flux. We use MODIS Terra and Aqua observations of LST at 1 km from 2000 to 2012 to assess changes in the surface energy partition during dry spells lasting 10 days or longer. The clear-sky LST data are aggregated to a global 0.5° grid before being composited as a function dry spell day across many events in a particular region and season. These composites are then used to calculate a Relative Warming Rate (RWR) between the land surface and near-surface air. This RWR can diagnose the typical strength of short term changes in surface heat fluxes and, by extension, changes in soil moisture limitation on evaporation. Offline land surface model (LSM) simulations offer a relatively inexpensive way to evaluate the surface processes of GCMs. They have the benefits that multiple models, and versions of models, can be compared on a common grid and using unbiased forcing. Here, we use the RWR diagnostic to assess global, offline simulations of several LSMs (e.g., JULES and JSBACH) driven by the WATCH Forcing Data-ERA Interim. Both the observed RWR and the LSMs use the same 0.5° grid, which allows the observed clear-sky sampling inherent in the underlying MODIS LST to be applied to the model outputs directly. This approach avoids some of the difficulties in analysing free-running simulations in which land and atmosphere are coupled and, as such, it provides a flexible intermediate step in the assessment of surface processes in GCMs.

Transforming the University Campus into a Sustainable Community

ERIC Educational Resources Information Center

Norton, Richard K.; Brix, Andrew; Brydon, Trevor; Davidian, Elijah; Dinse, Keely; Vidyarthi, Sanjeev

2007-01-01

This study addresses several common shortcomings of current university campus sustainability initiatives, including a lack of attention to integrative issues such as land use, housing, and transportation, and a generally reactive rather than proactive approach to sustainability. To engage these concerns, we develop a model for assessing the…

Flooding in ephemeral streams: incorporating transmission losses

USDA-ARS?s Scientific Manuscript database

Stream flow in semiarid lands commonly occurs as a form of flash floods in dry ephemeral stream beds. The goal of this research is to couple hydrological and hydraulic models treats channel transmission losses and test the methodology in the USDA-ARS Walnut Gulch Experimental Watershed (WGEW). For h...

Estimating raindrop kinetic energy: evaluation of a low-cost method

USDA-ARS?s Scientific Manuscript database

The Loess Plateau of China is regarded as the most intensively eroded region in the world and soil erosion caused by raindrop action is a common occurrence on agricultural land within this region. Therefore, understanding the influence of rainfall energy on the soil surface is needed for modeling pu...

A GIS-based groundwater travel time model to evaluate stream nitrate concentration reductions from land use change

USGS Publications Warehouse

Schilling, K.E.; Wolter, C.F.

2007-01-01

Excessive nitrate-nitrogen (nitrate) loss from agricultural watersheds is an environmental concern. A common conservation practice to improve stream water quality is to retire vulnerable row croplands to grass. In this paper, a groundwater travel time model based on a geographic information system (GIS) analysis of readily available soil and topographic variables was used to evaluate the time needed to observe stream nitrate concentration reductions from conversion of row crop land to native prairie in Walnut Creek watershed, Iowa. Average linear groundwater velocity in 5-m cells was estimated by overlaying GIS layers of soil permeability, land slope (surrogates for hydraulic conductivity and gradient, respectively) and porosity. Cells were summed backwards from the stream network to watershed divide to develop a travel time distribution map. Results suggested that groundwater from half of the land planted in prairie has reached the stream network during the 10 years of ongoing water quality monitoring. The mean travel time for the watershed was estimated to be 10.1 years, consistent with results from a simple analytical model. The proportion of land in the watershed and subbasins with prairie groundwater reaching the stream (10-22%) was similar to the measured reduction of stream nitrate (11-36%). Results provide encouragement that additional nitrate reductions in Walnut Creek are probable in the future as reduced nitrate groundwater from distal locations discharges to the stream network in the coming years. The high spatial resolution of the model (5-m cells) and its simplicity may make it potentially applicable for land managers interested in communicating lag time issues to the public, particularly related to nitrate concentration reductions over time. ?? 2007 Springer-Verlag.

Changes in Extremely Hot Summers over the Global Land Area under Various Warming Targets.

PubMed

Wang, Lei; Huang, Jianbin; Luo, Yong; Yao, Yao; Zhao, Zongci

2015-01-01

Summer temperature extremes over the global land area were investigated by comparing 26 models of the fifth phase of the Coupled Model Intercomparison Project (CMIP5) with observations from the Goddard Institute for Space Studies (GISS) and the Climate Research Unit (CRU). Monthly data of the observations and models were averaged for each season, and statistics were calculated for individual models before averaging them to obtain ensemble means. The summers with temperature anomalies (relative to 1951-1980) exceeding 3σ (σ is based on the local internal variability) are defined as "extremely hot". The models well reproduced the statistical characteristics evolution, and partly captured the spatial distributions of historical summer temperature extremes. If the global mean temperature increases 2°C relative to the pre-industrial level, "extremely hot" summers are projected to occur over nearly 40% of the land area (multi-model ensemble mean projection). Summers that exceed 5σ warming are projected to occur over approximately 10% of the global land area, which were rarely observed during the reference period. Scenarios reaching warming levels of 3°C to 5°C were also analyzed. After exceeding the 5°C warming target, "extremely hot" summers are projected to occur throughout the entire global land area, and summers that exceed 5σ warming would become common over 70% of the land area. In addition, the areas affected by "extremely hot" summers are expected to rapidly expand by more than 25%/°C as the global mean temperature increases by up to 3°C before slowing to less than 16%/°C as the temperature continues to increase by more than 3°C. The area that experiences summers with warming of 5σ or more above the warming target of 2°C is likely to maintain rapid expansion of greater than 17%/°C. To reduce the impacts and damage from severely hot summers, the global mean temperature increase should remain low.

GOES-derived fog and low cloud indices for coastal north and central California ecological analyses

USGS Publications Warehouse

Torregrosa, Alicia; Cindy Combs,; Peters, Jeff

2015-01-01

Fog and low cloud cover (FLCC) changes the water, energy, and nutrient flux of coastal ecosystems. Easy-to-use FLCC data are needed to quantify the impacts of FLC on ecosystem dynamics during hot, dry Mediterranean climate summers. FLCC indices were generated from 26,000 hourly night and day FLCC maps derived from Geostationary Environmental Operational Satellite (GOES) data for June, July, August, and September, 1999- 2009 for coastal California, latitude 34.50°N, south of Monterey Bay, to latitude 41.95°N, north of Crescent City. Monthly FLCC average hours per day (h/d) range from < 2 to 18. Average FLCC over the ocean increases from north (9 h/d) to south (14 h/d) whereas FLCC over land is reversed. Over land, FLCC is highest where land juts into the prevailing NW winds and is lowest in the lee of major capes. FLCC advects furthest inland through low-lying NW ocean-facing valleys. At night hours of FLCC is higher more frequently on land than over the ocean. Interannual FLCC coefficient of variation shows long term geographic stability strongly associated with landform position. Contours delineating homogeneous zones of FLCC, derived from average decadal h/d FLCC, provide data to refine the commonly used term ‘fog belt.’ FLCC indices are available for download from the California Landscape Conservation Cooperative Climate Commons website. FLCC indices can be used to improve analyses of biogeographic and bioclimatic species distribution models, meteorological mechanisms driving FLCC patterns, ecohydrological investigations of evapotranspiration, solar energy feasibility studies, agricultural irrigation demand and viticultural ripening models.

Dynamic Edge Effects in Small Mammal Communities across a Conservation-Agricultural Interface in Swaziland

PubMed Central

Hurst, Zachary M.; McCleery, Robert A.; Collier, Bret A.; Fletcher, Robert J.; Silvy, Nova J.; Taylor, Peter J.; Monadjem, Ara

2013-01-01

Across the planet, high-intensity farming has transformed native vegetation into monocultures, decreasing biodiversity on a landscape scale. Yet landscape-scale changes to biodiversity and community structure often emerge from processes operating at local scales. One common process that can explain changes in biodiversity and community structure is the creation of abrupt habitat edges, which, in turn, generate edge effects. Such effects, while incredibly common, can be highly variable across space and time; however, we currently lack a general analytical framework that can adequately capture such spatio-temporal variability. We extend previous approaches for estimating edge effects to a non-linear mixed modeling framework that captures such spatio-temporal heterogeneity and apply it to understand how agricultural land-uses alter wildlife communities. We trapped small mammals along a conservation-agriculture land-use interface extending 375 m into sugarcane plantations and conservation land-uses at three sites during dry and wet seasons in Swaziland, Africa. Sugarcane plantations had significant reductions in species richness and heterogeneity, and showed an increase in community similarity, suggesting a more homogenized small mammal community. Furthermore, our modeling framework identified strong variation in edge effects on communities across sites and seasons. Using small mammals as an indicator, intensive agricultural practices appear to create high-density communities of generalist species while isolating interior species in less than 225 m. These results illustrate how agricultural land-use can reduce diversity across the landscape and that effects can be masked or magnified, depending on local conditions. Taken together, our results emphasize the need to create or retain natural habitat features in agricultural mosaics. PMID:24040269

Adapting to Sea Level Rise to the Year 2100 and Beyond in the State of Florida, USA: A Regional Approach Based upon Common Vulnerabilities and the Utility of Shared Resources

NASA Astrophysics Data System (ADS)

Parkinson, R. W.; Harlem, P. W.; Meeder, J.

2014-12-01

We simulate the vulnerability of all 35 Florida coastal counties to the ongoing Anthropocene marine transgression unconstrained by the artificial end date of year 2100. Coastal submergence was emulated using a 'bathtub model' and rising sea level associated with an atmospheric temperature increase of +1 oC to +4 oC (see Levermann et al. [1]). Simulation results are organized into seven regions, each representing an area of common vulnerability characterized in this study as high (9% to 30% land loss), higher (16 to 68% land loss) and highest (48% to 97% land loss). This grouping provides a logical basis for establishing or re-enforcing collaboration based upon a common threat and the utility of shared technical and financial resources. Our bathtub model assumes Florida terrain is simply submerged as the shoreline migrates across a static landscape without change in the physical and biological materials subject to marine transgression. However, geologic studies of past and present Florida shorelines indicate the rate of rise is as important as the magnitude when predicting coastal response. To determine the utility of the bathtub model as a representative simulation of Florida's response to future sea level rise, we considered Florida's coastal response to varying rates of sea level rise over the last 14,000 years. Available data clearly demonstrate predicted rates of sea level rise will result in widespread submergence; the rate of rise will be too fast to be offset by the stabilizing forces of biogenic or physical sediment accumulation. Hence the magnitude of land loss and associated shoreline retreat in each of the seven Florida regions - and likely other coastal zones in the southeast U.S. - will be solely a function of topographic elevation and can therefore be reasonably forecast using a bathtub model. While our focus is on Florida's coastal counties, we recognize in some regions the effects of sea level rise will extend further inland. In these areas, the regional boundaries could be expanded to include adjacent non-coastal counties. However, differences in the perception of risk and associated vulnerability between coastal and inland counties may complicate timely collaboration. References: [1] A. Levermann et al. (2013), The Multi-Millennial Sea-Level Commitment of Global Warming, doi:10.1073/pnas.1219414110.

A Global Land Use Regression Model for Nitrogen Dioxide Air Pollution

PubMed Central

Larkin, Andrew; Geddes, Jeffrey A.; Martin, Randall V.; Xiao, Qingyang; Liu, Yang; Marshall, Julian D.; Brauer, Michael; Hystad, Perry

2017-01-01

Nitrogen dioxide is a common air pollutant with growing evidence of health impacts independent of other common pollutants such as ozone and particulate matter. However, the global distribution of NO2 exposure and associated impacts on global health is still largely uncertain. To advance global exposure estimates we created a global nitrogen dioxide (NO2) land use regression model for 2011 using annual measurements from 5,220 air monitors in 58 countries. The model captured 54% of global NO2 variation, with a mean absolute error of 3.7 ppb. Regional performance varied from R2 = 0.42 (Africa) to 0.67 (South America). Repeated 10% cross-validation using bootstrap sampling (n=10,000) demonstrated robust performance with respect to air monitor sampling in North America, Europe, and Asia (adjusted R2 within 2%) but not for Africa and Oceania (adjusted R2 within 11%) where NO2 monitoring data are sparse. The final model included 10 variables that captured both between and within-city spatial gradients in NO2 concentrations. Variable contributions differed between continental regions but major roads within 100m and satellite-derived NO2 were consistently the strongest predictors. The resulting model will be made available and can be used for global risk assessments and health studies, particularly in countries without existing NO2 monitoring data or models. PMID:28520422

Potential evapotranspiration and continental drying

USGS Publications Warehouse

Milly, Paul C.D.; Dunne, Krista A.

2016-01-01

By various measures (drought area and intensity, climatic aridity index, and climatic water deficits), some observational analyses have suggested that much of the Earth’s land has been drying during recent decades, but such drying seems inconsistent with observations of dryland greening and decreasing pan evaporation. ‘Offline’ analyses of climate-model outputs from anthropogenic climate change (ACC) experiments portend continuation of putative drying through the twenty-first century, despite an expected increase in global land precipitation. A ubiquitous increase in estimates of potential evapotranspiration (PET), driven by atmospheric warming, underlies the drying trends, but may be a methodological artefact. Here we show that the PET estimator commonly used (the Penman–Monteith PET for either an open-water surface or a reference crop) severely overpredicts the changes in non-water-stressed evapotranspiration computed in the climate models themselves in ACC experiments. This overprediction is partially due to neglect of stomatal conductance reductions commonly induced by increasing atmospheric CO2 concentrations in climate models. Our findings imply that historical and future tendencies towards continental drying, as characterized by offline-computed runoff, as well as other PET-dependent metrics, may be considerably weaker and less extensive than previously thought.

GIS Toolsets for Planetary Geomorphology and Landing-Site Analysis

NASA Astrophysics Data System (ADS)

Nass, Andrea; van Gasselt, Stephan

2015-04-01

Modern Geographic Information Systems (GIS) allow expert and lay users alike to load and position geographic data and perform simple to highly complex surface analyses. For many applications dedicated and ready-to-use GIS tools are available in standard software systems while other applications require the modular combination of available basic tools to answer more specific questions. This also applies to analyses in modern planetary geomorphology where many of such (basic) tools can be used to build complex analysis tools, e.g. in image- and terrain model analysis. Apart from the simple application of sets of different tools, many complex tasks require a more sophisticated design for storing and accessing data using databases (e.g. ArcHydro for hydrological data analysis). In planetary sciences, complex database-driven models are often required to efficiently analyse potential landings sites or store rover data, but also geologic mapping data can be efficiently stored and accessed using database models rather than stand-alone shapefiles. For landings-site analyses, relief and surface roughness estimates are two common concepts that are of particular interest and for both, a number of different definitions co-exist. We here present an advanced toolset for the analysis of image and terrain-model data with an emphasis on extraction of landing site characteristics using established criteria. We provide working examples and particularly focus on the concepts of terrain roughness as it is interpreted in geomorphology and engineering studies.

Estimation of Multiple Parameters over Vegetated Surfaces by Integrating Optical-Thermal Remote Sensing Observations

NASA Astrophysics Data System (ADS)

Ma, H.

2016-12-01

Land surface parameters from remote sensing observations are critical in monitoring and modeling of global climate change and biogeochemical cycles. Current methods for estimating land surface parameters are generally parameter-specific algorithms and are based on instantaneous physical models, which result in spatial, temporal and physical inconsistencies in current global products. Besides, optical and Thermal Infrared (TIR) remote sensing observations are usually separated to use based on different models , and the Middle InfraRed (MIR) observations have received little attention due to the complexity of the radiometric signal that mixes both reflected and emitted fluxes. In this paper, we proposed a unified algorithm for simultaneously retrieving a total of seven land surface parameters, including Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), land surface albedo, Land Surface Temperature (LST), surface emissivity, downward and upward longwave radiation, by exploiting remote sensing observations from visible to TIR domain based on a common physical Radiative Transfer (RT) model and a data assimilation framework. The coupled PROSPECT-VISIR and 4SAIL RT model were used for canopy reflectance modeling. At first, LAI was estimated using a data assimilation method that combines MODIS daily reflectance observation and a phenology model. The estimated LAI values were then input into the RT model to simulate surface spectral emissivity and surface albedo. Besides, the background albedo and the transmittance of solar radiation, and the canopy albedo were also calculated to produce FAPAR. Once the spectral emissivity of seven MODIS MIR to TIR bands were retrieved, LST can be estimated from the atmospheric corrected surface radiance by exploiting an optimization method. At last, the upward longwave radiation were estimated using the retrieved LST, broadband emissivity (converted from spectral emissivity) and the downward longwave radiation (modeled by MODTRAN). These seven parameters were validated over several representative sites with different biome type, and compared with MODIS and GLASS product. Results showed that this unified inversion algorithm can retrieve temporally complete and physical consistent land surface parameters with high accuracy.

A robust signalling system for land mobile satellite services

NASA Technical Reports Server (NTRS)

Irish, Dale; Shmith, Gary; Hart, Nick; Wines, Marie

1989-01-01

Presented here is a signalling system optimized to ensure expedient call set-up for satellite telephony services in a land mobile environment. In a land mobile environment, the satellite to mobile link is subject to impairments from multipath and shadowing phenomena, which result in signal amplitude and phase variations. Multipath, caused by signal scattering and reflections, results in sufficient link margin to compensate for these variations. Direct signal attenuation caused by shadowing due to buildings and vegetation may result in attenuation values in excess of 10 dB and commonly up to 20 dB. It is not practical to provide a link with sufficient margin to enable communication when the signal is blocked. When a moving vehicle passes these obstacles, the link will experience rapid changes in signal strength due to shadowing. Using statistical models of attenuation as a function of distance travelled, a communication strategy has been defined for the land mobile environment.

Evidence that local land use practices influence regional climate, vegetation, and stream flow patterns in adjacent natural areas

USGS Publications Warehouse

Stohlgren, T.J.; Chase, T.N.; Pielke, R.A.; Kittel, T.G.F.; Baron, Jill S.

1998-01-01

We present evidence that land use practices in the plains of Colorado influence regional climate and vegetation in adjacent natural areas in the Rocky Mountains in predictable ways. Mesoscale climate model simulations using the Colorado State University Regional Atmospheric Modelling System (RAMS) projected that modifications to natural vegetation in the plains, primarily due to agriculture and urbanization, could produce lower summer temperatures in the mountains. We corroborate the RAMS simulations with three independent sets of data: (i) climate records from 16 weather stations, which showed significant trends of decreasing July temperatures in recent decades; (ii) the distribution of seedlings of five dominant conifer species in Rocky Mountain National Park, Colorado, which suggested that cooler, wetter conditions occurred over roughly the same time period; and (iii) increased stream flow, normalized for changes in precipitation, during the summer months in four river basins, which also indicates cooler summer temperatures and lower transpiration at landscape scales. Combined, the mesoscale atmospheric/land-surface model, short-term in regional temperatures, forest distribution changes, and hydrology data indicate that the effects of land use practices on regional climate may overshadow larger-scale temperature changes commonly associated with observed increases in CO2 and other greenhouse gases.

Near-surface turbulence as a missing link in modeling evapotranspiration-soil moisture relationships

NASA Astrophysics Data System (ADS)

Haghighi, Erfan; Kirchner, James W.

2017-07-01

Despite many efforts to develop evapotranspiration (ET) models with improved parametrizations of resistance terms for water vapor transfer into the atmosphere, estimates of ET and its partitioning remain prone to bias. Much of this bias could arise from inadequate representations of physical interactions near nonuniform surfaces from which localized heat and water vapor fluxes emanate. This study aims to provide a mechanistic bridge from land-surface characteristics to vertical transport predictions, and proposes a new physically based ET model that builds on a recently developed bluff-rough bare soil evaporation model incorporating coupled soil moisture-atmospheric controls. The newly developed ET model explicitly accounts for (1) near-surface turbulent interactions affecting soil drying and (2) soil-moisture-dependent stomatal responses to atmospheric evaporative demand that influence leaf (and canopy) transpiration. Model estimates of ET and its partitioning were in good agreement with available field-scale data, and highlight hidden processes not accounted for by commonly used ET schemes. One such process, nonlinear vegetation-induced turbulence (as a function of vegetation stature and cover fraction) significantly influences ET-soil moisture relationships. Our results are particularly important for water resources and land use planning of semiarid sparsely vegetated ecosystems where soil surface interactions are known to play a critical role in land-climate interactions. This study potentially facilitates a mathematically tractable description of the strength (i.e., the slope) of the ET-soil moisture relationship, which is a core component of models that seek to predict land-atmosphere coupling and its feedback to the climate system in a changing climate.

Predicting Greater Prairie-Chicken Lek Site Suitability to Inform Conservation Actions

PubMed Central

Hovick, Torre J.; Dahlgren, David K.; Papeş, Monica; Elmore, R. Dwayne; Pitman, James C.

2015-01-01

The demands of a growing human population dictates that expansion of energy infrastructure, roads, and other development frequently takes place in native rangelands. Particularly, transmission lines and roads commonly divide rural landscapes and increase fragmentation. This has direct and indirect consequences on native wildlife that can be mitigated through thoughtful planning and proactive approaches to identifying areas of high conservation priority. We used nine years (2003–2011) of Greater Prairie-Chicken (Tympanuchus cupido) lek locations totaling 870 unique leks sites in Kansas and seven geographic information system (GIS) layers describing land cover, topography, and anthropogenic structures to model habitat suitability across the state. The models obtained had low omission rates (<0.18) and high area under the curve scores (AUC >0.81), indicating high model performance and reliability of predicted habitat suitability for Greater Prairie-Chickens. We found that elevation was the most influential in predicting lek locations, contributing three times more predictive power than any other variable. However, models were improved by the addition of land cover and anthropogenic features (transmission lines, roads, and oil and gas structures). Overall, our analysis provides a hierarchal understanding of Greater Prairie-Chicken habitat suitability that is broadly based on geomorphological features followed by land cover suitability. We found that when land features and vegetation cover are suitable for Greater Prairie-Chickens, fragmentation by anthropogenic sources such as roadways and transmission lines are a concern. Therefore, it is our recommendation that future human development in Kansas avoid areas that our models identified as highly suitable for Greater Prairie-Chickens and focus development on land cover types that are of lower conservation concern. PMID:26317349

Predicting Greater Prairie-Chicken Lek Site Suitability to Inform Conservation Actions.

PubMed

Hovick, Torre J; Dahlgren, David K; Papeş, Monica; Elmore, R Dwayne; Pitman, James C

2015-01-01

The demands of a growing human population dictates that expansion of energy infrastructure, roads, and other development frequently takes place in native rangelands. Particularly, transmission lines and roads commonly divide rural landscapes and increase fragmentation. This has direct and indirect consequences on native wildlife that can be mitigated through thoughtful planning and proactive approaches to identifying areas of high conservation priority. We used nine years (2003-2011) of Greater Prairie-Chicken (Tympanuchus cupido) lek locations totaling 870 unique leks sites in Kansas and seven geographic information system (GIS) layers describing land cover, topography, and anthropogenic structures to model habitat suitability across the state. The models obtained had low omission rates (<0.18) and high area under the curve scores (AUC >0.81), indicating high model performance and reliability of predicted habitat suitability for Greater Prairie-Chickens. We found that elevation was the most influential in predicting lek locations, contributing three times more predictive power than any other variable. However, models were improved by the addition of land cover and anthropogenic features (transmission lines, roads, and oil and gas structures). Overall, our analysis provides a hierarchal understanding of Greater Prairie-Chicken habitat suitability that is broadly based on geomorphological features followed by land cover suitability. We found that when land features and vegetation cover are suitable for Greater Prairie-Chickens, fragmentation by anthropogenic sources such as roadways and transmission lines are a concern. Therefore, it is our recommendation that future human development in Kansas avoid areas that our models identified as highly suitable for Greater Prairie-Chickens and focus development on land cover types that are of lower conservation concern.

A high-resolution and harmonized model approach for reconstructing and analyzing historic land changes in Europe

NASA Astrophysics Data System (ADS)

Fuchs, R.; Herold, M.; Verburg, P. H.; Clevers, J. G. P. W.

2012-10-01

Currently, up to 30% of global carbon emission is estimated to originate from land use and land changes. Existing historic land change reconstructions on the European scale do not sufficiently meet the requirements of greenhouse gas (GHG) and climate assessments, due to insufficient spatial and thematic detail and the consideration of various land change types. This paper investigates if the combination of different data sources, more detailed modeling techniques and the integration of land conversion types allow us to create accurate, high resolution historic land change data for Europe suited for the needs of GHG and climate assessments. We validated our reconstruction with historic aerial photographs from 1950 and 1990 for 73 sample sites across Europe and compared it with other land reconstructions like Klein Goldewijk et al. (2010, 2011), Ramankutty and Foley (1999), Pongratz et al. (2008) and Hurtt et al. (2006). The results indicate that almost 700 000 km2 (15.5%) of land cover in Europe changes over the period 1950 to 2010, an area similar to France. In Southern Europe the relative amount was almost 3.5% higher than average (19%). Based on the results the specific types of conversion, hot-spots of change and their relation to political decisions and socio-economic transitions were studied. The analysis indicate that the main drivers of land change over the studied period were urbanization, the reforestation program after the timber shortage since the Second World War, the fall of the Iron Curtain, Common Agricultural Policy and accompanying afforestation actions of the EU. Compared to existing land cover reconstructions, the new method takes stock of the harmonization of different datasets by achieving a high spatial resolution and regional detail with a full coverage of different land categories. These characteristic allow the data to be used to support and improve ongoing GHG inventories and climate research.

Common Pool Water Markets and their Role in Facilitating Land Use Change in Drying Climates

NASA Astrophysics Data System (ADS)

Teasley, R. L.; Milke, M.; Raffensperger, J. F.; Zargar, M.

2010-12-01

Concern is growing worldwide that climate change will lead to drier climates in many regions and in turn diminish water resources. To protect these limited resources, users may need to shift water use to more economically productive areas. However, changing the land use associated with water permits can be quite difficult, because water is not easily traded. Water markets have been well researched as a method for trading water between users, but these markets can often be difficult and costly requiring one-to-one trades between buyers and sellers. In contrast to a one-to-one market, a common pool market can reduce the transaction costs associated with trading water. In this research, a common pool market is applied to an example groundwater system set up in GWM2000 with ten users and various environmental constraints. The users represent three types of the largest groundwater users in the Canterbury region of New Zealand: agricultural, dairy and livestock. The response matrix from GWM2000 is used to develop constraints in the market model along with user bids. Bids are calculated from economic and water use data for Canterbury, New Zealand. Varying spatial distributions of water users by type are evaluated for the effect on the market under drying conditions. These conditions are simulated from climate change scenarios produced by the National Institute of Water and Atmospheric Research in New Zealand. The results demonstrate potential land use changes falls under drying conditions. As water availability falls, the price for additional water increases, particularly near environmental constraints, driving the land and water towards more efficient uses.

Scoring Methods in the International Land Benchmarking (ILAMB) Package

NASA Astrophysics Data System (ADS)

Collier, N.; Hoffman, F. M.; Keppel-Aleks, G.; Lawrence, D. M.; Mu, M.; Riley, W. J.; Randerson, J. T.

2017-12-01

The International Land Model Benchmarking (ILAMB) project is a model-data intercomparison and integration project designed to improve the performance of the land component of Earth system models. This effort is disseminated in the form of a python package which is openly developed (https://bitbucket.org/ncollier/ilamb). ILAMB is more than a workflow system that automates the generation of common scalars and plot comparisons to observational data. We aim to provide scientists and model developers with a tool to gain insight into model behavior. Thus, a salient feature of the ILAMB package is our synthesis methodology, which provides users with a high-level understanding of model performance. Within ILAMB, we calculate a non-dimensional score of a model's performance in a given dimension of the physics, chemistry, or biology with respect to an observational dataset. For example, we compare the Fluxnet-MTE Gross Primary Productivity (GPP) product against model output in the corresponding historical period. We compute common statistics such as the bias, root mean squared error, phase shift, and spatial distribution. We take these measures and find relative errors by normalizing the values, and then use the exponential to map this relative error to the unit interval. This allows for the scores to be combined into an overall score representing multiple aspects of model performance. In this presentation we give details of this process as well as a proposal for tuning the exponential mapping to make scores more cross comparable. However, as many models are calibrated using these scalar measures with respect to observational datasets, we also score the relationships among relevant variables in the model. For example, in the case of GPP, we also consider its relationship to precipitation, evapotranspiration, and temperature. We do this by creating a mean response curve and a two-dimensional distribution based on the observational data and model results. The response curves are then scored using a relative measure of the root mean squared error and the exponential as before. The distributions are scored using the so-called Hellinger distance, a statistical measure for how well one distribution is represented by another, and included in the model's overall score.

Sky radiance at a coastline and effects of land and ocean reflectivities

NASA Astrophysics Data System (ADS)

Kreuter, Axel; Blumthaler, Mario; Tiefengraber, Martin; Kift, Richard; Webb, Ann R.

2017-12-01

We present a unique case study of the spectral sky radiance distribution above a coastline. Results are shown from a measurement campaign in Italy involving three diode array spectroradiometers which are compared to 3-D model simulations from the Monte Carlo model MYSTIC. On the coast, the surrounding is split into two regions, a diffusely reflecting land surface and a water surface which features a highly anisotropic reflectance function. The reflectivities and hence the resulting radiances are a nontrivial function of solar zenith and azimuth angle and wavelength. We show that for low solar zenith angles (SZAs) around noon, the higher land albedo causes the sky radiance at 20° above the horizon to increase by 50 % in the near infrared at 850 nm for viewing directions towards the land with respect to the ocean. Comparing morning and afternoon radiances highlights the effect of the ocean's sun glint at high SZA, which contributes around 10 % to the measured radiance ratios. The model simulations generally agree with the measurements to better than 10 %. We investigate the individual effects of model input parameters representing land and ocean albedo and aerosols. Different land and ocean bi-directional reflectance functions (BRDFs) do not generally improve the model agreement. However, consideration of the uncertainties in the diurnal variation of aerosol optical depth can explain the remaining discrepancies between measurements and model. We further investigate the anisotropy effect of the ocean BRDF which is featured in the zenith radiances. Again, the uncertainty of the aerosol loading is dominant and obscures the modelled sun glint effect of 7 % at 650 nm. Finally, we show that the effect on the zenith radiance is restricted to a few kilometres from the coastline by model simulations along a perpendicular transect and by comparing the radiances at the coast to those measured at a site 15 km inland. Our findings are relevant to, for example, ground-based remote sensing of aerosol characteristics, since a common technique is based on sky radiance measurements along the solar almucantar.

Implications of overestimated anthropogenic CO2 emissions on East Asian and global land CO2 flux inversion

NASA Astrophysics Data System (ADS)

Saeki, Tazu; Patra, Prabir K.

2017-12-01

Measurement and modelling of regional or country-level carbon dioxide (CO2) fluxes are becoming critical for verification of the greenhouse gases emission control. One of the commonly adopted approaches is inverse modelling, where CO2 fluxes (emission: positive flux, sink: negative flux) from the terrestrial ecosystems are estimated by combining atmospheric CO2 measurements with atmospheric transport models. The inverse models assume anthropogenic emissions are known, and thus the uncertainties in the emissions introduce systematic bias in estimation of the terrestrial (residual) fluxes by inverse modelling. Here we show that the CO2 sink increase, estimated by the inverse model, over East Asia (China, Japan, Korea and Mongolia), by about 0.26 PgC year-1 (1 Pg = 1012 g) during 2001-2010, is likely to be an artifact of the anthropogenic CO2 emissions increasing too quickly in China by 1.41 PgC year-1. Independent results from methane (CH4) inversion suggested about 41% lower rate of East Asian CH4 emission increase during 2002-2012. We apply a scaling factor of 0.59, based on CH4 inversion, to the rate of anthropogenic CO2 emission increase since the anthropogenic emissions of both CO2 and CH4 increase linearly in the emission inventory. We find no systematic increase in land CO2 uptake over East Asia during 1993-2010 or 2000-2009 when scaled anthropogenic CO2 emissions are used, and that there is a need of higher emission increase rate for 2010-2012 compared to those calculated by the inventory methods. High bias in anthropogenic CO2 emissions leads to stronger land sinks in global land-ocean flux partitioning in our inverse model. The corrected anthropogenic CO2 emissions also produce measurable reductions in the rate of global land CO2 sink increase post-2002, leading to a better agreement with the terrestrial biospheric model simulations that include CO2-fertilization and climate effects.

Unmanned air vehicle: autonomous takeoff and landing

NASA Astrophysics Data System (ADS)

Lim, K. L.; Gitano-Briggs, Horizon Walker

2010-03-01

UAVs are increasing in popularity and sophistication due to the demonstrated performance which cannot be attained by manned aircraft1. These developments have been made possible by development of sensors, instrumentation, telemetry and controls during the last few decades. UAVs are now common in areas such as aerial observation and as communication relays3. Most UAVs, however, are still flown by a human pilot via remote control from a ground station. Even the existing autonomous UAVs often require a human pilot to handle the most difficult tasks of take off and landing2 (TOL). This is mainly because the navigation of the airplane requires observation, constant situational assessment and hours of experience from the pilot himself4. Therefore, an autonomous takeoff and landing system (TLS) for UAVs using a few practical design rules with various sensors, instrumentation, etc has been developed. This paper details the design and modeling of the UAV TLS. The model indicates that the UAV's TLS shows promising stability.

Unmanned air vehicle: autonomous takeoff and landing

NASA Astrophysics Data System (ADS)

Lim, K. L.; Gitano-Briggs, Horizon Walker

2009-12-01

UAVs are increasing in popularity and sophistication due to the demonstrated performance which cannot be attained by manned aircraft1. These developments have been made possible by development of sensors, instrumentation, telemetry and controls during the last few decades. UAVs are now common in areas such as aerial observation and as communication relays3. Most UAVs, however, are still flown by a human pilot via remote control from a ground station. Even the existing autonomous UAVs often require a human pilot to handle the most difficult tasks of take off and landing2 (TOL). This is mainly because the navigation of the airplane requires observation, constant situational assessment and hours of experience from the pilot himself4. Therefore, an autonomous takeoff and landing system (TLS) for UAVs using a few practical design rules with various sensors, instrumentation, etc has been developed. This paper details the design and modeling of the UAV TLS. The model indicates that the UAV's TLS shows promising stability.

Influence of solid waste and topography on urban floods: The case of Mexico City.

PubMed

Zambrano, Luis; Pacheco-Muñoz, Rodrigo; Fernández, Tania

2018-02-24

Floods in cities are increasingly common as a consequence of multifactor watershed dynamics, including geomorphology, land-use changes and land subsidence. However, urban managers have focused on infrastructure to address floods by reducing blocked sewage infrastructure, without significant success. Using Mexico City as a case study, we generated a spatial flood risk model with geomorphology and anthropogenic variables. The results helped contrast the implications of different public policies in land use and waste disposal, and correlating them with flood hazards. Waste disposal was only related to small floods. 58% of the city has a high risk of experiencing small floods, and 24% of the city has a risk for large floods. Half of the population with the lowest income is located in the high-risk areas for large floods. These models are easy to build, generate fast results and are able to help to flood policies, by understanding flood interactions in urban areas within the watershed.

Optimizing habitat protection using demographic models of population viability.

Treesearch

Robert G. Haight; Brian Cypher; Patrick A. Kelly; Scott Phillips; Hugh P. Possingham; Katherine Ralls; Anthony M. Starfield; P.J. White; Daniel Williams

2002-01-01

Expanding habitat protection is a common tactic for species conservation. When unprotected habitat is privately owned, decisions must be made about which areas to protect by land purchase or conservation easement. To address this problem, we developed an optimization framework for choosing the habitat protection strategy that minimizes the risk of population extinction...

Modified centroid for estimating sand, silt, and clay from soil texture class

USDA-ARS?s Scientific Manuscript database

Models that require inputs of soil particle size commonly use soil texture class for input; however, texture classes do not represent the continuum of soil size fractions. Soil texture class and clay percentage are collected as a standard practice for many land management agencies (e.g., NRCS, BLM, ...

Plant trait-based models identify direct and indirect effects of climate change on bundles of grassland ecosystem services

PubMed Central

Lamarque, Pénélope; Lavorel, Sandra; Mouchet, Maud; Quétier, Fabien

2014-01-01

Land use and climate change are primary causes of changes in the supply of ecosystem services (ESs). Although the consequences of climate change on ecosystem properties and associated services are well documented, the cascading impacts of climate change on ESs through changes in land use are largely overlooked. We present a trait-based framework based on an empirical model to elucidate how climate change affects tradeoffs among ESs. Using alternative scenarios for mountain grasslands, we predicted how direct effects of climate change on ecosystems and indirect effects through farmers’ adaptations are likely to affect ES bundles through changes in plant functional properties. ES supply was overall more sensitive to climate than to induced management change, and ES bundles remained stable across scenarios. These responses largely reflected the restricted extent of management change in this constrained system, which was incorporated when scaling up plot level climate and management effects on ecosystem properties to the entire landscape. The trait-based approach revealed how the combination of common driving traits and common responses to changed fertility determined interactions and tradeoffs among ESs. PMID:25225382

Plant trait-based models identify direct and indirect effects of climate change on bundles of grassland ecosystem services.

PubMed

Lamarque, Pénélope; Lavorel, Sandra; Mouchet, Maud; Quétier, Fabien

2014-09-23

Land use and climate change are primary causes of changes in the supply of ecosystem services (ESs). Although the consequences of climate change on ecosystem properties and associated services are well documented, the cascading impacts of climate change on ESs through changes in land use are largely overlooked. We present a trait-based framework based on an empirical model to elucidate how climate change affects tradeoffs among ESs. Using alternative scenarios for mountain grasslands, we predicted how direct effects of climate change on ecosystems and indirect effects through farmers' adaptations are likely to affect ES bundles through changes in plant functional properties. ES supply was overall more sensitive to climate than to induced management change, and ES bundles remained stable across scenarios. These responses largely reflected the restricted extent of management change in this constrained system, which was incorporated when scaling up plot level climate and management effects on ecosystem properties to the entire landscape. The trait-based approach revealed how the combination of common driving traits and common responses to changed fertility determined interactions and tradeoffs among ESs.

Evaluation of eco-physiological indicators in Northeast Asia dryland regions based on MODIS products and ecological models

NASA Astrophysics Data System (ADS)

Kang, W.

2017-12-01

Ecosystem carbon-energy-water circles have significant effect on function and structure and vice verse. Based on these circles mechanism, some eco-physiological indicators, like Transpiration (T), gross primary productivity (GPP), light use efficiency (LUE) and water use efficiency (WUE), are commonly applied to assess terrestrial ecosystem function and structure dynamics. The ecosystem weakened function and simple structure in Northeast dryland regions resulted from land degradation or desertification, which could be demonstrated by above-mentioned indicators. In this study, based on MODIS atmosphere (MYD07, MYD04, MYD06 data) and land products (MYD13A2 NDVI, MYD11A1 LST, MYD15A2 LAI and land cover data), we first retrieved transpiration and LUE via Penman-Monteith Model and modified Vegetation Photosynthesis Model (VPM), respectively; and then evaluated dynamics of these eco-physiological indicators (Tair, VPD, T, LUE, GPP and WUE) and some hotspots were found for next land degradation assessment. The results showed: (1) LUE and WUE are lower in barren or sparsely vegetated area and grasslands than in forest and croplands. (2) Whereas, all indicators presented higher variability in grassland area, particularly in east Mongolia. (3) GPP and transpiration have larger variability than other indicators due to fraction of absorbed Photosynthetically active radiation (FPAR). These eco-physiological indicators are expected to continue to change under future climate change and to help to assess land degradation from ecosystem energy-water-carbon perspectives.

Land Use as a Driver of Patterns of Rodenticide Exposure in Modeled Kit Fox Populations

PubMed Central

Nogeire, Theresa M.; Lawler, Joshua J.; Schumaker, Nathan H.; Cypher, Brian L.; Phillips, Scott E.

2015-01-01

Although rodenticides are increasingly regulated, they nonetheless cause poisonings in many non-target wildlife species. Second-generation anticoagulant rodenticide use is common in agricultural and residential landscapes. Here, we use an individual-based population model to assess potential population-wide effects of rodenticide exposures on the endangered San Joaquin kit fox (Vulpes macrotis mutica). We estimate likelihood of rodenticide exposure across the species range for each land cover type based on a database of reported pesticide use and literature. Using a spatially-explicit population model, we find that 36% of modeled kit foxes are likely exposed, resulting in a 7-18% decline in the range-wide modeled kit fox population that can be linked to rodenticide use. Exposures of kit foxes in low-density developed areas accounted for 70% of the population-wide exposures to rodenticides. We conclude that exposures of non-target kit foxes could be greatly mitigated by reducing the use of second-generation anticoagulant rodenticides in low-density developed areas near vulnerable populations. PMID:26244655

A high-resolution and harmonized model approach for reconstructing and analysing historic land changes in Europe

NASA Astrophysics Data System (ADS)

Fuchs, R.; Herold, M.; Verburg, P. H.; Clevers, J. G. P. W.

2013-03-01

Human-induced land use changes are nowadays the second largest contributor to atmospheric carbon dioxide after fossil fuel combustion. Existing historic land change reconstructions on the European scale do not sufficiently meet the requirements of greenhouse gas (GHG) and climate assessments, due to insufficient spatial and thematic detail and the consideration of various land change types. This paper investigates if the combination of different data sources, more detailed modelling techniques, and the integration of land conversion types allow us to create accurate, high-resolution historic land change data for Europe suited for the needs of GHG and climate assessments. We validated our reconstruction with historic aerial photographs from 1950 and 1990 for 73 sample sites across Europe and compared it with other land reconstructions like Klein Goldewijk et al. (2010, 2011), Ramankutty and Foley (1999), Pongratz et al. (2008) and Hurtt et al. (2006). The results indicate that almost 700 000 km2 (15.5%) of land cover in Europe has changed over the period 1950-2010, an area similar to France. In Southern Europe the relative amount was almost 3.5% higher than average (19%). Based on the results the specific types of conversion, hot-spots of change and their relation to political decisions and socio-economic transitions were studied. The analysis indicates that the main drivers of land change over the studied period were urbanization, the reforestation program resulting from the timber shortage after the Second World War, the fall of the Iron Curtain, the Common Agricultural Policy and accompanying afforestation actions of the EU. Compared to existing land cover reconstructions, the new method considers the harmonization of different datasets by achieving a high spatial resolution and regional detail with a full coverage of different land categories. These characteristics allow the data to be used to support and improve ongoing GHG inventories and climate research.

76 FR 61060 - Fisheries of the Northeastern United States; Northeast Multispecies Fishery; Correction to Cod...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-03

... Fishery; Correction to Cod Landing Limit for Handgear B Vessels in the Common Pool Fishery AGENCY... multispecies open access Handgear B permitted vessels fishing in the common pool fishery for the remainder of... landing limits for Handgear B (HB) vessels fishing under common pool regulations at Sec. 648.88(a)(1...

Land-use change reduces habitat suitability for supporting managed honey bee colonies in the Northern Great Plains

USGS Publications Warehouse

Otto, Clint R.; Roth, Cali; Carlson, Benjamin; Smart, Matthew

2016-01-01

Human reliance on insect pollination services continues to increase even as pollinator populations exhibit global declines. Increased commodity crop prices and federal subsidies for biofuel crops, such as corn and soybeans, have contributed to rapid land-use change in the US Northern Great Plains (NGP), changes that may jeopardize habitat for honey bees in a part of the country that supports >40% of the US colony stock. We investigated changes in biofuel crop production and grassland land covers surrounding ∼18,000 registered commercial apiaries in North and South Dakota from 2006 to 2014. We then developed habitat selection models to identify remotely sensed land-cover and land-use features that influence apiary site selection by Dakota beekeepers. Our study demonstrates a continual increase in biofuel crops, totaling 1.2 Mha, around registered apiary locations in North and South Dakota. Such crops were avoided by commercial beekeepers when selecting apiary sites in this region. Furthermore, our analysis reveals how grasslands that beekeepers target when selecting commercial apiary locations are becoming less common in eastern North and South Dakota, changes that may have lasting impact on pollinator conservation efforts. Our study highlights how land-use change in the NGP is altering the landscape in ways that are seemingly less conducive to beekeeping. Our models can be used to guide future conservation efforts highlighted in the US national pollinator health strategy by identifying areas that support high densities of commercial apiaries and that have exhibited significant land-use changes.

Land-use change reduces habitat suitability for supporting managed honey bee colonies in the Northern Great Plains

PubMed Central

Otto, Clint R. V.; Roth, Cali L.; Carlson, Benjamin L.; Smart, Matthew D.

2016-01-01

Human reliance on insect pollination services continues to increase even as pollinator populations exhibit global declines. Increased commodity crop prices and federal subsidies for biofuel crops, such as corn and soybeans, have contributed to rapid land-use change in the US Northern Great Plains (NGP), changes that may jeopardize habitat for honey bees in a part of the country that supports >40% of the US colony stock. We investigated changes in biofuel crop production and grassland land covers surrounding ∼18,000 registered commercial apiaries in North and South Dakota from 2006 to 2014. We then developed habitat selection models to identify remotely sensed land-cover and land-use features that influence apiary site selection by Dakota beekeepers. Our study demonstrates a continual increase in biofuel crops, totaling 1.2 Mha, around registered apiary locations in North and South Dakota. Such crops were avoided by commercial beekeepers when selecting apiary sites in this region. Furthermore, our analysis reveals how grasslands that beekeepers target when selecting commercial apiary locations are becoming less common in eastern North and South Dakota, changes that may have lasting impact on pollinator conservation efforts. Our study highlights how land-use change in the NGP is altering the landscape in ways that are seemingly less conducive to beekeeping. Our models can be used to guide future conservation efforts highlighted in the US national pollinator health strategy by identifying areas that support high densities of commercial apiaries and that have exhibited significant land-use changes. PMID:27573824

Modeling Land Application of Food-Processing Wastewater in the Central Valley, California

NASA Astrophysics Data System (ADS)

Rubin, Y.; Benito, P.; Miller, G.; McLaughlin, J.; Hou, Z.; Hermanowicz, S.; Mayer, U.

2007-12-01

California's Central Valley contains over 640 food-processing plants, serving a multi-billion dollar agricultural industry. These processors consume approximately 7.9 x 107 m3 of water per year. Approximately 80% of these processors discharge the resulting wastewater, which is typically high in organic matter, nitrogen, and salts, to land, and many of these use land application as a treatment method. Initial investigations revealed elevated salinity levels to be the most common form of groundwater degradation near land application sites, followed by concentrations of nitrogen compounds, namely ammonia and nitrate. Enforcement actions have been taken against multiple food processors, and the regulatory boards have begun to re-examine the land disposal permitting process. This paper summarizes a study that was commissioned in support of these actions. The study has multiple components which will be reviewed briefly, including: (1) characterization of the food-processing related waste stream; (2) fate and transport of the effluent waste stream in the unsaturated zone at the land application sites; (3) fate and transport of the effluent waste stream at the regional scale; (4) predictive uncertainty due to spatial variability and data scarcity at the land application sites and at the regional scale; (5) problem mitigation through off-site and in-situ actions; (6) long-term solutions. The emphasis of the talk will be placed on presenting and demonstrating a stochastic framework for modeling the transport and attenuation of these wastes in the vadose zone and in the saturated zone, and the related site characterization needs, as affected by site conditions, water table depth, waste water application rate, and waste constituent concentrations.

Macro-level safety analysis of pedestrian crashes in Shanghai, China.

PubMed

Wang, Xuesong; Yang, Junguang; Lee, Chris; Ji, Zhuoran; You, Shikai

2016-11-01

Pedestrian safety has become one of the most important issues in the field of traffic safety. This study aims at investigating the association between pedestrian crash frequency and various predictor variables including roadway, socio-economic, and land-use features. The relationships were modeled using the data from 263 Traffic Analysis Zones (TAZs) within the urban area of Shanghai - the largest city in China. Since spatial correlation exists among the zonal-level data, Bayesian Conditional Autoregressive (CAR) models with seven different spatial weight features (i.e. (a) 0-1 first order, adjacency-based, (b) common boundary-length-based, (c) geometric centroid-distance-based, (d) crash-weighted centroid-distance-based, (e) land use type, adjacency-based, (f) land use intensity, adjacency-based, and (g) geometric centroid-distance-order) were developed to characterize the spatial correlations among TAZs. Model results indicated that the geometric centroid-distance-order spatial weight feature, which was introduced in macro-level safety analysis for the first time, outperformed all the other spatial weight features. Population was used as the surrogate for pedestrian exposure, and had a positive effect on pedestrian crashes. Other significant factors included length of major arterials, length of minor arterials, road density, average intersection spacing, percentage of 3-legged intersections, and area of TAZ. Pedestrian crashes were higher in TAZs with medium land use intensity than in TAZs with low and high land use intensity. Thus, higher priority should be given to TAZs with medium land use intensity to improve pedestrian safety. Overall, these findings can help transportation planners and managers understand the characteristics of pedestrian crashes and improve pedestrian safety. Copyright © 2016 Elsevier Ltd. All rights reserved.

Using Remotely Sensed Data and Watershed and Hydrodynamic Models to Evaluate the Effects of Land Cover Land Use Change on Aquatic Ecosystems in Mobile Bay, AL

NASA Technical Reports Server (NTRS)

Al-Hamdan, Mohammad; Estes, Maurice G., Jr.; Judd, Chaeli; Woodruff, Dana; Ellis, Jean; Quattrochi, Dale; Watson, Brian; Rodriquez, Hugo; Johnson, Hoyt

2012-01-01

Alabama coastal systems have been subjected to increasing pressure from a variety of activities including urban and rural development, shoreline modifications, industrial activities, and dredging of shipping and navigation channels. The impacts on coastal ecosystems are often observed through the use of indicator species. One such indicator species for aquatic ecosystem health is submerged aquatic vegetation (SAV). Watershed and hydrodynamic modeling has been performed to evaluate the impact of land cover land use (LCLU) change in the two counties surrounding Mobile Bay (Mobile and Baldwin) on SAV stressors and controlling factors (temperature, salinity, and sediment) in the Mobile Bay estuary. Watershed modeling using the Loading Simulation Package in C++ (LSPC) was performed for all watersheds contiguous to Mobile Bay for LCLU scenarios in 1948, 1992, 2001, and 2030. Remotely sensed Landsat-derived National Land Cover Data (NLCD) were used in the 1992 and 2001 simulations after having been reclassified to a common classification scheme. The Prescott Spatial Growth Model was used to project the 2030 LCLU scenario based on current trends. The LSPC model simulations provided output on changes in flow, temperature, and sediment for 22 discharge points into the estuary. These results were inputted in the Environmental Fluid Dynamics Computer Code (EFDC) hydrodynamic model to generate data on changes in temperature, salinity, and sediment on a grid throughout Mobile Bay and adjacent estuaries. The changes in the aquatic ecosystem were used to perform an ecological analysis to evaluate the impact on SAV habitat suitability. This is the key product benefiting the Mobile Bay coastal environmental managers that integrates the influences of temperature, salinity, and sediment due to LCLU driven flow changes with the restoration potential of SAVs. Data products and results are being integrated into NOAA s EcoWatch and Gulf of Mexico Data Atlas online systems for dissemination to coastal resource managers and stakeholders. Objective 1: Develop and utilize Land Use scenarios for Mobile and Baldwin Counties, AL as input to models to predict the affects on water properties (temperature,salinity,)for Mobile Bay through 2030. Objective 2: Evaluate the impact of land use change on seagrasses and SAV in Mobile Bay. Hypothesis: Urbanization will significantly increase surface flows and impact salinity and temperature variables that effect seagrasses and SAVs.

Impacts of land use change on watershed streamflow and sediment yield: An assessment using hydrologic modelling and partial least squares regression

NASA Astrophysics Data System (ADS)

Yan, B.; Fang, N. F.; Zhang, P. C.; Shi, Z. H.

2013-03-01

SummaryUnderstanding how changes in individual land use types influence the dynamics of streamflow and sediment yield would greatly improve the predictability of the hydrological consequences of land use changes and could thus help stakeholders to make better decisions. Multivariate statistics are commonly used to compare individual land use types to control the dynamics of streamflow or sediment yields. However, one issue with the use of conventional statistical methods to address relationships between land use types and streamflow or sediment yield is multicollinearity. In this study, an integrated approach involving hydrological modelling and partial least squares regression (PLSR) was used to quantify the contributions of changes in individual land use types to changes in streamflow and sediment yield. In a case study, hydrological modelling was conducted using land use maps from four time periods (1978, 1987, 1999, and 2007) for the Upper Du watershed (8973 km2) in China using the Soil and Water Assessment Tool (SWAT). Changes in streamflow and sediment yield across the two simulations conducted using the land use maps from 2007 to 1978 were found to be related to land use changes according to a PLSR, which was used to quantify the effect of this influence at the sub-basin scale. The major land use changes that affected streamflow in the studied catchment areas were related to changes in the farmland, forest and urban areas between 1978 and 2007; the corresponding regression coefficients were 0.232, -0.147 and 1.256, respectively, and the Variable Influence on Projection (VIP) was greater than 1. The dominant first-order factors affecting the changes in sediment yield in our study were: farmland (the VIP and regression coefficient were 1.762 and 14.343, respectively) and forest (the VIP and regression coefficient were 1.517 and -7.746, respectively). The PLSR methodology presented in this paper is beneficial and novel, as it partially eliminates the co-dependency of the variables and facilitates a more unbiased view of the contribution of the changes in individual land use types to changes in streamflow and sediment yield. This practicable and simple approach could be applied to a variety of other watersheds for which time-sequenced digital land use maps are available.

Strategic directions for agent-based modeling: avoiding the YAAWN syndrome.

PubMed

O'Sullivan, David; Evans, Tom; Manson, Steven; Metcalf, Sara; Ligmann-Zielinska, Arika; Bone, Chris

In this short communication, we examine how agent-based modeling has become common in land change science and is increasingly used to develop case studies for particular times and places. There is a danger that the research community is missing a prime opportunity to learn broader lessons from the use of agent-based modeling (ABM), or at the very least not sharing these lessons more widely. How do we find an appropriate balance between empirically rich, realistic models and simpler theoretically grounded models? What are appropriate and effective approaches to model evaluation in light of uncertainties not only in model parameters but also in model structure? How can we best explore hybrid model structures that enable us to better understand the dynamics of the systems under study, recognizing that no single approach is best suited to this task? Under what circumstances - in terms of model complexity, model evaluation, and model structure - can ABMs be used most effectively to lead to new insight for stakeholders? We explore these questions in the hope of helping the growing community of land change scientists using models in their research to move from 'yet another model' to doing better science with models.

Strategic directions for agent-based modeling: avoiding the YAAWN syndrome

PubMed Central

O’Sullivan, David; Evans, Tom; Manson, Steven; Metcalf, Sara; Ligmann-Zielinska, Arika; Bone, Chris

2015-01-01

In this short communication, we examine how agent-based modeling has become common in land change science and is increasingly used to develop case studies for particular times and places. There is a danger that the research community is missing a prime opportunity to learn broader lessons from the use of agent-based modeling (ABM), or at the very least not sharing these lessons more widely. How do we find an appropriate balance between empirically rich, realistic models and simpler theoretically grounded models? What are appropriate and effective approaches to model evaluation in light of uncertainties not only in model parameters but also in model structure? How can we best explore hybrid model structures that enable us to better understand the dynamics of the systems under study, recognizing that no single approach is best suited to this task? Under what circumstances – in terms of model complexity, model evaluation, and model structure – can ABMs be used most effectively to lead to new insight for stakeholders? We explore these questions in the hope of helping the growing community of land change scientists using models in their research to move from ‘yet another model’ to doing better science with models. PMID:27158257

Modeling the Hydrologic Processes of a Depressional Forested Wetland in South Carolina, U.S.A.

Treesearch

Ge Sun; Timothy Callahan; Jennifer E. Pyzoha; Carl C. Trettin; Devendra M. Amatya

2004-01-01

Depressional forested wetlands or geographically isolated wetlands such as cypress swamps and Carolina bays are common land features in the Atlantic Coastal Plain of the southeastern US. Those wetlands play important roles in providing wildlife habitats, water quality improvement, and carbon sequestration. Great stresses have been imposed on those important ecosystems...

The Risk-Informed Materials Management (RIMM) Tool System for Determining Safe-Levels of Contaminated Materials Managed on the Land

EPA Science Inventory

EPA’s Risk-Informed Materials Management (RIMM) tool system is a modeling approach that helps risk assessors evaluate the safety of managing raw, reused, or waste material streams via a variety of common scenarios (e.g., application to farms, use as a component in road cons...

Geovisualization of land use and land cover using bivariate maps and Sankey flow diagrams

NASA Astrophysics Data System (ADS)

Strode, Georgianna; Mesev, Victor; Thornton, Benjamin; Jerez, Marjorie; Tricarico, Thomas; McAlear, Tyler

2018-05-01

The terms `land use' and `land cover' typically describe categories that convey information about the landscape. Despite the major difference of land use implying some degree of anthropogenic disturbance, the two terms are commonly used interchangeably, especially when anthropogenic disturbance is ambiguous, say managed forestland or abandoned agricultural fields. Cartographically, land use and land cover are also sometimes represented interchangeably within common legends, giving with the impression that the landscape is a seamless continuum of land use parcels spatially adjacent to land cover tracts. We believe this is misleading, and feel we need to reiterate the well-established symbiosis of land uses as amalgams of land covers; in other words land covers are subsets of land use. Our paper addresses this spatially complex, and frequently ambiguous relationship, and posits that bivariate cartographic techniques are an ideal vehicle for representing both land use and land cover simultaneously. In more specific terms, we explore the use of nested symbology as ways to represent graphically land use and land cover, where land cover are circles nested with land use squares. We also investigate bivariate legends for representing statistical covariance as a means for visualizing the combinations of land use and cover. Lastly, we apply Sankey flow diagrams to further illustrate the complex, multifaceted relationships between land use and land cover. Our work is demonstrated on data representing land use and cover data for the US state of Florida.

Utility of Thermal Infrared Satellite Data For Urban Landscapes

NASA Astrophysics Data System (ADS)

Xian, G.; Crane, M.; Granneman, B.

2006-12-01

Urban landscapes are comprised of a variety of surfaces that are characterized by contrasting radiative, thermal, aerodynamic, and moisture properties. These different surfaces possess diverse physical and thermal attributes that directly influence surface energy balance and our ability to determine surface characteristics in urban areas. Reflectance properties obtained from satellite imagery have proven useful for mapping urban land use and land cover change, as well as ecosystem health. Landsat reflectance bands are commonly used in regression tree models to generate linear equations that correspond to distinct land surface materials. However, urban land cover is generally a heterogeneous mix of bare soil, vegetation, rock, and anthropogenic impervious surfaces. Surface temperature obtained from satellite thermal infrared bands provides valuable information about surface biophysical properties and radiant thermal characteristics of land cover elements, especially for urban environments. This study demonstrates the improved characterization of land cover conditions for Seattle, Washington, and Las Vegas, Nevada, that were achieved by using both the reflectance and thermal bands of Landsat Enhanced Thematic Mapper Plus (ETM+) data. Including the thermal band in the image analysis increased the accuracy of discriminating cover types in heterogeneous landscapes with extreme contrasts, especially for mixed pixels at the urban interface.

Managed Clearings: an Unaccounted Land-cover in Urbanizing Regions

NASA Astrophysics Data System (ADS)

Singh, K. K.; Madden, M.; Meentemeyer, R. K.

2016-12-01

Managed clearings (MC), such as lawns, public parks and grassy transportation medians, are a common and ecologically important land cover type in urbanizing regions, especially those characterized by sprawl. We hypothesize that MC is underrepresented in land cover classification schemes and data products such as NLCD (National Land Cover Database) data, which may impact environmental assessments and models of urban ecosystems. We visually interpreted and mapped fine scale land cover with special attention to MC using 2012 NAIP (National Agriculture Imagery Program) images and compared the output with NLCD data. Areas sampled were 50 randomly distributed 1*1km blocks of land in three cities of the Char-lanta mega-region (Atlanta, Charlotte, and Raleigh). We estimated the abundance of MC relative to other land cover types, and the proportion of land-cover types in NLCD data that are similar to MC. We also assessed if the designations of recreation, transportation, and utility in MC inform the problem differently than simply tallying MC as a whole. 610 ground points, collected using the Google Earth, were used to evaluate accuracy of NLCD data and visual interpretation for consistency. Overall accuracy of visual interpretation and NLCD data was 78% and 58%, respectively. NLCD data underestimated forest and MC by 14.4km2 and 6.4km2, respectively, while overestimated impervious surfaces by 10.2km2 compared to visual interpretation. MC was the second most dominant land cover after forest (40.5%) as it covered about 28% of the total area and about 13% higher than impervious surfaces. Results also suggested that recreation in MC constitutes up to 90% of area followed by transportation and utility. Due to the prevalence of MC in urbanizing regions, the addition of MC to the synthesis of land-cover data can help delineate realistic cover types and area proportions that could inform ecologic/hydrologic models, and allow for accurate prediction of ecological phenomena.

Using Remotely Sensed Data and Watershed and Hydrodynamic Models to Evaluate the Effects of Land Cover Land Use Change on Aquatic Ecosystems in Mobile Bay, AL

NASA Technical Reports Server (NTRS)

Al-Hamdan, Mohammad Z.; Estes, Maurice G., Jr.; Judd, Chaeli; Thom, Ron; Woodruff, Dana; Ellis, Jean T.; Quattrochi, Dale; Watson, Brian; Rodriquez, Hugo; Johnson, Hoyt

2012-01-01

Alabama coastal systems have been subjected to increasing pressure from a variety of activities including urban and rural development, shoreline modifications, industrial activities, and dredging of shipping and navigation channels. The impacts on coastal ecosystems are often observed through the use of indicator species. One such indicator species for aquatic ecosystem health is submerged aquatic vegetation (SAV). Watershed and hydrodynamic modeling has been performed to evaluate the impact of land cover land use (LCLU) change in the two counties surrounding Mobile Bay (Mobile and Baldwin) on SAV stressors and controlling factors (temperature, salinity, and sediment) in the Mobile Bay estuary. Watershed modeling using the Loading Simulation Package in C++ (LSPC) was performed for all watersheds contiguous to Mobile Bay for LCLU scenarios in 1948, 1992, 2001, and 2030. Remotely sensed Landsat-derived National Land Cover Data (NLCD) were used in the 1992 and 2001 simulations after having been reclassified to a common classification scheme. The Prescott Spatial Growth Model was used to project the 2030 LCLU scenario based on current trends. The LSPC model simulations provided output on changes in flow, temperature, and sediment for 22 discharge points into the estuary. These results were inputted in the Environmental Fluid Dynamics Computer Code (EFDC) hydrodynamic model to generate data on changes in temperature, salinity, and sediment on a grid throughout Mobile Bay and adjacent estuaries. The changes in the aquatic ecosystem were used to perform an ecological analysis to evaluate the impact on SAV habitat suitability. This is the key product benefiting the Mobile Bay coastal environmental managers that integrates the influences of temperature, salinity, and sediment due to LCLU driven flow changes with the restoration potential of SAVs. Data products and results are being integrated into NOAA s EcoWatch and Gulf of Mexico Data Atlas online systems for dissemination to coastal resource managers and stakeholders.

Using Remotely Sensed Data and Watershed and Hydrodynamic Models to Evaluate the Effects of Land Cover Land Use Change on Aquatic Ecosystems in Mobile Bay, AL

NASA Astrophysics Data System (ADS)

Al-Hamdan, M. Z.; Estes, M. G.; Judd, C.; Thom, R.; Woodruff, D.; Ellis, J. T.; Quattrochi, D.; Watson, B.; Rodriguez, H.; Johnson, H.

2012-12-01

Alabama coastal systems have been subjected to increasing pressure from a variety of activities including urban and rural development, shoreline modifications, industrial activities, and dredging of shipping and navigation channels. The impacts on coastal ecosystems are often observed through the use of indicator species. One such indicator species for aquatic ecosystem health is submerged aquatic vegetation (SAV). Watershed and hydrodynamic modeling has been performed to evaluate the impact of land cover land use (LCLU) change in the two counties surrounding Mobile Bay (Mobile and Baldwin) on SAV stressors and controlling factors (temperature, salinity, and sediment) in the Mobile Bay estuary. Watershed modeling using the Loading Simulation Package in C++ (LSPC) was performed for all watersheds contiguous to Mobile Bay for LCLU scenarios in 1948, 1992, 2001, and 2030. Remotely sensed Landsat-derived National Land Cover Data (NLCD) were used in the 1992 and 2001 simulations after having been reclassified to a common classification scheme. The Prescott Spatial Growth Model was used to project the 2030 LCLU scenario based on current trends. The LSPC model simulations provided output on changes in flow, temperature, and sediment for 22 discharge points into the estuary. These results were inputted in the Environmental Fluid Dynamics Computer Code (EFDC) hydrodynamic model to generate data on changes in temperature, salinity, and sediment on a grid throughout Mobile Bay and adjacent estuaries. The changes in the aquatic ecosystem were used to perform an ecological analysis to evaluate the impact on SAV habitat suitability. This is the key product benefiting the Mobile Bay coastal environmental managers that integrates the influences of temperature, salinity, and sediment due to LCLU driven flow changes with the restoration potential of SAVs. Data products and results are being integrated into NOAA's EcoWatch and Gulf of Mexico Data Atlas online systems for dissemination to coastal resource managers and stakeholders.

Changes in Extremely Hot Summers over the Global Land Area under Various Warming Targets

PubMed Central

Wang, Lei; Huang, Jianbin; Luo, Yong; Yao, Yao; Zhao, Zongci

2015-01-01

Summer temperature extremes over the global land area were investigated by comparing 26 models of the fifth phase of the Coupled Model Intercomparison Project (CMIP5) with observations from the Goddard Institute for Space Studies (GISS) and the Climate Research Unit (CRU). Monthly data of the observations and models were averaged for each season, and statistics were calculated for individual models before averaging them to obtain ensemble means. The summers with temperature anomalies (relative to 1951–1980) exceeding 3σ (σ is based on the local internal variability) are defined as “extremely hot”. The models well reproduced the statistical characteristics evolution, and partly captured the spatial distributions of historical summer temperature extremes. If the global mean temperature increases 2°C relative to the pre-industrial level, “extremely hot” summers are projected to occur over nearly 40% of the land area (multi-model ensemble mean projection). Summers that exceed 5σ warming are projected to occur over approximately 10% of the global land area, which were rarely observed during the reference period. Scenarios reaching warming levels of 3°C to 5°C were also analyzed. After exceeding the 5°C warming target, “extremely hot” summers are projected to occur throughout the entire global land area, and summers that exceed 5σ warming would become common over 70% of the land area. In addition, the areas affected by “extremely hot” summers are expected to rapidly expand by more than 25%/°C as the global mean temperature increases by up to 3°C before slowing to less than 16%/°C as the temperature continues to increase by more than 3°C. The area that experiences summers with warming of 5σ or more above the warming target of 2°C is likely to maintain rapid expansion of greater than 17%/°C. To reduce the impacts and damage from severely hot summers, the global mean temperature increase should remain low. PMID:26090931

Analysis and Modeling of Intense Oceanic Lightning

NASA Astrophysics Data System (ADS)

Zoghzoghy, F. G.; Cohen, M.; Said, R.; Lehtinen, N. G.; Inan, U.

2014-12-01

Recent studies using lightning data from geo-location networks such as GLD360 suggest that lightning strokes are more intense over the ocean than over land, even though they are less common [Said et al. 2013]. We present an investigation of the physical differences between oceanic and land lightning. We have deployed a sensitive Low Frequency (1 MHz sampling rate) radio receiver system aboard the NOAA Ronald W. Brown research vessel and have collected thousands of lightning waveforms close to deep oceanic lightning. We analyze the captured waveforms, describe our modeling efforts, and summarize our findings. We model the ground wave (gw) portion of the lightning sferics using a numerical method built on top of the Stanford Full Wave Method (FWM) [Lehtinen and Inan 2008]. The gwFWM technique accounts for propagation over a curved Earth with finite conductivity, and is used to simulate an arbitrary current profile along the lightning channel. We conduct a sensitivity analysis and study the current profiles for land and for oceanic lightning. We find that the effect of ground conductivity is minimal, and that stronger oceanic radio intensity does not result from shorter current rise-time or from faster return stroke propagation speed.

External Device to Incrementally Skid the Habitat (E-DISH)

NASA Technical Reports Server (NTRS)

Brazell, J. W.; Introne, Steve; Bedell, Lisa; Credle, Ben; Holp, Graham; Ly, Siao; Tait, Terry

1994-01-01

A Mars habitat transport system was designed as part of the NASA Mars exploration program. The transport system, the External Device to Incrementally Skid the Habitat (E - DISH), will be used to transport Mars habitats from their landing sites to the colony base and will be detached after unloading. The system requirements for Mars were calculated and scaled for model purposes. Specific model materials are commonly found and recommendations for materials for the Mars design are included.

Analysis and predictive models of stormwater runoff volumes, loads, and pollutant concentrations from watersheds in the Twin Cities metropolitan area, Minnesota, USA.

PubMed

Brezonik, Patrick L; Stadelmann, Teresa H

2002-04-01

Urban nonpoint source pollution is a significant contributor to water quality degradation. Watershed planners need to be able to estimate nonpoint source loads to lakes and streams if they are to plan effective management strategies. To meet this need for the twin cities metropolitan area, a large database of urban and suburban runoff data was compiled. Stormwater runoff loads and concentrations of 10 common constituents (six N and P forms, TSS, VSS, COD, Pb) were characterized, and effects of season and land use were analyzed. Relationships between runoff variables and storm and watershed characteristics were examined. The best regression equation to predict runoff volume for rain events was based on rainfall amount, drainage area, and percent impervious area (R2 = 0.78). Median event-mean concentrations (EMCs) tended to be higher in snowmelt runoff than in rainfall runoff, and significant seasonal differences were found in yields (kg/ha) and EMCs for most constituents. Simple correlations between explanatory variables and stormwater loads and EMCs were weak. Rainfall amount and intensity and drainage area were the most important variables in multiple linear regression models to predict event loads, but uncertainty was high in models developed with the pooled data set. The most accurate models for EMCs generally were found when sites were grouped according to common land use and size.

Relations between retired agricultural land, water quality, and aquatic-community health, Minnesota River Basin

USGS Publications Warehouse

Christensen, Victoria G.; Lee, Kathy E.; McLees, James M.; Niemela, Scott L.

2012-01-01

The relative importance of agricultural land retirement on water quality and aquatic-community health was investigated in the Minnesota River Basin. Eighty-two sites, with drainage areas ranging from 4.3 to 2200 km2, were examined for nutrient concentrations, measures of aquatic-community health (e.g., fish index of biotic integrity [IBI] scores), and environmental factors (e.g., drainage area and amount of agricultural land retirement). The relation of proximity of agricultural land retirement to the stream was determined by calculating the land retirement percent in various riparian zones. Spearman's rho results indicated that IBI score was not correlated to the percentage of agricultural land retirement at the basin scale (p = 0.070); however, IBI score was correlated to retired land percentage in the 50- to 400-m riparian zones surrounding the streams (p < 0.05), indicating that riparian agricultural land retirement may have more influence on aquatic-community health than does agricultural land retirement in upland areas. Multivariate analysis of covariance and analysis of covariance models indicated that other environmental factors (such as drainage area and lacustrine and palustrine features) commonly were correlated to aquatic-community health measures, as were in-stream factors (standard deviation of water depth and substrate type). These results indicate that although agricultural land retirement is significantly related to fish communities as measured by the IBI scores, a combination of basin, riparian, and in-stream factors act together to influence IBI scores.

Validation of catchment models for predicting land-use and climate change impacts. 2. Case study for a Mediterranean catchment

NASA Astrophysics Data System (ADS)

Parkin, G.; O'Donnell, G.; Ewen, J.; Bathurst, J. C.; O'Connell, P. E.; Lavabre, J.

1996-02-01

Validation methods commonly used to test catchment models are not capable of demonstrating a model's fitness for making predictions for catchments where the catchment response is not known (including hypothetical catchments, and future conditions of existing catchments which are subject to land-use or climate change). This paper describes the first use of a new method of validation (Ewen and Parkin, 1996. J. Hydrol., 175: 583-594) designed to address these types of application; the method involves making 'blind' predictions of selected hydrological responses which are considered important for a particular application. SHETRAN (a physically based, distributed catchment modelling system) is tested on a small Mediterranean catchment. The test involves quantification of the uncertainty in four predicted features of the catchment response (continuous hydrograph, peak discharge rates, monthly runoff, and total runoff), and comparison of observations with the predicted ranges for these features. The results of this test are considered encouraging.

Paleoclimate diagnostics: consistent large-scale temperature responses in warm and cold climates

NASA Astrophysics Data System (ADS)

Izumi, Kenji; Bartlein, Patrick; Harrison, Sandy

2015-04-01

The CMIP5 model simulations of the large-scale temperature responses to increased raditative forcing include enhanced land-ocean contrast, stronger response at higher latitudes than in the tropics, and differential responses in warm and cool season climates to uniform forcing. Here we show that these patterns are also characteristic of CMIP5 model simulations of past climates. The differences in the responses over land as opposed to over the ocean, between high and low latitudes, and between summer and winter are remarkably consistent (proportional and nearly linear) across simulations of both cold and warm climates. Similar patterns also appear in historical observations and paleoclimatic reconstructions, implying that such responses are characteristic features of the climate system and not simple model artifacts, thereby increasing our confidence in the ability of climate models to correctly simulate different climatic states. We also show the possibility that a small set of common mechanisms control these large-scale responses of the climate system across multiple states.

Microbial Source Module (MSM): Documenting the Science ...

EPA Pesticide Factsheets

The Microbial Source Module (MSM) estimates microbial loading rates to land surfaces from non-point sources, and to streams from point sources for each subwatershed within a watershed. A subwatershed, the smallest modeling unit, represents the common basis for information consumed and produced by the MSM which is based on the HSPF (Bicknell et al., 1997) Bacterial Indicator Tool (EPA, 2013b, 2013c). Non-point sources include numbers, locations, and shedding rates of domestic agricultural animals (dairy and beef cows, swine, poultry, etc.) and wildlife (deer, duck, raccoon, etc.). Monthly maximum microbial storage and accumulation rates on the land surface, adjusted for die-off, are computed over an entire season for four land-use types (cropland, pasture, forest, and urbanized/mixed-use) for each subwatershed. Monthly point source microbial loadings to instream locations (i.e., stream segments that drain individual sub-watersheds) are combined and determined for septic systems, direct instream shedding by cattle, and POTWs/WWTPs (Publicly Owned Treatment Works/Wastewater Treatment Plants). The MSM functions within a larger modeling system that characterizes human-health risk resulting from ingestion of water contaminated with pathogens. The loading estimates produced by the MSM are input to the HSPF model that simulates flow and microbial fate/transport within a watershed. Microbial counts within recreational waters are then input to the MRA-IT model (Soller et

A numerical forecast model for road meteorology

NASA Astrophysics Data System (ADS)

Meng, Chunlei

2017-05-01

A fine-scale numerical model for road surface parameters prediction (BJ-ROME) is developed based on the Common Land Model. The model is validated using in situ observation data measured by the ROSA road weather stations of Vaisala Company, Finland. BJ-ROME not only takes into account road surface factors, such as imperviousness, relatively low albedo, high heat capacity, and high heat conductivity, but also considers the influence of urban anthropogenic heat, impervious surface evaporation, and urban land-use/land-cover changes. The forecast time span and the update interval of BJ-ROME in vocational operation are 24 and 3 h, respectively. The validation results indicate that BJ-ROME can successfully simulate the diurnal variation of road surface temperature both under clear-sky and rainfall conditions. BJ-ROME can simulate road water and snow depth well if the artificial removing was considered. Road surface energy balance in rainy days is quite different from that in clear-sky conditions. Road evaporation could not be neglected in road surface water cycle research. The results of sensitivity analysis show solar radiation correction coefficient, asphalt depth, and asphalt heat conductivity are important parameters in road interface temperatures simulation. The prediction results could be used as a reference of maintenance decision support system to mitigate the traffic jam and urban water logging especially in large cities.

Use of land surface remotely sensed satellite and airborne data for environmental exposure assessment in cancer research

USGS Publications Warehouse

Maxwell, S.K.; Meliker, J.R.; Goovaerts, P.

2010-01-01

In recent years, geographic information systems (GIS) have increasingly been used for reconstructing individual-level exposures to environmental contaminants in epidemiological research. Remotely sensed data can be useful in creating space-time models of environmental measures. The primary advantage of using remotely sensed data is that it allows for study at the local scale (e.g., residential level) without requiring expensive, time-consuming monitoring campaigns. The purpose of our study was to identify how land surface remotely sensed data are currently being used to study the relationship between cancer and environmental contaminants, focusing primarily on agricultural chemical exposure assessment applications. We present the results of a comprehensive literature review of epidemiological research where remotely sensed imagery or land cover maps derived from remotely sensed imagery were applied. We also discuss the strengths and limitations of the most commonly used imagery data (aerial photographs and Landsat satellite imagery) and land cover maps.

The sensitivity of ecosystem service models to choices of input data and spatial resolution

USGS Publications Warehouse

Bagstad, Kenneth J.; Cohen, Erika; Ancona, Zachary H.; McNulty, Steven; Sun, Ge

2018-01-01

Although ecosystem service (ES) modeling has progressed rapidly in the last 10–15 years, comparative studies on data and model selection effects have become more common only recently. Such studies have drawn mixed conclusions about whether different data and model choices yield divergent results. In this study, we compared the results of different models to address these questions at national, provincial, and subwatershed scales in Rwanda. We compared results for carbon, water, and sediment as modeled using InVEST and WaSSI using (1) land cover data at 30 and 300 m resolution and (2) three different input land cover datasets. WaSSI and simpler InVEST models (carbon storage and annual water yield) were relatively insensitive to the choice of spatial resolution, but more complex InVEST models (seasonal water yield and sediment regulation) produced large differences when applied at differing resolution. Six out of nine ES metrics (InVEST annual and seasonal water yield and WaSSI) gave similar predictions for at least two different input land cover datasets. Despite differences in mean values when using different data sources and resolution, we found significant and highly correlated results when using Spearman's rank correlation, indicating consistent spatial patterns of high and low values. Our results confirm and extend conclusions of past studies, showing that in certain cases (e.g., simpler models and national-scale analyses), results can be robust to data and modeling choices. For more complex models, those with different output metrics, and subnational to site-based analyses in heterogeneous environments, data and model choices may strongly influence study findings.

Links between land use change and recent dry season droughts in Amazonia

NASA Astrophysics Data System (ADS)

Khanna, J.; Medvigy, D.

2012-12-01

The Amazon region experienced catastrophic and unusually severe droughts in 2005 and 2010. These two droughts were phenomenologically different from the other, more common, El Niño-related droughts. Whereas El Niño-related droughts mostly affect the eastern and south-eastern parts of the region during the wet season (December-March), the droughts of 2005 and 2010 were most severe during the dry season (June-August) and affected the southern and western parts of the Amazon. A global warming driven mechanism has been suggested for these droughts wherein decreased moisture transport into the basin during the dry season is caused by anomalously high tropical north Atlantic SSTs, which weaken the northern hemisphere Hadley cell. But the facts that dry season droughts have been historically rare in this region and that the 2005 and 2010 droughts were strongest around locations of recent land use change activity suggest that deforestation may be contributing to this inter-annual variability in precipitation. This study addresses this research question by numerically modeling the 2005 and 2010 drought events for two land use scenarios, one of which (Deforested or DEF) represents the current state of land use in the Amazon and the other (Pristine Forest or PRF) represents a scenario of no deforestation. A variable resolution GCM, the Ocean-Land-Atmosphere Model (OLAM), is used to model these events. Land surface processes and soil moisture during the drought period are simulated using the Land Ecosystem Atmosphere Feedback model. The state of land cover in the Amazon in the two drought years is obtained from satellite-based land cover maps. The land grid has a variable resolution ranging from ≈75km in the South American sector to ≈200km elsewhere. This variable-resolution approach helps resolve topographic features and the medium-to-large scale land use patches in the Amazon area. The atmospheric runs are forced by National Oceanic and Atmospheric Administration weekly sea-surface temperature data. Soil moisture initial conditions were obtained from 8-year spin-ups for DEF and PRF. Then, ensembles of 18 month simulations were carried out, starting in June of 2004 and 2009. The ensembles consisted of 5 runs for each of the DEF and PRF experiments and are designed to reduce the effects of natural climate variability on the model results. Results are analyzed to test whether the intensity of the droughts, as measured by a water deficit index like maximum climatological water deficit (MCWD), increases from the PRF to the DEF case. An analysis of the statistical differences between the values of various meteorological and hydrological variables as obtained from the two land use scenarios will be presented. Thus this study will help both qualify and quantify the extent to which land use change can intensify a drought event.

Modeling Fence Location and Density at a Regional Scale for Use in Wildlife Management

PubMed Central

Poor, Erin E.; Jakes, Andrew; Loucks, Colby; Suitor, Mike

2014-01-01

Barbed and woven wire fences, common structures across western North America, act as impediments to wildlife movements. In particular, fencing influences pronghorn (Antilocapra americana) daily and seasonal movements, as well as modifying habitat selection. Because of fencing's impacts to pronghorn and other wildlife, it is a potentially important factor in both wildlife movement and habitat selection models. At this time, no geospatial fencing data is available at regional scales. Consequently, we constructed a regional fence model using a series of land tenure assumptions for the Hi-Line region of northern Montana – an area consisting of 13 counties over 103,400 km2. Randomized 3.2 km long transects (n = 738) on both paved and unpaved roads were driven to collect information on habitat, fence densities and fence type. Using GIS, we constructed a fence location and a density model incorporating ownership, size, neighboring parcels, township boundaries and roads. Local knowledge of land ownership and land use assisted in improving the final models. We predict there is greater than 263,300 km of fencing in the Hi-Line region, with a maximum density of 6.8 km of fencing per km2 and mean density of 2.4 km of fencing per km2. Using field data to assess model accuracy, Cohen's Kappa was measured at 0.40. On-the-ground fence modification or removal could be prioritized by identifying high fence densities in critical wildlife areas such as pronghorn migratory pathways or sage grouse lekking habitat. Such novel fence data can assist wildlife and land managers to assess effects of anthropogenic features to wildlife at various scales; which in turn may help conserve declining grassland species and overall ecological functionality. PMID:24416180

A Comparison of Selected Statistical Techniques to Model Soil Cation Exchange Capacity

NASA Astrophysics Data System (ADS)

Khaledian, Yones; Brevik, Eric C.; Pereira, Paulo; Cerdà, Artemi; Fattah, Mohammed A.; Tazikeh, Hossein

2017-04-01

Cation exchange capacity (CEC) measures the soil's ability to hold positively charged ions and is an important indicator of soil quality (Khaledian et al., 2016). However, other soil properties are more commonly determined and reported, such as texture, pH, organic matter and biology. We attempted to predict CEC using different advanced statistical methods including monotone analysis of variance (MONANOVA), artificial neural networks (ANNs), principal components regressions (PCR), and particle swarm optimization (PSO) in order to compare the utility of these approaches and identify the best predictor. We analyzed 170 soil samples from four different nations (USA, Spain, Iran and Iraq) under three land uses (agriculture, pasture, and forest). Seventy percent of the samples (120 samples) were selected as the calibration set and the remaining 50 samples (30%) were used as the prediction set. The results indicated that the MONANOVA (R2= 0.82 and Root Mean Squared Error (RMSE) =6.32) and ANNs (R2= 0.82 and RMSE=5.53) were the best models to estimate CEC, PSO (R2= 0.80 and RMSE=5.54) and PCR (R2= 0.70 and RMSE=6.48) also worked well and the overall results were very similar to each other. Clay (positively correlated) and sand (negatively correlated) were the most influential variables for predicting CEC for the entire data set, while the most influential variables for the various countries and land uses were different and CEC was affected by different variables in different situations. Although the MANOVA and ANNs provided good predictions of the entire dataset, PSO gives a formula to estimate soil CEC using commonly tested soil properties. Therefore, PSO shows promise as a technique to estimate soil CEC. Establishing effective pedotransfer functions to predict CEC would be productive where there are limitations of time and money, and other commonly analyzed soil properties are available. References Khaledian, Y., Kiani, F., Ebrahimi, S., Brevik, E.C., Aitkenhead-Peterson, J. 2016. Assessment and monitoring of soil degradation during land use change using multivariate analysis. Land Degradation and Development. doi: 10.1002/ldr.2541.

Orion Entry, Descent, and Landing Performance and Mission Design

NASA Technical Reports Server (NTRS)

Broome, Joel M.; Johnson, Wyatt

2007-01-01

The Orion Vehicle is the next spacecraft to take humans into space and will include missions to ISS as well as missions to the Moon. As part of that challenge, the vehicle will have to accommodate multiple mission design concepts, since return from Low Earth Orbit and return from the Moon can be quite different. Commonality between the different missions as it relates to vehicle systems, guidance capability, and operations concepts is the goal. Several unique mission design concepts include the specification of multiple land-based landing sites for a vehicle with closed-loop direct and skip entry guidance, followed by a parachute descent and landing attenuation system. This includes the ability of the vehicle to accurately target and land at a designated landing site, including site location aspects, landing site size, and landing opportunities assessments. Analyses associated with these mission design and flight performance challenges and constraints will be discussed as well as potential operational concepts to provide feasibility and/or mission commonality.

Measurement error in epidemiologic studies of air pollution based on land-use regression models.

PubMed

Basagaña, Xavier; Aguilera, Inmaculada; Rivera, Marcela; Agis, David; Foraster, Maria; Marrugat, Jaume; Elosua, Roberto; Künzli, Nino

2013-10-15

Land-use regression (LUR) models are increasingly used to estimate air pollution exposure in epidemiologic studies. These models use air pollution measurements taken at a small set of locations and modeling based on geographical covariates for which data are available at all study participant locations. The process of LUR model development commonly includes a variable selection procedure. When LUR model predictions are used as explanatory variables in a model for a health outcome, measurement error can lead to bias of the regression coefficients and to inflation of their variance. In previous studies dealing with spatial predictions of air pollution, bias was shown to be small while most of the effect of measurement error was on the variance. In this study, we show that in realistic cases where LUR models are applied to health data, bias in health-effect estimates can be substantial. This bias depends on the number of air pollution measurement sites, the number of available predictors for model selection, and the amount of explainable variability in the true exposure. These results should be taken into account when interpreting health effects from studies that used LUR models.

Historic distribution of Common Loons in Wisconsin in relation to changes in lake characteristics and surrounding land use

USGS Publications Warehouse

Kenow, Kevin P.; Garrison, Paul J.; Fox, Timothy J.; Meyer, Michael W.

2013-01-01

A study was conducted to evaluate changes in water quality and land-use change associated with lakes that are south of the current breeding range of Common Loons in Wisconsin but that historically supported breeding loons. Museum collection records and published accounts were examined to identify lakes in southern Wisconsin with a former history of loon nesting activity. Historical and recent water quality data were obtained from state and USEPA databases for the former loon nesting lakes that were identified and paleolimnological data were acquired for these lakes from sediment cores used to infer historical total phosphorus concentrations from diatom assemblages. U.S. General Land Office notes and maps from the original land survey conducted in Wisconsin during 1832-1866 and the National Land Cover Database 2006 were utilized to assess land use changes that occurred within the drainage basins of former loon nesting lakes. Our results indicate that the landscape of southern Wisconsin has changed dramatically since Common Loons last nested in the region. A number of factors have likely contributed to the decreased appeal of southern Wisconsin lakes to breeding Common Loons, including changes to water quality, altered trophic status resulting from nutrient enrichment, and reductions in suitable nesting habitat stemming from shoreline development and altered water levels. Increased nutrient and sediment inputs from agricultural and developed areas likely contributed to a reduction in habitat quality.

Sediment delivery modeling in practice: Comparing the effects of watershed characteristics and data resolution across hydroclimatic regions.

PubMed

Hamel, Perrine; Falinski, Kim; Sharp, Richard; Auerbach, Daniel A; Sánchez-Canales, María; Dennedy-Frank, P James

2017-02-15

Geospatial models are commonly used to quantify sediment contributions at the watershed scale. However, the sensitivity of these models to variation in hydrological and geomorphological features, in particular to land use and topography data, remains uncertain. Here, we assessed the performance of one such model, the InVEST sediment delivery model, for six sites comprising a total of 28 watersheds varying in area (6-13,500km 2 ), climate (tropical, subtropical, mediterranean), topography, and land use/land cover. For each site, we compared uncalibrated and calibrated model predictions with observations and alternative models. We then performed correlation analyses between model outputs and watershed characteristics, followed by sensitivity analyses on the digital elevation model (DEM) resolution. Model performance varied across sites (overall r 2 =0.47), but estimates of the magnitude of specific sediment export were as or more accurate than global models. We found significant correlations between metrics of sediment delivery and watershed characteristics, including erosivity, suggesting that empirical relationships may ultimately be developed for ungauged watersheds. Model sensitivity to DEM resolution varied across and within sites, but did not correlate with other observed watershed variables. These results were corroborated by sensitivity analyses performed on synthetic watersheds ranging in mean slope and DEM resolution. Our study provides modelers using InVEST or similar geospatial sediment models with practical insights into model behavior and structural uncertainty: first, comparison of model predictions across regions is possible when environmental conditions differ significantly; second, local knowledge on the sediment budget is needed for calibration; and third, model outputs often show significant sensitivity to DEM resolution. Copyright © 2016 Elsevier B.V. All rights reserved.

The Importance of Topography in Modeling the Climates of Potentially Habitable Worlds

NASA Astrophysics Data System (ADS)

Sohl, L. E.; Chandler, M. A.; Way, M.; Jonas, J.

2017-12-01

The surface features of distant potentially habitable worlds are unknown and likely to remain so for the foreseeable future. As a result, 3-D general circulation model (GCM) simulations of the climates of these worlds commonly utilize an aquaplanet configuration (no emergent land). We highlight here the differences in simulated climates that are produced when using realistic, reconstructed, or idealized continental distributions. Paleo-Earth scenarios as analogues of habitable exoplanets with emergent land exist back to 2 Gyr. There is high confidence in continental reconstructions back to 300 Myr, with moderate confidence reconstructions dating to at least 1 Gyr. A range of habitable states exists throughout the last two billion years of Earth history, including periods that are representative of both inner and outer edge environments, i.e., Snowball Earth and the Cretaceous Greenhouse. Using reconstructed land/ocean distributions with the GCM permits us to test hypotheses based on conceptual models (does a supercontinent at tropical latitudes encourage global cooling via albedo feedbacks?) as well as explore far-field climate teleconnections that may explain enhanced habitability (does the closing of an equatorial seaway drive increased heating in polar regions?). Paleo-Venus simulations, using current topography and a slow rotation rate, have shown that large land fraction in the tropics combined with modest amounts of water actually limits the amount of planetary warming to habitable levels, moreso than aquaplanets, given the equivalent solar flux - thus showing the inner edge of the HZ to be more transitional than previously described. For distant exoplanets or paleo-Earth prior to 2 Gyr, idealized continents or modern Earth topography help illustrate the range of possible habitable states for a given case. With idealized continents, varying the land fraction and location produces as much as a 20˚C difference in global MAT for otherwise identical simulations (same solar/GHG forcings). Synchronously rotating exoplanets modeled with modern Earth topography show how land barriers to zonal water/heat transports result in a global MAT considerably colder than the equivalent aquaplanet scenario, and ice and snow cover can increase by roughly a factor of two when land is beneath the substellar point.

Independent Verification of Mars-GRAM 2010 with Mars Climate Sounder Data

NASA Technical Reports Server (NTRS)

Justh, Hilary L.; Burns, Kerry L.

2014-01-01

The Mars Global Reference Atmospheric Model (Mars-GRAM) is an engineering-level atmospheric model widely used for diverse mission and engineering applications. Applications of Mars-GRAM include systems design, performance analysis, and operations planning for aerobraking, entry, descent and landing, and aerocapture. Atmospheric influences on landing site selection and long-term mission conceptualization and development can also be addressed utilizing Mars-GRAM. Mars-GRAM's perturbation modeling capability is commonly used, in a Monte Carlo mode, to perform high-fidelity engineering end-to-end simulations for entry, descent, and landing. Mars-GRAM is an evolving software package resulting in improved accuracy and additional features. Mars-GRAM 2005 has been validated against Radio Science data, and both nadir and limb data from the Thermal Emission Spectrometer (TES). From the surface to 80 km altitude, Mars-GRAM is based on the NASA Ames Mars General Circulation Model (MGCM). Above 80 km, Mars-GRAM is based on the University of Michigan Mars Thermospheric General Circulation Model (MTGCM). The most recent release of Mars-GRAM 2010 includes an update to Fortran 90/95 and the addition of adjustment factors. These adjustment factors are applied to the input data from the MGCM and the MTGCM for the mapping year 0 user-controlled dust case. The adjustment factors are expressed as a function of height (z), latitude and areocentric solar longitude (Ls).

Predictors of occurrence of the aquatic macrophyte Podostemum ceratophyllum in a southern Appalachian River

USGS Publications Warehouse

Argentina, Jane E.; Freeman, Mary C.; Freeman, Byron J.

2010-01-01

The aquatic macrophyte Podostemum ceratophyllum (Hornleaf Riverweed) commonly provides habitat for invertebrates and fishes in flowing-water portions of Piedmont and Appalachian streams in the eastern US. We quantified variation in percent cover by P. ceratophyllum in a 39-km reach of the Conasauga River, TN and GA, to test the hypothesis that cover decreased with increasing non-forest land use. We estimated percent P. ceratophyllum cover in quadrats (0.09 m2) placed at random coordinates within 20 randomly selected shoals. We then used hierarchical logistic regression, in an information-theoretic framework, to evaluate relative support for models incorporating alternative combinations of microhabitat and shoal-level variables to predict the occurrence of high (≥50%)P. ceratophyllum cover. As expected, bed sediment size and measures of light availability (location in the center of the channel, canopy cover) were included in best-supported models and had similar estimated-effect sizes across models. Podostemum ceratophyllum cover declined with increasing watershed size (included in 8 of 13 models in the confidence set of models); however, this decrease in cover was not well predicted by variation in land use. Focused monitoring of temporal and spatial trends in status of P. ceratophyllum are important due to its biotic importance in fast-flowing waters and its potential sensitivity to landscape-level changes, such as declines in forested land cover and homogenization of benthic habitats.

Modeling soil erosion and sediment transport from fires in forested watersheds of the South Carolina Piedmont

Treesearch

Tyler Crumbley; Ge Sun; Steve McNulty

2008-01-01

Forested watersheds in the Southeastern U.S. provide high quality water vital to ecosystem integrity and downstream aquatic resources. Excessive sedimentation from human activities in forest streams is of concern to responsible land managers. Prescribed fire is a common treatment applied to Southeastern piedmont forests and the risk of wildfire is becoming increasingly...

Using existing growth models to predict RCW habitat development following site preparation: pitfalls of the process and potential growth response

Treesearch

Benjamin O. Knapp; Joan L. Walker

2013-01-01

Land managers throughout the Southeast are interested in restoring the longleaf pine (Pinus palustris Mill.) ecosystem, due in part to its value as habitat for the endangered red-cockaded woodpecker (Picoides borealis). In 2003, we established a study at Camp Lejeune, NC, to determine the effects of common site preparation...

Integrating LIDAR and forest inventories to fill the trees outside forests data gap

Treesearch

Kristofer D. Johnson; Richard Birdsey; Jason Cole; Anu Swatantran; Jarlath O' Neil-Dunne; Ralph Dubayah; Andrew Lister

2015-01-01

Forest inventories are commonly used to estimate total tree biomass of forest land even though they are not traditionally designed to measure biomass of trees outside forests (TOF). The consequence may be an inaccurate representation of all of the aboveground biomass, which propagates error to the outputs of spatial and process models that rely on the inventory data....

Modeling soil erosion and sediment transport from fires in forested watersheds of the South Carolina Piedmont

Treesearch

Tyler Crumbley; Ge Sun; Steve McNulty

2007-01-01

Forested watersheds in the Southeastern U.S. provide high quality water vital to ecosystem integrity and downstream aquatic resources. Excessive sedimentation from human activities in forest streams is of concern to responsible land managers. Prescribed fire is a common treatment applied to Southeastern Piedmont forests and the risk of wildfire is becoming increasingly...

Modelling evapotranspiration during precipitation deficits: Identifying critical processes in a land surface model

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

Ukkola, Anna M.; Pitman, Andy J.; Decker, Mark

Surface fluxes from land surface models (LSMs) have traditionally been evaluated against monthly, seasonal or annual mean states. The limited ability of LSMs to reproduce observed evaporative fluxes under water-stressed conditions has been previously noted, but very few studies have systematically evaluated these models during rainfall deficits. We evaluated latent heat fluxes simulated by the Community Atmosphere Biosphere Land Exchange (CABLE) LSM across 20 flux tower sites at sub-annual to inter-annual timescales, in particular focusing on model performance during seasonal-scale rainfall deficits. The importance of key model processes in capturing the latent heat flux was explored by employing alternative representations of hydrology, leafmore » area index, soil properties and stomatal conductance. We found that the representation of hydrological processes was critical for capturing observed declines in latent heat during rainfall deficits. By contrast, the effects of soil properties, LAI and stomatal conductance were highly site-specific. Whilst the standard model performs reasonably well at annual scales as measured by common metrics, it grossly underestimates latent heat during rainfall deficits. A new version of CABLE, with a more physically consistent representation of hydrology, captures the variation in the latent heat flux during seasonal-scale rainfall deficits better than earlier versions, but remaining biases point to future research needs. Lastly, our results highlight the importance of evaluating LSMs under water-stressed conditions and across multiple plant functional types and climate regimes.« less

Modelling evapotranspiration during precipitation deficits: Identifying critical processes in a land surface model

DOE PAGES

Ukkola, Anna M.; Pitman, Andy J.; Decker, Mark; ...

2016-06-21

Surface fluxes from land surface models (LSMs) have traditionally been evaluated against monthly, seasonal or annual mean states. The limited ability of LSMs to reproduce observed evaporative fluxes under water-stressed conditions has been previously noted, but very few studies have systematically evaluated these models during rainfall deficits. We evaluated latent heat fluxes simulated by the Community Atmosphere Biosphere Land Exchange (CABLE) LSM across 20 flux tower sites at sub-annual to inter-annual timescales, in particular focusing on model performance during seasonal-scale rainfall deficits. The importance of key model processes in capturing the latent heat flux was explored by employing alternative representations of hydrology, leafmore » area index, soil properties and stomatal conductance. We found that the representation of hydrological processes was critical for capturing observed declines in latent heat during rainfall deficits. By contrast, the effects of soil properties, LAI and stomatal conductance were highly site-specific. Whilst the standard model performs reasonably well at annual scales as measured by common metrics, it grossly underestimates latent heat during rainfall deficits. A new version of CABLE, with a more physically consistent representation of hydrology, captures the variation in the latent heat flux during seasonal-scale rainfall deficits better than earlier versions, but remaining biases point to future research needs. Lastly, our results highlight the importance of evaluating LSMs under water-stressed conditions and across multiple plant functional types and climate regimes.« less

Land grants and the U.S. Forest Service

Treesearch

Carol Raish; Alice M. McSweeney

2008-01-01

The U.S. Forest Service (Forest Service) has a long, shared history with the land grants of northern New Mexico. During the land grant adjudication process after U.S. conquest, much common land from both Spanish and Mexican land grants was declared public domain, eventually becoming part of the northern and central New Mexico National Forests. These forests were...

Land management: data availability and process understanding for global change studies.

PubMed

Erb, Karl-Heinz; Luyssaert, Sebastiaan; Meyfroidt, Patrick; Pongratz, Julia; Don, Axel; Kloster, Silvia; Kuemmerle, Tobias; Fetzel, Tamara; Fuchs, Richard; Herold, Martin; Haberl, Helmut; Jones, Chris D; Marín-Spiotta, Erika; McCallum, Ian; Robertson, Eddy; Seufert, Verena; Fritz, Steffen; Valade, Aude; Wiltshire, Andrew; Dolman, Albertus J

2017-02-01

In the light of daunting global sustainability challenges such as climate change, biodiversity loss and food security, improving our understanding of the complex dynamics of the Earth system is crucial. However, large knowledge gaps related to the effects of land management persist, in particular those human-induced changes in terrestrial ecosystems that do not result in land-cover conversions. Here, we review the current state of knowledge of ten common land management activities for their biogeochemical and biophysical impacts, the level of process understanding and data availability. Our review shows that ca. one-tenth of the ice-free land surface is under intense human management, half under medium and one-fifth under extensive management. Based on our review, we cluster these ten management activities into three groups: (i) management activities for which data sets are available, and for which a good knowledge base exists (cropland harvest and irrigation); (ii) management activities for which sufficient knowledge on biogeochemical and biophysical effects exists but robust global data sets are lacking (forest harvest, tree species selection, grazing and mowing harvest, N fertilization); and (iii) land management practices with severe data gaps concomitant with an unsatisfactory level of process understanding (crop species selection, artificial wetland drainage, tillage and fire management and crop residue management, an element of crop harvest). Although we identify multiple impediments to progress, we conclude that the current status of process understanding and data availability is sufficient to advance with incorporating management in, for example, Earth system or dynamic vegetation models in order to provide a systematic assessment of their role in the Earth system. This review contributes to a strategic prioritization of research efforts across multiple disciplines, including land system research, ecological research and Earth system modelling. © 2016 John Wiley & Sons Ltd.

Land tenure reform and grassland degradation in Inner Mongolia, China

NASA Astrophysics Data System (ADS)

Liu, Min; Dries, Liesbeth; Heijman, Wim; Huang, Jikun; Zhu, Xueqin; Deng, Xiangzheng

2017-04-01

Since the start of the land tenure reform in the pastoral areas of China in the 1980s, grassland use rights have increasingly been assigned to individual households and subsequently more grasslands have been in private use. However, in the same period, most of the grasslands in China have experienced degradation. The question that this paper tries to address is whether the land tenure reform plays a significant role in grassland degradation. It is answered by an empirical analysis of the impact of land tenure reform on the changes in grassland condition, using data from 60 counties in Inner Mongolia between 1985 and 2008. Grassland condition is presented by grassland quantity and quality using spatial information based on remote sensing. The timing of the assignment of grassland use rights and the timing of the actual adoption of private use by households differ among counties. These timing differences and differences in grassland condition among counties allow disentangling the impact of the land tenure reform. A fixed effects model is used to control for climate, agricultural activity and the time-invariant heterogeneity among counties. The model results show that the private use of grasslands following the land tenure reform has had significantly negative effects on grassland quality and quantity in Inner Mongolia. Moreover, the negative effects did not disappear even after several years of experience with private use. In conclusion, our analysis reveals that the land tenure reform, namely privatisation of grassland use rights, is a significant driver of grassland degradation in Inner Mongolia in a long term, which presents "a tragedy of privatisation", as opposed to the well-known "tragedy of the commons".

Prospective mixture risk assessment and management prioritizations for river catchments with diverse land uses

PubMed Central

Brown, Colin D.; de Zwart, Dick; Diamond, Jerome; Dyer, Scott D.; Holmes, Christopher M.; Marshall, Stuart; Burton, G. Allen

2018-01-01

Abstract Ecological risk assessment increasingly focuses on risks from chemical mixtures and multiple stressors because ecosystems are commonly exposed to a plethora of contaminants and nonchemical stressors. To simplify the task of assessing potential mixture effects, we explored 3 land use–related chemical emission scenarios. We applied a tiered methodology to judge the implications of the emissions of chemicals from agricultural practices, domestic discharges, and urban runoff in a quantitative model. The results showed land use–dependent mixture exposures, clearly discriminating downstream effects of land uses, with unique chemical “signatures” regarding composition, concentration, and temporal patterns. Associated risks were characterized in relation to the land‐use scenarios. Comparisons to measured environmental concentrations and predicted impacts showed relatively good similarity. The results suggest that the land uses imply exceedances of regulatory protective environmental quality standards, varying over time in relation to rain events and associated flow and dilution variation. Higher‐tier analyses using ecotoxicological effect criteria confirmed that species assemblages may be affected by exposures exceeding no‐effect levels and that mixture exposure could be associated with predicted species loss under certain situations. The model outcomes can inform various types of prioritization to support risk management, including a ranking across land uses as a whole, a ranking on characteristics of exposure times and frequencies, and various rankings of the relative role of individual chemicals. Though all results are based on in silico assessments, the prospective land use–based approach applied in the present study yields useful insights for simplifying and assessing potential ecological risks of chemical mixtures and can therefore be useful for catchment‐management decisions. Environ Toxicol Chem 2018;37:715–728. © 2017 The Authors. Environmental Toxicology Chemistry Published by Wiley Periodicals, Inc. PMID:28845901

Spatial patterns of development drive water use

USGS Publications Warehouse

Sanchez, G.M.; Smith, J.W.; Terando, Adam J.; Sun, G.; Meentemeyer, R.K.

2018-01-01

Water availability is becoming more uncertain as human populations grow, cities expand into rural regions and the climate changes. In this study, we examine the functional relationship between water use and the spatial patterns of developed land across the rapidly growing region of the southeastern United States. We quantified the spatial pattern of developed land within census tract boundaries, including multiple metrics of density and configuration. Through non‐spatial and spatial regression approaches we examined relationships and spatial dependencies between the spatial pattern metrics, socio‐economic and environmental variables and two water use variables: a) domestic water use, and b) total development‐related water use (a combination of public supply, domestic self‐supply and industrial self‐supply). Metrics describing the spatial patterns of development had the highest measure of relative importance (accounting for 53% of model's explanatory power), explaining significantly more variance in water use compared to socio‐economic or environmental variables commonly used to estimate water use. Integrating metrics characterizing the spatial pattern of development into water use models is likely to increase their utility and could facilitate water‐efficient land use planning.

Spatial Patterns of Development Drive Water Use

NASA Astrophysics Data System (ADS)

Sanchez, G. M.; Smith, J. W.; Terando, A.; Sun, G.; Meentemeyer, R. K.

2018-03-01

Water availability is becoming more uncertain as human populations grow, cities expand into rural regions and the climate changes. In this study, we examine the functional relationship between water use and the spatial patterns of developed land across the rapidly growing region of the southeastern United States. We quantified the spatial pattern of developed land within census tract boundaries, including multiple metrics of density and configuration. Through non-spatial and spatial regression approaches we examined relationships and spatial dependencies between the spatial pattern metrics, socio-economic and environmental variables and two water use variables: a) domestic water use, and b) total development-related water use (a combination of public supply, domestic self-supply and industrial self-supply). Metrics describing the spatial patterns of development had the highest measure of relative importance (accounting for 53% of model's explanatory power), explaining significantly more variance in water use compared to socio-economic or environmental variables commonly used to estimate water use. Integrating metrics characterizing the spatial pattern of development into water use models is likely to increase their utility and could facilitate water-efficient land use planning.

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.

Some Physical and Computational Issues in Land Surface Data Assimilation of Satellite Skin Temperatures

NASA Astrophysics Data System (ADS)

Mackaro, Scott M.; McNider, Richard T.; Biazar, Arastoo Pour

2012-03-01

Skin temperatures that reflect the radiating temperature of a surface observed by infrared radiometers are one of the most widely available products from polar orbiting and geostationary satellites and the most commonly used satellite data in land surface assimilation. Past work has indicated that a simple land surface scheme with a few key parameters constrained by observations such as skin temperatures may be preferable to complex land use schemes with many unknown parameters. However, a true radiating skin temperature is sometimes not a prognostic variable in weather forecast models. Additionally, recent research has shown that skin temperatures cannot be directly used in surface similarity forms for inferring fluxes. This paper examines issues encountered in using satellite derived skin temperatures to improve surface flux specifications in weather forecast and air quality models. Attention is given to iterations necessary when attempting to nudge the surface energy budget equation to a desired state. Finally, the issue of mathematical operator splitting is examined in which the surface energy budget calculations are split with the atmospheric vertical diffusion calculations. However, the high level of connectivity between the surface and first atmospheric level means that the operator splitting leads to high frequency oscillations. These oscillations may hinder the assimilation of skin temperature derived moisture fluxes.

Developing a multi-stressor gradient for coral reefs | Science ...

EPA Pesticide Factsheets

Coral reefs are often found near coastal waters where multiple anthropogenic stressors co-occur at areas of human disturbance. Developing coral reef biocriteria under the U.S. Clean Water Act requires relationships between anthropogenic stressors and coral reef condition to be established. Developing stressor gradients presents challenges including: stressors which co-occur but operate at different or unknown spatial and temporal scales, inconsistent data availability measuring stressor levels, and unknown effects on exposed reef biota. We are developing a generalized stressor model using Puerto Rico as case study location, to represent the cumulative spatial/temporal co-occurrence of multiple anthropogenic stressors. Our approach builds on multi-stressor research in streams and rivers, and focuses on three high-priority stressors identified by coral reef experts: land-based sources of pollution (LBSP), global climate change (GCC) related temperature anomalies, and fishing pressure. Landscape development intensity index, based on land use/land cover data, estimates human impact in watersheds adjacent to coral reefs and is proxy for LBSP. NOAA’s retrospective daily thermal anomaly data is used to determine GCC thermal anomalies. Fishing pressure is modeled using gear-specific and fishery landings data. Stressor data was adjusted to a common scale or weighted for relative importance, buffered to account for diminished impact further from source, and compared wit

Improving Frozen Precipitation Density Estimation in Land Surface Modeling

NASA Astrophysics Data System (ADS)

Sparrow, K.; Fall, G. M.

2017-12-01

The Office of Water Prediction (OWP) produces high-value water supply and flood risk planning information through the use of operational land surface modeling. Improvements in diagnosing frozen precipitation density will benefit the NWS's meteorological and hydrological services by refining estimates of a significant and vital input into land surface models. A current common practice for handling the density of snow accumulation in a land surface model is to use a standard 10:1 snow-to-liquid-equivalent ratio (SLR). Our research findings suggest the possibility of a more skillful approach for assessing the spatial variability of precipitation density. We developed a 30-year SLR climatology for the coterminous US from version 3.22 of the Daily Global Historical Climatology Network - Daily (GHCN-D) dataset. Our methods followed the approach described by Baxter (2005) to estimate mean climatological SLR values at GHCN-D sites in the US, Canada, and Mexico for the years 1986-2015. In addition to the Baxter criteria, the following refinements were made: tests were performed to eliminate SLR outliers and frequent reports of SLR = 10, a linear SLR vs. elevation trend was fitted to station SLR mean values to remove the elevation trend from the data, and detrended SLR residuals were interpolated using ordinary kriging with a spherical semivariogram model. The elevation values of each station were based on the GMTED 2010 digital elevation model and the elevation trend in the data was established via linear least squares approximation. The ordinary kriging procedure was used to interpolate the data into gridded climatological SLR estimates for each calendar month at a 0.125 degree resolution. To assess the skill of this climatology, we compared estimates from our SLR climatology with observations from the GHCN-D dataset to consider the potential use of this climatology as a first guess of frozen precipitation density in an operational land surface model. The difference in model derived estimates and GHCN-D observations were assessed using time-series graphs of 2016-2017 winter season SLR observations and climatological estimates, as well as calculating RMSE and variance between estimated and observed values.

Evaluation of ecosystem service based on scenario simulation of land use in Yunnan Province

NASA Astrophysics Data System (ADS)

Zhang, Hong; Liao, Xiaoli; Zhai, Tianlin

2018-04-01

Climate change and rapid urbanization are important factors restricting future land use. Situational analysis, as an important foundation for the optimization of land use, needs to focus on the impact of climate factors and socio-economic factors. In this paper, the Markov model and the DLS (Simulation of Land System Dynamics) model are combined for the first time, and the land use pattern in 2020 is simulated based on the data of land use in 2000 and 2010 as well as the climate, soil, topography and socio-economic factors of Yunnan Province. In his paper, we took Yunnan Province as the case study area, and selected 12 driving factors by logistic regression method, then the land use demands and layout of Yunnan Province in 2020 has been forecasted and simulated under business as usual (BAU) scenario and farmland protection (FP) scenario and the changes in ecosystem service value has been calculated. The result shows that: (1) after the regression analysis and ROC (Relative Operating Characteristics) test, the 12 factors selected in this paper have a strong ability to explain the land use change in Yunnan Province. (2) Under the two scenarios, the significant reduction of arable land area is a common feature of land use change in Yunnan Province in the future, and its main land use type will be construction land. However, under FP scenario, the current situation where construction land encroach on arable land will be improved. Compared with the change from 2000 to 2010, the trend of arable land, forest land, water area, construction land and unused land will be the same under the two scenarios, whereas the change trend of grassland was opposite. (3) From 2000 to 2020, the value of ecosystem services in Yunnan Province is on the rise, but the ecosystem service value under FP scenario is higher than that of the ecosystem services under BAU scenario. In general, land use in 2020 in Yunnan Province continues the pattern of 2010, but there are also significant spatial differences. Under the BAU scenario, the construction land is mainly in the south of Lijiang City and the northeastern part of Kunming. Under the FP scenario, the new construction land is concentrated near the Lashi dam in northern Yunnan Province, and the high-quality arable land in the valley will be better protected. The research results can provide reference for the optimization of land use pattern in Yunnan Province, and provide scientific basis for land use management and planning. Based on the value of ecosystem services, we should implement the policy of strict protection of arable land, both to ensure food supply and promote the healthy development of ecological environment.

Revisiting the PLUMBER Experiments from a Process-Diagnostics Perspective

NASA Astrophysics Data System (ADS)

Nearing, G. S.; Ruddell, B. L.; Clark, M. P.; Nijssen, B.; Peters-Lidard, C. D.

2017-12-01

The PLUMBER benchmarking experiments [1] showed that some of the most sophisticated land models (CABLE, CH-TESSEL, COLA-SSiB, ISBA-SURFEX, JULES, Mosaic, Noah, ORCHIDEE) were outperformed - in simulations of half-hourly surface energy fluxes - by instantaneous, out-of-sample, and globally-stationary regressions with no state memory. One criticism of PLUMBER is that the benchmarking methodology was not derived formally, so that applying a similar methodology with different performance metrics can result in qualitatively different results. Another common criticism of model intercomparison projects in general is that they offer little insight into process-level deficiencies in the models, and therefore are of marginal value for helping to improve the models. We address both of these issues by proposing a formal benchmarking methodology that also yields a formal and quantitative method for process-level diagnostics. We apply this to the PLUMBER experiments to show that (1) the PLUMBER conclusions were generally correct - the models use only a fraction of the information available to them from met forcing data (<50% by our analysis), and (2) all of the land models investigated by PLUMBER have similar process-level error structures, and therefore together do not represent a meaningful sample of structural or epistemic uncertainty. We conclude by suggesting two ways to improve the experimental design of model intercomparison and/or model benchmarking studies like PLUMBER. First, PLUMBER did not report model parameter values, and it is necessary to know these values to separate parameter uncertainty from structural uncertainty. This is a first order requirement if we want to use intercomparison studies to provide feedback to model development. Second, technical documentation of land models is inadequate. Future model intercomparison projects should begin with a collaborative effort by model developers to document specific differences between model structures. This could be done in a reproducible way using a unified, process-flexible system like SUMMA [2]. [1] Best, M.J. et al. (2015) 'The plumbing of land surface models: benchmarking model performance', J. Hydrometeor. [2] Clark, M.P. et al. (2015) 'A unified approach for process-based hydrologic modeling: 1. Modeling concept', Water Resour. Res.

Sensitivity analysis of the Commonly Used Drought Indices on the different land use Types - Case Study over Turkey

NASA Astrophysics Data System (ADS)

Ersoy, E. N.; Hüsami Afşar, M.; Bulut, B.; Onen, A.; Yilmaz, M. T.

2017-12-01

Droughts are climatic phenomenon that may impact large and small regions alike for long or short time periods and influence society in terms of industrial, agricultural, domestic and many more aspects. The characteristics of the droughts are commonly investigated using indices like Standardized Precipitation Index (SPI), Palmer Drought Severity Index (PDSI), Standardized Precipitation Evapotranspiration Index (SPEI) and Normalized Difference Vegetation Index (NDVI). On the other hand, these indices may not necessarily yield similar performance over different vegetation types. The aim is to analyze the sensitivity of drought indices (SPI, SPEI, PDSI) to vegetation types over different climatic regions in Turkey. Here the magnitude of the drought severity is measured using MODIS NDVI data, while the vegetation type (e.g., non-irrigated arable lands, vineyards, fruit trees and berry plantations, olive groves, pastures, land principally occupied by agriculture) information is obtained using CORINE land cover classification. This study has compared the drought characteristics and vegetation conditions on different land use types using remotely sensed datasets (e.g., CORINE land use data, MODIS NDVI), and commonly used drought indices between 2000 and 2016 using gauge based precipitation and temperature measurements.

Using the Gravity Model to Estimate the Spatial Spread of Vector-Borne Diseases

PubMed Central

Barrios, José Miguel; Verstraeten, Willem W.; Maes, Piet; Aerts, Jean-Marie; Farifteh, Jamshid; Coppin, Pol

2012-01-01

The gravity models are commonly used spatial interaction models. They have been widely applied in a large set of domains dealing with interactions amongst spatial entities. The spread of vector-borne diseases is also related to the intensity of interaction between spatial entities, namely, the physical habitat of pathogens’ vectors and/or hosts, and urban areas, thus humans. This study implements the concept behind gravity models in the spatial spread of two vector-borne diseases, nephropathia epidemica and Lyme borreliosis, based on current knowledge on the transmission mechanism of these diseases. Two sources of information on vegetated systems were tested: the CORINE land cover map and MODIS NDVI. The size of vegetated areas near urban centers and a local indicator of occupation-related exposure were found significant predictors of disease risk. Both the land cover map and the space-borne dataset were suited yet not equivalent input sources to locate and measure vegetated areas of importance for disease spread. The overall results point at the compatibility of the gravity model concept and the spatial spread of vector-borne diseases. PMID:23202882

Using the gravity model to estimate the spatial spread of vector-borne diseases.

PubMed

Barrios, José Miguel; Verstraeten, Willem W; Maes, Piet; Aerts, Jean-Marie; Farifteh, Jamshid; Coppin, Pol

2012-11-30

The gravity models are commonly used spatial interaction models. They have been widely applied in a large set of domains dealing with interactions amongst spatial entities. The spread of vector-borne diseases is also related to the intensity of interaction between spatial entities, namely, the physical habitat of pathogens’ vectors and/or hosts, and urban areas, thus humans. This study implements the concept behind gravity models in the spatial spread of two vector-borne diseases, nephropathia epidemica and Lyme borreliosis, based on current knowledge on the transmission mechanism of these diseases. Two sources of information on vegetated systems were tested: the CORINE land cover map and MODIS NDVI. The size of vegetated areas near urban centers and a local indicator of occupation-related exposure were found significant predictors of disease risk. Both the land cover map and the space-borne dataset were suited yet not equivalent input sources to locate and measure vegetated areas of importance for disease spread. The overall results point at the compatibility of the gravity model concept and the spatial spread of vector-borne diseases.

Matrix approach to land carbon cycle modeling: A case study with the Community Land Model.

PubMed

Huang, Yuanyuan; Lu, Xingjie; Shi, Zheng; Lawrence, David; Koven, Charles D; Xia, Jianyang; Du, Zhenggang; Kluzek, Erik; Luo, Yiqi

2018-03-01

The terrestrial carbon (C) cycle has been commonly represented by a series of C balance equations to track C influxes into and effluxes out of individual pools in earth system models (ESMs). This representation matches our understanding of C cycle processes well but makes it difficult to track model behaviors. It is also computationally expensive, limiting the ability to conduct comprehensive parametric sensitivity analyses. To overcome these challenges, we have developed a matrix approach, which reorganizes the C balance equations in the original ESM into one matrix equation without changing any modeled C cycle processes and mechanisms. We applied the matrix approach to the Community Land Model (CLM4.5) with vertically-resolved biogeochemistry. The matrix equation exactly reproduces litter and soil organic carbon (SOC) dynamics of the standard CLM4.5 across different spatial-temporal scales. The matrix approach enables effective diagnosis of system properties such as C residence time and attribution of global change impacts to relevant processes. We illustrated, for example, the impacts of CO 2 fertilization on litter and SOC dynamics can be easily decomposed into the relative contributions from C input, allocation of external C into different C pools, nitrogen regulation, altered soil environmental conditions, and vertical mixing along the soil profile. In addition, the matrix tool can accelerate model spin-up, permit thorough parametric sensitivity tests, enable pool-based data assimilation, and facilitate tracking and benchmarking of model behaviors. Overall, the matrix approach can make a broad range of future modeling activities more efficient and effective. © 2017 John Wiley & Sons Ltd.

Spatiotemporal modeling of PM2.5 concentrations at the national scale combining land use regression and Bayesian maximum entropy in China.

PubMed

Chen, Li; Gao, Shuang; Zhang, Hui; Sun, Yanling; Ma, Zhenxing; Vedal, Sverre; Mao, Jian; Bai, Zhipeng

2018-05-03

Concentrations of particulate matter with aerodynamic diameter <2.5 μm (PM 2.5 ) are relatively high in China. Estimation of PM 2.5 exposure is complex because PM 2.5 exhibits complex spatiotemporal patterns. To improve the validity of exposure predictions, several methods have been developed and applied worldwide. A hybrid approach combining a land use regression (LUR) model and Bayesian Maximum Entropy (BME) interpolation of the LUR space-time residuals were developed to estimate the PM 2.5 concentrations on a national scale in China. This hybrid model could potentially provide more valid predictions than a commonly-used LUR model. The LUR/BME model had good performance characteristics, with R 2  = 0.82 and root mean square error (RMSE) of 4.6 μg/m 3 . Prediction errors of the LUR/BME model were reduced by incorporating soft data accounting for data uncertainty, with the R 2 increasing by 6%. The performance of LUR/BME is better than OK/BME. The LUR/BME model is the most accurate fine spatial scale PM 2.5 model developed to date for China. Copyright © 2018. Published by Elsevier Ltd.

Effects of local land-use planning on development and disturbance in riparian areas

Treesearch

Judith A. Dempsey; Andrew J. Plantinga; Jeffrey D. Kline; Joshua J. Lawler; Sebastian Martinuzzi; Volker C. Radeloff; Daniel P. Bigelow

2017-01-01

Land-use change can significantly affect the provision of ecosystem services. On a local scale, zoning laws and other land-use regulations are commonly used to influence land-use change, but their effectiveness is often unclear. We evaluate the effectiveness of local land-use planning in concentrating development and minimizing impacts in riparian areas. We use...

Assessing the homogenization of urban land management with an application to US residential lawn care

Treesearch

Colin Polsky; J. Morgan Grove; Chris Knudson; Peter M. Groffman; Neil Bettez; JJeannine Cavender-Bares; Sharon J. Hall; James B. Heffernan; Sarah E. Hobbie; Kelli L. Larson; Jennifer L. Morse; Christopher Neill; Kristen C. Nelson; Laura A. Ogden; Jarlath O' Neil-Dunne; Diane E. Pataki; Rinku Roy Chowdhury; Meredith K. Steele

2014-01-01

Changes in land use, land cover, and land management present some of the greatest potential global environmental challenges of the 21st century. Urbanization, one of the principal drivers of these transformations, is commonly thought to be generating land changes that are increasingly similar. An implication of this multiscale homogenization hypothesis is that the...

The Potential Radiative Forcing of Global Land Use and Land Cover Change Activities

NASA Astrophysics Data System (ADS)

Ward, D. S.; Mahowald, N. M.; Kloster, S.

2014-12-01

Given the expected increase in pressure on land resources over the next century, there is a need to understand the total impacts of activities associated with land use and land cover change (LULCC). Here we quantify these impacts using the radiative forcing metric, including forcings from changes in long-lived greenhouse gases, tropospheric ozone, aerosol effects, and land surface albedo. We estimate radiative forcings from the different agents for historical LULCC and for six future projections using simulations from the National Center for Atmospheric Research Community Land Model and Community Atmosphere Models and additional offline analyses. When all forcing agents are considered together we show that 45% (+30%, -20%) of the present-day (2010) anthropogenic radiative forcing can be attributed to LULCC. Changes in the emission of non-CO2 greenhouse gases and aerosols from LULCC enhance the total LULCC radiative forcing by a factor of 2 to 3 with respect to the forcing from CO2 alone. In contrast, the non-CO2 forcings from fossil fuel burning are roughly neutral, due largely to the negative (cooling) impact of aerosols from these sources. We partition the global LULCC radiative forcing into three major sources: direct modification of land cover (e.g. deforestation), agricultural activities, and fire regime changes. Contributions from deforestation and agriculture are roughly equal in the present day, while changes to wildfire activity impose a small negative forcing globally. In 2100, deforestation activities comprise the majority of the LULCC radiative forcing for all projections except one (Representative Concentration Pathway (RCP) 4.5). This suggests that realistic scenarios of future forest area change are essential for projecting the contribution of LULCC to climate change. However, the commonly used RCP land cover change projections all include decreases in global deforestation rates over the next 85 years. To place an upper bound on the potential radiative forcing from LULCC we create a 'worst-case scenario" in which all arable land is converted to agriculture by the year 2100. This scenario leads to a total radiative forcing of 4.3 Wm-2 (+/- 1 Wm-2) suggesting that well thought-out land policy is needed to minimize future increases in global anthropogenic radiative forcing.

Discrimination and Biophysical Characterization of Land Cover Types and Land Conversions in the Brazilian Cerrado Using EO-1 Hyperion Hyperspectral Imagery

NASA Astrophysics Data System (ADS)

Miura, T.; Huete, A. R.; Ferreira, L.

2002-12-01

The savanna, typically found in the sub-tropics and seasonal tropics, are the dominant vegetation biome type in the southern hemisphere, covering approximately 45 % of the South America. In Brazil, the savanna, locally known as "cerrado", is the most intensely stressed biome with rapid and aggressive land use conversions. Better characterization and discrimination of cerrado land cover types are needed in order to improve assessments of the impact of these land cover conversions on carbon storage, nutrient dynamics, and the prospect for sustainable land use in the Amazon region. In this study, we explored the utility of hyperspectral remote sensing in improving discrimination and biophysical/biochemical characterization of the cerrado land cover types by taking advantage of a newly available satellite-based, hyperspectral imaging sensor, "EO-1 Hyperion". A Hyperion image was acquired over the Brasilia National Park (BNP) and surrounding areas in Brasilia on July 20, 2001. Two commonly-used techniques, spectral derivatives and spectral mixture modeling, were applied to the atmospherically-corrected Hyperion scene. Derivative spectroscopy was useful in analyzing variations in spectral signatures and absorption depths, while spectral mixture modeling provided a means to simultaneously analyze variations in component fractions of photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV), and soil brightness. Data sets were extracted over a range of land cover types typically found in the Brazilian Cerrado. These included cerrado grassland, shrub cerrado, wooded cerrado, and cerrado woodland as undisturbed cerrado land cover types, and gallery forest as an undisturbed forest cover type in the Cerrado domain, and cultivated pasture as a converted land cover. In the derivative spectra analysis, both the position and magnitude of the red edge peak, and the ligno-cellulose absorptions at 2090nm and around 2300nm wavelengths showed large differences among the land cover types with the absorption depth of the latter correlating well with ground-measured % NPV cover. The multi-component fractional estimates successfully discriminated pasture and gallery forest from other cerrado land cover types. Likewise, PV and NPV fractional estimates for cerrado land cover types correlated well with ground-measured % green and NPV covers, respectively. These preliminary analyses showed a great potential of hyperspectral data in biophysical/biochemical characterization as well as discrimination of the land cover types in the Brazilian cerrado.

Using a Process Based Model to Simulate the Effects of Drainage and Land Use Change on Hydrology, and Sediment and Nutrient Transport in the Midwestern United States

NASA Astrophysics Data System (ADS)

Downer, C. W.; Pradhan, N. R.; Skahill, B. E.; Wahl, M.; Turnbull, S. J.

2015-12-01

Historically the Midwestern United State was a region dominated by prairie grasses and wetlands. To make use of the rich soils underlying these fertile environments, farmers converted the land to agriculture and currently the Midwest is a region of intensive agricultural production, with agriculture being a predominant land use. The Midwest is a region of gentle slopes, tight soils, and high water tables, and in order to make the lands suitable for agriculture, farmers have installed extensive networks of ditches to drain off excess surface water and subsurface tiles to lower the water table and remove excess soil water in the root zone that can stress common row crops, such as corn and soybeans. The combination of tiles, ditches, and intensive agricultural land practices radically alters the landscape and hydrology. As part of the Minnesota River Basin Integrated Study we are simulating nested watersheds in a sub-basin of the Minnesota River Basin, Seven Mile Creek, using the physics-based watershed model GSSHA (Gridded Surface Subsurface Hydrologic Analysis) to simulate water, sediment, and nutrients. Representative of the larger basin, more than 80% of the land in the watershed is dedicated to agricultural practices. From a process perspective, the hydrology is complicated, with snow accumulation and melt, frozen soil, and tile drains all being important processes within the watershed. In this study we attempt to explicitly simulate these processes, including the tile drains, which are simulated as a network of subsurface pipes that collect water from the local water table. Within the watershed, tiles discharge to both the ditch/stream network as well as overland locations, where the tile discharge appears to initiate gullies and exacerbate overland erosion. Testing of the methods on smaller basins demonstrates the ability of the model to simulate measured tile flow. At the larger scale, the model demonstrates ability to simulate flow and sediments. Sparse nutrient data limit the assessment of nutrient simulations. The models are being used to asses an array of potential future land use scenarios, including predevelopment and increased agricultural use. Results from these simulations will be presented. Preliminary results indicate that tile drains increase discharge and erosion in the watershed.

Quantifying nonpoint source emissions and their water quality responses in a complex catchment: A case study of a typical urban-rural mixed catchment

NASA Astrophysics Data System (ADS)

Chen, Lei; Dai, Ying; Zhi, Xiaosha; Xie, Hui; Shen, Zhenyao

2018-04-01

As two key threats to receiving water bodies, the generation mechanisms and processes of urban and agricultural nonpoint sources (NPSs) show clear differences, which lead to distinct characteristics of water quality responses with mixed land-uses catchments compared to single land-use ones. However, few studies have provided such insights in these characteristic or quantified different water environment responses to NPS pollution. In this study, an integrated modelling approach was developed for those complex catchments by combining three commonly used models: SWMM (Storm Water Management Model), SWAT (Soil and Water Assessment Tool) and MIKE 11. A case study was performed in a typical urban-rural catchment of Chao Lake, China. The simulated results indicated that urban NPS pollution responded sensitively to rainfall events and was greatly affected by the antecedent dry days. Compare to urban NPS, agricultural NPS pollution was characterized with the time-lag to rainfall depended on soil moisture and the post-rain-season emissions carried by lateral flows, and were also affected by the local farm-practice schedule. With comprehensive impacts from urban-rural land-uses, the time-interleaved urban and agricultural NPS pollution emissions and more abundant pollution accumulation both led to a decrease in the responsive time and an increase in the frequency of peak pollution concentration values even during the dry season. These obtained characteristics can provide guidance for drafting watershed management plans in similar mixed land use catchments.

Constraining global dry deposition of ozone: observations and modeling

NASA Astrophysics Data System (ADS)

Silva, S. J.; Heald, C. L.

2016-12-01

Ozone loss through dry deposition to vegetation is a critically important process for both air quality and ecosystem health. Current estimates are that nearly 25% of all surface ozone is destroyed through dry deposition, and billions of dollars are lost annually due to losses of ecosystem services and agricultural yield associated with ozone damage. However there are still substantial uncertainties regarding the spatial distribution and magnitude of the global depositional flux. As land cover change continues throughout this century, dry deposition of ozone will change in ways that are yet still poorly understood. Nearly every major atmospheric chemistry model uses a variation of the "resistor in series parameterization" for the calculation of dry deposition. By far the most commonly implemented parameterization is of the form presented in Wesely (1989), and is dependent on many variables, including land type look up tables, solar radiation, leaf area index, temperature, and more. The uncertainties contained within the various parts of this parameterization have to date not been fully explored. A lack of understanding of these uncertainties, coupled with a dearth of routine measurements of ozone deposition, ultimately challenges our ability to understand the impacts of land cover change on surface ozone. In this work, we use a suite of globally-distributed observations from the past two decades and the GEOS-Chem chemical transport model to constrain global dry deposition, improve our understanding of these uncertainties, and contextualize the impact of land cover change on ozone concentrations.

Relation of nitrate concentrations in ground water to well depth, well use, and land use in Franklin Township, Gloucester County, New Jersey, 1970-85

USGS Publications Warehouse

MacLeod, Cecilia Louise; Barringer, T.H.; Vowinkel, E.F.; Price, C.V.

1995-01-01

A water-quality data base was developed to permit the investigation of the relation of concentrations of nitrate (as nitrogen) in ground water to well depth, well use, and land use (agricultural, residential, urban nonresidential, and undeveloped) in Franklin Township. Nitrate concentrations in water from 868 wells tended to decrease with depth. A rank-order regression model of nitrate concen- trations and land-use percentages was fitted to data from 98 shallow domestic wells. The model, which explains about 25 percent of the variance in the data, indicated that nitrate concentration increased with the percentage of developed land in a well's buffer zone. Further stratification of the data based on well use (commercial, domestic, or agricultural/irrigation) indicated that elevated nitrate concentrations were more common in water from agricultural/irrigation wells than in water from domestic or commercial wells. Concentrations of nitrate were indicative of human activities in water from about one-third of the wells sampled but exceeded the U.S. Environmental Protection Agency's maximum contaminant level of 10 milligrams per liter in water from only 1 percent of the wells. A sampling strategy in which water from wells of different depths located within areas in each of the four land-use categories is sampled yearly and analyzed for nitrate and other constituents would facilitate determination of the effects of human activities on ground-water quality.

Complementing the topsoil information of the Land Use/Land Cover Area Frame Survey (LUCAS) with modelled N2O emissions.

PubMed

Lugato, Emanuele; Paniagua, Lily; Jones, Arwyn; de Vries, Wim; Leip, Adrian

2017-01-01

Two objectives of the Common Agricultural Policy post-2013 (CAP, 2014-2020) in the European Union (EU) are the sustainable management of natural resources and climate smart agriculture. To understand the CAP impact on these priorities, the Land Use/Cover statistical Area frame Survey (LUCAS) employs direct field observations and soil sub-sampling across the EU. While a huge amount of information can be retrieved from LUCAS points for monitoring the environmental status of agroecosystems and assessing soil carbon sequestration, a fundamental aspect relating to climate change action is missing, namely nitrous oxide (N2O) soil emissions. To fill this gap, we ran the DayCent biogeochemistry model for more than 11'000 LUCAS sampling points under agricultural use, assessing also the model uncertainty. The results showed that current annual N2O emissions followed a skewed distribution with a mean and median values of 2.27 and 1.71 kg N ha-1 yr-1, respectively. Using a Random Forest regression for upscaling the modelled results to the EU level, we estimated direct soil emissions of N2O in the range of 171-195 Tg yr-1 of CO2eq. Moreover, the direct regional upscaling using modelled N2O emissions in LUCAS points was on average 0.95 Mg yr-1 of CO2eq. per hectare, which was within the range of the meta-model upscaling (0.92-1.05 Mg ha-1 yr-1 of CO2eq). We concluded that, if information on management practices would be made available and model bias further reduced by N2O flux measurement at representative LUCAS points, the combination of the land use/soil survey with a well calibrated biogeochemistry model may become a reference tool to support agricultural, environmental and climate policies.

Potential effects of climate change on inland glacial lakes and implications for lake-dependent biota in Wisconsin: final report April 2013

USGS Publications Warehouse

Meyer, Michael W.; Walker, John F.; Kenow, Kevin P.; Rasmussen, Paul W.; Garrison, Paul J.; Hanson, Paul C.; Hunt, Randall J.

2013-01-01

F statewide, and an increase in precipitation of 1”–2”. However, summer precipitation in the northern part of the state is expected to be less and winter precipitation will be greater. By the end of the 21st century, the magnitude of changes in temperature and precipitation are expected to intensify. Such climatic changes have altered, and would further alter hydrological, chemical, and physical properties of inland lakes. Lake-dependent wildlife sensitive to changes in water quality, are particularly susceptible to lake quality-associated habitat changes and are likely to suffer restrictions to current breeding distributions under some climate change scenarios. We have selected the common loon (Gavia immer) to serve as a sentinel lake-dependent piscivorous species to be used in the development of a template for linking primary lake-dependent biota endpoints (e.g., decline in productivity and/or breeding range contraction) to important lake quality indicators. In the current project, we evaluate how changes in freshwater habitat quality (specifically lake clarity) may impact common loon lake occupancy in Wisconsin under detailed climate-change scenarios. In addition, we employ simple land-use/land cover and habitat scenarios to illustrate the potential interaction of climate and land-use/land cover effects. The methods employed here provide a template for studies where integration of physical and biotic models is used to project future conditions under various climate and land use change scenarios. Findings presented here project the future conditions of lakes and loons within an important watershed in northern Wisconsin – of importance to water resource managers and state citizens alike.

Gender comparisons between unilateral and bilateral landings.

PubMed

Weinhandl, Joshua T; Joshi, Mukta; O'Connor, Kristian M

2010-11-01

The increased number of women participating in sports has led to a higher knee injury rate in women compared with men. Among these injuries, those occurring to the ACL are commonly observed during landing maneuvers. The purpose of this study was to determine gender differences in landing strategies during unilateral and bilateral landings. Sixteen male and 17 female recreational athletes were recruited to perform unilateral and bilateral landings from a raised platform, scaled to match their individual jumping abilities. Three-dimensional kinematics and kinetics of the dominant leg were calculated during the landing phase and reported as initial ground contact angle, ranges of motion (ROM) and peak moments. Lower extremity energy absorption was also calculated for the duration of the landing phase. Results showed that gender differences were only observed in sagittal plane hip and knee ROM, potentially due to the use of a relative drop height versus the commonly used absolute drop height. Unilateral landings were characterized by significant differences in hip and knee kinematics that have been linked to increased injury risk and would best be classified as "stiff" landings. The ankle musculature was used more for impact absorption during unilateral landing, which required increased joint extension at touchdown and may increase injury risk during an unbalanced landing. In addition, there was only an 11% increase in total energy absorption during unilateral landings, suggesting that there was a substantial amount of passive energy transfer during unilateral landings.

Modeling and simulating industrial land-use evolution in Shanghai, China

NASA Astrophysics Data System (ADS)

Qiu, Rongxu; Xu, Wei; Zhang, John; Staenz, Karl

2018-01-01

This study proposes a cellular automata-based Industrial and Residential Land Use Competition Model to simulate the dynamic spatial transformation of industrial land use in Shanghai, China. In the proposed model, land development activities in a city are delineated as competitions among different land-use types. The Hedonic Land Pricing Model is adopted to implement the competition framework. To improve simulation results, the Land Price Agglomeration Model was devised to simulate and adjust classic land price theory. A new evolutionary algorithm-based parameter estimation method was devised in place of traditional methods. Simulation results show that the proposed model closely resembles actual land transformation patterns and the model can not only simulate land development, but also redevelopment processes in metropolitan areas.

The Flowering of the Suburbs: Common Land and Community Farming.

ERIC Educational Resources Information Center

Donahue, Brian

2000-01-01

Land's Sake, a community farm in suburban Weston (Massachusetts), cares for most of the town's conservation land, grows organic fruits and flowers, harvests forest products, employs young people, and offers various outdoor environmental education programs. The community's engagement with the land led to the passing of a bond issue to preserve the…

Helping Farmers Access Farmland: New Jersey's New Land Link Website

ERIC Educational Resources Information Center

Schilling, Brian J.; Marxen, Lucas J.; Everett, Jeffrey C.; Miller, Camille L.; Kimmel, David A.; Cook, Justine C.

2015-01-01

Access to land is a common obstacle for beginning farmers and established farmers seeking to expand their operations. Particularly in urban-influenced areas, leasing farmland is often more financially feasible than fee ownership. Locating available land or the right leasing situation, however, can be difficult. NJ Land Link (http://njlandlink.org)…

Seeking common ground: protecting homes from wildfires while making forests more resilient to fire

Treesearch

Noreen Parks; Alan Ager

2011-01-01

Federal policies direct public-land managers to reduce wildfire risks for urban areas close to wildlands, while broader agency goals call for landscape restoration to create fire-resilient forests. This study used wildfires simulation modeling to examine the tradeoffs between focusing fuel reduction efforts on a wildland-urban interface (WUI) in Oregon’s Blue Mountains...

Using machine learning to produce near surface soil moisture estimates from deeper in situ records at U.S. Climate Reference Network (USCRN) locations: Analysis and applications to AMSR-E satellite validation

USDA-ARS?s Scientific Manuscript database

Surface soil moisture is critical parameter for understanding the energy flux at the land atmosphere boundary. Weather modeling, climate prediction, and remote sensing validation are some of the applications for surface soil moisture information. The most common in situ measurement for these purpo...

Comparing Minnesota land cover/use area estimates using NRI and FIA data

Treesearch

Veronica C. Lessard; Mark H. Hansen; Mark D. Nelson

2002-01-01

Areas for land cover/use categories on non-Federal land in Minnesota were estimated from Forest Inventory and Analysis (FIA) data and National Resources Inventory (NRI) data. Six common land cover/use categories were defined, and the NRI and FIA land cover/use categories were assigned to them. Area estimates for these categories were calculated from the FIA and NRI...

Hyperparameterization of soil moisture statistical models for North America with Ensemble Learning Models (Elm)

NASA Astrophysics Data System (ADS)

Steinberg, P. D.; Brener, G.; Duffy, D.; Nearing, G. S.; Pelissier, C.

2017-12-01

Hyperparameterization, of statistical models, i.e. automated model scoring and selection, such as evolutionary algorithms, grid searches, and randomized searches, can improve forecast model skill by reducing errors associated with model parameterization, model structure, and statistical properties of training data. Ensemble Learning Models (Elm), and the related Earthio package, provide a flexible interface for automating the selection of parameters and model structure for machine learning models common in climate science and land cover classification, offering convenient tools for loading NetCDF, HDF, Grib, or GeoTiff files, decomposition methods like PCA and manifold learning, and parallel training and prediction with unsupervised and supervised classification, clustering, and regression estimators. Continuum Analytics is using Elm to experiment with statistical soil moisture forecasting based on meteorological forcing data from NASA's North American Land Data Assimilation System (NLDAS). There Elm is using the NSGA-2 multiobjective optimization algorithm for optimizing statistical preprocessing of forcing data to improve goodness-of-fit for statistical models (i.e. feature engineering). This presentation will discuss Elm and its components, including dask (distributed task scheduling), xarray (data structures for n-dimensional arrays), and scikit-learn (statistical preprocessing, clustering, classification, regression), and it will show how NSGA-2 is being used for automate selection of soil moisture forecast statistical models for North America.

Effect of land model ensemble versus coupled model ensemble on the simulation of precipitation climatology and variability

NASA Astrophysics Data System (ADS)

Wei, Jiangfeng; Dirmeyer, Paul A.; Yang, Zong-Liang; Chen, Haishan

2017-10-01

Through a series of model simulations with an atmospheric general circulation model coupled to three different land surface models, this study investigates the impacts of land model ensembles and coupled model ensemble on precipitation simulation. It is found that coupling an ensemble of land models to an atmospheric model has a very minor impact on the improvement of precipitation climatology and variability, but a simple ensemble average of the precipitation from three individually coupled land-atmosphere models produces better results, especially for precipitation variability. The generally weak impact of land processes on precipitation should be the main reason that the land model ensembles do not improve precipitation simulation. However, if there are big biases in the land surface model or land surface data set, correcting them could improve the simulated climate, especially for well-constrained regional climate simulations.

Characterization of streamflow, salinity, and selenium loading and land-use change in Montrose Arroyo, western Colorado, from 1992 to 2013

USGS Publications Warehouse

Richards, Rodney J.; Moore, Jennifer L.

2015-01-01

Land use was characterized for 1992, 2002, and 2009 for site MA3. The common land-use change in the MA3 subwatershed was a conversion from previously irrigated agricultural land to urban land use. The MA3 subwatershed had 124 acres of irrigated land use converted to urban land use and 27.1 acres of unirrigated desert converted to urban land use from 1992 to 2009. Consistent with findings in previous land-use change reports, salinity and dissolved-selenium loading at site MA3 showed significant decreases as irrigated land was converted to urban land use.

Groundwater-abstraction induced land subsidence and groundwater regulation in the North China Plain

NASA Astrophysics Data System (ADS)

Guo, H.; Wang, L.; Cheng, G.; Zhang, Z.

2015-11-01

Land subsidence can be induced when various factors such as geological, and hydrogeological conditions and intensive groundwater abstraction combine. The development and utilization of groundwater in the North China Plain (NCP) bring great benefits, and at the same time have led to a series of environmental and geological problems accompanying groundwater-level declines and land subsidence. Subsidence occurs commonly in the NCP and analyses show that multi-layer aquifer systems with deep confined aquifers and thick compressible clay layers are the key geological and hydrogeological conditions responsible for its development in this region. Groundwater overdraft results in aquifer-system compaction, resulting in subsidence. A calibrated, transient groundwater-flow numerical model of the Beijing plain portion of the NCP was developed using MODFLOW. According to available water supply and demand in Beijing plain, several groundwater regulation scenarios were designed. These different regulation scenarios were simulated with the groundwater model, and assessed using a multi-criteria fuzzy pattern recognition model. This approach is proven to be very useful for scientific analysis of sustainable development and utilization of groundwater resources. The evaluation results show that sustainable development of groundwater resources may be achieved in Beijing plain when various measures such as control of groundwater abstraction and increase of artificial recharge combine favourably.

Lifting the Green Veil: A Fresh Look at Synoptic Vegetation Dynamics

NASA Astrophysics Data System (ADS)

Henebry, G. M.; Vina, A.; Gitelson, A. A.

2003-12-01

Observing the dynamics of the vegetated land surface synoptically from spaceborne sensors plays a key role in understanding the global water, carbon, and nitrogen cycles, land cover and land use change, and biodiversity mapping. For the past three decades the study of global and regional vegetation dynamics has relied on satellite observations of the distinctive spectral contrast between red and near infrared reflectance exhibited by photosynthetically active green vegetation. It has long been recognized, however, that the spectral vegetation index with the widest currency-the Normalized Difference Vegetation Index (NDVI)-suffers a rapid decrease of sensitivity even at moderate Leaf Area Index (LAI) values of 2 to 4, as are commonly encountered in croplands and woodlands. This decrease in NDVI sensitivity casts a green veil over the land surface that obscures vegetation dynamics across vast areas during much of the growing season. This veil has important consequences for monitoring vegetation dynamics, developing land surface climatologies, and detecting significant changes. A straightforward modification of the NDVI, developed to increase its sensitivity under higher green biomass conditions, was applied to a standard, widely available AVHRR NDVI dataset for the conterminous US. The new Wide Dynamic Range Vegetation Index (WDRVI) exhibited increases in sensitivity between 30%-50% for Omernik Level III ecoregions dominated by woodlands, croplands, and grasslands. Ecoregions with lower aboveground net primary production, such as aridlands and semi-arid grasslands, showed no increase in sensitivity of the WDRVI over the NDVI. This powerful, new but simple approach creates an opportunity for a fresh look at the satellite data record. Further, it offers the possibility for significant improvements in the retrievals of canopy variables for carbon and nitrogen models, more accurate land surface characterizations for numerical weather prediction models, more sensitive analyses of land cover / land use change, and improvements in habitat mapping for biodiversity management.

Comparison of Atmospheric Parameters Derived from In-Situ and Hyper-/Multispectral Remote Sensing Data of Beautiful Bavarian Lakes

NASA Astrophysics Data System (ADS)

Riedel, S.; Gege, P.; Schneider, M.; Pfug, B.; Oppelt, N.

2016-08-01

Atmospheric correction is a critical step and can be a limiting factor in the extraction of aquatic ecosystem parameters from remote sensing data of coastal and lake waters. Atmospheric correction models commonly in use for open ocean water and land surfaces can lead to large errors when applied to hyperspectral images taken from satellite or aircraft. The main problems arise from uncertainties in aerosol parameters and neglecting the adjacency effect, which originates from multiple scattering of upwelling radiance from the surrounding land. To better understand the challenges for developing an atmospheric correction model suitable for lakes, we compare atmospheric parameters derived from Sentinel- 2A and airborne hyperspectral data (HySpex) of two Bavarian lakes (Klostersee, Lake Starnberg) with in-situ measurements performed with RAMSES and Ibsen spectrometer systems and a Microtops sun photometer.

Land cover change or land-use intensification: simulating land system change with a global-scale land change model.

PubMed

van Asselen, Sanneke; Verburg, Peter H

2013-12-01

Land-use change is both a cause and consequence of many biophysical and socioeconomic changes. The CLUMondo model provides an innovative approach for global land-use change modeling to support integrated assessments. Demands for goods and services are, in the model, supplied by a variety of land systems that are characterized by their land cover mosaic, the agricultural management intensity, and livestock. Land system changes are simulated by the model, driven by regional demand for goods and influenced by local factors that either constrain or promote land system conversion. A characteristic of the new model is the endogenous simulation of intensification of agricultural management versus expansion of arable land, and urban versus rural settlements expansion based on land availability in the neighborhood of the location. Model results for the OECD Environmental Outlook scenario show that allocation of increased agricultural production by either management intensification or area expansion varies both among and within world regions, providing useful insight into the land sparing versus land sharing debate. The land system approach allows the inclusion of different types of demand for goods and services from the land system as a driving factor of land system change. Simulation results are compared to observed changes over the 1970-2000 period and projections of other global and regional land change models. © 2013 John Wiley & Sons Ltd.

A Bayesian Hierarchical Modeling Approach to Predicting Flow in Ungauged Basins

NASA Astrophysics Data System (ADS)

Gronewold, A.; Alameddine, I.; Anderson, R. M.

2009-12-01

Recent innovative approaches to identifying and applying regression-based relationships between land use patterns (such as increasing impervious surface area and decreasing vegetative cover) and rainfall-runoff model parameters represent novel and promising improvements to predicting flow from ungauged basins. In particular, these approaches allow for predicting flows under uncertain and potentially variable future conditions due to rapid land cover changes, variable climate conditions, and other factors. Despite the broad range of literature on estimating rainfall-runoff model parameters, however, the absence of a robust set of modeling tools for identifying and quantifying uncertainties in (and correlation between) rainfall-runoff model parameters represents a significant gap in current hydrological modeling research. Here, we build upon a series of recent publications promoting novel Bayesian and probabilistic modeling strategies for quantifying rainfall-runoff model parameter estimation uncertainty. Our approach applies alternative measures of rainfall-runoff model parameter joint likelihood (including Nash-Sutcliffe efficiency, among others) to simulate samples from the joint parameter posterior probability density function. We then use these correlated samples as response variables in a Bayesian hierarchical model with land use coverage data as predictor variables in order to develop a robust land use-based tool for forecasting flow in ungauged basins while accounting for, and explicitly acknowledging, parameter estimation uncertainty. We apply this modeling strategy to low-relief coastal watersheds of Eastern North Carolina, an area representative of coastal resource waters throughout the world because of its sensitive embayments and because of the abundant (but currently threatened) natural resources it hosts. Consequently, this area is the subject of several ongoing studies and large-scale planning initiatives, including those conducted through the United States Environmental Protection Agency (USEPA) total maximum daily load (TMDL) program, as well as those addressing coastal population dynamics and sea level rise. Our approach has several advantages, including the propagation of parameter uncertainty through a nonparametric probability distribution which avoids common pitfalls of fitting parameters and model error structure to a predetermined parametric distribution function. In addition, by explicitly acknowledging correlation between model parameters (and reflecting those correlations in our predictive model) our model yields relatively efficient prediction intervals (unlike those in the current literature which are often unnecessarily large, and may lead to overly-conservative management actions). Finally, our model helps improve understanding of the rainfall-runoff process by identifying model parameters (and associated catchment attributes) which are most sensitive to current and future land use change patterns. Disclaimer: Although this work was reviewed by EPA and approved for publication, it may not necessarily reflect official Agency policy.

High Resolution, Consistent Online Estimation of Potential Flood Damage in The Netherlands

NASA Astrophysics Data System (ADS)

Hoes, O.; Hut, R.; van Leeuwen, E.

2014-12-01

In the current age where water authorities no longer blindly design and maintain all infrastructure just to meet a certain standardized return period, accurate estimation of potential flood damage is important in decision making with regards to flood prevention measures. We identify three issues with current methods of estimating flood damages. Firstly, common practice is to assume that for a given land use type, damage is mainly dependent on inundation depth, and sometimes flow velocity. We recognize that depending on the type of land use inundation depth, velocity, flood duration, season, detour time and recovery time influences the amount of damage significantly. Secondly, setting stage-damage curves is usually left to an end user and can thus vary between different water authorities within a single country. What was needed at a national level is a common way of calculating flood damages, so different prevention measures can be fairly compared. Finally, most flood models use relatively large grid cells, usually in the order of 25 m2 or coarser. Especially in urban areas this leads to obvious errors: different land uses (shops, housing, park, are all classified as "urban" and treated equally. To tackle these issues we developed a web-based model which can be accessed via www.waterschadeschatter.nl (water schade schatter is Dutch for water damage estimator). It includes all necessary data sources to calculate the damage of any potential flood in the Netherlands. It uses different damage functions for different land use types, which the user can, but need not change. It runs on 0.25m2 grid cells. Both the datasets required and the amount of calculation needed is more than a desktop computer can handle. In order to start a calculation a user needs to upload the relevant flood information to the website. The calculation is divided over several multicore servers, after which the user will receive an email with a link to the results of his calculations. Our presentation will include a life demonstration of our online model.

Predicting diffuse microbial pollution risk across catchments: The performance of SCIMAP and recommendations for future development.

PubMed

Porter, Kenneth D H; Reaney, Sim M; Quilliam, Richard S; Burgess, Chris; Oliver, David M

2017-12-31

Microbial pollution of surface waters in agricultural catchments can be a consequence of poor farm management practices, such as excessive stocking of livestock on vulnerable land or inappropriate handling of manures and slurries. Catchment interventions such as fencing of watercourses, streamside buffer strips and constructed wetlands have the potential to reduce faecal pollution of watercourses. However these interventions are expensive and occupy valuable productive land. There is, therefore, a requirement for tools to assist in the spatial targeting of such interventions to areas where they will have the biggest impact on water quality improvements whist occupying the minimal amount of productive land. SCIMAP is a risk-based model that has been developed for this purpose but with a focus on diffuse sediment and nutrient pollution. In this study we investigated the performance of SCIMAP in predicting microbial pollution of watercourses and assessed modelled outputs of E. coli, a common faecal indicator organism (FIO), against observed water quality information. SCIMAP was applied to two river catchments in the UK. SCIMAP uses land cover risk weightings, which are routed through the landscape based on hydrological connectivity to generate catchment scale maps of relative in-stream pollution risk. Assessment of the model's performance and derivation of optimum land cover risk weightings was achieved using a Monte-Carlo sampling approach. Performance of the SCIMAP framework for informing on FIO risk was variable with better performance in the Yealm catchment (r s =0.88; p<0.01) than the Wyre (r s =-0.36; p>0.05). Across both catchments much uncertainty was associated with the application of optimum risk weightings attributed to different land use classes. Overall, SCIMAP showed potential as a useful tool in the spatial targeting of FIO diffuse pollution management strategies; however, improvements are required to transition the existing SCIMAP framework to a robust FIO risk-mapping tool. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Modeling the human invader in the United States

USGS Publications Warehouse

Stohlgren, Thomas J.; Jarnevich, Catherine S.; Giri, Chandra P.

2010-01-01

Modern biogeographers recognize that humans are seen as constituents of ecosystems, drivers of significant change, and perhaps, the most invasive species on earth. We found it instructive to model humans as invasive organisms with the same environmental factors. We present a preliminary model of the spread of modern humans in the conterminous United States between 1992 and 2001 based on a subset of National Land Cover Data (NLCD), a time series LANDSAT product. We relied on the commonly used Maxent model, a species-environmental matching model, to map urbanization. Results: Urban areas represented 5.1% of the lower 48 states in 2001, an increase of 7.5% (18,112 km2) in the nine year period. At this rate, an area the size of Massachusetts is converted to urban land use every ten years. We used accepted models commonly used for mapping plant and animal distributions and found that climatic and environmental factors can strongly predict our spread (i.e., the conversion of forests, shrub/grass, and wetland areas into urban areas), with a 92.5% success rate (Area Under the Curve). Adding a roads layer in the model improved predictions to a 95.5% success rate. 8.8% of the 1-km2> cells in the conterminous U.S. now have a major road in them. In 2001, 0.8% of 1-km2 > cells in the U.S. had an urbanness value of > 800, (>89% of a 1-km2> cell is urban), while we predict that 24.5% of 1-km2> cells in the conterminous U.S. will be > 800 eventually. Main conclusion: Humans have a highly predictable pattern of urbanization based on climatic and topographic variables. Conservation strategies may benefit from that predictability.

Evidence supporting the need for a common soil monitoring protocol

Treesearch

Derrick A. Reeves; Mark D. Coleman; Deborah S. Page-Dumroese

2013-01-01

Many public land management agencies monitor forest soils for levels of disturbance related to management activities. Although several soil disturbance monitoring protocols based on visual observation have been developed to assess the amount and types of disturbance caused by forest management, no common method is currently used on National Forest lands in the United...

Revitalization of the shared commons: education for sustainability and marginalized cultures

NASA Astrophysics Data System (ADS)

Glasson, George E.

2010-06-01

Education for sustainability provides a vision for revitalizing the environmental commons while preserving cultural traditions and human rights. What happens if the environmental commons is shared by two politically disparate and conflicting cultures? As in many shared common lands, what happens if one culture is dominant and represents a more affluent society with more resources and educational opportunities? In the case of the Tal and Alkaher study (Cult Stud Sci Edu, 2009), asymmetric power differences between the dominant Israeli society and the minority Arab population yielded different environmental narratives and perceptions of students involved in learning about a mediated conflict in national park land. Similarly, marginalized indigenous cultures in Malawi, Africa share common lands with the dominant European landowners but have distinctly different environmental narratives. Although indigenous ways of living with nature contribute to the sustainability of the environment and culture, African funds of knowledge are conspicuously absent from the Eurocentric school science curriculum. In contrast, examples of experiential learning and recent curriculum development efforts in sustainability science in Malawi are inclusive of indigenous knowledge and practices and are essential for revitalizing the shared commons.

Comprehensive Representation of Hydrologic and Geomorphic Process Coupling in Numerical Models: Internal Dynamics and Basin Evolution

NASA Astrophysics Data System (ADS)

Istanbulluoglu, E.; Vivoni, E. R.; Ivanov, V. Y.; Bras, R. L.

2005-12-01

Landscape morphology has an important control on the spatial and temporal organization of basin hydrologic response to climate forcing, affecting soil moisture redistribution as well as vegetation function. On the other hand, erosion, driven by hydrology and modulated by vegetation, produces landforms over geologic time scales that reflect characteristic signatures of the dominant land forming process. Responding to extreme climate events or anthropogenic disturbances of the land surface, infrequent but rapid forms of erosion (e.g., arroyo development, landsliding) can modify topography such that basin hydrology is significantly influenced. Despite significant advances in both hydrologic and geomorphic modeling over the past two decades, the dynamic interactions between basin hydrology, geomorphology and terrestrial ecology are not adequately captured in current model frameworks. In order to investigate hydrologic-geomorphic-ecologic interactions at the basin scale we present initial efforts in integrating the CHILD landscape evolution model (Tucker et al. 2001) with the tRIBS hydrology model (Ivanov et al. 2004), both developed in a common software environment. In this talk, we present preliminary results of the numerical modeling of the coupled evolution of basin hydro-geomorphic response and resulting landscape morphology in two sets of examples. First, we discuss the long-term evolution of both the hydrologic response and the resulting basin morphology from an initially uplifted plateau. In the second set of modeling experiments, we implement changes in climate and land-use to an existing topography and compare basin hydrologic response to the model results when landscape form is fixed (e.g. no coupling between hydrology and geomorphology). Model results stress the importance of internal basin dynamics, including runoff generation mechanisms and hydrologic states, in shaping hydrologic response as well as the importance of employing comprehensive conceptualizations of hydrology in modeling landscape evolution.

Effects of Experimental Anterior Knee Pain on Muscle Activation During Landing and Jumping Performed at Various Intensities.

PubMed

Park, Jihong; Denning, W Matt; Pitt, Jordan D; Francom, Devin; Hopkins, J Ty; Seeley, Matthew K

2017-01-01

Although knee pain is common, some facets of this pain are unclear. The independent effects (ie, independent from other knee injury or pathology) of knee pain on neural activation of lower-extremity muscles during landing and jumping have not been observed. To investigate the independent effects of knee pain on lower-extremity muscle (gastrocnemius, vastus medialis, medial hamstrings, gluteus medius, and gluteus maximus) activation amplitude during landing and jumping, performed at 2 different intensities. Laboratory-based, pretest, posttest, repeated-measures design, where all subjects performed both data-collection sessions. Thirteen able-bodied subjects performed 2 different land and jump tasks (forward and lateral) under 2 different conditions (control and pain), at 2 different intensities (high and low). For the pain condition, experimental knee pain was induced via a hypertonic saline injection into the right infrapatellar fat pad. Functional linear models were used to evaluate the influence of experimental knee pain on muscle-activation amplitude throughout the 2 land and jump tasks. Experimental knee pain independently altered activation for all of the observed muscles during various parts of the 2 different land and jump tasks. These activation alterations were not consistently influenced by task intensity. Experimental knee pain alters activation amplitude of various lower-extremity muscles during landing and jumping. The nature of the alteration varies between muscles, intensities, and phases of the movement (ie, landing and jumping). Generally, experimental knee pain inhibits the gastrocnemius, medial hamstring, and gluteus medius during landing while independently increasing activation of the same muscles during jumping.

Environmental impacts of in-house windrow composting of broiler litter prior to land application in subtropical/semi-arid conditions

USDA-ARS?s Scientific Manuscript database

Land application to crop and pasture land is a common and effective method of utilizing the resource value of poultry litter. In-house windrow composting of litter is an emerging management practice with the potential to mitigate water quality and nuisance odor concerns associated with land applica...

78 FR 77488 - Notice of Realty Action: Recreation and Public Purposes Act Classification of Public Land in...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-23

... laws. 5. The above described land has been used for solid waste disposal. Solid waste commonly includes... DEPARTMENT OF THE INTERIOR Bureau of Land Management [LLNML00000 L14300000.FR0000 NMNM 037574] Notice of Realty Action: Recreation and Public Purposes Act Classification of Public Land in Sierra...

An integrated approach to modeling resource utilization for rural communities in developing countries.

PubMed

Hartter, Joel; Boston, Kevin

2007-10-01

Resource consumption in developing countries has been the focus of a considerable amount of research. What has been understudied however, has been the feedback affects of resource consumption on resource availability to both households and communities. Heavy reliance on natural resources and intensive smallholder agriculture common to many rural communities in developing countries has forced people to fulfill short-term needs to the detriment of long-term ecological and livelihood sustainability. This paper introduces a conceptual framework to examine how individuals and households fulfill daily caloric needs and the aggregate effects on resource availability and consumption. Data were collected from a large number of published case studies of rural land-use dynamics, growth and yield models, and human livelihoods were reviewed from scientific journals, reports published by NGOs, and government reports. Using inputs defined by the user, the model tracks annual fuelwood and agricultural land use based on meeting individual energy demands. A case-study-based analysis was patterned after smallholder agriculturalists at the family and community level. Three scenarios are presented in this paper using data from Uganda to illustrate the application of this model.

Examining the utility of satellite-based wind sheltering estimates for lake hydrodynamic modeling

USGS Publications Warehouse

Van Den Hoek, Jamon; Read, Jordan S.; Winslow, Luke A.; Montesano, Paul; Markfort, Corey D.

2015-01-01

Satellite-based measurements of vegetation canopy structure have been in common use for the last decade but have never been used to estimate canopy's impact on wind sheltering of individual lakes. Wind sheltering is caused by slower winds in the wake of topography and shoreline obstacles (e.g. forest canopy) and influences heat loss and the flux of wind-driven mixing energy into lakes, which control lake temperatures and indirectly structure lake ecosystem processes, including carbon cycling and thermal habitat partitioning. Lakeshore wind sheltering has often been parameterized by lake surface area but such empirical relationships are only based on forested lakeshores and overlook the contributions of local land cover and terrain to wind sheltering. This study is the first to examine the utility of satellite imagery-derived broad-scale estimates of wind sheltering across a diversity of land covers. Using 30 m spatial resolution ASTER GDEM2 elevation data, the mean sheltering height, hs, being the combination of local topographic rise and canopy height above the lake surface, is calculated within 100 m-wide buffers surrounding 76,000 lakes in the U.S. state of Wisconsin. Uncertainty of GDEM2-derived hs was compared to SRTM-, high-resolution G-LiHT lidar-, and ICESat-derived estimates of hs, respective influences of land cover type and buffer width on hsare examined; and the effect of including satellite-based hs on the accuracy of a statewide lake hydrodynamic model was discussed. Though GDEM2 hs uncertainty was comparable to or better than other satellite-based measures of hs, its higher spatial resolution and broader spatial coverage allowed more lakes to be included in modeling efforts. GDEM2 was shown to offer superior utility for estimating hs compared to other satellite-derived data, but was limited by its consistent underestimation of hs, inability to detect within-buffer hs variability, and differing accuracy across land cover types. Nonetheless, considering a GDEM2 hs-derived wind sheltering potential improved the modeled lake temperature root mean square error for non-forested lakes by 0.72 °C compared to a commonly used wind sheltering model based on lake area alone. While results from this study show promise, the limitations of near-global GDEM2 data in timeliness, temporal and spatial resolution, and vertical accuracy were apparent. As hydrodynamic modeling and high-resolution topographic mapping efforts both expand, future remote sensing-derived vegetation structure data must be improved to meet wind sheltering accuracy requirements to expand our understanding of lake processes.

Evolutionary origin of phytochrome responses and signaling in land plants.

PubMed

Inoue, Keisuke; Nishihama, Ryuichi; Kohchi, Takayuki

2017-11-01

Phytochromes comprise one of the major photoreceptor families in plants, and they regulate many aspects of plant growth and development throughout the plant life cycle. A canonical land plant phytochrome originated in the common ancestor of streptophytes. Phytochromes have diversified in seed plants and some basal land plants because of lineage-specific gene duplications that occurred during the course of land plant evolution. Molecular genetic analyses using Arabidopsis thaliana suggested that there are two types of phytochromes in angiosperms, light-labile type I and light-stable type II, which have different signaling mechanisms and which regulate distinct responses. In basal land plants, little is known about molecular mechanisms of phytochrome signaling, although red light/far-red photoreversible physiological responses and the distribution of phytochrome genes are relatively well documented. Recent advances in molecular genetics using the moss Physcomitrella patens and the liverwort Marchantia polymorpha revealed that basal land plants show far-red-induced responses and that the establishment of phytochrome-mediated transcriptional regulation dates back to at least the common ancestor of land plants. In this review, we summarize our knowledge concerning functions of land plant phytochromes, especially in basal land plants, and discuss subfunctionalization/neofunctionalization of phytochrome signaling during the course of land plant evolution. © 2017 John Wiley & Sons Ltd.

Spatial variability in levels of benzene, formaldehyde, and total benzene, toluene, ethylbenzene and xylenes in New York City: a land-use regression study.

PubMed

Kheirbek, Iyad; Johnson, Sarah; Ross, Zev; Pezeshki, Grant; Ito, Kazuhiko; Eisl, Holger; Matte, Thomas

2012-07-31

Hazardous air pollutant exposures are common in urban areas contributing to increased risk of cancer and other adverse health outcomes. While recent analyses indicate that New York City residents experience significantly higher cancer risks attributable to hazardous air pollutant exposures than the United States as a whole, limited data exist to assess intra-urban variability in air toxics exposures. To assess intra-urban spatial variability in exposures to common hazardous air pollutants, street-level air sampling for volatile organic compounds and aldehydes was conducted at 70 sites throughout New York City during the spring of 2011. Land-use regression models were developed using a subset of 59 sites and validated against the remaining 11 sites to describe the relationship between concentrations of benzene, total BTEX (benzene, toluene, ethylbenzene, xylenes) and formaldehyde to indicators of local sources, adjusting for temporal variation. Total BTEX levels exhibited the most spatial variability, followed by benzene and formaldehyde (coefficient of variation of temporally adjusted measurements of 0.57, 0.35, 0.22, respectively). Total roadway length within 100 m, traffic signal density within 400 m of monitoring sites, and an indicator of temporal variation explained 65% of the total variability in benzene while 70% of the total variability in BTEX was accounted for by traffic signal density within 450 m, density of permitted solvent-use industries within 500 m, and an indicator of temporal variation. Measures of temporal variation, traffic signal density within 400 m, road length within 100 m, and interior building area within 100 m (indicator of heating fuel combustion) predicted 83% of the total variability of formaldehyde. The models built with the modeling subset were found to predict concentrations well, predicting 62% to 68% of monitored values at validation sites. Traffic and point source emissions cause substantial variation in street-level exposures to common toxic volatile organic compounds in New York City. Land-use regression models were successfully developed for benzene, formaldehyde, and total BTEX using spatial indicators of on-road vehicle emissions and emissions from stationary sources. These estimates will improve the understanding of health effects of individual pollutants in complex urban pollutant mixtures and inform local air quality improvement efforts that reduce disparities in exposure.

Using stylized agent-based models for population-environment research: A case study from the Galápagos Islands

PubMed Central

Miller, Brian W.; Breckheimer, Ian; McCleary, Amy L.; Guzmán-Ramirez, Liza; Caplow, Susan C.; Jones-Smith, Jessica C.; Walsh, Stephen J.

2010-01-01

Agent Based Models (ABMs) are powerful tools for population-environment research but are subject to trade-offs between model complexity and abstraction. This study strikes a compromise between abstract and highly specified ABMs by designing a spatially explicit, stylized ABM and using it to explore policy scenarios in a setting that is facing substantial conservation and development challenges. Specifically, we present an ABM that reflects key Land Use / Land Cover (LULC) dynamics and livelihood decisions on Isabela Island in the Galápagos Archipelago of Ecuador. We implement the model using the NetLogo software platform, a free program that requires relatively little programming experience. The landscape is composed of a satellite-derived distribution of a problematic invasive species (common guava) and a stylized representation of the Galápagos National Park, the community of Puerto Villamil, the agricultural zone, and the marine area. The agent module is based on publicly available data and household interviews, and represents the primary livelihoods of the population in the Galápagos Islands – tourism, fisheries, and agriculture. We use the model to enact hypothetical agricultural subsidy scenarios aimed at controlling invasive guava and assess the resulting population and land cover dynamics. Findings suggest that spatially explicit, stylized ABMs have considerable utility, particularly during preliminary stages of research, as platforms for (1) sharpening conceptualizations of population-environment systems, (2) testing alternative scenarios, and (3) uncovering critical data gaps. PMID:20539752

Using stylized agent-based models for population-environment research: A case study from the Galápagos Islands.

PubMed

Miller, Brian W; Breckheimer, Ian; McCleary, Amy L; Guzmán-Ramirez, Liza; Caplow, Susan C; Jones-Smith, Jessica C; Walsh, Stephen J

2010-05-01

Agent Based Models (ABMs) are powerful tools for population-environment research but are subject to trade-offs between model complexity and abstraction. This study strikes a compromise between abstract and highly specified ABMs by designing a spatially explicit, stylized ABM and using it to explore policy scenarios in a setting that is facing substantial conservation and development challenges. Specifically, we present an ABM that reflects key Land Use / Land Cover (LULC) dynamics and livelihood decisions on Isabela Island in the Galápagos Archipelago of Ecuador. We implement the model using the NetLogo software platform, a free program that requires relatively little programming experience. The landscape is composed of a satellite-derived distribution of a problematic invasive species (common guava) and a stylized representation of the Galápagos National Park, the community of Puerto Villamil, the agricultural zone, and the marine area. The agent module is based on publicly available data and household interviews, and represents the primary livelihoods of the population in the Galápagos Islands - tourism, fisheries, and agriculture. We use the model to enact hypothetical agricultural subsidy scenarios aimed at controlling invasive guava and assess the resulting population and land cover dynamics. Findings suggest that spatially explicit, stylized ABMs have considerable utility, particularly during preliminary stages of research, as platforms for (1) sharpening conceptualizations of population-environment systems, (2) testing alternative scenarios, and (3) uncovering critical data gaps.

A Systems Approach to the Estimation of Ecosystem and Human Health Stressors in Air, Land and Water

NASA Astrophysics Data System (ADS)

Cooter, E. J.; Dennis, R. L.; Bash, J. O.

2013-12-01

Nitrogen (N) and sulfur oxides (SOx) in air, land and water media are parts of tightly coupled geophysical systems resulting in multiple routes for human and ecosystem exposure. For instance, excess forms of total reactive N in water can lead to harmful algal blooms, with the depletion of oxygen and adverse impacts to aquatic ecosystem productivity in coastal estuaries. Acidic deposition can result in lost forest productivity for terrestrial ecosystem and impacts to trout and other fishery resources in inland waters. Human pulmonary health can be impaired when N and SOx in the atmosphere lead to the generation of ozone and particulate matter (PM). Atmospheric N deposition can also contribute to eutrophication of drinking water sources. The U.S. Environmental Protection Agency (USEPA) Office of Research and Development (ORD) has embarked on the development of a multi-media 'one environment' systems approach to these issues to help develop management decisions that create win-win policies. The purpose of this project is to develop a 'one environment' set of models that can inform protection of ecosystems and human health in both the current state and under future climate scenarios. The research framework focuses on three interrelated themes; coupling air quality with land use and agricultural land management, connecting the hydrosphere (i.e., coupling meteorology and hydrology) and linking the air/land/hydrosphere with ecosystem models and benefits models. We will present an overall modeling framework and then move to the presentation of on-going research results related to direct linkage of air quality with land use and agricultural land management. A modeling interface system has been developed that facilitates the simulation of field-scale agricultural land management decisions over a gridded domain at multiple grid resolutions for the Contiguous United States (CONUS) using a modified version of the USDA EPIC (Environmental Policy Integrated Climate) model. EPIC is a field-scale semi-empirical biogeochemical process model that operates on a daily time step. Options have been added to the CMAQ (Community Multi-Scale Air Quality) model to simulate bidirectional flux of ammonia that require the temporally and spatially detailed information produced by the combined FEST-C (Fertilizer Emissions Scenario Tool for CMAQ) and EPIC system (FEST-C/EPIC). An example of improved estimates of wet and dry atmospheric N deposition and ambient PM concentrations that result from coupling these two models using a common simulated meteorology will be presented. The biogeochemistry in EPIC also allows us to explore the potential co-benefits and unanticipated outcomes of changing atmospheric deposition in response to regulated emissions, management or climate changes on field-scale N balances and N export in surface runoff, lateral flow, and in percolation or as attached to particles leaving the field surface. An illustrative example of N status response to select atmospheric deposition changes will be presented. Methods are also outlined for further combining these results with hydrologic models such as SWAT (Soil and Water Assessment Tool) and the NEWS (Nutrient Export from WaterSheds) model.

Microhabitat selection by three common bird species of montane farmlands in Northern Greece.

PubMed

Tsiakiris, Rigas; Stara, Kalliopi; Pantis, John; Sgardelis, Stefanos

2009-11-01

Common farmland birds are declining throughout Europe; however, marginal farmlands that escaped intensification or land abandonment remain a haven for farmland species in some Mediterranean mountains. The purpose of this study is to identify the most important anthropogenic microhabitat characteristics for Red-Backed Shrike (Lanius collurio), Corn Bunting (Miliaria calandra) and Common Whitethroat (Sylvia communis) in three such areas within the newly established Northern Pindos National Park. We compare land use structural and physiognomic characteristics of the habitat within 133 plots containing birds paired with randomly selected "non-bird" plots. Using logistic regression and classification-tree models we identify the specific habitat requirements for each of the three birds. The three species show a preference for agricultural mosaics dominated by rangelands with scattered shrub or short trees mixed with arable land. Areas with dikes and dirt roads are preferred by all three species, while the presence of fences and periodically burned bushes and hedges are of particular importance for Red-Backed Shrike. Across the gradient of vegetation density and height, M. calandra is mostly found in grasslands with few dwarf shrubs and short trees, S. communis in places with more dense and tall vegetation of shrub, trees and hedges, and L. collurio, being a typical bird of ecotones, occurs in both habitats and in intermediate situations. In all cases those requirements are associated with habitat features maintained either directly or indirectly by the traditional agricultural activities in the area and particularly by the long established extensive controlled grazing that prevent shrub expansion.

Microhabitat Selection by Three Common Bird Species of Montane Farmlands in Northern Greece

NASA Astrophysics Data System (ADS)

Tsiakiris, Rigas; Stara, Kalliopi; Pantis, John; Sgardelis, Stefanos

2009-11-01

Common farmland birds are declining throughout Europe; however, marginal farmlands that escaped intensification or land abandonment remain a haven for farmland species in some Mediterranean mountains. The purpose of this study is to identify the most important anthropogenic microhabitat characteristics for Red-Backed Shrike ( Lanius collurio), Corn Bunting ( Miliaria calandra) and Common Whitethroat ( Sylvia communis) in three such areas within the newly established Northern Pindos National Park. We compare land use structural and physiognomic characteristics of the habitat within 133 plots containing birds paired with randomly selected “non-bird” plots. Using logistic regression and classification-tree models we identify the specific habitat requirements for each of the three birds. The three species show a preference for agricultural mosaics dominated by rangelands with scattered shrub or short trees mixed with arable land. Areas with dikes and dirt roads are preferred by all three species, while the presence of fences and periodically burned bushes and hedges are of particular importance for Red-Backed Shrike. Across the gradient of vegetation density and height, M. calandra is mostly found in grasslands with few dwarf shrubs and short trees, S. communis in places with more dense and tall vegetation of shrub, trees and hedges, and L. collurio, being a typical bird of ecotones, occurs in both habitats and in intermediate situations. In all cases those requirements are associated with habitat features maintained either directly or indirectly by the traditional agricultural activities in the area and particularly by the long established extensive controlled grazing that prevent shrub expansion.

Variability of Total Below Ground Carbon Allocation amongst Common Agricultural Land Management Practices: a Case Study

NASA Astrophysics Data System (ADS)

Wacha, K. M.; Papanicolaou, T.; Wilson, C. G.

2010-12-01

Field measurements and numerical models are currently being used to estimate quantities of Total Belowground Carbon Allocation (TBCA) for three representative land uses, viz. corn, soybeans, and prairie bromegrass for CRP (Conservation Reserve Program) of an agricultural Iowa sub-watershed, located within the Clear Creek Watershed (CCW). Since it is difficult to measure TBCA directly, a mass balance approach has been implemented to estimate TBCA as follows: TBCA = FS + FE+ Δ(CS + CR + CL) - FA , where the term Fs denotes soil respiration; FE is the carbon content of the eroded/deposited soil; ΔCS, ΔCR, ΔCL denote the changes in carbon content of the mineral soil, plant roots, and litter layer, respectively; and FA is the above ground litter fall of dead plant material to the soil. The terms are hypothesized to have a huge impact on TBCA within agricultural settings due to intensive tillage practices, water-driven soil erosion/deposition, and high usage of fertilizer. To test our hypothesis, field measurements are being performed at the plot scale, replicating common agricultural land management practices. Soil respiration (FS) is being measured with an EGM-4 CO2 Gas Analyzer and SRC-1 Soil Respiration Chamber (PP Systems), soil moisture and temperature are recorded in the top 20 cm for each respective soil respiration measurement, and litter fall rates (FA) are acquired by collecting the residue in a calibrated pan. The change in carbon content of the soil (ΔCS), roots (ΔCR) and litter layer (ΔCL) are being analyzed by collecting soil samples throughout the life cycle of the plant. To determine the term FE for the three representative land management practices, a funnel collection system located at the plot outlet was used for collecting the eroded material after natural rainfall events. Field measurements of TBCA at the plot scale via the mass balance approach are used to calibrate the numerical agronomic process model DAYCENT, which simulates the daily fluxes of carbon (CS) and soil respiration (FS) and incorporates a plant-growth model that allows the determination of the terms FA, CR, and CL. Once calibrated, DAYCENT can be used in conjunction with the Watershed Erosion Prediction Project (WEPP) model, which calculates erosion/deposition rates, to provide estimates of TBCA at a larger global scale.

Towards an improved and more flexible representation of water stress in coupled photosynthesis-stomatal conductance models; implications for simulated land surface fluxes and variables at various spatiotemporal scales

NASA Astrophysics Data System (ADS)

Egea, G.; Verhoef, A.; Vidale, P. L.; Black, E.; Van den Hoof, C.

2012-04-01

Coupled photosynthesis-stomatal conductance (A-gs) models are commonly used in ecosystem models to represent the exchange rate of CO2 and H2O between vegetation and the atmosphere. The ways these models account for water stress differ greatly among modelling schemes. This study provides insight into the impact of contrasting model configurations of water stress on the simulated leaf-level values of net photosynthesis (A), stomatal conductance (gs), the functional relationship among them and their ratio, the intrinsic water use efficiency (A/gs), as soil dries. A simple, yet versatile, normalized soil moisture dependent function was used to account for the effects of water stress on gs, on mesophyll conductance (gm ) and on the biochemical capacity (Egea et al., 2011). Model output was compared to leaf-level values obtained from the literature. The sensitivity analyses emphasized the necessity to combine both stomatal and non-stomatal limitations of A in coupled A-gs models to accurately capture the observed functional relationships A vs. gs and A/gs vs. gs in response to drought. Accounting for water stress in coupled A-gs models by imposing either stomatal or biochemical limitations of A, as commonly practiced in most ecosystem models, failed to reproduce the observed functional relationship between key leaf gas exchange attributes. A quantitative limitation analysis revealed that the general pattern of C3 photosynthetic response to water stress can be represented in coupled A-gs models by imposing the highest limitation strength to mesophyll conductance, then to stomatal conductance and finally to the biochemical capacity. This more realistic representation of soil water stress on the simulated leaf-level values of A and gs was embedded in the JULES (Joint UK Land Environment Simulator; Best et al., 2011), model and tested for a number of vegetation types, for which driving and flux verification data were available. These simulations provide an insight into the effect that the revised parameterization will have on GCM simulations of climate variability and change. Best, M. J. et al. (2011). The Joint UK Land Environment Simulator (JULES), model description - Part 1: Energy and water fluxes. Geosci. Model Dev., 4, 677-699. Egea, G., Verhoef, A., Vidale, P.L. (2011) Towards an improved and more flexible representation of water stress in coupled photosynthesis-stomatal conductance models. Agricultural and Forest Meteorology, 151 (10), 1370-1384.

The growth of finfish in global open-ocean aquaculture under climate change.

PubMed

Klinger, Dane H; Levin, Simon A; Watson, James R

2017-10-11

Aquaculture production is projected to expand from land-based operations to the open ocean as demand for seafood grows and competition increases for inputs to land-based aquaculture, such as freshwater and suitable land. In contrast to land-based production, open-ocean aquaculture is constrained by oceanographic factors, such as current speeds and seawater temperature, which are dynamic in time and space, and cannot easily be controlled. As such, the potential for offshore aquaculture to increase seafood production is tied to the physical state of the oceans. We employ a novel spatial model to estimate the potential of open-ocean finfish aquaculture globally, given physical, biological and technological constraints. Finfish growth potential for three common aquaculture species representing different thermal guilds-Atlantic salmon ( Salmo salar ), gilthead seabream ( Sparus aurata ) and cobia ( Rachycentron canadum )-is compared across species and regions and with climate change, based on outputs of a high-resolution global climate model. Globally, there are ample areas that are physically suitable for fish growth and potential expansion of the nascent aquaculture industry. The effects of climate change are heterogeneous across species and regions, but areas with existing aquaculture industries are likely to see increases in growth rates. In areas where climate change results in reduced growth rates, adaptation measures, such as selective breeding, can probably offset potential production losses. © 2017 The Author(s).

Soil Texture Often Exerts a Stronger Influence Than Precipitation on Mesoscale Soil Moisture Patterns

NASA Astrophysics Data System (ADS)

Dong, Jingnuo; Ochsner, Tyson E.

2018-03-01

Soil moisture patterns are commonly thought to be dominated by land surface characteristics, such as soil texture, at small scales and by atmospheric processes, such as precipitation, at larger scales. However, a growing body of evidence challenges this conceptual model. We investigated the structural similarity and spatial correlations between mesoscale (˜1-100 km) soil moisture patterns and land surface and atmospheric factors along a 150 km transect using 4 km multisensor precipitation data and a cosmic-ray neutron rover, with a 400 m diameter footprint. The rover was used to measure soil moisture along the transect 18 times over 13 months. Spatial structures of soil moisture, soil texture (sand content), and antecedent precipitation index (API) were characterized using autocorrelation functions and fitted with exponential models. Relative importance of land surface characteristics and atmospheric processes were compared using correlation coefficients (r) between soil moisture and sand content or API. The correlation lengths of soil moisture, sand content, and API ranged from 12-32 km, 13-20 km, and 14-45 km, respectively. Soil moisture was more strongly correlated with sand content (r = -0.536 to -0.704) than with API for all but one date. Thus, land surface characteristics exhibit coherent spatial patterns at scales up to 20 km, and those patterns often exert a stronger influence than do precipitation patterns on mesoscale spatial patterns of soil moisture.

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.

Taming Data to Make Decisions: Using a Spatial Fuzzy Logic Decision Support Framework to Inform Conservation and Land Use Planning

NASA Astrophysics Data System (ADS)

Sheehan, T.; Baker, B.; Degagne, R. S.

2015-12-01

With the abundance of data sources, analytical methods, and computer models, land managers are faced with the overwhelming task of making sense of a profusion of data of wildly different types. Luckily, fuzzy logic provides a method to work with different types of data using language-based propositions such as "the landscape is undisturbed," and a simple set of logic constructs. Just as many surveys allow different levels of agreement with a proposition, fuzzy logic allows values reflecting different levels of truth for a proposition. Truth levels fall within a continuum ranging from Fully True to Fully False. Hence a fuzzy logic model produces continuous results. The Environmental Evaluation Modeling System (EEMS) is a platform-independent, tree-based, fuzzy logic modeling framework. An EEMS model provides a transparent definition of an evaluation model and is commonly developed as a collaborative effort among managers, scientists, and GIS experts. Managers specify a set of evaluative propositions used to characterize the landscape. Scientists, working with managers, formulate functions that convert raw data values into truth values for the propositions and produce a logic tree to combine results into a single metric used to guide decisions. Managers, scientists, and GIS experts then work together to implement and iteratively tune the logic model and produce final results. We present examples of two successful EEMS projects that provided managers with map-based results suitable for guiding decisions: sensitivity and climate change exposure in Utah and the Colorado Plateau modeled for the Bureau of Land Management; and terrestrial ecological intactness in the Mojave and Sonoran region of southern California modeled for the Desert Renewable Energy Conservation Plan.

Harmonic regression of Landsat time series for modeling attributes from national forest inventory data

NASA Astrophysics Data System (ADS)

Wilson, Barry T.; Knight, Joseph F.; McRoberts, Ronald E.

2018-03-01

Imagery from the Landsat Program has been used frequently as a source of auxiliary data for modeling land cover, as well as a variety of attributes associated with tree cover. With ready access to all scenes in the archive since 2008 due to the USGS Landsat Data Policy, new approaches to deriving such auxiliary data from dense Landsat time series are required. Several methods have previously been developed for use with finer temporal resolution imagery (e.g. AVHRR and MODIS), including image compositing and harmonic regression using Fourier series. The manuscript presents a study, using Minnesota, USA during the years 2009-2013 as the study area and timeframe. The study examined the relative predictive power of land cover models, in particular those related to tree cover, using predictor variables based solely on composite imagery versus those using estimated harmonic regression coefficients. The study used two common non-parametric modeling approaches (i.e. k-nearest neighbors and random forests) for fitting classification and regression models of multiple attributes measured on USFS Forest Inventory and Analysis plots using all available Landsat imagery for the study area and timeframe. The estimated Fourier coefficients developed by harmonic regression of tasseled cap transformation time series data were shown to be correlated with land cover, including tree cover. Regression models using estimated Fourier coefficients as predictor variables showed a two- to threefold increase in explained variance for a small set of continuous response variables, relative to comparable models using monthly image composites. Similarly, the overall accuracies of classification models using the estimated Fourier coefficients were approximately 10-20 percentage points higher than the models using the image composites, with corresponding individual class accuracies between six and 45 percentage points higher.

[Abundance of larvae and nymphs of the taiga tick Ixodes persuicatus (Acari: Ixodidae) on small mammals in the cut-over lands of the middle taiga subzone of Karelia].

PubMed

Bugmyrin, S V; Bespiatova, L A; Anikanova, V S; Ieshko, E P

2009-01-01

Data of long-term investigations (1998-2004) on the abundance of the taiga tick larvae and nymphs in the cut-over lands of different age in the middle taiga subzone of Karelia (62 degrees 04'S; 33 degrees 55'W) are presented. The investigation was carried out on three model cut-over lands of different age: 1) "young" cut-over land; age of cut-over in the beginning of investigation is 7 years; Betula-Deschampsia cespitosa-Agrostis tenuis; 2) "middle" cut-over land; age of cut-over is 12 years; Salix-Deschampsia cespitosa-Agrostis tenuis; 3) "old" cut-over land; age of cut-over 25 years; Alnus incana-Rubus idaeus-grass. The number of ticks was estimated by using common parasitological indices: prevalence, abundance, and index of feeding intensity (the tick abundance multiply by the number of small mammals per hundred traps-nights). In the beginning of investigation the "young" cut-over land was a typical meadow association. The lowest tick abundance was recorded here. That was a result of unfavorable abiotic conditions and low number of small mammals in the beginning of summer. "Middle" cut-over land is characterized by the highest number of the tick larvae, which is the evidence for high number of the hosts of tick imago. "Old" cut-over land has the optimum conditions for development of taiga ticks. High abundance of the ticks (larvae and nymphs) was recorded during the whole period of investigations. The number of preimaginal ticks is shown to be much higher in cut-over lands as compared with that in mixed and coniferous forests, due to the higher number of small mammals.

Stream Sediment Sources in Midwest Agricultural Basins with Land Retirement along Channel.

PubMed

Williamson, T N; Christensen, V G; Richardson, W B; Frey, J W; Gellis, A C; Kieta, K A; Fitzpatrick, F A

2014-09-01

Documenting the effects of agricultural land retirement on stream-sediment sources is critical to identifying management practices that improve water quality and aquatic habitat. Particularly difficult to quantify are the effects from conservation easements that commonly are discontinuous along channelized streams and ditches throughout the agricultural midwestern United States. Our hypotheses were that sediment from cropland, retired land, stream banks, and roads would be discernible using isotopic and elemental concentrations and that source contributions would vary with land retirement distribution along tributaries of West Fork Beaver Creek in Minnesota. Channel-bed and suspended sediment were sampled at nine locations and compared with local source samples by using linear discriminant analysis and a four-source mixing model that evaluated seven tracers: In, P, total C, Be, Tl, Th, and Ti. The proportion of sediment sources differed significantly between suspended and channel-bed sediment. Retired land contributed to channel-bed sediment but was not discernible as a source of suspended sediment, suggesting that retired-land material was not mobilized during high-flow conditions. Stream banks were a large contributor to suspended sediment; however, the percentage of stream-bank sediment in the channel bed was lower in basins with more continuous retired land along the riparian corridor. Cropland sediments had the highest P concentrations; basins with the highest cropland-sediment contributions also had the highest P concentrations. Along stream reaches with retired land, there was a lower proportion of cropland material in suspended sediment relative to sites that had almost no land retirement, indicating less movement of nutrients and sediment from cropland to the channel as a result of land retirement. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Resource-mediated indirect effects of grassland management on arthropod diversity.

PubMed

Simons, Nadja K; Gossner, Martin M; Lewinsohn, Thomas M; Boch, Steffen; Lange, Markus; Müller, Jörg; Pašalić, Esther; Socher, Stephanie A; Türke, Manfred; Fischer, Markus; Weisser, Wolfgang W

2014-01-01

Intensive land use is a driving force for biodiversity decline in many ecosystems. In semi-natural grasslands, land-use activities such as mowing, grazing and fertilization affect the diversity of plants and arthropods, but the combined effects of different drivers and the chain of effects are largely unknown. In this study we used structural equation modelling to analyse how the arthropod communities in managed grasslands respond to land use and whether these responses are mediated through changes in resource diversity or resource quantity (biomass). Plants were considered resources for herbivores which themselves were considered resources for predators. Plant and arthropod (herbivores and predators) communities were sampled on 141 meadows, pastures and mown pastures within three regions in Germany in 2008 and 2009. Increasing land-use intensity generally increased plant biomass and decreased plant diversity, mainly through increasing fertilization. Herbivore diversity decreased together with plant diversity but showed no response to changes in plant biomass. Hence, land-use effects on herbivore diversity were mediated through resource diversity rather than quantity. Land-use effects on predator diversity were mediated by both herbivore diversity (resource diversity) and herbivore quantity (herbivore biomass), but indirect effects through resource quantity were stronger. Our findings highlight the importance of assessing both direct and indirect effects of land-use intensity and mode on different trophic levels. In addition to the overall effects, there were subtle differences between the different regions, pointing to the importance of regional land-use specificities. Our study underlines the commonly observed strong effect of grassland land use on biodiversity. It also highlights that mechanistic approaches help us to understand how different land-use modes affect biodiversity.

Resource-Mediated Indirect Effects of Grassland Management on Arthropod Diversity

PubMed Central

Simons, Nadja K.; Gossner, Martin M.; Lewinsohn, Thomas M.; Boch, Steffen; Lange, Markus; Müller, Jörg; Pašalić, Esther; Socher, Stephanie A.; Türke, Manfred; Fischer, Markus; Weisser, Wolfgang W.

2014-01-01

Intensive land use is a driving force for biodiversity decline in many ecosystems. In semi-natural grasslands, land-use activities such as mowing, grazing and fertilization affect the diversity of plants and arthropods, but the combined effects of different drivers and the chain of effects are largely unknown. In this study we used structural equation modelling to analyse how the arthropod communities in managed grasslands respond to land use and whether these responses are mediated through changes in resource diversity or resource quantity (biomass). Plants were considered resources for herbivores which themselves were considered resources for predators. Plant and arthropod (herbivores and predators) communities were sampled on 141 meadows, pastures and mown pastures within three regions in Germany in 2008 and 2009. Increasing land-use intensity generally increased plant biomass and decreased plant diversity, mainly through increasing fertilization. Herbivore diversity decreased together with plant diversity but showed no response to changes in plant biomass. Hence, land-use effects on herbivore diversity were mediated through resource diversity rather than quantity. Land-use effects on predator diversity were mediated by both herbivore diversity (resource diversity) and herbivore quantity (herbivore biomass), but indirect effects through resource quantity were stronger. Our findings highlight the importance of assessing both direct and indirect effects of land-use intensity and mode on different trophic levels. In addition to the overall effects, there were subtle differences between the different regions, pointing to the importance of regional land-use specificities. Our study underlines the commonly observed strong effect of grassland land use on biodiversity. It also highlights that mechanistic approaches help us to understand how different land-use modes affect biodiversity. PMID:25188423

Stream sediment sources in midwest agricultural basins with land retirement along channel

USGS Publications Warehouse

Williamson, Tanja N.; Christensen, Victoria G.; Richardson, William B.; Frey, Jeffrey W.; Gellis, Allen C.; Kieta, K. A.; Fitzpatrick, Faith A.

2014-01-01

Documenting the effects of agricultural land retirement on stream-sediment sources is critical to identifying management practices that improve water quality and aquatic habitat. Particularly difficult to quantify are the effects from conservation easements that commonly are discontinuous along channelized streams and ditches throughout the agricultural midwestern United States. Our hypotheses were that sediment from cropland, retired land, stream banks, and roads would be discernible using isotopic and elemental concentrations and that source contributions would vary with land retirement distribution along tributaries of West Fork Beaver Creek in Minnesota. Channel-bed and suspended sediment were sampled at nine locations and compared with local source samples by using linear discriminant analysis and a four-source mixing model that evaluated seven tracers: In, P, total C, Be, Tl, Th, and Ti. The proportion of sediment sources differed significantly between suspended and channel-bed sediment. Retired land contributed to channel-bed sediment but was not discernible as a source of suspended sediment, suggesting that retired-land material was not mobilized during high-flow conditions. Stream banks were a large contributor to suspended sediment; however, the percentage of stream-bank sediment in the channel bed was lower in basins with more continuous retired land along the riparian corridor. Cropland sediments had the highest P concentrations; basins with the highest cropland-sediment contributions also had the highest P concentrations. Along stream reaches with retired land, there was a lower proportion of cropland material in suspended sediment relative to sites that had almost no land retirement, indicating less movement of nutrients and sediment from cropland to the channel as a result of land retirement.

Modelling past land use using archaeological and pollen data

NASA Astrophysics Data System (ADS)

Pirzamanbein, Behnaz; Lindström, johan; Poska, Anneli; Gaillard-Lemdahl, Marie-José

2016-04-01

Accurate maps of past land use are necessary for studying the impact of anthropogenic land-cover changes on climate and biodiversity. We develop a Bayesian hierarchical model to reconstruct the land use using Gaussian Markov random fields. The model uses two observations sets: 1) archaeological data, representing human settlements, urbanization and agricultural findings; and 2) pollen-based land estimates of the three land-cover types Coniferous forest, Broadleaved forest and Unforested/Open land. The pollen based estimates are obtained from the REVEALS model, based on pollen counts from lakes and bogs. Our developed model uses the sparse pollen-based estimations to reconstruct the spatial continuous cover of three land cover types. Using the open-land component and the archaeological data, the extent of land-use is reconstructed. The model is applied on three time periods - centred around 1900 CE, 1000 and, 4000 BCE over Sweden for which both pollen-based estimates and archaeological data are available. To estimate the model parameters and land use, a block updated Markov chain Monte Carlo (MCMC) algorithm is applied. Using the MCMC posterior samples uncertainties in land-use predictions are computed. Due to lack of good historic land use data, model results are evaluated by cross-validation. Keywords. Spatial reconstruction, Gaussian Markov random field, Fossil pollen records, Archaeological data, Human land-use, Prediction uncertainty

Public Open Access and Private Timber Harvests: Theory and Application to the Effects of Trade Liberalization in Mexico

Treesearch

Jeffrey P. Prestemon

2000-01-01

A common popular assertion is that trade liberalization encourages deforestation. But whether this is true depends on how trade policies affect the allocation of land among competing uses and how they influence illegal cutting of public forests. A model is presented that allows for forests to be either public or private, and public forests are divided into protected (...

Effects of vegetation types on soil moisture estimation from the normalized land surface temperature versus vegetation index space

NASA Astrophysics Data System (ADS)

Zhang, Dianjun; Zhou, Guoqing

2015-12-01

Soil moisture (SM) is a key variable that has been widely used in many environmental studies. Land surface temperature versus vegetation index (LST-VI) space becomes a common way to estimate SM in optical remote sensing applications. Normalized LST-VI space is established by the normalized LST and VI to obtain the comparable SM in Zhang et al. (Validation of a practical normalized soil moisture model with in situ measurements in humid and semiarid regions [J]. International Journal of Remote Sensing, DOI: 10.1080/01431161.2015.1055610). The boundary conditions in the study were set to limit the point A (the driest bare soil) and B (the wettest bare soil) for surface energy closure. However, no limitation was installed for point D (the full vegetation cover). In this paper, many vegetation types are simulated by the land surface model - Noah LSM 3.2 to analyze the effects on soil moisture estimation, such as crop, grass and mixed forest. The locations of point D are changed with vegetation types. The normalized LST of point D for forest is much lower than crop and grass. The location of point D is basically unchanged for crop and grass.

Environmental Assessment: Land Acquisition at Whiteman Air Force Base, Missouri

DTIC Science & Technology

2011-06-01

Canadian clearweed (Pilea pumila), common duckweed ( Lemna minor ), common rush (Juncus effusus), cottonwood (Populus deltoides), crabgrass...resources, hazardous materials and hazardous waste, and safety. Implementation of the Proposed Action would result in minor , short-term adverse impacts...consumption of petroleum products during fence construction. As a result of implementing the Proposed Action, minor long-term adverse impacts to land use

Cross-site comparison of land-use decision-making and its consequences across land systems with a generalized agent-based model.

PubMed

Magliocca, Nicholas R; Brown, Daniel G; Ellis, Erle C

2014-01-01

Local changes in land use result from the decisions and actions of land-users within land systems, which are structured by local and global environmental, economic, political, and cultural contexts. Such cross-scale causation presents a major challenge for developing a general understanding of how local decision-making shapes land-use changes at the global scale. This paper implements a generalized agent-based model (ABM) as a virtual laboratory to explore how global and local processes influence the land-use and livelihood decisions of local land-users, operationalized as settlement-level agents, across the landscapes of six real-world test sites. Test sites were chosen in USA, Laos, and China to capture globally-significant variation in population density, market influence, and environmental conditions, with land systems ranging from swidden to commercial agriculture. Publicly available global data were integrated into the ABM to model cross-scale effects of economic globalization on local land-use decisions. A suite of statistics was developed to assess the accuracy of model-predicted land-use outcomes relative to observed and random (i.e. null model) landscapes. At four of six sites, where environmental and demographic forces were important constraints on land-use choices, modeled land-use outcomes were more similar to those observed across sites than the null model. At the two sites in which market forces significantly influenced land-use and livelihood decisions, the model was a poorer predictor of land-use outcomes than the null model. Model successes and failures in simulating real-world land-use patterns enabled the testing of hypotheses on land-use decision-making and yielded insights on the importance of missing mechanisms. The virtual laboratory approach provides a practical framework for systematic improvement of both theory and predictive skill in land change science based on a continual process of experimentation and model enhancement.

Cross-Site Comparison of Land-Use Decision-Making and Its Consequences across Land Systems with a Generalized Agent-Based Model

PubMed Central

Magliocca, Nicholas R.; Brown, Daniel G.; Ellis, Erle C.

2014-01-01

Local changes in land use result from the decisions and actions of land-users within land systems, which are structured by local and global environmental, economic, political, and cultural contexts. Such cross-scale causation presents a major challenge for developing a general understanding of how local decision-making shapes land-use changes at the global scale. This paper implements a generalized agent-based model (ABM) as a virtual laboratory to explore how global and local processes influence the land-use and livelihood decisions of local land-users, operationalized as settlement-level agents, across the landscapes of six real-world test sites. Test sites were chosen in USA, Laos, and China to capture globally-significant variation in population density, market influence, and environmental conditions, with land systems ranging from swidden to commercial agriculture. Publicly available global data were integrated into the ABM to model cross-scale effects of economic globalization on local land-use decisions. A suite of statistics was developed to assess the accuracy of model-predicted land-use outcomes relative to observed and random (i.e. null model) landscapes. At four of six sites, where environmental and demographic forces were important constraints on land-use choices, modeled land-use outcomes were more similar to those observed across sites than the null model. At the two sites in which market forces significantly influenced land-use and livelihood decisions, the model was a poorer predictor of land-use outcomes than the null model. Model successes and failures in simulating real-world land-use patterns enabled the testing of hypotheses on land-use decision-making and yielded insights on the importance of missing mechanisms. The virtual laboratory approach provides a practical framework for systematic improvement of both theory and predictive skill in land change science based on a continual process of experimentation and model enhancement. PMID:24489696

The Use of Asymptotic Functions for Determining Empirical Values of CN Parameter in Selected Catchments of Variable Land Cover

NASA Astrophysics Data System (ADS)

Wałęga, Andrzej; Młyński, Dariusz; Wachulec, Katarzyna

2017-12-01

The aim of the study was to assess the applicability of asymptotic functions for determining the value of CN parameter as a function of precipitation depth in mountain and upland catchments. The analyses were carried out in two catchments: the Rudawa, left tributary of the Vistula, and the Kamienica, right tributary of the Dunajec. The input material included data on precipitation and flows for a multi-year period 1980-2012, obtained from IMGW PIB in Warsaw. Two models were used to determine empirical values of CNobs parameter as a function of precipitation depth: standard Hawkins model and 2-CN model allowing for a heterogeneous nature of a catchment area. The study analyses confirmed that asymptotic functions properly described P-CNobs relationship for the entire range of precipitation variability. In the case of high rainfalls, CNobs remained above or below the commonly accepted average antecedent moisture conditions AMCII. The study calculations indicated that the runoff amount calculated according to the original SCS-CN method might be underestimated, and this could adversely affect the values of design flows required for the design of hydraulic engineering projects. In catchments with heterogeneous land cover, the results of CNobs were more accurate when 2-CN model was used instead of the standard Hawkins model. 2-CN model is more precise in accounting for differences in runoff formation depending on retention capacity of the substrate. It was also demonstrated that the commonly accepted initial abstraction coefficient λ = 0.20 yielded too big initial loss of precipitation in the analyzed catchments and, therefore, the computed direct runoff was underestimated. The best results were obtained for λ = 0.05.

PSOLA: A Heuristic Land-Use Allocation Model Using Patch-Level Operations and Knowledge-Informed Rules.

PubMed

Liu, Yaolin; Peng, Jinjin; Jiao, Limin; Liu, Yanfang

2016-01-01

Optimizing land-use allocation is important to regional sustainable development, as it promotes the social equality of public services, increases the economic benefits of land-use activities, and reduces the ecological risk of land-use planning. Most land-use optimization models allocate land-use using cell-level operations that fragment land-use patches. These models do not cooperate well with land-use planning knowledge, leading to irrational land-use patterns. This study focuses on building a heuristic land-use allocation model (PSOLA) using particle swarm optimization. The model allocates land-use with patch-level operations to avoid fragmentation. The patch-level operations include a patch-edge operator, a patch-size operator, and a patch-compactness operator that constrain the size and shape of land-use patches. The model is also integrated with knowledge-informed rules to provide auxiliary knowledge of land-use planning during optimization. The knowledge-informed rules consist of suitability, accessibility, land use policy, and stakeholders' preference. To validate the PSOLA model, a case study was performed in Gaoqiao Town in Zhejiang Province, China. The results demonstrate that the PSOLA model outperforms a basic PSO (Particle Swarm Optimization) in the terms of the social, economic, ecological, and overall benefits by 3.60%, 7.10%, 1.53% and 4.06%, respectively, which confirms the effectiveness of our improvements. Furthermore, the model has an open architecture, enabling its extension as a generic tool to support decision making in land-use planning.

PSOLA: A Heuristic Land-Use Allocation Model Using Patch-Level Operations and Knowledge-Informed Rules

PubMed Central

Liu, Yaolin; Peng, Jinjin; Jiao, Limin; Liu, Yanfang

2016-01-01

Optimizing land-use allocation is important to regional sustainable development, as it promotes the social equality of public services, increases the economic benefits of land-use activities, and reduces the ecological risk of land-use planning. Most land-use optimization models allocate land-use using cell-level operations that fragment land-use patches. These models do not cooperate well with land-use planning knowledge, leading to irrational land-use patterns. This study focuses on building a heuristic land-use allocation model (PSOLA) using particle swarm optimization. The model allocates land-use with patch-level operations to avoid fragmentation. The patch-level operations include a patch-edge operator, a patch-size operator, and a patch-compactness operator that constrain the size and shape of land-use patches. The model is also integrated with knowledge-informed rules to provide auxiliary knowledge of land-use planning during optimization. The knowledge-informed rules consist of suitability, accessibility, land use policy, and stakeholders’ preference. To validate the PSOLA model, a case study was performed in Gaoqiao Town in Zhejiang Province, China. The results demonstrate that the PSOLA model outperforms a basic PSO (Particle Swarm Optimization) in the terms of the social, economic, ecological, and overall benefits by 3.60%, 7.10%, 1.53% and 4.06%, respectively, which confirms the effectiveness of our improvements. Furthermore, the model has an open architecture, enabling its extension as a generic tool to support decision making in land-use planning. PMID:27322619

Prophylactic knee bracing alters lower-limb muscle forces during a double-leg drop landing.

PubMed

Ewing, Katie A; Fernandez, Justin W; Begg, Rezaul K; Galea, Mary P; Lee, Peter V S

2016-10-03

Anterior cruciate ligament (ACL) injury can be a painful, debilitating and costly consequence of participating in sporting activities. Prophylactic knee bracing aims to reduce the number and severity of ACL injury, which commonly occurs during landing maneuvers and is more prevalent in female athletes, but a consensus on the effectiveness of prophylactic knee braces has not been established. The lower-limb muscles are believed to play an important role in stabilizing the knee joint. The purpose of this study was to investigate the changes in lower-limb muscle function with prophylactic knee bracing in male and female athletes during landing. Fifteen recreational athletes performed double-leg drop landing tasks from 0.30m and 0.60m with and without a prophylactic knee brace. Motion analysis data were used to create subject-specific musculoskeletal models in OpenSim. Static optimization was performed to calculate the lower-limb muscle forces. A linear mixed model determined that the hamstrings and vasti muscles produced significantly greater flexion and extension torques, respectively, and greater peak muscle forces with bracing. No differences in the timings of peak muscle forces were observed. These findings suggest that prophylactic knee bracing may help to provide stability to the knee joint by increasing the active stiffness of the hamstrings and vasti muscles later in the landing phase rather than by altering the timing of muscle forces. Further studies are necessary to quantify whether prophylactic knee bracing can reduce the load placed on the ACL during intense dynamic movements. Copyright © 2016 Elsevier Ltd. All rights reserved.

Land subsidence in Yunlin, Taiwan, due to Agricultural and Domestic Water Use

NASA Astrophysics Data System (ADS)

Hsu, K.; Lin, P.; Lin, Z.

2013-12-01

Subsidence in a layered aquifer is caused by groundwater excess extraction and results in complicated problems in Taiwan. Commonly, responsibility to subsidence for agricultural and domestic water users is difficulty to identify due to the lack of quantitative evidences. An integrated model was proposed to analyze subsidence problem. The flow field utilizes analytical solution for pumping in a layered system from Neuman and Witherspoon (1969) to calculate the head drawdown variation. The subsidence estimation applies Terzaghi (1943) one-dimensional consolidation theory to calculate the deformation in each layer. The proposed model was applied to estimate land subsidence and drawdown variation at the Yuanchang Township of Yunlin County in Taiwan. Groundwater data for dry-season periods were used for calibration and validation. Seasonal effect in groundwater variation was first filtered out. Dry-season pumping effect on land subsidence was analyzed. The results show that multi-layer pumping contributes more in subsidence than single-layer pumping on the response of drawdown and land subsidence in aquifer 2 with a contribution of 97% total change at Yuanchang station. Pumping in aquifer 2 contributes more significant than pumping in aquifer 3 to cause change in drawdown and land subsidence in aquifer 2 with a contribution of 70% total change at Yuanchang station. Larger area of subsidence in Yuanchang Township was attributed pumping at aquifer 2 while pumping at aquifer 3 results in significant subsidence near the well field. The single-layer user contributes most area of subsidence but the multi-layer user generates more serious subsidence.

Spatial variation in the ecological relationships among the components of Beijing's carbon metabolic system.

PubMed

Xia, Linlin; Fath, Brian D; Scharler, Ursula M; Zhang, Yan

2016-02-15

In this paper, we construct a spatially explicit model of carbon metabolism for the flows of carbon among the components of an urban area. We used the model to identify spatial heterogeneity in the ecological relationships within a carbon metabolic network. We combined land-use and cover type maps for Beijing from 1990 to 2010 with empirical coefficients and socioeconomic data to quantify the flows. We used utility analysis to determine the ecological relationships between the components of the system and analyzed their changes during urban development. We used ArcGIS to analyze their spatial variation. We found that the positive utilities in Beijing decreased over time and that negative relationships mostly outweighed positive relationships after 2000. The main ecological relationships were distributed throughout the entire urban area before 2000; subsequently, exploitation, control, and mutualism relationships became concentrated in the southeast, leaving competition relationships to dominate the northwest. Mutualism relationships were most common for natural components, but were not stable because they were easily disturbed by urban expansion. Transportation and industrial land and urban land were the most important contributors to exploitation and control relationships and may be important indicators of spatial adjustment. Increasing competition relationships unbalanced the carbon metabolism, and limitations on the area of land available for development and on the water resources led to increasingly serious competition. The results provide an objective basis for planning adjustments to Beijing's land-use patterns to improve its carbon metabolism and reduce carbon emission. Copyright © 2015 Elsevier B.V. All rights reserved.

Characterizing the relationship between Asian tiger mosquito abundance and habitat in urban New Jersey

NASA Astrophysics Data System (ADS)

Ferwerda, Carolin

2009-12-01

Since its introduction to North America in 1987, the Asian tiger mosquito (Aedes albopictus) has spread rapidly. Due to its unique ecology and preference for container breeding sites, Ae. albopictus commonly inhabits urban/suburban areas and is often in close contact with humans. An aggressive pest, this mosquito species is a vector of multiple arboviruses. In order for mosquito control efforts to remain effective, control of this important vector must be guided by spatially explicit habitat models that aid in predicting mosquito outbreaks. Using linear regression, I determined the relationship between adult Ae. albopictus abundance and climate, census, and land use factors in nine urban/suburban study sites in central New Jersey. Systematically collected adult counts (females and males) from July to October 2008, served as estimates of abundance. Fine-scale land use/land cover data were obtained from object-oriented classifications of 2007 CIR orthophotos in Definiens eCognition. Mosquito abundance data were tested for spatial autocorrelation via Moran's I, semivariograms, and hotspot analysis in order to reveal consistent patterns in abundance. Spatial pattern analysis produced little evidence of consistent spatial autocorrelation, though several sites exhibited recurring hotspots, especially in areas near residential housing and vegetation. Stepwise multiple regression was able to explain 20-25 percent of variation in Ae. albopictus abundance at the 'backyard' or cell level and 72-78 percent of variation in abundance at the 'neighborhood' or study site level. Meteorological variables (temperature on the trap date and precipitation), census variables (vacant housing units and population density), and more detailed land use/land cover classes (deciduous woody vegetation, rights-of-way and vacant lots) were frequently selected in all eight models, though many other independent variables were included in the individual models. The results of the spatial statistics suggest that clustering may occur at a broader extent, while the superior predictive ability of the site level models over the finer grain cell level models supports this conclusion. Future work should focus on validating these models with 2009 field data and testing whether finer grain weather and census data enhance the models' predictive ability. Given the major differences between individual county models, future studies should further explore variations in Ae. albopictus habitat preferences in different geographic locations.

Spatial modeling of agricultural land use change at global scale

NASA Astrophysics Data System (ADS)

Meiyappan, P.; Dalton, M.; O'Neill, B. C.; Jain, A. K.

2014-11-01

Long-term modeling of agricultural land use is central in global scale assessments of climate change, food security, biodiversity, and climate adaptation and mitigation policies. We present a global-scale dynamic land use allocation model and show that it can reproduce the broad spatial features of the past 100 years of evolution of cropland and pastureland patterns. The modeling approach integrates economic theory, observed land use history, and data on both socioeconomic and biophysical determinants of land use change, and estimates relationships using long-term historical data, thereby making it suitable for long-term projections. The underlying economic motivation is maximization of expected profits by hypothesized landowners within each grid cell. The model predicts fractional land use for cropland and pastureland within each grid cell based on socioeconomic and biophysical driving factors that change with time. The model explicitly incorporates the following key features: (1) land use competition, (2) spatial heterogeneity in the nature of driving factors across geographic regions, (3) spatial heterogeneity in the relative importance of driving factors and previous land use patterns in determining land use allocation, and (4) spatial and temporal autocorrelation in land use patterns. We show that land use allocation approaches based solely on previous land use history (but disregarding the impact of driving factors), or those accounting for both land use history and driving factors by mechanistically fitting models for the spatial processes of land use change do not reproduce well long-term historical land use patterns. With an example application to the terrestrial carbon cycle, we show that such inaccuracies in land use allocation can translate into significant implications for global environmental assessments. The modeling approach and its evaluation provide an example that can be useful to the land use, Integrated Assessment, and the Earth system modeling communities.

Modeling the effects of environmental disturbance on wildlife communities: avian responses to prescribed fire.

PubMed

Russell, Robin E; Royle, J Andrew; Saab, Victoria A; Lehmkuhl, John F; Block, William M; Sauer, John R

2009-07-01

Prescribed fire is a management tool used to reduce fuel loads on public lands in forested areas in the western United States. Identifying the impacts of prescribed fire on bird communities in ponderosa pine (Pinus ponderosa) forests is necessary for providing land management agencies with information regarding the effects of fuel reduction on sensitive, threatened, and migratory bird species. Recent developments in occupancy modeling have established a framework for quantifying the impacts of management practices on wildlife community dynamics. We describe a Bayesian hierarchical model of multi-species occupancy accounting for detection probability, and we demonstrate the model's usefulness for identifying effects of habitat disturbances on wildlife communities. Advantages to using the model include the ability to estimate the effects of environmental impacts on rare or elusive species, the intuitive nature of the modeling, the incorporation of detection probability, the estimation of parameter uncertainty, the flexibility of the model to suit a variety of experimental designs, and the composite estimate of the response that applies to the collection of observed species as opposed to merely a small subset of common species. Our modeling of the impacts of prescribed fire on avian communities in a ponderosa pine forest in Washington indicate that prescribed fire treatments result in increased occupancy rates for several bark-insectivore, cavity-nesting species including a management species of interest, Black-backed Woodpeckers (Picoides arcticus). Three aerial insectivore species, and the ground insectivore, American Robin (Turdus migratorius), also responded positively to prescribed fire, whereas three foliage insectivores and two seed specialists, Clark's Nutcracker (Nucifraga columbiana) and the Pine Siskin (Carduelis pinus), declined following treatments. Land management agencies interested in determining the effects of habitat manipulations on wildlife communities can use these methods to provide guidance for future management activities.

Synergy between land use and climate change increases future fire risk in Amazon forests

NASA Astrophysics Data System (ADS)

Le Page, Yannick; Morton, Douglas; Hartin, Corinne; Bond-Lamberty, Ben; Cardoso Pereira, José Miguel; Hurtt, George; Asrar, Ghassem

2017-12-01

Tropical forests have been a permanent feature of the Amazon basin for at least 55 million years, yet climate change and land use threaten the forest's future over the next century. Understory forest fires, which are common under the current climate in frontier forests, may accelerate Amazon forest losses from climate-driven dieback and deforestation. Far from land use frontiers, scarce fire ignitions and high moisture levels preclude significant burning, yet projected climate and land use changes may increase fire activity in these remote regions. Here, we used a fire model specifically parameterized for Amazon understory fires to examine the interactions between anthropogenic activities and climate under current and projected conditions. In a scenario of low mitigation efforts with substantial land use expansion and climate change - Representative Concentration Pathway (RCP) 8.5 - projected understory fires increase in frequency and duration, burning 4-28 times more forest in 2080-2100 than during 1990-2010. In contrast, active climate mitigation and land use contraction in RCP4.5 constrain the projected increase in fire activity to 0.9-5.4 times contemporary burned area. Importantly, if climate mitigation is not successful, land use contraction alone is very effective under low to moderate climate change, but does little to reduce fire activity under the most severe climate projections. These results underscore the potential for a fire-driven transformation of Amazon forests if recent regional policies for forest conservation are not paired with global efforts to mitigate climate change.

Long-term changes in Serengeti-Mara wildebeest and land cover: Pastoralism, population, or policies?

PubMed Central

Homewood, K.; Lambin, E. F.; Coast, E.; Kariuki, A.; Kikula, I.; Kivelia, J.; Said, M.; Serneels, S.; Thompson, M.

2001-01-01

Declines in habitat and wildlife in semiarid African savannas are widely reported and commonly attributed to agropastoral population growth, livestock impacts, and subsistence cultivation. However, extreme annual and shorter-term variability of rainfall, primary production, vegetation, and populations of grazers make directional trends and causal chains hard to establish in these ecosystems. Here two decades of changes in land cover and wildebeest in the Serengeti-Mara region of East Africa are analyzed in terms of potential drivers (rainfall, human and livestock population growth, socio-economic trends, land tenure, agricultural policies, and markets). The natural experiment research design controls for confounding variables, and our conceptual model and statistical approach integrate natural and social sciences data. The Kenyan part of the ecosystem shows rapid land-cover change and drastic decline for a wide range of wildlife species, but these changes are absent on the Tanzanian side. Temporal climate trends, human population density and growth rates, uptake of small-holder agriculture, and livestock population trends do not differ between the Kenyan and Tanzanian parts of the ecosystem and cannot account for observed changes. Differences in private versus state/communal land tenure, agricultural policy, and market conditions suggest, and spatial correlations confirm, that the major changes in land cover and dominant grazer species numbers are driven primarily by private landowners responding to market opportunities for mechanized agriculture, less by agropastoral population growth, cattle numbers, or small-holder land use. PMID:11675492

The GEWEX LandFlux project: Evaluation of model evaporation using tower-based and globally gridded forcing data

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

McCabe, M. F.; Ershadi, A.; Jimenez, C.

Determining the spatial distribution and temporal development of evaporation at regional and global scales is required to improve our understanding of the coupled water and energy cycles and to better monitor any changes in observed trends and variability of linked hydrological processes. With recent international efforts guiding the development of long-term and globally distributed flux estimates, continued product assessments are required to inform upon the selection of suitable model structures and also to establish the appropriateness of these multi-model simulations for global application. In support of the objectives of the Global Energy and Water Cycle Exchanges (GEWEX) LandFlux project, fourmore » commonly used evaporation models are evaluated against data from tower-based eddy-covariance observations, distributed across a range of biomes and climate zones. The selected schemes include the Surface Energy Balance System (SEBS) approach, the Priestley–Taylor Jet Propulsion Laboratory (PT-JPL) model, the Penman–Monteith-based Mu model (PM-Mu) and the Global Land Evaporation Amsterdam Model (GLEAM). Here we seek to examine the fidelity of global evaporation simulations by examining the multi-model response to varying sources of forcing data. To do this, we perform parallel and collocated model simulations using tower-based data together with a global-scale grid-based forcing product. Through quantifying the multi-model response to high-quality tower data, a better understanding of the subsequent model response to the coarse-scale globally gridded data that underlies the LandFlux product can be obtained, while also providing a relative evaluation and assessment of model performance. Using surface flux observations from 45 globally distributed eddy-covariance stations as independent metrics of performance, the tower-based analysis indicated that PT-JPL provided the highest overall statistical performance (0.72; 61 W m –2; 0.65), followed closely by GLEAM (0.68; 64 W m –2; 0.62), with values in parentheses representing the R 2, RMSD and Nash–Sutcliffe efficiency (NSE), respectively. PM-Mu (0.51; 78 W m –2; 0.45) tended to underestimate fluxes, while SEBS (0.72; 101 W m –2; 0.24) overestimated values relative to observations. A focused analysis across specific biome types and climate zones showed considerable variability in the performance of all models, with no single model consistently able to outperform any other. Results also indicated that the global gridded data tended to reduce the performance for all of the studied models when compared to the tower data, likely a response to scale mismatch and issues related to forcing quality. Rather than relying on any single model simulation, the spatial and temporal variability at both the tower- and grid-scale highlighted the potential benefits of developing an ensemble or blended evaporation product for global-scale LandFlux applications. Hence, challenges related to the robust assessment of the LandFlux product are also discussed.« less

The GEWEX LandFlux project: Evaluation of model evaporation using tower-based and globally gridded forcing data

DOE PAGES

McCabe, M. F.; Ershadi, A.; Jimenez, C.; ...

2016-01-26

Determining the spatial distribution and temporal development of evaporation at regional and global scales is required to improve our understanding of the coupled water and energy cycles and to better monitor any changes in observed trends and variability of linked hydrological processes. With recent international efforts guiding the development of long-term and globally distributed flux estimates, continued product assessments are required to inform upon the selection of suitable model structures and also to establish the appropriateness of these multi-model simulations for global application. In support of the objectives of the Global Energy and Water Cycle Exchanges (GEWEX) LandFlux project, fourmore » commonly used evaporation models are evaluated against data from tower-based eddy-covariance observations, distributed across a range of biomes and climate zones. The selected schemes include the Surface Energy Balance System (SEBS) approach, the Priestley–Taylor Jet Propulsion Laboratory (PT-JPL) model, the Penman–Monteith-based Mu model (PM-Mu) and the Global Land Evaporation Amsterdam Model (GLEAM). Here we seek to examine the fidelity of global evaporation simulations by examining the multi-model response to varying sources of forcing data. To do this, we perform parallel and collocated model simulations using tower-based data together with a global-scale grid-based forcing product. Through quantifying the multi-model response to high-quality tower data, a better understanding of the subsequent model response to the coarse-scale globally gridded data that underlies the LandFlux product can be obtained, while also providing a relative evaluation and assessment of model performance. Using surface flux observations from 45 globally distributed eddy-covariance stations as independent metrics of performance, the tower-based analysis indicated that PT-JPL provided the highest overall statistical performance (0.72; 61 W m –2; 0.65), followed closely by GLEAM (0.68; 64 W m –2; 0.62), with values in parentheses representing the R 2, RMSD and Nash–Sutcliffe efficiency (NSE), respectively. PM-Mu (0.51; 78 W m –2; 0.45) tended to underestimate fluxes, while SEBS (0.72; 101 W m –2; 0.24) overestimated values relative to observations. A focused analysis across specific biome types and climate zones showed considerable variability in the performance of all models, with no single model consistently able to outperform any other. Results also indicated that the global gridded data tended to reduce the performance for all of the studied models when compared to the tower data, likely a response to scale mismatch and issues related to forcing quality. Rather than relying on any single model simulation, the spatial and temporal variability at both the tower- and grid-scale highlighted the potential benefits of developing an ensemble or blended evaporation product for global-scale LandFlux applications. Hence, challenges related to the robust assessment of the LandFlux product are also discussed.« less

Applicability of land use models for the Houston area test site

NASA Technical Reports Server (NTRS)

Petersburg, R. K.; Bradford, L. H.

1973-01-01

Descriptions of land use models are presented which were considered for their applicability to the Houston Area Test Site. These models are representative both of the prevailing theories of land use dynamics and of basic approaches to simulation. The models considered are: a model of metropolis, land use simulation model, emperic land use forecasting model, a probabilistic model for residential growth, and the regional environmental management allocation process. Sources of environmental/resource information are listed.

Analysis of consistency of global net land-use change carbon emission scenario using offline vegetation model and earth system model

NASA Astrophysics Data System (ADS)

Kato, E.; Kawamiya, M.

2010-12-01

For CMIP5 experiments, emissions scenarios data sets for climate models are prepared as Representative Concentration Pathways (RCPs) by the Integrated Assessment Models (IAMs). IAMs also have depicted regional land-use scenarios based on the socioeconomic assumption of the future scenarios of RCPs. In the land-use harmonization project, gridded land-use transition data has been constructed from the regional IAMs future land-use scenarios which smoothly connects historical reconstructions of land-use based on HYDE 3 data and FAO wood harvest data. In this study, using the gridded transition land-use scenario data, global net CO2 emission from land-use change for each RCPs scenarios is evaluated with a offline version of terrestrial biogeochemical model, VISIT (Vegetation Integrative SImulation Tool), utilizing a protocol to estimate carbon emission from deforested biomass considering delayed decomposition of product pools, and regrowth absorption from the secondary lands with abandoned agricultural lands. From the model output, effect of CO2 fertilization and land-use scenario itself on the emission is assessed to see the consistency of the scenarios. In addition, to see the effect of climate change and the climate-carbon feedback on terrestrial ecosystems, net land-use change CO2 emission is also evaluated with an earth system model, MIROC-ESM incorporating a DGVM with land-use change component. In the simulations with earth system model, RCP 6.0 scenario has been evaluated by model runs with and without land-use change forcing.

Integrating global socio-economic influences into a regional land use change model for China

NASA Astrophysics Data System (ADS)

Xu, Xia; Gao, Qiong; Peng, Changhui; Cui, Xuefeng; Liu, Yinghui; Jiang, Li

2014-03-01

With rapid economic development and urbanization, land use in China has experienced huge changes in recent years; and this will probably continue in the future. Land use problems in China are urgent and need further study. Rapid land-use change and economic development make China an ideal region for integrated land use change studies, particularly the examination of multiple factors and global-regional interactions in the context of global economic integration. This paper presents an integrated modeling approach to examine the impact of global socio-economic processes on land use changes at a regional scale. We develop an integrated model system by coupling a simple global socio-economic model (GLOBFOOD) and regional spatial allocation model (CLUE). The model system is illustrated with an application to land use in China. For a given climate change, population growth, and various socio-economic situations, a global socio-economic model simulates the impact of global market and economy on land use, and quantifies changes of different land use types. The land use spatial distribution model decides the type of land use most appropriate in each spatial grid by employing a weighted suitability index, derived from expert knowledge about the ecosystem state and site conditions. A series of model simulations will be conducted and analyzed to demonstrate the ability of the integrated model to link global socioeconomic factors with regional land use changes in China. The results allow an exploration of the future dynamics of land use and landscapes in China.

An interval chance-constrained fuzzy modeling approach for supporting land-use planning and eco-environment planning at a watershed level.

PubMed

Ou, Guoliang; Tan, Shukui; Zhou, Min; Lu, Shasha; Tao, Yinghui; Zhang, Zuo; Zhang, Lu; Yan, Danping; Guan, Xingliang; Wu, Gang

2017-12-15

An interval chance-constrained fuzzy land-use allocation (ICCF-LUA) model is proposed in this study to support solving land resource management problem associated with various environmental and ecological constraints at a watershed level. The ICCF-LUA model is based on the ICCF (interval chance-constrained fuzzy) model which is coupled with interval mathematical model, chance-constrained programming model and fuzzy linear programming model and can be used to deal with uncertainties expressed as intervals, probabilities and fuzzy sets. Therefore, the ICCF-LUA model can reflect the tradeoff between decision makers and land stakeholders, the tradeoff between the economical benefits and eco-environmental demands. The ICCF-LUA model has been applied to the land-use allocation of Wujiang watershed, Guizhou Province, China. The results indicate that under highly land suitable conditions, optimized area of cultivated land, forest land, grass land, construction land, water land, unused land and landfill in Wujiang watershed will be [5015, 5648] hm 2 , [7841, 7965] hm 2 , [1980, 2056] hm 2 , [914, 1423] hm 2 , [70, 90] hm 2 , [50, 70] hm 2 and [3.2, 4.3] hm 2 , the corresponding system economic benefit will be between 6831 and 7219 billion yuan. Consequently, the ICCF-LUA model can effectively support optimized land-use allocation problem in various complicated conditions which include uncertainties, risks, economic objective and eco-environmental constraints. Copyright © 2017 Elsevier Ltd. All rights reserved.

Research Progress of Building Materials Used in Construction Land

NASA Astrophysics Data System (ADS)

Niu, Yan

2018-01-01

Construction land preparation is an important aspect of land remediation project. The research of materials in the process of land improvement is the foundation and the core. Therefore, it is necessary to study the materials that may be involved in the process of building land preparation. In this paper, the research on the construction materials such as recycled concrete, geosynthetics, soil stabilizers, soil improvers, building insulation materials and inorganic fibrous insulation materials, which are commonly used in construction sites, is reviewed and discussed in this paper. Land remediation project involved in the construction of land materials to provide reference.

The Puerto Rico Gap Analysis Project Volume 1: land cover, vertebrate species distributions, and land stewardship

Treesearch

W. A. Gould; C. Alarcon; B. Fevold; M.E. Jimenez; S. Martinuzzi; G. Potts; M. Quinones; M. Solórzano; E. Ventosa

2008-01-01

Puerto Rico faces a number of problems common to much of the world. Population is increasing while land area is not, and there are reassessments of land use policy and practice to accommodate growing populations, shifting economies, and changing public value systems. Puerto Rico shares similarities with the Eastern United States with its history of agricultural...

The roles of nearest neighbor methods in imputing missing data in forest inventory and monitoring databases

Treesearch

Bianca N. I. Eskelson; Hailemariam Temesgen; Valerie Lemay; Tara M. Barrett; Nicholas L. Crookston; Andrew T. Hudak

2009-01-01

Almost universally, forest inventory and monitoring databases are incomplete, ranging from missing data for only a few records and a few variables, common for small land areas, to missing data for many observations and many variables, common for large land areas. For a wide variety of applications, nearest neighbor (NN) imputation methods have been developed to fill in...

Effects of climate change and seed dispersal on airborne ragweed pollen loads in Europe

NASA Astrophysics Data System (ADS)

Hamaoui-Laguel, Lynda; Vautard, Robert; Liu, Li; Solmon, Fabien; Viovy, Nicolas; Khvorostyanov, Dmitry; Essl, Franz; Chuine, Isabelle; Colette, Augustin; Semenov, Mikhail A.; Schaffhauser, Alice; Storkey, Jonathan; Thibaudon, Michel; Epstein, Michelle M.

2015-08-01

Common ragweed (Ambrosia artemisiifolia) is an invasive alien species in Europe producing pollen that causes severe allergic disease in susceptible individuals. Ragweed plants could further invade European land with climate and land-use changes. However, airborne pollen evolution depends not only on plant invasion, but also on pollen production, release and atmospheric dispersion changes. To predict the effect of climate and land-use changes on airborne pollen concentrations, we used two comprehensive modelling frameworks accounting for all these factors under high-end and moderate climate and land-use change scenarios. We estimate that by 2050 airborne ragweed pollen concentrations will be about 4 times higher than they are now, with a range of uncertainty from 2 to 12 largely depending on the seed dispersal rate assumptions. About a third of the airborne pollen increase is due to on-going seed dispersal, irrespective of climate change. The remaining two-thirds are related to climate and land-use changes that will extend ragweed habitat suitability in northern and eastern Europe and increase pollen production in established ragweed areas owing to increasing CO2. Therefore, climate change and ragweed seed dispersal in current and future suitable areas will increase airborne pollen concentrations, which may consequently heighten the incidence and prevalence of ragweed allergy.

Coupled hydrologic and land use change models for decision making on land and water resources in the Upper Blue Nile basin

NASA Astrophysics Data System (ADS)

Yalew, Seleshi; van der Zaag, Pieter; Mul, Marloes; Uhlenbrook, Stefan; Teferi, Ermias; van Griensven, Ann; van der Kwast, Johannes

2013-04-01

Hydrology of a basin, alongside climate change, is well documented to impact and to be impacted by land use/land cover change processes. The need to understand the impacts of hydrology on land use change and vice- versa cannot be overstated especially in basins such as the Upper Blue Nile in Ethiopia, where the vast majority of farmers depend on rain-fed agriculture. A slight fluctuation in rainy seasons or an increase or decrease in magnitude of precipitation can easily trigger drought or flooding. On the other hand, ever growing population and emerging economic development, among others, is likely to continually alter land use/land cover change, thereby affecting hydrological processes. With the intention of identifying and analyzing interactions and future scenarios of the hydrology and land use/land cover, we carried out a case study on a meso-scale catchment, in the Upper Blue Nile basin. A land use model using SITE (SImulation of Terrestrial Environments) was built for analyzing land use trends from aerial land cover photographs of 1957 and simulate until 2009 based on socio-economic as well as biophysical factors. Major land use drivers in the catchment were identified and used as input to the land use model. Separate land use maps were produced using Landsat images of 1972, 1986, 1994 and 2009 for historical calibration of the land use model. By the same token, a hydrological model for the same catchment was built using the SWAT (Soil and Water Assessment Tool) model. After calibration of the two independent models, they were loosely coupled for analyzing the changes in either of the models and impacts on the other. Among other details, the coupled model performed better in identifying limiting factors from both the hydrology as well as from the land use perspectives. For instance, the simulation of the uncoupled land use model alone (without inputs from SWAT on the water budget of each land use parcel) continually considered a land use type such as a wet land/marsh land, simply as a wetland until the simulation period finishes. The wetland or the marsh land, which is not crop friendly in the location, does not get allocated to any other land use such as for certain crop types or settlement, because the land use model cannot tell how much water is added to or drained from each parcel every season. However, the simulation feedback from the coupled hydrological model shows that certain wetland/marsh land parcels, in fact, hold less and less water or even dry up during the simulation period, thereby putting themselves as a good candidate to be picked by the land use model in a next time step and to be allocated to other land use types. The same way, a measure in the land use aspect, which considers socio-economic as well as biophysical driving forces of in the catchment, shows changes in runoff and sedimentation levels in SWAT model outputs. The results of a future scenario considering the continuing population growth projects that about 35% of the wetland dries up and gets converted to cultivation by 2020. This study emphasizes the importance of identifying possible impacts of the future hydrology on other components of the socio-environmental systems and contrariwise during environmental decision making, especially in areas where a relatively small change may have large impacts (such flood and/or drought prone basins as the Nile). The study also demonstrates a sound methodology for assessing the impact of land use change on hydrology and vice-versa by dynamically exchanging data through feedback mechanisms (coupling socio-environmental and hydrological models) which lead to a better understanding of socio-environmental problems. Keywords: Coupling, socio-environment, Nile, land use models, hydrological models

NCAR global model topography generation software for unstructured grids

NASA Astrophysics Data System (ADS)

Lauritzen, P. H.; Bacmeister, J. T.; Callaghan, P. F.; Taylor, M. A.

2015-06-01

It is the purpose of this paper to document the NCAR global model topography generation software for unstructured grids. Given a model grid, the software computes the fraction of the grid box covered by land, the gridbox mean elevation, and associated sub-grid scale variances commonly used for gravity wave and turbulent mountain stress parameterizations. The software supports regular latitude-longitude grids as well as unstructured grids; e.g. icosahedral, Voronoi, cubed-sphere and variable resolution grids. As an example application and in the spirit of documenting model development, exploratory simulations illustrating the impacts of topographic smoothing with the NCAR-DOE CESM (Community Earth System Model) CAM5.2-SE (Community Atmosphere Model version 5.2 - Spectral Elements dynamical core) are shown.

Water Accounting Plus (WA+) - a water accounting procedure for complex river basins based on satellite measurements

NASA Astrophysics Data System (ADS)

Karimi, P.; Bastiaanssen, W. G. M.; Molden, D.

2012-11-01

Coping with the issue of water scarcity and growing competition for water among different sectors requires proper water management strategies and decision processes. A pre-requisite is a clear understanding of the basin hydrological processes, manageable and unmanageable water flows, the interaction with land use and opportunities to mitigate the negative effects and increase the benefits of water depletion on society. Currently, water professionals do not have a common framework that links hydrological flows to user groups of water and their benefits. The absence of a standard hydrological and water management summary is causing confusion and wrong decisions. The non-availability of water flow data is one of the underpinning reasons for not having operational water accounting systems for river basins in place. In this paper we introduce Water Accounting Plus (WA+), which is a new framework designed to provide explicit spatial information on water depletion and net withdrawal processes in complex river basins. The influence of land use on the water cycle is described explicitly by defining land use groups with common characteristics. Analogous to financial accounting, WA+ presents four sheets including (i) a resource base sheet, (ii) a consumption sheet, (iii) a productivity sheet, and (iv) a withdrawal sheet. Every sheet encompasses a set of indicators that summarize the overall water resources situation. The impact of external (e.g. climate change) and internal influences (e.g. infrastructure building) can be estimated by studying the changes in these WA+ indicators. Satellite measurements can be used for 3 out of the 4 sheets, but is not a precondition for implementing WA+ framework. Data from hydrological models and water allocation models can also be used as inputs to WA+.

Higher landing accuracy in expert pilots is associated with lower activity in the caudate nucleus.

PubMed

Adamson, Maheen M; Taylor, Joy L; Heraldez, Daniel; Khorasani, Allen; Noda, Art; Hernandez, Beatriz; Yesavage, Jerome A

2014-01-01

The most common lethal accidents in General Aviation are caused by improperly executed landing approaches in which a pilot descends below the minimum safe altitude without proper visual references. To understand how expertise might reduce such erroneous decision-making, we examined relevant neural processes in pilots performing a simulated landing approach inside a functional MRI scanner. Pilots (aged 20-66) were asked to "fly" a series of simulated "cockpit view" instrument landing scenarios in an MRI scanner. The scenarios were either high risk (heavy fog-legally unsafe to land) or low risk (medium fog-legally safe to land). Pilots with one of two levels of expertise participated: Moderate Expertise (Instrument Flight Rules pilots, n = 8) or High Expertise (Certified Instrument Flight Instructors or Air-Transport Pilots, n = 12). High Expertise pilots were more accurate than Moderate Expertise pilots in making a "land" versus "do not land" decision (CFII: d' = 3.62 ± 2.52; IFR: d' = 0.98 ± 1.04; p<.01). Brain activity in bilateral caudate nucleus was examined for main effects of expertise during a "land" versus "do not land" decision with the no-decision control condition modeled as baseline. In making landing decisions, High Expertise pilots showed lower activation in the bilateral caudate nucleus (0.97 ± 0.80) compared to Moderate Expertise pilots (1.91 ± 1.16) (p<.05). These findings provide evidence for increased "neural efficiency" in High Expertise pilots relative to Moderate Expertise pilots. During an instrument approach the pilot is engaged in detailed examination of flight instruments while monitoring certain visual references for making landing decisions. The caudate nucleus regulates saccade eye control of gaze, the brain area where the "expertise" effect was observed. These data provide evidence that performing "real world" aviation tasks in an fMRI provide objective data regarding the relative expertise of pilots and brain regions involved in it.

Land-based approach to evaluate sustainable land management and adaptive capacity of ecosystems/lands

NASA Astrophysics Data System (ADS)

Kust, German; Andreeva, Olga

2015-04-01

A number of new concepts and paradigms appeared during last decades, such as sustainable land management (SLM), climate change (CC) adaptation, environmental services, ecosystem health, and others. All of these initiatives still not having the common scientific platform although some agreements in terminology were reached, schemes of links and feedback loops created, and some models developed. Nevertheless, in spite of all these scientific achievements, the land related issues are still not in the focus of CC adaptation and mitigation. The last did not grow much beyond the "greenhouse gases" (GHG) concept, which makes land degradation as the "forgotten side of climate change" The possible decision to integrate concepts of climate and desertification/land degradation could be consideration of the "GHG" approach providing global solution, and "land" approach providing local solution covering other "locally manifesting" issues of global importance (biodiversity conservation, food security, disasters and risks, etc.) to serve as a central concept among those. SLM concept is a land-based approach, which includes the concepts of both ecosystem-based approach (EbA) and community-based approach (CbA). SLM can serve as in integral CC adaptation strategy, being based on the statement "the more healthy and resilient the system is, the less vulnerable and more adaptive it will be to any external changes and forces, including climate" The biggest scientific issue is the methods to evaluate the SLM and results of the SLM investments. We suggest using the approach based on the understanding of the balance or equilibrium of the land and nature components as the major sign of the sustainable system. Prom this point of view it is easier to understand the state of the ecosystem stress, size of the "health", range of adaptive capacity, drivers of degradation and SLM nature, as well as the extended land use, and the concept of environmental land management as the improved SLM approach. A number of case studies justify the schemes developed to explain this approach.

Conflicts, security and marginalisation: institutional change of the pastoral commons in a 'glocal' world.

PubMed

Haller, T; Van Dijk, H; Bollig, M; Greiner, C; Schareika, N; Gabbert, C

2016-11-01

This paper argues that pastoral commons are under increasing pressure not just from overuse by pastoralists themselves, but from land management policies. Since colonial times, these have been based on a persistent misconception of the nature of pastoral economies and combined with increasing land alienation and fragmentation through government policies and covert privatisation of pastures. The paper focuses especially on pastoral populations in African drylands and is based on long-term research by independent researchers summarising some of their experiences in western, eastern and southern Africa. Most of them are organised in the African Drylands Dialogue, trying to shed some light on the developments in these areas. Before discussing the actual situation of African pastoralists, the authors focus on basic institutional features of the political and economic management of common grazing lands. This is followed by an overview of land alienation processes in colonial times, which serves as a basis for understanding the current land alienation constellations. The paper then moves on to explain how and why pastoralists are framed by the national discourses as the 'other' and the 'troublemaker', even being labelled as terrorists in nation state contexts. This goes hand in hand with a new wave of land alienation in the form of large-scale land acquisitions or 'land grabbing' (including water grabbing and 'green grabbing' processes). The paper then outlines different coping and adaptation strategies adopted by pastoral groups in a context in which a range of different global and local political, economic and ecological situations interrelate ('glocal'). Finally, the paper discusses the way in which pastoralism could be reframed in a participatory way in the future.

Bayesian Geostatistical Analysis and Ecoclimatic Determinants of Corynebacterium pseudotuberculosis Infection among Horses

PubMed Central

Boysen, Courtney; Davis, Elizabeth G.; Beard, Laurie A.; Lubbers, Brian V.; Raghavan, Ram K.

2015-01-01

Kansas witnessed an unprecedented outbreak in Corynebacterium pseudotuberculosis infection among horses, a disease commonly referred to as pigeon fever during fall 2012. Bayesian geostatistical models were developed to identify key environmental and climatic risk factors associated with C. pseudotuberculosis infection in horses. Positive infection status among horses (cases) was determined by positive test results for characteristic abscess formation, positive bacterial culture on purulent material obtained from a lanced abscess (n = 82), or positive serologic evidence of exposure to organism (≥1:512)(n = 11). Horses negative for these tests (n = 172)(controls) were considered free of infection. Information pertaining to horse demographics and stabled location were obtained through review of medical records and/or contact with horse owners via telephone. Covariate information for environmental and climatic determinants were obtained from USDA (soil attributes), USGS (land use/land cover), and NASA MODIS and NASA Prediction of Worldwide Renewable Resources (climate). Candidate covariates were screened using univariate regression models followed by Bayesian geostatistical models with and without covariates. The best performing model indicated a protective effect for higher soil moisture content (OR = 0.53, 95% CrI = 0.25, 0.71), and detrimental effects for higher land surface temperature (≥35°C) (OR = 2.81, 95% CrI = 2.21, 3.85) and habitat fragmentation (OR = 1.31, 95% CrI = 1.27, 2.22) for C. pseudotuberculosis infection status in horses, while age, gender and breed had no effect. Preventative and ecoclimatic significance of these findings are discussed. PMID:26473728

Bayesian Geostatistical Analysis and Ecoclimatic Determinants of Corynebacterium pseudotuberculosis Infection among Horses.

PubMed

Boysen, Courtney; Davis, Elizabeth G; Beard, Laurie A; Lubbers, Brian V; Raghavan, Ram K

2015-01-01

Kansas witnessed an unprecedented outbreak in Corynebacterium pseudotuberculosis infection among horses, a disease commonly referred to as pigeon fever during fall 2012. Bayesian geostatistical models were developed to identify key environmental and climatic risk factors associated with C. pseudotuberculosis infection in horses. Positive infection status among horses (cases) was determined by positive test results for characteristic abscess formation, positive bacterial culture on purulent material obtained from a lanced abscess (n = 82), or positive serologic evidence of exposure to organism (≥ 1:512)(n = 11). Horses negative for these tests (n = 172)(controls) were considered free of infection. Information pertaining to horse demographics and stabled location were obtained through review of medical records and/or contact with horse owners via telephone. Covariate information for environmental and climatic determinants were obtained from USDA (soil attributes), USGS (land use/land cover), and NASA MODIS and NASA Prediction of Worldwide Renewable Resources (climate). Candidate covariates were screened using univariate regression models followed by Bayesian geostatistical models with and without covariates. The best performing model indicated a protective effect for higher soil moisture content (OR = 0.53, 95% CrI = 0.25, 0.71), and detrimental effects for higher land surface temperature (≥ 35°C) (OR = 2.81, 95% CrI = 2.21, 3.85) and habitat fragmentation (OR = 1.31, 95% CrI = 1.27, 2.22) for C. pseudotuberculosis infection status in horses, while age, gender and breed had no effect. Preventative and ecoclimatic significance of these findings are discussed.

A Realization of Bias Correction Method in the GMAO Coupled System

NASA Technical Reports Server (NTRS)

Chang, Yehui; Koster, Randal; Wang, Hailan; Schubert, Siegfried; Suarez, Max

2018-01-01

Over the past several decades, a tremendous effort has been made to improve model performance in the simulation of the climate system. The cold or warm sea surface temperature (SST) bias in the tropics is still a problem common to most coupled ocean atmosphere general circulation models (CGCMs). The precipitation biases in CGCMs are also accompanied by SST and surface wind biases. The deficiencies and biases over the equatorial oceans through their influence on the Walker circulation likely contribute the precipitation biases over land surfaces. In this study, we introduce an approach in the CGCM modeling to correct model biases. This approach utilizes the history of the model's short-term forecasting errors and their seasonal dependence to modify model's tendency term and to minimize its climate drift. The study shows that such an approach removes most of model climate biases. A number of other aspects of the model simulation (e.g. extratropical transient activities) are also improved considerably due to the imposed pre-processed initial 3-hour model drift corrections. Because many regional biases in the GEOS-5 CGCM are common amongst other current models, our approaches and findings are applicable to these other models as well.

Assessment of model estimates of land-atmosphere CO2 exchange across northern Eurasia

USGS Publications Warehouse

Rawlins, M.A.; McGuire, A.D.; Kimball, J.S.; Dass, P.; Lawrence, D.; Burke, E.; Chen, X.; Delire, C.; Koven, C.; MacDougall, A.; Peng, S.; Rinke, A.; Saito, K.; Zhang, W.; Alkama, R.; Bohn, T. J.; Ciais, P.; Decharme, B.; Gouttevin, I.; Hajima, T.; Ji, D.; Krinner, G.; Lettenmaier, D.P.; Miller, P.; Moore, J.C.; Smith, B.; Sueyoshi, T.

2015-01-01

A warming climate is altering land-atmosphere exchanges of carbon, with a potential for increased vegetation productivity as well as the mobilization of permafrost soil carbon stores. Here we investigate land-atmosphere carbon dioxide (CO2) cycling through analysis of net ecosystem productivity (NEP) and its component fluxes of gross primary productivity (GPP) and ecosystem respiration (ER) and soil carbon residence time, simulated by a set of land surface models (LSMs) over a region spanning the drainage basin of Northern Eurasia. The retrospective simulations cover the period 1960–2009 at 0.5° resolution, which is a scale common among many global carbon and climate model simulations. Model performance benchmarks were drawn from comparisons against both observed CO2 fluxes derived from site-based eddy covariance measurements as well as regional-scale GPP estimates based on satellite remote-sensing data. The site-based comparisons depict a tendency for overestimates in GPP and ER for several of the models, particularly at the two sites to the south. For several models the spatial pattern in GPP explains less than half the variance in the MODIS MOD17 GPP product. Across the models NEP increases by as little as 0.01 to as much as 0.79 g C m−2 yr−2, equivalent to 3 to 340 % of the respective model means, over the analysis period. For the multimodel average the increase is 135 % of the mean from the first to last 10 years of record (1960–1969 vs. 2000–2009), with a weakening CO2 sink over the latter decades. Vegetation net primary productivity increased by 8 to 30 % from the first to last 10 years, contributing to soil carbon storage gains. The range in regional mean NEP among the group is twice the multimodel mean, indicative of the uncertainty in CO2 sink strength. The models simulate that inputs to the soil carbon pool exceeded losses, resulting in a net soil carbon gain amid a decrease in residence time. Our analysis points to improvements in model elements controlling vegetation productivity and soil respiration as being needed for reducing uncertainty in land-atmosphere CO2 exchange. These advances will require collection of new field data on vegetation and soil dynamics, the development of benchmarking data sets from measurements and remote-sensing observations, and investments in future model development and intercomparison studies.

Assessment of model estimates of land-atmosphere CO 2 exchange across Northern Eurasia

DOE PAGES

Rawlins, M. A.; McGuire, A. D.; Kimball, J. S.; ...

2015-07-28

A warming climate is altering land-atmosphere exchanges of carbon, with a potential for increased vegetation productivity as well as the mobilization of permafrost soil carbon stores. Here we investigate land-atmosphere carbon dioxide (CO 2) cycling through analysis of net ecosystem productivity (NEP) and its component fluxes of gross primary productivity (GPP) and ecosystem respiration (ER) and soil carbon residence time, simulated by a set of land surface models (LSMs) over a region spanning the drainage basin of Northern Eurasia. The retrospective simulations cover the period 1960–2009 at 0.5° resolution, which is a scale common among many global carbon and climatemore » model simulations. Model performance benchmarks were drawn from comparisons against both observed CO 2 fluxes derived from site-based eddy covariance measurements as well as regional-scale GPP estimates based on satellite remote-sensing data. The site-based comparisons depict a tendency for overestimates in GPP and ER for several of the models, particularly at the two sites to the south. For several models the spatial pattern in GPP explains less than half the variance in the MODIS MOD17 GPP product. Across the models NEP increases by as little as 0.01 to as much as 0.79 g C m⁻² yr⁻², equivalent to 3 to 340 % of the respective model means, over the analysis period. For the multimodel average the increase is 135 % of the mean from the first to last 10 years of record (1960–1969 vs. 2000–2009), with a weakening CO 2 sink over the latter decades. Vegetation net primary productivity increased by 8 to 30 % from the first to last 10 years, contributing to soil carbon storage gains. The range in regional mean NEP among the group is twice the multimodel mean, indicative of the uncertainty in CO 2 sink strength. The models simulate that inputs to the soil carbon pool exceeded losses, resulting in a net soil carbon gain amid a decrease in residence time. Our analysis points to improvements in model elements controlling vegetation productivity and soil respiration as being needed for reducing uncertainty in land-atmosphere CO 2 exchange. These advances will require collection of new field data on vegetation and soil dynamics, the development of benchmarking data sets from measurements and remote-sensing observations, and investments in future model development and intercomparison studies.« less

Mapping raised bogs with an iterative one-class classification approach

NASA Astrophysics Data System (ADS)

Mack, Benjamin; Roscher, Ribana; Stenzel, Stefanie; Feilhauer, Hannes; Schmidtlein, Sebastian; Waske, Björn

2016-10-01

Land use and land cover maps are one of the most commonly used remote sensing products. In many applications the user only requires a map of one particular class of interest, e.g. a specific vegetation type or an invasive species. One-class classifiers are appealing alternatives to common supervised classifiers because they can be trained with labeled training data of the class of interest only. However, training an accurate one-class classification (OCC) model is challenging, particularly when facing a large image, a small class and few training samples. To tackle these problems we propose an iterative OCC approach. The presented approach uses a biased Support Vector Machine as core classifier. In an iterative pre-classification step a large part of the pixels not belonging to the class of interest is classified. The remaining data is classified by a final classifier with a novel model and threshold selection approach. The specific objective of our study is the classification of raised bogs in a study site in southeast Germany, using multi-seasonal RapidEye data and a small number of training sample. Results demonstrate that the iterative OCC outperforms other state of the art one-class classifiers and approaches for model selection. The study highlights the potential of the proposed approach for an efficient and improved mapping of small classes such as raised bogs. Overall the proposed approach constitutes a feasible approach and useful modification of a regular one-class classifier.

Joint DEnKF-albedo assimilation scheme that considers the common land model subgrid heterogeneity and a snow density-based observation operator for improving snow depth simulations

NASA Astrophysics Data System (ADS)

Xu, Jianhui; Zhang, Feifei; Zhao, Yi; Shu, Hong; Zhong, Kaiwen

2016-07-01

For the large-area snow depth (SD) data sets with high spatial resolution in the Altay region of Northern Xinjiang, China, we present a deterministic ensemble Kalman filter (DEnKF)-albedo assimilation scheme that considers the common land model (CoLM) subgrid heterogeneity. In the albedo assimilation of DEnKF-albedo, the assimilated albedos over each subgrid tile are estimated with the MCD43C1 bidirectional reflectance distribution function (BRDF) parameters product and CoLM calculated solar zenith angle. The BRDF parameters are hypothesized to be consistent over all subgrid tiles within a specified grid. In the SCF assimilation of DEnKF-albedo, a DEnKF combining a snow density-based observation operator considers the effects of the CoLM subgrid heterogeneity and is employed to assimilate MODIS SCF to update SD states over all subgrid tiles. The MODIS SCF over a grid is compared with the area-weighted sum of model predicted SCF over all the subgrid tiles within the grid. The results are validated with in situ SD measurements and AMSR-E product. Compared with the simulations, the DEnKF-albedo scheme can reduce errors of SD simulations and accurately simulate the seasonal variability of SD. Furthermore, it can improve simulations of SD spatiotemporal distribution in the Altay region, which is more accurate and shows more detail than the AMSR-E product.

Design and landing dynamic analysis of reusable landing leg for a near-space manned capsule

NASA Astrophysics Data System (ADS)

Yue, Shuai; Nie, Hong; Zhang, Ming; Wei, Xiaohui; Gan, Shengyong

2018-06-01

To improve the landing performance of a near-space manned capsule under various landing conditions, a novel landing system is designed that employs double chamber and single chamber dampers in the primary and auxiliary struts, respectively. A dynamic model of the landing system is established, and the damper parameters are determined by employing the design method. A single-leg drop test with different initial pitch angles is then conducted to compare and validate the simulation model. Based on the validated simulation model, seven critical landing conditions regarding nine crucial landing responses are found by combining the radial basis function (RBF) surrogate model and adaptive simulated annealing (ASA) optimization method. Subsequently, the adaptability of the landing system under critical landing conditions is analyzed. The results show that the simulation effectively results match the test results, which validates the accuracy of the dynamic model. In addition, all of the crucial responses under their corresponding critical landing conditions satisfy the design specifications, demonstrating the feasibility of the landing system.

Evaluation of snow modeling with Noah and Noah-MP land surface models in NCEP GFS/CFS system

NASA Astrophysics Data System (ADS)

Dong, J.; Ek, M. B.; Wei, H.; Meng, J.

2017-12-01

Land surface serves as lower boundary forcing in global forecast system (GFS) and climate forecast system (CFS), simulating interactions between land and the atmosphere. Understanding the underlying land model physics is a key to improving weather and seasonal prediction skills. With the upgrades in land model physics (e.g., release of newer versions of a land model), different land initializations, changes in parameterization schemes used in the land model (e.g., land physical parametrization options), and how the land impact is handled (e.g., physics ensemble approach), it always prompts the necessity that climate prediction experiments need to be re-conducted to examine its impact. The current NASA LIS (version 7) integrates NOAA operational land surface and hydrological models (NCEP's Noah, versions from 2.7.1 to 3.6 and the future Noah-MP), high-resolution satellite and observational data, and land DA tools. The newer versions of the Noah LSM used in operational models have a variety of enhancements compared to older versions, where the Noah-MP allows for different physics parameterization options and the choice could have large impact on physical processes underlying seasonal predictions. These impacts need to be reexamined before implemented into NCEP operational systems. A set of offline numerical experiments driven by the GFS forecast forcing have been conducted to evaluate the impact of snow modeling with daily Global Historical Climatology Network (GHCN).

Utilizing Model Eliciting Activities (MEA's) to engage middle school teachers and students in storm water management practices to mitigate human impacts of land development

NASA Astrophysics Data System (ADS)

Tazaz, A.; Wilson, R. M.; Schoen, R.; Blumsack, S.; King, L.; Dyehouse, M.

2013-12-01

'The Integrating STEM Project' engaged 6-8 grade teachers through activities incorporating mathematics, science and technology incorporating both Next Generation Science Standards (NGSS) and Common Core State Standards-Mathematics (CCSS-Math). A group of researchers from Oceanography, Mathematics, and Education set out to provide middle school teachers with a 2 year intensive STEM integration professional development with a focus on environmental topics and to monitor the achievement outcomes in their students. Over the course of 2 years the researchers created challenging professional development sessions to expand teacher knowledge and teachers were tasked to transform the information gained during the professional development sessions for classroom use. One lesson resource kit presented to the teachers, which was directly applicable to the classroom, included Model Eliciting Activities (MEA's) to explore the positive and negative effects land development has on climate and the environment, and how land development impacts storm water management. MEA's were developed to encourage students to create models to solve complex problems and to allow teachers to investigate students thinking. MEA's are a great curriculum technique used in engineering fields to help engage students by providing hands on activities using real world data and problems. We wish to present the Storm Water Management Resource toolkit including the MEA and present the outcomes observed from student engagement in this activity.

SCIMAP: Modelling Diffuse Pollution in Large River Basins

NASA Astrophysics Data System (ADS)

Milledge, D.; Heathwaite, L.; Lane, S. N.; Reaney, S. M.

2009-12-01

Polluted rivers are a problem for the plants and animals that require clean water to survive. Watershed scale processes can influence instream aquatic ecosystems by delivering fine sediment, solutes and organic matter from diffuse sources. To improve our rivers we need to identify the pollution sources. Models can help us to do this but these rarely address the extent to which risky land uses are hydrologically-connected, and hence able to deliver, to the drainage network. Those that do tend to apply a full hydrological scheme, which is unfeasible for large watersheds. Here we develop a risk-based modelling framework, SCIMAP, for diffuse pollution from agriculture (Nitrate, Phosphate and Fine Sediment). In each case the basis of the analysis is the joint consideration of the probability of a unit of land (25 m2 cell) producing a particular environmental risk and then of that risk reaching the river. The components share a common treatment of hydrological connectivity but differ in their treatment of each pollution type. We test and apply SCIMAP using spatially-distributed instream water quality data for some of the UK’s largest catchments to infer the processes and the associated process parameters that matter in defining their concentrations. We use these to identify a series of risky field locations, where this land use is readily connected to the river system by overland flow.

Adaptation Measures Evaliation on Agriculture Under Future Climate and Land Use Scenarios in Central Chile

NASA Astrophysics Data System (ADS)

Henriquez Dole, L. E.; Vicuna, S.; Gironas, J. A.; Meza, F. J.

2016-12-01

Future climate change scenarios threaten current practices in agriculture and therefore adaptation measures have been proposed to overcome this possible situation. Regional to local ideas apply for all kind of adaptation measures and can be found among literature for Central Chile, but their quantitative efficiency is rarely evaluated. Furthermore, land uses changes are commonly neglected in such evaluations. This research use the Water Evaluation and Planning (WEAP) model and the Plant Growth Model (PGM) to simulate weekly water distribution and consumption in Chile's rural areas up to 2050. Using information directly provided by the Water User Organizations (WUO), the developed model assesses possible future impacts on 2 crops (corn and plum) under 15 climate scenarios and land use trends. Results show that WEAP-PGM tool can represent satisfactorily crop sensitiveness to historic and future circumstances. Nine scenarios satisfy average crop water demands, but all of them present a diminished yield (1%-14%) and production (8%-20%). Just six scenarios cannot meet crop water demands (40-70% of reliability) if adaptation measures are not applied. Given this need, two adaptation measures were evaluated: a) using all water rights and b) irrigation improvements. The second option showed to be the most effective measure leading to the satisfaction of crop water demands under all the scenarios, but still a diminished yield and production remained.

The Proposed U.S.-Panama Free Trade Agreement

DTIC Science & Technology

2011-04-13

growing traffic volume generated along the U.S. East Coast-to-Asia trade route (especially U.S.- China ). About one-third of all cargo passing...of the canal and its operations to Panama, the country also inherited a substantial amount of land and physical assets. The conversion of these...its prospects as a business venture, but because it is forward looking rather than relying on the “maquiladora” business model common in much of the

A commentary on domestic animals as dual-purpose models that benefit agricultural and biomedical research.

PubMed

Ireland, J J; Roberts, R M; Palmer, G H; Bauman, D E; Bazer, F W

2008-10-01

Research on domestic animals (cattle, swine, sheep, goats, poultry, horses, and aquatic species) at land grant institutions is integral to improving the global competitiveness of US animal agriculture and to resolving complex animal and human diseases. However, dwindling federal and state budgets, years of stagnant funding from USDA for the Competitive State Research, Education, and Extension Service National Research Initiative (CSREES-NRI) Competitive Grants Program, significant reductions in farm animal species and in numbers at land grant institutions, and declining enrollment for graduate studies in animal science are diminishing the resources necessary to conduct research on domestic species. Consequently, recruitment of scientists who use such models to conduct research relevant to animal agriculture and biomedicine at land grant institutions is in jeopardy. Concerned stakeholders have addressed this critical problem by conducting workshops, holding a series of meetings with USDA and National Institutes of Health (NIH) officials, and developing a white paper to propose solutions to obstacles impeding the use of domestic species as dual-purpose animal models for high-priority problems common to agriculture and biomedicine. In addition to shortfalls in research support and human resources, overwhelming use of mouse models in biomedicine, lack of advocacy from university administrators, long-standing cultural barriers between agriculture and human medicine, inadequate grantsmanship by animal scientists, and a scarcity of key reagents and resources are major roadblocks to progress. Solutions will require a large financial enhancement of USDA's Competitive Grants Program, educational programs geared toward explaining how research using agricultural animals benefits both animal agriculture and human health, and the development of a new mind-set in land grant institutions that fosters greater cooperation among basic and applied researchers. Recruitment of outstanding scientists dedicated to using domestic animal models for agricultural and biomedical research, strong incentives for scientists to take advantage of training opportunities to write NIH grants, and greater NIH and USDA cooperation to sponsor the use of agricultural animals as dual-purpose animal models that benefit agriculture and biomedicine will also be necessary. In conclusion, the broad diversity of animal models needed for agricultural and biomedical research is at risk unless research priorities at the land grant universities are critically evaluated and financial support for such research is dramatically increased.

High Resolution Land Surface Modeling with the next generation Land Data Assimilation Systems

NASA Astrophysics Data System (ADS)

Kumar, S. V.; Eylander, J.; Peters-Lidard, C.

2005-12-01

Knowledge of land surface processes is important to many real-world applications such as agricultural production, water resources management, and flood predication. The Air Force Weather Agency (AFWA) has provided the USDA and other customers global soil moisture and temperature data for the past 30 years using the agrometeorological data assimilation model (now called AGRMET), merging atmospheric data. Further, accurate initialization of land surface conditions has been shown to greatly influence and improve weather forecast model and seasonal-to-interannual climate predictions. The AFWA AGRMET model exploits real time precipitation observations and analyses, global forecast model and satellite data to generate global estimates of soil moisture, soil temperature and other land surface states at 48km spatial resolution. However, to truly address the land surface initialization and climate prediction problem, and to mitigate the errors introduced by the differences in spatial scales of models, representations of land surface conditions need to be developed at the same fine scales such as that of cloud resolving models. NASA's Goddard Space Flight Center has developed an offline land data assimilation system known as the Land Information System (LIS) capable of modeling land atmosphere interactions at spatial resolutions as fine as 1km. LIS provides a software architecture that integrates the use of the state of the art land surface models, data assimilation techniques, and high performance computing and data management tools. LIS also employs many high resolution surface parameters such as the NASA Earth Observing System (EOS)-era products. In this study we describe the development of a next generation high resolution land surface modeling and data assimilation system, combining the capabilities of LIS and AGRMET. We investigate the influence of high resolution land surface data and observations on the land surface conditions by comparing with the operational AGRMET outputs.

OPAL Land Condition Model

DTIC Science & Technology

2014-08-01

ER D C/ CE RL S R- 14 -7 Optimal Allocation of Land for Training and Non-training Uses OPAL Land Condition Model Co ns tr uc tio n En...Optimal Allocation of Land for Training and Non-training Uses ERDC/CERL SR-14-7 August 2014 OPAL Land Condition Model Daniel Koch, Scott Tweddale...programmer information supporting the Op- timal Programming of Army Lands ( OPAL ) model, which was designed for use by trainers, Integrated Training

Spatiotemporal Modelling of Dust Storm Sources Emission in West Asia

NASA Astrophysics Data System (ADS)

Khodabandehloo, E.; Alimohamdadi, A.; Sadeghi-Niaraki, A.; Darvishi Boloorani, A.; Alesheikh, A. A.

2013-09-01

Dust aerosol is the largest contributor to aerosol mass concentrations in the troposphere and has considerable effects on the air quality of spatial and temporal scales. Arid and semi-arid areas of the West Asia are one of the most important regional dust sources in the world. These phenomena directly or indirectly affecting almost all aspects life in almost 15 countries in the region. So an accurate estimate of dust emissions is very crucial for making a common understanding and knowledge of the problem. Because of the spatial and temporal limits of the ground-based observations, remote sensing methods have been found to be more efficient and useful for studying the West Asia dust source. The vegetation cover limits dust emission by decelerating the surface wind velocities and therefore reducing the momentum transport. While all models explicitly take into account the change of wind speed and soil moisture in calculating dust emissions, they commonly employ a "climatological" land cover data for identifying dust source locations and neglect the time variation of surface bareness. In order to compile the aforementioned model, land surface features such as soil moisture, texture, type, and vegetation and also wind speed as atmospheric parameter are used. Having used NDVI data show significant change in dust emission, The modeled dust emission with static source function in June 2008 is 17.02 % higher than static source function and similar result for Mach 2007 show the static source function is 8.91 % higher than static source function. we witness a significant improvement in accuracy of dust forecasts during the months of most soil vegetation changes (spring and winter) compared to outputs resulted from static model, in which NDVI data are neglected.

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.

Monitoring and Predicting Land-use Changes and the Hydrology of the Urbanized Paochiao Watershed in Taiwan Using Remote Sensing Data, Urban Growth Models and a Hydrological Model.

PubMed

Lin, Yu-Pin; Lin, Yun-Bin; Wang, Yen-Tan; Hong, Nien-Ming

2008-02-04

Monitoring and simulating urban sprawl and its effects on land-use patterns andhydrological processes in urbanized watersheds are essential in land-use and waterresourceplanning and management. This study applies a novel framework to the urbangrowth model Slope, Land use, Excluded land, Urban extent, Transportation, andHillshading (SLEUTH) and land-use change with the Conversion of Land use and itsEffects (CLUE-s) model using historical SPOT images to predict urban sprawl in thePaochiao watershed in Taipei County, Taiwan. The historical and predicted land-use datawas input into Patch Analyst to obtain landscape metrics. This data was also input to theGeneralized Watershed Loading Function (GWLF) model to analyze the effects of futureurban sprawl on the land-use patterns and watershed hydrology. The landscape metrics ofthe historical SPOT images show that land-use patterns changed between 1990-2000. TheSLEUTH model accurately simulated historical land-use patterns and urban sprawl in thePaochiao watershed, and simulated future clustered land-use patterns (2001-2025). TheCLUE-s model also simulated land-use patterns for the same period and yielded historical trends in the metrics of land-use patterns. The land-use patterns predicted by the SLEUTHand CLUE-s models show the significant impact urban sprawl will have on land-usepatterns in the Paochiao watershed. The historical and predicted land-use patterns in thewatershed tended to fragment, had regular shapes and interspersion patterns, but wererelatively less isolated in 2001-2025 and less interspersed from 2005-2025 compared withland-use pattern in 1990. During the study, the variability and magnitude of hydrologicalcomponents based on the historical and predicted land-use patterns were cumulativelyaffected by urban sprawl in the watershed; specifically, surface runoff increasedsignificantly by 22.0% and baseflow decreased by 18.0% during 1990-2025. The proposedapproach is an effective means of enhancing land-use monitoring and management ofurbanized watersheds.

Problem in application carrying capacity approach for land allocation assessment in Indonesian municipal spatial planning: A case of Kutai Kartanegara Regency

NASA Astrophysics Data System (ADS)

Wijaya, I. N. S.; Rahadi, B.; Lusiana, N.; Maulidina, I.

2017-06-01

Urbanization in many countries, such as Indonesia, is commonly appeared as a dynamic population of developed areas. It is followed with reducing rural uses of land for improving urban land uses such as housing, industry, infrastructure, etc. in response to the growth of population. One may not be sufficiently considered by the urban planners and the decision makers, urbanization also means escalation of natural resources consumption that should be supported by the natural capacity of the area. In this situation, balancing approach as carrying capacity calculation in spatial planning is needed for sustainability. Indonesian Spatial Planning Law 26/2007 has already expressed about the balance approach in the system. Moreover, it strictly regulates the assessment and the permission system in controlling land development, especially for the conversion. However, the reductions over the rural uses of land, especially agriculture, are continuously occurred. Concerning the planning approach, this paper aims to disclose common insufficiency of carrying capacity considerations in Indonesian spatial planning practice. This paper describes common calculation weaknesses in projecting area for the urban development by recalculating the actual gap between supply and demand of agriculture land areas. Here, municipal spatial plan of Kutai Kartanegara Regency is utilized as single sample case to discuss. As the result, the recalculation shows that: 1) there are serious deficit status of agriculture land areas in order to fulfil the demanded agriculture production for the existed population, 2) some calculation of agriculture production may be miss-interpreted because of insufficient explanation toward the productivity of each agriculture commodity.

A Multi-Sector Assessment of the Effects of Climate Change at the Energy-Water-Land Nexus in the US

NASA Astrophysics Data System (ADS)

McFarland, J.; Sarofim, M. C.; Martinich, J.

2017-12-01

Rising temperatures and changing precipitation patterns due to climate change are projected to alter many sectors of the US economy. A growing body of research has examined these effects in the energy, water, and agricultural sectors. Rising summer temperatures increase the demand for electricity. Changing precipitation patterns effect the availability of water for hydropower generation, thermo-electric cooling, irrigation, and municipal and industrial consumption. A combination of changes to temperature and precipitation alter crop yields and cost-effective farming practices. Although a significant body of research exists on analyzing impacts to individual sectors, fewer studies examine the effects using a common set of assumptions (e.g., climatic and socio-economic) within a coupled modeling framework. The present analysis uses a multi-sector, multi-model framework with common input assumptions to assess the projected effects of climate change on energy, water, and land-use in the United States. The analysis assesses the climate impacts for across 5 global circulation models for representative concentration pathways (RCP) of 8.5 and 4.5 W/m2. The energy sector models - Pacific Northwest National Lab's Global Change Assessment Model (GCAM) and the National Renewable Energy Laboratory's Regional Energy Deployment System (ReEDS) - show the effects of rising temperature on energy and electricity demand. Electricity supply in ReEDS is also affected by the availability of water for hydropower and thermo-electric cooling. Water availability is calculated from the GCM's precipitation using the US Basins model. The effects on agriculture are estimated using both a process-based crop model (EPIC) and an agricultural economic model (FASOM-GHG), which adjusts water supply curves based on information from US Basins. The sectoral models show higher economic costs of climate change under RCP 8.5 than RCP 4.5 averaged across the country and across GCM's.

Methods for land use impact assessment: A review

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

Perminova, Tataina, E-mail: tatiana.perminova@utt.fr; Department of Geoecology and Geochemistry, Institute of Natural Resources, National Research Tomsk Polytechnic University, 30 Lenin Avenue, 634050 Tomsk; Sirina, Natalia, E-mail: natalia.sirina@utt.fr

Many types of methods to assess land use impact have been developed. Nevertheless a systematic synthesis of all these approaches is necessary to highlight the most commonly used and most effective methods. Given the growing interest in this area of research, a review of the different methods of assessing land use impact (LUI) was performed using bibliometric analysis. One hundred eighty seven articles of agricultural and biological science, and environmental sciences were examined. According to our results, the most frequently used land use assessment methods are Life-Cycle Assessment, Material Flow Analysis/Input–Output Analysis, Environmental Impact Assessment and Ecological Footprint. Comparison ofmore » the methods allowed their specific features to be identified and to arrive at the conclusion that a combination of several methods is the best basis for a comprehensive analysis of land use impact assessment. - Highlights: • We identified the most frequently used methods in land use impact assessment. • A comparison of the methods based on several criteria was carried out. • Agricultural land use is by far the most common area of study within the methods. • Incentive driven methods, like LCA, arouse the most interest in this field.« less

Constraining the Surface Energy Balance of Snow in Complex Terrain

NASA Astrophysics Data System (ADS)

Lapo, Karl E.

Physically-based snow models form the basis of our understanding of current and future water and energy cycles, especially in mountainous terrain. These models are poorly constrained and widely diverge from each other, demonstrating a poor understanding of the surface energy balance. This research aims to improve our understanding of the surface energy balance in regions of complex terrain by improving our confidence in existing observations and improving our knowledge of remotely sensed irradiances (Chapter 1), critically analyzing the representation of boundary layer physics within land models (Chapter 2), and utilizing relatively novel observations to in the diagnoses of model performance (Chapter 3). This research has improved the understanding of the literal and metaphorical boundary between the atmosphere and land surface. Solar irradiances are difficult to observe in regions of complex terrain, as observations are subject to harsh conditions not found in other environments. Quality control methods were developed to handle these unique conditions. These quality control methods facilitated an analysis of estimated solar irradiances over mountainous environments. Errors in the estimated solar irradiance are caused by misrepresenting the effect of clouds over regions of topography and regularly exceed the range of observational uncertainty (up to 80Wm -2) in all regions examined. Uncertainty in the solar irradiance estimates were especially pronounced when averaging over high-elevation basins, with monthly differences between estimates up to 80Wm-2. These findings can inform the selection of a method for estimating the solar irradiance and suggest several avenues of future research for improving existing methods. Further research probed the relationship between the land surface and atmosphere as it pertains to the stable boundary layers that commonly form over snow-covered surfaces. Stable conditions are difficult to represent, especially for low wind speed values and coupled land-atmosphere models have difficulty representing these processes. We developed a new method analyzing turbulent fluxes at the land surface that relies on using the observed surface temperature, which we called the offline turbulence method. We used this method to test a number of stability schemes as they are implemented within land models. Stability schemes can cause small biases in the simulated sensible heat flux, but these are caused by compensating errors, as no single method was able to accurately reproduce the observed distribution of the sensible heat flux. We described how these turbulence schemes perform within different turbulence regimes, particularly noting the difficulty representing turbulence during conditions with faster wind speeds and the transition between weak and strong wind turbulence regimes. Heterogeneity in the horizontal distribution of surface temperature associated with different land surface types likely explains some of the missing physics within land models and is manifested as counter-gradient fluxes in observations. The coupling of land and atmospheric models needs further attention, as we highlight processes that are missing. Expanding on the utility of surface temperature, Ts, in model evaluations, we demonstrated the utility of using surface temperature in snow models evaluations. Ts is the diagnostic variable of the modeled surface energy balance within physically-based models and is an ideal supplement to traditional evaluation techniques. We demonstrated how modeling decisions affect Ts, specifically testing the impact of vertical layer structure, thermal conductivity, and stability corrections in addition to the effect of uncertainty in forcing data on simulated Ts. The internal modeling decisions had minimal impacts relative to uncertainty in the forcing data. Uncertainty in downwelling longwave was found to have the largest impact on simulated Ts. Using Ts, we demonstrated how various errors in the forcing data can be identified, noting that uncertainty in downwelling longwave and wind are the easiest to identify due to their effect on night time minimum Ts.

NASA GLDAS Evapotranspiration Data and Climatology

NASA Technical Reports Server (NTRS)

Rui, Hualan; Beaudoing, Hiroko Kato; Teng, William L.; Vollmer, Bruce; Rodell, Matthew

2012-01-01

Evapotranspiration (ET) is the water lost to the atmosphere by evaporation and transpiration. ET is a shared component in the energy and water budget, therefore, a critical variable for global energy and water cycle and climate change studies. However, direct ET measurements and data acquisition are difficult and expensive, especially at the global level. Therefore, modeling is one common alternative for estimating ET. With the goal to generate optimal fields of land surface states and fluxes, the Global Land Data Assimilation System (GLDAS) has been generating quality-controlled, spatially and temporally consistent, terrestrial hydrologic data, including ET and other variables that affect evaporation and transpiration, such as temperature, precipitation, humidity, wind, soil moisture, heat flux, and solar radiation. This poster presents the long-term ET climatology (mean and monthly), derived from the 61-year GLDAS-2 monthly 1.0 deg x 1.0 deg. NOAH model Experiment-1 data, and describes the basic characteristics of spatial and seasonal variations of the climatology. The time series of GLDAS-2 precipitation and radiation, and ET are also discussed to show the improvement of GLDAS-2 forcing data and model output over those from GLDAS-1.

Improving Representations of Near-Surface Permafrost and Soil Temperature Profiles in the Regional Arctic System Model (RASM)

NASA Astrophysics Data System (ADS)

Gergel, D. R.; Hamman, J.; Nijssen, B.

2017-12-01

Permafrost and seasonally frozen soils are a key characteristic of the terrestrial Arctic, and the fate of near-surface permafrost as a result of climate change is projected to have strong impacts on terrestrial biogeochemistry. The active layer thickness (ALT) is the layer of soil that freezes and thaws annually, and shifts in the depth of the ALT are projected to occur over large areas of the Arctic that are characterized by discontinuous permafrost. Faithful representation of permafrost in land models in climate models is a product of both soil dynamics and the coupling of air and soil temperatures. A common problem is a large bias in simulated ALT due to a model depth that is too shallow. Similarly, soil temperatures often show systematic biases, which lead to biases in air temperature due to poorly modeled air-soil temperature feedbacks in a coupled environment. In this study, we use the Regional Arctic System Model (RASM), a fully-coupled regional earth system model that is run at a 50-km land/atmosphere resolution over a pan-Arctic domain and uses the Variable Infiltration Capacity (VIC) model as its land model. To understand what modeling decisions are necessary to accurately represent near-surface permafrost and soil temperature profiles, we perform a large number of RASM simulations with prescribed atmospheric forcings (e.g. VIC in standalone mode in RASM) while varying the model soil depth, thickness of soil moisture layers, number of soil layers and the distribution of soil nodes. We compare modeled soil temperatures and ALT to observations from the Circumpolar Active Layer Monitoring (CALM) network. CALM observations include annual ALT observations as well as daily soil temperature measurements at three soil depths for three sites in Alaska. In the future, we will use our results to inform our modeling of permafrost dynamics in fully-coupled RASM simulations.

Moral Minimalism in American Indian Land Claims

ERIC Educational Resources Information Center

Hendrix, Burke A.

2005-01-01

This is an essay about Indian claims for the return of historically stolen lands, written from the perspective of a "Western" academic moral philosopher. I want to try to outline points of agreement and disagreement between Indian and Western moral conceptions and to seek common ground on which land claims can be more clearly evaluated…

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.

Analyzing historical land use changes using a Historical Land Use Reconstruction Model: a case study in Zhenlai County, northeastern China

PubMed Central

Yang, Yuanyuan; Zhang, Shuwen; Liu, Yansui; Xing, Xiaoshi; de Sherbinin, Alex

2017-01-01

Historical land use information is essential to understanding the impact of anthropogenic modification of land use/cover on the temporal dynamics of environmental and ecological issues. However, due to a lack of spatial explicitness, complete thematic details and the conversion types for historical land use changes, the majority of historical land use reconstructions do not sufficiently meet the requirements for an adequate model. Considering these shortcomings, we explored the possibility of constructing a spatially-explicit modeling framework (HLURM: Historical Land Use Reconstruction Model). Then a three-map comparison method was adopted to validate the projected reconstruction map. The reconstruction suggested that the HLURM model performed well in the spatial reconstruction of various land-use categories, and had a higher figure of merit (48.19%) than models used in other case studies. The largest land use/cover type in the study area was determined to be grassland, followed by arable land and wetland. Using the three-map comparison, we noticed that the major discrepancies in land use changes among the three maps were as a result of inconsistencies in the classification of land-use categories during the study period, rather than as a result of the simulation model. PMID:28134342

RUSLE2015: Modelling soil erosion at continental scale using high resolution input layers

NASA Astrophysics Data System (ADS)

Panagos, Panos; Borrelli, Pasquale; Meusburger, Katrin; Poesen, Jean; Ballabio, Cristiano; Lugato, Emanuele; Montanarella, Luca; Alewell, Christine

2016-04-01

Soil erosion by water is one of the most widespread forms of soil degradation in the Europe. On the occasion of the 2015 celebration of the International Year of Soils, the European Commission's Joint Research Centre (JRC) published the RUSLE2015, a modified modelling approach for assessing soil erosion in Europe by using the best available input data layers. The objective of the recent assessment performed with RUSLE2015 was to improve our knowledge and understanding of soil erosion by water across the European Union and to accentuate the differences and similarities between different regions and countries beyond national borders and nationally adapted models. RUSLE2015 has maximized the use of available homogeneous, updated, pan-European datasets (LUCAS topsoil, LUCAS survey, GAEC, Eurostat crops, Eurostat Management Practices, REDES, DEM 25m, CORINE, European Soil Database) and have used the best suited approach at European scale for modelling soil erosion. The collaboration of JRC with many scientists around Europe and numerous prominent European universities and institutes resulted in an improved assessment of individual risk factors (rainfall erosivity, soil erodibility, cover-management, topography and support practices) and a final harmonized European soil erosion map at high resolution. The mean soil loss rate in the European Union's erosion-prone lands (agricultural, forests and semi-natural areas) was found to be 2.46 t ha-1 yr-1, resulting in a total soil loss of 970 Mt annually; equal to an area the size of Berlin (assuming a removal of 1 meter). According to the RUSLE2015 model approximately 12.7% of arable lands in the European Union is estimated to suffer from moderate to high erosion(>5 t ha-1 yr-1). This equates to an area of 140,373 km2 which equals to the surface area of Greece (Environmental Science & Policy, 54, 438-447; 2015). Even the mean erosion rate outstrips the mean formation rate (<1.4 tonnes per ha annually). The recent RUSLE2015 estimated that the policy interventions (i.e. reduced tillage, crop residues, grass margins, cover crops, stone walls and contouring) through the common agricultural policy (CAP) during last decade have reduced the rate of soil loss in the EU by an average of 9.5% overall, and by 20% for arable lands (NATURE, 526, 195). Latest developments in RUSLE2015 allow to incorporate the forthcoming intensification of rainfall (climate changes) and land use changes such as afforestation, land abandonment and arable land expansion. Recently, a module of CENTURY model was coupled with the RUSLE2015 for estimating the effect of erosion in current carbon balance in European agricultural lands.

Landscape characteristics and livestock presence influence common ravens: Relevance to greater sage-grouse conservation

USGS Publications Warehouse

Coates, Peter S.; Brussee, Brianne E.; Howe, Kristy; Gustafson, K. Ben; Casazza, Michael L.; Delehanty, David J.

2016-01-01

Common raven (Corvus corax; hereafter, raven) population abundance in the sagebrush steppe of the American West has increased threefold during the previous four decades, largely as a result of unintended resource subsidies from human land-use practices. This is concerning because ravens frequently depredate nests of species of conservation concern, such as greater sage-grouse (Centrocercus urophasianus; hereafter, sage-grouse). Grazing by livestock in sagebrush ecosystems is common practice on most public lands, but associations between livestock and ravens are poorly understood. The primary objective of this study was to identify the effects of livestock on raven occurrence while accounting for landscape characteristics within human-altered sagebrush steppe habitat, particularly in areas occupied by breeding sage-grouse. Using data from southeastern Idaho collected during spring and summer across 3 yr, we modeled raven occurrence as a function of the presence of livestock while accounting for multiple landscape covariates, including land cover features, topographical features, and proximity to sage-grouse lek sites (breeding grounds), as well as site-level anthropogenic features. While accounting for landscape characteristics, we found that the odds of raven occurrence increased 45.8% in areas where livestock were present. In addition, ravens selected areas near sage-grouse leks, with the odds of occurrence decreasing 8.9% for every 1-km distance, increase away from the lek. We did not find an association between livestock use and distance to lek. We also found that ravens selected sites with relatively lower elevation containing increased amounts of cropland, wet meadow, and urbanization. Limiting raven access to key anthropogenic subsidies and spatially segregating livestock from sage-grouse breeding areas would likely reduce exposure of predatory ravens to sage-grouse nests and chicks.

Modelling Participatory Geographic Information System for Customary Land Conflict Resolution

NASA Astrophysics Data System (ADS)

Gyamera, E. A.; Arko-Adjei, A.; Duncan, E. E.; Kuma, J. S. Y.

2017-11-01

Since land contributes to about 73 % of most countries Gross Domestic Product (GDP), attention on land rights have tremendously increased globally. Conflicts over land have therefore become part of the major problems associated with land administration. However, the conventional mechanisms for land conflict resolution do not provide satisfactory result to disputants due to various factors. This study sought to develop a Framework of using Participatory Geographic Information System (PGIS) for customary land conflict resolution. The framework was modelled using Unified Modelling Language (UML). The PGIS framework, called butterfly model, consists of three units namely, Social Unit (SU), Technical Unit (TU) and Decision Making Unit (DMU). The name butterfly model for land conflict resolution was adopted for the framework based on its features and properties. The framework has therefore been recommended to be adopted for land conflict resolution in customary areas.

Implication of Agricultural Land Use Change on Regional Climate Projection

NASA Astrophysics Data System (ADS)

Wang, G.; Ahmed, K. F.; You, L.

2015-12-01

Agricultural land use plays an important role in land-atmosphere interaction. Agricultural activity is one of the most important processes driving human-induced land use land cover change (LULCC) in a region. In addition to future socioeconomic changes, climate-induced changes in crop yield represent another important factor shaping agricultural land use. In feedback, the resulting LULCC influences the direction and magnitude of global, regional and local climate change by altering Earth's radiative equilibrium. Therefore, assessment of climate change impact on future agricultural land use and its feedback is of great importance in climate change study. In this study, to evaluate the feedback of projected land use changes to the regional climate in West Africa, we employed an asynchronous coupling between a regional climate model (RegCM) and a prototype land use projection model (LandPro). The LandPro model, which was developed to project the future change in agricultural land use and the resulting shift in natural vegetation in West Africa, is a spatially explicit model that can account for both climate and socioeconomic changes in projecting future land use changes. In the asynchronously coupled modeling framework, LandPro was run for every five years during the period of 2005-2050 accounting for climate-induced change in crop yield and socioeconomic changes to project the land use pattern by the mid-21st century. Climate data at 0.5˚ was derived from RegCM to drive the crop model DSSAT for each of the five-year periods to simulate crop yields, which was then provided as input data to LandPro. Subsequently, the land use land cover map required to run RegCM was updated every five years using the outputs from the LandPro simulations. Results from the coupled model simulations improve the understanding of climate change impact on future land use and the resulting feedback to regional climate.

Impacts of climate and land use changes on regional nutrient export in the South Saskatchewan River catchment

NASA Astrophysics Data System (ADS)

Morales-Marin, L. A.; Wheater, H. S.; Lindenschmidt, K. E.

2016-12-01

Climate and land use changes modify the physical functioning of river catchments and, in particular, influence the transport of nutrients from land to water. In large-scale catchments, where a variety of climates, topographies, soil types and land uses co-exist to form a highly heterogeneous environment, a more complex nutrient dynamic is imposed by climate and land use changes. This is the case of the South Saskatchewan River (SSR) that, along with the North Saskatchewan River, forms the largest river system in western Canada. In the past years changes in the land use and new industrial developments in the SSR area have heightened serious concerns about the future of water quality in the catchment and downstream waters. Agricultural activities have increased the supply of manure and fertilizer for cropping. Oil and gas exploitation has also increased the risk of surface water and groundwater contamination. The rapid population growth not only leads to increments in water consumption and wastewater, but in the construction of roads, railways and the expansion of new urban developments that impose hydraulic controls on the catchment hydrology and therefore the sediment and nutrient transport. Consequences of the actual anthropogenic changes have been notorious in reservoirs where algal blooms and signs of eutrophication have become common during certain times of the year. Although environmental agencies are constantly improving the mechanisms to reduce nutrient export into the river and ensure safe water quality standards, further research is needed in order to identify major nutrient sources and quantify nutrient export and also, to assess how nutrients are going to vary as a result of future climate and land use change scenarios. The SPAtially Referenced Regression On Watershed (SPARROW) model is therefore implemented to assess water quality regionally, in order to describe spatial and temporal patterns to identify those factors and processes that affect water quality. Climate and land uses change scenarios are incorporated into the model to explain how nutrient export will vary across the catchment in 30, 60 and 90 years from now. Uncertainty of nutrient predictions is also assesses in order to determine the degree of reliability of the estimates.

Impacts of climate and land use changes on regional nutrient export in the South Saskatchewan River catchment

NASA Astrophysics Data System (ADS)

Morales-Marin, L. A.; Wheater, H. S.; Lindenschmidt, K. E.

2015-12-01

Climate and land use changes modify the physical functioning of river catchments and, in particular, influence the transport of nutrients from land to water. In large-scale catchments, where a variety of climates, topographies, soil types and land uses co-exist to form a highly heterogeneous environment, a more complex nutrient dynamic is imposed by climate and land use changes. This is the case of the South Saskatchewan River (SSR) that, along with the North Saskatchewan River, forms the largest river system in western Canada. In the past years changes in the land use and new industrial developments in the SSR area have heightened serious concerns about the future of water quality in the catchment and downstream waters. Agricultural activities have increased the supply of manure and fertilizer for cropping. Oil and gas exploitation has also increased the risk of surface water and groundwater contamination. The rapid population growth not only leads to increments in water consumption and wastewater, but in the construction of roads, railways and the expansion of new urban developments that impose hydraulic controls on the catchment hydrology and therefore the sediment and nutrient transport. Consequences of the actual anthropogenic changes have been notorious in reservoirs where algal blooms and signs of eutrophication have become common during certain times of the year. Although environmental agencies are constantly improving the mechanisms to reduce nutrient export into the river and ensure safe water quality standards, further research is needed in order to identify major nutrient sources and quantify nutrient export and also, to assess how nutrients are going to vary as a result of future climate and land use change scenarios. The SPAtially Referenced Regression On Watershed (SPARROW) model is therefore implemented to assess water quality regionally, in order to describe spatial and temporal patterns to identify those factors and processes that affect water quality. Climate and land uses change scenarios are incorporated into the model to explain how nutrient export will vary across the catchment in 30, 60 and 90 years from now. Uncertainty of nutrient predictions is also assesses in order to determine the degree of reliability of the estimates.

Land-use planning: One geologist's viewpoint

USGS Publications Warehouse

Zen, E.-A.

1983-01-01

Planning for the best use of land and its resources should take fully into consideration the long-term consequences of each type of use in order to stretch out most beneficially the well-being of society in the future, and to protect the integrity of the land and its biota. Three kinds of land-use can be distinguished for planning purposes. Reversible land-use leaves the land, after use, essentially as it was before; little or no man-induced modification remains. An example of reversible use in the United States is the designation of certain public lands as Wilderness. Terminal land-use commits the land to a chosen particular use, and any attempt at reversal requires either time-scales that are long compared with the expected lifespan of the social and political institution, or a commitment of resources that is too high for society to consider worth bearing. Examples of terminal land-use are location of metropolises and sites of toxic and/or radioactive waste disposals; by its nature the list grows monotonically. A current source of some social tension arises from the fact that Wilderness designation appears to assign a terminal-use status by legislative fiat, whereas in fact the land is being used reversibly. In between these two extremes of reversible and terminal land-use, the bulk of land-use is sequential, in which each use of land changes its potentials and configurations, and these changes are mainly irreversible. One goal of geologic input to land-use planning is to identify the various pathways along which a given land may be used, in order to extract the greatest benefit to society with the least harm to the land and its life. The proposed planning format consists of identification of (1) types of land, (2) types of use, (3) nature of consumption of resources when (2) acts upon (1), (4) identification of alternative pathways of land recovery to the original or some new state, and (5) due consideration of potentials for future use. Some consumptions are tangible; others, such as consumption of future options, are not. However, all must be considered in deciding how the land should be used, and both internal and environmental costs need to be included in the planning. Predictive methodology for land-use planning and for estimations of uncertainties must be developed to allow for the needs and consequences of both land-use and land recovery. Hardin (1968) spoke of the tragedy of the commons; White (1967) discussed the constraints of the western cultural heritage on our attitude towards our land and its resources. Land-use presents an archetype of the problem of the commons; only by community awareness of the dire consequences of the latent tragedy can effective societal action begin for the stewardship of the commons. Land-use decisions involve value judgement and are problems without technical solutions; but they require technical input, and earth scientists have a major role to play in both providing the input and in pointing out the implications of alternative decisions. ?? 1983.

Management-focused approach to investigating coastal water-quality drivers and impacts in the Baltic Sea

NASA Astrophysics Data System (ADS)

Vigouroux, G.; Destouni, G.; Chen, Y.; Bring, A.; Jönsson, A.; Cvetkovic, V.

2017-12-01

Coastal areas link human-driven conditions on land with open sea conditions, and include crucial and vulnerable ecosystems that provide a variety of ecosystem services. Eutrophication is a common problem that is not least observed in the Baltic Sea, where coastal water quality is influenced both by land-based nutrient loading and by partly eutrophic open sea conditions. Robust and adaptive management of coastal systems is essential and necessitates integration of large scale catchment-coastal-marine systems as well as consideration of anthropogenic drivers and impacts, and climate change. To address this coastal challenge, relevant methodological approaches are required for characterization of coupled land, local coastal, and open sea conditions under an adaptive management framework for water quality. In this paper we present a new general and scalable dynamic characterization approach, developed for and applied to the Baltic Sea and its coastal areas. A simple carbon-based water quality model is implemented, dividing the Baltic Sea into main management basins that are linked to corresponding hydrological catchments on land, as well as to each other though aggregated three-dimensional marine hydrodynamics. Relevant hydrodynamic variables and associated water quality results have been validated on the Baltic Sea scale and show good accordance with available observation data and other modelling approaches. Based on its scalability, this methodology is further used on coastal zone scale to investigate the effects of hydrodynamic, hydro-climatic and nutrient load drivers on water quality and management implications for coastal areas in the Baltic Sea.

Evaluation of Land Use Regression Models for Nitrogen Dioxide and Benzene in Four US Cities

PubMed Central

Mukerjee, Shaibal; Smith, Luther; Neas, Lucas; Norris, Gary

2012-01-01

Spatial analysis studies have included the application of land use regression models (LURs) for health and air quality assessments. Recent LUR studies have collected nitrogen dioxide (NO2) and volatile organic compounds (VOCs) using passive samplers at urban air monitoring networks in El Paso and Dallas, TX, Detroit, MI, and Cleveland, OH to assess spatial variability and source influences. LURs were successfully developed to estimate pollutant concentrations throughout the study areas. Comparisons of development and predictive capabilities of LURs from these four cities are presented to address this issue of uniform application of LURs across study areas. Traffic and other urban variables were important predictors in the LURs although city-specific influences (such as border crossings) were also important. In addition, transferability of variables or LURs from one city to another may be problematic due to intercity differences and data availability or comparability. Thus, developing common predictors in future LURs may be difficult. PMID:23226985

One-dimensional soil temperature assimilation experiment based on unscented particle filter and Common Land Model

NASA Astrophysics Data System (ADS)

Fu, Xiao Lei; Jin, Bao Ming; Jiang, Xiao Lei; Chen, Cheng

2018-06-01

Data assimilation is an efficient way to improve the simulation/prediction accuracy in many fields of geosciences especially in meteorological and hydrological applications. This study takes unscented particle filter (UPF) as an example to test its performance at different two probability distribution, Gaussian and Uniform distributions with two different assimilation frequencies experiments (1) assimilating hourly in situ soil surface temperature, (2) assimilating the original Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) once per day. The numerical experiment results show that the filter performs better when increasing the assimilation frequency. In addition, UPF is efficient for improving the soil variables (e.g., soil temperature) simulation/prediction accuracy, though it is not sensitive to the probability distribution for observation error in soil temperature assimilation.

The Chlamydomonas Genome Reveals the Evolution of Key Animal and Plant Functions

PubMed Central

Merchant, Sabeeha S.; Prochnik, Simon E.; Vallon, Olivier; Harris, Elizabeth H.; Karpowicz, Steven J.; Witman, George B.; Terry, Astrid; Salamov, Asaf; Fritz-Laylin, Lillian K.; Maréchal-Drouard, Laurence; Marshall, Wallace F.; Qu, Liang-Hu; Nelson, David R.; Sanderfoot, Anton A.; Spalding, Martin H.; Kapitonov, Vladimir V.; Ren, Qinghu; Ferris, Patrick; Lindquist, Erika; Shapiro, Harris; Lucas, Susan M.; Grimwood, Jane; Schmutz, Jeremy; Cardol, Pierre; Cerutti, Heriberto; Chanfreau, Guillaume; Chen, Chun-Long; Cognat, Valérie; Croft, Martin T.; Dent, Rachel; Dutcher, Susan; Fernández, Emilio; Ferris, Patrick; Fukuzawa, Hideya; González-Ballester, David; González-Halphen, Diego; Hallmann, Armin; Hanikenne, Marc; Hippler, Michael; Inwood, William; Jabbari, Kamel; Kalanon, Ming; Kuras, Richard; Lefebvre, Paul A.; Lemaire, Stéphane D.; Lobanov, Alexey V.; Lohr, Martin; Manuell, Andrea; Meier, Iris; Mets, Laurens; Mittag, Maria; Mittelmeier, Telsa; Moroney, James V.; Moseley, Jeffrey; Napoli, Carolyn; Nedelcu, Aurora M.; Niyogi, Krishna; Novoselov, Sergey V.; Paulsen, Ian T.; Pazour, Greg; Purton, Saul; Ral, Jean-Philippe; Riaño-Pachón, Diego Mauricio; Riekhof, Wayne; Rymarquis, Linda; Schroda, Michael; Stern, David; Umen, James; Willows, Robert; Wilson, Nedra; Zimmer, Sara Lana; Allmer, Jens; Balk, Janneke; Bisova, Katerina; Chen, Chong-Jian; Elias, Marek; Gendler, Karla; Hauser, Charles; Lamb, Mary Rose; Ledford, Heidi; Long, Joanne C.; Minagawa, Jun; Page, M. Dudley; Pan, Junmin; Pootakham, Wirulda; Roje, Sanja; Rose, Annkatrin; Stahlberg, Eric; Terauchi, Aimee M.; Yang, Pinfen; Ball, Steven; Bowler, Chris; Dieckmann, Carol L.; Gladyshev, Vadim N.; Green, Pamela; Jorgensen, Richard; Mayfield, Stephen; Mueller-Roeber, Bernd; Rajamani, Sathish; Sayre, Richard T.; Brokstein, Peter; Dubchak, Inna; Goodstein, David; Hornick, Leila; Huang, Y. Wayne; Jhaveri, Jinal; Luo, Yigong; Martínez, Diego; Ngau, Wing Chi Abby; Otillar, Bobby; Poliakov, Alexander; Porter, Aaron; Szajkowski, Lukasz; Werner, Gregory; Zhou, Kemin; Grigoriev, Igor V.; Rokhsar, Daniel S.; Grossman, Arthur R.

2010-01-01

Chlamydomonas reinhardtii is a unicellular green alga whose lineage diverged from land plants over 1 billion years ago. It is a model system for studying chloroplast-based photosynthesis, as well as the structure, assembly, and function of eukaryotic flagella (cilia), which were inherited from the common ancestor of plants and animals, but lost in land plants. We sequenced the ∼120-megabase nuclear genome of Chlamydomonas and performed comparative phylogenomic analyses, identifying genes encoding uncharacterized proteins that are likely associated with the function and biogenesis of chloroplasts or eukaryotic flagella. Analyses of the Chlamydomonas genome advance our understanding of the ancestral eukaryotic cell, reveal previously unknown genes associated with photosynthetic and flagellar functions, and establish links between ciliopathy and the composition and function of flagella. PMID:17932292

The value of flexibility in conservation financing.

PubMed

Lennox, Gareth D; Fargione, Joseph; Spector, Sacha; Williams, Gwyn; Armsworth, Paul R

2017-06-01

Land-acquisition strategies employed by conservation organizations vary in their flexibility. Conservation-planning theory largely fails to reflect this by presenting models that are either extremely inflexible-parcel acquisitions are irreversible and budgets are fixed-or extremely flexible-previously acquired parcels can readily be sold. This latter approach, the selling of protected areas, is infeasible or problematic in many situations. We considered the value to conservation organizations of increasing the flexibility of their land-acquisition strategies through their approach to financing deals. Specifically, we modeled 2 acquisition-financing methods commonly used by conservation organizations: borrowing and budget carry-over. Using simulated data, we compared results from these models with those from an inflexible fixed-budget model and an extremely flexible selling model in which previous acquisitions could be sold to fund new acquisitions. We then examined 3 case studies of how conservation organizations use borrowing and budget carry-over in practice. Model comparisons showed that borrowing and budget carry-over always returned considerably higher rewards than the fixed-budget model. How they performed relative to the selling model depended on the relative conservation value of past acquisitions. Both the models and case studies showed that incorporating flexibility through borrowing or budget carry-over gives conservation organizations the ability to purchase parcels of higher conservation value than when budgets are fixed without the problems associated with the selling of protected areas. © 2016 Society for Conservation Biology.

19. First floor, room south of second floor landing, looking ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

19. First floor, room south of second floor landing, looking east - Veterans Administration Center, Officers Duplex Quarters, 5302 East Kellogg (Legal Address); 5500 East Kellogg (Common Address), Wichita, Sedgwick County, KS

Worldwide Historical Estimates of Leaf Area Index, 1932-2000

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

Scurlock, JMO

2002-02-06

Approximately 1000 published estimates of leaf area index (LAI) from nearly 400 unique field sites, covering the period 1932-2000, have been compiled into a single data set. LA1 is a key parameter for global and regional models of biosphere/atmosphere exchange of carbon dioxide, water vapor, and other materials. It also plays an integral role in determining the energy balance of the land surface. This data set provides a benchmark of typical values and ranges of LA1 for a variety of biomes and land cover types, in support of model development and validation of satellite-derived remote sensing estimates of LA1 andmore » other vegetation parameters. The LA1 data are linked to a bibliography of over 300 original source references. These historic LA1 data are mostly from natural and seminatural (managed) ecosystems, although some agricultural estimates are also included. Although methodologies for determining LA1 have changed over the decades, it is useful to represent the inconsistencies (e.g., in maximum value reported for a particular biome) that are actually found in the scientific literature. Needleleaf (coniferous) forests are by far the most commonly measured biome/land cover types in this compilation, with 22% of the measurements from temperate evergreen needleleaf forests, and boreal evergreen needleleaf forests and crops the next most common (about 9% each). About 40% of the records in the data set were published in the past 10 years (1991-2000), with a further 20% collected between 1981 and 1990. Mean LAI ({+-} standard deviation), distributed between 15 biome/land cover classes, ranged from 1.31 {+-} 0.85 for deserts to 8.72 {+-} 4.32 for tree plantations, with evergreen forests (needleleaf and broadleaf) displaying the highest LA1 among the natural terrestrial vegetation classes. We have identified statistical outliers in this data set, both globally and according to the different biome/land cover classes, but despite some decreases in mean LA1 values reported, our overall conclusions remained the same. This report documents the development of this data set, its contents, and its availability on the Internet from the Oak Ridge National Laboratory Distributed Active Archive Center for Biogeochemical Dynamics. Caution is advised in using these data, which were collected using a wide range of methodologies and assumptions that may not allow comparisons among sites.« less

Effects of optimized root water uptake parameterization schemes on water and heat flux simulation in a maize agroecosystem

NASA Astrophysics Data System (ADS)

Cai, Fu; Ming, Huiqing; Mi, Na; Xie, Yanbing; Zhang, Yushu; Li, Rongping

2017-04-01

As root water uptake (RWU) is an important link in the water and heat exchange between plants and ambient air, improving its parameterization is key to enhancing the performance of land surface model simulations. Although different types of RWU functions have been adopted in land surface models, there is no evidence as to which scheme most applicable to maize farmland ecosystems. Based on the 2007-09 data collected at the farmland ecosystem field station in Jinzhou, the RWU function in the Common Land Model (CoLM) was optimized with scheme options in light of factors determining whether roots absorb water from a certain soil layer ( W x ) and whether the baseline cumulative root efficiency required for maximum plant transpiration ( W c ) is reached. The sensibility of the parameters of the optimization scheme was investigated, and then the effects of the optimized RWU function on water and heat flux simulation were evaluated. The results indicate that the model simulation was not sensitive to W x but was significantly impacted by W c . With the original model, soil humidity was somewhat underestimated for precipitation-free days; soil temperature was simulated with obvious interannual and seasonal differences and remarkable underestimations for the maize late-growth stage; and sensible and latent heat fluxes were overestimated and underestimated, respectively, for years with relatively less precipitation, and both were simulated with high accuracy for years with relatively more precipitation. The optimized RWU process resulted in a significant improvement of CoLM's performance in simulating soil humidity, temperature, sensible heat, and latent heat, for dry years. In conclusion, the optimized RWU scheme available for the CoLM model is applicable to the simulation of water and heat flux for maize farmland ecosystems in arid areas.

Searching for Feedbacks between Land-use/Land-cover Changes and the Water Budget in Complex Terrain at the Dry Creek Experimental Watershed in Idaho, USA

NASA Astrophysics Data System (ADS)

Huang, Y.; Engdahl, N.

2017-12-01

Proactive management to improve water resource sustainability is often limited by a lack of understanding about the hydrological consequences of human activities and climate induced land use and land cover (LULC) change. Changes in LULC can alter runoff, soil moisture, and evapotranspiration, but these effects are complex and traditional modeling techniques have had limited successes in realistically simulating the relevant feedbacks. Recent studies have investigated the coupled interactions but typically do so at coarse resolutions with simple topographic settings, so it is unclear if the previous conclusions remain valid in the steep, complex terrains that dominate the western USA. This knowledge gap was explored with a series of integrated hydrologic simulations based on the Dry Creek Experimental Watershed (DCEW) in southwestern Idaho, USA, using the ParFlow.CLM model. The DCEW has extensive monitoring data that allowed for a direct calibration and validation of the base-case simulation, which is not commonly done with integrated models. The effects of LULC change on the hydrologic and water budgets were then assessed at two grid resolutions (20m and 40m) under four LULC scenarios: 1) current LULC; 2) LULC change from a small but gradual decrease in potential recharge (PR); 3) LULC change from a large but rapid decrease in PR; and 4) LULC change from a large but gradual decrease in PR. The results show that the methods used for terrain processing and the grid resolution can both heavily impact the simulation results and that LULC change can significantly alter the relative amounts of groundwater storage and runoff.

NCEP/NLDAS Drought Monitoring and Prediction

NASA Astrophysics Data System (ADS)

Xia, Y.; Ek, M.; Wood, E.; Luo, L.; Sheffield, J.; Lettenmaier, D.; Livneh, B.; Cosgrove, B.; Mocko, D.; Meng, J.; Wei, H.; Restrepo, P.; Schaake, J.; Mo, K.

2009-05-01

The NCEP Environmental Modeling Center (EMC) collaborated with its CPPA (Climate Prediction Program of the Americas) partners to develop a North American Land Data Assimilation System (NLDAS, http://www.emc.ncep.noaa.gov/mmb/nldas) to monitor and predict the drought over the Continental United States (CONUS). The realtime NLDAS drought monitor, executed daily at NCEP/EMC, including daily, weekly and monthly anomaly and percentile of six fields (soil moisture, snow water equivalent, total runoff, streamflow, evaporation, precipitation) outputted from four land surface models (Noah, Mosaic, SAC, and VIC) on a common 1/8th degree grid using common hourly land surface forcing. The non-precipitation surface forcing is derived from NCEP's retrospective and realtime North American Regional Reanalysis System (NARR). The precipitation forcing is anchored to a daily gauge-only precipitation analysis over CONUS that applies a Parameter-elevation Regressions on Independent Slopes Model (PRISM) correction. This daily precipitation analysis is then temporally disaggregated to hourly precipitation amounts using radar and satellite precipitation. The NARR- based surface downward solar radiation is bias-corrected using seven years (1997-2004) of GOES satellite- derived solar radiation retrievals. The uncoupled ensemble seasonal drought prediction utilizes the following three independent approaches for generating downscaled ensemble seasonal forecasts of surface forcing: (1) Ensemble Streamflow Prediction, (2) CPC Official Seasonal Climate Outlook, and (3) NCEP CFS ensemble dynamical model prediction. For each of these three approaches, twenty ensemble members of forcing realizations are generated using a Bayesian merging algorithm developed by Princeton University. The three forcing methods are then used to drive the VIC model in seasonal prediction mode over thirteen large river basins that together span the CONUS domain. One to nine month ensemble seasonal prediction products such as air temperature, precipitation, soil moisture, snowpack, total runoff, evaporation and streamflow are derived for each forcing approach. The anomalies and percentiles of the predicted products for each approach may be used for CONUS drought prediction. This system is executed at the beginning of each month and distributes its products by the 10th of each month. The prediction products are evaluated using corresponding monitoring products for the VIC model and are compared with the prediction products from other research groups (e.g., University of Washington at Seattle, NASA Goddard) in the CONUS.

Urban stream syndrome in a small, lightly developed watershed: a statistical analysis of water chemistry parameters, land use patterns, and natural sources.

PubMed

Halstead, Judith A; Kliman, Sabrina; Berheide, Catherine White; Chaucer, Alexander; Cock-Esteb, Alicea

2014-06-01

The relationships among land use patterns, geology, soil, and major solute concentrations in stream water for eight tributaries of the Kayaderosseras Creek watershed in Saratoga County, NY, were investigated using Pearson correlation coefficients and multivariate regression analysis. Sub-watersheds corresponding to each sampling site were delineated, and land use patterns were determined for each of the eight sub-watersheds using GIS. Four land use categories (urban development, agriculture, forests, and wetlands) constituted more than 99 % of the land in the sub-watersheds. Eleven water chemistry parameters were highly and positively correlated with each other and urban development. Multivariate regression models indicated urban development was the most powerful predictor for the same eleven parameters (conductivity, TN, TP, NO[Formula: see text], Cl(-), HCO(-)3, SO9(2-)4, Na(+), K(+), Ca(2+), and Mg(2+)). Adjusted R(2) values, ranging from 19 to 91 %, indicated that these models explained an average of 64 % of the variance in these 11 parameters across the samples and 70 % when Mg(2+) was omitted. The more common R (2), ranging from 29 to 92 %, averaged 68 % for these 11 parameters and 72 % when Mg(2+) was omitted. Water quality improved most with forest coverage in stream watersheds. The strong associations between water quality variables and urban development indicated an urban source for these 11 water quality parameters at all eight sampling sites was likely, suggesting that urban stream syndrome can be detected even on a relatively small scale in a lightly developed area. Possible urban sources of Ca(2+) and HCO(-)3 are suggested.

Modeling the effects of climate and land use change on instream temperature in the Upper Tar River, North Carolina

NASA Astrophysics Data System (ADS)

Daraio, J. A.; Bales, J. D.

2011-12-01

Freshwater mussels are among the most imperiled groups of organisms in the world. Declines in abundance and diversity in North America have been attributed to a wide range of human activities, and many species occur in habitats close to their upper thermal tolerance. We are modeling instream temperature (T) as part of an effort to understand the response of imperiled freshwater mussels to anthropogenically induced changes in water T, habitat, and flow. We used the Precipitation-Runoff Modeling System (PRMS) to model projected changes in stream discharge, and the Stream Network Temperature Model (SNTEMP) to model changes in instream T due to climate and land-use change in the Upper Tar River, North Carolina, which has a drainage area of 2200 mi^2. Down-scaled gridded 12km Global Circulation Models were used for precipitation and T inputs to PRMS simulations from the present through 2060. Land-use change through 2060 in the Upper Tar basin was estimated from SLEUTH, a model that estimates land-use change using the probability of urbanization, (results available from NC State University) and incorporated into PRMS for long term simulations. Stream segment discharge and lateral and groundwater flow into each stream segment from PRMS were used as input for SNTEMP. Groundwater T was assumed equal to the average annual air T for the basin. Lateral inflow T was estimated from physical characteristics of the basin (e.g. impervious area, cover density, cover type, solar radiation, air T) when possible, or from a regression with air T based on empirical field data at 20 sites throughout the basin. In addition to T, data on mussel and fish populations (e.g., density and species composition?) and microhabitat have been collected at these sites. The SNTEMP model was calibrated using the mean daily T at each site. Nash-Sutcliffe efficiency values ranged from 0.86 to 0.94 for mean daily T, and from 0.80 to 0.93 for maximum daily T. Ensemble simulations were run for a range of climate change and land use scenarios to estimate the potential for increased instream T at each of the 20 sites. The results of these simulations will be used in conjunction with field and laboratory data on the thermal tolerances of mussels to assess the potential for elevated temperatures to adversely affect rare and common mussel populations.

Are wetland regulations cost effective for species protection? A case study of amphibian metapopulations.

PubMed

Bauer, Dana Marie; Paton, Peter W C; Swallow, Stephen K

2010-04-01

Recent declines in amphibian populations have raised concern among conservation biologists, with habitat loss and degradation due to human activities among the leading causes. The most common policies used to protect the habitat of pond-breeding amphibians are wetland regulations that safeguard the wetland itself. However, many amphibians spend much of their adult lives foraging and over-wintering in upland habitats and exist as metapopulations with dispersal among ponds. With no consideration of lands in the dispersal matrix, wetland policies may be ineffective at protecting amphibians or other wetland species that disperse across the landscape. This paper examined the adequacy and cost effectiveness of alternative conservation policies and their corresponding land use patterns on the long-term persistence of pond-breeding amphibians in exurban landscapes. We used computer simulations to compare outcomes of wetland buffer policies and broader landscape-wide conservation policies across a variety of landscape scenarios, and we conducted sensitivity analyses on the model's species parameters in order to generalize our results to other wetland species. Results showed that, in the majority of human-dominated landscapes, some amount of dispersal matrix protection is necessary for long-term species persistence. However, in landscapes with extremely low-intensity land use (e.g., low-density residential housing) and high pond density, wetland buffer policies may be all that is required. It is not always more cost effective to protect core habitat over the dispersal matrix, a common conservation practice. Conservation costs that result from forgone residential, commercial, or agricultural activities can vary substantially but increase in a nonlinear manner regardless of land use zoning. There appears to be a threshold around an average habitat patch occupancy level of 80%, after which opportunity costs rise dramatically.

Synergy between land use and climate change increases future fire risk in Amazon forests

DOE PAGES

Le Page, Yannick; Morton, Douglas; Hartin, Corinne; ...

2017-12-20

Tropical forests have been a permanent feature of the Amazon basin for at least 55 million years, yet climate change and land use threaten the forest's future over the next century. Understory forest fires, which are common under the current climate in frontier forests, may accelerate Amazon forest losses from climate-driven dieback and deforestation. Far from land use frontiers, scarce fire ignitions and high moisture levels preclude significant burning, yet projected climate and land use changes may increase fire activity in these remote regions. Here, we used a fire model specifically parameterized for Amazon understory fires to examine the interactionsmore » between anthropogenic activities and climate under current and projected conditions. In a scenario of low mitigation efforts with substantial land use expansion and climate change – Representative Concentration Pathway (RCP) 8.5 – projected understory fires increase in frequency and duration, burning 4–28 times more forest in 2080–2100 than during 1990–2010. In contrast, active climate mitigation and land use contraction in RCP4.5 constrain the projected increase in fire activity to 0.9–5.4 times contemporary burned area. Importantly, if climate mitigation is not successful, land use contraction alone is very effective under low to moderate climate change, but does little to reduce fire activity under the most severe climate projections. These results underscore the potential for a fire-driven transformation of Amazon forests if recent regional policies for forest conservation are not paired with global efforts to mitigate climate change.« less

Synergy between land use and climate change increases future fire risk in Amazon forests

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

Le Page, Yannick; Morton, Douglas; Hartin, Corinne

Tropical forests have been a permanent feature of the Amazon basin for at least 55 million years, yet climate change and land use threaten the forest's future over the next century. Understory forest fires, which are common under the current climate in frontier forests, may accelerate Amazon forest losses from climate-driven dieback and deforestation. Far from land use frontiers, scarce fire ignitions and high moisture levels preclude significant burning, yet projected climate and land use changes may increase fire activity in these remote regions. Here, we used a fire model specifically parameterized for Amazon understory fires to examine the interactionsmore » between anthropogenic activities and climate under current and projected conditions. In a scenario of low mitigation efforts with substantial land use expansion and climate change – Representative Concentration Pathway (RCP) 8.5 – projected understory fires increase in frequency and duration, burning 4–28 times more forest in 2080–2100 than during 1990–2010. In contrast, active climate mitigation and land use contraction in RCP4.5 constrain the projected increase in fire activity to 0.9–5.4 times contemporary burned area. Importantly, if climate mitigation is not successful, land use contraction alone is very effective under low to moderate climate change, but does little to reduce fire activity under the most severe climate projections. These results underscore the potential for a fire-driven transformation of Amazon forests if recent regional policies for forest conservation are not paired with global efforts to mitigate climate change.« less

Land Surface Microwave Emissivity Dynamics: Observations, Analysis and Modeling

NASA Technical Reports Server (NTRS)

Tian, Yudong; Peters-Lidard, Christa D.; Harrison, Kenneth W.; Kumar, Sujay; Ringerud, Sarah

2014-01-01

Land surface microwave emissivity affects remote sensing of both the atmosphere and the land surface. The dynamical behavior of microwave emissivity over a very diverse sample of land surface types is studied. With seven years of satellite measurements from AMSR-E, we identified various dynamical regimes of the land surface emission. In addition, we used two radiative transfer models (RTMs), the Community Radiative Transfer Model (CRTM) and the Community Microwave Emission Modeling Platform (CMEM), to simulate land surface emissivity dynamics. With both CRTM and CMEM coupled to NASA's Land Information System, global-scale land surface microwave emissivities were simulated for five years, and evaluated against AMSR-E observations. It is found that both models have successes and failures over various types of land surfaces. Among them, the desert shows the most consistent underestimates (by approx. 70-80%), due to limitations of the physical models used, and requires a revision in both systems. Other snow-free surface types exhibit various degrees of success and it is expected that parameter tuning can improve their performances.

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.

[A review on research of land surface water and heat fluxes].

PubMed

Sun, Rui; Liu, Changming

2003-03-01

Many field experiments were done, and soil-vegetation-atmosphere transfer(SVAT) models were stablished to estimate land surface heat fluxes. In this paper, the processes of experimental research on land surface water and heat fluxes are reviewed, and three kinds of SVAT model(single layer model, two layer model and multi-layer model) are analyzed. Remote sensing data are widely used to estimate land surface heat fluxes. Based on remote sensing and energy balance equation, different models such as simplified model, single layer model, extra resistance model, crop water stress index model and two source resistance model are developed to estimate land surface heat fluxes and evapotranspiration. These models are also analyzed in this paper.

Learjet Model 55 Wing Analysis with Landing Loads

NASA Technical Reports Server (NTRS)

Boroughs, R. R.

1985-01-01

The NASTRAN analysis was used to determine the impact of new landing loads on the Learjet Model 55 wing. These new landing loads were the result of a performance improvement effort to increase the landing weight of the aircraft to 18,000 lbs. from 17,000 lbs. and extend the life of the tires and brakes by incorporating larger tires and heavy duty brakes. Landing loads for the original 17,000 lb. airplane landing configuration were applied to the full airplane NASTRAN model. The analytical results were correlated with the strain gage data from the original landing load static tests. The landing loads for the 18,000 lb. airplane were applied to the full airplane NASTRAN model, and a comparison was made with the original Model 55 data. The results of this comparison enable Learjet to determine the difference in stress distribution in the wing due to these two different sets of landing loads.

POST2 End-To-End Descent and Landing Simulation for the Autonomous Landing and Hazard Avoidance Technology Project

NASA Technical Reports Server (NTRS)

Fisher, Jody l.; Striepe, Scott A.

2007-01-01

The Program to Optimize Simulated Trajectories II (POST2) is used as a basis for an end-to-end descent and landing trajectory simulation that is essential in determining the design and performance capability of lunar descent and landing system models and lunar environment models for the Autonomous Landing and Hazard Avoidance Technology (ALHAT) project. This POST2-based ALHAT simulation provides descent and landing simulation capability by integrating lunar environment and lander system models (including terrain, sensor, guidance, navigation, and control models), along with the data necessary to design and operate a landing system for robotic, human, and cargo lunar-landing success. This paper presents the current and planned development and model validation of the POST2-based end-to-end trajectory simulation used for the testing, performance and evaluation of ALHAT project system and models.

Numerical simulation of the effects of urban land-use changes on the local climate of multiple desert cities

NASA Astrophysics Data System (ADS)

Kamal, S. M.; Huang, H. P.; Myint, S. W.

2016-12-01

This study quantifies the effect of urbanization on local climate by numerical simulations for multiple desert cities with a wide range of urban size, baseline climatology, and composition of land cover. The numerical experiments use the Weather Research and Forecasting (WRF) model with multiple layers of nesting centered at a desert city. To extract the influence of land-use changes, twin runs are performed with each pair driven by the same time-varying lateral boundary conditions from reanalysis but different land surface conditions from Landsat observations for 1985 and 2010. The differences in the meteorological fields between the two runs are interpreted as the effects of land-use changes due to urbanization from 1985-2010. Using this strategy, simulations are carried out for five desert cities: (1) Las Vegas, United States, (2) Hotan, China, (3) Kharga, Egypt, (4) Beer Sheva, Israel, and (5) Jodhpur, India. The results of the simulations reveal a common pattern of the climatic effect of desert urbanization with nighttime warming but daytime cooling over areas where urbanization occurred. This effect is mainly confined to the urban area and is not sensitive to the size of the city or the detail of land cover in the surrounding non-urban areas. The pattern is similar in winter and summer. Exceptions to this pattern are found in a few cases in which the noisiness of local circulation, specifically monsoon and land-sea breeze, overwhelms the climatic signal induced by land-use changes. Although the local climatic responses to urbanization are qualitatively similar for the five desert cities, quantitative differences exist in the magnitudes of nighttime warming and daytime cooling. The possible reasons for those secondary differences are discussed.

Vgi for Land Administration - a Quality Perspective

NASA Astrophysics Data System (ADS)

Navratil, G.; Frank, A. U.

2013-05-01

Since the use of volunteered geographic information (VGI) or crowd sourced data (Goodchild, 2007) became more common, several people proposed the use of such methods of data collection for various fields. Success stories were Wikipedia encyclopaedia and OpenStreetMap (OSM), but also using VGI in land administration has been proposed. Robin McLaren proposed crowd sourcing as a way to get a new citizen collaboration model in land administration to enhance transparency and decrease costs (McLaren, 2011). Keenja et al. discussed the perception of VGI within the Dutch cadastre (Keenja, De Vries, Bennet, & Laarakker, 2012). Basiouka and Potsiou even discuss how crowd sourcing can be used to identify errors in the Hellenic cadastre (Basiouka & Potsiou, 2012). One problem of VGI is the quality control (compare Goodchild & Li, 2012). The problem with most data in a land administration system is that there is only a small group of people that can verify the correctness of information. The correct location of a boundary, for example, can only be assessed by the owners of the pieces of land touching at the boundary (and surveyors after investigation and measurement). How shall VGI then provide reliable data? Boundaries between areas of different use may be visible but land administration is often interested in ownership boundaries. In the paper we discuss the types of data used in land administration as discussed by Dale and McLaughlin (1999). These categories are then analyzed to identify the areas where VGI can actually provide reliable input. What we hope to learn from such an analysis is how to use the methodology of crowd sourcing for land administration, even if the data collection authoritatively.

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.

The Proposed U.S.-Panama Free Trade Agreement

DTIC Science & Technology

2010-02-22

China ). About one-third of all cargo passing through the canal has its origin or destination in the United States. The canal’s total economic...has begun the expansion project. With transfer of the canal and its operations to Panama, the country also inherited a substantial amount of land ...prospects as a business venture, but because it is forward looking rather than relying on the “maquiladora” business model common in much of the region.12

The Proposed U.S.-Panama Free Trade Agreement

DTIC Science & Technology

2011-04-21

largest and fastest growing traffic volume generated along the U.S. East Coast-to-Asia trade route (especially U.S.- China ). About one-third of all cargo...With transfer of the canal and its operations to Panama, the country also inherited a substantial amount of land and physical assets. The conversion...not only for its prospects as a business venture, but because it is forward looking rather than relying on the “maquiladora” business model common in

Functional connectivity in replicated urban landscapes in the land snail (Cornu aspersum).

PubMed

Balbi, Manon; Ernoult, Aude; Poli, Pedro; Madec, Luc; Guiller, Annie; Martin, Marie-Claire; Nabucet, Jean; Beaujouan, Véronique; Petit, Eric J

2018-03-01

Urban areas are highly fragmented and thereby exert strong constraints on individual dispersal. Despite this, some species manage to persist in urban areas, such as the garden snail, Cornu aspersum, which is common in cityscapes despite its low mobility. Using landscape genetic approaches, we combined study area replication and multiscale analysis to determine how landscape composition, configuration and connectivity influence snail dispersal across urban areas. At the overall landscape scale, areas with a high percentage of roads decreased genetic differentiation between populations. At the population scale, genetic differentiation was positively linked with building surface, the proportion of borders where wooded patches and roads appeared side by side and the proportion of borders combining wooded patches and other impervious areas. Analyses based on pairwise genetic distances validated the isolation-by-distance and isolation-by-resistance models for this land snail, with an equal fit to least-cost paths and circuit-theory-based models. Each of the 12 landscapes analysed separately yielded specific relations to environmental features, whereas analyses integrating all replicates highlighted general common effects. Our results suggest that urban transport infrastructures facilitate passive snail dispersal. At a local scale, corresponding to active dispersal, unfavourable habitats (wooded and impervious areas) isolate populations. This work upholds the use of replicated landscapes to increase the generalizability of landscape genetics results and shows how multiscale analyses provide insight into scale-dependent processes. © 2018 John Wiley & Sons Ltd.

Setting limits: The development and use of factor-ceiling distributions for an urban assessment using macroinvertebrates

USGS Publications Warehouse

Carter, J.L.; Fend, S.V.

2005-01-01

Lotic habitats in urban settings are often more modified than in other anthropogenically influenced areas. The extent, degree, and permanency of these modifications compromise the use of traditional reference-based study designs to evaluate the level of lotic impairment and establish restoration goals. Directly relating biological responses to the combined effects of urbanization is further complicated by the nonlinear response often observed in common metrics (e.g., Ephemeroptera, Plecoptera, and Trichoptera [EPT] species richness) to measures of human influence (e.g., percentage urban land cover). A characteristic polygonal biological response often arises from the presence of a generalized limiting factor (i.e., urban land use) plus the influence of multiple additional stressors that are nonuniformly distributed throughout the urban environment. Benthic macroinvertebrates, on-site physical habitat and chemistry, and geographical information systems-derived land cover data for 85 sites were collected within the 1,600-km2 Santa Clara Valley (SCV), California urban area. A biological indicator value was derived from EPT richness and percentage EPT. Partitioned regression was used to define reference conditions and estimate the degree of site impairment. We propose that an upper-boundary condition (factor-ceiling) modeled by partitioned regression using ordinary least squares represents an attainable upper limit for biological condition in the SCV area. Indicator values greater than the factor-ceiling, which is monotonically related to existing land use, are considered representative of reference conditions under the current habitat conditions imposed by existing land cover and land use.

Modelling environmental variables for geohazards and georesources assessment to support sustainable land-use decisions in Zaragoza (Spain)

NASA Astrophysics Data System (ADS)

Lamelas, M. T.; Hoppe, A.; de la Riva, J.; Marinoni, O.

2009-10-01

Land-use decisions are usually made on the basis of a variety of criteria. While it is common practice to integrate economic, ecological and social (triple bottom line) criteria, explicit geoscientific factors are relatively rarely considered. If a planned land use involves an interaction with the geosphere, geoscientific aspects should be playing a more important role in the process. With the objective to facilitate a sustainable land-use decision-making a research project was initiated. The area around the city of Zaragoza, in the Ebro Basin of northern Spain, was chosen due to its high degree of industrialisation and urbanization. The area is exposed to several geohazards (e.g., sinkholes and erosion) that may have significant negative effects on current and future land uses. Geographical Information System (GIS) technologies are used to process the complex geoscientific information. Further GIS analysis comprised the creation of an erosion susceptibility map that follows the ITC (International Institute for Geo-Information Science and Earth Observation) system of terrain analysis. The agricultural capability of the soil was determined using the Microleis System. We identify geomorphologic units that show high susceptibility to erosion and high agricultural potential and suggest a method to implement this information in a land-use planning process. Degraded slopes developed upon Tertiary rocks show the highest susceptibility to erosion and low values of agricultural capability, whereas the flat valley bottoms and irrigated flood plains have the highest values of agricultural capability.

Fuzzy logic-based assessment for mapping potential infiltration areas in low-gradient watersheds.

PubMed

Quiroz Londoño, Orlando Mauricio; Romanelli, Asunción; Lima, María Lourdes; Massone, Héctor Enrique; Martínez, Daniel Emilio

2016-07-01

This paper gives an account of the design a logic-based approach for identifying potential infiltration areas in low-gradient watersheds based on remote sensing data. This methodological framework is applied in a sector of the Pampa Plain, Argentina, which has high level of agricultural activities and large demands for groundwater supplies. Potential infiltration sites are assessed as a function of two primary topics: hydrologic and soil conditions. This model shows the state of each evaluated subwatershed respecting to its potential contribution to infiltration mainly based on easily measurable and commonly used parameters: drainage density, geomorphologic units, soil media, land-cover, slope and aspect (slope orientation). Mapped outputs from the logic model displayed 42% very low-low, 16% moderate, 41% high-very high contribution to potential infiltration in the whole watershed. Subwatersheds in the upper and lower section were identified as areas with high to very high potential infiltration according to the following media features: low drainage density (<1.5 km/km(2)), arable land and pastures as the main land-cover categories, sandy clay loam to loam - clay loam soils and with the geomorphological units named poorly drained plain, channelized drainage plain and, dunes and beaches. Copyright © 2016 Elsevier Ltd. All rights reserved.

Land Use, Recreation, and Wildlife Habitats: GIS Applications Using FIA Plot Data

Treesearch

Victor A. Rudis

2001-01-01

Spatial contexts govern whether and how land is used. Forest surveys inventory land uses from sampled plots and provide common forest resource summaries with limited information about associated nearby uses, or the landscape context. I used the USDA Forest Service's Forest Inventory and Analysis program of the South-Central States survey region (Alabama, Arkansas...

Phylogenetic analysis of pectin-related gene families in Physcomitrella patens and nine other plant species yields evolutionary insights into cell walls

PubMed Central

2014-01-01

Background Pectins are acidic sugar-containing polysaccharides that are universally conserved components of the primary cell walls of plants and modulate both tip and diffuse cell growth. However, many of their specific functions and the evolution of the genes responsible for producing and modifying them are incompletely understood. The moss Physcomitrella patens is emerging as a powerful model system for the study of plant cell walls. To identify deeply conserved pectin-related genes in Physcomitrella, we generated phylogenetic trees for 16 pectin-related gene families using sequences from ten plant genomes and analyzed the evolutionary relationships within these families. Results Contrary to our initial hypothesis that a single ancestral gene was present for each pectin-related gene family in the common ancestor of land plants, five of the 16 gene families, including homogalacturonan galacturonosyltransferases, polygalacturonases, pectin methylesterases, homogalacturonan methyltransferases, and pectate lyase-like proteins, show evidence of multiple members in the early land plant that gave rise to the mosses and vascular plants. Seven of the gene families, the UDP-rhamnose synthases, UDP-glucuronic acid epimerases, homogalacturonan galacturonosyltransferase-like proteins, β-1,4-galactan β-1,4-galactosyltransferases, rhamnogalacturonan II xylosyltransferases, and pectin acetylesterases appear to have had a single member in the common ancestor of land plants. We detected no Physcomitrella members in the xylogalacturonan xylosyltransferase, rhamnogalacturonan I arabinosyltransferase, pectin methylesterase inhibitor, or polygalacturonase inhibitor protein families. Conclusions Several gene families related to the production and modification of pectins in plants appear to have multiple members that are conserved as far back as the common ancestor of mosses and vascular plants. The presence of multiple members of these families even before the divergence of other important cell wall-related genes, such as cellulose synthases, suggests a more complex role than previously suspected for pectins in the evolution of land plants. The presence of relatively small pectin-related gene families in Physcomitrella as compared to Arabidopsis makes it an attractive target for analysis of the functions of pectins in cell walls. In contrast, the absence of genes in Physcomitrella for some families suggests that certain pectin modifications, such as homogalacturonan xylosylation, arose later during land plant evolution. PMID:24666997

Responsiveness of Rural and Urban Land Uses to Land Rent Determinants in the U.S. South

Treesearch

Ian Hardie; Peter Parks; Peter Gottleib; David N. Wear

2000-01-01

Ricardian and von Thünen land rent models are combined into a single land use shore model including farm, forest, and urban lurid uses. The lurid share model is applied to the Southern United States, and elasticities are extracted that measure land share response to changes in iqulation, income, land values, prices, and costs in counties with different degrees of...

Parametric design and analysis on the landing gear of a planet lander using the response surface method

NASA Astrophysics Data System (ADS)

Zheng, Guang; Nie, Hong; Luo, Min; Chen, Jinbao; Man, Jianfeng; Chen, Chuanzhi; Lee, Heow Pueh

2018-07-01

The purpose of this paper is to obtain the design parameter-landing response relation for designing the configuration of the landing gear in a planet lander quickly. To achieve this, parametric studies on the landing gear are carried out using the response surface method (RSM), based on a single landing gear landing model validated by experimental results. According to the design of experiment (DOE) results of the landing model, the RS (response surface)-functions of the three crucial landing responses are obtained, and the sensitivity analysis (SA) of the corresponding parameters is performed. Also, two multi-objective optimizations designs on the landing gear are carried out. The analysis results show that the RS (response surface)-model performs well for the landing response design process, with a minimum fitting accuracy of 98.99%. The most sensitive parameters for the three landing response are the design size of the buffers, struts friction and the diameter of the bending beam. Moreover, the good agreement between the simulated model and RS-model results are obtained in two optimized designs, which show that the RS-model coupled with the FE (finite element)-method is an efficient method to obtain the design configuration of the landing gear.

Land cover characterization and land surface parameterization research

USGS Publications Warehouse

Steyaert, Louis T.; Loveland, Thomas R.; Parton, William J.

1997-01-01

The understanding of land surface processes and their parameterization in atmospheric, hydrologic, and ecosystem models has been a dominant research theme over the past decade. For example, many studies have demonstrated the key role of land cover characteristics as controlling factors in determining land surface processes, such as the exchange of water, energy, carbon, and trace gases between the land surface and the lower atmosphere. The requirements for multiresolution land cover characteristics data to support coupled-systems modeling have also been well documented, including the need for data on land cover type, land use, and many seasonally variable land cover characteristics, such as albedo, leaf area index, canopy conductance, surface roughness, and net primary productivity. Recently, the developers of land data have worked more closely with the land surface process modelers in these efforts.

Assessing development pressure in the Chesapeake Bay watershed: An evaluation of two land-use change models

USGS Publications Warehouse

Claggett, Peter; Jantz, Claire A.; Goetz, S.J.; Bisland, C.

2004-01-01

Natural resource lands in the Chesapeake Bay watershed are increasingly susceptible to conversion into developed land uses, particularly as the demand for residential development grows. We assessed development pressure in the Baltimore-Washington, DC region, one of the major urban and suburban centers in the watershed. We explored the utility of two modeling approaches for forecasting future development trends and patterns by comparing results from a cellular automata model, SLEUTH (slope, land use, excluded land, urban extent, transportation), and a supply/demand/allocation model, the Western Futures Model. SLEUTH can be classified as a land-cover change model and produces projections on the basis of historic trends of changes in the extent and patterns of developed land and future land protection scenarios. The Western Futures Model derives forecasts from historic trends in housing units, a U.S. Census variable, and exogenously supplied future population projections. Each approach has strengths and weaknesses, and combining the two has advantages and limitations. ?? 2004 Kluwer Academic Publishers.

Assessing development pressure in the Chesapeake Bay watershed: an evaluation of two land-use change models.

PubMed

Claggett, Peter R; Jantz, Claire A; Goetz, Scott J; Bisland, Carin

2004-06-01

Natural resource lands in the Chesapeake Bay watershed are increasingly susceptible to conversion into developed land uses, particularly as the demand for residential development grows. We assessed development pressure in the Baltimore-Washington, DC region, one of the major urban and suburban centers in the watershed. We explored the utility of two modeling approaches for forecasting future development trends and patterns by comparing results from a cellular automata model, SLEUTH (slope, land use, excluded land, urban extent, transportation), and a supply/demand/allocation model, the Western Futures Model. SLEUTH can be classified as a land-cover change model and produces projections on the basis of historic trends of changes in the extent and patterns of developed land and future land protection scenarios. The Western Futures Model derives forecasts from historic trends in housing units, a U.S. Census variable, and exogenously supplied future population projections. Each approach has strengths and weaknesses, and combining the two has advantages and limitations.

Regional Climate Change Impact on Agricultural Land Use in West Africa

NASA Astrophysics Data System (ADS)

Ahmed, K. F.; Wang, G.; You, L.

2014-12-01

Agriculture is a key element of the human-induced land use land cover change (LULCC) that is influenced by climate and can potentially influence regional climate. Temperature and precipitation directly impact the crop yield (by controlling photosynthesis, respiration and other physiological processes) that then affects agricultural land use pattern. In feedback, the resulting changes in land use and land cover play an important role to determine the direction and magnitude of global, regional and local climate change by altering Earth's radiative equilibrium. The assessment of future agricultural land use is, therefore, of great importance in climate change study. In this study, we develop a prototype land use projection model and, using this model, project the changes to land use pattern and future land cover map accounting for climate-induced yield changes for major crops in West Africa. Among the inputs to the land use projection model are crop yield changes simulated by the crop model DSSAT, driven with the climate forcing data from the regional climate model RegCM4.3.4-CLM4.5, which features a projected decrease of future mean crop yield and increase of inter-annual variability. Another input to the land use projection model is the projected changes of food demand in the future. In a so-called "dumb-farmer scenario" without any adaptation, the combined effect of decrease in crop yield and increase in food demand will lead to a significant increase in agricultural land use in future years accompanied by a decrease in forest and grass area. Human adaptation through land use optimization in an effort to minimize agricultural expansion is found to have little impact on the overall areas of agricultural land use. While the choice of the General Circulation Model (GCM) to derive initial and boundary conditions for the regional climate model can be a source of uncertainty in projecting the future LULCC, results from sensitivity experiments indicate that the changes in land use pattern are robust.

Observed and modeled carbon and energy fluxes for agricultural sites under North American Carbon Program site-level interim synthesis

NASA Astrophysics Data System (ADS)

Lokupitiya, E. Y.; Denning, A.

2010-12-01

Croplands are unique, man-made ecosystems with dynamics mostly dependent on human decisions. Crops uptake a significant amount of Carbon dioxide (CO2) during their short growing seasons. Reliability of the available models to predict the carbon exchanges by croplands is important in estimating the cropland contribution towards overall land-atmosphere carbon exchange and global carbon cycle. The energy exchanges from croplands include both sensible and latent heat fluxes. This study focuses on analyzing the performance of 19 land surface models across five agricultural sites under the site-level interim synthesis of North American Carbon Program (NACP). Model simulations were performed using a common simulation protocol and input data, including gap-filled meteorological data corresponding to each site. The net carbon fluxes (i.e. net ecosystem exchange; NEE) and energy fluxes (sensible and latent heat) predicted by 12 models with sub-hourly/hourly temporal resolution and 7 models with daily temporal resolution were compared against the site-specific gap-filled observed flux tower data. Comparisons were made by site and crop type (i.e. maize, soybean, and wheat), mainly focusing on the coefficient of determination, correlation, root mean square error, and standard deviation. Analyses also compared the diurnal, seasonal, and inter-annual variability of the modeled fluxes against the observed data and the mean modeled data.

Drainage area characterization for evaluating green infrastructure using the Storm Water Management Model

NASA Astrophysics Data System (ADS)

Lee, Joong Gwang; Nietch, Christopher T.; Panguluri, Srinivas

2018-05-01

Urban stormwater runoff quantity and quality are strongly dependent upon catchment properties. Models are used to simulate the runoff characteristics, but the output from a stormwater management model is dependent on how the catchment area is subdivided and represented as spatial elements. For green infrastructure modeling, we suggest a discretization method that distinguishes directly connected impervious area (DCIA) from the total impervious area (TIA). Pervious buffers, which receive runoff from upgradient impervious areas should also be identified as a separate subset of the entire pervious area (PA). This separation provides an improved model representation of the runoff process. With these criteria in mind, an approach to spatial discretization for projects using the US Environmental Protection Agency's Storm Water Management Model (SWMM) is demonstrated for the Shayler Crossing watershed (SHC), a well-monitored, residential suburban area occupying 100 ha, east of Cincinnati, Ohio. The model relies on a highly resolved spatial database of urban land cover, stormwater drainage features, and topography. To verify the spatial discretization approach, a hypothetical analysis was conducted. Six different representations of a common urbanscape that discharges runoff to a single storm inlet were evaluated with eight 24 h synthetic storms. This analysis allowed us to select a discretization scheme that balances complexity in model setup with presumed accuracy of the output with respect to the most complex discretization option considered. The balanced approach delineates directly and indirectly connected impervious areas (ICIA), buffering pervious area (BPA) receiving impervious runoff, and the other pervious area within a SWMM subcatchment. It performed well at the watershed scale with minimal calibration effort (Nash-Sutcliffe coefficient = 0.852; R2 = 0.871). The approach accommodates the distribution of runoff contributions from different spatial components and flow pathways that would impact green infrastructure performance. A developed SWMM model using the discretization approach is calibrated by adjusting parameters per land cover component, instead of per subcatchment and, therefore, can be applied to relatively large watersheds if the land cover components are relatively homogeneous and/or categorized appropriately in the GIS that supports the model parameterization. Finally, with a few model adjustments, we show how the simulated stream hydrograph can be separated into the relative contributions from different land cover types and subsurface sources, adding insight to the potential effectiveness of planned green infrastructure scenarios at the watershed scale.

Results from Assimilating AMSR-E Soil Moisture Estimates into a Land Surface Model Using an Ensemble Kalman Filter in the Land Information System

NASA Technical Reports Server (NTRS)

Blankenship, Clay B.; Crosson, William L.; Case, Jonathan L.; Hale, Robert

2010-01-01

Improve simulations of soil moisture/temperature, and consequently boundary layer states and processes, by assimilating AMSR-E soil moisture estimates into a coupled land surface-mesoscale model Provide a new land surface model as an option in the Land Information System (LIS)

Modeling the Spatial Dynamics of Regional Land Use: The CLUE-S Model

NASA Astrophysics Data System (ADS)

Verburg, Peter H.; Soepboer, Welmoed; Veldkamp, A.; Limpiada, Ramil; Espaldon, Victoria; Mastura, Sharifah S. A.

2002-09-01

Land-use change models are important tools for integrated environmental management. Through scenario analysis they can help to identify near-future critical locations in the face of environmental change. A dynamic, spatially explicit, land-use change model is presented for the regional scale: CLUE-S. The model is specifically developed for the analysis of land use in small regions (e.g., a watershed or province) at a fine spatial resolution. The model structure is based on systems theory to allow the integrated analysis of land-use change in relation to socio-economic and biophysical driving factors. The model explicitly addresses the hierarchical organization of land use systems, spatial connectivity between locations and stability. Stability is incorporated by a set of variables that define the relative elasticity of the actual land-use type to conversion. The user can specify these settings based on expert knowledge or survey data. Two applications of the model in the Philippines and Malaysia are used to illustrate the functioning of the model and its validation.

Modeling the spatial dynamics of regional land use: the CLUE-S model.

PubMed

Verburg, Peter H; Soepboer, Welmoed; Veldkamp, A; Limpiada, Ramil; Espaldon, Victoria; Mastura, Sharifah S A

2002-09-01

Land-use change models are important tools for integrated environmental management. Through scenario analysis they can help to identify near-future critical locations in the face of environmental change. A dynamic, spatially explicit, land-use change model is presented for the regional scale: CLUE-S. The model is specifically developed for the analysis of land use in small regions (e.g., a watershed or province) at a fine spatial resolution. The model structure is based on systems theory to allow the integrated analysis of land-use change in relation to socio-economic and biophysical driving factors. The model explicitly addresses the hierarchical organization of land use systems, spatial connectivity between locations and stability. Stability is incorporated by a set of variables that define the relative elasticity of the actual land-use type to conversion. The user can specify these settings based on expert knowledge or survey data. Two applications of the model in the Philippines and Malaysia are used to illustrate the functioning of the model and its validation.

International land deals, local people's livelihood, and environment nexus (How to create win-win land deals in Ethiopia?)

NASA Astrophysics Data System (ADS)

Teklemariam Gebremeskel, Dereje; Witlox, Frank; Azadi, Hossein; Haile, Mitiku; Nyssen, Jan

2013-04-01

Following the global raise in demand for food and biofuel production, transnational companies are acquiring large scale agricultural land in developing countries such as Ethiopia. Considering land as one of the factors to be outsourced for development, the government of Ethiopia is supplying millions of hectares of land to transnational companies in the form of longterm lease. Many of the companies which engage in large scale land acquisition are of Indian, Chinese, Ethiopian diaspora, German, Malaysian, Italian, British, Dutch, Turkish, and Saudi-Arabian origin. The boom in the acquisition of farm land in the country has sparked an all-rounded debate among civil society groups, international institutions, nongovernmental organizations and independent development experts. The common reflections concerning the land deals in Ethiopia and elsewhere contain much rhetoric and hype which lack analysis of the real situation "on the ground" giving different connotations such as 'land grabbing', 'agricultural outsourcing', 'neo-colonialism', 'agrarian colonialism', and 'land underdevelopment'. However, deforestation, soil degradation, marginalization of local indigenous communities, and minimally unfair gains from investment by the host country are among the real points of concern arising out of the long term land lease contracts. Scientific evidence is lacking concerning the pragmatic impacts of large scale agricultural land acquisitions by transnational companies upon the natural environment (forest and land), local peoples' livelihood, and the contacting parties (the host country and the companies). The major objective of this study is to investigate the impacts in the context of Ethiopia, orienting to reinvent win-win land use models which constitute sustainable land use, local peoples' livelihood and the company-host country interests. To achieve this overall objective, the study employs a number of methods and methodologies constituting both qualitative and quantitative data analyses at different levels of focus ranging from household and farm levels to national and transnational. The study focuses on the western lowlands of Ethiopia where there are many companies engaged in large scale commercial farming, where 75% of it is below 1500 m a.s.l with average annual temperature of 20-25°C and annual rainfall of 500-1800 mm. Some preliminary exploratory findings indicate that there is massive land use conversion (deforestation) and 'voluntary' displacement of indigenous communities, which requires further triangulation. Key words: agricultural outsourcing; environmental services; land grabbing; sustainable livelihood; soil conservation

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

Meeks, H.

The purpose of this article is to provide information on the reality and procedure of the Bureau of Land Management's Simultaneous Oil and Gas Leasing System, commonly called the Government Oil and Gas Lottery. The article is about noncompetitive leases. This kind of leasing is done through the Simultaneous Oil and Gas Leasing System. Lands that are not within any known geologic structure of a producing oil and gas field, commonly known as wildcat lands, are subject to leasing to the first qualified person making application for a lease. Such a lease is termed noncompetitive since the applicant is entitledmore » to the lease without competitive bidding. Most Federal oil and gas leases are obtained through noncompetitive leasing procedures.« less

An overview of the Southern Nevada Agency Partnership science and research synthesis: Chapter 1 in The Southern Nevada Agency Partnership science and research synthesis: science to support land management in southern Nevada

USGS Publications Warehouse

Chambers, Jeanne C.; Brooks, Matthew L.; Turner, Kent; Raish, Carol B.; Ostoja, Steven M.

2013-01-01

Maintaining and restoring the diverse ecosystems and resources that occur in southern Nevada in the face of rapid socio-economic and ecological change presents numerous challenged to Federal land managers. Rapid population growth since the 1980s, the land uses associated with that growth, and the interactions of those uses with the generally dry and highly variable climate result in numerous stresses to ecosystems, species, and cultural resource. In addition, climate models predict that the rate of temperature increase and, thus, changes in ecological processes, will be highest for ecosystems like the Mojave Desert. The Southern Nevada Agency Partnership (SNAP; http:www.SNAP.gov) was established in 1999 to address common issues pertaining to public lands in southern Nevada. Partners include the Bureau of Land Management, National Park Service, U.S. Fish and Wildlife Service, and USDA Forest Service and they work with each other, the local community, and other partners. SNAP agencies manage more than seven million acres of public lands in southern Nevada (95% of the land area). Federal land includes two national recreation areas, two national conservation area, four national wildlife refuges, 18 congressionally designated wilderness areas, five wilderness study areas, and 22 areas of critical environmental concern. The partnership's activities are mainly centered in Southern Nevada's Clark County (fig. 1.1), but lands managed by SNAP partner agencies also include portions of Lake Mead National Recreation Area in Mohave County, Arizona, U.S. Fish and Wildlife Service, and USDA Forest Service-managed lands in Lincoln and Nye Counties, Nevada, and all lands and activities managed by the Southern Nevada District Office of the Bureau of Land Management. These lands encompass nine distinct ecosystem types (fig. 1.2), support multiple species of management concern an 17 listed species, and are rich in cultural and historic resource. This introductory executive summary discusses the Science and Research Strategy developed by the SNAP agencies, the Science and Research Report, and need for science-based management in southern Nevada.

Computational Fluid Dynamic Analyses for the High-Lift Common Research Model Using the USM3D and FUN3D Flow Solvers

NASA Technical Reports Server (NTRS)

Rivers, Melissa; Hunter, Craig; Vatsa, Veer

2017-01-01

Two Navier-Stokes codes were used to compute flow over the High-Lift Common Research Model (HL-CRM) in preparation for a wind tunnel test to be performed at the NASA Langley Research Center 14-by-22-Foot Subsonic Tunnel in fiscal year 2018. Both flight and wind tunnel conditions were simulated by the two codes at set Mach numbers and Reynolds numbers over a full angle-of-attack range for three configurations: cruise, landing and takeoff. Force curves, drag polars and surface pressure contour comparisons are shown for the two codes. The lift and drag curves compare well for the cruise configuration up to 10deg angle of attack but not as well for the other two configurations. The drag polars compare reasonably well for all three configurations. The surface pressure contours compare well for some of the conditions modeled but not as well for others.

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.

USGS perspectives on an integrated approach to watershed and coastal management

USGS Publications Warehouse

Larsen, Matthew C.; Hamilton, Pixie A.; Haines, John W.; Mason, Jr., Robert R.

2010-01-01

The writers discuss three critically important steps necessary for achieving the goal for improved integrated approaches on watershed and coastal protection and management. These steps involve modernization of monitoring networks, creation of common data and web services infrastructures, and development of modeling, assessment, and research tools. Long-term monitoring is needed for tracking the effectiveness approaches for controlling land-based sources of nutrients, contaminants, and invasive species. The integration of mapping and monitoring with conceptual and mathematical models, and multidisciplinary assessments is important in making well-informed decisions. Moreover, a better integrated data network is essential for mapping, statistical, and modeling applications, and timely dissemination of data and information products to a broad community of users.

Modeling a two-layer flow system at the subarctic, subalpine tree line during snowmelt

NASA Astrophysics Data System (ADS)

Leenders, Erica E.; Woo, Ming-Ko

2002-10-01

In the subarctic it is common to encounter a two-layer flow system consisting of a porous organic cover overlying frozen or unfrozen mineral soils with much lower hydraulic conductivities. The "simple lumped reservoir parametric," or "semidistributed land-use-based runoff processes" (SLURP), model was adapted to simulate runoff generated by such a flow system from an upland shrub land to an open woodland downslope. A subalpine site in Wolf Creek, Yukon, Canada, was subdivided into two aggregated simulation areas (ASA), each being a unit characterized by a set of parameters. The model computes the vertical water balance and flow generation from several storages, and then routes the water out of the ASA. When applied to the 1999 snowmelt season, the model simulated the very low lateral flow and a large increase in storage in the mineral soil, as was observed in the field. The model was used to assess the sensitivity of the two-layer flow system under a range of temperature, snow cover, and frost conditions. Results show that within the range of possible climatic conditions, the hydrologic system is unlikely to yield significant runoff across the subalpine tree line, but if ground ice is abundant in the soil pores, percolation will be limited and fast flow from the surface layer is enhanced.

Summertime land-sea thermal contrast and atmospheric circulation over East Asia in a warming climate—Part I: Past changes and future projections

NASA Astrophysics Data System (ADS)

Kamae, Youichi; Watanabe, Masahiro; Kimoto, Masahide; Shiogama, Hideo

2014-11-01

Land-sea surface air temperature (SAT) contrast, an index of tropospheric thermodynamic structure and dynamical circulation, has shown a significant increase in recent decades over East Asia during the boreal summer. In Part I of this two-part paper, observational data and the results of transient warming experiments conducted using coupled atmosphere-ocean general circulation models (GCMs) are analyzed to examine changes in land-sea thermal contrast and the associated atmospheric circulation over East Asia from the past to the future. The interannual variability of the land-sea SAT contrast over the Far East for 1950-2012 was found to be tightly coupled with a characteristic tripolar pattern of tropospheric circulation over East Asia, which manifests as anticyclonic anomalies over the Okhotsk Sea and around the Philippines, and a cyclonic anomaly over Japan during a positive phase, and vice versa. In response to CO2 increase, the cold northeasterly winds off the east coast of northern Japan and the East Asian rainband were strengthened with the circulation pattern well projected on the observed interannual variability. These results are commonly found in GCMs regardless of future forcing scenarios, indicating the robustness of the East Asian climate response to global warming. The physical mechanisms responsible for the increase of the land-sea contrast are examined in Part II.

Investigating the Potential of Land Use Modifications to Mitigate the Respiratory Health Impacts of NO2: A Case Study in the Portland-Vancouver Metropolitan Area

NASA Astrophysics Data System (ADS)

Rao, Meenakshi

The health impacts of urban air pollution are a growing concern in our rapidly urbanizing world. Urban air pollutants show high intra-urban spatial variability linked to urban land use and land cover (LULC). This correlation of air pollutants with LULC is widely recognized; LULC data is an integral input into a wide range of models, especially land use regression models developed by epidemiologists to study the impact of air pollution on human health. Given the demonstrated links between LULC and urban air pollution, and between urban air pollution and health, an interesting question arises: what is the potential of LULC modifications to mitigate the health impacts of urban air pollution? In this dissertation we assess the potential of LULC modifications to mitigate the health impacts of NO2, a respiratory irritant and strong marker for combustion-related air pollution, in the Portland-Vancouver metropolitan area in northwestern USA. We begin by measuring summer and winter NO2 in the area using a spatially dense network of passive NO 2 samplers. We next develop an annual average model for NO2 based on the observational data, using random forest--for the first time in the realm of urban air pollution--to disentangle the effects of highly correlated LULC variables on ambient NO2 concentrations. We apply this random forest (LURF) model to a 200m spatial grid covering the study area, and use this 200m LURF model to quantify the effect of different urban land use categories on ambient concentrations of NO2. Using the changes in ambient NO2 concentrations resulting from land use modifications as input to BenMAP (a health benefits assessment tool form the US EPA), we assess the NO2-related health impact associated with each land use category and its modifications. We demonstrate how the LURF model can be used to assess the respiratory health benefits of competing land use modifications, including city-wide and local-scale mitigation strategies based on modifying tree canopy and vehicle miles traveled (VMT). Planting trees is a common land cover modification strategy undertaken by cities to reduce air pollution. Statistical models such as LUR and LURF demonstrate a correlation between tree cover and reduced air pollution, but they cannot demonstrate causation. Hence, we run the atmospheric chemistry and transport model CMAQ to examine to what extent the dry deposition mechanism can explain the reduction of NO2 which statistical models associate with tree canopy. Results from our research indicate that even though the Portland-Vancouver area is in compliance with the US EPA NO2 standards, ambient concentrations of NO2 still create an annual health burden of at least 40 million USD. Our model suggests that NO2 associated with high intensity development and VMT may be creating an annual health burden of 7 million and 3.3 million USD respectively. Existing tree canopy, on the other hand, is associated with an annual health benefit of 1.4 million USD. LULC modifications can mitigate some fraction of this health burden. A 2% increase in tree canopy across the study area may reduce incidence rates of asthma exacerbation by as much as 7%. We also find that increasing tree canopy is a more effective strategy than reducing VMT in terms of mitigating the health burden of NO 2. CMAQ indicates that the amount of NO2 removed by dry deposition is an order of magnitude smaller than that predicted by our statistical model. About one-third of the difference can be explained by the lower NO2 values predicted by CMAQ, and one-third may be attributable to parameterization of stomatal uptake.

On the Land-Ocean Contrast of Tropical Convection and Microphysics Statistics Derived from TRMM Satellite Signals and Global Storm-Resolving Models

NASA Technical Reports Server (NTRS)

Matsui, Toshihisa; Chern, Jiun-Dar; Tao, Wei-Kuo; Lang, Stephen E.; Satoh, Masaki; Hashino, Tempei; Kubota, Takuji

2016-01-01

A 14-year climatology of Tropical Rainfall Measuring Mission (TRMM) collocated multi-sensor signal statistics reveal a distinct land-ocean contrast as well as geographical variability of precipitation type, intensity, and microphysics. Microphysics information inferred from the TRMM precipitation radar and Microwave Imager (TMI) show a large land-ocean contrast for the deep category, suggesting continental convective vigor. Over land, TRMM shows higher echo-top heights and larger maximum echoes, suggesting taller storms and more intense precipitation, as well as larger microwave scattering, suggesting the presence of morelarger frozen convective hydrometeors. This strong land-ocean contrast in deep convection is invariant over seasonal and multi-year time-scales. Consequently, relatively short-term simulations from two global storm-resolving models can be evaluated in terms of their land-ocean statistics using the TRMM Triple-sensor Three-step Evaluation via a satellite simulator. The models evaluated are the NASA Multi-scale Modeling Framework (MMF) and the Non-hydrostatic Icosahedral Cloud Atmospheric Model (NICAM). While both simulations can represent convective land-ocean contrasts in warm precipitation to some extent, near-surface conditions over land are relatively moisture in NICAM than MMF, which appears to be the key driver in the divergent warm precipitation results between the two models. Both the MMF and NICAM produced similar frequencies of large CAPE between land and ocean. The dry MMF boundary layer enhanced microwave scattering signals over land, but only NICAM had an enhanced deep convection frequency over land. Neither model could reproduce a realistic land-ocean contrast in in deep convective precipitation microphysics. A realistic contrast between land and ocean remains an issue in global storm-resolving modeling.

Model of land cover change prediction in West Java using cellular automata-Markov chain (CA-MC)

NASA Astrophysics Data System (ADS)

Virtriana, Riantini; Sumarto, Irawan; Deliar, Albertus; Pasaribu, Udjianna S.; Taufik, Moh.

2015-04-01

Land is a fundamental factor that closely related to economic growth and supports the needs of human life. Land-use activity is a major issue and challenge for country planners. The cause of change in land use type activity may be due to socio economic development or due to changes in the environment or may be due to both. In an effort to understand the phenomenon of land cover changes, can be approached through land cover change modelling. Based on the facts and data contained, West Java has a high economic activity that will have an impact on land cover change. CA-MC is a model that used to determine the statistical change probabilistic for each of land cover type from land cover data at different time periods. CA-MC is able to provide the output of land cover type that should occurred. Results from a CA-MC modelling in predicting land cover changes showed an accuracy rate of 95.42%.

Hardwood planting

Treesearch

Richard M. Godman

1992-01-01

Hardwood planting used to be most common on private land. Now more and more hardwoods are being planted on public land. Not much hardwood planting research is going on but recent summaries of earlier trials allow us to give you the following guidelines.

An individual-based modelling approach to estimate landscape connectivity for bighorn sheep (Ovis canadensis).

PubMed

Allen, Corrie H; Parrott, Lael; Kyle, Catherine

2016-01-01

Background. Preserving connectivity, or the ability of a landscape to support species movement, is among the most commonly recommended strategies to reduce the negative effects of climate change and human land use development on species. Connectivity analyses have traditionally used a corridor-based approach and rely heavily on least cost path modeling and circuit theory to delineate corridors. Individual-based models are gaining popularity as a potentially more ecologically realistic method of estimating landscape connectivity. However, this remains a relatively unexplored approach. We sought to explore the utility of a simple, individual-based model as a land-use management support tool in identifying and implementing landscape connectivity. Methods. We created an individual-based model of bighorn sheep (Ovis canadensis) that simulates a bighorn sheep traversing a landscape by following simple movement rules. The model was calibrated for bighorn sheep in the Okanagan Valley, British Columbia, Canada, a region containing isolated herds that are vital to conservation of the species in its northern range. Simulations were run to determine baseline connectivity between subpopulations in the study area. We then applied the model to explore two land management scenarios on simulated connectivity: restoring natural fire regimes and identifying appropriate sites for interventions that would increase road permeability for bighorn sheep. Results. This model suggests there are no continuous areas of good habitat between current subpopulations of sheep in the study area; however, a series of stepping-stones or circuitous routes could facilitate movement between subpopulations and into currently unoccupied, yet suitable, bighorn habitat. Restoring natural fire regimes or mimicking fire with prescribed burns and tree removal could considerably increase bighorn connectivity in this area. Moreover, several key road crossing sites that could benefit from wildlife overpasses were identified. Discussion. By linking individual-scale movement rules to landscape-scale outcomes, our individual-based model of bighorn sheep allows for the exploration of how on-the-ground management or conservation scenarios may increase functional connectivity for the species in the study area. More generally, this study highlights the usefulness of individual-based models to identify how a species makes broad use of a landscape for movement. Application of this approach can provide effective quantitative support for decision makers seeking to incorporate wildlife conservation and connectivity into land use planning.

An individual-based modelling approach to estimate landscape connectivity for bighorn sheep (Ovis canadensis)

PubMed Central

Allen, Corrie H.; Kyle, Catherine

2016-01-01

Background. Preserving connectivity, or the ability of a landscape to support species movement, is among the most commonly recommended strategies to reduce the negative effects of climate change and human land use development on species. Connectivity analyses have traditionally used a corridor-based approach and rely heavily on least cost path modeling and circuit theory to delineate corridors. Individual-based models are gaining popularity as a potentially more ecologically realistic method of estimating landscape connectivity. However, this remains a relatively unexplored approach. We sought to explore the utility of a simple, individual-based model as a land-use management support tool in identifying and implementing landscape connectivity. Methods. We created an individual-based model of bighorn sheep (Ovis canadensis) that simulates a bighorn sheep traversing a landscape by following simple movement rules. The model was calibrated for bighorn sheep in the Okanagan Valley, British Columbia, Canada, a region containing isolated herds that are vital to conservation of the species in its northern range. Simulations were run to determine baseline connectivity between subpopulations in the study area. We then applied the model to explore two land management scenarios on simulated connectivity: restoring natural fire regimes and identifying appropriate sites for interventions that would increase road permeability for bighorn sheep. Results. This model suggests there are no continuous areas of good habitat between current subpopulations of sheep in the study area; however, a series of stepping-stones or circuitous routes could facilitate movement between subpopulations and into currently unoccupied, yet suitable, bighorn habitat. Restoring natural fire regimes or mimicking fire with prescribed burns and tree removal could considerably increase bighorn connectivity in this area. Moreover, several key road crossing sites that could benefit from wildlife overpasses were identified. Discussion. By linking individual-scale movement rules to landscape-scale outcomes, our individual-based model of bighorn sheep allows for the exploration of how on-the-ground management or conservation scenarios may increase functional connectivity for the species in the study area. More generally, this study highlights the usefulness of individual-based models to identify how a species makes broad use of a landscape for movement. Application of this approach can provide effective quantitative support for decision makers seeking to incorporate wildlife conservation and connectivity into land use planning. PMID:27168997

Incorporating Land-Use Mapping Uncertainty in Remote Sensing Based Calibration of Land-Use Change Models

NASA Astrophysics Data System (ADS)

Cockx, K.; Van de Voorde, T.; Canters, F.; Poelmans, L.; Uljee, I.; Engelen, G.; de Jong, K.; Karssenberg, D.; van der Kwast, J.

2013-05-01

Building urban growth models typically involves a process of historic calibration based on historic time series of land-use maps, usually obtained from satellite imagery. Both the remote sensing data analysis to infer land use and the subsequent modelling of land-use change are subject to uncertainties, which may have an impact on the accuracy of future land-use predictions. Our research aims to quantify and reduce these uncertainties by means of a particle filter data assimilation approach that incorporates uncertainty in land-use mapping and land-use model parameter assessment into the calibration process. This paper focuses on part of this work, more in particular the modelling of uncertainties associated with the impervious surface cover estimation and urban land-use classification adopted in the land-use mapping approach. Both stages are submitted to a Monte Carlo simulation to assess their relative contribution to and their combined impact on the uncertainty in the derived land-use maps. The approach was applied on the central part of the Flanders region (Belgium), using a time-series of Landsat/SPOT-HRV data covering the years 1987, 1996, 2005 and 2012. Although the most likely land-use map obtained from the simulation is very similar to the original classification, it is shown that the errors related to the impervious surface sub-pixel fraction estimation have a strong impact on the land-use map's uncertainty. Hence, incorporating uncertainty in the land-use change model calibration through particle filter data assimilation is proposed to address the uncertainty observed in the derived land-use maps and to reduce uncertainty in future land-use predictions.

Understanding Decreases in Land Relative Humidity with Global Warming: Conceptual Model and GCM Simulations

NASA Astrophysics Data System (ADS)

Byrne, Michael P.; O'Gorman, Paul A.

2016-12-01

Climate models simulate a strong land-ocean contrast in the response of near-surface relative humidity to global warming: relative humidity tends to increase slightly over oceans but decrease substantially over land. Surface energy balance arguments have been used to understand the response over ocean but are difficult to apply over more complex land surfaces. Here, a conceptual box model is introduced, involving moisture transport between the land and ocean boundary layers and evapotranspiration, to investigate the decreases in land relative humidity as the climate warms. The box model is applied to idealized and full-complexity (CMIP5) general circulation model simulations, and it is found to capture many of the features of the simulated changes in land relative humidity. The box model suggests there is a strong link between fractional changes in specific humidity over land and ocean, and the greater warming over land than ocean then implies a decrease in land relative humidity. Evapotranspiration is of secondary importance for the increase in specific humidity over land, but it matters more for the decrease in relative humidity. Further analysis shows there is a strong feedback between changes in surface-air temperature and relative humidity, and this can amplify the influence on relative humidity of factors such as stomatal conductance and soil moisture.

Land Use, climate change and BIOdiversity in cultural landscapes (LUBIO): Assessing feedbacks and promoting land-use strategies towards a viable future

NASA Astrophysics Data System (ADS)

Dullinger, Iwona; Bohner, Andreas; Dullinger, Stefan; Essl, Franz; Gaube, Veronika; Haberl, Helmut; Mayer, Andreas; Plutzar, Christoph; Remesch, Alexander

2016-04-01

Land-use and climate change are important, pervasive drivers of global environmental change and pose major threats to global biodiversity. Research to date has mostly focused either on land-use change or on climate change, but rarely on the interactions between both drivers, even though it is expected that systemic feedbacks between changes in climate and land use will have important effects on biodiversity. In particular, climate change will not only alter the pool of plant and animal species capable of thriving in a specific area, it will also force land owners to reconsider their land use decisions. Such changes in land-use practices may have major additional effects on local and regional species composition and abundance. In LUBIO, we will explore the anticipated systemic feedbacks between (1) climate change, (2) land owner's decisions on land use, (3) land-use change, and (4) changes in biodiversity patterns during the coming decades in a regional context which integrates a broad range of land use practices and intensity gradients. To achieve this goal, an integrated socioecological model will be designed and implemented, consisting of three principal components: (1) an agent based model (ABM) that simulates decisions of important actors, (2) a spatially explicit GIS model that translates these decisions into changes in land cover and land use patterns, and (3) a species distribution model (SDM) that calculates changes in biodiversity patterns following from both changes in climate and the land use decisions as simulated in the ABM. Upon integration of these three components, the coupled socioecological model will be used to generate scenarios of future land-use decisions of landowners under climate change and, eventually, the combined effects of climate and land use changes on biodiversity. Model development of the ABM will be supported by a participatory process intended to collect regional and expert knowledge through a series of expert interviews, a series of transdisciplinary participatory modelling workshops, and a questionnaire-based survey targeted at regional farmers. Beside the integrated socioecological model a catalogue of recommended actions will be developed in order to distribute the insights of the research to the most relevant regional stakeholder groups.

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.

Ten-year history of an Oregon coastal plantation.

Treesearch

Robert H. Ruth

1957-01-01

Very productive forest land, capable of producing 1,000 to 1,500 board-feet of softwood per acre per year, is common in the "fog belt" along the Oregon Coast. Good forest management requires that this valuable land be kept in constant production with minimum time lost during the regeneration period. Also, if the land is to be managed for conifer production,...

Differences in forest plant functional trait distributions across land-use and productivity gradients

Treesearch

Margaret M. Mayfield; John M. Dwyer; Loic Chalmandrier; Jessie A. Wells; Stephen P. Bonser; Carla P. Catterall; Fabrice DeClerck; Yi Ding; Jennifer M. Fraterrigo; Daniel J. Metcalfe; Cibele Queiroz; Peter A. Vesk; John W. Morgan

2013-01-01

• Premise of study: Plant functional traits are commonly used as proxies for plant responses to environmental challenges, yet few studies have explored how functional trait distributions differ across gradients of land-use change. By comparing trait distributions in intact forests with those across land-use change gradients, we can improve our understanding of the ways...

A global assessment of gross and net land change dynamics for current conditions and future scenarios

NASA Astrophysics Data System (ADS)

Fuchs, Richard; Prestele, Reinhard; Verburg, Peter H.

2018-05-01

The consideration of gross land changes, meaning all area gains and losses within a pixel or administrative unit (e.g. country), plays an essential role in the estimation of total land changes. Gross land changes affect the magnitude of total land changes, which feeds back to the attribution of biogeochemical and biophysical processes related to climate change in Earth system models. Global empirical studies on gross land changes are currently lacking. Whilst the relevance of gross changes for global change has been indicated in the literature, it is not accounted for in future land change scenarios. In this study, we extract gross and net land change dynamics from large-scale and high-resolution (30-100 m) remote sensing products to create a new global gross and net change dataset. Subsequently, we developed an approach to integrate our empirically derived gross and net changes with the results of future simulation models by accounting for the gross and net change addressed by the land use model and the gross and net change that is below the resolution of modelling. Based on our empirical data, we found that gross land change within 0.5° grid cells was substantially larger than net changes in all parts of the world. As 0.5° grid cells are a standard resolution of Earth system models, this leads to an underestimation of the amount of change. This finding contradicts earlier studies, which assumed gross land changes to appear in shifting cultivation areas only. Applied in a future scenario, the consideration of gross land changes led to approximately 50 % more land changes globally compared to a net land change representation. Gross land changes were most important in heterogeneous land systems with multiple land uses (e.g. shifting cultivation, smallholder farming, and agro-forestry systems). Moreover, the importance of gross changes decreased over time due to further polarization and intensification of land use. Our results serve as an empirical database for land change dynamics that can be applied in Earth system models and integrated assessment models.

Bio-Optics of the Chesapeake Bay from Measurements and Radiative Transfer Calculations

NASA Technical Reports Server (NTRS)

Tzortziou, Maria; Herman, Jay R.; Gallegos, Charles L.; Neale, Patrick J.; Subramaniam, Ajit; Harding, Lawrence W., Jr.; Ahmad, Ziauddin

2005-01-01

We combined detailed bio-optical measurements and radiative transfer (RT) modeling to perform an optical closure experiment for optically complex and biologically productive Chesapeake Bay waters. We used this experiment to evaluate certain assumptions commonly used when modeling bio-optical processes, and to investigate the relative importance of several optical characteristics needed to accurately model and interpret remote sensing ocean-color observations in these Case 2 waters. Direct measurements were made of the magnitude, variability, and spectral characteristics of backscattering and absorption that are critical for accurate parameterizations in satellite bio-optical algorithms and underwater RT simulations. We found that the ratio of backscattering to total scattering in the mid-mesohaline Chesapeake Bay varied considerably depending on particulate loading, distance from land, and mixing processes, and had an average value of 0.0128 at 530 nm. Incorporating information on the magnitude, variability, and spectral characteristics of particulate backscattering into the RT model, rather than using a volume scattering function commonly assumed for turbid waters, was critical to obtaining agreement between RT calculations and measured radiometric quantities. In situ measurements of absorption coefficients need to be corrected for systematic overestimation due to scattering errors, and this correction commonly employs the assumption that absorption by particulate matter at near infrared wavelengths is zero.

Landing Characteristics in Waves of Three Dynamic Models of Flying Boats

NASA Technical Reports Server (NTRS)

Benson, James M.; Havens, Robert F.; Woodward, David R.

1947-01-01

Powered models of three different flying boats were landed in oncoming wave of various heights and lengths. The resulting motions and acceleration were recorded to survey the effects of varying the trim at landing, the deceleration after landing, and the size of the waves. One of the models had an unusually long afterbody. The data for landing with normal rates of deceleration indicated that the most severe motions and accelerations were likely to occur at some period of the landing run subsequent to the initial impact. Landings made at abnormally low trims led to unusually severe bounces during the runout. The least severe landing occurred after a small lending when the model was rapidly decelerated at about 0.4 g in a simulation of the proposed use of braking devices. The severity of the landings increased with wave height and was at a maximum when the wave length was of the order of from one and one-half to twice the over-all length of the model. The models with afterbodies of moderate length frequently bounced clear of the water into a stalled attitude at speeds below flying speed. The model with the long afterbody had less tendency to bounce from the waves and consequently showed less severe accelerations during the landing run than the models with moderate lengths of afterbody.

The Land Use and Land Cover Dichotomy: A Comparison of Two Land Classification Systems in Support of Urban Earth Science Applications

NASA Technical Reports Server (NTRS)

McAllister, William K.

2003-01-01

One is likely to read the terms 'land use' and 'land cover' in the same sentence, yet these concepts have different origins and different applications. Land cover is typically analyzed by earth scientists working with remotely sensed images. Land use is typically studied by urban planners who must prescribe solutions that could prevent future problems. This apparent dichotomy has led to different classification systems for land-based data. The works of earth scientists and urban planning practitioners are beginning to come together in the field of spatial analysis and in their common use of new spatial analysis technology. In this context, the technology can stimulate a common 'language' that allows a broader sharing of ideas. The increasing amount of land use and land cover change challenges the various efforts to classify in ways that are efficient, effective, and agreeable to all groups of users. If land cover and land uses can be identified by remote methods using aerial photography and satellites, then these ways are more efficient than field surveys of the same area. New technology, such as high-resolution satellite sensors, and new methods, such as more refined algorithms for image interpretation, are providing refined data to better identify the actual cover and apparent use of land, thus effectiveness is improved. However, the closer together and the more vertical the land uses are, the more difficult the task of identification is, and the greater is the need to supplement remotely sensed data with field study (in situ). Thus, a number of land classification methods were developed in order to organize the greatly expanding volume of data on land characteristics in ways useful to different groups. This paper distinguishes two land based classification systems, one developed primarily for remotely sensed data, and the other, a more comprehensive system requiring in situ collection methods. The intent is to look at how the two systems developed and how they can work together so that land based information can be shared among different users and compared over time.

Development of a prototype land use model for statewide transportation planning activities.

DOT National Transportation Integrated Search

2011-11-30

Future land use forecasting is an important input to transportation planning modeling. Traditionally, land use is allocated to individual : traffic analysis zones (TAZ) based on variables such as the amount of vacant land, zoning restriction, land us...

integrated Earth System Model

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

Jones, Andew; Di Vittorio, Alan; Collins, William

The integrated Earth system model (iESM) has been developed as a new tool for projecting the joint human/climate system. The iESM is based upon coupling an integrated assessment model (IAM) and an Earth system model (ESM) into a common modeling infrastructure. IAMs are the primary tool for describing the human-Earth system, including the sources of global greenhouse gases (GHGs) and short-lived species (SLS), land use and land cover change (LULCC), and other resource-related drivers of anthropogenic climate change. ESMs are the primary scientific tools for examining the physical, chemical, and biogeochemical impacts of human-induced changes to the climate system. Themore » iESM project integrates the economic and human-dimension modeling of an IAM and a fully coupled ESM within a single simulation system while maintaining the separability of each model if needed. Both IAM and ESM codes are developed and used by large communities and have been extensively applied in recent national and international climate assessments. By introducing heretofore-omitted feedbacks between natural and societal drivers, we can improve scientific understanding of the human-Earth system dynamics. Potential applications include studies of the interactions and feedbacks leading to the timing, scale, and geographic distribution of emissions trajectories and other human influences, corresponding climate effects, and the subsequent impacts of a changing climate on human and natural systems.« less

Modelling land use change with generalized linear models--a multi-model analysis of change between 1860 and 2000 in Gallatin Valley, Montana.

PubMed

Aspinall, Richard

2004-08-01

This paper develops an approach to modelling land use change that links model selection and multi-model inference with empirical models and GIS. Land use change is frequently studied, and understanding gained, through a process of modelling that is an empirical analysis of documented changes in land cover or land use patterns. The approach here is based on analysis and comparison of multiple models of land use patterns using model selection and multi-model inference. The approach is illustrated with a case study of rural housing as it has developed for part of Gallatin County, Montana, USA. A GIS contains the location of rural housing on a yearly basis from 1860 to 2000. The database also documents a variety of environmental and socio-economic conditions. A general model of settlement development describes the evolution of drivers of land use change and their impacts in the region. This model is used to develop a series of different models reflecting drivers of change at different periods in the history of the study area. These period specific models represent a series of multiple working hypotheses describing (a) the effects of spatial variables as a representation of social, economic and environmental drivers of land use change, and (b) temporal changes in the effects of the spatial variables as the drivers of change evolve over time. Logistic regression is used to calibrate and interpret these models and the models are then compared and evaluated with model selection techniques. Results show that different models are 'best' for the different periods. The different models for different periods demonstrate that models are not invariant over time which presents challenges for validation and testing of empirical models. The research demonstrates (i) model selection as a mechanism for rating among many plausible models that describe land cover or land use patterns, (ii) inference from a set of models rather than from a single model, (iii) that models can be developed based on hypothesised relationships based on consideration of underlying and proximate causes of change, and (iv) that models are not invariant over time.

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 climate and carbon cycle impacts of CMIP6 Land Use and Land Cover Change in the Community Earth System Model (CESM2)

NASA Astrophysics Data System (ADS)

Lawrence, P.; Lawrence, D. M.; O'Neill, B. C.; Hurtt, G. C.

2017-12-01

For the next round of CMIP6 climate simulations there are new historical and SSP - RCP land use and land cover change (LULCC) data sets that have been compiled through the Land Use Model Intercomparison Project (LUMIP). The new time series data include new functionality following lessons learned through CMIP5 project and include new developments in the Community Land Model (CLM5) that will be used in all the CESM2 simulations of CMIP6. These changes include representing explicit crop modeling and better forest representation through the extended to 12 land units of the Global Land Model (GLM). To include this new information in CESM2 and CLM5 simulations new transient land surface data sets have been generated for the historical period 1850 - 2015 and for preliminary SSP - RCP paired future scenarios. The new data sets use updated MODIS Land Cover, Vegetation Continuous Fields, Leaf Area Index and Albedo to describe Primary and Secondary, Forested and Non Forested land units, as well as Rangelands and Pasture. Current day crop distributions are taken from the MIRCA2000 crop data set as done with the CLM 4.5 crop model and used to guide historical and future crop distributions. Preliminary "land only" simulations with CLM5 have been performed for the historical period and for the SSP1-RCP2.6 and SSP3-RCP7 land use and land cover change time series data. Equivalent no land use and land cover change simulations have been run for these periods under the same meteorological forcing data. The "land only" simulations use GSWP3 historical atmospheric forcing data from 1850 to 2010 and then time increasing RCP 8.5 atmospheric CO2 and climate anomalies on top of the current day GSWP3 atmospheric forcing data from 2011 to 2100. The offline simulations provide a basis to evaluate the surface climate, carbon cycle and crop production impacts of changing land use and land cover for each of these periods. To further evaluate the impacts of the new CLM5 model and the CMIP6 land use data, these results are compared to the equivalent investigations performed in CMIP5 with the CLM4/CESM1 model. We find the role of land use and land cover change in a changing climate is strongly dependent on both of these.

What are the effects of Agro-Ecological Zones and land use region boundaries on land resource projection using the Global Change Assessment Model?

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

Di Vittorio, Alan V.; Kyle, Page; Collins, William D.

Understanding potential impacts of climate change is complicated by spatially mismatched land representations between gridded datasets and models, and land use models with larger regions defined by geopolitical and/or biophysical criteria. Here in this study, we quantify the sensitivity of Global Change Assessment Model (GCAM) outputs to the delineation of Agro-Ecological Zones (AEZs), which are normally based on historical (1961–1990) climate. We reconstruct GCAM's land regions using projected (2071–2100) climate, and find large differences in estimated future land use that correspond with differences in agricultural commodity prices and production volumes. Importantly, historically delineated AEZs experience spatially heterogeneous climate impacts overmore » time, and do not necessarily provide more homogenous initial land productivity than projected AEZs. Finally, we conclude that non-climatic criteria for land use region delineation are likely preferable for modeling land use change in the context of climate change, and that uncertainty associated with land delineation needs to be quantified.« less

Impact of high resolution land surface initialization in Indian summer monsoon simulation using a regional climate model

NASA Astrophysics Data System (ADS)

Unnikrishnan, C. K.; Rajeevan, M.; Rao, S. Vijaya Bhaskara

2016-06-01

The direct impact of high resolution land surface initialization on the forecast bias in a regional climate model in recent years over Indian summer monsoon region is investigated. Two sets of regional climate model simulations are performed, one with a coarse resolution land surface initial conditions and second one used a high resolution land surface data for initial condition. The results show that all monsoon years respond differently to the high resolution land surface initialization. The drought monsoon year 2009 and extended break periods were more sensitive to the high resolution land surface initialization. These results suggest that the drought monsoon year predictions can be improved with high resolution land surface initialization. Result also shows that there are differences in the response to the land surface initialization within the monsoon season. Case studies of heat wave and a monsoon depression simulation show that, the model biases were also improved with high resolution land surface initialization. These results show the need for a better land surface initialization strategy in high resolution regional models for monsoon forecasting.

What are the effects of Agro-Ecological Zones and land use region boundaries on land resource projection using the Global Change Assessment Model?

DOE PAGES

Di Vittorio, Alan V.; Kyle, Page; Collins, William D.

2016-09-03

Understanding potential impacts of climate change is complicated by spatially mismatched land representations between gridded datasets and models, and land use models with larger regions defined by geopolitical and/or biophysical criteria. Here in this study, we quantify the sensitivity of Global Change Assessment Model (GCAM) outputs to the delineation of Agro-Ecological Zones (AEZs), which are normally based on historical (1961–1990) climate. We reconstruct GCAM's land regions using projected (2071–2100) climate, and find large differences in estimated future land use that correspond with differences in agricultural commodity prices and production volumes. Importantly, historically delineated AEZs experience spatially heterogeneous climate impacts overmore » time, and do not necessarily provide more homogenous initial land productivity than projected AEZs. Finally, we conclude that non-climatic criteria for land use region delineation are likely preferable for modeling land use change in the context of climate change, and that uncertainty associated with land delineation needs to be quantified.« less

Pelvic Floor Dynamics During High-Impact Athletic Activities: A Computational Modeling Study

PubMed Central

Dias, Nicholas; Peng, Yun; Khavari, Rose; Nakib, Nissrine A.; Sweet, Robert M.; Timm, Gerald W.; Erdman, Arthur G.; Boone, Timothy B.

2017-01-01

Background Stress urinary incontinence is a significant problem in young female athletes, but the pathophysiology remains unclear because of the limited knowledge of the pelvic floor support function and limited capability of currently available assessment tools. The aim of our study is to develop an advanced computer modeling tool to better understand the dynamics of the internal pelvic floor during highly transient athletic activities. Methods Apelvic model was developed based on high-resolution MRI scans of a healthy nulliparous young female. A jump-landing process was simulated using realistic boundary conditions captured from jumping experiments. Hypothesized alterations of the function of pelvic floor muscles were simulated by weakening or strengthening the levator ani muscle stiffness at different levels. Intra-abdominal pressures and corresponding deformations of pelvic floor structures were monitored at different levels of weakness or enhancement. Findings Results show that pelvic floor deformations generated during a jump-landing process differed greatly from those seen in a Valsalva maneuver which is commonly used for diagnosis in clinic. The urethral mobility was only slightly influenced by the alterations of the levator ani muscle stiffness. Implications for risk factors and treatment strategies were also discussed. Interpretation Results suggest that clinical diagnosis should make allowances for observed differences in pelvic floor deformations between a Valsalva maneuver and a jump-landing process to ensure accuracy. Urethral hypermobility may be a less contributing factor than the intrinsic sphincteric closure system to the incontinence of young female athletes. PMID:27886590

Estimating Demand for Industrial and Commercial Land Use Given Economic Forecasts

PubMed Central

Batista e Silva, Filipe; Koomen, Eric; Diogo, Vasco; Lavalle, Carlo

2014-01-01

Current developments in the field of land use modelling point towards greater level of spatial and thematic resolution and the possibility to model large geographical extents. Improvements are taking place as computational capabilities increase and socioeconomic and environmental data are produced with sufficient detail. Integrated approaches to land use modelling rely on the development of interfaces with specialized models from fields like economy, hydrology, and agriculture. Impact assessment of scenarios/policies at various geographical scales can particularly benefit from these advances. A comprehensive land use modelling framework includes necessarily both the estimation of the quantity and the spatial allocation of land uses within a given timeframe. In this paper, we seek to establish straightforward methods to estimate demand for industrial and commercial land uses that can be used in the context of land use modelling, in particular for applications at continental scale, where the unavailability of data is often a major constraint. We propose a set of approaches based on ‘land use intensity’ measures indicating the amount of economic output per existing areal unit of land use. A base model was designed to estimate land demand based on regional-specific land use intensities; in addition, variants accounting for sectoral differences in land use intensity were introduced. A validation was carried out for a set of European countries by estimating land use for 2006 and comparing it to observations. The models’ results were compared with estimations generated using the ‘null model’ (no land use change) and simple trend extrapolations. Results indicate that the proposed approaches clearly outperformed the ‘null model’, but did not consistently outperform the linear extrapolation. An uncertainty analysis further revealed that the models’ performances are particularly sensitive to the quality of the input land use data. In addition, unknown future trends of regional land use intensity widen considerably the uncertainty bands of the predictions. PMID:24647587

Comparison of two perturbation methods to estimate the land surface modeling uncertainty

NASA Astrophysics Data System (ADS)

Su, H.; Houser, P.; Tian, Y.; Kumar, S.; Geiger, J.; Belvedere, D.

2007-12-01

In land surface modeling, it is almost impossible to simulate the land surface processes without any error because the earth system is highly complex and the physics of the land processes has not yet been understood sufficiently. In most cases, people want to know not only the model output but also the uncertainty in the modeling, to estimate how reliable the modeling is. Ensemble perturbation is an effective way to estimate the uncertainty in land surface modeling, since land surface models are highly nonlinear which makes the analytical approach not applicable in this estimation. The ideal perturbation noise is zero mean Gaussian distribution, however, this requirement can't be satisfied if the perturbed variables in land surface model have physical boundaries because part of the perturbation noises has to be removed to feed the land surface models properly. Two different perturbation methods are employed in our study to investigate their impact on quantifying land surface modeling uncertainty base on the Land Information System (LIS) framework developed by NASA/GSFC land team. One perturbation method is the built-in algorithm named "STATIC" in LIS version 5; the other is a new perturbation algorithm which was recently developed to minimize the overall bias in the perturbation by incorporating additional information from the whole time series for the perturbed variable. The statistical properties of the perturbation noise generated by the two different algorithms are investigated thoroughly by using a large ensemble size on a NASA supercomputer and then the corresponding uncertainty estimates based on the two perturbation methods are compared. Their further impacts on data assimilation are also discussed. Finally, an optimal perturbation method is suggested.

Numerical simulation of earth fissures caused by overly aquifer exploitation at Guangming Village, China

NASA Astrophysics Data System (ADS)

Ye, S.; Franceschini, A.; Zhang, Y.; Janna, C.; Gong, X.; Yu, J.; Teatini, P.

2017-12-01

Earth fissures accompanying anthropogenic land subsidence due to overly aquifer exploitation create significant geohazards in China. In the framework of an efficient and safe management of groundwater, numerical models represent a unique scientific approach to predict the generation and development of earth fissures. However, the common geomechanical simulators fail to reproduce fissure development because, due to compatibility conditions, they cannot be effectively applied in discontinuous mechanics. We present an innovative modelling approach for the simulation of fissure development. Firstly, a regional 3D groundwater model is calibrated on available piezometric records; secondly, the regional outcome is used to define the boundary conditions of a local 3D groundwater model developed at the fissure scale and implementing a refined discretization of the local hydrogeologic setting; finally, the pressure change are used as forcing factor in a local 3D geomechanical model, which combines Finite Elements and Interface Elements to simulate the deformation of the continuous aquifer system and the generation and sliding/opening of earth fissures The approach has been applied to simulate the earth fissure at Guangming Village in Wuxi, China with land subsidence of more than 1 m caused by the overexploitation of the second confined aquifer. The first earth fissure was observed in 1998. It developed fast from 1998 to 2007. The domain addressed by the local simulations is 2 km wide and 5 km long. The thickness of the aquifer system ranges from 0 m, in the proximity of a mountain ridge southward, to 210 m northward and includes a phreatic aquifer, the first and second confined aquifers, and four aquitards. The simulations spanned the period from 1980, i.e. before the inception of large groundwater withdrawals, to 2015. The modelling results highlight that the earth fissures at Guangming Village have been caused by tension and shear, which developed from the land surface downward. The main factors contributing to fissure generation include the shallow bedrock with a sharp ridge, the asymmetric shape of ridge, the uneven thickness of the sedimentary deposits at the west and east side of the buried ridge together with a different pressure change that have been responsible for differential land subsidence.

Assessing Regional-Scale Impacts of Short Rotation Coppices on Ecosystem Services by Modeling Land-Use Decisions.

PubMed

Schulze, Jule; Frank, Karin; Priess, Joerg A; Meyer, Markus A

2016-01-01

Meeting the world's growing energy demand through bioenergy production involves extensive land-use change which could have severe environmental and social impacts. Second generation bioenergy feedstocks offer a possible solution to this problem. They have the potential to reduce land-use conflicts between food and bioenergy production as they can be grown on low quality land not suitable for food production. However, a comprehensive impact assessment that considers multiple ecosystem services (ESS) and biodiversity is needed to identify the environmentally best feedstock option, as trade-offs are inherent. In this study, we simulate the spatial distribution of short rotation coppices (SRCs) in the landscape of the Mulde watershed in Central Germany by modeling profit-maximizing farmers under different economic and policy-driven scenarios using a spatially explicit economic simulation model. This allows to derive general insights and a mechanistic understanding of regional-scale impacts on multiple ESS in the absence of large-scale implementation. The modeled distribution of SRCs, required to meet the regional demand of combined heat and power (CHP) plants for solid biomass, had little or no effect on the provided ESS. In the policy-driven scenario, placing SRCs on low or high quality soils to provide ecological focus areas, as required within the Common Agricultural Policy in the EU, had little effect on ESS. Only a substantial increase in the SRC production area, beyond the regional demand of CHP plants, had a relevant effect, namely a negative impact on food production as well as a positive impact on biodiversity and regulating ESS. Beneficial impacts occurred for single ESS. However, the number of sites with balanced ESS supply hardly increased due to larger shares of SRCs in the landscape. Regression analyses showed that the occurrence of sites with balanced ESS supply was more strongly driven by biophysical factors than by the SRC share in the landscape. This indicates that SRCs negligibly affect trade-offs between individual ESS. Coupling spatially explicit economic simulation models with environmental and ESS assessment models can contribute to a comprehensive impact assessment of bioenergy feedstocks that have not yet been planted.

Multi-criteria decision analysis using hydrological indicators for decision support - a conceptual framework.

NASA Astrophysics Data System (ADS)

Butchart-Kuhlmann, Daniel; Kralisch, Sven; Meinhardt, Markus; Fleischer, Melanie

2017-04-01

Assessing the quantity and quality of water available in water stressed environments under various potential climate and land-use changes is necessary for good water and environmental resources management and governance. Within the region covered by the Southern African Science Service Centre for Climate Change and Adaptive Land Management (SASSCAL) project, such areas are common. One goal of the SASSCAL project is to develop and provide an integrated decision support system (DSS) with which decision makers (DMs) within a given catchment can obtain objective information regarding potential changes in water flow quantity and timing. The SASSCAL DSS builds upon existing data storage and distribution capability, through the SASSCAL Information System (IS), as well as the J2000 hydrological model. Using output from validated J2000 models, the SASSCAL DSS incorporates the calculation of a range of hydrological indicators based upon Indicators of Hydrological Alteration/Environmental Flow Components (IHA/EFC) calculated for a historic time series (pre-impact) and a set of model simulations based upon a selection of possible climate and land-use change scenarios (post-impact). These indicators, obtained using the IHA software package, are then used as input for a multi-criteria decision analysis (MCDA) undertaken using the open source diviz software package. The results of these analyses will provide DMs with an indication as to how various hydrological indicators within a catchment may be altered under different future scenarios, as well providing a ranking of how each scenario is preferred according to different DM preferences. Scenarios are represented through a combination of model input data and parameter settings in J2000, and preferences are represented through criteria weighting in the MCDA. Here, the methodology is presented and applied to the J2000 Luanginga model results using a set of hypothetical decision maker preference values as input for an MCDA based on the PROMETHEE II outranking method. Future work on the SASSCAL DSS will entail automation of this process, as well as its application to other hydrological models and land-use and/or climate change scenarios.

Assessing Regional-Scale Impacts of Short Rotation Coppices on Ecosystem Services by Modeling Land-Use Decisions

PubMed Central

Schulze, Jule; Frank, Karin; Priess, Joerg A.; Meyer, Markus A.

2016-01-01

Meeting the world’s growing energy demand through bioenergy production involves extensive land-use change which could have severe environmental and social impacts. Second generation bioenergy feedstocks offer a possible solution to this problem. They have the potential to reduce land-use conflicts between food and bioenergy production as they can be grown on low quality land not suitable for food production. However, a comprehensive impact assessment that considers multiple ecosystem services (ESS) and biodiversity is needed to identify the environmentally best feedstock option, as trade-offs are inherent. In this study, we simulate the spatial distribution of short rotation coppices (SRCs) in the landscape of the Mulde watershed in Central Germany by modeling profit-maximizing farmers under different economic and policy-driven scenarios using a spatially explicit economic simulation model. This allows to derive general insights and a mechanistic understanding of regional-scale impacts on multiple ESS in the absence of large-scale implementation. The modeled distribution of SRCs, required to meet the regional demand of combined heat and power (CHP) plants for solid biomass, had little or no effect on the provided ESS. In the policy-driven scenario, placing SRCs on low or high quality soils to provide ecological focus areas, as required within the Common Agricultural Policy in the EU, had little effect on ESS. Only a substantial increase in the SRC production area, beyond the regional demand of CHP plants, had a relevant effect, namely a negative impact on food production as well as a positive impact on biodiversity and regulating ESS. Beneficial impacts occurred for single ESS. However, the number of sites with balanced ESS supply hardly increased due to larger shares of SRCs in the landscape. Regression analyses showed that the occurrence of sites with balanced ESS supply was more strongly driven by biophysical factors than by the SRC share in the landscape. This indicates that SRCs negligibly affect trade-offs between individual ESS. Coupling spatially explicit economic simulation models with environmental and ESS assessment models can contribute to a comprehensive impact assessment of bioenergy feedstocks that have not yet been planted. PMID:27082742

Environmental Sensitive Areas (ESAs) changes in the Canyoles river watershed in Eastern Spain since the European Common Agriculture Policies (CAP) implementation

NASA Astrophysics Data System (ADS)

Ángel González Peñaloza, Félix; Cerdà, Artemi

2014-05-01

The Enviromental Sensitive Areas (ESAs) approach to study the Land Degradation is a methodology developed by professor Costas Kosmas et al., (1999) to map environmental sensitive areas and then the impact of Land Degradation and desertification on Mediterranean Type Ecosystems (Salvati et al., 2013). This methodology has been applied mainly to the Mediterranean Belt (Lavado Contador et al., 2009), but other authors adapted the methodology to other climatic regions (Izzo et al., 2013). The ESAs methodology allows mapping changes in the distribution of the sensitive areas to Desertification as a consequence of biophysical or human chances. In the Mediterranean countries of Europe, especially Spain, suffered a dramatic change due to the application of the European Common Agricultural Policies (CAP) after 1992. The objective of the CAP was to implemented policies to improve the environmental conditions of agricultural land. This target is especially relevant in Mediterranean areas of Spain, mainly the South and the East of the country. An Environmental Sensitive Area (ESAs) model (Kosmas et al., 2009) was implemented using Geographical Information System (GIS) tools, to identify, assess, monitor and map the levels of sensitivity to land degradation in the Canyoles river watershed, which is a representative landscape of the Mediterranean belt in Eastern Spain The results show that it was found that after the implementation of CAP, the most sensitive areas have expanded. This increase in degraded areas is driven by the expansion of commercial and chemically managed crops that increased the soil erosion (Cerdà et al., 2009) and that few soil conservation strategies were applied (Giménez Morera et al., 2010). Another factor that triggered Desertification processes is the increase in the recurrencesof forest fires as a consequence of land abandonment (Cerdà and Lasanta, 2005; Cerdà and Doerr, 2007). This contributed to an increase of scrubland. Our research show an increase in the rangeland vegetation that is dominated by scrubland, meanwhile the woodlands are reduced. Circa 50 % of the land that was classified as "Critical" to land degradation after 1985 had been previously classified as "Non-affected". However, not all changes occurred in the Cànyoles watershed are characterized by a negative change; i.e., 82 % of the land has turned from "Critical" values to "Non- sensitive" to land degradation between mid-20th century and recent times. We found this negative trend to be having been caused by the removal of those crops that are most sensitive to land degradation, such as rain-fed crops, and that are mainly located in the west of the studied watershed. Similar findings were found by Zema et al., (2012) when applying the AnnAGNPS model to the agriculture land in Belgiums, Prokop and Poreba (2012) to the India, Miao e t al., (2012) in China and Haile and Fetene (2012) in Ethiopia: man made changes in the landscape that trigger land degradation processes.. Acknowledgements This research was undertaken in the frame of the 7FP project LEDDRA - Land Ecosystem Degradation and Desertification: Assessing the Fit of Responses - ENV, 2009.2.1.3.2. We thank professor Costas Kosmas for his guidance. References Cerdà, A., Doerr, S.H. 2007. Soil wettability, runoff and erodibility of major dry-Mediterranean land use types on calcareous soils. Hydrological Processes, 21, 2325-2336. doi: 10.1016/j.catena.2008.03.010. Cerdà, A., Giménez-Morera, A. y Bodí, M.B. 2009. Soil and water losses from new citrus orchards growing on sloped soils in the western Mediterranean basin. Earth Surface Processes and Landforms, 34, 1822-1830. DOI: 10.1002/esp.1889 Cerdà, A., Lasanta, A. 2005. Long-term erosional responses after fire in the Central Spanish Pyrenees: 1. Water and sediment yield. Catena, 60, 59-80. Giménez Morera, A., Ruiz Sinoga, J.D. y Cerdà, A. 2010. The impact of cotton geotextiles on soil and water losses in Mediterranean rainfed agricultural land. Land Degradation and Development , 210- 217. DOI: 10.1002/ldr.971. Haile, G.W., and Fetene, M. 2012. Assessment of soil erosion hazard in Kilie catchment, East Shoa, Ethiopia. Land Degradation & Development, 23 (3): 293-306. Miao, C. Y., Yang, L., Chen, X. H., Gao, Y. 2012. The vegetation cover dynamics (1982-2006) in different erosion regions of the Yellow River Basin, China. Land Degradation & Development, 23: 62- 71. DOI 10.1002/ldr.1050 Izzo, M., Araujo, N., Aucelli, P. P. C., Maratea, A., and Sánchez, A. 2013. Land sensitivity to Desertification in the Dominican Republic: an adaptation of the ESA methodology. Land Degradation & Development, 24: 486- 498. DOI 10.1002/ldr.2241 Kosmas, C., Ferrara, A., Briassouli, H., Imeson, A., 1999. Methodology for mapping Environmentally Sensitive Areas (ESAs) to Desertification. In: Kosmas, C., Kirkby, M., Geeson, N. (Eds.), The Medalus project: Mediterranean desertification and land use. Manual of key indicator of desertification and mapping environmentally sensitive areas to desertification. European Union, 31-47. Lavado Contador, J.F., Schnabel, S., Gómez Gutiérrez, A., Pulido Fernández, M., 2009. Mapping sensitivity to land degradation in Extremadura, SW Spain. Land Degradation and Development 20, 129-144. Prokop, P., Poreba, G. J. 2012. Soil erosion associated with an upland farming system under population pressure in Northeast India. Land Degradation & Development, 23: 310- 321. DOI 10.1002/ldr.2147 Salvati, L., Zitti, M., Perini, L. 2013. Fifty years on: long-term patterns of land sensitivity to desertification in Italy. Land Degradation and Development DOI: 10.1002/ldr.2226 Science 61, 174-185. Similar findings were found by Zema et al., (2012) when applying the AnnAGNPS model to the agriculture land in Belgiums, Prokop and Poreba (2012) to the India, Miao e t al., (2012) in China and Haile and Fetene (2012) in Ethiopia: man made changes in the landscape that trigger land degradation processes.. Zema, D. A., Bingner, R. L., Denisi, P., Govers, G., Licciardello, F., Zimbone, S. M. 2012. Evaluation of runoff, peak flow and sediment yield for events simulated by the AnnAGNPS model in a belgian agricultural watershed. Land Degradation & Development, 23: 205- 215. DOI 10.1002/ldr.1068

A NEW LAND-SURFACE MODEL IN MM5

EPA Science Inventory

There has recently been a general realization that more sophisticated modeling of land-surface processes can be important for mesoscale meteorology models. Land-surface models (LSMs) have long been important components in global-scale climate models because of their more compl...

Impacts of historic and projected land-cover, land-use, and land-management change on carbon and water fluxes: The Land Use Model Intercomparison Project (LUMIP)

NASA Astrophysics Data System (ADS)

Lawrence, D. M.; Lombardozzi, D. L.; Lawrence, P.; Hurtt, G. C.

2017-12-01

Human land-use activities have resulted in large changes to the Earth surface, with resulting implications for climate. In the future, land-use activities are likely to intensify to meet growing demands for food, fiber, and energy. The Land Use Model Intercomparison Project (LUMIP) aims to further advance understanding of the broad question of impacts of land-use and land-cover change (LULCC) as well as more detailed science questions to get at process-level attribution, uncertainty, and data requirements in more depth and sophistication than possible in a multi-model context to date. LUMIP is multi-faceted and aims to advance our understanding of land-use change from several perspectives. In particular, LUMIP includes a factorial set of land-only simulations that differ from each other with respect to the specific treatment of land use or land management (e.g., irrigation active or not, crop fertilization active or not, wood harvest on or not), or in terms of prescribed climate. This factorial series of experiments serves several purposes and is designed to provide a detailed assessment of how the specification of land-cover change and land management affects the carbon, water, and energy cycle response to land-use change. The potential analyses that are possible through this set of experiments are vast. For example, comparing a control experiment with all land management active to an experiment with no irrigation allows a multi-model assessment of whether or not the increasing use of irrigation during the 20th century is likely to have significantly altered trends of regional water and energy fluxes (and therefore climate) and/or crop yield and carbon fluxes in agricultural regions. Here, we will present preliminary results from the factorial set of experiments utilizing the Community Land Model (CLM5). The analyses presented here will help guide multi-model analyses once the full set of LUMIP simulations are available.

Modeling the Land Use/Cover Change in an Arid Region Oasis City Constrained by Water Resource and Environmental Policy Change using Cellular Automata Model

NASA Astrophysics Data System (ADS)

Hu, X.; Li, X.; Lu, L.

2017-12-01

Land use/cover change (LUCC) is an important subject in the research of global environmental change and sustainable development, while spatial simulation on land use/cover change is one of the key content of LUCC and is also difficult due to the complexity of the system. The cellular automata (CA) model had an irreplaceable role in simulating of land use/cover change process due to the powerful spatial computing power. However, the majority of current CA land use/cover models were binary-state model that could not provide more general information about the overall spatial pattern of land use/cover change. Here, a multi-state logistic-regression-based Markov cellular automata (MLRMCA) model and a multi-state artificial-neural-network-based Markov cellular automata (MANNMCA) model were developed and were used to simulate complex land use/cover evolutionary process in an arid region oasis city constrained by water resource and environmental policy change, the Zhangye city during the period of 1990-2010. The results indicated that the MANNMCA model was superior to MLRMCA model in simulated accuracy. These indicated that by combining the artificial neural network with CA could more effectively capture the complex relationships between the land use/cover change and a set of spatial variables. Although the MLRMCA model were also some advantages, the MANNMCA model was more appropriate for simulating complex land use/cover dynamics. The two proposed models were effective and reliable, and could reflect the spatial evolution of regional land use/cover changes. These have also potential implications for the impact assessment of water resources, ecological restoration, and the sustainable urban development in arid areas.

Land and atmosphere interactions using satellite remote sensing and a coupled mesoscale/land surface model

NASA Astrophysics Data System (ADS)

Hong, Seungbum

Land and atmosphere interactions have long been recognized for playing a key role in climate and weather modeling. However their quantification has been challenging due to the complex nature of the land surface amongst various other reasons. One of the difficult parts in the quantification is the effect of vegetation which are related to land surface processes such soil moisture variation and to atmospheric conditions such as radiation. This study addresses various relational investigations among vegetation properties such as Normalized Difference Vegetation Index (NDVI), Leaf Area Index (LAI), surface temperature (TSK), and vegetation water content (VegWC) derived from satellite sensors such as Moderate Resolution Imaging Spectroradiometer (MODIS) and EOS Advanced Microwave Scanning Radiometer (AMSR-E). The study provides general information about a physiological behavior of vegetation for various environmental conditions. Second, using a coupled mesoscale/land surface model, we examined the effects of vegetation and its relationship with soil moisture on the simulated land-atmospheric interactions through the model sensitivity tests. The Weather Research and Forecasting (WRF) model was selected for this study, and the Noah land surface model (Noah LSM) implemented in the WRF model was used for the model coupled system. This coupled model was tested through two parameterization methods for vegetation fraction using MODIS data and through model initialization of soil moisture from High Resolution Land Data Assimilation System (HRLDAS). Then, this study evaluates the model improvements for each simulation method.

Evaluation of various LandFlux evapotranspiration algorithms using the LandFlux-EVAL synthesis benchmark products and observational data

NASA Astrophysics Data System (ADS)

Michel, Dominik; Hirschi, Martin; Jimenez, Carlos; McCabe, Mathew; Miralles, Diego; Wood, Eric; Seneviratne, Sonia

2014-05-01

Research on climate variations and the development of predictive capabilities largely rely on globally available reference data series of the different components of the energy and water cycles. Several efforts aimed at producing large-scale and long-term reference data sets of these components, e.g. based on in situ observations and remote sensing, in order to allow for diagnostic analyses of the drivers of temporal variations in the climate system. Evapotranspiration (ET) is an essential component of the energy and water cycle, which can not be monitored directly on a global scale by remote sensing techniques. In recent years, several global multi-year ET data sets have been derived from remote sensing-based estimates, observation-driven land surface model simulations or atmospheric reanalyses. The LandFlux-EVAL initiative presented an ensemble-evaluation of these data sets over the time periods 1989-1995 and 1989-2005 (Mueller et al. 2013). Currently, a multi-decadal global reference heat flux data set for ET at the land surface is being developed within the LandFlux initiative of the Global Energy and Water Cycle Experiment (GEWEX). This LandFlux v0 ET data set comprises four ET algorithms forced with a common radiation and surface meteorology. In order to estimate the agreement of this LandFlux v0 ET data with existing data sets, it is compared to the recently available LandFlux-EVAL synthesis benchmark product. Additional evaluation of the LandFlux v0 ET data set is based on a comparison to in situ observations of a weighing lysimeter from the hydrological research site Rietholzbach in Switzerland. These analyses serve as a test bed for similar evaluation procedures that are envisaged for ESA's WACMOS-ET initiative (http://wacmoset.estellus.eu). Reference: Mueller, B., Hirschi, M., Jimenez, C., Ciais, P., Dirmeyer, P. A., Dolman, A. J., Fisher, J. B., Jung, M., Ludwig, F., Maignan, F., Miralles, D. G., McCabe, M. F., Reichstein, M., Sheffield, J., Wang, K., Wood, E. F., Zhang, Y., and Seneviratne, S. I. (2013). Benchmark products for land evapotranspiration: LandFlux-EVAL multi-data set synthesis. Hydrology and Earth System Sciences, 17(10): 3707-3720.

Coupling a high resolution soil erosion model with an agro-ecosystem model of SOC dynamics. An approach to assess the potential environmental effect of the new Common Agricultural Policy on soil degradation

NASA Astrophysics Data System (ADS)

Borrelli, Pasqualle; Paustian, Keith; Panagos, Panos; Jones, Arwyn; Schütt, Brigitta; Lugato, Emanuele

2016-04-01

At the European Union level, the main mechanisms to promote a more sustainable and environmentally friendly agriculture was introduced by the Common Agricultural Policy (CAP) reform in 2003, through the Cross-compliance. According to this new regulation, the farmer support payments were regulated with respect to environmental, animal welfare and food safety standards. This brought to the Good Agricultural and Environmental Conditions (GAEC), firstly established by Council Regulation No. 1782/2003 and subsequently Council Regulation (EC) No 73/2009. The prevention of soil erosion and maintenance of soil organic matter were two of GAEC requirements, which each Member State was obliged to address through national standards such as: i) minimal soil cover maintenance (GAEC 4); ii) minimum land management reflecting site specific conditions to limit soil loss (GAEC 5) and iii) maintenance of soil organic matter level through appropriate practices including ban on burning arable stubbles (GAEC 6). Although Member States are required to verify whether the farmers are compliant with the regulations (Cross-compliance), the environmental effect of Good Agricultural and Environmental Conditions (GAEC) applications on erosion and carbon budgets are still little known and studied. To investigate the potential impacts of the GAEC, we coupled a high resolution erosion model based on Revised Universal Soil Loss Equation (RUSLE) with the CENTURY biogeochemical model (Land Use Policy, 50, 408-421; 2016). The Italian arable land was selected as a study area, since it is well-known to be highly sensitive to soil erosion. Multi scenario modelling approach was undertaken, i.e., i) a baseline scenario without scenario excluding GAEC (pre 2003 period); ii) a present scenario including the current GAEC standards (post 2003 period), and iii) a technical potential scenario assuming that the GAEC standards were applied to the entire Italian arable land. The results show a 10.8% decrease, from 8.33 Mg ha-1 yr-1 to 7.43 Mg ha-1 yr-1, in soil loss potential due to the adoption of the GAEC conservation practices (with respect to the baseline scenario). The technical potential scenario shows a 50.1% decrease in the soil loss potential (soil loss 4.1 Mg ha-1 yr-1). With regard to the soil organic carbon (SOC), the GAEC application in the current scenario shown an overall soil organic carbon (SOC) gains, with about 17% of the SOC variation related to avoided SOC transport by sediment erosion. The technical potential scenario suggests a potential gain up to 23.3 Mt of C by 2020 with the full GAEC application.

A Land System representation for global assessments and land-use modeling.

PubMed

van Asselen, Sanneke; Verburg, Peter H

2012-10-01

Current global scale land-change models used for integrated assessments and climate modeling are based on classifications of land cover. However, land-use management intensity and livestock keeping are also important aspects of land use, and are an integrated part of land systems. This article aims to classify, map, and to characterize Land Systems (LS) at a global scale and analyze the spatial determinants of these systems. Besides proposing such a classification, the article tests if global assessments can be based on globally uniform allocation rules. Land cover, livestock, and agricultural intensity data are used to map LS using a hierarchical classification method. Logistic regressions are used to analyze variation in spatial determinants of LS. The analysis of the spatial determinants of LS indicates strong associations between LS and a range of socioeconomic and biophysical indicators of human-environment interactions. The set of identified spatial determinants of a LS differs among regions and scales, especially for (mosaic) cropland systems, grassland systems with livestock, and settlements. (Semi-)Natural LS have more similar spatial determinants across regions and scales. Using LS in global models is expected to result in a more accurate representation of land use capturing important aspects of land systems and land architecture: the variation in land cover and the link between land-use intensity and landscape composition. Because the set of most important spatial determinants of LS varies among regions and scales, land-change models that include the human drivers of land change are best parameterized at sub-global level, where similar biophysical, socioeconomic and cultural conditions prevail in the specific regions. © 2012 Blackwell Publishing Ltd.

Computer program for simulation of variable recharge with the U. S. Geological Survey modular finite-difference ground-water flow model (MODFLOW)

USGS Publications Warehouse

Kontis, A.L.

2001-01-01

The Variable-Recharge Package is a computerized method designed for use with the U.S. Geological Survey three-dimensional finitedifference ground-water flow model (MODFLOW-88) to simulate areal recharge to an aquifer. It is suitable for simulations of aquifers in which the relation between ground-water levels and land surface can affect the amount and distribution of recharge. The method is based on the premise that recharge to an aquifer cannot occur where the water level is at or above land surface. Consequently, recharge will vary spatially in simulations in which the Variable- Recharge Package is applied, if the water levels are sufficiently high. The input data required by the program for each model cell that can potentially receive recharge includes the average land-surface elevation and a quantity termed ?water available for recharge,? which is equal to precipitation minus evapotranspiration. The Variable-Recharge Package also can be used to simulate recharge to a valley-fill aquifer in which the valley fill and the adjoining uplands are explicitly simulated. Valley-fill aquifers, which are the most common type of aquifer in the glaciated northeastern United States, receive much of their recharge from upland sources as channeled and(or) unchanneled surface runoff and as lateral ground-water flow. Surface runoff in the uplands is generated in the model when the applied water available for recharge is rejected because simulated water levels are at or above land surface. The surface runoff can be distributed to other parts of the model by (1) applying the amount of the surface runoff that flows to upland streams (channeled runoff) to explicitly simulated streams that flow onto the valley floor, and(or) (2) applying the amount that flows downslope toward the valley- fill aquifer (unchanneled runoff) to specified model cells, typically those near the valley wall. An example model of an idealized valley- fill aquifer is presented to demonstrate application of the method and the type of information that can be derived from its use. Documentation of the Variable-Recharge Package is provided in the appendixes and includes listings of model code and of program variables. Comment statements in the program listings provide a narrative of the code. Input-data instructions and printed model output for the package are included.

Scenarios of land use change for agriculture: the role of Land Evaluation in improving model simulation

NASA Astrophysics Data System (ADS)

Mereu, V.; Santini, M.; Dettori, G.; Muresu, P.; Spano, D.; Duce, P.

2009-12-01

Integrated scenarios of future climate and land use represent a useful input for impact studies about global changes. In particular, improving future land use simulations is essential for the agricultural sector, which is influenced by both biogeophysical constraints and human needs. Often land use change models are mainly based on statistical relationships between known land use distribution and biophysical or socio-economic factors, neglecting the necessary consideration of physical constraints that interact in making lands more or less capable for agriculture and suitable for supporting specific crops. In this study, a well developed land use change model (CLUE@CMCC) was suited for the Mediterranean basin case study, focusing on croplands. Several climate scenarios and future demands for croplands were combined to drive the model, while the same climate scenarios were used to more reliably allocate crops in the most suitable areas on the basis of Land Evaluation techniques. The probability for each map unit to sustain a specific crop, usually related to location characteristics, elasticity to conversion and competition among land use types, now includes specific crop-favoring location characteristics. Results, besides improving the consistency of the land use change model to allocate land for the future, can have the main feedback to suggest feasibility or reasonable thresholds to adjust land use demands during dynamic simulations.

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.

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.

Integrated modeling of land-use change: the role of coupling, interactions and feedbacks between the human and Earth systems

NASA Astrophysics Data System (ADS)

Monier, E.; Kicklighter, D. W.; Ejaz, Q.; Winchester, N.; Paltsev, S.; Reilly, J. M.

2016-12-01

Land-use change integrates a large number of components of the human and Earth systems, including climate, energy, water, and land. These complex coupling elements, interactions and feedbacks take place on a variety of space and time scales, thus increasing the complexity of land-use change modeling frameworks. In this study, we aim to identify which coupling elements, interactions and feedbacks are important for modeling land-use change, both at the global and regional level. First, we review the existing land-use change modeling framework used to develop land-use change projections for the Representative Concentration Pathways (RCP) scenarios. In such framework, land-use change is simulated by Integrated Assessment Models (IAMs) and mainly influenced by economic, energy, demographic and policy drivers. IAMs focus on representing the demand for agriculture and forestry goods (crops for food and bioenergy, forest products for construction and bioenergy), the interactions with other sectors of the economy and trade between various regions of the world. Then, we investigate how important various coupling elements and feedbacks with the Earth system are for projections of land-use change at the global and regional level. We focus on the following: i) the climate impacts on land productivity and greenhouse gas emissions, which requires climate change information and coupling to a terrestrial ecosystem model/crop model; ii) the climate and economic impacts on irrigation availability, which requires coupling the LUC modeling framework to a water resources management model and disaggregating rainfed and irrigated croplands; iii) the feedback of land-use change on the global and regional climate system through land-use change emissions and changes in the surface albedo and hydrology, which requires coupling to an Earth system model. Finally, we conclude our study by highlighting the current lack of clarity in how various components of the human and Earth systems are coupled in IAMs , and the need for a lexicon that is agreed upon by the IAM community.

Coupling Cellular Automata Land Use Change with Distributed Hydrologic Models

NASA Astrophysics Data System (ADS)

Shu, L.; Duffy, C.

2017-12-01

There has been extensive research on LUC modeling with broad applications to simulating urban growth and changing demographic patterns across multiple scales. The importance of land conversion is a critical issue in watershed scale studies and is generally not treated in most watershed modeling approaches. In this study we apply spatially explicit hydrologic and landuse change models and the Conestoga Watershed in Lancaster County, Pennsylvania. The Penn State Integrated Hydrologic Model (PIHM) partitions the water balance in space and time over the urban catchment, the coupled Cellular Automata Land Use Change model (CALUC) dynamically simulates the evolution of land use classes based on physical measures associated with population change and land use demand factors. The CALUC model is based on iteratively applying discrete rules to each individual spatial cell. The essence the CA modeling involves calculation of the Transition Potential (TP) for conversion of a grid cell from one land use class to another. This potential includes five factors: random perturbation, suitability, accessibility, neighborhood effect, inertia effects and zonal factors. In spite of simplicity, this CALUC model has been shown to be very effective for simulating LUC leading to the emergence of complex spatial patterns. The components of TP are derived from present land use data for landuse reanalysis and for realistic future land use scenarios. For the CALUC we use early-settlement (circa 1790) initial land class values and final or present-day (2010) land classes to calibrate the model. CALUC- PIHM dynamically simulates the hydrologic response of conversion from pre-settlement to present landuse. The simulations highlight the capability and value of dynamic coupling of catchment hydrology with land use change over long time periods. Analysis of the simulation uses various metrics such as the distributed water balance, flow duration curves, etc. to show how deforestation, urbanization and agricultural land development interact for the period 1790- present.

ORCHIDEE-SOM: modeling soil organic carbon (SOC) and dissolved organic carbon (DOC) dynamics along vertical soil profiles in Europe

NASA Astrophysics Data System (ADS)

Camino-Serrano, Marta; Guenet, Bertrand; Luyssaert, Sebastiaan; Ciais, Philippe; Bastrikov, Vladislav; De Vos, Bruno; Gielen, Bert; Gleixner, Gerd; Jornet-Puig, Albert; Kaiser, Klaus; Kothawala, Dolly; Lauerwald, Ronny; Peñuelas, Josep; Schrumpf, Marion; Vicca, Sara; Vuichard, Nicolas; Walmsley, David; Janssens, Ivan A.

2018-03-01

Current land surface models (LSMs) typically represent soils in a very simplistic way, assuming soil organic carbon (SOC) as a bulk, and thus impeding a correct representation of deep soil carbon dynamics. Moreover, LSMs generally neglect the production and export of dissolved organic carbon (DOC) from soils to rivers, leading to overestimations of the potential carbon sequestration on land. This common oversimplified processing of SOC in LSMs is partly responsible for the large uncertainty in the predictions of the soil carbon response to climate change. In this study, we present a new soil carbon module called ORCHIDEE-SOM, embedded within the land surface model ORCHIDEE, which is able to reproduce the DOC and SOC dynamics in a vertically discretized soil to 2 m. The model includes processes of biological production and consumption of SOC and DOC, DOC adsorption on and desorption from soil minerals, diffusion of SOC and DOC, and DOC transport with water through and out of the soils to rivers. We evaluated ORCHIDEE-SOM against observations of DOC concentrations and SOC stocks from four European sites with different vegetation covers: a coniferous forest, a deciduous forest, a grassland, and a cropland. The model was able to reproduce the SOC stocks along their vertical profiles at the four sites and the DOC concentrations within the range of measurements, with the exception of the DOC concentrations in the upper soil horizon at the coniferous forest. However, the model was not able to fully capture the temporal dynamics of DOC concentrations. Further model improvements should focus on a plant- and depth-dependent parameterization of the new input model parameters, such as the turnover times of DOC and the microbial carbon use efficiency. We suggest that this new soil module, when parameterized for global simulations, will improve the representation of the global carbon cycle in LSMs, thus helping to constrain the predictions of the future SOC response to global warming.

Assessing temporally and spatially resolved PM 2.5 exposures for epidemiological studies using satellite aerosol optical depth measurements

NASA Astrophysics Data System (ADS)

Kloog, Itai; Koutrakis, Petros; Coull, Brent A.; Lee, Hyung Joo; Schwartz, Joel

2011-11-01

Land use regression (LUR) models provide good estimates of spatially resolved long-term exposures, but are poor at capturing short term exposures. Satellite-derived Aerosol Optical Depth (AOD) measurements have the potential to provide spatio-temporally resolved predictions of both long and short term exposures, but previous studies have generally showed relatively low predictive power. Our objective was to extend our previous work on day-specific calibrations of AOD data using ground PM 2.5 measurements by incorporating commonly used LUR variables and meteorological variables, thus benefiting from both the spatial resolution from the LUR models and the spatio-temporal resolution from the satellite models. Later we use spatial smoothing to predict PM 2.5 concentrations for day/locations with missing AOD measures. We used mixed models with random slopes for day to calibrate AOD data for 2000-2008 across New-England with monitored PM 2.5 measurements. We then used a generalized additive mixed model with spatial smoothing to estimate PM 2.5 in location-day pairs with missing AOD, using regional measured PM 2.5, AOD values in neighboring cells, and land use. Finally, local (100 m) land use terms were used to model the difference between grid cell prediction and monitored value to capture very local traffic particles. Out-of-sample ten-fold cross-validation was used to quantify the accuracy of our predictions. For days with available AOD data we found high out-of-sample R2 (mean out-of-sample R2 = 0.830, year to year variation 0.725-0.904). For days without AOD values, our model performance was also excellent (mean out-of-sample R2 = 0.810, year to year variation 0.692-0.887). Importantly, these R2 are for daily, rather than monthly or yearly, values. Our model allows one to assess short term and long-term human exposures in order to investigate both the acute and chronic effects of ambient particles, respectively.

Assessing the Regional/Diurnal Bias between Satellite Retrievals and GEOS-5/MERRA Model Estimates of Land Surface Temperature

NASA Astrophysics Data System (ADS)

Scarino, B. R.; Smith, W. L., Jr.; Minnis, P.; Bedka, K. M.

2017-12-01

Atmospheric models rely on high-accuracy, high-resolution initial radiometric and surface conditions for better short-term meteorological forecasts, as well as improved evaluation of global climate models. Continuous remote sensing of the Earth's energy budget, as conducted by the Clouds and Earth's Radiant Energy System (CERES) project, allows for near-realtime evaluation of cloud and surface radiation properties. It is unfortunately common for there to be bias between atmospheric/surface radiation models and Earth-observations. For example, satellite-observed surface skin temperature (Ts), an important parameter for characterizing the energy exchange at the ground/water-atmosphere interface, can be biased due to atmospheric adjustment assumptions and anisotropy effects. Similarly, models are potentially biased by errors in initial conditions and regional forcing assumptions, which can be mitigated through assimilation with true measurements. As such, when frequent, broad-coverage, and accurate retrievals of satellite Ts are available, important insights into model estimates of Ts can be gained. The Satellite ClOud and Radiation Property retrieval System (SatCORPS) employs a single-channel thermal-infrared method to produce anisotropy-corrected Ts over clear-sky land and ocean surfaces from data taken by geostationary Earth orbit (GEO) satellite imagers. Regional and diurnal changes in model land surface temperature (LST) performance can be assessed owing to the somewhat continuous measurements of the LST offered by GEO satellites - measurements which are accurate to within 0.2 K. A seasonal, hourly comparison of satellite-observed LST with the NASA Goddard Earth Observing System Version 5 (GEOS-5) and the Modern-Era Retrospective Analysis for Research and Applications (MERRA) LST estimates is conducted to reveal regional and diurnal biases. This assessment is an important first step for evaluating the effectiveness of Ts assimilation, as well for determining the impact anisotropy correction has on observation - model bias, and is of critical importance for CERES.

Modeling the effects of environmental disturbance on wildlife communities: Avian responses to prescribed fire

USGS Publications Warehouse

Russell, R.E.; Royle, J. Andrew; Saab, V.A.; Lehmkuhl, J.F.; Block, W.M.; Sauer, J.R.

2009-01-01

Prescribed fire is a management tool used to reduce fuel loads on public lands in forested areas in the western United States. Identifying the impacts of prescribed fire on bird communities in ponderosa pine (Pinus ponderosa) forests is necessary for providing land management agencies with information regarding the effects of fuel reduction on sensitive, threatened, and migratory bird species. Recent developments in occupancy modeling have established a framework for quantifying the impacts of management practices on wildlife community dynamics. We describe a Bayesian hierarchical model of multi-species occupancy accounting for detection probability, and we demonstrate the model's usefulness for identifying effects of habitat disturbances on wildlife communities. Advantages to using the model include the ability to estimate the effects of environmental impacts on rare or elusive species, the intuitive nature of the modeling, the incorporation of detection probability, the estimation of parameter uncertainty, the flexibility of the model to suit a variety of experimental designs, and the composite estimate of the response that applies to the collection of observed species as opposed to merely a small subset of common species. Our modeling of the impacts of prescribed fire on avian communities in a ponderosa pine forest in Washington indicate that prescribed fire treatments result in increased occupancy rates for several bark-insectivore, cavity-nesting species including a management species of interest, Black-backed Woodpeckers (Picoides arcticus). Three aerial insectivore species, and the ground insectivore, American Robin (Turdus migratorius), also responded positively to prescribed fire, whereas three foliage insectivores and two seed specialists, Clark's Nutcracker (Nucifraga columbiana) and the Pine Siskin (Carduelis pinus), declined following treatments. Land management agencies interested in determining the effects of habitat manipulations on wildlife communities can use these methods to provide guidance for future management activities. ?? 2009 by the Ecological Society of America.

The urban heat island in the city of Poznań as derived from Landsat 5 TM

NASA Astrophysics Data System (ADS)

Majkowska, Agnieszka; Kolendowicz, Leszek; Półrolniczak, Marek; Hauke, Jan; Czernecki, Bartosz

2017-05-01

To study urban heat island (UHI), Landsat 5 TM data and in situ measurements of air temperature from nine points in Poznań (Poland) for the period June 2008-May 2013 were used. Based on data from measurement points located in different types of land use, the surface urban heat island (SUHI) maps were created. All available and quality-controlled Landsat 5 TM images from 15 unique days were used to obtain the characteristics of land surface temperature (LST) and UHI intensity. In addition, spatial analysis of UHI was conducted on the basis of Corine Land Cover 2006 dataset. In situ measurements at a height of 2 m above ground level show that the UHI is a common occurrence in Poznań with a mean annual intensity of 1.0 °C. The UHI intensity is greater during the warm half of the year. Moreover, results based on the remote sensing data and the Corine Land Cover 2006 indicate that the highest value of the mean LST anomalies (3.4 °C) is attained by the continuous urban fabric, while the lowest value occurs within the broad-leaved forests (-3.1 °C). To re-count from LST to the air temperature at a height of 2 m above ground level ( T agl), linear and non-linear regression models were created. For both models, coefficients of determination equal about 0.80, with slightly higher value for the non-linear approach, which was applied to estimate the T agl spatial variability over the city of Poznań.

Design of a Thermal and Micrometeorite Protection System for an Unmanned Lunar Cargo Lander

NASA Technical Reports Server (NTRS)

Hernandez, Carlos A.; Sunder, Sankar; Vestgaard, Baard

1989-01-01

The first vehicles to land on the lunar surface during the establishment phase of a lunar base will be unmanned lunar cargo landers. These landers will need to be protected against the hostile lunar environment for six to twelve months until the next manned mission arrives. The lunar environment is characterized by large temperature changes and periodic micrometeorite impacts. An automatically deployable and reconfigurable thermal and micrometeorite protection system was designed for an unmanned lunar cargo lander. The protection system is a lightweight multilayered material consisting of alternating layers of thermal and micrometeorite protection material. The protection system is packaged and stored above the lander common module. After landing, the system is deployed to cover the lander using a system of inflatable struts that are inflated using residual fuel (liquid oxygen) from the fuel tanks. Once the lander is unloaded and the protection system is no longer needed, the protection system is reconfigured as a regolith support blanket for the purpose of burying and protecting the common module, or as a lunar surface garage that can be used to sort and store lunar surface vehicles and equipment. A model showing deployment and reconfiguration of the protection system was also constructed.

Application and study of land-reclaim based on Arc/Info

NASA Astrophysics Data System (ADS)

Zhao, Jun; Zhang, Ruiju; Wang, Zhian; Li, Shiyong

2005-10-01

This paper firstly puts forward the evaluation models of land-reclaim, which is derived from the thoery of Fuzzy associative memory nerve network and corresponding supplemental CASE tools, based on the model the mode of land reclaim can determined, and then the elements of land-reclaim are displayed and synthesized visually and virtually by virtue of Arc/Info software. In the process of land reclaim, it is particularly important to build the model of land-reclaim and to map the distribution of soil elements. In this way rational and feasible schemes are adopted in order to instruct the project of land reclaim. This thesis mainly takes the fourth mining area of East Beach as an example and puts this model into practice. Based on Arc/Info software the application of land-reclaim is studied and good results are achieved.

The Land Use Model Intercomparison Project (LUMIP) contribution to CMIP6: rationale and experimental design

NASA Astrophysics Data System (ADS)

Lawrence, David M.; Hurtt, George C.; Arneth, Almut; Brovkin, Victor; Calvin, Kate V.; Jones, Andrew D.; Jones, Chris D.; Lawrence, Peter J.; de Noblet-Ducoudré, Nathalie; Pongratz, Julia; Seneviratne, Sonia I.; Shevliakova, Elena

2016-09-01

Human land-use activities have resulted in large changes to the Earth's surface, with resulting implications for climate. In the future, land-use activities are likely to expand and intensify further to meet growing demands for food, fiber, and energy. The Land Use Model Intercomparison Project (LUMIP) aims to further advance understanding of the impacts of land-use and land-cover change (LULCC) on climate, specifically addressing the following questions. (1) What are the effects of LULCC on climate and biogeochemical cycling (past-future)? (2) What are the impacts of land management on surface fluxes of carbon, water, and energy, and are there regional land-management strategies with the promise to help mitigate climate change? In addressing these questions, LUMIP will also address a range of more detailed science questions to get at process-level attribution, uncertainty, data requirements, and other related issues in more depth and sophistication than possible in a multi-model context to date. There will be particular focus on the separation and quantification of the effects on climate from LULCC relative to all forcings, separation of biogeochemical from biogeophysical effects of land use, the unique impacts of land-cover change vs. land-management change, modulation of land-use impact on climate by land-atmosphere coupling strength, and the extent to which impacts of enhanced CO2 concentrations on plant photosynthesis are modulated by past and future land use.LUMIP involves three major sets of science activities: (1) development of an updated and expanded historical and future land-use data set, (2) an experimental protocol for specific LUMIP experiments for CMIP6, and (3) definition of metrics and diagnostic protocols that quantify model performance, and related sensitivities, with respect to LULCC. In this paper, we describe LUMIP activity (2), i.e., the LUMIP simulations that will formally be part of CMIP6. These experiments are explicitly designed to be complementary to simulations requested in the CMIP6 DECK and historical simulations and other CMIP6 MIPs including ScenarioMIP, C4MIP, LS3MIP, and DAMIP. LUMIP includes a two-phase experimental design. Phase one features idealized coupled and land-only model simulations designed to advance process-level understanding of LULCC impacts on climate, as well as to quantify model sensitivity to potential land-cover and land-use change. Phase two experiments focus on quantification of the historic impact of land use and the potential for future land management decisions to aid in mitigation of climate change. This paper documents these simulations in detail, explains their rationale, outlines plans for analysis, and describes a new subgrid land-use tile data request for selected variables (reporting model output data separately for primary and secondary land, crops, pasture, and urban land-use types). It is essential that modeling groups participating in LUMIP adhere to the experimental design as closely as possible and clearly report how the model experiments were executed.

The Land Use Model Intercomparison Project (LUMIP) contribution to CMIP6: rationale and experimental design

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

Lawrence, David M.; Hurtt, George C.; Arneth, Almut

Human land-use activities have resulted in large changes to the Earth's surface, with resulting implications for climate. In the future, land-use activities are likely to expand and intensify further to meet growing demands for food, fiber, and energy. The Land Use Model Intercomparison Project (LUMIP) aims to further advance understanding of the impacts of land-use and land-cover change (LULCC) on climate, specifically addressing the following questions. (1) What are the effects of LULCC on climate and biogeochemical cycling (past-future)? (2) What are the impacts of land management on surface fluxes of carbon, water, and energy, and are there regional land-managementmore » st rategies with the promise to help mitigate climate change? In addressing these questions, LUMIP will also address a range of more detailed science questions to get at process-level attribution, uncertainty, data requirements, and other related issues in more depth and sophistication than possible in a multi-model context to date. There will be particular focus on the separation and quantification of the effects on climate from LULCC relative to all forcings, separation of biogeochemical from biogeophysical effects of land use, the unique impacts of land-cover change vs. land-management change, modulation of land-use impact on climate by land-atmosphere coupling strength, and the extent to which impacts of enhanced CO 2 concentrations on plant photosynthesis are modulated by past and future land use.LUMIP involves three major sets of science activities: (1) development of an updated and expanded historical and future land-use data set, (2) an experimental protocol for specific LUMIP experiments for CMIP6, and (3) definition of metrics and diagnostic protocols that quantify model performance, and related sensitivities, with respect to LULCC. In this paper, we describe LUMIP activity (2), i.e., the LUMIP simulations that will formally be part of CMIP6. These experiments are explicitly designed to be complementary to simulations requested in the CMIP6 DECK and historical simulations and other CMIP6 MIPs including ScenarioMIP, C4MIP, LS3MIP, and DAMIP. LUMIP includes a two-phase experimental design. Phase one features idealized coupled and land-only model simulations designed to advance process-level understanding of LULCC impacts on climate, as well as to quantify model sensitivity to potential land-cover and land-use change. Phase two experiments focus on quantification of the historic impact of land use and the potential for future land management decisions to aid in mitigation of climate change. This paper documents these simulations in detail, explains their rationale, outlines plans for analysis, and describes a new subgrid land-use tile data request for selected variables (reporting model output data separately for primary and secondary land, crops, pasture, and urban land-use types). It is essential that modeling groups participating in LUMIP adhere to the experimental design as closely as possible and clearly report how the model experiments were executed.« less

The Land Use Model Intercomparison Project (LUMIP) contribution to CMIP6: rationale and experimental design

DOE PAGES

Lawrence, David M.; Hurtt, George C.; Arneth, Almut; ...

2016-09-02

Human land-use activities have resulted in large changes to the Earth's surface, with resulting implications for climate. In the future, land-use activities are likely to expand and intensify further to meet growing demands for food, fiber, and energy. The Land Use Model Intercomparison Project (LUMIP) aims to further advance understanding of the impacts of land-use and land-cover change (LULCC) on climate, specifically addressing the following questions. (1) What are the effects of LULCC on climate and biogeochemical cycling (past-future)? (2) What are the impacts of land management on surface fluxes of carbon, water, and energy, and are there regional land-managementmore » st rategies with the promise to help mitigate climate change? In addressing these questions, LUMIP will also address a range of more detailed science questions to get at process-level attribution, uncertainty, data requirements, and other related issues in more depth and sophistication than possible in a multi-model context to date. There will be particular focus on the separation and quantification of the effects on climate from LULCC relative to all forcings, separation of biogeochemical from biogeophysical effects of land use, the unique impacts of land-cover change vs. land-management change, modulation of land-use impact on climate by land-atmosphere coupling strength, and the extent to which impacts of enhanced CO 2 concentrations on plant photosynthesis are modulated by past and future land use.LUMIP involves three major sets of science activities: (1) development of an updated and expanded historical and future land-use data set, (2) an experimental protocol for specific LUMIP experiments for CMIP6, and (3) definition of metrics and diagnostic protocols that quantify model performance, and related sensitivities, with respect to LULCC. In this paper, we describe LUMIP activity (2), i.e., the LUMIP simulations that will formally be part of CMIP6. These experiments are explicitly designed to be complementary to simulations requested in the CMIP6 DECK and historical simulations and other CMIP6 MIPs including ScenarioMIP, C4MIP, LS3MIP, and DAMIP. LUMIP includes a two-phase experimental design. Phase one features idealized coupled and land-only model simulations designed to advance process-level understanding of LULCC impacts on climate, as well as to quantify model sensitivity to potential land-cover and land-use change. Phase two experiments focus on quantification of the historic impact of land use and the potential for future land management decisions to aid in mitigation of climate change. This paper documents these simulations in detail, explains their rationale, outlines plans for analysis, and describes a new subgrid land-use tile data request for selected variables (reporting model output data separately for primary and secondary land, crops, pasture, and urban land-use types). It is essential that modeling groups participating in LUMIP adhere to the experimental design as closely as possible and clearly report how the model experiments were executed.« less

Evaluation of historical land cover, land use, and land-use change emissions in the GCAM integrated assessment model

NASA Astrophysics Data System (ADS)

Calvin, K. V.; Wise, M.; Kyle, P.; Janetos, A. C.; Zhou, Y.

2012-12-01

Integrated Assessment Models (IAMs) are often used as science-based decision-support tools for evaluating the consequences of climate and energy policies, and their use in this framework is likely to increase in the future. However, quantitative evaluation of these models has been somewhat limited for a variety of reasons, including data availability, data quality, and the inherent challenges in projections of societal values and decision-making. In this analysis, we identify and confront methodological challenges involved in evaluating the agriculture and land use component of the Global Change Assessment Model (GCAM). GCAM is a global integrated assessment model, linking submodules of the regionally disaggregated global economy, energy system, agriculture and land-use, terrestrial carbon cycle, oceans and climate. GCAM simulates supply, demand, and prices for energy and agricultural goods from 2005 to 2100 in 5-year increments. In each time period, the model computes the allocation of land across a variety of land cover types in 151 different regions, assuming that farmers maximize profits and that food demand is relatively inelastic. GCAM then calculates both emissions from land-use practices, and long-term changes in carbon stocks in different land uses, thus providing simulation information that can be compared to observed historical data. In this work, we compare GCAM results, both in recent historic and future time periods, to historical data sets. We focus on land use, land cover, land-use change emissions, and albedo.

Outline of the survey on the development of earth observation satellites

NASA Technical Reports Server (NTRS)

1977-01-01

An independent earth observation system with land and sea satellites to be developed by Japan is described. Visible and infrared radiometers, microwave radiometers, microwave scattermeters, synthetic aperture radar, and laser sensors are among the instrumentation discussed. Triaxial attitude control, basic technology common to sea and land observation satellites as well as land data analytical technology developed for U.S. LANDSAT data are reviewed.

The global gridded crop model intercomparison: Data and modeling protocols for Phase 1 (v1.0)

DOE PAGES

Elliott, J.; Müller, C.; Deryng, D.; ...

2015-02-11

We present protocols and input data for Phase 1 of the Global Gridded Crop Model Intercomparison, a project of the Agricultural Model Intercomparison and Improvement Project (AgMIP). The project consist of global simulations of yields, phenologies, and many land-surface fluxes using 12–15 modeling groups for many crops, climate forcing data sets, and scenarios over the historical period from 1948 to 2012. The primary outcomes of the project include (1) a detailed comparison of the major differences and similarities among global models commonly used for large-scale climate impact assessment, (2) an evaluation of model and ensemble hindcasting skill, (3) quantification ofmore » key uncertainties from climate input data, model choice, and other sources, and (4) a multi-model analysis of the agricultural impacts of large-scale climate extremes from the historical record.« less

Perfluorinated Compounds In Lime-Treated Biosolids

EPA Science Inventory

Land application of wastewater treatment residuals, or biosolids, is a common practice in the United States, about 50% of all biosolids being applied to agricultural land as a soil amendment. Incidents have been reported in Germany and the United States where biosolids containin...

A land-use and land-cover modeling strategy to support a national assessment of carbon stocks and fluxes

USGS Publications Warehouse

Sohl, Terry L.; Sleeter, Benjamin M.; Zhu, Zhiliang; Sayler, Kristi L.; Bennett, Stacie; Bouchard, Michelle; Reker, Ryan R.; Hawbaker, Todd J.; Wein, Anne M.; Liu, Shuguang; Kanengieter, Ronald L.; Acevedo, William

2012-01-01

Changes in land use, land cover, disturbance regimes, and land management have considerable influence on carbon and greenhouse gas (GHG) fluxes within ecosystems. Through targeted land-use and land-management activities, ecosystems can be managed to enhance carbon sequestration and mitigate fluxes of other GHGs. National-scale, comprehensive analyses of carbon sequestration potential by ecosystem are needed, with a consistent, nationally applicable land-use and land-cover (LULC) modeling framework a key component of such analyses. The U.S. Geological Survey has initiated a project to analyze current and projected future GHG fluxes by ecosystem and quantify potential mitigation strategies. We have developed a unique LULC modeling framework to support this work. Downscaled scenarios consistent with IPCC Special Report on Emissions Scenarios (SRES) were constructed for U.S. ecoregions, and the FORE-SCE model was used to spatially map the scenarios. Results for a prototype demonstrate our ability to model LULC change and inform a biogeochemical modeling framework for analysis of subsequent GHG fluxes. The methodology was then successfully used to model LULC change for four IPCC SRES scenarios for an ecoregion in the Great Plains. The scenario-based LULC projections are now being used to analyze potential GHG impacts of LULC change across the U.S.

Comparing two tools for ecosystem service assessments regarding water resources decisions.

PubMed

Dennedy-Frank, P James; Muenich, Rebecca Logsdon; Chaubey, Indrajeet; Ziv, Guy

2016-07-15

We present a comparison of two ecohydrologic models commonly used for planning land management to assess the production of hydrologic ecosystem services: the Soil and Water Assessment Tool (SWAT) and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) annual water yield model. We compare these two models at two distinct sites in the US: the Wildcat Creek Watershed in Indiana and the Upper Upatoi Creek Watershed in Georgia. The InVEST and SWAT models provide similar estimates of the spatial distribution of water yield in Wildcat Creek, but very different estimates of the spatial distribution of water yield in Upper Upatoi Creek. The InVEST model may do a poor job estimating the spatial distribution of water yield in the Upper Upatoi Creek Watershed because baseflow provides a significant portion of the site's total water yield, which means that storage dynamics which are not modeled by InVEST may be important. We also compare the ability of these two models, as well as one newly developed set of ecosystem service indices, to deliver useful guidance for land management decisions focused on providing hydrologic ecosystem services in three particular decision contexts: environmental flow ecosystem services, ecosystem services for potable water supply, and ecosystem services for rainfed irrigation. We present a simple framework for selecting models or indices to evaluate hydrologic ecosystem services as a way to formalize where models deliver useful guidance. Copyright © 2016 Elsevier Ltd. All rights reserved.

Simulating water quality and ecological status of Lake Vansjø, Norway, under land-use and climate change by linking process-oriented models with a Bayesian network.

PubMed

Couture, Raoul-Marie; Moe, S Jannicke; Lin, Yan; Kaste, Øyvind; Haande, Sigrid; Lyche Solheim, Anne

2018-04-15

Excess nutrient inputs and climate change are two of multiple stressors affecting many lakes worldwide. Lake Vansjø in southern Norway is one such eutrophic lake impacted by blooms of toxic blue-green algae (cyanobacteria), and classified as moderate ecological status under the EU Water Framework Directive. Future climate change may exacerbate the situation. Here we use a set of chained models (global climate model, hydrological model, catchment phosphorus (P) model, lake model, Bayesian Network) to assess the possible future ecological status of the lake, given the set of climate scenarios and storylines common to the EU project MARS (Managing Aquatic Ecosystems and Water Resources under Multiple Stress). The model simulations indicate that climate change alone will increase precipitation and runoff, and give higher P fluxes to the lake, but cause little increase in phytoplankton biomass or changes in ecological status. For the storylines of future management and land-use, however, the model results indicate that both the phytoplankton biomass and the lake ecological status can be positively or negatively affected. Our results also show the value in predicting a biological indicator of lake ecological status, in this case, cyanobacteria biomass with a BN model. For all scenarios, cyanobacteria contribute to worsening the status assessed by phytoplankton, compared to using chlorophyll-a alone. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Research on the decision-making model of land-use spatial optimization

NASA Astrophysics Data System (ADS)

He, Jianhua; Yu, Yan; Liu, Yanfang; Liang, Fei; Cai, Yuqiu

2009-10-01

Using the optimization result of landscape pattern and land use structure optimization as constraints of CA simulation results, a decision-making model of land use spatial optimization is established coupled the landscape pattern model with cellular automata to realize the land use quantitative and spatial optimization simultaneously. And Huangpi district is taken as a case study to verify the rationality of the model.

Land use alters the resistance and resilience of soil food webs to drought

USGS Publications Warehouse

de Vries, Franciska T.; Liiri, Mira E.; Bjørnlund, Lisa; Bowker, Matthew A.; Christensen, Søren; Setälä, Heikki; Bardgett, Richard D.

2012-01-01

Soils deliver several ecosystem services including carbon sequestration and nutrient cycling, which are of central importance to climate mitigation and sustainable food production. Soil biota play an important role in carbon and nitrogen cycling, and, although the effects of land use on soil food webs are well documented the consequences for their resistance and resilience to climate change are not known. We compared the resistance and resilience to drought--which is predicted to increase under climate change of soil food webs of two common land-use systems: intensively managed wheat with a bacterial-based soil food web and extensively managed grassland with a fungal-based soil food web. We found that the fungal-based food web, and the processes of C and N loss it governs, of grassland soil was more resistant, although not resilient, and better able to adapt to drought than the bacterial-based food web of wheat soil. Structural equation modelling revealed that fungal-based soil food webs and greater microbial evenness mitigated C and N loss. Our findings show that land use strongly affects the resistance and resilience of soil food webs to climate change, and that extensively managed grassland promotes more resistant, and adaptable, fungal-based soil food webs.

Effects of land cover change on evapotranspiration and streamflow of small catchments in the Upper Xingu River Basin, Central Brazi

NASA Astrophysics Data System (ADS)

Costa, M. H.; Dias, L. C. P.; Macedo, M.; Coe, M. T.; Neill, C.

2014-12-01

This study assess the influence of land cover changes on evapotranspiration and streamflow in small catchments in the Upper Xingu River Basin (Mato Grosso state, Brazil). Streamflow was measured in catchments with uniform land use for September 1, 2008 to August 31, 2010. We used models to simulate evapotranspiration and streamflow for the four most common land cover types found in the Upper Xingu: tropical forest, cerrado (savanna), pasture, and soybean croplands. We used INLAND to perform single point simulations considering tropical rainforest, cerrado and pasturelands, and AgroIBIS for croplands. Converting natural vegetation to agriculture substantially modifies evapotranspiration and streamflow in small catchments. Measured mean streamflow in soy catchments was about three times greater than that of forest catchments, while the mean annual amplitude of flow in soy catchments was more than twice that of forest catchments. Simulated mean annual evapotranspiration was 39% lower in agricultural ecosystems (pasture and soybean cropland) than in natural ecosystems (tropical rainforest and cerrado). Observed and simulated mean annual streamflows in agricultural ecosystems were more than 100% higher than in natural ecosystems. The accuracy of the simulations is improved by using field-measured soil hydraulic properties. The inclusion of local measurements of key soil parameters is likely to improve hydrological simulations in other tropical regions.

Effects of land cover change on evapotranspiration and streamflow of small catchments in the Upper Xingu River Basin, Central Brazi

NASA Astrophysics Data System (ADS)

Costa, M. H.; Dias, L. C. P.; Macedo, M.; Coe, M. T.; Neill, C.

2015-12-01

This study assess the influence of land cover changes on evapotranspiration and streamflow in small catchments in the Upper Xingu River Basin (Mato Grosso state, Brazil). Streamflow was measured in catchments with uniform land use for September 1, 2008 to August 31, 2010. We used models to simulate evapotranspiration and streamflow for the four most common land cover types found in the Upper Xingu: tropical forest, cerrado (savanna), pasture, and soybean croplands. We used INLAND to perform single point simulations considering tropical rainforest, cerrado and pasturelands, and AgroIBIS for croplands. Converting natural vegetation to agriculture substantially modifies evapotranspiration and streamflow in small catchments. Measured mean streamflow in soy catchments was about three times greater than that of forest catchments, while the mean annual amplitude of flow in soy catchments was more than twice that of forest catchments. Simulated mean annual evapotranspiration was 39% lower in agricultural ecosystems (pasture and soybean cropland) than in natural ecosystems (tropical rainforest and cerrado). Observed and simulated mean annual streamflows in agricultural ecosystems were more than 100% higher than in natural ecosystems. The accuracy of the simulations is improved by using field-measured soil hydraulic properties. The inclusion of local measurements of key soil parameters is likely to improve hydrological simulations in other tropical regions.

Statistically extracted fundamental watershed variables for estimating the loads of total nitrogen in small streams

USGS Publications Warehouse

Kronholm, Scott C.; Capel, Paul D.; Terziotti, Silvia

2016-01-01

Accurate estimation of total nitrogen loads is essential for evaluating conditions in the aquatic environment. Extrapolation of estimates beyond measured streams will greatly expand our understanding of total nitrogen loading to streams. Recursive partitioning and random forest regression were used to assess 85 geospatial, environmental, and watershed variables across 636 small (<585 km2) watersheds to determine which variables are fundamentally important to the estimation of annual loads of total nitrogen. Initial analysis led to the splitting of watersheds into three groups based on predominant land use (agricultural, developed, and undeveloped). Nitrogen application, agricultural and developed land area, and impervious or developed land in the 100-m stream buffer were commonly extracted variables by both recursive partitioning and random forest regression. A series of multiple linear regression equations utilizing the extracted variables were created and applied to the watersheds. As few as three variables explained as much as 76 % of the variability in total nitrogen loads for watersheds with predominantly agricultural land use. Catchment-scale national maps were generated to visualize the total nitrogen loads and yields across the USA. The estimates provided by these models can inform water managers and help identify areas where more in-depth monitoring may be beneficial.

Validation and Verification of Operational Land Analysis Activities at the Air Force Weather Agency

NASA Technical Reports Server (NTRS)

Shaw, Michael; Kumar, Sujay V.; Peters-Lidard, Christa D.; Cetola, Jeffrey

2012-01-01

The NASA developed Land Information System (LIS) is the Air Force Weather Agency's (AFWA) operational Land Data Assimilation System (LDAS) combining real time precipitation observations and analyses, global forecast model data, vegetation, terrain, and soil parameters with the community Noah land surface model, along with other hydrology module options, to generate profile analyses of global soil moisture, soil temperature, and other important land surface characteristics. (1) A range of satellite data products and surface observations used to generate the land analysis products (2) Global, 1/4 deg spatial resolution (3) Model analysis generated at 3 hours. AFWA recognizes the importance of operational benchmarking and uncertainty characterization for land surface modeling and is developing standard methods, software, and metrics to verify and/or validate LIS output products. To facilitate this and other needs for land analysis activities at AFWA, the Model Evaluation Toolkit (MET) -- a joint product of the National Center for Atmospheric Research Developmental Testbed Center (NCAR DTC), AFWA, and the user community -- and the Land surface Verification Toolkit (LVT), developed at the Goddard Space Flight Center (GSFC), have been adapted to operational benchmarking needs of AFWA's land characterization activities.

Modelling land cover change in the Ganga basin

NASA Astrophysics Data System (ADS)

Moulds, S.; Tsarouchi, G.; Mijic, A.; Buytaert, W.

2013-12-01

Over recent decades the green revolution in India has driven substantial environmental change. Modelling experiments have identified northern India as a 'hot spot' of land-atmosphere coupling strength during the boreal summer. However, there is a wide range of sensitivity of atmospheric variables to soil moisture between individual climate models. The lack of a comprehensive land cover change dataset to force climate models has been identified as a major contributor to model uncertainty. In this work a time series dataset of land cover change between 1970 and 2010 is constructed for northern India to improve the quantification of regional hydrometeorological feedbacks. The MODIS instrument on board the Aqua and Terra satellites provides near-continuous remotely sensed datasets from 2000 to the present day. However, the quality of satellite products before 2000 is poor. To complete the dataset MODIS images are extrapolated back in time using the Conversion of Land Use and its Effects at small regional extent (CLUE-s) modelling framework. Non-spatial estimates of land cover area from national agriculture and forest statistics, available on a state-wise, annual basis, are used as a direct model input. Land cover change is allocated spatially as a function of biophysical and socioeconomic drivers identified using logistic regression. This dataset will provide an essential input to a high resolution, physically based land surface model to generate the lower boundary condition to assess the impact of land cover change on regional climate.

Land Surface Data Assimilation

NASA Astrophysics Data System (ADS)

Houser, P. R.

2012-12-01

Information about land surface water, energy and carbon conditions is of critical importance to real-world applications such as agricultural production, water resource management, flood prediction, water supply, weather and climate forecasting, and environmental preservation. While ground-based observational networks are improving, the only practical way to observe these land surface states on continental to global scales is via satellites. Remote sensing can make spatially comprehensive measurements of various components of the terrestrial system, but it cannot provide information on the entire system (e.g. evaporation), and the observations represent only an instant in time. Land surface process models may be used to predict temporal and spatial terrestrial dynamics, but these predictions are often poor, due to model initialization, parameter and forcing, and physics errors. Therefore, an attractive prospect is to combine the strengths of land surface models and observations (and minimize the weaknesses) to provide a superior terrestrial state estimate. This is the goal of land surface data assimilation. Data Assimilation combines observations into a dynamical model, using the model's equations to provide time continuity and coupling between the estimated fields. Land surface data assimilation aims to utilize both our land surface process knowledge, as embodied in a land surface model, and information that can be gained from observations. Both model predictions and observations are imperfect and we wish to use both synergistically to obtain a more accurate result. Moreover, both contain different kinds of information, that when used together, provide an accuracy level that cannot be obtained individually. Model biases can be mitigated using a complementary calibration and parameterization process. Limited point measurements are often used to calibrate the model(s) and validate the assimilation results. This presentation will provide a brief background on land surface observation, modeling and data assimilation, followed by a discussion of various hydrologic data assimilation challenges, and finally conclude with several land surface data assimilation case studies.

Modeling the Dynamic Interrelations between Mobility, Utility, and Land Asking Price

NASA Astrophysics Data System (ADS)

Hidayat, E.; Rudiarto, I.; Siegert, F.; Vries, W. D.

2018-02-01

Limited and insufficient information about the dynamic interrelation among mobility, utility, and land price is the main reason to conduct this research. Several studies, with several approaches, and several variables have been conducted so far in order to model the land price. However, most of these models appear to generate primarily static land prices. Thus, a research is required to compare, design, and validate different models which calculate and/or compare the inter-relational changes of mobility, utility, and land price. The applied method is a combination of analysis of literature review, expert interview, and statistical analysis. The result is newly improved mathematical model which have been validated and is suitable for the case study location. This improved model consists of 12 appropriate variables. This model can be implemented in the Salatiga city as the case study location in order to arrange better land use planning to mitigate the uncontrolled urban growth.

Models meet data: Challenges and opportunities in implementing land management in Earth system models.

PubMed

Pongratz, Julia; Dolman, Han; Don, Axel; Erb, Karl-Heinz; Fuchs, Richard; Herold, Martin; Jones, Chris; Kuemmerle, Tobias; Luyssaert, Sebastiaan; Meyfroidt, Patrick; Naudts, Kim

2018-04-01

As the applications of Earth system models (ESMs) move from general climate projections toward questions of mitigation and adaptation, the inclusion of land management practices in these models becomes crucial. We carried out a survey among modeling groups to show an evolution from models able only to deal with land-cover change to more sophisticated approaches that allow also for the partial integration of land management changes. For the longer term a comprehensive land management representation can be anticipated for all major models. To guide the prioritization of implementation, we evaluate ten land management practices-forestry harvest, tree species selection, grazing and mowing harvest, crop harvest, crop species selection, irrigation, wetland drainage, fertilization, tillage, and fire-for (1) their importance on the Earth system, (2) the possibility of implementing them in state-of-the-art ESMs, and (3) availability of required input data. Matching these criteria, we identify "low-hanging fruits" for the inclusion in ESMs, such as basic implementations of crop and forestry harvest and fertilization. We also identify research requirements for specific communities to address the remaining land management practices. Data availability severely hampers modeling the most extensive land management practice, grazing and mowing harvest, and is a limiting factor for a comprehensive implementation of most other practices. Inadequate process understanding hampers even a basic assessment of crop species selection and tillage effects. The need for multiple advanced model structures will be the challenge for a comprehensive implementation of most practices but considerable synergy can be gained using the same structures for different practices. A continuous and closer collaboration of the modeling, Earth observation, and land system science communities is thus required to achieve the inclusion of land management in ESMs. © 2017 John Wiley & Sons Ltd.

An integrated approach to modeling changes in land use, land cover, and disturbance and their impact on ecosystem carbon dynamics: a case study in the Sierra Nevada Mountains of California

USGS Publications Warehouse

Sleeter, Benjamin M.; Liu, Jinxun; Daniel, Colin; Frid, Leonardo; Zhu, Zhiliang

2015-01-01

Increased land-use intensity (e.g. clearing of forests for cultivation, urbanization), often results in the loss of ecosystem carbon storage, while changes in productivity resulting from climate change may either help offset or exacerbate losses. However, there are large uncertainties in how land and climate systems will evolve and interact to shape future ecosystem carbon dynamics. To address this we developed the Land Use and Carbon Scenario Simulator (LUCAS) to track changes in land use, land cover, land management, and disturbance, and their impact on ecosystem carbon storage and flux within a scenario-based framework. We have combined a state-and-transition simulation model (STSM) of land change with a stock and flow model of carbon dynamics. Land-change projections downscaled from the Intergovernmental Panel on Climate Change’s (IPCC) Special Report on Emission Scenarios (SRES) were used to drive changes within the STSM, while the Integrated Biosphere Simulator (IBIS) ecosystem model was used to derive input parameters for the carbon stock and flow model. The model was applied to the Sierra Nevada Mountains ecoregion in California, USA, a region prone to large wildfires and a forestry sector projected to intensify over the next century. Three scenario simulations were conducted, including a calibration scenario, a climate-change scenario, and an integrated climate- and land-change scenario. Based on results from the calibration scenario, the LUCAS age-structured carbon accounting model was able to accurately reproduce results obtained from the process-based biogeochemical model. Under the climate-only scenario, the ecoregion was projected to be a reliable net sink of carbon, however, when land use and disturbance were introduced, the ecoregion switched to become a net source. This research demonstrates how an integrated approach to carbon accounting can be used to evaluate various drivers of ecosystem carbon change in a robust, yet transparent modeling environment.

Topsoil organic carbon content of Europe, a new map based on a generalised additive model

NASA Astrophysics Data System (ADS)

de Brogniez, Delphine; Ballabio, Cristiano; Stevens, Antoine; Jones, Robert J. A.; Montanarella, Luca; van Wesemael, Bas

2014-05-01

There is an increasing demand for up-to-date spatially continuous organic carbon (OC) data for global environment and climatic modeling. Whilst the current map of topsoil organic carbon content for Europe (Jones et al., 2005) was produced by applying expert-knowledge based pedo-transfer rules on large soil mapping units, the aim of this study was to replace it by applying digital soil mapping techniques on the first European harmonised geo-referenced topsoil (0-20 cm) database, which arises from the LUCAS (land use/cover area frame statistical survey) survey. A generalized additive model (GAM) was calibrated on 85% of the dataset (ca. 17 000 soil samples) and a backward stepwise approach selected slope, land cover, temperature, net primary productivity, latitude and longitude as environmental covariates (500 m resolution). The validation of the model (applied on 15% of the dataset), gave an R2 of 0.27. We observed that most organic soils were under-predicted by the model and that soils of Scandinavia were also poorly predicted. The model showed an RMSE of 42 g kg-1 for mineral soils and of 287 g kg-1 for organic soils. The map of predicted OC content showed the lowest values in Mediterranean countries and in croplands across Europe, whereas highest OC content were predicted in wetlands, woodlands and in mountainous areas. The map of standard error of the OC model predictions showed high values in northern latitudes, wetlands, moors and heathlands, whereas low uncertainty was mostly found in croplands. A comparison of our results with the map of Jones et al. (2005) showed a general agreement on the prediction of mineral soils' OC content, most probably because the models use some common covariates, namely land cover and temperature. Our model however failed to predict values of OC content greater than 200 g kg-1, which we explain by the imposed unimodal distribution of our model, whose mean is tilted towards the majority of soils, which are mineral. Finally, average OC content predictions for each land cover class compared well between models, with our model always showing smaller standard deviations. We concluded that the chosen model and covariates are appropriate for the prediction of OC content in European mineral soils. We presented in this work the first map of topsoil OC content at European scale based on a harmonised soil dataset. The associated uncertainty map shall support the end-users in a careful use of the predictions.

Landing impact studies of a 0.3-scale model air cushion landing system for a Navy fighter airplane

NASA Technical Reports Server (NTRS)

Leland, T. J. W.; Thompson, W. C.

1975-01-01

An experimental study was conducted in order to determine the landing-impact behavior of a 0.3-scale, dynamically (but not physically) similar model of a high-density Navy fighter equipped with an air cushion landing system. The model was tested over a range of landing contact attitudes at high forward speeds and sink rates on a specialized test fixture at the Langley aircraft landing loads and traction facility. The investigation indicated that vertical acceleration at landing impact was highly dependent on the pitch angle at ground contact, the higher acceleration of approximately 5g occurring near zero body-pitch attitude. A limited number of low-speed taxi tests were made in order to determine model stability characteristics. The model was found to have good pitch-damping characteristics but stability in roll was marginal.

A predictive pilot model for STOL aircraft landing

NASA Technical Reports Server (NTRS)

Kleinman, D. L.; Killingsworth, W. R.

1974-01-01

An optimal control approach has been used to model pilot performance during STOL flare and landing. The model is used to predict pilot landing performance for three STOL configurations, each having a different level of automatic control augmentation. Model predictions are compared with flight simulator data. It is concluded that the model can be effective design tool for studying analytically the effects of display modifications, different stability augmentation systems, and proposed changes in the landing area geometry.

Evaporation from soils subjected to natural boundary conditions at the land-atmospheric interface

NASA Astrophysics Data System (ADS)

Smits, K.; Illngasekare, T.; Ngo, V.; Cihan, A.

2012-04-01

Bare soil evaporation is a key process for water exchange between the land and the atmosphere and an important component of the water balance in semiarid and arid regions. However, there is no agreement on the best methodology to determine evaporation under different boundary conditions at the land surface. This becomes critical in developing models that couples land to the atmosphere. Because it is difficult to measure evaporation from soil, with the exception of using lysimeters, numerous formulations have been proposed to establish a relationship between the rate of evaporation and soil moisture and/or soil temperature and thermal properties. Different formulations vary in how they partition available energy. A need exists to systematically compare existing methods to experimental data under highly controlled conditions not achievable in the field. The goal of this work is to perform controlled experiments under transient conditions of soil moisture, temperature and wind at the land/atmospheric interface to test different conceptual and mathematical formulations for the soil surface boundary conditions to develop appropriate numerical models to be used in simulations. In this study, to better understand the coupled water-vapor-heat flow processes in the shallow subsurface near the land surface, we modified a previously developed theory by Smits et al. [2011] that allows non-equilibrium liquid/gas phase change with gas phase vapor diffusion to better account for dry soil conditions. The model did not implement fitting parameters such as a vapor enhancement factor that is commonly introduced into the vapor diffusion coefficient as an arbitrary multiplication factor. In order to experimentally test the numerical formulations/code, we performed a two-dimensional physical model experiment under varying boundary conditions using test sand for which the hydraulic and thermal properties were well characterized. Precision data under well-controlled transient heat and wind boundary conditions was generated and results from numerical simulations were compared with experimental data. Results demonstrate that the boundary condition approaches varied in their ability to capture stage 1- and stage 2- evaporation. Results also demonstrated the importance of properly characterizing soil thermal properties and accounting for dry soil conditions. The contribution of film flow to hydraulic conductivity for the layer above the drying front is dominant compared to that of capillary flow, demonstrating the importance of including film flow in modeling efforts for dry soils, especially for fine grained soils. Comparisons of different formulations of the surface boundary condition validate the need for joint evaluation of heat and mass transfer for better modeling accuracy. This knowledge is applicable to many current hydrologic and environmental problems to include climate modeling and the simulation of contaminant transport and volatilization in the shallow subsurface. Smits, K. M., A. Cihan, T. Sakaki, and T. H. Illangasekare (2011). Evaporation from soils under thermal boundary conditions: Experimental and modeling investigation to compare equilibrium- and nonequilibrium-based approaches, Water Resour. Res., 47, W05540, doi:10.1029/2010WR009533.

Simulating carbon, water and energy fluxes of a rainforest and an oil palm plantation using the Community Land Model (CLM4.5)

NASA Astrophysics Data System (ADS)

Fan, Yuanchao; Bernoux, Martial; Roupsard, Olivier; Panferov, Oleg; Le Maire, Guerric; Tölle, Merja; Knohl, Alexander

2014-05-01

Deforestation and forest degradation driven by the expansion of oil palm (Elaeis guineensis) plantations has become the major source of GHG emission in Indonesia. Changes of land surface properties (e.g. vegetation composition, soil property, surface albedo) associated with rainforest to oil palm conversion might alter the patterns of land-atmosphere energy, water and carbon cycles and therefore affect local or regional climate. Land surface modeling has been widely used to characterize the two-way interactions between climate and human disturbances on land surface. The Community Land Model (CLM) is a third-generation land model that simulates a wide range of biogeophysical and biogeochemical processes. This project utilizes the land-cover/land-use change (LCLUC) capability of the latest CLM versions 4/4.5 to characterize quantitatively how anthropogenic land surface dynamics in Indonesia affect land-atmosphere carbon, water and energy fluxes. Before simulating land use changes, the first objective is to parameterize and validate the CLM model at local rainforest and oil palm plantation sites through separate point simulations. This entails creation and parameterization of a new plant functional type (PFT) for oil palm, as well as sensitivity analysis and adaptation of model parameters for the rainforest PFTs. CLM modelled fluxes for the selected sites are to be compared with field observations from eddy covariance (EC) flux towers (e.g. a rainforest site in Bariri, Sulawesi; an oil palm site in Jambi, Sumatra). After validation, the project will proceed to parameterize land-use transformation system using remote sensing data and to simulate the impacts of historical LUCs on carbon, water and energy fluxes. Last but not least, the effects of future LUCs in Indonesia on the fluxes and carbon sequestration capacity will be investigated through scenario study. Historical land cover changes, especially oil palm coverage, are retrieved from Landsat or MODIS archival images. Oil palm concession boundaries are used to define and project future land use scenarios. Initial results include outputs from a single-point simulation for the Bariri rainforest site forced with locally measured meteorological data which already showed significant advantage over global forcing data in predicting net ecosystem exchange and latent and sensible heat fluxes. Modeled fluxes are being compared with EC flux observations and with Mixfor-SVAT model outputs from another project at the same site. In the next few months, focus will be on sensitivity analyses of model parameters including PFT optical, morphological and physiological parameters that are necessary to configure the new oil palm PFT and represent rainforest to oil palm conversion. The new parameterization will contribute to the development of the CLM model and its implementation in the modelling of LUC effects in tropical regions will help understanding land-climate interactions.

Advancing the retrievals of surface emissivity by modelling the spatial distribution of temperature in the thermal hyperspectral scene

NASA Astrophysics Data System (ADS)

Shimoni, M.; Haelterman, R.; Lodewyckx, P.

2016-05-01

Land Surface Temperature (LST) and Land Surface Emissivity (LSE) are commonly retrieved from thermal hyperspectral imaging. However, their retrieval is not a straightforward procedure because the mathematical problem is ill-posed. This procedure becomes more challenging in an urban area where the spatial distribution of temperature varies substantially in space and time. For assessing the influence of several spatial variances on the deviation of the temperature in the scene, a statistical model is created. The model was tested using several images from various times in the day and was validated using in-situ measurements. The results highlight the importance of the geometry of the scene and its setting relative to the position of the sun during day time. It also shows that when the position of the sun is in zenith, the main contribution to the thermal distribution in the scene is the thermal capacity of the landcover materials. In this paper we propose a new Temperature and Emissivity Separation (TES) method which integrates 3D surface and landcover information from LIDAR and VNIR hyperspectral imaging data in an attempt to improve the TES procedure for a thermal hyperspectral scene. The experimental results prove the high accuracy of the proposed method in comparison to another conventional TES model.

A Novel Optical Model for Remote Sensing of Near-Surface Soil Moisture

NASA Astrophysics Data System (ADS)

Babaeian, E.; Sadeghi, M.; Jones, S. B.; Tuller, M.

2016-12-01

Common triangle and trapezoid methods that are based on both optical and thermal remote sensing (RS) information have been widely applied in the past to estimate near-surface soil moisture from the soil temperature - vegetation index space (e.g., LST-NDVI). For most cases, this approach assumes a linear relationship between soil moisture and temperature. Though this linearity assumption yields reasonable moisture estimates, it is not always justified as evidenced by laboratory and field measurements. Furthermore, this approach requires optical as well as thermal RS data for definition of the land surface temperature (LST) - vegetation index space, therefore, it is not applicable to satellites that do not provide thermal output such as the ESA Sentinel-2. To overcome these limitations, we propose a novel trapezoid model that only relies on optical NIR and SWIR data. The new model was validated using Sentinel-2 and Landsat-8 data for the semiarid Walnut Gulch (AZ) and sub humid Little Washita (OK) watersheds that vastly differ in land use and surface cover and provide excellent ground-truth moisture information from extensive sensor networks. Preliminary results for 2015-2016 indicate significant potential of the new model with a RMSE smaller than 4% volumetric near-surface moisture content and also confirm the enhanced utility of the high spatially and temporally resolved Sentinel-2 data.

The development and application of a decision support system for land management in the Lake Tahoe Basin—The Land Use Simulation Model

USGS Publications Warehouse

Forney, William M.; Oldham, I. Benson; Crescenti, Neil

2013-01-01

This report describes and applies the Land Use Simulation Model (LUSM), the final modeling product for the long-term decision support project funded by the Southern Nevada Public Land Management Act and developed by the U.S. Geological Survey’s Western Geographic Science Center for the Lake Tahoe Basin. Within the context of the natural-resource management and anthropogenic issues of the basin and in an effort to advance land-use and land-cover change science, this report addresses the problem of developing the LUSM as a decision support system. It includes consideration of land-use modeling theory, fire modeling and disturbance in the wildland-urban interface, historical land-use change and its relation to active land management, hydrologic modeling and the impact of urbanization as related to the Lahontan Regional Water Quality Control Board’s recently developed Total Maximum Daily Load report for the basin, and biodiversity in urbanizing areas. The LUSM strives to inform land-management decisions in a complex regulatory environment by simulating parcel-based, land-use transitions with a stochastic, spatially constrained, agent-based model. The tool is intended to be useful for multiple purposes, including the multiagency Pathway 2007 regional planning effort, the Tahoe Regional Planning Agency (TRPA) Regional Plan Update, and complementary research endeavors and natural-resource-management efforts. The LUSM is an Internet-based, scenario-generation decision support tool for allocating retired and developed parcels over the next 20 years. Because USGS staff worked closely with TRPA staff and their “Code of Ordinances” and analyzed datasets of historical management and land-use practices, this report accomplishes the task of providing reasonable default values for a baseline scenario that can be used in the LUSM. One result from the baseline scenario for the model suggests that all vacant parcels could be allocated within 12 years. Results also include: assessment of model functionality, brief descriptions of the 7 basic output tables, assessment of the rate of change in land-use allocation pools over time, locations and amounts of the spatially explicit probabilities of land-use transitions by real estate commodity, and analysis of the state change from today’s existing land cover to potential land uses in the future. Assumptions and limitations of the model are presented. This report concludes with suggested next steps to support the continued utility of the LUSM and additional research avenues.

Development of a prototype land use model for statewide transportation planning activities : summary.

DOT National Transportation Integrated Search

2011-01-01

Developing computer models of land use and : integrated transportation-land use are high : priorities for Florida transportation planners. : Land use information is fundamental to siting : roadways, signaling, setting maintenance : priorities, routin...

High-resolution Continental Scale Land Surface Model incorporating Land-water Management in United States

NASA Astrophysics Data System (ADS)

Shin, S.; Pokhrel, Y. N.

2016-12-01

Land surface models have been used to assess water resources sustainability under changing Earth environment and increasing human water needs. Overwhelming observational records indicate that human activities have ubiquitous and pertinent effects on the hydrologic cycle; however, they have been crudely represented in large scale land surface models. In this study, we enhance an integrated continental-scale land hydrology model named Leaf-Hydro-Flood to better represent land-water management. The model is implemented at high resolution (5km grids) over the continental US. Surface water and groundwater are withdrawn based on actual practices. Newly added irrigation, water diversion, and dam operation schemes allow better simulations of stream flows, evapotranspiration, and infiltration. Results of various hydrologic fluxes and stores from two sets of simulation (one with and the other without human activities) are compared over a range of river basin and aquifer scales. The improved simulations of land hydrology have potential to build consistent modeling framework for human-water-climate interactions.

An econometric analysis of changes in arable land utilization using multinomial logit model in Pinggu district, Beijing, China.

PubMed

Xu, Yueqing; McNamara, Paul; Wu, Yanfang; Dong, Yue

2013-10-15

Arable land in China has been decreasing as a result of rapid population growth and economic development as well as urban expansion, especially in developed regions around cities where quality farmland quickly disappears. This paper analyzed changes in arable land utilization during 1993-2008 in the Pinggu district, Beijing, China, developed a multinomial logit (MNL) model to determine spatial driving factors influencing arable land-use change, and simulated arable land transition probabilities. Land-use maps, as well as social-economic and geographical data were used in the study. The results indicated that arable land decreased significantly between 1993 and 2008. Lost arable land shifted into orchard, forestland, settlement, and transportation land. Significant differences existed for arable land transitions among different landform areas. Slope, elevation, population density, urbanization rate, distance to settlements, and distance to roadways were strong drivers influencing arable land transition to other uses. The MNL model was proved effective for predicting transition probabilities in land use from arable land to other land-use types, thus can be used for scenario analysis to develop land-use policies and land-management measures in this metropolitan area. Copyright © 2013 Elsevier Ltd. All rights reserved.

Alaska Interim Land Cover Mapping Program; final report

USGS Publications Warehouse

Fitzpatrick-Lins, Katherine; Doughty, E.F.; Shasby, Mark; Benjamin, Susan

1989-01-01

In 1985, the U.S. Geological Survey initiated a research project to develop an interim land cover data base for Alaska as an alternative to the nationwide Land Use and Land Cover Mapping Program. The Alaska Interim Land Cover Mapping Program was subsequently created to develop methods for producing a series of land cover maps that utilized the existing Landsat digital land cover classifications produced by and for the major land management agencies for mapping the vegetation of Alaska. The program was successful in producing digital land cover classifications and statistical summaries using a common statewide classification and in reformatting these data to produce l:250,000-scale quadrangle-based maps directly from the Scitex laser plotter. A Federal and State agency review of these products found considerable user support for the maps. Presently the Geological Survey is committed to digital processing of six to eight quadrangles each year.

47 CFR 32.2111 - Land.

Code of Federal Regulations, 2010 CFR

2010-10-01

... FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) COMMON CARRIER SERVICES UNIFORM SYSTEM OF ACCOUNTS FOR... of more than one year used for purposes other than the location of outside plant (see Accounts 2411..., Nonoperating Plant. (e) When land is acquired in excess of that required for telecommunications purposes, the...

47 CFR 32.2111 - Land.

Code of Federal Regulations, 2011 CFR

2011-10-01

... FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) COMMON CARRIER SERVICES UNIFORM SYSTEM OF ACCOUNTS FOR... of more than one year used for purposes other than the location of outside plant (see Accounts 2411..., Nonoperating Plant. (e) When land is acquired in excess of that required for telecommunications purposes, the...

7 CFR 1450.6 - Access to land.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 10 2014-01-01 2014-01-01 false Access to land. 1450.6 Section 1450.6 Agriculture Regulations of the Department of Agriculture (Continued) COMMODITY CREDIT CORPORATION, DEPARTMENT OF AGRICULTURE LOANS, PURCHASES, AND OTHER OPERATIONS BIOMASS CROP ASSISTANCE PROGRAM (BCAP) Common Provisions...

7 CFR 1450.6 - Access to land.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 10 2011-01-01 2011-01-01 false Access to land. 1450.6 Section 1450.6 Agriculture Regulations of the Department of Agriculture (Continued) COMMODITY CREDIT CORPORATION, DEPARTMENT OF AGRICULTURE LOANS, PURCHASES, AND OTHER OPERATIONS BIOMASS CROP ASSISTANCE PROGRAM (BCAP) Common Provisions...

7 CFR 1450.6 - Access to land.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 10 2013-01-01 2013-01-01 false Access to land. 1450.6 Section 1450.6 Agriculture Regulations of the Department of Agriculture (Continued) COMMODITY CREDIT CORPORATION, DEPARTMENT OF AGRICULTURE LOANS, PURCHASES, AND OTHER OPERATIONS BIOMASS CROP ASSISTANCE PROGRAM (BCAP) Common Provisions...

7 CFR 1450.6 - Access to land.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 10 2012-01-01 2012-01-01 false Access to land. 1450.6 Section 1450.6 Agriculture Regulations of the Department of Agriculture (Continued) COMMODITY CREDIT CORPORATION, DEPARTMENT OF AGRICULTURE LOANS, PURCHASES, AND OTHER OPERATIONS BIOMASS CROP ASSISTANCE PROGRAM (BCAP) Common Provisions...

Alternative Zoning Scenarios for Regional Sustainable Land Use Controls in China: A Knowledge-Based Multiobjective Optimisation Model

PubMed Central

Xia, Yin; Liu, Dianfeng; Liu, Yaolin; He, Jianhua; Hong, Xiaofeng

2014-01-01

Alternative land use zoning scenarios provide guidance for sustainable land use controls. This study focused on an ecologically vulnerable catchment on the Loess Plateau in China, proposed a novel land use zoning model, and generated alternative zoning solutions to satisfy the various requirements of land use stakeholders and managers. This model combined multiple zoning objectives, i.e., maximum zoning suitability, maximum planning compatibility and maximum spatial compactness, with land use constraints by using goal programming technique, and employed a modified simulated annealing algorithm to search for the optimal zoning solutions. The land use zoning knowledge was incorporated into the initialisation operator and neighbourhood selection strategy of the simulated annealing algorithm to improve its efficiency. The case study indicates that the model is both effective and robust. Five optimal zoning scenarios of the study area were helpful for satisfying the requirements of land use controls in loess hilly regions, e.g., land use intensification, agricultural protection and environmental conservation. PMID:25170679

A digital spatial predictive model of land-use change using economic and environmental inputs and a statistical tree classification approach: Thailand, 1970s--1990s

NASA Astrophysics Data System (ADS)

Felkner, John Sames

The scale and extent of global land use change is massive, and has potentially powerful effects on the global climate and global atmospheric composition (Turner & Meyer, 1994). Because of this tremendous change and impact, there is an urgent need for quantitative, empirical models of land use change, especially predictive models with an ability to capture the trajectories of change (Agarwal, Green, Grove, Evans, & Schweik, 2000; Lambin et al., 1999). For this research, a spatial statistical predictive model of land use change was created and run in two provinces of Thailand. The model utilized an extensive spatial database, and used a classification tree approach for explanatory model creation and future land use (Breiman, Friedman, Olshen, & Stone, 1984). Eight input variables were used, and the trees were run on a dependent variable of land use change measured from 1979 to 1989 using classified satellite imagery. The derived tree models were used to create probability of change surfaces, and these were then used to create predicted land cover maps for 1999. These predicted 1999 maps were compared with actual 1999 landcover derived from 1999 Landsat 7 imagery. The primary research hypothesis was that an explanatory model using both economic and environmental input variables would better predict future land use change than would either a model using only economic variables or a model using only environmental. Thus, the eight input variables included four economic and four environmental variables. The results indicated a very slight superiority of the full models to predict future agricultural change and future deforestation, but a slight superiority of the economic models to predict future built change. However, the margins of superiority were too small to be statistically significant. The resulting tree structures were used, however, to derive a series of principles or "rules" governing land use change in both provinces. The model was able to predict future land use, given a series of assumptions, with 90 percent overall accuracies. The model can be used in other developing or developed country locations for future land use prediction, determination of future threatened areas, or to derive "rules" or principles driving land use change.

Revitalization of the Shared Commons: Education for Sustainability and Marginalized Cultures

ERIC Educational Resources Information Center

Glasson, George E.

2010-01-01

Education for sustainability provides a vision for revitalizing the environmental commons while preserving cultural traditions and human rights. What happens if the environmental commons is shared by two politically disparate and conflicting cultures? As in many shared common lands, what happens if one culture is dominant and represents a more…

Integrated assessment of future land use in Brazil under increasing demand for bioenergy

NASA Astrophysics Data System (ADS)

Verstegen, Judith; van der Hilst, Floor; Karssenberg, Derek; Faaij, André

2014-05-01

Environmental impacts of a future increase in demand for bioenergy depend on the magnitude, location and pattern of the direct and indirect land use change of energy cropland expansion. Here we aim at 1) projecting the spatiotemporal pattern of sugar cane expansion and the effect on other land uses in Brazil towards 2030, and 2) assessing the uncertainty herein. For the spatio-temporal projection, four model components are used: 1) an initial land use map that shows the initial amount and location of sugar cane and all other relevant land use classes in the system, 2) an economic model to project the quantity of change of all land uses, 3) a spatially explicit land use model that determines the location of change of all land uses, and 4) various analysis to determine the impacts of these changes on water, socio-economics, and biodiversity. All four model components are sources of uncertainty, which is quantified by defining error models for all components and their inputs and propagating these errors through the chain of components. No recent accurate land use map is available for Brazil, so municipal census data and the global land cover map GlobCover are combined to create the initial land use map. The census data are disaggregated stochastically using GlobCover as a probability surface, to obtain a stochastic land use raster map for 2006. Since bioenergy is a global market, the quantity of change in sugar cane in Brazil depends on dynamics in both Brazil itself and other parts of the world. Therefore, a computable general equilibrium (CGE) model, MAGNET, is run to produce a time series of the relative change of all land uses given an increased future demand for bioenergy. A sensitivity analysis finds the upper and lower boundaries hereof, to define this component's error model. An initial selection of drivers of location for each land use class is extracted from literature. Using a Bayesian data assimilation technique and census data from 2007 to 2012 as observational data, the model is identified, meaning that the final selection and optimal relative importance of the drivers of location are determined. The data assimilation technique takes into account uncertainty in the observational data and yields a stochastic representation of the identified model. Using all stochastic inputs, this land use change model is run to find at which locations the future land use changes occur and to quantify the associated uncertainty. The results indicate that in the initial land use map especially the shape of sugar cane and other land use patches are uncertain, not so much the location. From the economic model we can derive that dynamics in the livestock sector play a major role in the land use development of Brazil, the effect of this uncertainty on the model output is large. If the intensity of the livestock sector is not increased future projections show a large loss of natural vegetation. Impacts on water are not that large, except when irrigation is applied on the expanded cropland.

Integration of environmental simulation models with satellite remote sensing and geographic information systems technologies: case studies

USGS Publications Warehouse

Steyaert, Louis T.; Loveland, Thomas R.; Brown, Jesslyn F.; Reed, Bradley C.

1993-01-01

Environmental modelers are testing and evaluating a prototype land cover characteristics database for the conterminous United States developed by the EROS Data Center of the U.S. Geological Survey and the University of Nebraska Center for Advanced Land Management Information Technologies. This database was developed from multi temporal, 1-kilometer advanced very high resolution radiometer (AVHRR) data for 1990 and various ancillary data sets such as elevation, ecological regions, and selected climatic normals. Several case studies using this database were analyzed to illustrate the integration of satellite remote sensing and geographic information systems technologies with land-atmosphere interactions models at a variety of spatial and temporal scales. The case studies are representative of contemporary environmental simulation modeling at local to regional levels in global change research, land and water resource management, and environmental simulation modeling at local to regional levels in global change research, land and water resource management and environmental risk assessment. The case studies feature land surface parameterizations for atmospheric mesoscale and global climate models; biogenic-hydrocarbons emissions models; distributed parameter watershed and other hydrological models; and various ecological models such as ecosystem, dynamics, biogeochemical cycles, ecotone variability, and equilibrium vegetation models. The case studies demonstrate the important of multi temporal AVHRR data to develop to develop and maintain a flexible, near-realtime land cover characteristics database. Moreover, such a flexible database is needed to derive various vegetation classification schemes, to aggregate data for nested models, to develop remote sensing algorithms, and to provide data on dynamic landscape characteristics. The case studies illustrate how such a database supports research on spatial heterogeneity, land use, sensitivity analysis, and scaling issues involving regional extrapolations and parameterizations of dynamic land processes within simulation models.

Impact of Land Model Calibration on Coupled Land-Atmosphere Prediction

NASA Technical Reports Server (NTRS)

Santanello, Joseph A., Jr.; Kumar, Sujay V.; Peters-Lidard, Christa D.; Harrison, Ken; Zhou, Shujia

2012-01-01

Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface heat and moisture budgets, as well as controlling feedbacks with clouds and precipitation that lead to the persistence of dry and wet regimes. Recent efforts to quantify the strength of L-A coupling in prediction models have produced diagnostics that integrate across both the land and PBL components of the system. In this study, we examine the impact of improved specification of land surface states, anomalies, and fluxes on coupled WRF forecasts during the summers of extreme dry and wet land surface conditions in the U.S. Southern Great Plains. The improved land initialization and surface flux parameterizations are obtained through calibration of the Noah land surface model using the new optimization and uncertainty estimation subsystem in NASA's Land Information System (LIS-OPT/UE). The impact of the calibration on the a) spinup of the land surface used as initial conditions, and b) the simulated heat and moisture states and fluxes of the coupled WRF simulations is then assessed. Changes in ambient weather and land-atmosphere coupling are evaluated along with measures of uncertainty propagation into the forecasts. In addition, the sensitivity of this approach to the period of calibration (dry, wet, average) is investigated. Results indicate that the offline calibration leads to systematic improvements in land-PBL fluxes and near-surface temperature and humidity, and in the process provide guidance on the questions of what, how, and when to calibrate land surface models for coupled model prediction.

VLUIS, a land use data product for Victoria, Australia, covering 2006 to 2013

PubMed Central

Morse-McNabb, Elizabeth; Sheffield, Kathryn; Clark, Rob; Lewis, Hayden; Robson, Susan; Cherry, Don; Williams, Steve

2015-01-01

Land Use Information is a key dataset required to enable an understanding of the changing nature of our landscapes and the associated influences on natural resources and regional communities. The Victorian Land Use Information System (VLUIS) data product has been created within the State Government of Victoria to support land use assessments. The project began in 2007 using stakeholder engagement to establish product requirements such as format, classification, frequency and spatial resolution. Its genesis is significantly different to traditional methods, incorporating data from a range of jurisdictions to develop land use information designed for regular on-going creation and consistency. Covering the entire landmass of Victoria, the dataset separately describes land tenure, land use and land cover. These variables are co-registered to a common spatial base (cadastral parcels) across the state for the period 2006 to 2013; biennially for land tenure and land use, and annually for land cover. Data is produced as a spatial GIS feature class. PMID:26602150

VLUIS, a land use data product for Victoria, Australia, covering 2006 to 2013.

PubMed

Morse-McNabb, Elizabeth; Sheffield, Kathryn; Clark, Rob; Lewis, Hayden; Robson, Susan; Cherry, Don; Williams, Steve

2015-11-24

Land Use Information is a key dataset required to enable an understanding of the changing nature of our landscapes and the associated influences on natural resources and regional communities. The Victorian Land Use Information System (VLUIS) data product has been created within the State Government of Victoria to support land use assessments. The project began in 2007 using stakeholder engagement to establish product requirements such as format, classification, frequency and spatial resolution. Its genesis is significantly different to traditional methods, incorporating data from a range of jurisdictions to develop land use information designed for regular on-going creation and consistency. Covering the entire landmass of Victoria, the dataset separately describes land tenure, land use and land cover. These variables are co-registered to a common spatial base (cadastral parcels) across the state for the period 2006 to 2013; biennially for land tenure and land use, and annually for land cover. Data is produced as a spatial GIS feature class.

Population Density Modeling for Diverse Land Use Classes: Creating a National Dasymetric Worker Population Model

NASA Astrophysics Data System (ADS)

Trombley, N.; Weber, E.; Moehl, J.

2017-12-01

Many studies invoke dasymetric mapping to make more accurate depictions of population distribution by spatially restricting populations to inhabited/inhabitable portions of observational units (e.g., census blocks) and/or by varying population density among different land classes. LandScan USA uses this approach by restricting particular population components (such as residents or workers) to building area detected from remotely sensed imagery, but also goes a step further by classifying each cell of building area in accordance with ancillary land use information from national parcel data (CoreLogic, Inc.'s ParcelPoint database). Modeling population density according to land use is critical. For instance, office buildings would have a higher density of workers than warehouses even though the latter would likely have more cells of detection. This paper presents a modeling approach by which different land uses are assigned different densities to more accurately distribute populations within them. For parts of the country where the parcel data is insufficient, an alternate methodology is developed that uses National Land Cover Database (NLCD) data to define the land use type of building detection. Furthermore, LiDAR data is incorporated for many of the largest cities across the US, allowing the independent variables to be updated from two-dimensional building detection area to total building floor space. In the end, four different regression models are created to explain the effect of different land uses on worker distribution: A two-dimensional model using land use types from the parcel data A three-dimensional model using land use types from the parcel data A two-dimensional model using land use types from the NLCD data, and A three-dimensional model using land use types from the NLCD data. By and large, the resultant coefficients followed intuition, but importantly allow the relationships between different land uses to be quantified. For instance, in the model using two-dimensional building area, commercial building area had a density 2.5 times greater than public building area and 4 times greater than industrial building area. These coefficients can be applied to define the ratios at which population is distributed to building cells. Finally, possible avenues for refining the methodology are presented.

A hierarchical community occurrence model for North Carolina stream fish

USGS Publications Warehouse

Midway, S.R.; Wagner, Tyler; Tracy, B.H.

2016-01-01

The southeastern USA is home to one of the richest—and most imperiled and threatened—freshwater fish assemblages in North America. For many of these rare and threatened species, conservation efforts are often limited by a lack of data. Drawing on a unique and extensive data set spanning over 20 years, we modeled occurrence probabilities of 126 stream fish species sampled throughout North Carolina, many of which occur more broadly in the southeastern USA. Specifically, we developed species-specific occurrence probabilities from hierarchical Bayesian multispecies models that were based on common land use and land cover covariates. We also used index of biotic integrity tolerance classifications as a second level in the model hierarchy; we identify this level as informative for our work, but it is flexible for future model applications. Based on the partial-pooling property of the models, we were able to generate occurrence probabilities for many imperiled and data-poor species in addition to highlighting a considerable amount of occurrence heterogeneity that supports species-specific investigations whenever possible. Our results provide critical species-level information on many threatened and imperiled species as well as information that may assist with re-evaluation of existing management strategies, such as the use of surrogate species. Finally, we highlight the use of a relatively simple hierarchical model that can easily be generalized for similar situations in which conventional models fail to provide reliable estimates for data-poor groups.

Simultaneous Assimilation of AMSR-E Brightness Temperature and MODIS LST to Improve Soil Moisture with Dual Ensemble Kalman Smoother

NASA Astrophysics Data System (ADS)

Huang, Chunlin; Chen, Weijin; Wang, Weizhen; Gu, Juan

2017-04-01

Uncertainties in model parameters can easily cause systematic differences between model states and observations from ground or satellites, which significantly affect the accuracy of soil moisture estimation in data assimilation systems. In this paper, a novel soil moisture assimilation scheme is developed to simultaneously assimilate AMSR-E brightness temperature (TB) and MODIS Land Surface Temperature (LST), which can correct model bias by simultaneously updating model states and parameters with dual ensemble Kalman filter (DEnKS). The Common Land Model (CoLM) and a Q-h Radiative Transfer Model (RTM) are adopted as model operator and observation operator, respectively. The assimilation experiment is conducted in Naqu, Tibet Plateau, from May 31 to September 27, 2011. Compared with in-situ measurements, the accuracy of soil moisture estimation is tremendously improved in terms of a variety of scales. The updated soil temperature by assimilating MODIS LST as input of RTM can reduce the differences between the simulated and observed brightness temperatures to a certain degree, which helps to improve the estimation of soil moisture and model parameters. The updated parameters show large discrepancy with the default ones and the former effectively reduces the states bias of CoLM. Results demonstrate the potential of assimilating both microwave TB and MODIS LST to improve the estimation of soil moisture and related parameters. Furthermore, this study also indicates that the developed scheme is an effective soil moisture downscaling approach for coarse-scale microwave TB.

Using plot experiments to test the validity of mass balance models employed to estimate soil redistribution rates from 137Cs and 210Pb(ex) measurements.

PubMed

Porto, Paolo; Walling, Des E

2012-10-01

Information on rates of soil loss from agricultural land is a key requirement for assessing both on-site soil degradation and potential off-site sediment problems. Many models and prediction procedures have been developed to estimate rates of soil loss and soil redistribution as a function of the local topography, hydrometeorology, soil type and land management, but empirical data remain essential for validating and calibrating such models and prediction procedures. Direct measurements using erosion plots are, however, costly and the results obtained relate to a small enclosed area, which may not be representative of the wider landscape. In recent years, the use of fallout radionuclides and more particularly caesium-137 ((137)Cs) and excess lead-210 ((210)Pb(ex)) has been shown to provide a very effective means of documenting rates of soil loss and soil and sediment redistribution in the landscape. Several of the assumptions associated with the theoretical conversion models used with such measurements remain essentially unvalidated. This contribution describes the results of a measurement programme involving five experimental plots located in southern Italy, aimed at validating several of the basic assumptions commonly associated with the use of mass balance models for estimating rates of soil redistribution on cultivated land from (137)Cs and (210)Pb(ex) measurements. Overall, the results confirm the general validity of these assumptions and the importance of taking account of the fate of fresh fallout. However, further work is required to validate the conversion models employed in using fallout radionuclide measurements to document soil redistribution in the landscape and this could usefully direct attention to different environments and to the validation of the final estimates of soil redistribution rate as well as the assumptions of the models employed. Copyright © 2012 Elsevier Ltd. All rights reserved.

Landing characteristics in waves of three dynamic models of flying boats

NASA Technical Reports Server (NTRS)

Benson, James M; Havens, Robert F; Woodward, David R

1952-01-01

Powered models of three different flying boats were landed in oncoming waves of various heights and lengths. The effects of varying the trim at landing, the deceleration after landing, and the size of the waves were determined. Data are presented on the motions and accelerations obtained during landings in rough water.